Economic Valuation of Riverside Wetland Services in the Lower Moshi Irrigation Scheme

7/28/2019 Economic Valuation of Riverside Wetland Services in the Lower Moshi Irrigation Scheme

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Economic Valuation of Riverside Wetland Services

in the Lower Moshi Irrigation Scheme

Abstract: We attempted to estimate the economic value of riverside wetland services in the

Lower Moshi Irrigation Scheme in Tanzania. The Rau river water is the source of water for

irrigation in the Lower Moshi irrigation Scheme. The Scheme is found in the Moshi Rural

District in Kilimanjaro region about 20km from Moshi town. Over abstraction for irrigation

water from the river, caused degradation of the riverside wetland. The conservation of

riverside wetlands in the Rau river will provided by healthy riverside vegetation, fish and

wildlife habitats, water purification, soil erosion control and recreation. The objective of this

study was to estimate non marketed value of riverside wetland service provided by

conservation of riverside wetland services in the Rau River in the LMIS in which contingent

valuation survey in 105 households in the lower Moshi irrigation Scheme were administered.

Respondents were given a current and hypothetical scenario and asked a willingness-to-pay

(WTP) question regarding purchasing water for conservation of riverside wetland services

through higher irrigation water fees. Results from 105 household interviewed indicated that

households would pay an average of Tshs 27 860 per Ha per annum. WTP was found related

to key variables suggested by economic theory and contingent valuation studies elsewhere:

income, educational level, number of children in the household and initial bid amount. These

results will allow decision makers to compare the benefits generated by different water uses,

including riverside wetland services, and to manage scarce water resources under a long-

term sustainable approach.

Keywords: Contingent Valuation Method; Riverside Services; Willingness-to-Pay

Abiud January Bongole

School of Business Studies and Economics,University of Dodoma

P. O Box 395, Dodoma, Tanzania

ISSN 2319-9725


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March, 2013 www.ijirs.com Vol 2 Issue 3

International Journal of Innovative Research and Studies Page 50

1. Background:This article addresses the economic value of various services provided by conservation of the

Rau river wetland in the Lower Moshi irrigation Scheme. The study used the Contingent

Valuation Method (CVM) to elicit the willingness to pay for the services provided by the

riverside wetland in the Rau river in the Lower Moshi Irrigation Scheme (LMIS). Ecosystem

products do have an economic value and can represent an important source of income for

rural and urban communities (Speelman, 2008). Riverside wetlands, for example, exhibit

large diversity in size and shape, are complex and dynamic ecosystems that protect rivers by

storing nutrients and reducing sediment loads. Considerable progress needs to be made in the

science and art of river side wetlands development planning and management to conciliate

production and conservation objectives (Kosz, 1994).

An increasing scarcity of water supply relative to demand has resulted into resource

competition, insufficiency water to support riverside wetland ecosystems, recreational

amenity and disputes among multiple users. Due to the increase of water resources

competition, the livelihoods of the poor and other vulnerable groups like women and children

are highly insecure (Kadigi et al., 2006).

According to a number of studies, water scarcity in the Lower Moshi Irrigation Scheme has

resulted into a severe deficit in water available for irrigation and conservation of riverside

wetland services. As a result, water demands are not being met. Decreased instream flow of

water in the Rau river causes poor conservation of the functions and services provided by

riverside wetlands while the competition for water between upstream and downstream

farmers has been increased (Turpie et al., 2003).

This in turn requires a good understanding of the value of riverside wetland services and the

implications of water management for conservation of riverside wetland services (Johnson

and Baltodano, 2004). In other words, decision makers and other stakeholders need to be

precisely informed of the economic value of riverside wetland services if efficient

management and allocation of water resources are to be achieved (Kadigi et al., 2006).

The quantification of the value of irrigation water and riverside wetland services is a

relatively new area of research, particularly in developing countries. Although studies by

Kadigi et al., (2006), Tupie et al., (2003) and Maganga (2001) among others have gone to

lengths to estimate the economic value of irrigation water using Residual Imputation Method,


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much less attention has been paid in to measuring the economic value of ecosystem services

in complex natural systems such as rivers using Contingent Valuation Method.

This study estimated the non marketed value of riverside wetland services provided by

conservation of riverside wetland services in the Rau River in the LMIS. The results of this

study will allow decision makers to compare the benefits generated by different water uses,

including riverside wetland services, and to manage scarce water resources under a long-term

sustainable approach.

2. Literature Review:2.1 Economic Valuation of Wetland Services:

According to Loomis (1987) and Brander and Jane (2006) dollar values for in-stream flows

can often compare favorably against the value of water in traditional economically beneficial

uses such as irrigation. While still relatively limited in number, attempts by ecological and

environmental economists and other researchers to assess the monetary value of protecting

in-stream flow and associated riparian areas to sustain several environmental services are

increasing.

There are several techniques that can be used to value the benefits of improved ecosystem

services. The Non-market valuation approaches can be divided into two categories: revealed

preference and stated preference methods.

2.2 Revealed Preference Methods

Revealed preference methods, also known as indirect valuation methods, look for related or

surrogate markets in which the environmental good is implicitly traded (Birol and Phoebe,

2006; Garrod, 1999). Information derived from observed behaviour in the surrogate markets

is used to estimate willingness to pay (WTP), which represents an individual's valuation of,

or the benefits derived from, the environmental resource. Two such methods prevalent in the

environmental economics literature are the hedonic pricing and the travel cost methods.

These methods are suitable for valuing those water resources that are marketed indirectly and

are thus only able to estimate their use (direct and indirect) values (Ojeda e t al., 2008; Chiueh

and Ming, 2008).

The revealed preference methods include the Travel Costs, Replacement Cost, AvertiveExpenditures, Production Function Approach, Net Factor Income, Cost-of-Illness (COI), and


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Market prices. The description of several revealed preference approaches, advantages, and

disadvantages as well as their use for valuing water, are discussed in detailed by Birol and

Phoebe(2006).

2.3 Stated Preference Methods

According to Birol and Phoebe(2006), Stated Preference Methods (SPM) also called Direct

Valuation Methods, have been developed to solve the problem of valuing environmental

resources that are not traded in any market, including the surrogate. In addition to their ability

to estimate use values of environmental goods, the most important feature of these survey-

based methods is that they can estimate the nonuse values, enabling the estimation of each

component of TEV.

Stated preference methods, such as Conjoint, Choice Experiments, and Contingent Valuation,

attempt to solve the problem of non-use valuation of water by capturing benefits that may be

neglected by the other methods. These methods are commonly used to estimate the non-use

value of the environment by directly surveying consumers on their willingness to pay (WTP)

for existing or potential environmental attributes in a hypothetical, constructed market. The

most commonly used form of questioning on hypothetical futures is the CVM (Chiare and

Peter 2008; de Oca and Bateman, 2006). According to Biroland Phoebe(2006) and Ojeda etal. (2008) the advantage of CVM is that, it does not require the conceptual linkage between

market prices and a non-market resource, since the researcher elicits information on the value

of the amenity directly by using a questionnaire or interview to create a hypothetical market

or referendum in which individuals reveal the values they place on the resource.

2.4 Empirical Examples Of Resource Valuation

There are a range of studies that have examined the economic value of natural resources

using the contingent valuation methods. The empirical results from the studies are somewhat

mixed. Griffin and Mjelde (2000), for example, examined customers preferences in seven

Texan cities, using CVM. Loomis (1987) found that, when instream flow rates were 30% of

peak flows in several rivers in the western United States. The values of in-stream flow are at

least as much as the value of water for use in irrigation. However, just imposing a minimum

flow constraint also has its problems because it imposes a fixed relative allocation of

resources between in-stream and out-of-stream uses. A recent study by Travisi and Nijikamp

(2008), on economic assessment of the non-market benefits of safety improvements in the


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environmental and health safety of agricultural production revealed that, the annual WTP of

an Italian household ranges from 874 to protect all the 15 endangered bird species; 1 465

to eliminate soil and groundwater contamination in farmland areas (currently set at 65%); to

1 286 to eliminate all the cases of acute pesticide intoxication.

Ojeda et al. (2008) used CVM in a study on the economic value of environmental services

provided by in-stream flows of water in the Yaqui River Delta in Mexico. In the study,

respondents indicated that they were willing to pay an average of 73 Pesos/month to restore

in-stream flows in the water-scarce Yaqui River Delta. Shins and Kims (2005), study on the

economic valuation of environmentally friendly agriculture for improving environmental

quality, found that environmentally friendly agriculture improved the quality of the

environment quality with respect to the conservation of water and soil, species and ecosystem

diversity in addition to stimulating agriculture.

2.5 Contingent Valuation Method:

There are cases in which it is not possible to derive value measures from observing individual

choices through a market. Ojeda et al. (2008), call the methods developed to measure

environmental values in such cases hypothetical methods. In such an approach, respondents

are offered a hypothetical market in which they are asked to express WTP for existing orpotential environmental conditions not registered in any real market.

The most common form of questioning on hypothetical futures is called the contingent

valuation method (CVM). It involves asking individuals directly, what they would be willing

to pay for particular goods or services contingenton some hypothetical change in the future

state of the world. The monetary values obtained thereafter, are said to be contingent upon

the nature of the constructed market and the commodity described in the survey scenario

(Shyamsundar and Kramer, 1996).

According to Lankford and Franks (2000), many analysts have applied the CVM to water-

related issues. However, a limitation on ascertaining the marginal value of water may occur,

because the questions asked do not relate to incrementalchanges in water supply or quality,

but to the value of the site or policy itself. However, Young (2005) argued that, questions

regarding different amounts of water for fishing, boating or streamside recreation, illustrated

with photographs of alternative situations, have elicited useful estimates of the marginal

value of stream flow.


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The CVM has great flexibility, allowing valuation of a wider variety of non-market goods

and services than is possible with any of the indirecttechniques. It is currently the available

method for estimating non-use values, in other words it is the only method that has any hope

of measuring existence values, that is, the value that individuals place on a scarce natural

resource by simply knowing that it exists in an improved state (Han and Zhao 2007).

According to Ojeda et al. (2008) for natural resources, contingent valuation studies generally

derive values through the elicitation of respondents WTP to prevent damage to, or to restore,

natural resources.

In CVMs, random or stratified samples of individuals selected from the general population

are given information about a particular problem, and are presented with a hypothetical

occurrence such as a disaster and a policy action that ensures against the disaster. They are

then asked how much they would be willing to pay, for instance, in extra utility taxes, income

taxes, or access fees either to avoid a negative occurrence or bring about a positive one

(Griffin and Mjelde,2000). The actual format may take the form of a direct question (how

much), or it may be a bidding procedure (a ranking of alternatives) or a referendum (ye s/no)

votes. Economists generally prefer the referendum method of obtaining values, since it is one

most people are familiar with (Windevoxhel, 1993).

The resulting data are then analyzed statistically and extrapolated to the population that the

sample represents. These studies are conducted as face-to-face interviews, telephone

interviews or mail surveys. The face-to-face interviews are the most expensive survey

administration format, but it is considered as the best, especially if visual material needs to be

presented. However, non-response bias is always a concern in all sampling frames, because

on average, people who do not respond have different values compared to those people that

respond (Moran and Dann, 2008).

3. Methodology:3.1 Data Collection:

The study was conducted in Lower Moshi irrigation Scheme which covers Chekereni, Oria,

Mabogoni and villages where primary data were collected. The objective of this study was to

estimate non marketed value of riverside wetland service provided by conservation of

riverside wetland services in the Rau River in the LMIS in which contingent valuation survey

in 105 households in the lower Moshi irrigation Scheme were administered. Respondents


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were given a current and hypothetical scenario and asked a willingness-to-pay (WTP)

question regarding purchasing water for conservation of riverside wetland services through

higher irrigation water fees. A sampling unit for this study was a household which was

randomly selected in all villages with 5 percent as the sampling intensity for households in

each village. A random sample should represent 5 percent of the total population as a

representative of that population (Bailey, 1994). A total of 105 households were interviewed

where both qualitative and quantitative data were collected. Secondary data such water

consumption and price of irrigation water in paddy and maize production were obtained from

Lower Moshi Irrigation Scheme office and Kilimanjaro Agricultural Training Center

(KATC).


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Figure 1: Map of Kilimanjaro Region showing Lower Moshi Irrigation Scheme


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3.2 Determination of Environmental Services (Riverside Wetland Services):

The important activity was to undertake a CVM to identify the functions or services used to

describe the environmental outcomes. Based on this methodology, different riverside wetland

services used in conservation of the Rau River were identified; such as the prevention and

control of soil erosion, natural purification of water, and habitat for fish, amphibians, birds

and other wildlife. This was done through focus group meetings/ discussions.

3.3 Description of Payment Vehicle:

Selection of the right payment vehicle depends on the resource to be valued, the socio-

economic characteristics of the sample, and the institutional structure governing the area

(Chiueh and Ming, 2008). In this study, fund contribution was used as the payment vehicle to

the riverside wetlands services conservation in the Rau River as proposed by Ojeda e t al.

(2008) and de Oca and Bateman (2006) in their respective CVM studies in Mexico City and

Loomis (2000) in a CVM study in California.

3.4 Survey Structure:

The format for the survey was based on previous CVM questionnaires conducted around the

world, such as those by Loomis et al. (2000) and de Oca and Bateman (2006). This is in

terms of the introductory questions, background information, proposals, alternatives, visual

aids and WTP questions. In addition, the respondents were presented with the following

information (shown in appendix 1) to frame the hypothetical market and set the CVM

scenario, in the form of photographs. The respondents were first handed a card that listed the

key riverside wetland services such as prevention and control of soil erosion, natural

purification of water, and habitat for fish, amphibians, birds and other wildlife. The survey

questions are listed in appendix 1. In addition, the respondents were presented with thefollowing information to frame the hypothetical market:

a) Background of Rau River: The descriptions on agricultural activity, summary of someof the environmentally sensitive issues and ecosystem health losses that the Rau River

is facing due to the lack of water in the River were presented.

b) Riverside wetland services used in conserving the Rau River: The information on thekey riverside wetland services that could be provided by the Rau River riverside

wetland was presented.


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c) Scenario description: The overall riverside wetland services under the currentconditions and with increased riverside wetland services used to conserve the

existence of the Rau River wetland were explained.

d) Payment vehicle: The interviewer explained that improvement of the Rau Riverriverside wetland would require the provision of funds for environmental management

and the funds would be obtained by increasing the irrigation water fee per Ha per

irrigation season.

3.5 Questionnaire Design and Administration:

The primary data for this study were collected from January 2008 to March 2009 using a

structured questionnaire. Information collected was willingness to pay to conserve riverside

wetland services, as dependent variable, while the independent variables were income, age,

Household size, bid amount and sex.

Secondary data were obtained from KATC and KADP in the Lower Moshi. The pre-testing

of questionnaire was done in the study area in December 2008 before final data collection.

Necessary tasks such as translating the questionnaire from English to Kiswahili were done

before the actual data collection.

3.6 Data Analysis:

Quantitative and qualitative techniques were used to analyze the data. For more precise

analysis, computer based statistical programs (Microsoft EXCEL, LIMDEP 8.0 and SPSS 12)

were used. Descriptive statistics, charts and tables were used to present the results. Different

analytical tools were used to estimate willingness to pay for conservation of riverside wetland

services.

3.7 Estimation of the Economic Value of Riverside Wetland Services:

The CVM was used to elicit information on household willingness to pay for the conservation

of riverside wetland services. Two different sets of household WTP information were used as

dependent variables in the analyses, that is, the yes/no answers to the first annual bid offered

in the Dichotomous choice format question and the follow-up question which allowed the

respondents to give an open-ended maximum WTP answer. The bid amount X was assigned


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randomly to the respondents and came from a set of possible values in the range of 20,000 to

50,000Tshs per annum in increments of 5,000Tshs.

A logit model was applied to fit the yes/no answers to the first water fee offered in the

Dichotomous choice format question data.

655443322110 Y

(1)

Where Y=

YesP

YesPLog

1

and are the probabilities that a respondent accepts or rejects the payment of

a certain bid respectively.

is the intercept term and 654321 ,,,,, are the variable coefficients.

Bid is the bid amount. The expected sign of the coefficient is (-), as respondents are bound

to reject a payment as it gets higher.

Gender is a nominal variable. There are no priori indications for its expected sign

(Raggkos and Asimakis,2006).

The expected sign of the coefficient of variable Age is (+),

HH- Household size

3.8 Factors That Determine The Willingness To Pay For Riverside Wetland

Services:

The factors that determine the WTP were analysed using ordinary least square (OLS)regression to test the robustness of the model, which has been commonly applied in other

similar studies (Ojeda et al., 2008). To simplify the regression analysis, the socio-

demographic and attitude variables were subjected to tests to determine whether the mean

responses for a given independent variable were statistically different.

6655443322110 WTP (2)

Where;

YesP YesP1

0


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WTP- Willingness to pay

is the intercept term and 654321 ,,,,, are the variable coefficients.

Bid is the bid amount. The expected sign of the coefficient is (-), as respondents are boundto reject a payment as it gets higher.

Gender is a nominal variable. There are no priori indications for its expected sign

(Raggkos and Asimakis, 2006).

The expected sign of the coefficient of variable Age is (+).

HH- Household size

The mean WTP from the dichotomous choice results was calculated using the formula:

(3)

Where

- is the total number of responses

- is the bid level

- is the number of yes responses to that bid level

4. Results:4.1 Economic Value of Riverside Wetland Services:

The economic value of riverside wetland services was elicited through dichotomous

questions on the willingness to pay for the conservation of the riverside wetlands services.

4.1.1 Dichotomous Choice Results:

Table 1 shows the distribution of initial bids and the corresponding answers from the

respondents.

0

i

N

i

iYXN1

1

N

iX

iY


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Bid level in

Tshs

Number of

Respondents per

given bid level

Number of respondents

agreeing to bid level

Number of respondents

not agreeing to bid level

20 000 15 15 0

25 000 21 20 1

30 000 20 18 2

35 000 14 13 1

40 000 18 15 3

45 000 10 5 5

50 000 7 2 5

Total 105 88 17

Table 1: Distribution of initial bids and corresponding answers

Using the formula in Eq. (3), mean WTP was calculated at the mean of the other independentvariables. The resulting annual mean willingness to pay per household to conserve riverside

services in the Rau river was Tshs 27 860 per Ha per annum (equivalent to 19.9 US$ per Ha

per annum)

4.1.2 WTP Distribution:

The distribution of WTP obtained from the follow-up open ended question is shown in Figure

2. The mean WTP for riverside wetland services was Tshs 36,195 per Ha per annum

(equivalent to US$ 25.8 per Ha per annum). The mean WTP from the open-ended question is

significantly higher than the mean WTP calculated from the dichotomous choice question.

This is because, on average, most respondents who accepted the initial bids indicated a WTP

that was significantly higher than the initial bid when asked for their maximum WTP, while

respondents who did not accept the initial bid chose a slightly lower WTP than the initial bid.

The WTP distribution shown in figure 2 appears to be normally distributed which means that

the sample comes from a normally distributed population of observations.


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Figure 2: Distribution of willingness to pay

4.1.3 Statistical Analysis

Results from the t-test and the one-way ANOVA test indicated that the t and F statistics,

respectively, were greater than the statistical critical values (at least at the 0.05 significancelevel) for six variables: bid amount, income, sex, age, education and household size. This

implies that, the mean WTP is not equal across different groups for the variables and

confirms that they have a significant influence on WTP.

Table 2 below shows the estimated coefficients and their associated t- statistics for logit

model and linear regression model as shown in equations 1 and 2. In addition, the sign

expected for each coefficient is also indicated in the Table.

0

2

4

6

8

10

12

14

16

18

20000 24111 28222 32333 36444 40555 44666 48777 52888 More

Willingness To Pay (WTP)

Frequency


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Linear regression model Logit regression Model

Expected sign

of coefficient

Estimated

coefficient t-Statistic

Estimated

coefficient t-Statistic

Constant 4.61 4.908 66.463 1.7

Bid amount - 0.293 3.909 -14.005 2.82

Income + 0.19 6.191 5.295 3.11

Information + -0.017 -0.361 0.996 0.78

Sex -0.038 -0.949 0.212 0.2

Age + 0.037 0.404 0.454 0.13

Education + 0.028 0.449 2.273 0.97

Household + -0.002 -0.044 -1.364 1.89

Adjusted R 38.3 43.3

Table 2: Logit and Linear regression models results

The linear and logit regression analyses gave roughly similar results in terms of the number

of significant determinants and the corresponding levels of significance associated with the

estimated coefficients. The four significant determinants for the WTP bids were found to be

the initial bid amount, number of years of formal education, Size of households and

household annual income. On the one hand, as expected, the coefficient associated with the

initial bid amount had a positive sign for the linear model, indicating that the higher theamount of money (in Tshs) the respondent was asked to pay initially, the higher the

respondent's final WTP. On the other hand, the coefficient associated with the initial bid for

the logit model was negative, indicating that respondents were more likely to give a negative

answer as the initial bid increased.

The WTP also increased with income and household educational level. Finally, it was found

out that the WTP also decreased with the number of household size, which is different from

the result found in most WTP studies (Ragkos and Asimakis, 2006).


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The adjusted R2 of the linear and logit models were 0.41 and 0.43, respectively, which,

according to Mitchell and Carson (1989), are more reliable. The linear model fit is slightly

inferior to the logit model fit, but the relative similarity between these two types of models

indicates that the WTP-determinant relationships found here are robust.

5. Conclusion And Recommendations:In view of the major findings of the study, the following are the conclusions made. Access to

irrigation water and suitable wetland for wet and dry season irrigated agriculture constitute

one of the most important determinants of livelihood in the Lower Moshi Irrigation Scheme.

Cultivation of crops such as paddy, sunflower and maize (as are the main crops under

irrigation in the area), require easy access to water and at the same time, protection ofriverside wetland which assist in the purification of polluted water (to access quality water for

irrigation), control erosion and hence high yield for the cultivated crops.

Decreasing water supplies in the Lower Moshi Irrigation Scheme and poor water inflows in

the Rau River especially during the dry seasons, affect negatively the existence of important

services conserved by Riverside wetlands. Thus it can be concluded that, current water use

practices in the Lower Moshi Irrigation Scheme are unsustainable since there is high

allocation of water for agricultural activities, thus leaving aside other important sectors such

as riverside wetlands which also need water to conserve their services.

Since farmers are willing to pay for the conservation of riverside wetlands, the government

should establish riverside services conservation projects where farmers will participate

through contributions for the water they use for irrigation for the purpose of the riverside

services conservation.

Funds collected should be used for conservation activities they should not misused, since thiswill discourage farmers from contributing to the project. The initial amount that the farmers

would contribute should be reasonable, so that every farmer would be able to pay as higher

amounts could lead to a low willingness to pay as found in the study.


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Acknowledgements:

The preparation of this work has been possible through the grace of our almighty GOD. We

are grateful to the Kyela District Council, Tanzania, Department of Agriculture and Livestock

Development for providing financial support for this study. This is gratefully acknowledged.

We are also thankful to all people who participated in the data collection in the study area.

Finally we are indebted to Water Use Association members, households, key informants,

KATC management and Water Authorities for providing the required information and data

for this study.


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Economic Valuation of Riverside Wetland Services in the Lower Moshi Irrigation Scheme