A DECISION SUPPORT SYSTEM FOR SOIL AND WATER CONSERVATION … · water conservation structures widely adopted by farming communities throughout the world. The DSS is capable of providing

land degradation & development

Land Degrad. Develop. 15: 49–63 (2004)

Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/ldr.589

A DECISION SUPPORT SYSTEM FOR SOIL AND WATER CONSERVATIONMEASURES ON AGRICULTURAL WATERSHEDS

A. SARANGI,1* C. A. MADRAMOOTOO2 AND C. COX3

1Agricultural and Biosystems Engineering, MS-1-019, Macdonald Campus, McGill University, Montreal, H9X3V9, Canada2Brace Centre of Water Management and Department of Agricultural and Bio-systems Engineering, McGill University, Montreal, Canada

3Agricultural and Biosystems Engineering, McGill University, Montreal, Canada

Received 7 December 2002; Revised 23 July 2003; Accepted 3 September 2003

ABSTRACT

Integrated watershed management (IWM) is vital in achieving agricultural sustainability in terms of both production andenvironmental protection. A decision support system (DSS) is useful in generating alternative decision scenarios formanagement of natural resources, facilitating the implementation of IWM concepts in an interactive and holistic way. Thedecision to implement an appropriate land use coupled with suitable soil and water conservation techniques not only enhanceswatershed health but also prevents sediment losses. Besides reducing basin fertility, such losses decrease the storage capacity ofdownstream reservoirs through silt deposition, which can, in turn, give rise to low biomass production and poorer flood control.In order to facilitate IWM, an effort was made to develop, in the Visual Basic programming language, a soil and waterconservation DSS which considered both structural and cropping practices for arresting sediment loss. Input parameters to theDSS for a given tract of land included: mean slope; sediment loss; soil type; and land capability class (LCC). Outputs includeddecision criteria to choose among alternative structural measures and suggested cropping systems to serve as biologicalmeasures to reduce soil loss and conserve water. Structural watershed management measures included a variety of soil andwater conservation structures widely adopted by farming communities throughout the world. The DSS is capable of providingsediment control solutions not only for small watersheds but also for larger drainage basins, by dividing the basin into smallerwatersheds. The DSS was validated for a watershed on the Caribbean island of St Lucia and used to suggest measures for a 10�

slope under specific soil type, sediment loss and LCC conditions. The measures proposed included bench terraces, gradedcontour bunds, conservation ditches, concrete chute spillways, diversion dams and conservation cropping systems. Themeasures actually adopted on-site were conservation ditches, graded contour bunds and conservation cropping systems, a closeparallel to the DSS’s proposed measures. On slopes ranging from 5–55�, implementation of the suggested control measuresresulted in a 34–37 per cent reduction in soil loss on the watershed. Copyright # 2004 John Wiley & Sons, Ltd.

key words: decision support systems; integrated watershed management; conservation structures; Visual Basic programming language;

sediment yield; sustainability

INTRODUCTION

Soil and water are the two critical resources for agricultural production and thus there is an urgent and ongoing

need for research to devise ways to manage soil and water resources in a more sustainable manner (National

Research Council, 1991). Integrated watershed management (IWM) is a vital approach for sustainable develop-

ment as the watershed is the hydrogeological unit that harbours these natural resources. IWM can be defined as a

multidisciplinary, holistic way of protecting and managing a watershed’s natural resources to enhance biomass

production in an eco-friendly manner. The watershed is viewed as a hydrogeological complex and dynamic

ecosystem in which natural and anthropogenic processes occur and interact, which gives rise to runoff at the

Copyright # 2004 John Wiley & Sons, Ltd.

�Correspondence to: A. Sarangi, Agricultural and Biosystems Engineering, MS-1-019, Macdonald Campus, McGill University, Montreal,H9X3V9, Canada.E-mail: [email protected]

watershed outlet. Furthermore, the watershed also acts as a social, economic and political unit for planning and

management purposes. Hence, the watershed manager and policy makers must consider all technical, social,

economic, environmental, legal and institutional aspects of watershed planning processes.

Concern about widespread soil degradation and scarce, poorly managed water resources has led to the

implementation of watershed management investments throughout Asia, Africa and Latin America (Kerr and

Chung, 2001). Despite the growing importance of watershed projects as an approach to rural development and

natural resource management, until now there has been relatively little research on their impact (Kerr and Chung,

2001). In this context, development of a decision support system (DSS) to address specific issues of watershed

management assumes importance and holds the promise of making watershed management simpler and more

effective. DSSs show great promise in the strategic planning of soil conservation efforts and can aid in the selection

of appropriate soil conservation practices for agricultural watersheds (Montas and Madramootoo, 1992). The

ability to reach decisions regarding alternative land uses and structural measures for different soil types and land

capability classes is essential to IWM. Altogether an IWM system will: (1) control sediment outflow to prevent

downstream flooding; (2) conserve water and soil fertility; (3) facilitate crop management and use land effectively;

(4) assist in soil and water resources planning and management; (5) reduce environmental and ecological

degradation; and (6) resolve issues related to stakeholder conflicts. Sustainable land management is an issue that

has long been debated. However, using a DSS to integrate all the data and information into a meaningful and

effective toolbox for use by land managers is gaining wider acceptance (Bishr and Radwan, 1995; Beynon et al.,

2002). It is now generally accepted that sustainable land management must be approached with the watershed as

the basic management unit (Cox, 2002). In the planning phase, watershed management requires that a broad range

of data be integrated into a logical framework. Land-use practices and structures adopted by indigenous farming

communities around the world along with standard well-known practices can be included in a DSS. Moreover, for

decision makers and managers to conceptualize environmentally sustainable, economically viable and socially

acceptable management options, a set of clearly defined input parameters must be defined.

A DSS supports technological and managerial decision-making by assisting in the organization of knowledge

about ill-structured, semi-structured or unstructured issues. When developing a DSS, the emphasis is on providing

decision-makers with a user-friendly tool to help them better evaluate and assess the watershed-scale impacts of

implementing conservation measures. The development of the DSS also seeks to enhance the accuracy and

usefulness of the decision-set provided to decision-makers. From the inception of DSSs, it has become clear that

they aid and assist decision makers but do not replace them (Kersten et al., 2000).

Datta (1995) developed a DSS for micro-watershed management, allowing investigation of water allocation and

agricultural production alternatives for the Bankura District, West Bengal, India. This menu-driven, user-

interactive, PC-based DSS, encoded ‘C’ on a MS-DOS platform, used a water budget to arrive at decision

scenarios. Its input requirements were watershed, soil, water resources, crop and weather-related data. Pertiwi et al.

(1998) developed a soil conservation DSS for upland farm management, with special consideration given to

estimating potential annual soil loss and comparing it to a tolerable soil-loss criterion. Encoded in Visual Basic

(VB) on a Windows 95TM platform, the DSS required universal soil loss equation (USLE) parameters as input. It

suggested improved soil conservation farming practices, including the most suitable soil tillage machinery, when

soil loss exceeded a tolerable soil-loss criterion. However, application of the DSS was location specific as it was

preloaded with data only suited to Japanese conditions. Bishr and Radwan (1995) developed a DSS for watershed

management integrating a geographic information system (GIS) tool, object-oriented data modeling and a

knowledge-based system to assist decision-makers in selecting the best management practices (BMPs) for

controlling soil erosion and water quality. The DSS was a combination of conceptual models such as the

agricultural non-point source pollution (AGNPS) model, interpretive routines and expert judgment by specialists

in the field of watershed management. The developed DSS for watershed management is very data intensive,

requiring a GIS tool to input watershed details, and a hydrologic model to predict soil loss and pollutant loads.

It appears that no existing watershed management DSSs offer watershed-scale structural and vegetative soil and

water conservation alternatives in response to inputs of land slope, soil type, measured sediment loss and land-

capability classification. An effort was made to collect, from published literature, research articles and Internet

50 A. SARANGI ET AL.

Copyright # 2004 John Wiley & Sons, Ltd. LAND DEGRADATION & DEVELOPMENT, 15: 49–63 (2004)

sources, information on existing soil and water conservation structures and vegetative measures adopted on

different watershed slope ranges, land-capability classes and soil types. The information was synthesized and

linked with recorded sediment-loss data. A decision-flow logic, which sought to reduce soil loss and conserve

water, was conceptualized and presented as a DSS using Visual Basic (Version 6�0). When the DSS is run with a

given set of input parameters, the recommended conservation measures are displayed along with images of

locations where such conservation practices have been adopted, in a variety of watersheds and agro-ecological

regions. The user interacts with the DSS to gather information on structural and biological measures suitable for

the watershed and then the suggested measures are implemented on the watershed. The DSS presented in this

paper is a new approach supported by a logical interpretation of existing published reports of watershed-based

conservation measures with a quantification of their effectiveness. As such, this DSS is one of a kind in terms of its

contribution to watershed-management decision making. The established historical data used in the DSS ensures

its versatility and application to watersheds around the world. Minor modifications of the recommended

conservation measures to fit local and indigenous practice may be required for global adoption. Moreover, St

Lucia and the entire Caribbean region need this type of management tool, because of the extensive soil erosion of

the steep hillside lands and the urgent need for conservation measures (Cox, 1997; Schwab et al., 1993).

Additionally, the VB programming language makes the DSS flexible enough to be interfaced with any GIS-based

soil and water resources conservation targeted watershed management support system.

Table I. USDA land capability and recommended land management practices (USDA, Pretall and Polius, 1981)

Land Most intensive suitable usecapabilityclass USDA Polius and Pretell (1981)

I Suitable for cultivation with almost no limitations. Level soils suitable for cultivation with almostno limitations on use

Fertilizers should be applied to maintain nutrient statusII Suitable for cultivation with one limiting factor of low Level to nearly level soils suitable for cultivation

degree with some moderate limitations that reduce thechoice of plants and require moderateconservation practices

III Suitable for cultivation with two limiting factors or Level to undulating soils suitable for cultivationcapability class of limitation with severe limitations that reduce the choice of

plants and/or require special conservation practicesIV Suitable for tree crops, improved pasture, and marginal Level to undulating soils suitable for cultivation with

for cultivation with three factors or degrees of very severe limitations that restrict the choice oflimitation plants and/or require very careful management

V Unsuitable for cultivation, but suitable for afforestation, Level soils without erosion hazard, not suitable fortree crops, or grass with four factors or degrees of cultivation except in certain areas where rice can belimitation grown. Suitable chiefly for pasture

VI Unsuitable for cultivation. Suitable for poor forest Very undulating to hilly soils with severe limitationsthat make them generally unsuited to seasonal cropsand restrict their use mainly to tree crops, pastures,or woodland

VII Little or no agricultural use Very steeply sloping soils with severe limitationsthat make them unsuited to cultivation and restricttheir use largely to woodland and wildlife

VIII Very steeply sloping soils, beach sands, or mangroveareas, having severe limitations that preclude theiragricultural use and restrict them to recreation,wildlife, water supply, or scenic use

In both classifications, the major limiting factors identified included high erosion risk, impeded/excessive drainage, aridity, shallow soil depth,stoniness, presence of hardpans and extreme slope steepness.

DECISION SUPPORT FOR SOIL AND WATER CONSERVATION 51


DATA COLLECTION FOR THE DSS

The data used for development of the DSS is mostly of secondary type and collected from the published texts and

articles on watershed management. The photographs presented in the DSS showing different soil and water

conservation measures and the information of the land uses are collected form different Internet web resources1,2,3.

The information of land capability classes (Stark et al., 1966; Pretall and Polius, 1981) and proposed land

treatment (Ahmed, 1989) information are extensively used in the DSS, which is presented in Tables I and II

respectively. The recommended conservation measures as shown in Table II are for the management of watersheds

in the Caribbean Island of St Lucia (Cox, 2002). The sources of further data used in developing the DSS are

enumerated under the following sub-headings.

Watershed Slope

At the watershed scale, land slope and roughness are of paramount importance in controlling the hydrological

process of movement and deposition of water-born soil (Cogo et al., 1984). Therefore, the relief and slope of the

land are the prime considerations for implementing structural and vegetative soil conservation measures on

watersheds. It was revealed that structures suggested for arresting sediment loss and conserving water differ little

for a variation in slope of �5 per cent (Srinivasan and Engel, 1991; Schwab et al., 1993). Therefore the DSS was

built on slope ranges of 1 to 2 per cent, 2 to 5 per cent, 5 to 10 per cent, 10 to 15 per cent, 15 to 20 per cent and slopes

greater than 20 per cent. For slope ranges of 1–2 per cent and 2–5 per cent the implementation of a combination of

soil and water conservation structures adopted in different regions (bunds, pipe inlet structures, tiled ditches,

contour drains, terraces and grassed waterways) was recommended. For a slope of 20 per cent or greater the

conservation measures are limited to vegetative barriers and afforestation techniques only, because it is difficult to

construct physical structures on such a slope and achieve structural stabilization (Cox, 1997; Hudson, 1995). The

DSS takes care of the slope of the watershed in two ways: (1) the mean slope calculated for the watershed as a

whole, representative of the entire watershed; and (2) the individual slopes of the hydrologic response units (HRUs)

within the watershed. Mean watershed slope is calculated using the expression as given in Equation 1. However, for

Table II. Soil stability classes and recommended land treatments proposed by Ahmad (1989)

Soil stability Slope class Capability Recommended conservation treatmentsclass (degree) class

Stable (A) 0–20 A1 Wide range of crops suitable; mulching; leguminous ground cover;diversion ditches; dyked contour drains

20–30 A2 Banana or tree crops along contour; grass barriers; contour drains;step drains; grassed waterways

>30 A3 Tree crops or forest; no tillage; partial or selective land clearingonly; ground cover for tree crops; hillside ditches; grassed waterways

Less stable (B) 0–10 B1 Range of crops; conservation tillage; diversion ditches; grass barriers;contour drains; grasses waterways; storm drains

10–20 B2 Banana or tree crops; mini-basins; contour planting; dyked contourdrains; grass barriers; step drains; grassed waterways

>20 B3 Preferably tree crops or forest trees; bananas with great care; partialclearing done manually; planting in mini-basins; no tillage; contourdrains; grassed waterways; step drains

Fragile (C) 0–5 C1 Food crops on contour; grass barriers; soil surface protection;minimum tillage

5–10 C2 Diversion ditches; food crops on contour ridges; grass barriers; grassedwaterways; minimum tillage; surface protection; agro-forestry

>10 C3 No disturbance; re-afforestation; agro-forestry



a HRU, the individual slope of the watershed is the relief of the watershed divided by the maximum length of the

selected HRU. This representative slope of the HRU is used as the input value for running the DSS.

Sa ¼H�Lca

ð10AÞ ð1Þ

Where

Sa is the average watershed slope in per cent

H is the maximum watershed relief in meters

Lca is the average length of the clearly identifiable contours within the watershed in km.

A is the area of the watershed in km2.

Moreover, the unit of slope used in the DSS is per cent slope, and the expression for conversion of degree slope to

per cent slope is given in Equation 24.

Percentage slope ¼ ððð½Slope in degrees��3�14159 = 180ÞTanÞ�100Þ ð2Þwhere Tan is the trigonometric tangent.

Sediment Yield from Watersheds

Sediment yield is the quantity of detached soil particles flowing out of the watershed and generally measured at the

stream outlet or calculated from the established soil loss empirical equations or conceptual hydrological models

(Hudson, 1995). Sediment outflow is influenced by a number of geomorphological processes. It may be

substantially less than the amount actually eroded in the basin due to successive erosion and deposition processes

within the watershed system. Sediment yield is typically expressed as the total sediment volume or mass delivered

to a specified location in the basin, divided by the effective drainage area above that location for a given period of

time. However, it is also necessary to estimate yield from a watershed from individual storm events of specified

frequency (e.g., 5-, 25-, 50-, or 100-year events). Individual event yields are reported as metric tons or cubic meters

per event. In some watersheds, single-event sediment yields often exceed average annual values by several orders

of magnitude (Cox, 1997). Moreover, the spatial and temporal variation in the biological and physical features of

the watershed causes the estimation of sediment yield an extremely difficult and imprecise task. Important

variables include soils and geology, relief, climate, vegetation, soil moisture, soil organic matter, biota,

precipitation, drainage density channel morphology, and human influences. Dominant processes within a

watershed may be entirely different between physiographic or ecological regions, and may change with time.

The problem becomes even more complex when grain size distribution and sediment yield for particular events

must be estimated for input to sedimentation transport simulation models. There is no widely accepted procedure

for computing basin sediment yield and grain size distribution directly from watershed characteristics without

measured information (Cox, 2002).

The DSS is developed using the data of annual sediment loss generated from soil-loss equations or soil-loss

prediction conceptual models having units in tons ha�1 yr�1 or megagrams Mg ha�1 yr�1. In the case of

watersheds having sediment load data of the out flowing stream expressed in weight or volume of sediment per

unit volume of runoff water, the data is transformed to Mg ha�1 yr�1 using the contributory area of watershed and

the total runoff volume measured at the discharge point. For implementation of conservation measures, the

‘tolerable soil loss’ must be defined. It is the maximum soil erosion that will permit a high level of crop

productivity to be sustained economically and indefinitely (Troeh et al., 1999). The tolerable soil-loss values

assigned by a group of American scientists during 1961 and 1962 ranged from 4 to 13 Mg ha�1 yr�1, later it was

agreed to be 11 Mg ha�1 yr�1 and for fragile soils the rate 2 Mg ha�1 yr�1 is considered (Troeh et al., 1999). It is

recognized that any level of agricultural land utilization will invariably generate some amount of soil loss, hence

the concept ‘tolerable soil loss’ makes sense. Keeping in view of this limit and the soil-loss information of the St

Lucia watershed (Cox, 1997), the tolerable soil loss limit is set to be 10 Mg ha�1 yr�1. This consideration is also

based on the concept that there will not be much variation in selection of soil and water conservation structures to

arrest sediment loss between 1 to 10 Mg ha�1 yr�1, as for most of the soil types with land capability classes from I



to VII, the soil loss varies from 8 to 13 Mg ha�1 yr�1 (Hall et al., 1985). However, there may be a combination of

different types of conservation measures to arrest sediment loss within 1 to 10 Mg ha�1 yr�1, which is suitably

dealt in the DSS by listing a number of vegetative and structural measures to arrest soil loss. It is also observed

from soil conservation publications that there is not much change in the type of conservation structures within a

soil loss of 10 Mg ha�1 yr�1 (Pertiwi et al., 1998). Therefore, considering all this published information, the

incremental value of sediment load considered in DSS is 10 Mg ha�1 yr�1, within which there is no abrupt change

in the suggestive conservation measures. Moreover, the DSS is flexible enough to accommodate different sediment

load ranges starting from minimum of 2 Mg ha�1 yr�1 to maximum of 13 Mg ha�1 yr�1 as discussed above. Hence,

with an aim to extend the applicability of this DSS for flat watersheds with low sediment-loss values, the sediment

range of 2 Mg ha�1 yr�1 and 5 Mg ha�1 yr�1 are also incorporated in the DSS. However, to account for the

different conservation measures within 10 Mg ha�1 yr�1 in real situations, there should be different conservation

practices to avoid redundancy in prediction. Keeping in view of the St Lucia watershed and eastern Caribbean

locations, the sediment-loss ranges considered in the DSS are 0 to 10, 11 to 20, 21 to 30, and so on, up to

80 Mg ha�1 yr�1 and greater than 80 Mg ha�1 yr�1. The incremental range of 10 Mg ha�1 yr�1 is also selected to

minimize the number of looping statements in the algorithms. It was observed that an incremental range of less

than 10 Mg ha�1 yr�1 did not provide any new control measures, but made the algorithm more complicated.

Moreover, in some watersheds the soil loss is more than the extreme value of 80 Mg ha�1 yr�1, but the conservation

practices remain almost identical to practices within sediment loss of 60 to 80 Mg ha�1 yr�1 and there is no

dramatic change in sediment-control measures, barring some combination of conservation measures.

Soil Type and Land Capability Classes (LCC) of the Watershed

The soil types considered in the DSS are ‘stable’, ‘less stable’ and ‘fragile’, and they are denoted as soil types ‘A’,

‘B’ and ‘C’, respectively. These soil types are related to a given slope range, and the land capability subclasses are

associated with each major class (Table II). Details of United States Department of Agriculture (USDA) land

capability classes (LCC) and soil stability types along with the conservation practices are presented in Tables I and

II. Soil types are used in conjunction with the LCC to suggest appropriate soil-management practices and the

structural measures for soil conservation in regions where the soil-type-based land classifications are more

prevalent than the USDA classification and vice versa. Consideration of both LCC and land classification on soil

stability through soil types ‘A’, ‘B’ and ‘C’ incorporates flexibility in the developed DSS.

Structural (Mechanical or Physical) Conservation Measures

A number of structural measures to prevent erosion by controlling the movement of water over the soil surface, and

specific to given land conditions and slope, are available for implementation on watersheds. Such measures are

generally employed in conjunction with agronomic measures (Morgan, 1986). The DSS lists contour bunds (also

known as contour furrows or desert-strip farming), semi-circular hoops (to catch and retain runoff water), strip

cropping, tied ridging (for water management), grass strips, permeable barriers, terraces (bench, diversion and

retention terraces), grassed waterways, contour farming (agricultural operations done along land contours),

stabilization structures (chute spillways, drop structures, pipe-inlet structures, rock-filled dams, brush-wood check

dams, woven-wire mesh dams and other indigenous structures to prevent sediment outflow) and geotextiles

(several types of netting and woven materials from natural fibers) (Morgan, 1986; Pimentel et al., 1993; Hudson,

1995). Woven geotextile mesh filled with soil after it is laid on the ground becomes more effective and can reduce

erosion by up to 20 per cent compared to unprotected land (Morgan, 1986). Afforestation is proposed as a

vegetative mechanical method to prevent erosion on steep slopes.

Vegetative or Biological Control Measures

Vegetation is preferred over structural measures since concrete, masonry, wood or any other building materials

are subjected to decay and liable to be undermined or bypassed. They thus become less effective with the passage

of time. Vegetation, on the other hand, can thrive and improve over the years. The vegetation prevents soil erosion

by reducing the velocity of runoff and providing physical protection from soil scouring (Schwab et al., 1993;



Hudson, 1995). Different afforestation and vegetation measures are incorporated in the DSS. They are proposed

by the DSS based upon the LCCs, slope ranges, and sediment loss. Crop, animal and land husbandry can be seen

as elements of biological conservation measures. The techniques proposed by the DSS include: farming

on grades; strip cropping (useful on gentle slopes); crop rotations; shifting cultivation; mixed cropping and

inter-planting; deep tillage; ripping or subsoiling (breaking the hard pan and enhancing porosity); conservation

tillage (surface mulching, minimum tillage, trash farming and strip tillage, etc.); reduced tillage (no-till, direct

tillage, small strip tillage and rotary tillage, etc.); agroforestry (plantation crop combinations); silvipastoral

practices; alley cropping (growing food crops between hedges) and combinations of rip-rap and vegetation across

and along the slope. However, for soil-conservation recommendations based on slope and LCCs, a combination

of vegetative measures works better than a single measure (Hudson, 1995; Hurni et al., 1996; Troeh et al., 1999).

Therefore, the DSS suggested a combined list of methods applicable for the given slope and land type, with the

final implementation of the conservation measures proposed dependant upon the suitability of the techniques at

the regional level.

Images from all over the world, of structural and vegetative controls adopted for watershed-scale soil con-

servation projects, are shown by the DSS. These images were collected from the USDA Natural Resources

Conservation Service photo gallery,5 FAO web site6 and textbooks on soil and water conservation (Schwab et al.,

1993; Hudson, 1995).

DEVELOPMENT OF THE DECISION SUPPORT SYSTEM

The DSS is an integrated assembly of models, data, interpretive routines and other relevant information that

efficiently processes input data, runs the models, and displays the results in an easy-to-interpret format (George

et al., 2002). The DSS is intended for use by watershed managers, government policy planners and those advising

farmers on the selection of watershed-wide sediment-control measures. It is a computer-based information system

designed to support decision makers interactively in making decisions about relatively unstructured problems. The

DSS developed does not contain any mathematical model per se, but consists of a decision rule relating the

secondary or historical data and interpretive routines using the published research articles on watershed

management. The DSS generates structural and biological soil and water conservation measures to be adopted

on watersheds. It is developed in the form of a computer program using the interactive controls and algorithms of

Visual Basic 6�0 programming language. The nested If . . .Then . . .Else construct is extensively used as an

interpretive algorithm for the generation of alternative decisions using the input information. The DSS runs on a

platform of Windows 95TM, or above, is user-friendly and is best viewed at a screen resolution of 1024 by 768

pixels. The Graphic User Interface (GUI) of the DSS is a combination of pop-up windows, pull-down menus and

button controls and is mouse driven. The model uses the set of conservation measures adopted for a given slope

and soil type as discussed under the vegetative and structural control measures section. After collecting the

necessary input information from the user, the DSS will suggest possible structural and vegetative measures, along

with land tillage and management options to be implemented to prevent the sediment losses reported by the user.

The DSS does not predict any sediment loss, but provides suggestive control measures to reduce the present level

of sediment loss, as measured at the outlet of the watershed.

The flow chart of the DSS showing different forms and major flow controls of the main decision frame is shown

in Figure 1. The highest range of sediment loss considered in the DSS (80 Mg ha�1 yr�1 and higher) is observed to

be possible for highly unstable soil type C and for land capability classes VII or VIII (Cox, 2002). The sediment

loss is then decreased by a step of 10 Mg ha�1 yr�1 and linked with different soil types, land capability classes and

slope values to suggest a given type of land use (e.g. afforestation, tree crops, horticultural crops, intensive

agriculture, etc.). A similar concept is also adopted for sediment-loss-rate ranges of 5 Mg ha�1 yr�1 and

2 Mg ha�1 yr�1.

The DSS consists of four Visual Basic (VB) forms (GUI windows) named as ‘welcome frame’, ‘definition of

terms used frame’, the ‘main DSS frame’ and ‘picture of conservation measures frame’. All the VB forms are



Figure 1. Flow chart of the DSS displaying the major flow-control architecture.



linked in a VB 6�0 environment. This programme is compiled and presented as an executable file named

WSDSS.EXE (WaterShed Decision Support System). The source code is available on the attached CD-ROM in

Microsoft Word format (sourcecode.doc). The screen dumps of the ‘main DSS frame’ and ‘picture of conservation

structures frame’ are shown in Figures 2 and 3, respectively.

OPERATING THE DSS

The DSS consists of four different forms (window frames) linked sequentially and presented in the executable

file WSDSS.EXE file. The ‘welcome’ screen presents a few photographs of watershed management with

different themes. The definitions of terms form displays the basic definitions of the terms used in the DSS. The

main DSS frame form consists of both the input and output boxes, allowing the user to input the information of

the study watershed and the suggested conservation measures are displayed as output of the DSS in the decision

boxes for structural and vegetative measures. From the standpoint of application of conservation measures, it is

established that the higher LCCs such as VIII, VII, VI and V do not support much vegetation, are steeper, and

exhibit higher sediments losses than flat lands. However, high sediment outflow is also observed from less steep

lands having LCCs of I, II, III and IV. For such cases, the DSS also takes into account the sediment outflow rate

in suggesting land-use changes. For example, with a 2 per cent slope, sediment loss of 54 Mg ha�1 yr�1, soil

Figure 2. Main DSS frame with a sample data and displayed decisions.



group ‘A’ and LCC ‘II’, clicking on the suggested-land-use button, the message ‘Thesedimentlossisexcessivefor flat lands, if so, agricultural cropwith crop rotationand detention structuresare recommended’ appears on

the text box of DSS. Again pressing the structural-measures button the message’ ‘Pipe spillways, water har-vestingstructures, earthenridgesandbunds, semi-circularhoops, contour furrows, multi-slot divisors, diver-sion structures, graded bunds and narrow grassed waterways’ appear on the decision text box (Figure 3).

The Main DSS frame window also displays a slope conversion calculator (Figure 3), which converts slope in

degrees to percentage, as the DSS slope input is in percentage. When the user inputs the slope in degrees and

clicks the convert button, the slope in percentage in displayed in the text box. The DSS main frame also displays

a ‘pictures of conservation measure’ button. Clicking the ‘pictures of conservation measures’ command button

opens a new window frame with two scroll-down combo image boxes listing the name of different conservation

measures and picture frames to display the images of measures selected by the user. However, the frame does not

contain the pictures of all the conservation measures, which can be obtained by running the DSS for different

parameter values. It does contain 50 pictures of the conservation measures adopted in different countries. For

example, an image of the DSS frame showing a concrete chute spillway as a structural measure and a Canadian

sugar maple woodland as a vegetative measure is shown in Figure 4. The user can move to the main DSS frame

by clicking on the ‘back’ button and try other input information of the watershed. The user can move to the

definition frame to have a basic understanding of the terms used in the DSS. The DSS is developed with the aim

of storing the available information useful for IWM and retrieving the same when instructed by the user. This

would include input parameters of soil type, slope, LCC and measured sediment loss. In cases where the

Figure 3. The DSS window frame displaying the picture of conservation measures.



Figure 4. Location map of St Lucia watershed (Cox, 1997).



sediment loss is low (less than 10 Mg ha�1 yr�1) and slope is very high (greater than 50 per cent) and LCC is I or

II, the suggested land use test box displays ‘Thedataenteredmaynot berealistic,Lowsloperangeswithhighersediment loss or vice versa and also high slope and high sediment loss values at LCC I, II, III and IV with bettersoil typeandviceversa’. This statement makes sense in relation to plausible land-capability class, slope range,

sediment yield and soil-type combinations. This message handles extreme conditions, which are not realistic for

most of the real field situations. It is well established that the LCCs I, II and III are productive classes, with mild

slope, ideal for growing crops and yielding less sediment load if runoff passes over such lands. In special cases,

there may be sediment loss but not very high, i.e. in the range of 50–60 Mg ha�1 yr�1. The DSS incorporates

established information on structural and vegetative measures adopted in different agroclimatic regions, so a

conventional validation of the DSS is unnecessary. However, the flow logic or decision rules applied for

suggestive measure needs to be tested on different watershed slopes and conservation measures in order to make

the DSS more versatile and capable of displaying alternative decisions on extreme soil loss, different slope and

soil-type combinations. Thus, to further investigate the validity of measures proposed by the DSS, it was

validated using information from a watershed in St Lucia.

Application of the DSS to the Eastern Caribbean Region

The developed DSS was validated for a watershed in St Lucia, located in the Windward Islands of the Caribbean.

The vegetative and structural conservation measures implemented in the Marquis watershed of St Lucia are

considered in the present study (Figure 4). This is a hilly watershed with 32 per cent of the watershed area having a

slope between 0�–10� (0 to 17�6 per cent), 25 per cent of the land area having a slope between 10�–20� (17�6 to

36�4 per cent), 30 per cent of the land surface having slopes between 20�–30� (36�4 per cent to 57�7 per cent) and

rest of the land area (13 per cent) having a slope greater than 30� (57�7 per cent) (Cox, 1997; Pretall and Polius,

1981). Over the entire island, annual mean rainfall ranges from 1500 to 3800 mm, mean daytime temperature from

26–32 �C, and the mean relative humidity is 75 per cent. The soil loss estimated for this watershed ranged from 10

to 100 Mg ha�1 yr�1 in the lower parts of the watershed to over 1000 Mg ha�1 yr�1 in the steep upper reaches,

under mixed intensive farming (Cox, 1997). The average soil loss across the watershed was estimated to be

309 Mg ha�1 yr�1. The soil loss was reduced to 157 Mg ha�1 yr�1 by implementation of the conservation practices

and land-vegetation-cover measures. The recommended practices were in line with the measures suggested by the

DSS. As an example, using the land information of the watershed, such as slopes greater than 30�, soil type less

stable or ‘B’ and LCC V, sediment loss of 309 Mg ha�1 yr�1, clicking the command button for structural measures

yielded ‘Afforestation, detention ditches along contour, short length flumes, isolated or staggered terraces onsteep slopes’and the suggestive vegetative measures was ‘Afforestation, silvi-pasture, woodland and recrea-tional planning’. The screen dump of the main frame of the DSS is presented in Figure 5. It is observed from

the land use of the watershed that for high slope ranges, the conservation practices adopted are ‘agroforestry and

forestry’ (Cox, 1997), and these are in close agreement with the predictions of the DSS. The other measures

proposed were also implemented in the region and resulted in less sediment outflow in subsequent years. For input

data of 10� slope, LCC II, sediment loss of 100 Mg ha�1 yr�1 and soil type A (stable soil), the measures suggested

were ‘Bench terraces, graded contour bunds, conservation ditches, concrete chute spillways, diversion dams,stone wall contours’ as structural measures and ‘Agriculture with contour bunds and terraces along with treecrops’ as vegetative measures (Figure 6). The present land use of the Marquis watershed for slope of 10� and

given soil types are ‘Intensive agriculture’ (Cox, 1997). This is also in close agreement with the DSS-suggested

measures for the lower slope region of the watershed and its specific soil-capability classes. As the DSS proposes,

for a given range of slope, soil types, LCCs and sediment losses, all possible structural and vegetative measures

collected over a wide range of agroecological regions, not all measures suggested by the DSS (Figures 5 and 6)

could be implemented in the St Lucia watershed. Implementing the suggested measures for slope ranges from 5–

55� of Marquis subwatershed resulted in reductions in soil loss of 34 per cent to 37 per cent, respectively (Table

III). However, the DSS can also be tested for watersheds at different locations to ensure its versatility. The VB

programming code can easily be modified to accommodate further information on structural and conservation

measures.



SUMMARY AND CONCLUSIONS

The prime objective of this work has been to develop a DSS on watershed conservation measures incorporating the

established information on implementation of structural and vegetative control measures based on slope, soil type,

LCC and sediment-loss data. Conceptual decision flow logic was formulated to link these information through the

VB programming language. The DSS was developed with graphic user interface (GUI) capability. This provides

the user with an interactive environment to enter input information of slope, soil type, LCC and sediment loss, and

then to obtain structural and vegetative control measures in response to those input values. These suggested

measures displayed in decision boxes vary according to the input values as per the decision-flow logic used in DSS

development. The user selects the soil and water conservation measures to be implemented in the watershed.

Moreover, the availability of pictures of different conservation measures in a separate user form, but linked with

the main DSS window transmits a sense of visual familiarity to the user on different conservation measures

adopted at diversified watershed locations. Validation of the DSS for the St Lucia watershed revealed that the

measures suggested for different slope, soil type and LCC combinations were in close accord with the measures

actually implemented in the watershed. These implemented conservation measures reduced soil loss for the study

watersheds.

The DSS is flexible to further modification in terms of inclusion of additional data and pictorials on conservation

measures. This is possible due to the VB programming language, which is easily amenable to subsequent

modifications. The incorporation of more data will expand the decision-making ability of the DSS for application

to watersheds under different agroecological regions. The DSS will be useful not only for watershed managers and

researchers but also for course instructors to disseminate watershed-management concepts in the classroom.

Figure 5. The main DSS frame displaying the suggested measures of St Lucia watershed.



The developed DSS can be linked to conceptual and empirical sediment prediction models. Moreover, using the

built-in macro language of GIS software, this DSS can be linked with any GIS as an interface to generate

conservation measures for both watersheds and farmers’ fields. The DSS is flexible in its linkage to other

hydrological models as a decision-making tool for prediction of soil and water conservation measures and it is

unique in terms of generating decisions with minimum input information for a watershed.

Figure 6. The main DSS frame displaying the suggested measures of St Lucia watershed.

Table III. Comparison of soil loss rates with and without conservation practices for Marquis sub watershed of St. Lucia(Revised Universal Soil Loss Formulae (RUSLE) is used for estimation of soil loss rate) (Cox, 1997)

Slope range Range of sediment loss rates without Range of sediment loss rates with suggested Reduction of soil(degrees) conservation practices (t ha�1 yr�1) conservation practices (t ha�1 yr�1) loss in (%)

0–5 5�36–41�21 4�84–27�24 9�70–33�905–10 41�21–77�06 27�24–49�64 33�90–35�58

10–15 77�06–112�91 49�64–72�04 35�58–36�2015–20 112�91–148�76 72�04–94�44 36�20–36�5220–25 148�76–184�61 94�44–116�84 36�52–36�7125–30 184�61–220�46 116�84–139�24 36�71–36�8430–35 220�46–256�31 139�24–161�64 36�84–36�9435–40 256�31–292�16 161�64–184�04 36�94 –37�0140–45 292�16–328�01 184�04–206�44 37�01–37�0645–50 328�01–363�86 206�44–228�84 37�06–37�1150–55 363�86–399�71 228�84–251�24 37�11–37�1455þ 399�71þ 251�24þ 37�14þ



references

Ahmed N. 1989. A Treatment Oriented Land Classification for St Lucia. Technical Report. Dept. of Soil Science, University of West Indies, StAugustine, Trinidad, West Indies; 20–63.

Beynon M, Rasmequan S, Russ S. 2002. A new paradigm for computer-based decision support. Decision Support Systems 33: 127–142.Bishr YA, Radwan MM. 1995. Preliminary design of a decision support system for watershed management. ITC Journal 1: 23–28.Cogo NP, Moldenhauer WC, Foster GR. 1984. Soil loss reduction from conservation tillage practices. Soil Science Society of America Journal48: 368–373.

Cox CA. 1997. Watershed master planning for St Lucia using geographic information system, MSc Thesis, McGill University, Montreal,Canada; 14–18 & 53–96.

Cox CA. 2002. Geographic information systems-based hydrology modelling applications in support of watershed management planning for StLucia. PhD Thesis, McGill University, Montreal, Canada; 23–45 & 123–150.

Datta S. 1995. A Decision Support System (DSS) for micro-watershed management in India. Journal of Operational Research Society 46: 592–603.

George BA, Reddy BRS, Raghuwanshi NS, Wallender WW. 2002. Decision support system for estimating reference evapotranspiration.Journal Irrigation Drainage Engineering Division 128(1): 1–10.

Hall GF, Logan TJ, Young KK. 1985. Criteria for determining tolerable erosion rates. In Soil Erosion and Crop Productivity, Follett RF, StewartBA (eds). ASA, CSSA, SSSA Inc., Publishers Madison: Wisconsin, USA; 173–188.

Hudson N. 1995. Soil Conservation, 3rd edn. Batsford: London, 391 pp.Hurni H, Cook MG, Sombatpanit S. 1996. Soil conservation extension—A world perspective. In Soil Conservation Extension from Concepts toAdoption. Sombatpanit S, Zobisch MA, Sanders DW, Cook MG (eds). Science Publishers: Enfield, USA; 3–18.

Kerr J, Chung K. 2001. Evaluating watershed management projects. Water Policy 3: 537–554.Kersten GE, Mikolajuk Z, Yeh AG. 2000. Decision Support System for Sustainable Development. A Resource Book on Methods andApplications. Kluwer Academic Publishers: Norwell, Massachusetts, USA; 29–51.

Montas H, Madramootoo CA. 1992. A decision support system (DSS) for soil conservation planning. Computers and Electronics in Agriculture7(1): 187–202.

Morgan RPC. 1986. Soil Erosion and Conservation. Longman Scientific and Technical Group Ltd: Hongkong; 111–210.National Research Council. 1991. Towards Sustainability: Soil and Water Research Priorities for Developing Countries. National Academy

Press: Washington, DC; 22–23.Pertiwi S, Konaka T, Koike M. 1998. Decision support system for management of upland farming with special consideration on soil

conservation. In Proceeding of First Conference on Agricultural Information Technology in Asia and Oceania—24th to 26th January. TheAsian Federation for Information Technology in Agriculture: Wakayama-City, Japan; 73–78.

Pimentel D, Allen J, Beers A, Guinand L, Hawkins A, Linder R, McLaughlin P, Meer B, Musonda D, Perdue D, Poisson S, Salazar R, Siebert S,Stoner K. 1993. Soil erosion and agricultural productivity. In World Soil Erosion and Conservation, Pimentel D (ed.). Cambridge UniversityPress: Cambridge, UK; 277–292.

Pretall O, Polius J. 1981. Land resources in St Lucia: land capability classification and crop allocation. In St Lucia Development Atlas,Department of Regional Development, Organization of American States, Washington DC, USA, 29 pp.

Schwab GO, Fangmeier DD, Elliot WJ, Fervert RK. 1993. Soil and Water Conservation Engineering, 4th edn. Wiley: New York, USA; 1–17 &91–242.

Srinivasan R, Engel BA. 1991. Effect of slope prediction methods on slope and erosion estimates. Applied Engineering and Agriculture 7(6):779–783.

Stark J, Lajoie P, Green AJ. 1966. Soil and Land Use Surveys, No. 20, St Lucia, University of West Indies: St Augustine, Trinidad, West Indies;20–45.

Troeh FR, Hobbs JA, Donahue RL. 1999. Soil and Water Conservation Productivity and Environmental Protection, 3rd edn. Prentice Hall: NJ,USA; 115–125.

internet references

1. Sediment Production and Yield http://www.glc.org/projects/sediment/causes.html

2. Sediment and erosion resources http://www.earthit.com/services/erosion.html

3. A research article in GIS development http://www.gisdevelopment.net/application/nrm/water/watershed/

watws0003pf.htm

4. Conversion of degree and percentage slopes (slope formulae) http://www.cae.wisc.edu/�cee655/final/

finalformula.html

5. The picture of Conservation Structures http://www.photogallery.nrcs.usda.gov/Index.asp

6. Pictures of soil and water conservation practices http://www.fao.org/docrep/T0321E/t0321e-10.htm#

P1119_78691



Documents

A DECISION SUPPORT SYSTEM FOR SOIL AND WATER CONSERVATION … · water conservation structures widely adopted by farming communities throughout the world. The DSS is capable of providing