ASSESSMENT OF UPLAND EROSION PROCESSES …soilandwater.bee.cornell.edu/Research/international/docs/Bound... · erosion and control practices and to identify factors affecting farmers’

ASSESSMENT OF UPLAND EROSION PROCESSES AND FARMER’S

PERCEPTION OF LAND CONSERVATION IN DEBRE-MEWI WATERSHED,

NEAR LAKE TANA, ETHIOPIA

A Thesis Presented to the Faculty of Graduate School

of Cornell University

in Partial Fulfillment of the Requirements for the Degree of

Masters of Professional Studies

By

Assefa Derebe Zegeye

May 2009

© 2009 Assefa Derebe Zegeye

ABSTRACT

Soil erosion is affecting global food security. Though it is a natural process, its

rate has increased significantly during the last century mainly by human activity. In

developing countries in order to combat erosion, many soil and water conservation

practices have been proposed but only a few, if any, are implemented by farmers on a

long-term basis. Therefore, this study sets out to evaluate upland erosion and evaluate

the effectiveness of practices used by farmers and the farmers’ perception about

erosion and control practices and to identify factors affecting farmers’ land

conservation decision-making processes. The watershed chosen was Debre-Mewi

located south of Bahir Dar, 30 km from Lake Tana. In this study, the paper presents

and discusses the results of the 15 surveyed agricultural fields and personal interview

of 80 households conducted in the Debre Mewi watershed. To quantify the amount of

soil loss due to rill erosion in the watershed, each rill’s dimensions were carefully

measured to determine its volume and hence to obtain average magnitudes and rates of

soil erosion for the fields. The result showed that the average soil loss in the surveyed

fields was 36t/ha provided that the contribution of inter-rill erosion assumed to be 25%

of the actual soil loss (taken from different literatures). Sediment measured from the

control plot of AARC experimental station located within surveyed fields was

estimated as 38.3 t/ha whereas using USLE model predicted 39 t/ha. Thus, all three

methods gave similar results. The knowledge and perceptions of the farmers about

erosion problems and mitigation measures, their reasons for not carrying out periodic

maintenance and construction of new conservation measures and conservations

practices that are widely used by the farmers are also discussed in this paper.

BIOGRAPHICAL SKETCH

Assefa Derebe was born in 1975 in the Amhara Regional State, Achefer

District, Ethiopia. He is married and has two children (a daughter and a newborn

boy). He was a teacher of mathematics and director of secondary schools for at least

10 years. He was also the chief administrator of Achefer Woreda before he joined the

Cornell Masters program conducted at Bahir Dar University.

He received his Diploma in Mathematics at Gonder Teacher’s College in 1997

and BSc at Bahir Dar University in 2003.

He has deep-rooted interest to study erosion modeling, soil and water

conservation, soil physics and hydrology.

In the name of GOD.

This work is dedicated for Haimanot Amare (my wife), Dessalegn Yizengaw (my dear

friend) and Meklit Assefa (3 yrs) (my daughter), who were the main initiator to join

this program and to complete this work with your patience, love, support and prayer.

Therefore, I dedicate this work for you with love.

vi

ACKNOWLEDGEMENTS

Above all, always and forever I thank my God for helping me throughout my

life and especially during my studies. Then, my thanks directly extends to Cornell

University for granting me financial support during the course time and finalizing this

study. I would like to thank the Bahir Dar University also who prepared this joint

program with collaboration to Cornell University that enabled me to get this chance.

My special thanks go to professors (Tammo S. Steenhuis, Stephen D. DeGloria,

Dwight Bowman, Robert W. Blake, Angela Neilan, Charles F. Nicholson, Dawit

Solomon and Amy S Collick) at Cornell University who gave me all the intended

courses with their gorgeous methodologies. I learned many teaching techniques from

them that I should practice it through out my life.

I would like to express my deepest gratitude to Professor Tammo S. Steenhuis,

for his supervision, valuable guidance, intellectual encouragement and critical and

constructive comments. I want to express my maximum respect to him. My

appreciation extends to Professor Blake, animal scientist at Cornell University, He has

taught me many things and has given a great deal of constructive feedback, valuable

and very critical comments on the structure and organization of this thesis. I am also

deeply indebted to Dr. Selamyihun Kidanu, his comments, advice and supports during

proposal writing and selection of research theme, modification of questionnaire, in

general his guidance how to start and finish the study were great to me. His

intellectual encourages and help are unforgettable. A special word of thank goes also

to Dr. Amy S Collick, Coordinator of this joint program. I do appreciate her

comments, editing and organizing this thesis. She gave us very helpful trainings

regarding to thesis writing and her valuable experiences.

The fieldwork for this research was carried out in Adet Woreda, Ethiopia. I

would like to acknowledge the support of Adet Agricultural Research Center (AARC).

vii

Especially I appreciate Ato Tadele Amare who never got tired of supporting me by

providing different resources and relevant data collected from the study site with his

valuable advices. Dr. Farzad Dadgari, SWHISA worker, has also a special place in this

study for his support during the proposal writing and supervising the fieldwork. His

comments were very constructive.

I am grateful to all (2007-2009) CU-BDU students for their encouragements

during the thesis writing. I have had an enjoyable time with you during the entire

study program.

Finally yet importantly, I have appreciated the endeavor and courage of my

wife Haimanot Amare, and my dear friend Dessalegn Yizengaw (Canada) and all my

family, especially my mother-in-law, Alem Gobezie, her support cannot be expressed

in words. Without her support, I would have hardly finished the entire program. I am

extremely happy to have a family like you.

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TABLE OF CONTENTS

BIOGRAPHICAL SKETCH .....................................................................................IV

ACKNOWLEDGEMENTS .......................................................................................VI

TABLE OF CONTENTS ....................................................................................... VIII

LIST OF FIGURE ....................................................................................................... X

LIST OF TABLES .................................................................................................... XII

ABBREVIATIONS .................................................................................................. XIV

1 INTRODUCTION ................................................................................................ 1

2 STUDY AREA ...................................................................................................... 8

2.1 Description of the study sites ........................................................................... 8

2.2 Climate ............................................................................................................. 10

2.3 Soil .................................................................................................................... 11

2.4 Farming system ............................................................................................... 12

3 METHODOLOGY ............................................................................................. 13

3.1 Erosion measurement and prediction ........................................................... 13 3.1.1 Measurement of rill erosion ........................................................................... 13 3.1.2 Prediction of soil loss .................................................................................... 15

3.2 Infiltration, Bulk density and Water holding capacity ............................... 16

3.3 Farmers’ perceptions of SWC measures ...................................................... 17

3.4 Methods of data analysis ................................................................................ 19 3.4.1 Rill erosion .................................................................................................... 19 3.4.2 Social Survey Analysis .................................................................................. 21

4 RESULTS AND DISCUSSION ......................................................................... 22

4.1 Physical properties of soil in the sampled fields .......................................... 22

ix

4.1.1 Bulk density ................................................................................................... 22 4.1.2 Moisture Content (MC) ................................................................................... 23 4.1.3 Infiltration ...................................................................................................... 23

4.2 Rill erosion ...................................................................................................... 24 4.2.1 Soil loss due to rill erosion under different situations ................................... 24 4.2.2 Classification of rills ...................................................................................... 26 4.2.3 Nature of rill erosion in crop types ............................................................... 28 4.2.4 The nature of rill erosion in different slope positions ................................... 33 4.2.5 Estimation of soil loss using USLE ............................................................... 34

4.3 Effects of different physical factors on soil erosion and processes ............ 38 4.3.1 Effects of rainfall to soil erosion ................................................................... 38 4.3.2 Effects of run-on to soil erosion .................................................................... 40 4.3.3 Effects of crop cover to soil erosion .............................................................. 41 4.3.4 Effects of soil texture on erosion processes .................................................. 44

5 FARMERS’ PERCEPTION OF LAND CONSERVATION ......................... 46

5.1 Household and farm characteristics ............................................................. 46

5.2 Perceptions of erosion as a problem ............................................................. 50

5.3 Causes of Soil erosion, Soil fertility and Productivity decline .................... 51

5.4 Farmers’ conservation practices in the watershed ...................................... 53

5.5 Farmers’ perception, acceptance and adoption of SWC measures ........... 56

5.6 Factors Affecting Adoption of the Introduced SWC Technologies ........... 58

6 RECOMMENDATIONS ................................................................................... 60

7 CONCLUSIONS ................................................................................................. 62

8 REFERENCES ................................................................................................... 64

APPENDIX A: TABLES ........................................................................................... 71

APPENDIX B: QUESTIONNAIRE ......................................................................... 87

x

LIST OF FIGURE

Figure 1: Location of the area of Debre Mewi watershed, Ethiopia .............................. 8

Figure 2: Location of surveyed fields and villages where respondents were selected ... 9

Figure 3: Partial view of Debre Mewi watershed (photo by Assefa D. July 2008) ..... 10

Figure 4: Mean monthly rainfall, humidy and mean monthly temperature for the Adet

weather station for the years 1996-2005, seven km from the Debre Mewi

watershed .............................................................................................................. 11

Figure 5: A single plot divided in to five transects to show how to measure rills ....... 14

Figure 6: Photographs of rill dimension measurements: depth on the right and width

on the left (photo by Assefa D. 2008) .................................................................. 15

Figure 7: Infiltration rate (IR mm/hr) of two locations at down slope (DS) and mid

slope fields ............................................................................................................ 24

Figure 8: Photograph to show on-site effects of erosion features (rills and sheet) in one

of surveyed fields in Debre Mewi watershed, Ethiopia. ...................................... 28

Figure 9: Photographs of the severity of erosion damage with onsite effect (A) and

offsite effect (B) of erosion (photographs taken during the survey, 2008), Debre

Mewi watershed, Ethiopia .................................................................................... 28

Figure 10: Stuffing activity of tef fields by animals, Debre Mewi watershed, Ethiopia

.............................................................................................................................. 30

Figure 11: Photograph to show rill erosion feature in tef fields, Debre Mewi, Ethiopia

.............................................................................................................................. 30

Figure 12: Erosion rate in tons /ha over the growing season as a function of slope

position; where DS is down slope, MS is middle slope and US is upper slope.

AAD is area actual damaged due to rill formation in m2/ha. ............................... 34

Figure 13: Average soil loss for the 15 upland agricultural fields in the Debre-Mewi

watershed, the light shaded columns is the cumulative soil loss for the season.

xi

The black boxes are the soil losses for the individual storms; the line with

diamonds is the cumulative rainfall. ..................................................................... 39

Figure 14: Graph of crop cover versus soil loss rate .................................................... 42

Figure 15: Photograph of active gully formation in the Debre Mewi watershed,

Ethiopia ................................................................................................................. 50

Figure 16: Side effects of cultural ditches, the left side is improperly designed and the

right side indicates the overflowing of concentrated runoff . ............................... 55

xii

LIST OF TABLES

Table 1: Soil physical characteristics in the surveyed fields taken in the rainy season.

.............................................................................................................................. 23

Table 2: Classification of rills and their contribution in soil loss ................................. 25

Table 3: General descriptions of rill erosion magnitudes in the Debre Mewi watershed

measured in two months of July and August ........................................................ 27

Table 4: Rill magnitudes in different crop types .......................................................... 31

Table 5: Multiple comparisons (LSD, ANOVA) to show significant differences of

variables among crop cover types (T is crop type, AAD is area of actual ........... 32

Table 6: Multiple comparisons (LSD, ANOVA) to show significant difference

between each slope positions ................................................................................ 36

Table 7: Rill magnitudes in three different slope positions. Different letters (a,b,c)

along the column indicate that they are significantly different, whereas the same

letters indicate not significantly different within each slope position .................. 36

Table 8: Comparison between measured and predicted soil loss in Debre Mewi

watershed (see appendix A Table A3 how each parameters were estimated) ....... 37

Table 9: Contribution of run-on on rill formation and soil loss ................................... 41

Table 10: Relationship between soil loss and crop cover (cc). .................................... 43

Table 11: Laboratory analysis result of the plough layer soil property at six

representative locations in Debre Mewi watershed by AARC in 2008. ............... 44

Table 12: Characteristics of total households and their livestock in the four villages of

the watershed (HH stands for household) ............................................................ 47

Table 13: The percentage of respondents who owned livestock and farm size ........... 48

Table 14: Perception of respondents for soil erosion as a problem .............................. 51

Table 15: Farmers’ response to the causes of soil erosion, fertility and productivity

decline ................................................................................................................... 52

xiii

Table 16: Farmers’ conservation practices in the Debre Mewi watershed, Ethiopia ... 54

Table 17: Indicators of acceptance and adoption of SWC technologies ...................... 57

Table 18: Farmers’ reasons for not adopting the newly introduced SWC measures .. 58

xiv

ABBREVIATIONS

AAD Area of Actual Damage

AARC Adet Agricultural Research Center

BD Bulk Density

CC Crop Cover

DA Developmental Agent

DS Downslope

HH Household

IR Infiltration Rate

masl meter above sea level

MoA Ministry of Agriculture

MC Moisture content

MS Midslope

RF Rainfall

SCRP Soil Conservation Research Program

SWC Soil and Water Conservation

SWHISA Sustainable Water-Harvesting and Institutional Strengthening in

Amhara

US Up Slope

1

CHAPTER ONE

1 INTRODUCTION

Soil erosion is recognized as one of the world's most serious environmental

problems (Pimentel et al., 1995, Shiferaw and Holden, 1999). Globally, about 80% of

the current degradation of agricultural land is caused by soil erosion (Angima et al.,

2003). Erosion by water, at a global scale, is the main soil degradation process in

agricultural areas (Bewket and Sterk 2002). It generates strong environmental impacts

and major economic losses from decreased agricultural production and from off-site

effects on infrastructure and water quality by sedimentation processes (Zinabu et al.,

2002; Daba, 2003; Haregeweyn et al., 2005; Amsalu et al., 2007). Morgan (1996),

summarized the maximum annual rates of soil erosion in cultivated fields ranging from

200t/ha in China, to 30t/ha in Belgium.

Soil erosion creates severe limitations to sustainable agricultural land use, as it

reduces on-farm soil productivity and causes food insecurity (Tadesse, 2001;

Sonneveld, 2002; Beshah, 2003, Moges and Holden, 2006, Bewket, 2007). In most

developing countries, including Ethiopia, human activity triggers these losses

(Mohammad et al., 2001, Belyaev et al., 2004, Bewket and Sterk, 2005, Hurni et al.,

2005). This is associated with rapid population growth, inadequate attention to the

basic natural resources (soils, water and vegetation), and the need to maximize

production to meet the needs of the growing population (Shiferaw and Holden, 1999,

2000, Bewket, 2002, Feoli et al., 2002). This situation is more serious in poor

developing countries like Ethiopia (Feoli et al., 2002), where subsistence production

predominates. The Ethiopian farmer, who on average cultivates one hectare of food

crops and keeps some livestock, is nowadays dependent on natural conditions and

cannot tolerate further deterioration of soil productivity (Sonneveld and Keyzer, 2003).

Increasing population, intense land cultivation, uncontrolled grazing, and deforestation

2

often lead to, or exacerbate, soil erosion (Tadesse, 2001 and Bewket, 2002). These

factors undermine agricultural productivity and frustrate economic development

efforts, especially in developing countries where there is heavy land dependence

(Shiferaw and Holden, 2000) in low external-input farming systems (e.g., the

Ethiopian highlands).

Ethiopia has a total surface area of 112 million hectares (Bobe, 2004 and

Makombe, 2007) of which 60 million hectares is estimated to be agriculturally

productive. Out of the estimated agriculturally productive lands, about 27 million

hectares are significantly eroded, 14 million hectares are seriously eroded and 2

million hectares have reached the point of no return, with an estimated total loss of 2

billion m3 of top soil per year (Bewket and Sterk 2002, Bobe, 2004). Estimation of soil

erosion in Ethiopian highlands, according to Jaggar and Pender (2003), 2 million

hectares of lands have been severely degraded and hence annually, Ethiopia loses over

1.5 billion tons of topsoil from these highlands by erosion (Tadesse, 2001).

Particularly, in the highlands of Ethiopia, the degradation of agricultural land creates a

serious threat to current and potential food production (Azene, 2001; Sonneveld and

Keyzer, 2003, Bewket and Sterk, 2002). With fertile soils and good rainfall, these

highlands (>1500 masl)) hold the highest agricultural potential in the country (Hurni,

1993; Shiferaw and Holden, 2001).

Soil erosion from unsustainable land use practices in Ethiopia is not a new

phenomenon. It is as old as the history of agriculture itself (Daba et al., 2003).

However, it is only very recently, in the past three decades that the Ethiopian

government recognized the impact of soil erosion after the devastating famine in 1970s

(Shiferaw and Holden, 1998, 1999, Bewket and Sterk, 2002). To address this problem,

considerable efforts have been made since that time to rehabilitate degraded

environments and stop further degradation by the government (Herweg, 1993;

3

Yeraswork, 2000, Amsalu and Graaff, 2004, Bewket, 2006). By this action, huge areas

were covered with terraces, and millions of trees were planted (Yeraswork, 2000;

Tadesse, 2001).

Water action during soil erosion comprise the following processes: (1) splash

erosion, which occurs when soil particles are detached and transported as a result of

the impact of falling raindrops; (2) sheet or inter-rill erosion, which removes soil in

thin layers and is caused by the combined effects of splash erosion and surface runoff;

(3) rill erosion, which is the transport or detachment of soil particles caused by

concentrations of flowing water; and (4) gully erosion, which occurs when flow

concentration increases and the incision becomes deeper and wider than rills

(Mwendera & Mohamed Saleem, 1997; Mwendera et al., 1997; Morgan, 2005; Mitiku

et al., 2006).

Visible erosion features, such as rills, gullies and concentrated accumulations,

are features that often indicate hot spots, those parts of an area that are seriously

affected by soil erosion (Mitiku et al., 2006). Rills are very shallow channels that are

formed by the concentration of surface runoff along depressions or low points in

sloping lands. Rill erosion is the very visible mechanism of soil loss from sloping,

cultivated land Soil erosion that occurs in areas between rills by the action of raindrops

(causing splash erosion) and surface runoff (causing sheet erosion) is called inter-rill

erosion. Compared to sheet erosion, rill has an entirely different characteristic. It

removes a considerable amount of topsoil greater than sheet/inter-rill erosion (Nyssen

et al., 2004). Through rills, eroded particles are transported quickly over a large

distance. Large particles are more effectively transported. Rills differ from gullies in

that they are temporary features and can be easily destroyed during plowing, whereas

gullies are more permanent features in the landscape. Rills and gullies constitute an

“embryonic” drainage system (Mitiku et al., 2006), which, if unchecked, will develop

4

eventually in to badlands. This may involve irreversibility of the land to put it back

into crop production in agricultural systems that are based on animal-drawn

implements for cultivating the land (Mitiku et al., 2006).

Rill erosion is a result of surface runoff and associated sheet wash, which is a

process that selectively removes fine material and organic matter that are very

important determinants of land productivity (Bewket and Sterk, 2003). The shearing

power of the water can detach, pick up and remove soil particles making these

channels the preferred routes for sediment transport. Hence, rill erosion is probably the

most important form of soil loss in cultivated fields because in the absence of these

channels, which serve the purpose of transporting detached materials, inter-rill erosion

will be negligible (Bewket and Sterk, 2003).

The evaluation of soil erosion was undertaken through measurement of rill

erosion features (Bewket and Sterk, 2003, Belyaev et al., 2004, Casalí et al., 2006).

This method is used to estimate the amount of material removed from the field by

concentrated runoff. As suggested by Bewket and Sterk (2003), for practical

conservation planning purposes rill survey is a key. Most quantitative research on soil

erosion has dealt with soil loss rates due to rill and inter-rill erosion, mostly from

runoff plots; and the magnitude of soil erosion and its effect has been extrapolated

based on plot level and catchment level to larger spatial scales (Bewket and Sterk,

2003, Nyssen et al, 2004, Belyaev et al., 2004). These methods have their own

drawbacks when the results are extrapolated and conclusions are made about the wider

landscape (Brazier, 2004).

Plot studies measure only the movement of soil over a relatively small area,

which is not entirely related to the real-life situation where deposition takes place

further down the slope. This is likely to lead to an overestimation of on-site soil loss

from small plots (Mwendera et al., 1997, Brazier, 2004). Moreover, plots are often

5

sited where erosion is known to occur (Brazier, 2004). The physical constraints of plot

boundaries are also a potential problem. Most plot sites fail to recreate the conditions

found within the field, as boundaries eliminate any flow paths in and out of the plot

and interrupt the movement of sediment by splash along the plot margins (Wainwright

et al., 2000, Brazier, 2004).

Catchment-level studies measure the actual loss of soil from the land and take

into account the deposition of sediment on the land surface. However, there are also

problems associated with catchment-level data; the calculation of erosion rates from

recordings of river sediment loads requires the specification of a sediment delivery

ratio, the value of which is unknown for most catchments (Brazier, 2004).

Furthermore, measuring sediment at the outlet of the watershed does not indicate from

which land use in the watershed such amount of sediment came from. It reflects an

aggregate output across the whole area and cannot provide details of re-deposition or

redistribution within the watershed. This limitation is further discussed by Bewket and

Sterk (2003), who argued that as erosion does not occur in a uniform fashion across

the whole plot, it shows extreme spatial variation with variations in rainfall energy,

gradient and length of slopes, inherent soil characteristics affecting its erodibility and

land use and land management practices. Therefore, this method may mislead one to

consider soil loss in terms of mass per unit area to plan appropriate SWC measures.

On the other hand, field surveys of rills have an integral role to play in the sustainable

management of agricultural lands in particular. Without involving expensive

instrumentation and sophisticated modeling of soil loss, this strategy may yield more

economical (and efficient) solutions in local areas than the application of the existing

generation of erosion models (Herweg, 1996; Bewket and Sterk, 2003). It must also be

treated as a means in itself to aid soil conservation (Herweg 1996) and to inform

6

catchment managers and decision/policy makers. Hence, assessment of soil loss by

surveying rill erosion plays a great role for soil and water conservation planning.

Effective control of soil erosion is a critical component of natural resource

management when the aim is to achieve sustainable agriculture and acceptable

ecosystem integrity (Pimentel et al. 1995; Tamene et al, 2006). Farmers’ perception of

land degradation by erosion is a key social factor that is also important in deciding

options for controlling soil losses (Graaff, 1993). Some authors who studied in

different parts of Ethiopian highlands reported that farmers are more likely to adopt

conservation measures in plots that are highly prone to soil erosion, such as plots

where slopes are steep and erosion features are visible (Shiferaw and Holden, 1998;

Bekele and Drake 2003; Gebremedhin and Swinton 2003). Amsalu and Graaff (2006)

concluded that under the current conditions in the Ethiopian central highlands, soil and

water conservation interventions should consider farmers’ conservation knowledge

and practices to improve the possibility of acceptance and adoption of the

recommendations. Farmers rather frequently reject newly introduced SWC

technologies even when they are aware that the measure protect and improves

productivity of their lands.

Based on the literature cited above, it is obvious that the newly introduced

SWC technologies need to be evaluated not only for their technical efficacy but also

for the probability of their sustainable adoption and utilization by the land users. The

latter requires identification of barriers to and facilitators of adoption of the

technologies. Once the barriers and facilitators are identified, recommendations can be

made on appropriate steps that need to be taken to enhance the adoption of the

technologies and to effect sustainable land use (Amsalu and Graaff, 2006).

Understanding farmers’ knowledge and their perception and factors that influence their

land management practices are of paramount importance for promoting sustainable

7

land management. During the qualitative phase of this study, we attempted to

understand farmers’ knowledge and perception on soil erosion processes, soil fertility,

acceptance and adoption of the newly introduced soil and water conservation (SWC)

measures and other relevant data used for the study.

The overall goal of this research is to determine the severity of soil erosion and

to identify factors affecting the decision making process of farmers in their land

conservation practices. The specific objectives are (1) to document the severity and

rate of soil loss due to rill erosion; (2) to identify the high-risk erosion areas in the

watershed (hot spots) using pictures; (3) to understand the farmers’ perception and

awareness of erosion processes and SWC measures as a land management practice; (4)

to examine the local farmers’ acceptance and adoption of land conservation

technologies; and (5) to identify factors affecting their land conservation decisions.

The study was carried out in the Debre Mewi watershed south of Bahir Dar.

The research involved a rill survey methodology on different slope positions and crop

types. Semi-structured questionnaire and some soil samples were also used. Finally,

soil loss obtained from rill measurements was compared with USLE model and

sediment collected from the control plot of the Adet Agricultural Research Center

(AARC) experimental station in the study site.

8

CHAPTER TWO

2 STUDY AREA

2.1 Description of the study sites

This paper is based on a survey conducted during the months of July to

October 2008 in the Debre Mewi watershed located between 11o20’13’’ and

11o21’58’’ N and 37o24’07’’ and 37o25’55’’ E which is situated within two kebele

administrations, Debre Mewi (Yilmana Densa Woreda) and Fereswoga (Bahirdar

Zuria Woreda). The watershed is located about 500 km north of Addis Ababa, capital

of Ethiopia, and 30 km south of Lake Tana at Bahir Dar Town, the capital of Amhara

Regional State in the northern Ethiopian highlands (Figure 1). The elevation ranges

between 1950 and 2309 m.a.s.l. Thus, the area experiences semi-humid climate. The

slope gradient of the watershed ranges from 8 to 30%.

Figure 1: Location of the area of Debre Mewi watershed, Ethiopia

The total area of the watershed is estimated to be 523 ha (nearly 5km2). There

are four villages identified within the watershed named, Quyo, Mariam-wuha, Shanko-

bahir and Feres-woga (Figure 2). The total number of households living in these

villages is estimated to be 276 of which 35 (13%) are women-headed households. It is

also estimated that about 1092 people are living in the watershed. Most farmers whose

9

farmlands are found in the watershed are living near the edge and outside of the

watershed. Several farmers also have farmlands outside the watershed.

Figure 2: Location of surveyed fields and villages where respondents were selected

The watershed is sensitive to erosion. Vegetation cover is poor (see Figure 3),

and rills and gullies are prominent features, threatening the existence of the

communities, reducing the arable area, cutting roads and making access difficult. As a

result, the area is considered as one of the degraded areas in Ethiopia. To reduce soil

loss, farmers had installed drainage furrows (locally called feses) slightly off the

contour. The few conservation efforts like stone and soil bunds that were installed

with the help of outsiders were not maintained. Most of these structures (stone and soil

bunds) are damaged, reducing their effectiveness and even allowing concentrated flow

that enhances the development of rills and gullies downstream.

10

Figure 3: Partial view of Debre Mewi watershed (photo by Assefa D. July 2008)

2.2 Climate

Based on 10 years (1996-2005, see appendix A Table A4-9) of metrological

data for the Adet station (7 km from the site), the climatic can be characterized as

follows: maximum annual temperatures occur in either March or April and ranges

from 22 to 29.4oC whereas; minimum annual temperature occur in either November or

December with a range of 5.4 to 12.1oC over the 10 years. The average annual rainfall

is 1238 mm with a maximum of 1695 mm in 1996 and a minimum of 956 mm in 2002.

Since the watershed lies at a higher elevation than Adet, temperatures are often slightly

lower while rainfall is likely greater. The rainfall follows a unimodal annual

distribution with more than 72% of the annual rainfall during the four months from

June to September (locally called kiremt). It is in this season that the major agricultural

activities, such as plowing, sowing and weeding are performed. The dry months are

between November and March (known as bega) when less than 6% of the total annual

rainfall occurs. The kiremt season (June – September) is more dependable for farming

activities.

According to the method of calculation made by the manual of watershed

management of Ministry of Agriculture in Ethiopia (2001), the annual potential

Sampled fields

11

evapotranspiration (PET) ranges from 110 to 125 mm. The length of growing period

(LGP) which is defined as the continuous period of the year when rainfall exceeds half

the potential evapotranspiration (PET) plus the period required evaporating an

assumed 100 mm of stored soil water (MoA, 2001) ranges from 120 to 180 days and

hence it is classified as a moist zone. The wind speed ranges from 0.68m/s in

November to 1.14 m/s in May. According to Bahir Dar station 30 km from the site, the

mean sun shines duration range from 4.4 hours in July and August to 10.0 hours in

February.

The relationship between mean annual rainfall, mean annual temperature and

mean annual humidity is illustrated in Figure 4.

Figure 4: Mean monthly rainfall, humidy and mean monthly temperature for the Adet weather station for the years 1996-2005, seven km from the Debre Mewi watershed

2.3 Soil

The dominant soil types in the watershed include vertic nitosols (locally known

as silehana) located at the major mid-slope positions. It is reddish-brown and popular

especially for tef crop production. Nitosols (locally, dewel) located in the upper part of

the watershed. This is a very deep, well-drained red clay loam soil. This is considered

12

as the most productive soil type in the watershed. The other major soil type is vertisols

(locally, walka), which covers the major lower slope positions of the watershed. This

soil class can be characterized by heavy clay black color and are mostly water logged

during the rainy season (Mohammad et al., 2001, Mintesinot, et al 2004).

2.4 Farming system

Agriculture in Debre Mewi watershed is rain-fed, with a subsistence mixing

farming system. Land and livestock are therefore the most important livelihood assets.

Tef (Eragrostis tef), finger millet, maize (Zea mays) and Wheat (Triticum vulgare) are

the major crops cultivated during the rainy season.

In the Debre Mewi watershed, livestock is kept for various reasons, such as a

means of transportation, sources of milk and meat, traction (plowing and land

preparation), and skins. Cows, oxen, sheep, goats and donkeys are the major livestock

in the area. Small ruminants like sheep and goats are kept for income generation. Oxen

are used for plowing while donkeys transport agricultural and non-agricultural

products.

13

CHAPTER THREE

3 METHODOLOGY

Rate of erosion was determined by measuring the dimension of the rills in time

and calculating from that the soil removed from the rills. The measured soil erosion

rates were compared to those predicted with the USLE. In addition, to understand

farmers’ perception of soil erosion processes and land conservation technologies,

personal interviews and group discussions were undertaken. The methods are

discussed in detail in the following sections.

3.1 Erosion measurement and prediction

For determining, the erosion by the rill measurements, 15 representative fields

were selected from the 523 ha land of the whole Debre Mewi watershed. The total area

of the 15 fields was 3.56 ha (almost 1% of the watershed area). These fields were

classified into three slope positions: upslope, mid-slope and down-slope fields. They

were defined according to their positions from the up-slope edge of the watershed (Fig.

2). The total distance from the edge to the river was 450 m, the up-slope plots were

within the first 100 m from the edge and had a slope of 9%, the mid-slope plots were

located from 100 to 250 m with a slope of 10%. Finally, the bottom plots were in

remainder concave part of the watershed with an average slope 13% (Appendix A,

TableA1). In the down slope position, all the six fields were covered by tef crop and in

the up slope position, both fields were sown with finger millet, whereas in the mid

slope position, four fields were covered with tef and the rest three fields were maize,

finger millet and wheat crops. Therefore, the rate of soil loss between different crop

types was compared only in the mid slope fields.

3.1.1 Measurement of rill erosion

. A series of transects across the slope with an average distance of 10m between

two transects was established; positioned one above another (Figure 5) to minimize

14

rill measurement errors and marked using sticks and stones (Hudson, 1993). Cultural

ditches (locally called feses) constructed in the field for conservation mechanisms

were also used as transects so that measurements of rills found between two

consecutive ditches were undertaken.

Figure 5: A single plot divided in to five transects to show how to measure rills

During the months of July and August when the greatest rainfall amounts

causing significant soil loss were recorded, each field was repeatedly visited

immediately after rainfall storms had occurred. Rill measurements were not taken until

rills were clearly noticed. At the initial measurement of rills, fields intended for tef

were not sown yet. For other fields intended for maize, wheat and millet,

measurements were carried out after sowing.

Though the channel size and shape of rills had a great influence on

measurement accuracy (Casalí et al., 2006), the length, width and depth of the rills

were carefully measured along two successive transects. The length of a rill was

measured from its starting point up to the place where the eroded soil was deposited.

The width and depth of rill was measured as shown in Figure 6. Widths were

measured at several points along a rill (Figure 6) to give a better approximation of a

mean width because the width varied along the rill (Herweg, 1996). Since the depths

Rills due to runon

Rills within field

Sticks or stones

One transect

15

of most rills were homogenous, the number of depth measurement points was not as

numerous as the width measurement points. From these measurements, different

magnitudes of rill erosion, such as rill volumes, rates of erosion, density of rills, area

of actual damage by the rills and the percentage of area covered by the rills to the total

area of surveyed fields, were determined (Herweg, 1996, Hagmann, 1996, Bewket and

Sterk, 2003).

Figure 6: Photographs of rill dimension measurements: depth on the right and width on the left (photo by Assefa D. 2008)

Metrological data of 10 years (1996-2005) was collected from the Adet

Metrological station (7 km from the study site) in order to describe the climatic

conditions of the study area. Daily rainfall data were obtained from this station before

the Adet Agricultural Research Center (AARC) installed a rain gauge in the watershed

at the end of July 2008 (see Appendix A Table A4-9). Starting from August 1, the

onsite rain gauge was used to measure daily rainfall amounts, which were used to

examine the relationship between the temporal distribution of rainfall amount, eroded

soil volume and rate due to rills (Mitiku et al., 2006, Bewket, and Sterk, 2003).

3.1.2 Prediction of soil loss

Finally, parameters including average annual rainfall, slope length, slope

gradient, soil color, land cover and management practices were collected in all the

surveyed fields and estimated according to Hurni (1985b) adapted for Ethiopian

conditions cited in the guide of watershed management by Ministry of Agriculture

(MoA) (2001) in order to test the universal soil loss equation (USLE). The USLE is as

follows:

E = R * K * L * S * C* P ….............................. Equation 1

where E is the mean annual soil loss, R is a rainfall erosivity index, K is a soil

erodibliity index, L is the slope length, S represents slope steepness, C is a crop factor,

16

P is a conservation practice factor. Hence, the amount of soil loss was estimated by

this equation and compared with the measured soil loss. The sediment collected from

the control plot of AARC research station was also used to compare with the surveyed

result.

3.2 Infiltration, Bulk density and Water holding capacity

Two infiltration tests on the mid-slope and down slope fields were conducted

in October using double-ring infiltrometer with diameters of 53cm and 30cm for the

larger and smaller rings respectively (Gregory et al., 2005). The ring was driven into

the ground an average of 15 cm on all locations. Both the outer and inner rings were

filled with water (100 mm depth), and the rate at which the water moves into the soil

was measured and this activity took for an hour until the rate became constant. A

graduated plastic ruler was used to read water depth differences in the inner ring. The

major constraint was shortage of water to replicate the measurements and therefore

only two tests were carried out. The other limitation was that siphon was not used for

further minimizing errors.

For the soil BD and MC assessment, soil samples were collected in the three

typical slope positions from fifteen fields in three locations within each field using a

core-sampler. The three locations in each of fifteen fields were selected to represent

the surveyed fields. Forty-five soil samples were collected from the topsoil of all

surveyed fields to estimate the bulk density (BD) and moisture content (MC) of the

soil. For confirmation of the initial measurements of MC, soil samples were collected

again at each of the three-slope positions one month after the first sample was taken.

Soil samples were brought back to the soil laboratory for air-dried and

examined for their physical properties like BD, MC. To estimate the value of bulk

density and moisture content of the soil, each core sampler before it was filled by soil

and after filled soil were carefully measured before entered to the oven to dry. The

17

dried soil was calculated by subtracting the mass of moisture and core-sampler having

volume 98.1 cm3 to get the bulk density of each sample. The MC was calculated by

subtracting the dried soil from moist soil measured before entered to the oven and

expressed as percentage.

3.3 Farmers’ perceptions of SWC measures

In order to capture the perception of soil erosion process and factors affecting

farmers’ land conservation decision-making processes and related reasons, a formal

and informal interview were conducted. In addition, the researcher periodically visited

the entire research area and the wider farming system so that he was able to learn

several things by observation. Issues that immerged from observation were used to

guide interviews and discussions with selected farmers. Closer observations were

made in selected fields where measurements were carried out.

Data and information about perceptions of farmers in soil erosion processes

and SWC technologies were collected using formal interviews with the sampled

households. To obtain information about the same fact from multiple methods and to

increase validity and reliability of data, focus group discussions (composed of elders,

male and female farmers and community leaders) and informal interviews with

developmental agents and Woreda agricultural experts were carried out.

The formal interview was conducted with 80 households (owning 95 ha crop

lands of which some plots are out of the watershed) selected in the four villages of the

Debre Mewi watershed (Quyo, Shanko-Bahir, Mariam-Wuha and Feres-Woga) as

indicated in figure 2 above. The sampled households (HHs) were randomly selected

from a list of total HHs collected from the representatives of each village. Every fourth

HH on the list contained all 276 HHs of the watershed was included in the sample

group before personal interview was conducted in August. However, using this

technique, only 69 HHs were selected. The rest 11 HHs were added by considering

18

those who possessed fields treated with soil and water conservation technologies and

those who had untreated fields. When the selected household was unavailable after

repeated visits or specifically stated their unwillingness, the next household on the list

was interviewed. Eight households, most of them from Fereswega village, were

substituted for this study. A few farmers in this village felt land insecure and not

willing to participate. They believed incorrectly that the objective of the interviews

was a trick to sell their land. Their belief was based on the experience of farmers in a

community in the neighboring kebele, 10 km towards Bahir Dar town, where land was

sold to investors for flower production

Most interviews were undertaken by going to each interviewee’s homestead

and some times in Debre Mewi small town when they came for marketing activities.

Since this interview used to obtain farmers’ knowledge and attitude of erosion

processes and the decisive factors that influence the adoption of the newly introduced

conservation measures, special care was given while interviewing farmers to get

enough information for the intended study.

Since the field work for this study was conducted during the rainy season (July

to September of 2008), the farmers were occupied with the preparation of the land,

sowing crops and weeding. Therefore, farmers did not have time to sit down and

participate in a formal interview in these working days. However, since all the

inhabitants in the watershed have only one type of religion (Orthodox), the only

options the researcher used was the holydays to undertake most of the interviews. In

these holydays (at least 12 days in a month), the regulation and rule of their religion

forbids working any agricultural practices. Violating the law makes out of any social

activities. Therefore, these days were convenient to undertake the formal interview.

The questionnaire was comprised of open and closed-ended questions. The final

questionnaire was modified conducted after pre-testing. The questionnaire included

19

issues of household and farm characteristics, perceptions of erosion problems and

noticeable changes in soil fertility and productivity and some hydrological parameters

over time. Causes of soil erosion, currently implemented soil conservation measures

and farmers’ conservation knowledge were also covered in the survey instrument.

Moreover, indicators of acceptance and adoptions of the newly introduced SWC

measures, and major limitations to apply SWC measures were the most important parts

of the instrument. Information which is used for explaining the perception of the soil

erosion problem, the adoption of conservation measures, household demographic and

some socioeconomic characteristics which were relevant for the study were collected

mostly using open ended questions.

The respondents were encouraged in order to express their perceptions,

feelings, knowledge and all ideas they had about the planned study. Though some

attempts were made to crosscheck responses of the farmers, like landholding sizes and

number of livestock owned from records of the DA and local agricultural office, the

researcher could not find any recent document regarding to such points.

3.4 Methods of data analysis

3.4.1 Rill erosion

In each field, maximum development of rills, both in number and dimensions,

was attained during August 1, 2008 (see appendix A, Table A2 how to calculate rill

magnitudes). After this time, the rill dimensions did not show significant change

though there was still soil loss as long as there is rainfall. Therefore, the maximum

value was analyzed in this paper to estimate the total soil loss due to rills. The eroded

soil volumes, rill densities, areas of actual damage and other quantities were calculated

from the measured rill dimensions: length, width and depth (Herweg, 1996). The soil

volume was calculated using the following formula.

..……………………….Equation 2 ( )A

NDWLX iiii

10000∑=

20

where X is the volume of rills in m3/ha, L is the length (m) of the rills, W is the width

(cm) of the rills, D is the depth (cm) of rills, A is the area of each field in ha, N is the

number of rills, i is the number of homogeneous dimensions. The calculated volume is

equivalent to the volume of soil lost from the formation of the rills. The total volume

of soil loss was obtained simply by summing the volumes of all homogenous rill

segments as shown in Equation 2. The eroded soil volume was also expressed in terms

of weight of eroded soil by multiplying the calculated volume by the measured bulk

density of the soils at each of the 15 fields in the site (Hagmann, 1996). The total soil

loss was converted into per unit hectare of land to express the annual rate of soil loss.

The area of actual damage per unit hectare was obtained from the product of length

and width dimensions of each homogenous rill segment by using Equation 3. The rill

density was calculated by dividing the total rill lengths, obtained by summing up the

length measurements of all the rills, by the total area of the surveyed fields (Equation

4).

..………………………Equation 3

.…………………………….. Equation 4

where AAD is the area of actual damage by rills in m2/ha, L is the length (m) of the

rills, W is the width (cm) of the rills, D is the density (m/ha) of rills, A is the area of

each field in ha, N is the number of rills, i is the number of homogeneous dimensions.

The rill densities were also converted into per unit hectare of land. The soil loss due to

cultural ditches themselves was estimated by calculating the changes of their widths

and depths by Equation 2. The relationships between soil loss rate, rainfall and crop

coverage were analyzed. The number of rills originating from upper fields and rills

( )A

NWLAAD iii

100∑=

( )A

NLD ii∑=

21

initiated within the field and their contributions to soil loss were identified in the

study. The spatial variation of rill erosion was analyzed by assessing the distribution of

the rate of soil erosion, rill density and areas of actual damage across the surveyed

fields in reference to their relative topographic positions (i.e. upslope, mid-slope and

down-slope), crop type and type classification. The difference of rill magnitudes

between each slope positions and crop cover types were analyzed statistically using

SPSS software. The sediment measured from control plot of experimental plots

monitored by AARC was used to compare the soil loss rate with the result of measured

soil loss using rill survey. Finally, the soil loss in the surveyed fields was estimated by

using universal soil loss equation (USLE) adapted for Ethiopian conditions by Hurni

(1985b).

3.4.2 Social Survey Analysis

The data generated by the structured questionnaires was analyzed using excel

and the frequencies and descriptive procedures of the statistical Package for Social

Science (SPSS) software, version 12. The data were thoroughly checked by the

researcher before the analysis by directly comparing all 80 cases with the original

questionnaire. The relevant qualitative information generated by the informal

discussions with farmers and other concerned bodies were integrated with the

quantitative data for better understanding of the issues covered in the study.

22

CHAPTER FOUR

4 RESULTS AND DISCUSSION

4.1 Physical properties of soil in the sampled fields

4.1.1 Bulk density

Soil bulk density is defined as the ratio of a mass of dry soil (oven-dried at

105oC) of its field volume and usually expressed in terms of grams per cubic

centimeter (g/cm3). Bulk density is determined by the texture of the soil and by soil

structure and the amount of soil pore space, which can be changed by management.

Compaction increases bulk density by reducing soil pore space. It is an increase in

bulk density and soil strength and a decrease in soil porosity by the application of

mechanical forces to the soil. The action of tillage implements and similar physical

forces crush soil aggregates and push soil particles closer together, especially under

wet soil conditions. Compacted soils or soil layers restrict root growth, water

movement, and air exchange.

The BD of soils under up slope fields was at about 6% higher than mid-slope

field soils and 8% higher than soils in the down slope fields. This means the BD

decreases down a slope positions However, it was not significantly different

statistically among the three slope positions (P-value = 0.09 within groups) (Table 1).

However, as we will see in section 4.2.5 by multiple comparison of ANOVA both

down and mid-slope fields showed were significantly different at (P < 0.01) (see

appendix A, Table12, for detail information).

23

Table 1: Soil physical characteristics in the surveyed fields taken in the rainy season.

Different letters (a,b,c) along the column indicate that they are significantly different, whereas the same letters indicate not significantly different within each slope position. Detailed information is attached in the appendix A, Table A11

4.1.2 Moisture Content (MC)

MC is the amount of water in a soil during the time of data collection. Soil

texture, structure, porosity, and organic-matter content determine soil moisture.

Though there was no significant difference at 0.05 levels, the moisture content of soil

in the down slope fields was 6% higher than soils in the mid-slope fields and 15%

higher than soils in the up-slope fields (Table 1). This result has an implication to the

erosion processes that will be discussed in the next section.

4.1.3 Infiltration

Infiltration is the process by which water arriving at the soil surface enters the

soil. This process affects surface runoff, soil erosion, and groundwater recharge

(Hanson, 2004, Bewket and Sterk, 2005). The measurement was carried out in October

2008 when the average MC of the soil was decreased by half (13 to 19%) from the

first measurement in the rainy season (32 to 38%).

Since there were no replicates during measurements of infiltration, it was

difficult to analyze the significances statistically. However, water drained better in the

upper fields than the down slope fields. At the initial point, the down slope fields

showed higher infiltration rate (varies between 300 and 7.5 mm/hr) than upper fields

(varies between 240 and 15 mm/hr). Hence, after one hour monitoring, the level of

water at down slope and mid-slope fields decreased by 54mm and 47mm respectively.

Topography Moisture content (%)

Bulk density (g/cm3)

Infiltration (mm/hr)

Down slope 37a 1.18a 7.5a Mid-slope 36a 1.21a 15a Upslope 32a 1.28b =

24

However, during the last 20 minutes, the rate in the down slope fields constantly

showed half the rate of the upper fields (Figure 7). This situation had implication for

the erosion mechanisms. As described in section 4.2.5 there was a greater soil loss

from the fields at lower elevations than higher up the slope fields. The reason may be

that the lower fields were either at saturation or close to saturation before the rainstorm

occurred while the upper fields better drained.

Figure 7: Infiltration rate (IR mm/hr) of two locations at down slope (DS) and mid slope fields

4.2 Rill erosion

4.2.1 Soil loss due to rill erosion under different situations

In general, the soil loss and number of rills increases for all crops with slope

position The upslope loss from rills is 8 t/ha, mid-slope 23t/ha and down slope 35t /ha.

The corresponding rill intensities are 1029, 2860 and 4946 m/ha. In the down-slope

field the rills covered 884 m2/ha or almost 9% of the area (Table 2). The average rill

densities from total rill length of 3549m in 2.53ha of tef fields before sowing (July

25

11,2008) was 1403m/ha and after sowing (July12 to August 27, 2008) all crops

(3.56ha) was 2614 m/ha from total rill length of 9305m. Therefore, the average rill

density before and after sowing crops from the total rill length of 12,854m was

3,611m/ha (Table 2 and (Table 3). In general, tef fields had the greatest soil loss

followed by maize and wehet and millet. As we will see later, the field preparation

affected these results.

Table 2: Classification of rills and their contribution in soil loss

Types of rills

No of rills Soil loss (t/ha) AAD (m2/ha) Rill density (m/ha)

US MS DS US MS DS US MS DS US MS DS Small 103 376 865 7 12 24 107 334 610 686 2299 4424Medium 2 74 94 1 9 11 69 271 274 21 543 522 Large 3 11 363 115 Total 105 453 959 8 23 35 176 662 885 708 2860 4946

Note: the widths of Small rills (<25cm), medium (25 to 200cm), Large (>200cm)

The rill erosion measurement does not consider soil loss from the land between

the rills (i.e., inter-rill erosion) and thus underestimate the actual erosion. According to

Zachar (1982), rill erosion underestimates 10 to 30 % of the actual soil loss. Govers

(1991) also reported, as the contribution of inter-rill erosion can be more than 30 % of

the total soil loss in fields where rills are present. Bewket and Sterk (2003) also

assumed 30% of the actual soil loss to calculate the contribution of inter-rill erosion to

soil loss. For this study, therefore, we assumed that the measured rill erosion rates

underestimated soil loss by 25%, making the annual average actual soil loss rates

around 36t/ha. If it were 30%, it would be around 38t/ha.

26

4.2.2 Classification of rills

By using the method of classification of rills of Herweg (1996), rills in the

study area were classified according to their widths in to three categories: Small (<25

cm), medium (25-200 cm), and large wide rills (>200 cm) (Table 3).

The depth of the rills in most cases did not vary much from field to field in the

surveyed fields (appendix A, Table A2). Therefore, to classify the rills we looked at

the widths. We found that 88.5% of the total rills were classified as small and 11% fell

in the medium classes. The large rills were the least in number (0.5% of the total). The

rills classified as large width were observed in one tef field in the medium slope

position. This field has no cultural ditches. However, it had damaged stone bunds that

could not control the high runoff from uplands. In other fields, the many cultural

ditches inside the field installed by the farmers might have prevented the formation of

the large and wide rills. Small rills contributed the largest amount (63.5% of the total)

of soil loss (Table 3) whereas the damage caused by large rills was minor, with a soil

loss of 3 percent and a damaged area of 3.4 percent (Table 3). This result contradicts

the result obtained by Bewket and Sterk (2003) and Hagman (1996) in which few large

rills contributed the highest amount of soil loss in their study. Indeed, their studies did

not indicate clearly if there were cultural ditches in their study sites.

One attempt at one tef field was made to measure the damage caused by

siltation of eroded materials in the mid-slope position at the field boundary (Figure 8).

The field had a 10% slope and flat (3% slope) at the lower part where siltation

occurred.

27

Table 3: General descriptions of rill erosion magnitudes in the Debre Mewi watershed measured in two months of July and August

Types of rills

Crop type

No of rills Soil loss (t/ha) AAD (m2/ha) Rill Density (m/ha) US MS DS Total US MS DS T US MS DS Total US MS DS Mean

Small

Maize 46 46 11 11 299 299 2209 2209 Wheat 13 13 4.5 4.5 106 106 705 705 Millet 103 21 124 7 4.5 6 156 51 123 997 695 903 TAS 272 538 810 6.5 18 17 415 422 419 2755 2835 2807 Sum 1 103 352 538 993 7 11 18 14 156 311 422 344 997 2146 2835 2330 TBS 24 327 351 2 5 4 39 188 136 258 1590 1126 Total 1 103 376 865 1344 7 12 24 17 156 334 610 441 997 2299 4424 3130

Medium

Maize 2 2 3 3 74 74 109 109 Wheat 1 1 3 3 63 63 126 126 Millet 2 5 7 1 3 1.4 100 189 128 31 168 74 TAS 36 60 96 9 8 9 212 199 204 442 304 352 Sum 2 2 44 60 106 1 5 8 7 100 169 199 175 31 315 304 276 TBS 30 34 64 7 3 4 173 76 109 385 218 276 Total 2 2 74 94 170 1 9 11 9 100 271 274 252 31 543 522 473

Wide* Sum 3 3 3 11 11 363 363 115 115 Total sum 105 453 959 1517 8 23 35 27 256 662 884 717 1029 2860 4946 3611

TBS = tef before sowing, TAS = tef after sowing, DS = down slope, MS = mid-slope US = upslope, AAD = area of actual damage, all values are rounded to whole numbers. * indicates that the rate was calculated by the area of that single field where the three large wide rills were developed.

28

Figure 8: Photograph to show on-site effects of erosion features (rills and sheet) in one of surveyed fields in Debre Mewi watershed, Ethiopia.

From the measurement of this silt, more than 60% of eroded soil was

accumulated at this field border. The crop in this area was totally damaged as shown

in the Figure 8. Hence, the owner of the field had to sow again the same seed after

erosion decreased a bit due to crop cover increment on the rest part of the field.

Figure 9B shows the fine materials and organic matter transported in the

runoff water, and the offsite effects caused by sedimentation process are depicted in

Figure 9B

A B Figure 9: Photographs of the severity of erosion damage with onsite effect (A) and offsite effect (B) of erosion (photographs taken during the survey, 2008), Debre Mewi watershed, Ethiopia

4.2.3 Nature of rill erosion in crop types

Tef is the dominant cereal crop in the watershed followed by maize, finger

millet and wheat. Local farmers sow tef from early July to early August, Finger millet

29

from late may to late June, maize from late April to mid June and wheat in June. This

timing has an implication on contribution of ground cover of the croplands in reducing

erosion. Tef and finger millet lands need five to seven times plowing, four times for

wheat and barely and three times for maize. Each sample observations are included in

appendix A Table A13.

The amount of soil eroded from the tef plots after land preparation and just

before sowing (July 11, 2008) was 8 t/ha (Table 4). An addition 26t/ha was lost after

sowing tef (between July 12 and August 27, 2008). Soil loss after that was negligible.

Thus the total soil loss for tef was 34 t/ha (Table 4). The soil loss in tef was three

times greater than for finger millet and wheat, and twice that in maize crops. The

ANOVA in Table 5 shows that the soil loss differences between crop covers was

significant. However, millet and wheat did not show significant differences. The area

actually damaged (AAD) by rills, only tef showed significant different with other crop

fields.

The main reason for the high erosion loss for tef is that the period of land

preparation for tef is during middle of the rainy season with high intensity rains, while

for the other crops tillage occurred earlier when rains were less intense. Another factor

that might be contributing was packing by animals’ feet (mostly by farm animals and

donkeys) just before sowing as shown in Figure 10. This activity is also common in

finger millet fields except, in this field, the activity is done twice just before and after

sowing.

30

Figure 10: Stuffing activity of tef fields by animals, Debre Mewi watershed, Ethiopia

Packing was performed because the farmers believed that unless it is

compacted, the crop would dry before the expected crop calendar (locally this

situation known as waag) without any yield. Moreover, as it was observed during the

survey, the root of tef crop was neither strong nor deep enough to protect the soil from

high surface runoff. All the above reasons confirmed that tef fields were very

susceptible for soil erosion process compared to other cover types as clearly shown in

Figure 11.

Figure 11: Photograph to show rill erosion feature in tef fields, Debre Mewi, Ethiopia

31

Table 4: Rill magnitudes in different crop types

CT= crop type, TAS = tef after sowing, TBS = tef before sowing, US = up slope, MS = mid-slope, DS = down slope Different letters along the column indicate significantly different, and the same letters indicate not significantly different

CT No of rills Soil loss (t/ha) AAD (m2/ha) Rill density (m/ha)

US MS DS Total US MS DS Total US MS DS Total US MS DS Mean

Maize 48 48 14.2 14a 372.9 373a 2317 2317a

Wheat 14 14 7.6 7.6b 168.9 169a 832 832b

Millet 105 26 131 8.1 7 7.7b 256 240.5 251a 1029 863 977b

TAS 311 598 909 23.5 26.6 26 723.9 620 656 3227 3138.2 3158

TBS 54 361 415 8.9 7.6 8 211.4 264 246 643.2 1807.9 1403

TAS+TBS 365 959 1324 32.4 34.2 34c 935.2 884 902b 3870 4946 4561.3 4561c

Total 105 453 959 1517 8.1 23.2 34.2 26.5 256 662.1 884 717 1029 2860 4946.1 3603

32

Table 5: Multiple comparisons (LSD, ANOVA) to show significant differences of variables among crop cover types (CT is crop type, AAD is area of actual damage, MD is mean difference, Sig. is significance (P), * indicates those values that are significant at 0.05 level

In finger millet cropland, at the beginning of rill survey the numerous very

shallow rills were observed. However, after monitoring of one month (up to the

middle of August) almost all rills had disappeared.

Erosion hardly exists in wheat field since the surface, before and after sowing,

was rough. This increases infiltration, which in turn decreases runoff that was

considered as the major source of rills and sheet erosions in the area. The growth of

Soil Erosion (t/ha) AAD (m2/ha)

(I) CT (J) CT MD (I-J) Sig. MD (I-J) Sig.

Maize Wheat 6.4* 0.00 51 0.13

Millet 6.8* 0.00 44 0.23

Tef -4.7* 0.02 -340* 0.00

Wheat Maize -6.4* 0.00 -51 0.13

Millet 0.4 0.84 -7 0.84

Tef -11* 0.00 -391* 0.00

Millet Maize -6.8* 0.00 -44 0.23

Wheat -0.4 0.84 7 0.84

Tef -11.5* 0.00 -384* 0.00

Tef Maize 4.7* 0.02 340* 0.00

Wheat 11* 0.00 391* 0.00

Millet 11* 0.00 384* 0.00

33

wheat was faster than the other crops and a cover was established before the roughness

became smooth due to high rainfall.

Soil loss rate in maize crop fields was grater than finger millet and wheat but

less than for tef. The leaves of maize only protect the soil late in the rainy season. The

farmer removes weeds, which grow faster and can protect the soil.

4.2.4 The nature of rill erosion in different slope positions

Rill erosion is the most visible mechanism of soil loss from sloping cultivated

land (Herweg 1996). The analysis from ANOVA in SPSS software indicated that the

soil loss, the area of actual damage and rill density are significantly different among

the three slope positions (P = 0.0008, P = 0.0001, P = 0.0004) (Table 6 and Table 7).

The rate of soil loss due to rills from the down slope fields was 1.5 times that of the

mid-slope fields and 3.3 times that of the upslope fields. Though all surveyed fields

were cultivated, comparison of soil loss in the same crop types at different field slope

position was mandatory. Hence, the rate of erosion in down-slope tef field was 12%

greater than mid-slope tef fields. In millet fields, the up-slope fields had 14 % more

erosion than the millet field in the mid-slope position. This is opposite the general

trend when soil loss is averaged over all crops.

The reason that millet had less erosion in mid slope might have been due to

soil bunds (even unmaintained). In addition, the slope gradient and slope length of this

field was a bit less than for the up slope millet fields.

The area of actual damage due to rills when averaged over all crops in the

down-slope fields was 1.3 times that of the mid-slope fields and 3.5 times that of from

the up-slope fields (Table 4). However, the opposite was true for tef mid and down-

slope fields (Table 4). The damaged area by rills in the mid-slope tef fields was 1.2

times that in the down-slope tef fields (Table 5). This was because that all large wide

rills developed by surface runoff coming from the upland fields were found in mid-

34

slope fields. In down slope fields, most of the rills were initiated within fields. Hence,

the widths of rills were smaller compared to the mid-slope tef fields.

Figure 12: Erosion rate in tons /ha over the growing season as a function of slope position; where DS is down slope, MS is middle slope and US is upper slope. AAD is area actual damaged due to rill formation in m2/ha.

The slope lengths in the down and mid-slope fields showed significant

difference with upslope fields’. Statistically (Table 6 and Table 7), no significant

difference of slope length and slope gradient was observed between down with mid-

slope fields and mid with upslope fields respectively. However, the slope in the down

slope fields was significantly greater than with the mid and upslope fields (Table 7).

4.2.5 Estimation of soil loss using USLE

Hurni (1985b) adapted the six parameters of USLE to Ethiopian situation. The

values are described in the manual of watershed management of MoA (2001) and

listed in the appendix A Table A14. According to this assumption, the annual soil loss

from the 15 surveyed fields was estimated as 39 t/ha (Table 8). The values of all

USLE factors of each field plots are indicated in appendix A Table A3. For example,

to determine the soil loss from a control plot of AARC experimental station in the

study site according to the manual stated above, the annual rainfall was 1165 mm (R =

35

647); the soil color to estimate erodiblity was red brown (K = 0.2); the slope length of

a plot was 30m (L = 1.3); The average slope gradient was 10% (S =1); The land cover

was tef (C = 0.25) and since it was control plot, only contour plowing was used as soil

conservation (P = 0.9). Therefore, the product of these values gave the amount of soil

loss rate in this single plot per year (i.e., 38 t/ha per annum).

The results estimated by the three methods (measured, USLE model and

experimental plot without conservation structure) above were similar; they showed

almost the same result. The correlation between measured and predicted data for the

15 surveyed fields was 72%. This value indicates that the equation USLE was best

approximation for soil loss due to rill and sheet erosion. Therefore, rill survey method

can be concluded as a central way to quantify soil loss at field level and to plan

effective and site dependent SWC measures. According to the method introduced by

Hurni (1993), the estimated soil loss rates from cultivated fields in the Debre Mewi

watershed was a bit lower compared to the average soil loss rates estimated for an

“average” cultivated fields of Ethiopia (42t/ha per annum).

Since USLE can be used to compute the total average annual soil loss from

sheet and rill erosion within a particular watershed, the soil loss from these erosion

features were calculated to compare with the measured soil loss (Table 8). The R2

value of measured and predicted soil loss was 0.5 (Appendix A, Figure A1). The

method under predicts the soil loss of the down slope fields that are saturated part of

the time.

36

Table 6: Multiple comparisons (LSD, ANOVA) to show significant difference between each slope positions

Table 7: Rill magnitudes in three different slope positions. Different letters (a,b,c) along the column indicate that they are significantly different, whereas the same letters indicate not significantly different within each slope position

Dependant variable

Soil loss(t/ha)

Moisture content

Bulk density

AAD Rill density Slope length

Slope gradient

(I) Slope

(J) Slope

MD (I-J)

Sig. MD (I-J)

Sig. MD (I-J)

Sig. MD (I-J)

Sig. MD (I-J)

Sig. MD (I-J)

Sig. MD (I-J)

Sig.

DS MS 5.9* 0.02 0.6 0.47 -0.03 0.12 280* 0.00 678* 0.01 2.1 0.78 3.6* 0.01 US 12.2* 0.00 2.8 0.05 -0.09* 0.00 726* 0.00 1378* 0.00 25* 0.04 5* 0.02MS DS -5.9* 0.02 -0.6 0.47 0.03 0.12 -281* 0.00 -678* 0.01 -2.1 0.78 -3.7* 0.01 US 6.2* 0.03 2.2 0.13 -0.06* 0.02 445* 0.00 699* 0.02 22.8 0.05 1.3 0.48US DS -12.2* 0.00 -2.8 0.05 0.09* 0.00 -726* 0.00 -1378* 0.00 -25* 0.04 -5* 0.02 MS -6.2* 0.03 -2.2 0.13 0.06* 0.02 -445* 0.00 -699* 0.02 -22.8 0.05 -1.3 0.48CT = crop type, AAD = area of actual damage, MD= mean difference, Sig. = significance, * = significant at 0.05 level

Slope Position

Soil erosion effects Erosion factors Soil loss

(t/ha) Area of actual damage

(m2/ha) Rill density

(m/ha) Length

(m) Slope (%)

Down slope 34a 884a 4946a 53a 14a Mid-slope 23b 662b 2860b 51a 10b Upslope 8c 256c 1029c 39b 9b

37

Table 8: Comparison between measured and predicted soil loss in Debre Mewi watershed (see appendix A Table A3 how each parameters were estimated)

Field number

Field size (ha)

SL due to rill (t/ha)

Estimated soil loss due to sheet (t/ha)

Total SL (rill +

sheet) (t/ha)

Predicted Soil loss

(t/ha) 1 0.27 32.3 11.5 43.8 34.4 2 0.34 61.7 22.0 83.7 73.4 3 0.41 29.9 10.7 40.6 66.4 4 0.24 23.1 8.2 31.3 69.0 5 0.16 26.2 9.4 35.6 57.1 6 0.24 26.6 9.5 36.0 29.9 7 0.23 14.7 5.2 19.9 23.9 8 0.24 28.8 10.3 39.1 45.3 9 0.25 27.1 9.7 36.8 39.2 10 0.19 7.6 2.7 10.3 18.2 11 0.24 44.8 16.0 60.7 39.6 12 0.15 17.2 6.1 23.4 27.2 13 0.19 6.9 2.5 9.3 19.0 14 0.25 10.6 3.8 14.4 25.8 15 0.17 5.6 2.0 7.6 16.8

Ave 3.56 26.6 9.5 36.1 39.0

The average soil loss of the study area (and especially in the downslope area)

was severe. As described above, soil loss due to rill and sheet/inter-rill erosion was

estimated as 36t/ha/yr, which is equivalent to 3.6 mm/yr, provided that 1t/ha was

equivalent to 0.1 mm/yr (Morgan, 1996; Tadesse, 2001). According to Basic et al.

(2004), the erosion risk in the watershed can be estimated by dividing the erosion rate

by the soil loss tolerance. Assuming the mean soil loss tolerance be 10 t/ha, which

was accepted as appropriate for moderate thickness of soil (Morgan, 1996; Mwendera

et al., 1997; Tadesse, 2001), then the soil loss obtained from this study increased by

70% (approximately four fold of soil loss tolerance). This also greater by 97% to soil

formation, by assuming the average soil formation worldwide is 0.1 mm/yr (the range

is from 0.01 to 7.7 mm/yr) taken from the book of Morgan (1996). According to this

assumption, the Debre Mewi watershed can be characterized by high erosion risk area.

38

4.3 Effects of different physical factors on soil erosion and processes

4.3.1 Effects of rainfall to soil erosion

From the group discussion and personal interviews, it was reported that rill

formation started at the beginning of the rainy season. Though the study had begun

lately after 25% of rainfall passed, the field survey showed almost the same result with

the interview. Of course, the rainfall in the months before monitoring dates was not

distributed evenly. There was no high rainfall recorded to erode significant amount of

soil loss compared to July and August months. The peak erosion was occurred in the

month of July which accounted for more than 90% soil loss, of which, about 42% was

occurred at the beginning of rill measurements, in the month of early July. This 42%

soil loss was recognized by 18% of the rainfall recorded in this July month. This result

showed similar findings with Herweg, et al. (2002). In general, at the beginning of

measuring date the soil loss was accounted approximately 37.5% of the total soil loss.

As it was described in the Figure 13, after the first measurement of rill

volumes, the rate of soil loss was increasing at decreasing rate. Only a few more rills

were formed in the month of August. Thus, most erosion occurred before the time of

highest rainfall. Though the rainfall increased, the change in rill erosion magnitudes

between each monitoring dates was getting smaller. Finally the redistributions of

sediment affected the rill dimensions and hence no significant change in magnitude of

rill erosion was observed at the mid-August and then. This finding is in agreement

with findings by Bewket and Sterk (2003) and Herweg et al (2002).

39

Figure 13: Average soil loss for the 15 upland agricultural fields in the Debre-Mewi watershed, the light shaded columns is the cumulative soil loss for the season. The black boxes are the soil losses for the individual storms; the line with diamonds is the cumulative rainfall.

Therefore, a large proportion of annual soil loss was occurred during a few

rainstorm periods (Herweg and Ludi, 1999). The generated runoff from these periods

was the most important direct driver of severe soil erosion. Rills were initiated mostly

by these few destructive storms, but their continued growth throughout much of the

wet season was the effect of the cumulative rainfall (Bewket and Sterk, 2003).

Therefore, the effectiveness of SWC technology depends on the extent to which it can

resist such ‘extreme’ rainstorm periods.

As observed during survey, the life span of rills was not uniform throughout

the wet season. Most of the shallow rills lost their depths and widths by sediment

redistributions and by the time, the crop covered the soil. Some of the rills joined to

other wider rills and after a while, they would disappear.

40

4.3.2 Effects of run-on to soil erosion

Run-on, surface runoff coming from the upper fields, was the cause of rill

formation in the mid and down-slope fields. Surface runoff coming as a run-on had

considerable contributions in rill formation and then soil loss. The upslope-surveyed

fields did not receive any surface runoff from the uplands due to the main car road

crossed and acting as a divide. Therefore, the rills in the upslope positions were

initiated by surface runoff generated inside the fields that created very small

dimensions of rills. In the mid-slope fields, the run-on coming from the upland fields

formed 46% of rills developed in the upper boundary of fields (Table 9). They

received large amounts of surface runoff from areas in the upslope position. The rills

contributed 68% soil loss resulted from the upper parts (in the first upper transects) of

seven mid-slope fields (Table 9). All rills classified in large wide rills were found in

this slope position.

Most down-slope fields had grasslands at the upslope boundary. As a result,

only 31% of rills initiated in the upper boundaries of the down slope-surveyed fields

were developed by run-on. These rills contributed 35% of soil loss formed in the first

upper transects of the down fields.

Hence, contrary to the mid-slope fields, the amount of soil loss produced from

rills initiated by run-on in the down slope fields was less than produced by within field

rills. One reason for this may be that all fields in this slope position were sown tef

crop, which is very susceptible to erosion. The soil type, slope gradient, slope lengths

and other hydrological factors may be other reasons.

41

Table 9: Contribution of run-on on rill formation and soil loss Field No

No of rills in field

No of rills as run-on

Soil loss due to all

rills (t)

Soil Loss (t)

% of soil loss due to run-on

to total

% of No of rills due to

run-on to total1 0.0 1.0 0.4 0.4 100.0 100.0 2 4.0 6.0 0.3 0.2 60.0 60.0 3 7.0 5.0 0.5 0.2 41.7 41.7 4 20.0 4.0 1.3 0.2 16.7 16.7 5 8.0 2.0 0.9 0.2 20.0 20.0 6 10.0 4.0 0.8 0.2 28.6 28.6

S1 49.0 22.0 4.1 1.4 34.5 31.0 7 8.0 7.0 0.8 0.4 46.7 46.7 8 0.0 2.0 1.1 1.1 100.0 100.0 9 0.0 2.0 0.9 0.9 100.0 100.0 10 0.0 8.0 0.3 0.3 100.0 100.0 11 11.0 14.0 0.5 0.3 56.0 56.0 12 16.0 0.0 0.3 0.0 0.0 0.0 13 15.0 9.0 1.1 0.4 37.5 37.5 S2 50.0 42.0 5.0 3.4 67.6 45.7 T 99.0 64.0 9.1 4.8 52.6 39.3

In general, from the upper boundaries of 13 fields found in the mid and down-

slope positions of the study site, about 39.3% of the rills that contributed more than

half amount of soil loss (52.6%) were initiated due to run-on (Table 9). This result has

important implications in designing SWC measures. The result obtained in this study

can help as an initial for the watershed practitioners to plan what types of SWC

measures to which area are appropriate to reduce soil erosion risk and to increase

productivity.

4.3.3 Effects of crop cover to soil erosion

The role of crop cover is extensively studied in the literature. Cover reduces

the direct impact of raindrops on the soil, it increases the flow depth, infiltration and

surface roughness and it reduces the speed of runoff. Thus, cover reduces the amount

of soil detached by flowing water and the capacity of water flow to transport sediment

(Morgan, 1991; Mwendera et al., 1997; Tamene and Vlek, 2007). Therefore, the

percentage cover of each crop was estimated whenever each rill measurements were

42

undertaken. The result clearly showed that it has direct effect on the magnitudes of

rills (Figure 14).

Figure 14: Graph of crop cover versus soil loss rate

During fieldwork observation, the peak soil loss was measured when the cover

was approximately zero. Though there were other factors for this result, the cover

effect might take the major contributions. The effect of the five days temporal

variations of rainfall and crop coverage of the four crop types (namely Tef, Wheat,

Millet and Maize) in 2008 on soil loss for individual storms is clearly described in

Table 10 and Figure 14. The result showed almost similar trend. This means that the

soil loss rate in all fields decreased slowly while the cover continues its growth. The

correlation coefficient of soil loss and cover percentage of the three crop types (tef,

millet, and maize) was -0.7 and with wheat was -0.5. At the beginning of rill

43

measurement, the cover of tef and wheat lands was zero whereas the other two

croplands were covered in some amount. The soil loss in tef field was strictly

decreased with increasing the cover, whereas maize and wheat fields scored

exceptionally high value during the second and the third measurement time

respectively. Weeding during this time might be the case for special increment of soil

loss. As clearly shown in the Figure 14, the four graphs started in the first quadrant of

the plane figure and ended up in the second quadrant. This clearly shows that the soil

loss in all crops decreases as the cover increases. In general, coverage has direct

impact on erosion processes. Table 10: Relationship between soil loss and crop cover (cc).

Mon

th

Observation Date

RF/5 days (mm)

Rate of soil loss (t/ha) Crop coverage (%)

mz wh mt tef CC, mz

CC, wh

CC, mt

CC, tef

July

7/11/2008 51 4.9 0.9 6.9 7.3 26 3 10 0 7/18/2008 75 8.3 0.6 -1.4 6.8 36 10 25 1

7/22/2008 69 1.4 4.9 -2.0 4.2 40 25 30 5 7/29/2008 55 0.1 0.5 0.8 2.2 46 53 55 15

Aug

ust 8/1/2008 57 -1.0 0.6 -0.5 2.4 50 55 55 17

8/12/2008 34 -3.0 -0.7 -3.8 -7.0 60 70 70 40 8/27/2008 52 -1.1 -0.7 -0.6 75 85 90 75

mz is maize, wh is wheat and mt is millet

Therefore, soil cover can decrease soil erosion whose effectiveness can be

greatly increased if it is combined with good soil management practices. A unit

increase of percentage cover can bring about a much reduction in soil loss only where

the soil is properly managed.

44

4.3.4 Effects of soil texture on erosion processes

Soil erosion depends much of the infiltration rate of a soil. The infiltration rate

again depends on the soil texture. Morgan (1996) recommended that the types of SWC

structures constructed in cultivated land mainly depend on the soil texture found on

the slope where conservation was planned. According to the soil profile analysis made

by AARC in six different locations of the entire watershed in 2008, soil texture class

ranges from clay loam to heavy clay with the later being a dominant. Nevertheless, at

the top layer (0-15 cm) of soil texture class as shown in Table 11 was analyzed as clay

soil (>40%), which is mostly characterized by poor infiltration rate that results high

runoff. This value also indicates that the soil is from moderately to severely eroded

(Tegegne, 1992). The farmers during personal interview and group discussion also

assured this phenomenon, which will be discussed latter. In the down slope area,

common water lodged in rainy season was observed which indicates poorly drained

and resulted high runoff. Table 11: Laboratory analysis result of the plough layer soil property at six representative locations in Debre Mewi watershed by AARC in 2008. Chemical property Physical property No PH %

C % OM

% Sand

% Clay

% Silt

Class

1 6.06 0.078 0.13 28 37.44 34.6 Clay loam 2 6.54 1.113 1.92 18 45.44 36.6 Clay 3 6.81 1.38 2.38 24 49.44 26.6 Clay 4 6.63 1.007 1.72 24 53.44 22.6 Clay 5 6.38 2.08 3.58 32 43.44 24.6 Clay 6 6.78 2.4 4.13 38 31.44 30.6 Clay loam Ave 6.53 1.34 2.31 27.3 43.44 29.2 Clay

From the Table 11, the percentage of organic matter in most sampled plots of

the plough layer of the study area indicates that the area was severely eroded

according to the conclusion made by Tegegne (1992) and Hagmann (1996). This

45

might be because of the high erosion rates are related to low organic matter contents

(Tegegne, 1992).

46

CHAPTER 5

5 FARMERS’ PERCEPTION OF LAND CONSERVATION

5.1 Household and farm characteristics

As it is described in Table 12, the total households living in the Debre Mewi

watershed is 276, of which 241 were headed by males and 35 by females. The total

population of these households was 1092, of which 47% were below 15 and 3% above

60. As reported by the farmers during discussion, the dramatically increase in

population caused multiple problems in the watershed. However, population increase

can be positive as well. For example, Amsalu and Graaff (2004) cited in their study

that better environmental conditions were observed in Kenya with growth in

population.

There were 485 people in the 80 surveyed households. The average family

size was six persons (Table 12). The average age of sampled farmers was 44, with a

minimum age of 30 and maximum 74. Of the total respondents, 7% were female,

mainly divorcees. Over half of the respondents (65%) were illiterate while the rest

could read and write through basic education and religion schools.

All of the interviewed farmers owned land. The mean holding size was about

1.2 ha. Taking the average household size and average land holdings of the sample

households, the per capita holding was 0.2 ha, which showed an agreement with

Benjamin et al., (2007) study that describes the average land holdings in Ethiopia

falling from 0.5 ha per person in 1960 to 0.11 ha per person in 1999. There was a

significant variation in the size of land holdings among householders. Of the sampled

households, the majority (56.2%) possessed between 0.6-1.0 ha of land. Only 9.4%

had more than two ha and some 14.1% had less than or equal to 0.5 ha (Table 12).

Though it was not included in the personal interview, the participants in the group

discussions reported that one household possessed up to six plots of farmlands within

47

the small total farm size. This fragmentation has its own negative effects to implement

soil and water conservation measures. As farmers noted during discussion,

constructing terraces or bunds on these small sized farmlands is believed as adding

another problem greater than erosion problems. Farmers do not recommend

constructing physical structures on very small croplands. Table 12: Characteristics of total households and their livestock in the four villages of the watershed (HH stands for household)

Characteristics Villages Mariam Wuha

Quyo Shanko Bahir

Feres Wag

Total

Total No of HH 52 83 52 89 276 Family size 149 285 243 415 1092 Age of 0-14 55 144 123 190 512

15-60 91 133 116 210 550 >60 3 8 4 15 30

Sample HH 26 26 11 17 80 Oxen 93 87 82 110 371 Cow 69 62 67 77 275

Young bull 42 40 45 42 169 Heifers 43 58 34 37 172 Calves 50 42 48 59 198 Mule 3 6 3 1 13 Horse 0 0 0 0 0

Donkey 48 60 34 50 192 Sheep 197 156 200 235 787 Goat 24 5 21 46 96

As in all other parts of the Ethiopian highlands, livestock are the most essential

element for the life of the people in the study area to fulfill a complex role in

smallholder mixed systems. They are not only used to produce meat and milk, but are

used as a store of wealth, for insurance purposes (as a saving account), that is, the

farmer can sell his livestock at the local markets whenever he is in need urgent of cash

and often for fulfilling social obligations (Tadesse, 2001, Thornton, 2003, Randolph et

al., 2007). The percentage of animals kept by the surveyed households is clearly

shown in Table 13. The composition of the farm animals was such that cattle

48

accounted for 50%, sheep 36%, goats 3% and mule and donkeys for 11%. Oxen

determine the efficiency of cropping. Nearly 10% of the households did not possess an

ox; some 19% owned only a single ox; 45% had a pair of oxen; 26% had 3 to 5 oxen.

Table 13: The percentage of respondents who owned livestock and farm size

Farm size (ha)

% of HH

No of livestock

cow %

ox %

donkey %

sheep %

goat %

0 – 0.5 12.5 0 18.75 10 43.75 15 93.750.6 - 1 37.5 1 40 18.75 35 5 0 1.1 - 2 47.5 2 25 45 13.75 31.25 2.5

> 2 2.5 3 6.25 12.5 7.5 22.5 0 <1 26.25 4 3.75 8.75 0 13.75 1.25

<mean 50 5 6.25 5 0 7.5 2.5 > mean 50 >5 0 0 0 5 0

Oxen are the decisive factor of production in the most of Ethiopian highlands

in general and in the Debre Mewi watershed in particular. Farmers have no any option

to produce crops without these main resources. Farmers without or one ox have

difficulty to plow the land, which is a serious farming constraint. Farmers without

oxen usually are renting their lands for crop sharing or for money. Those who

possessed one ox have used pairing (locally called kenja) with those facing the same

problem and sometimes with those possessing more than two oxen to overcome such

problems.

Leasing lands has its own negative implication for SWC practices as observed

in the study area. Croplands, which are leased especially for money, were cultivated

without any conservation structures except some traditional ditches. As farmers said,

these lands are fast loosing their productivity due to lack of attention given by the

owner or the one who rent. In the Debre Mewi watershed, ruminant animals like sheep

are very important sources of cash. The mules and donkeys transport people and

goods. There are only a few goats due to lack of feed as they mostly graze leaves of

small trees.

49

The major sources of fodder in the watershed are the crop residues and grazing

on closure and communal lands. In rainy season (kiremt) the livestock is dependent on

heavily degraded (overgrazed) communal lands. Some edible weed species from the

crop fields are also important sources of livestock feed during this rainy season.

During the dry season (bega), crop residues (mainly tef straw) are the main feed.

During this season, croplands serve as grazing lands. According to the farmer,

currently fodder availability is becoming a critical factor determining livestock

productivity. Farmers have reported that areas that have potential for pasture and

grazing are being used for crop production due to high population growth in the area

(Bewket, 2002).

From field observation, gullies in the watershed are a large threat and decrease

grazing lands and cultivation lands as discussed by Jaggar and Pender, (2003) as

shown in the Figure 15. Common grazing lands play a significant roll for this gully

formation. During transect walk in the rainy season, numerous very active gullies

were observed; farmers also confirmed this fact. Some farmers during informal

interview and group discussions suggested that distribution of these common grazing

lands for the community members for private use would decrease land degradation

due to animal track and over grazing. Contrarily, other farmers quoted, “unless there is

free grazing, our cows do not have a probability to get a bull for reproduction

activity”. Especially, those who possessed large number of animals supported this

idea, as they could not feed their animals by only collecting crop residues.

50

Figure 15: Photograph of active gully formation in the Debre Mewi watershed, Ethiopia

5.2 Perceptions of erosion as a problem

All the interviewed farmers perceived soil erosion as a problem constraining crop

production (Table 13). They reported that the most important top soil for crop

production activity was deteriorating over time due to erosion processes. Hence, they

observed frequently how the loss of soil from cultivated fields has been reducing the

depth of the topsoil through time and the number of stones in their farmlands has been

increasing over time. Moreover, when soil depth decreases the unproductive soil

(locally called zinza or sometimes gel) will be left. This soil is not productive. This

penomenon was common in the watershed.

The majority of the farmers reported that the occurrence of rill erosion was the

dominant erosion feature (89%) on their farmlands (Table 14). This percentage of

respondents also compared rill erosion problem as the highest with other erosion

features. Gully erosion was also reported by 11.25% of farmers along their farm

boundaries and waterways. Surprisingly, not all the respondents perceived sheet

erosion as a problem, which has been estimated in the literature to contribution to soil

up to 30% of actual soil loss (for example Govers, 1991). From all respondents, 64%

of the farmers rated the extent of the problem as sever and all the respondents

51

mentioned that the rate of soil erosion has been increasing over time. All of them also

answered that erosion can be controlled.

Table 14: Perception of respondents for soil erosion as a problem

Farmers’ responses to: Options Percentage (n=80)

Occurrence of soil erosion

Yes No

100 0

Prevailing form of erosion

Sheet erosion Rill erosion Gulley erosion

0 89 11

Extent of soil erosion severe Moderate Minor

64 36

Rill erosion compared to other erosion features

highest medium low

89 10 1

The rate of erosion over time

Increasing Same Decreasing

100 0 0

Can soil erosion be controlled?

Yes No

100 0

Farmers were asked to response how did they know soil erosion occurs on their

farmlands in open-ended question part. Some of the responses were; when there is

overflow of constructed ditches and damage their crops; when there is siltation in and

out of their field mostly at the lower field border; when rills appeared on their fields,

when the color of soil in the upper part of the field goes to red whereas the lower part

goes to black. From these responses, it can be concluded that farmers have good

perception of erosion as a problem that limits soil productivity.

5.3 Causes of Soil erosion, Soil fertility and Productivity decline

As indicated in Table 15, the major cause of soil erosion mentioned by 98 %

farmers was lack of conservation structures. Indeed, the transect walk in the entire

watershed confirmed that the SWC technologies were poorly constructed. Even those

few constructed conservation structures, mostly in the western part, were damaged

52

conservation structures. The majority of the farmers (61%) believed that damaged

structures contributed to soil loss. Minor contribution for soil erosion were steep

slopes (10%), lack of diversion ditch (5%) and others 5%.

Table 15: Farmers’ response to the causes of soil erosion, fertility and productivity decline

Farmers’ response to: Options Percentage (n=80)

Causes of soil erosion Lack of conservation structures Steep land w/o conservation structure Damaged conservation structures Lack of diversion ditch Others

98 10 61 5

Causes for soil fertility declining

Repeated cultivation Lack of manure Soil erosion Lack of fertilizer Others

79 9

100 0 0

Causes of crop productivity decline

Rain fall shortage Fertility decline Continuous cultivation Soil erosion Others

11 76 31 83 3

Note: Totals over 100% are due to multiple responses

Almost all of the farmers that either participated in the group discussion or in

interview reported declining in soil fertility in their farm plots over time. All the

respondents suggested that soil erosion was the major cause of soil fertility decline.

Repeated cultivation (continuous cultivation without rest) was also the other major

causes mentioned by 79% of the respondents. The other reasons given little

importance for fertility decline process were lack of manure (9%) and insufficient use

of artificial fertilizers.

Almost all of the interviewed farmers reported productivity decline. The

respondents mentioned that soil erosion was the main cause of productivity decline

53

was 83% followed by soil fertility (77%). Only 31% of them reported that continuous

cultivation had its own effect on soil productivity, whereas rainfall shortage was not

reported as a problem (Table 15). This observation agrees with those of Amsalu and

Graaff (2004) in the central highlands of Ethiopia, Bewket and Sterk (2002) in the

western Ethiopian highlands.

In general, soil fertility was the most important factor for crop production

mentioned by the farmers of the Debre Mewi watershed. It reflects the availability of

plant nutrients and soil organic matter (Moges and Holden, 2006). However, it is

decreasing over time due to soil erosion resulting from improper and exploitative

farming practices in the watershed. Most farmers in the watershed lack attention for

the effects of soil erosion on soil fertility. From the group discussions, farmers noted

that resting the land restores the nutrient depletion by soil erosion. Nevertheless, due

to scarcity of farm sizes this method cannot be practiced. To maintain soil fertility in

their lands, farmers commonly used animal manure and crop residues mostly around

their home and chemical fertilizer in other croplands. Few farmers have prepared

composts in order to minimize the expenditure of chemical fertilizers. However, lack

of materials like crop residues for this preparation and lack of technical supports from

extension agents limited their efforts to exercise such production of organic matter.

Some resource-poor farmers were observed while sowing crops without chemical

fertilizer because the price was beyond their capability. These practices do not secure

food as the fertilizer response of all crop fields is decreasing over time.

5.4 Farmers’ conservation practices in the watershed

Almost all of the farmers reported that SWC measures were very helpful for

erosion control and better crop production. Farmers commonly used to protect their

farm lands from soil erosion were stone terraces/bunds, cultural drainage ditches, soil

bunds, waterways and contour plowing (Table 16).

54

Table 16: Farmers’ conservation practices in the Debre Mewi watershed, Ethiopia

Management options Percentage (n=80)

Contour plowing Cultural ditches Soil bunds Stone bunds Grass strips Waterways Others

48 75 61 1 0 13 0

Note: Totals over 100% are due to multiple responses.

Traditional ditches (locally called feses, or sometimes shina) were indigenous

practices widely used by 75% of the surveyed farmers for erosion control (Table 16).

These are micro-channels constructed on cultivated fields to drive out excess water

from cultivated fields (Figure 16). The dimension and orientation of ditches are

different from normal plow furrow and their construction is performed in every

cropping season.

Most fields have traditional ditches and farmers believed that these ditches are

used to conserve soils, seeds and fertilizers by decreasing the dimensions of rills up to

the cover became strong enough to resist such erosion features. Indeed, the researcher

observed during the survey that these ditches had advantages to decrease the lengths of

rills and hence, widths and depths of rills by decreasing the concentration of runoff.

This may be one of the reasons for most rills grouped under shallow (or small) rills.

Though these ditches could reduce the dimensions of rills, soils, which were

transported by the rills, entered to it that was important means for the disposal of

eroded soils out of the field.

55

Figure 16: Side effects of cultural ditches, the left side is improperly designed and the right side indicates the overflowing of concentrated runoff .

Farmers reported during their interview that the ditches were effective

especially for one cropping season to conserve soil and chemical fertilizer from high

runoff. They also emphasized, “ditches demand less labor and low cost and short time

to construct compared to other newly introduced conservation measures”. However

finally, they underlined that for sustainability of the land, ditches have little

importance compared to other conservation structures like bunds and others. This

shows that though farmers have awareness for conservation structures to sustain land

productivity, they are still using conservation measures, which are important for short

span of time. This suggests that efforts of educating and training farmers towards the

newly introduced SWC technologies are very important.

Soil bunds were reported as the other means to conserve soil practiced by 61%

of the surveyed farmers. However, from field observation, soil bunds were rarely

constructed and poorly maintained. Though stone-bunds were not reported as a

measure of conservation, there were some efforts in the northwestern part of the

watershed where stones are easily available. Farmers indicated the inappropriateness

of the soil bunds on steep slopes where runoff is high. Waterways, permanent

56

structures constructed alongside the cultivated fields, were used by 12% of the

respondents. These structures are wider and deeper than the ditches and normally

require maintenance. Farmers connect the ditches to waterways for the safe disposal of

excess water.

Contour plowing was widely used in the area mentioned by 48% of the

respondents. This measure was commonly used not only to conserve soil from erosion

but also to decrease traction power of animas during plowing. As SWC measure, it is

an efficient technique for reducing runoff mainly in moderately and gently sloping

areas. On steep slopes, as farmers noted, contour plowing only may not be effective; it

needs other techniques like bunds to do with effectively control erosion. Furthermore,

during discussion, crop rotation was reported as one of the important mechanism to

reduce soil erosion impacts. Fallowing was hardly possible due to scarcity of land.

Intercropping has also rarely been applied because of priority of farmers for high

market value crops.

5.5 Farmers’ perception, acceptance and adoption of SWC measures

As it can be seen in Table 17, almost all of the respondents (98%) reported

that the technologies were effective in arresting soil erosion. Similarly, all of the

respondents believed that the new SWC technologies had the potential to improve land

productivity. The farmers who tried to implement some conservation measures in their

plots were interviewed how they measure the effectiveness of SWC technologies.

They had already observed a better growth and development of crops particularly

along the structures where fertile sediments were trapped. They also evaluated that the

amount of sediment trapped by the structure was very high which would be out of the

field if that conservation structure were not built. During group discussion,

participants who treated their lands by some conservation structures gave witness for

the group that the technology they have been using improved their land productivity.

57

Table 17: Indicators of acceptance and adoption of SWC technologies

Farmers’ response to: Options Yes No Indicators of acceptance

- Their knowledge of SWC measures - Effectiveness of SWC in arresting

soil erosion - SWC have a potential to improve

land productivity

98.75

98.75

100

1.25

1.25 0

Indicators of adoption - Plan to implement the new SWC tech. - Plan to maintain the constructed

structures - Farmers should be paid for

constructing and maintaining SWC in their farm

98.75

100

15

1.25 0

85

The farmers were asked also what their intentions were regarding using the

introduced SWC technologies in the future (Table 17). Almost all of the respondents

expressed their commitment to continue maintaining the established structures. In

addition to this, from the farmers interviewed whether they would like to apply the

SWC technologies in the rest of their farm fields (plots that were not treated by that

time), all of the respondents expressed that they had plan to implement the SWC

measures. To assess their attitudes towards support need from the government, they

were asked whether they should be paid for constructing and maintaining the SWC

technology in their farm. The majority (85%) responded “NO” while only 15%

answered, “Yes”. This showed farmers had a potential to construct conservation

measures if they have technical support from concerned body.

Except some factors that limit their acceptance and adoption as stated in the

next section, it can be concluded that the introduced SWC technologies were widely

acknowledged and accepted as effective measures against soil erosion and as having

the potential to improve land productivity. Though they eagerly expressed the belief

58

that they could control erosion on their farm plots, yet the constructed SWC structures

in the farmlands were not maintained and some of them totally damaged

5.6 Factors Affecting Adoption of the Introduced SWC Technologies

In the watershed, the newly introduced soil and water conservation measures are rare.

Though farmers showed willingness to adopt the newly introduced SWC structures,

they are reluctant to practice these measures to their farmlands. From the interviewed

farmers, 87% reported that some conservation measures like terraces, bunds and

fanyajuus were time consuming and labor demanding for construction (Table 18). The

other issue that affected their conservation practices was lack of technical support

(23%) from the agricultural experts to construct bunds and terraces (locally known as

kiyessa). In the group discussion and informal interviews, lack of kiyessa was the big

issue raised by the participants. Table 18: Farmers’ reasons for not adopting the newly introduced SWC measures

Options Percentage (n = 80) Requires too much labor to implement Land insecurity Decrease farm size and difficult to plow Harbor mole-rats Lack of knowledge Not considering erosion as a problem Others (lack of technical support)

88 5 19 11 10 0 23

Note: Totals over 100% are due to multiple responses.

For example, farmers who wanted to construct with his indigenous knowledge

like terraces and if his neighbor does not, the runoff will not drained out, as the owner

of the down slope fields does not permit to receive the runoff since he did not

construct some conservation measures like the one who did. However, they

underlined, “if there were kiyessa, all the farmers would construct”, “even tomorrow

morning”. The researcher interviewed this issue to the Adet local district agricultural

office experts. They of course confirmed that there was little attention given to this

59

issue. However, they also assured that the office designed strategies to apply the

technology based on the farmers’ indigenous knowledge. The experts added that

farmers have awareness to the technologies but are unwilling to implement except few

in the district. In the watershed especially in Feres-woga village, few farmers felt land

insecure because they perceived as the government would take the watershed for the

investment purpose as was done at their neighbor kebele.

Finally, farmers during personal interview and group discussion were asked to

recommend what should be done to improve the effectiveness of SWC measures. They

suggested: (a) most farmers do not have materials to construct terraces and bunds.

Therefore, the concerned body like government should support in this regard; (b)

technical support from experts to design the SWC measures is mandatory; (c) though

farmers have awareness to soil erosion problem, continuous training and experience

sharing and incentives should be given for the community to understand and

implement the new SWC measures; (d) Once conservation structure constructed, it

should be maintained whenever necessary; (e) efforts should be taken until farmers

show willingness to adopt/adapt the technology; (f) the gap between two consecutive

terraces should consider the steepness of the crop lands; (g) if there is accessibility of

grasses and trees seedlings, they have dual purposes: for forage and for soil

conservation measures.

60

CHAPTER SIX

6 RECOMMENDATIONS

The current trend of land degradation by soil erosion is a threat to food security

and Debre Mewi watershed is not an exception. The farmers in the Debre-Mewi

watershed suffer from severe erosion. Gullies and their effects are increasing at

alarming. Basic natural resources like soil, water and vegetative cover in the

watershed are deteriorating. Farmers are not satisfied with the status of their current

land holding. Based on the interview and field observation, the intensity of the rainfall

coupled with poor vegetation cover has aggravated the soil erosion in the watershed.

Hence, crop production and soil productivity have been decreasing overtime. Sofar,

farmers hardly undertake action to reduce erosion. Only few soil conservation

structures accompanied with poor management practices at household level were

observed frequently during the survey. If nothing is done to correct the existing

situation, more land will become unsuitable for crop production amd put even more

strain on the existing resources Therefore, sustainable soil management systems must

be developed to reduce further degradation and restore the productivity of the eroded

land. The management options to reduce the soil loss are to implement conservation

measures and/or to change the crop to be planted. Soil conservation methods including

terraces and bunds as well as semi-permeable structures like grass strips are used as

barriers to holdback runoff and sediment carried with it. Agronomic measures like

contour plowing have the advantage to reduce runoff and soil loss. Changing to crops

that need less tillage and improve the soil structure can reduce the problem of erosion.

Especially the soil conservation designers should find a mechanism in such a way that

farmer can plant tef to get high profit while its contribution to erosion is minimized.

Cultural ditches currently implemented by farmers are effective in general and should

be an integral part in soil and water management practices proposed by soil

61

conservation designers. In the few cases that the cultural ditches did not perform well

they should be designed properly.

Farmers should be motivated to adapt the newly introduced SWC technologies

based on their indigenous knowledge. This may require a long and continuous effort

until they accept and implement the technology. During discussions with local

farmers, they showed great interest to practice terraces/bunds and grass strips and

plantation in their croplands. However, accessibility of grasses and trees seedling may

limit the application of such measures. The author hopes that AARC together with the

local office of Agriculture can help farmers in this regard.

Finally, the participation of different stakeholders during strategy

development, policy formulation and technology selection to sustain agricultural

productivities will help to identify the interests of the different stakeholders and to

choose more acceptable and appropriate management options. Therefore, detail

investigation should be undertaken through the collaboration of stakeholders to

identify better management options that decrease soil erosion and improve food

productivity. At last but not the least, as there is no best conservation measure, the

integration measures are highly recommended.

62

CHAPTER SEVEN

7 CONCLUSIONS

The measurement and description of rill erosion was an important aspect of

erosion research in the Debre Mewi watershed. At the study site, highest erosion rates

were observed in early July that can be attributed to the higher erosivity of rains,

higher erodibility of the soil surface after a warm and dry season, and the poor soil

cover due to land preparation for sowing crops. The results obtained from the

surveyed fields indicated that the amount of soil loss due to rills was 26.6 t/ha. By

assuming the amount of soil loss due to inter-rills as different literatures is 25% of the

actual soil loss, the total soil loss is going to be 36 t/ha. This rate is an agreement with

total sediment measured from control plot of AARC experimental station in the study

site, which was estimated to be 38.3 t/ha. However, if it were assumed to be 30% of

actual soil loss contributed due to inter-rills as Bewket and Sterk (2003) did, it would

be almost the same result (38t/ha) with that control plot. Moreover, the USLE

experimental model predicted the soil loss in all surveyed fields as 39 t/ha and in the

expressed control plot was as 37.8 t/ha. Therefore, it can be concluded that rill survey

was an important methodology to quantify soil loss at field level.

The erosion rate was correlated wih slope positions and crop cover types, of

which the second was the most important. The highest erosion was found at down

slopes fields and tef crops. Furthermore, physical factors such as rainfall, run-on, soil

texture and land cover are important factors assessed as causes of soil erosion

processes. About 39% of the rills were developed in the above measured transects of

13 surveyed fields due to run-on from uplands, which contributed 53% of soil loss in

these transects.

All the interviewed farmers perceived soil erosion as a problem constraining

crop production. Most of these respondents reported that the occurrence of erosion

63

damages get bigger when the soil was bare (before vegetative growth). Farmers

expressed the opinion that the loss of soil from cultivated fields reduced the depth of

the topsoil and lead to a reduced production potential. Rill erosion was the dominant

forms mentioned by 89% of the farmers whereas, sheet erosion was not perceived as

erosion problem. The farmers consider that erosion is severe mostly when the visible

erosion features like rills and gullies appeared in their fields.

The most widely used land conservation techniques by farmers in Debre Mewi

watershed were: traditional ditches, soil bunds and contour plowing. Of these,

drainage ditches, whose limitations and advantages are discussed in this paper, are the

preferred and most widely practiced conservation measures because they are less labor

demanding and more effective in disposal of excess water after heavy rain occurred.

The major factors influencing farmers’ land conservation decision processes were:

demanding much labor, decreasing farm size and difficult to plow and lack of

technical support from agricultural experts.

64

CHAPTER EIGHT

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71

APPENDIX A: TABLES

TABLE A1: SOME DESCRIPTIONS OF THE SURVEYED FIELDS Slope positions

Field No

Field L (m)

Field W (m)

Field size (ha)

Crop type

Date of sowing

First measurement

date

Slope (%)

Slope length (m)

Critical distance

(m)

Down slope

1 60 45 0.27 Tef 7/14/2008 7/11/2008 11_16 60 5 2 75 45 0.34 Tef 7/13/2008 7/11/2008 12_20 75 5 3 55 74 0.41 Tef 7/16/2008 7/11/2008 14_16 55 6 4 50 47 0.24 Tef 7/15/2008 7/11/2008 10_15 50 5 5 44 36 0.16 Tef 7/15/2008 7/11/2008 12_16 44 6 6 34 70 0.24 Tef 7/15/2008 7/11/2008 11_12 34 6

Mid slope

7 78 29 0.23 Maize 6/11/2008 7/11/2008 12_18 78 6 8 62 38 0.24 Tef 7/16/2008 7/12/2008 8_12 62 7 9 56 45 0.25 Tef 7/15/2008 7/12/2008 8_10 56 7 10 49 39 0.19 Wheat 7/7/2008 7/12/2008 9_12 49 6 11 40 60 0.24 Tef 7/4/2008 7/2/2008 10_12 40 6 12 31 49 0.15 Tef 7/16/2008 7/12/2008 7_9 31 7 13 41 47 0.19 Millet 7/3/2008 7/12/2008 7_9 41 7

upslope

14 50 50 0.25 Millet 7/4/2008 7/12/2008 9_10 50 7 15 28 60 0.17 Millet 6/23/2008 7/12/2008 8_10 28 7

Total 3.56

72

TABLE A2: SELECTED MAXIMUM RILL DIMENSIONS AIDING ANALYSIS OF RILL MAGNITUDES Observ. Date

Tran sect

No of rills

Ave L (m)

Ave W (cm)

Ave. D (cm)

Field size (ha)

soil loss (m3)

Soil Loss ∑(m3)

Soil loss (t)

Soil loss (t/ha)

AAD (m2)

AAD ∑(m2)

AAD as% to field size (%)

Soil Loss per AAD m3/ha

Total length (m)

Rill density (m/ha)

8/1/

2008

1 1 17 70 3 0.27

0.36 0.36 0.43 1.60 11.9 11.9 0.4 300.0 17.0 63.0 17 10 15 3 0.05 0.77 0.93 3.43 1.5 25.5 0.9 300.0 170.0 629.6

2 12 8 15 3 0.04 0.43 0.52 1.94 1.2 14.4 0.5 300.0 96.0 355.6 1 8 50 4 0.16 0.16 0.19 0.72 4.0 4.0 0.1 400.0 8.0 29.6 1 10 150 4 0.60 0.60 0.73 2.69 15.0 15.0 0.6 400.0 10.0 37.0

3 1 10 50 3 0.15 0.15 0.18 0.67 5.0 5.0 0.2 300.0 10.0 37.0 20 8 10 3 0.02 0.48 0.58 2.15 0.8 16.0 0.6 300.0 160.0 592.6 2 12 200 3 0.72 1.44 1.74 6.45 24.0 48.0 1.8 300.0 24.0 88.9

4 1 18 200 4 1.44 1.44 1.74 6.45 36.0 36.0 1.3 400.0 18.0 66.7 8 8 8 2 0.01 0.10 0.12 0.46 0.6 5.1 0.2 200.0 64.0 237.0 1 14 150 4 0.84 0.84 1.02 3.76 21.0 21.0 0.8 400.0 14.0 51.9

Sum 4 65 11.2 83.5 3.3 4.38 6.77 8.19 30.32 121.0 201.9 7.5 335.1 591.0 2188.9

8/1/

2008

1 18 8 15 4 0.34

0.05 0.86 1.05 3.10 1.2 21.6 0.6 400.0 144.0 426.7 2 9 195 4 0.70 1.40 1.70 5.03 17.6 35.1 1.0 400.0 18.0 53.3 10 8 12 5 0.05 0.48 0.58 1.72 1.0 9.6 0.3 500.0 80.0 237.0 2 1 16 60 4 0.38 0.38 0.46 1.38 9.6 9.6 0.3 400.0 16.0 47.4 12 8 15 4 0.05 0.58 0.70 2.07 1.2 14.4 0.4 400.0 96.0 284.4 10 10 12 4 0.05 0.48 0.58 1.72 1.2 12.0 0.4 400.0 100.0 296.3 3 9 12 15 4 0.07 0.65 0.78 2.32 1.8 16.2 0.5 400.0 108.0 320.0 1 11 90 4.5 0.45 0.45 0.54 1.60 9.9 9.9 0.3 450.0 11.0 32.6 4 9 10 12 3 0.04 0.32 0.39 1.16 1.2 10.8 0.3 300.0 90.0 266.7 20 10 20 4 0.08 1.60 1.94 5.74 2.0 40.0 1.2 400.0 200.0 592.6 1 10 30 3 0.09 0.09 0.11 0.32 3.0 3.0 0.1 300.0 10.0 29.6 5 20 10 25 3 0.08 1.50 1.82 5.38 2.5 50.0 1.5 300.0 200.0 592.6 6 18 10 20 3 0.06 1.08 1.31 3.87 2.0 36.0 1.1 300.0 180.0 533.3

73

7 10 9 10 3 0.03 0.27 0.33 0.97 0.9 9.0 0.3 300.0 90.0 266.7 Sum 7 141 10 37.93 3.75 2.16 10.15 12.28 36.37 55.0 277.2 8.2 366.0 1343.0 3979.3 FIELD 3

8/1/

2008

1 3 15 50 5 0.41

0.38 1.13 1.36 3.34 7.5 22.5 0.6 500.0 45.0 110.3 20 7 15 4 0.04 0.84 1.02 2.49 1.1 21.0 0.5 400.0 140.0 343.1 2 16 6 10 5 0.03 0.48 0.58 1.42 0.6 9.6 0.2 500.0 96.0 235.3 18 8 12 4 0.04 0.69 0.84 2.05 1.0 17.3 0.4 400.0 144.0 352.9 3 41 7 12 5 0.04 1.72 2.08 5.11 0.8 34.4 0.8 500.0 287.0 703.4 4 25 8 15 4 0.05 1.20 1.45 3.56 1.2 30.0 0.7 400.0 200.0 490.2 8 12 15 6 0.11 0.86 1.05 2.56 1.8 14.4 0.4 600.0 96.0 235.3 5 1 12 20 8 0.19 0.19 0.23 0.57 2.4 2.4 0.1 800.0 12.0 29.4 14 10 10 5 0.05 0.70 0.85 2.08 1.0 14.0 0.3 500.0 140.0 343.1 6 12 8 10 4 0.03 0.38 0.46 1.14 0.8 9.6 0.2 400.0 96.0 235.3

Sum 6 158 9.3 16.9 5 0.96 8.20 9.92 24.31 18.2 175.2 4.3 467.9 1256.0 3078.4 FIELD 4

8/1/

2008

1 16 8 13 5 0.05 0.83 1.01 4.28 1.0 16.6 0.7 500.0 128.0 544.7 2 18 7 12 3 0.03 0.45 0.55 2.34 0.8 15.1 0.6 300.0 126.0 536.2 3 6 7 12 3.5 0.03 0.18 0.21 0.91 0.8 5.0 0.2 350.0 42.0 178.7 4 6 5 15 3.5 0.03 0.16 0.19 0.81 0.8 4.5 0.2 350.0 30.0 127.7 5 19 9 13 3 0.04 0.67 0.81 3.43 1.2 22.2 0.9 300.0 171.0 727.7 6 24 8 12 4.5 0.04 1.04 1.25 5.34 1.0 23.0 1.0 450.0 192.0 817.0

6 89 7.3 12.83 3.75 0.24 0.21 3.32 4.02 17.11 5.6 86.6 3.7 383.9 689.0 2931.9 FIELD 5

8/1/

2008

1 10 10 25 3 0.16 0.08 0.75 0.91 5.73 2.5 25.0 1.6 300.0 100.0 631.3 2 14 10 18 3 0.05 0.76 0.91 5.78 1.8 25.2 1.6 300.0 140.0 883.8 3 17 8 20 3 0.05 0.82 0.99 6.23 1.6 27.2 1.7 300.0 136.0 858.6 4 22 7 15 2.5 0.03 0.58 0.70 4.41 1.1 23.1 1.5 250.0 154.0 972.2 2 14 15 4 0.08 0.17 0.20 1.28 2.1 4.2 0.3 400.0 28.0 176.8

Sum 4 65 9.8 18.6 3.1 0.29 3.07 3.71 23.43 9.1 104.7 6.6 293.0 558.0 3522.7

74

FIELD 6

8/1/

2008

1 2 7 15 1.5 0.24 0.02 0.03 0.04 0.16 1.1 2.1 0.1 150.0 14.0 58.1 2 11 8 15 4 0.05 0.53 0.64 2.65 1.2 13.2 0.5 400.0 88.0 365.4 3 12 10 10 8 0.08 0.96 1.16 4.82 1.0 12.0 0.5 800.0 120.0 498.3 4 16 10 15 6 0.09 1.44 1.74 7.24 1.5 24.0 1.0 600.0 160.0 664.5 5 5 4 15 2 0.01 0.06 0.07 0.30 0.6 3.0 0.1 200.0 20.0 83.1 7 10 15 3 0.05 0.32 0.38 1.58 1.5 10.5 0.4 300.0 70.0 290.7 6 5 12 10 10 0.12 0.60 0.73 3.01 1.2 6.0 0.2 1000.0 60.0 249.2 7 11 9 20 2 0.04 0.40 0.48 1.99 1.8 19.8 0.8 200.0 99.0 411.1 8 14 9 25 2 0.05 0.63 0.76 3.17 2.3 31.5 1.3 200.0 126.0 523.3

8 83 8.78 15.56 4.28 0.49 4.96 6.00 24.93 12.1 122.1 5.1 406.3 757.0 3143.7 FIELD 7

7/29

/200

8

1 14 10 15 3 0.23 0.05 0.63 0.76 3.37 1.5 21.0 0.9 300.0 140.0 618.9 2 9 7 10 3 0.02 0.19 0.23 1.01 0.7 6.3 0.3 300.0 63.0 278.5 7 20 15 3 0.09 0.63 0.76 3.37 3.0 21.0 0.9 300.0 140.0 618.9 1 15 75 4 0.45 0.45 0.54 2.41 11.3 11.3 0.5 400.0 15.0 66.3 3 1 10 45 6 0.27 0.27 0.33 1.44 4.5 4.5 0.2 600.0 10.0 44.2 5 9 10 3 0.03 0.14 0.16 0.72 0.9 4.5 0.2 300.0 45.0 198.9 4 11 12 10 3 0.04 0.40 0.48 2.12 1.2 13.2 0.6 300.0 132.0 583.6

Sum 4 48 12 25.71 3.571 0.94 2.70 3.27 14.44 23.1 81.8 3.6 330.3 545.0 2409.4 FIELD 8

8/2/

2008

1 13 15 10 2.5 0.24 0.04 0.49 0.59 2.50 1.5 19.5 0.8 250.0 195.0 827.7 2 6 300 2.5 0.45 0.90 1.09 4.62 18.0 36.0 1.5 250.0 12.0 50.9 2 1 15 325 2.5 1.22 1.22 1.47 6.26 48.8 48.8 2.1 250.0 15.0 63.7 20 6 12 3 0.02 0.43 0.52 2.22 0.7 14.4 0.6 300.0 120.0 509.3 3 6 12 20 3 0.07 0.43 0.52 2.22 2.4 14.4 0.6 300.0 72.0 305.6

sum 3 42 11 133.4 2.7 1.80 3.47 4.20 17.82 71.4 133.1 5.6 260.8 414.0 1757.2 FIELD 9 8/2/2008 1 14 7 20 3 0.15 0.04 0.59 0.71 4.68 1.4 19.6 1.3 300.0 98.0 645.2

2 1 5 60 3 0.09 0.09 0.11 0.72 3.0 3.0 0.2 300.0 5.0 32.9

75

16 6 12 2.5 0.02 0.29 0.35 2.29 0.7 11.5 0.8 250.0 96.0 632.0 3 19 9 10 2.5 0.02 0.43 0.52 3.41 0.9 17.1 1.1 250.0 171.0 1125.7 2 8 150 3 0.36 0.72 0.87 5.74 12.0 24.0 1.6 300.0 16.0 105.3

Sum 3 52 7 50.4 2.8 0.53 2.11 2.56 16.84 18.0 75.2 5.0 281.0 386.0 2541.1 FIELD 10

8/2/

2008

1 8 6 15 4 0.19 0.04 0.29 0.35 1.82 0.9 7.2 0.4 400.0 48.0 251.2 2 2 7 15 3 0.03 0.06 0.08 0.40 1.1 2.1 0.1 300.0 14.0 73.3 3 3 24 15 3 0.11 0.32 0.39 2.05 3.6 10.8 0.6 300.0 72.0 376.8 1 24 50 4 0.48 0.48 0.58 3.04 12.0 12.0 0.6 400.0 24.0 125.6

Sum 3 14 15 23.75 3.5 0.66 1.16 1.40 7.31 17.6 32.1 1.7 359.8 158.0 826.8 FIELD 11

8/2/

2008

1 12 10 20 3 0.24 0.06 0.72 0.87 3.65 2.0 24.0 1.0 300.0 120.0 502.5 6 14 55 4 0.31 1.85 2.24 9.36 7.7 46.2 1.9 400.0 84.0 351.8 2 17 9 12 3 0.03 0.55 0.67 2.79 1.1 18.4 0.8 300.0 153.0 640.7 1 14 150 5 1.05 1.05 1.27 5.32 21.0 21.0 0.9 500.0 14.0 58.6 3 22 8 12 3 0.03 0.63 0.77 3.21 1.0 21.1 0.9 300.0 176.0 737.0 10 4 15 3 0.02 0.18 0.22 0.91 0.6 6.0 0.3 300.0 40.0 167.5 4 20 7 12 3 0.03 0.50 0.61 2.55 0.8 16.8 0.7 300.0 140.0 586.3 5 15 8 10 2.5 0.02 0.30 0.36 1.52 0.8 12.0 0.5 250.0 120.0 502.5 6 6 5 8 2 0.01 0.05 0.06 0.24 0.4 2.4 0.1 200.0 30.0 125.6 1 10 100 10 1.00 1.00 1.21 5.07 10.0 10.0 0.4 1000.0 10.0 41.9 7 25 5 12 2.5 0.02 0.38 0.45 1.90 0.6 15.0 0.6 250.0 125.0 523.5

Sum 7 135 8.5 36.9 3.7 2.57 7.21 8.72 36.53 46.0 192.9 8.1 373.8 1012.0 4237.9 FIELD 12

7/12

/200

8

1 16 6 10 2.5 0.19 0.02 0.24 0.29 1.51 0.6 9.6 0.5 250.0 96.0 498.2 2 16 6 8 2.5 0.01 0.19 0.23 1.21 0.5 7.7 0.4 250.0 96.0 498.2 3 17 5 10 2 0.01 0.17 0.21 1.07 0.5 8.5 0.4 200.0 85.0 441.1 4 8 7 12 2 0.02 0.13 0.16 0.84 0.8 6.7 0.3 200.0 56.0 290.6 5 22 6 10 2.5 0.02 0.33 0.40 2.07 0.6 13.2 0.7 250.0 132.0 685.0

Sum 5 79 6 10 2.3 0.07 1.07 1.29 6.70 3.0 45.7 2.4 233.3 465.0 2413.1

76

FIELD 13

8/2/

2008

1 10 11 30 3 0.25 0.10 0.99 1.20 4.75 3.3 33.0 1.3 300.0 110.0 436.5 2 15 10 25 3 0.08 1.13 1.36 5.40 2.5 37.5 1.5 300.0 150.0 595.2 3 14 12 12 2.5 0.04 0.50 0.61 2.42 1.4 20.2 0.8 250.0 168.0 666.7 4 16 15 10 2.5 0.04 0.60 0.73 2.88 1.5 24.0 1.0 250.0 240.0 952.4 5 24 15 10 2.5 0.04 0.90 1.09 4.32 1.5 36.0 1.4 250.0 360.0 1428.6

5 79 13 17.4 2.7 0.29 4.12 4.98 19.78 10.2 150.7 6.0 273.4 1028.0 4079.4 FIELD 14

7/23

/200

8

1 25 6 10 2.5 0.25

0.02 0.38 0.45 1.82 0.6 15.0 0.6 250.0 150.0 600.0 2 18 8 10 2.5 0.02 0.36 0.44 1.74 0.8 14.4 0.6 250.0 144.0 576.0 3 18 7 12 3 0.03 0.45 0.55 2.20 0.8 15.1 0.6 300.0 126.0 504.0 1 8 60 3 0.14 0.14 0.17 0.70 4.8 4.8 0.2 300.0 8.0 32.0 4 1 14 18 4 0.10 0.10 0.12 0.49 2.5 2.5 0.1 400.0 14.0 56.0 9 8 12 2.5 0.02 0.22 0.26 1.05 1.0 8.6 0.3 250.0 72.0 288.0 8 5 20 2.5 0.03 0.20 0.24 0.97 1.0 8.0 0.3 250.0 40.0 160.0 5 12 5 15 3 0.02 0.27 0.33 1.31 0.8 9.0 0.4 300.0 60.0 240.0

Sum 5 92 7.6 19.63 2.875 0.38 2.12 2.56 10.26 12.3 77.5 3.1 273.5 614.0 2456.0 FIELD 15 7/23/ 2008

1 1 6 200 3 0.17 0.36 0.36 0.44 2.59 12.0 12.0 0.7 300.0 6.0 35.7 2 12 6 25 2 0.03 0.36 0.44 2.59 1.5 18.0 1.1 200.0 72.0 428.6

Sum 2 13 6 112.5 2 0.39 0.72 0.87 5.19 13.5 30.0 1.8 240.0 78.0 464.3

77

TABLE A3: ESTIMATION OF SOIL LOSS USING USLE MODEL No Collected data for USLE parameters in each field Estimated values for each parameter At slope

length (15m)

Crop cover

RF (mm)

Soil color

L (m)

S (%)

Soil mgt Crop cover

RF (mm)

Soil color

L (m)

S% Avg

Soil mgt

Predict. Soil loss (t/ha)

at L = 15m

Soil loss at L=15m

1 Tef 1165 Brown 60 13.5 So. bund 0.25 647 0.2 1.6 1.33 0.5 34.4 0.8 34.4 2 Tef 1165 Brown 75 14 contour 0.25 647 0.2 1.8 1.40 0.9 73.4 0.8 36.2 3 Tef 1165 Brown 55 15 contour 0.25 647 0.2 1.5 1.50 0.9 66.4 0.8 38.8 4 Tef 1165 Brown 50 16 contour 0.25 647 0.2 1.5 1.58 0.9 69.0 0.8 40.9 5 Tef 1165 Brown 44 14 contour 0.25 647 0.2 1.4 1.40 0.9 57.1 0.8 36.2 6 Tef 1165 Black 34 11.5 contour 0.25 647 0.15 1.2 1.14 0.9 29.9 0.8 22.1 7 Maize 1165 Red 78 17 So. bund 0.1 647 0.25 1.8 1.64 0.5 23.9 0.8 21.2 8 Tef 1165 Red 62 10 St. bund 0.25 647 0.25 1.6 1.00 0.7 45.3 0.8 32.4 9 Tef 1165 Red 56 9 contour 0.25 647 0.25 1.5 0.90 0.7 39.2 0.8 29.1 10 Wheat 1165 Red 49 10.5 So. bund 0.15 647 0.25 1.5 1.00 0.5 18.2 0.8 19.4 11 Tef 1165 Red 40 10.5 contour 0.25 647 0.25 1.4 1.00 0.7 39.6 0.8 32.4 12 Tef 1165 Red 31 8 contour 0.25 647 0.25 1.2 0.80 0.7 27.2 0.8 25.9 13 Millet 1165 Red 41 8 contour 0.15 647 0.25 1.4 0.80 0.7 19.0 0.8 15.5 14 Millet 1165 Red 50 9.5 contour 0.15 647 0.25 1.6 0.95 0.7 25.8 0.8 18.4 15 Millet 1165 Red 28 9 contour 0.15 647 0.25 1.1 0.90 0.7 16.8 0.8 17.5 39 28

78

TTAABBLLEE AA44:: MMOONNTTHHLLYY RRAAIINN FFAALLLL ((mmmm)) FFOORR AADDEETT SSTTAATTIIOONN ((77 kkmm FFRROOMM TTHHEE SSTTUUDDYY AARREEAA)) Jan Feb March April May June July Aug Sep Oct Nov Dec 1996 6.2 2.5 95.1 165.8 174.2 205.1 341.6 283.1 275.9 19.7 124.6 1.3 1997 3.4 0 48.9 20.2 247.3 158.6 255.3 195.1 237.9 170.8 43.7 0 1998 2.5 0 23.5 19.7 182 155.1 327.8 259.7 169.7 196.4 9.9 1.2 1999 26.3 0 1.7 24.1 95.8 129.4 332.8 242.8 115.6 143.1 26.6 16.4 2000 0 0.2 2.4 134.9 58.7 99.6 250.6 248 127.3 159.8 24.4 9.1 2001 0 4.1 8.7 34.4 136.9 193.7 340.9 369 146.2 85.4 25 10.8 2002 11.7 3.8 39.2 35.6 50.5 136 281.6 198.6 122.4 54.9 8.9 13.5 2003 0 7.9 10.1 6.1 16.2 162.7 340.6 292.4 205.1 52.4 21.6 3.1 2004 5.4 7 0 32.5 10.2 189.3 286.1 246.9 204.1 120.3 21.6 0 2005 17 0 27.9 40.4 30.2 105.1 330.8 213.6 192.6 152.7 27.4 0 Mean 7.25 2.55 25.75 51.37 100.2 153.46 308.81 254.92 179.68 115.55 33.37 5.54 TTAABBLLEE AA55:: MMOONNTTHHLLYY MMAAXXIIMMUUMM TTEEMMPPEERRAATTUURREESS ((00CC)) FFOORR AADDEETT Jan Feb March April May June July Aug Sep Oct Nov Dec 1996 26.5 28.9 29.2 28.4 26 23.4 22.3 22.1 24.3 25.5 25.2 25.7 1997 26 28.5 29.1 29.1 27.2 24.7 21.9 23.2 25.1 24.6 25.1 26.6 1998 27.4 28 29.2 29.9 27.8 25.6 21.2 21.2 23.2 24.2 25 25.8 1999 25.7 28.9 29.3 29.9 28.4 25.6 21.5 21.9 23.7 23 24.6 25.2 2000 26.6 28.1 29.9 26.1 27.8 25.8 22.5 22 23.7 23.5 24.5 25.3 2001 26 28.5 28.5 29.6 28 23.6 23 22.8 24.8 26 25.1 26.7 2002 26.6 28.7 29.1 30 29.5 26.2 24.3 23.3 24.1 25.6 25.9 25.9 2003 27.2 28.9 29.7 30.3 30.8 26.5 22.6 22.6 23.7 25.1 25.6 26 2004 27.2 28.1 30 28.7 30 25.4 23.4 22.9 23.9 24.4 25.4 26.2 2005 26.4 30 29.7 29.8 29 27.3 22.4 23.3 24.2 24.4 25.3 26 Mean 26.7 28.7 29.4 29.2 28.5 25.4 22.5 22.5 24.1 24.6 25.2 25.9

79

TTAABBLLEE AA66:: MMOONNTTHHLLYY MMIINNIIMMUUMM TTEEMMPPEERRAATTUURREESS ((00CC)) FFOORR AADDEETT Jan Feb March April May June July Aug Sep Oct Nov Dec 1996 4.1 5.5 9.1 11 11.8 11.5 11.8 11.5 11.1 8.9 7.6 5.7 1997 3.7 5.1 10 10.2 11.8 11.1 11.6 11.7 10 10 9.1 5.5 1998 5 4.6 9.5 8.9 11.4 11.5 11.4 12.2 11.2 11 6.9 4.3 1999 5.4 6.5 4.8 7.3 9.2 10.9 11.9 11.9 10.2 10.6 6.4 6.2 2000 5.7 6.5 6.7 9.7 11 10.7 11.7 11.2 10.3 10.9 7.9 6.3 2001 4.4 7.5 10 10.7 11.4 11.9 12.5 12.6 10.7 11 7.9 6.8 2002 6.3 8.5 10 11 11.4 12.7 12.1 12.4 10.7 9.8 8.7 6.5 2003 6 9.5 12 11.6 13.4 12.8 12.9 13 11.4 10 8.3 6.6 2004 7.2 8.2 10.4 12.6 12.2 12.1 11.7 12.3 10.9 9.4 9.2 7.4 2005 6.1 8.8 10.8 13 11.6 11.6 11.9 12.3 11.9 11.1 7.7 4.7 Mean 5.39 7.07 9.33 10.6 11.52 11.68 11.95 12.11 10.84 10.27 7.97 6

TTAABBLLEESS AA44DD:: MMOONNTTHHLLYY MMEEAANN SSUUNNSSHHIINNEE DDUURRAATTIIOONN FFOORR BBAAHHIIRR DDAARR SSTTAATTIIOONN Jan Feb March April May June July Aug Sep Oct Nov Dec 1996 9.6 10.2 8.9 8.9 6.4 6.9 5.4 4.3 6.9 9.6 9 10 1997 9.1 10.2 8.4 8.3 7.9 6.2 5.2 5.3 8.1 7.9 9.1 10.1 1998 9.6 10.1 9 9.7 8.5 8.1 3.3 3.6 6.4 8.4 10.1 10.7 1999 9.6 10.7 10.4 9.7 8.5 7.1 4.7 5 6.5 7.4 10.4 10.1 2000 10.4 10.3 10.3 7.3 8.8 7.7 4.9 3.6 6.6 7.3 9.5 9.7 2001 10.3 9.8 7.9 9.5 8.5 5.3 4.2 3.9 7.3 8.3 9.6 9.9 2002 8.7 9.9 8.8 10.3 9.9 7.4 5.8 5 7 8.9 9.5 10.1 2003 10.3 9.3 8.8 9.8 8.5 6.5 3.8 3.5 5.5 9.5 9.6 10 2004 9.7 9.8 9.9 7.9 9.7 6.2 5.4 4.6 6.2 8.7 9 9.7 2005 9.3 10 8.8 8.6 8.7 7.1 3.8 5.1 6.7 8.6 9.5 10 Mean 9.66 10.03 9.12 9 8.54 6.85 4.65 4.39 6.72 8.46 9.53 10.03

80

TABLE A7: MONTHLY RELATIVE HUMIDITY FOR ADET STATION

Year Months

Jan Feb March April May June July Aug Sep Oct Nov Dec 1996 50.7 44.7 51.7 58 66.3 66 78.7 79.3 74.3 62 59.3 57 1997 47.3 43.7 55.3 51 64.3 71.7 80.3 78.7 69.7 69.3 63.3 54.7 1998 50 43 47.3 41.3 57 70 84.3 86.3 79 75 62.7 53.7 1999 62 49 47.5 47 62.5 68 84 79.5 75.5 76.5 59 59.5 2000 51.3 45.3 40.3 59.3 57.3 68.7 80 83.7 76 79 65.7 63.3 2001 58 55 50.3 50.3 63.3 79 83.3 84.3 75.7 74 68.7 63.3 2002 64 62.7 65 59.7 60.3 71.7 76.3 83.7 83 80 74.7 71 2003 64 61.3 60 53.3 52.7 79 89 90.7 88 80.3 76 71.3 2004 67.7 65.3 59.3 63.3 60.7 80.3 86.7 89.7 88 79.7 78 66.3 2005 45.3 32.7 42 38 42.7 64.1 64.3 79 77.3 71.4 62.3 48.2 Mean 56.03 50.27 51.87 52.12 58.71 71.85 80.69 83.49 78.65 74.72 66.97 60.83

TABLE A8: TEN YEARS (1996-2005) AVERAGE METEOROLOGICAL DATA FROM ADET STATION

Jan Feb March April May June July Aug Sep Oct Nov Dec

Rain Fall 7.25 2.55 25.75 51.37 100.2 153.46 308.81 254.92 179.68 115.55 33.37 5.54 Mean Temp 16.045 17.885 19.365 19.9 20.01 18.54 17.225 17.305 17.47 17.435 16.585 15.95 Mean Hum 56.03 50.27 51.87 52.12 58.71 71.85 80.69 83.49 78.65 74.72 66.97 60.83

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TABLE A9: SUM OF FIVE DAYS RAINFALL DATA DURING RESEARCH TIME (2008) Date April May June July August Sep 1_5 4 47.6 38 9.8 56.5 30 6_10 28.2 33.6 21.6 51.2 35 12 11_15 112.9 13.8 19.9 51.4 34 43.5 16_20 0 9.7 35.2 75 40 12 21_25 10.4 2.3 14.1 69.1 35 16 26_31 12.8 36.4 13.9 55.1 52 33 Total 168.3 143.4 142.7 311.6 252.5 146.5

TABLE A10: RATE OF SOIL LOSS IN DIFFERENT CROP COVER TYPE AND COVER EFFECT

Month

Observation Date

RF/5 days

Rate of soil loss (t/ha) Crop coverage (%) maize wheat millet tef CC,

maize CC,

wheat CC,

millet CC, tef Ave

cc July

7/11/2008 51 4.89 0.94 6.86 7.31 26 3 10 0 9.8 51

7/18/2008 75 8.27 0.58 -1.44 6.8 36 10 25 1 18.0 7/22/2008 69 1.41 4.94 -1.95 4.17 40 25 30 5 21.5 7/29/2008 55 0.11 0.47 0.82 2.24 46 53 55 15 32.8

August

8/1/2008 57 -1.01 0.62 -0.46 2.39 50 55 55 17 38.5 35

8/12/2008 34 -3.03 -0.7 -3.83 -7.03 60 70 70 40 56.3 40 35

8/27/2008 52 -1.04 -0.74 -0.58 75 85 90 75 75.0

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TABLE A11: ANALYSIS OF MC, BD AND IR Down slope Mid-slope Time (min) Initial Depth (mm) Difference in depth (mm) IR (mm/h) Initial Depth (mm) Difference in depth (mm) IR (mm/h)

0 100 100 1 95 5 300 96 4 240 2 91 4 240 93 3 180 3 87 4 240 90 3 180 4 84 3 180 88 2 120 5 81 3 180 86 2 120 6 78 3 180 84 2 120 7 76 2 120 82 2 120 8 74 2 120 80 2 120 9 72 2 120 79 1 60

10 70 2 120 78 1 60 12 67 3 90 76 2 60 14 65 2 60 74 2 60 16 63 2 60 72 2 60 18 62 1 30 71 1 30 20 60 2 60 69 2 60 24 56 4 60 66 3 45 28 54 2 30 64 2 30 32 52 2 30 62 2 30 36 50 2 30 60 2 30 40 49 1 15 58 2 30 44 48 1 15 57 1 15 48 47.5 0.5 7.5 56 1 15 52 47 0.5 7.5 55 1 15 56 46.5 0.5 7.5 54 1 15 60 46 0.5 7.5 53 1 15

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ANALYSIS OF MC AND BD

FIELD Moist soil (g) Dry soil (g) MC BD

DS MS US DS MS US DS MS US DS MS US 1 117.7 119.9 123.3 165.9 164.6 164.7 48.2 44.7 41.4 1.20 1.22 1.26 2 104.8 125.1 120.6 146.2 172.9 163.1 41.4 47.8 42.5 1.07 1.27 1.23 3 118.0 117.8 124.4 162.5 161.9 162.6 44.5 44.1 38.2 1.20 1.20 1.27 4 120.1 121.6 128.5 162.5 166.8 168.1 42.4 45.2 39.6 1.22 1.24 1.31 5 119.1 120.6 129.1 165.1 164.4 170.1 46 43.8 41.0 1.21 1.23 1.32 6 127.5 121.8 125.2 173.9 164 165.7 46.4 42.2 40.5 1.30 1.24 1.28 7 114.4 117.6 159.9 163.8 45.5 46.2 1.17 1.20 8 122.1 120.9 167.4 162.9 45.3 42 1.24 1.23 9 111.3 117.1 154 158 42.7 40.9 1.13 1.19

10 111.3 122.3 149.3 169.4 38 47.1 1.13 1.25 11 121.9 120.6 167.6 162.5 45.7 41.9 1.24 1.23 12 127.1 124.1 171.1 168.8 44 44.7 1.30 1.26 13 124.5 118.7 170.7 158.1 46.2 39.4 1.27 1.21 14 110.3 124.3 152.5 170.6 42.2 46.3 1.12 1.27 15 114.8 122.3 158.7 165.2 43.9 42.9 1.17 1.25 16 107.1 114.3 148.7 151.8 41.6 37.5 1.09 1.16 17 115.6 116.3 156.5 154.9 40.9 38.6 1.18 1.19 18 107.3 120.5 146.3 165.2 39 44.7 1.09 1.23 19 112.8 103.5 153 141.9 40.2 38.4 1.15 1.05 20 116.2 115.3 159.6 153.3 43.4 38 1.18 1.18 21 112.5 153.1 40.6 1.15 22 118.9 161.6 42.7 1.21

In % 37.3 35.9 32.4

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MC DURING MEASURMENT OF IR cup (g) Soil + cup (g) moist soil Dried soil + Cup dried soil MC % 1095.2 1855.2 760 1708.5 613.3 146.7 19.3 1098.3 1916.4 818.1 1792.1 693.8 124.3 15.2 180.7 513.2 332.5 469.6 288.9 43.6 13.1

TABLE A12: RILL MAGNITUDES AT EACH SAMPLE OF OBSERVATION DATE IN THRE SLOPE POSITIONS

Observation Date

Soil loss rate (t/ha)

AAD in m2 Rill density (m/ha)

DS MS US DS MS US DS MS US 7/11/2008 8.50 6.15 7.14 435.85 273.39 94.28 1808 1000 1292 7/18/2008 14.24 11.40 7.42 672.78 475.34 95.9 2600 1813 1632 7/22/2008 18.90 14.51 8.69 787.78 589.55 107.48 2858 2396 1656 7/29/2008 23.34 16.04 7.44 906.22 640.69 88.99 3121 2383 1510 8/1/2008 25.99 17.36 4.25 965.61 692.79 63.34 3136 2483 1033 8/12/2008 22.69 13.87 1023.67 547.93 3094 2481 8/27/2008 20.72 13.18 921.74 529.12 3000 2316

TABLE A13: RILL MAGNITUDES AT EACH SAMPLE OF OBSERVATION DATE IN FOUR CROP FIELDS

Observation Date Rate of soil loss (t/ha)

AAD (m2)

Rill density (m/ha)

maize wheat millet tef maize wheat millet tef maize wheat millet tef 7/11/2008 4.89 0.94 6.86 7.31 29.65 4.8 45.7 193.24 1017 209 2413 858 7/18/2008 13.16 1.52 5.42 14.11 81.6 6.75 31 355.99 2347 235 1043 2187 7/22/2008 14.57 6.46 3.47 18.28 85.76 27.9 23.6 452.29 2454 680 981 3065 7/29/2008 14.68 6.93 4.29 20.52 81.75 29.7 26.28 502.96 2409 733 851 3071 8/1/2008 13.67 7.55 3.83 22.91 83.2 32.1 25.68 551.81 2356 827 851 3234 8/12/2008 10.64 6.85 15.88 81.45 30.9 435.58 2157 701 2951 8/27/2008 9.60 6.11 15.30 80.5 31.6 412.22 2025 701 2742

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TABLE A14: THE UNIVERSAL SOIL LOSS EQUATION (USLE) ADAPTED FOR ETHIOPIA (HURNI 1985B). SOURCE: WISCHIMEIER AND SMITH, 1978 ADAPTATIONS: R CORRELATION, HURNI, 1985

K VALUES, FROM BONO AND SEILER, 1983, 1984: WELGEL, 1985

S EXTRAPOLATION: HURNI, 1982 EQUATION: A = R K L S C P 1. R: RAINFALL EROSIVITY ANNUAL RF (mm): 100 200 400 800 1200 1600 2000 2400 ANNUAL FAC, R: 48 104 217 441 666 890 1115 1340 2 K: SOIL ERODIBILITY SOIL COLOR BLACK BROWN RED YELLOW -------------------------------------------------------------------------------------------------------- FACTOR K 0.15 0.20 0.25 0.30 3 L: SLOPE LENGTH LENGTH (m) 5 10 20 40 80 160 240 320 -------------------------------------------------------------------------------------------------------- FACTOR L 0.5 0.7 1.0 1.4 1.9 2.7 3.2 3.8 4 S: SLOPE GRADIENT SLOPE (%) 5 10 15 20 30 40 50 60 -------------------------------------------------------------------------------------------------------- FACTOR S 0.4 1.0 1.6 2.2 3.0 3.8 4.3 4.8 5. C: LANDCOVER DENSE FOREST 0.001 DENSE GRASS: 0.01 OTHER FOREST SEE GRASS DEGRADED GRASSES 0.05 BAD LANDS HARD 0.05 FALLOW HARD 0.05 BAD LANDSSOFT 0.40 FALLOW PLOUGHED 0.60 SORGHUM, MAIZE 0.10 EHTIOPIAN TEF 0.25 CEREALS, PULSES 0.15 CONTINUOUS FALLOW 1.00 6 P: MANAGEMENT FACTOR PLOUGHING UP AND DOWN 1.00 STRIP CROPPING 0.80 APPLYING MULCH 0.60 STONE COVER 80% 0.50 STONE COVER 40% 0.80 PLOUGHING ON CONOUR 0.90 INTERCROPPING 0.80 DENSE INTERCROPPING 0.70

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Source: Ministry of Agriculture Watershed Management guide page 51, January, 2001

Figure A1: The R-squared value (R2) between measured and predicted value of soil loss

y = 0.6748x + 16.851R2 = 0.5213

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0

Measured value (t/ha)

Pred

icte

d va

lue

(t/h

a)

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APPENDIX B: QUESTIONNAIRE Debre-Mewi Micro watershed, Amharic Regional State, Ethiopia, 2008 This questionnaire has been prepared to generate information on the extent of the farmers’ attitudes, acceptance and adoption of the introduced SWC technologies. Their awareness and perception of erosion processes, hazards and Factors that constraint their land conservation decision making processes. The approach followed in the planning and implementation of the technologies. Name of the household’s head--------------------------------------- Sex -------- age----- Part one Open ended questions 1 House hold characteristics, and access to resources

HH member Education Age Dependant I ------------------- ------------ --------- ------------- II ------------------- ------------ --------- ------------- III ------------------- ------------ --------- ------------- IV ------------------- ------------ --------- ------------- Farm size (ha) ------------ Livestock owned: Cow ------- Ox------ Donkey ----- Goat ----- Sheep ----, others------ 1 What are the major crops you have been using to your farmland?

-----------------------------------------------------------------------------------------------2 Is there a major change in cropping pattern during the last 15 years --------------

If yes what are the reasons -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

3 How does change in cropping pattern affect soil erosion? -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

4 Do you have a problem of erosion in your farm? ----------- 5 How do you know soil erosion occurs on your farm land? (Indicators) ----------

-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

6 What are the noticeable changes in your farm land over time in: i Soil fertility / crop productivity / fertilizer response ----------------------------

-----------------------------------------------------------------------------------------------

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-----------------------------------------------------------------------------------------------------------------------

ii Intensity of rill erosion -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

iii soil depth/surface stoniness ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

iv runoff generation /infiltration/ water holding capacity -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

7 From where dose the major runoff that cause soil erosion in your farm comes from? -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

8 Have you ever discussed the issue with your fellow farmer and draw potential solutions? ---------------------- If yes, what were problems to materialize the potential solutions? -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

9 How do you protect your farmland from erosion? (List all methods you are applying) -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

10 Are methods you applying effective? ------------------------- 11 How do you measure the effectiveness of SWC measure? -------------------------

---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

12 Do you know about SWC technologies? ---------------------- 13 Have you ever participated in SWC technology demonstration, field days or

workshops before? ---------- 14 Do you have information on use of different SWC practices / technologies? ----

-----------------If yes, state the advantages and disadvantages. Advantages ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Disadvantages ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------

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-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

15 Do you apply SWC on your whole farm? ---------- If no, how do you select a farm plot for SWC treatment? --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Years used in this way-------------------------------------------------------------------

16 In your opinion, what should be done to improve the effectiveness of SWC measure? --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

17 Do you apply fertilizer to your farmland? ------------------------ If yes, since

when? -----------------------------------------------------------------------------------------------------------

18 What level of yield advantage you would expect from fertilizer addition? Without fertilizer = -----------------With fertilizer = ----------------------------- yield addition in% =---------------------------------------------------------------------------------------------------------------------------------------------------------------------

19 Do you expect the yield advantage would remain the same amount with the same quantity of fertilizer of the next 5 years? -------------------, 10 years? ------

What was the trend over the past: 5 years? --------------------------------------------------------- 10 years? ------------------------------------------------------- 15 years? -------------------------------------------------------- 20 Have you applied the same amount and type of fertilizer since you start

applying fertilizer to your farmland (crop)? --------------------------------------- Part two Closed questions Farmers’ perceptions of soil erosion hazards in the watershed 1 Is soil erosion a problem in your farm? A/ yes B/ no 2 If yes, what is the severity of the problem A/ sever B/ moderate C/minor 3 Under what conditions do you say erosion is severe? A/ sheet B/ rill C/ gully 4 How do you compare the soil loss due to rill with other erosion features? A/

highest B/ medium C/low 4 You believe that the rate of erosion over time is, A/ increasing B/ same

C/decreasi 5 Observed change in soil erosion severity over the past 10 years: A/ large B/

moderate C/ no change 6 What do you believe is the impact of soil erosion on crop yields? A/ large

decrease B/ moderate decrease C/ no change D/ moderate increase E/ large increase

7 Do you believe that soil erosion can be controlled A / yes B/ no

90

For 8-10 choose those you agree with 8/ The main causes of soil erosion on your farm

9/ The main causes for declining of soil fertility on your farm

10/ The main causes of productivity decline on your farm

A/ lack of conservation structures B/ steep land without conservation structures C/ damaged conservation structures D/ lack of diversion ditch E/ the land is under steep ridges F/ others-----------------------------------------------------------------------------

A/ repeated cultivation B/ lack of manure C/ soil erosion D/ lack of fertilizer E/ others --------------------------------------------------------------------------------------------------------------------

A/ rain fall shortage B / fertility decline C/continuos cultivation D/ soil erosion E/ others -------------------------------------------------------------------------------------------------------------------------------

11 Indicators of farmers’ acceptance and adoption of the SWC technologies in

the watershed acceptance and adoption Answer

Yes No11.1 Indicators of acceptance Did you know the introduced SWC technologies before? Are the newly introduced SWC technologies effective in arresting soil erosion?

Do you believe that the new SWC technologies have the potential to improve land productivity?

11.2. Indicators of adoption Do you have plan/intention to maintain the constructed structures? Do you have plan/intention to implement the new technologies in the rest of your plots currently untreated?

Do you believe that SWC is farmers’ responsibility? Should farmers be paid for constructing and maintaining SWC in their farms?

12 What are the major limitations to apply SWC measures on your farm land? A/ The new technologies require too much labor to implement B/ Land tenure insecurity C/ Decrease the size of crop land D/ The new technologies harbor mole rats E/ Lack knowledge F/ Not considering erosion as a major problem G/Others -----------------------------------------------------------------------------------

13 What are the major determinant factors to adopt SWC measures? A/ Farm experience (age) B/farm size C/ plot size D/ severity of soil erosion E/ Others ---------------------------------------------------------------------------------------------------------------------------------------------

Documents

ASSESSMENT OF UPLAND EROSION PROCESSES …soilandwater.bee.cornell.edu/Research/international/docs/Bound... · erosion and control practices and to identify factors affecting farmers’