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Stochastic impact evaluation of an irrigation development intervention in Northern Ethiopia
Abstract
Irrigation plays a significant role in achieving food and nutrition security in dry regions. However, detailed ex- ante appraisals of irrigation development investments are required to efficiently allocate resources and optimize returns on investment. Due to the inherent system complexity and uncertain consequences of irrigation develop- ment interventions coupled with limited data availability, deterministic cost-benefit analysis can be ineffective in guiding formal decision-making. Stochastic Impact Evaluation (SIE) helps to overcome the challenges of evaluat- ing investments in such contexts. In this paper, we applied SIE to assess the viability of an irrigation dam con- struction project in northern Ethiopia. We used expert knowledge elicitation to generate a causal model of the planned intervention's impact pathway, including all identified benefits, costs and risks. Estimates of the input variables were collected from ten subject matter experts. We then applied the SIE tools: Monte Carlo simulation, Partial Least Squares regression, and Value of Information analysis to project prospective impacts of the project and identify critical knowledge gaps. Model results indicate that the proposed irrigation dam project is highly likely to increase the overall benefits and improve food and nutrition status of local farmers. However, the overall value of these benefits is unlikely to exceed the sum of the investment costs and negative externalities involved in the intervention. Simulation results suggest that the planned irrigation dam may improve income, as well as food and nutrition security, but would generate negative environmental effects and high investment costs. The Stochastic Impact Evaluation approach proved effective in this study and is likely to have potential for evaluating other agricultural development interventions that face system complexity, data scarcity and uncertainty.
... The failure and under-performance of irrigation schemes in Ethiopia is mostly related to either problems during design and implementation and/or operation and maintenance. Low level of community participation during project study and design phases (Aberra, 2004;Amede, 2015;Wegerich et al., 2008;Yami, 2013), lack of site specific reliable hydrological data Hagos and Mamo, 2014;Negash et al., 2020), poorly designed infrastructures (Aberra, 2004;Amede, 2015;Chukalla et al., 2013;Embaye et al., 2020;Gebremeskel et al., 2018b;Gurmu et al., 2019), high construction costs (Butterworth et al., 2013;Yigzaw et al., 2019a) and delayed project completion (Annys et al., 2020a;Mulugeta, 2019) are among the major problems during the design and implementation phases of irrigation projects. A top-down approach that excludes local experiences and community needs is commonly practiced during irrigation development. ...
... Regardless of the national water sector policy, partial investment cost recovery and irrigation water pricing systems had not been implemented yet in Ethiopia. The implementation of investment cost recovery system is beyond the financial capacity of smallholder farmers due to the high investment cost (Butterworth et al., 2013;Hagos and Mamo, 2014;Lefore et al., 2019;Yigzaw et al., 2019a) and additional costs resulting from over delay of project construction (Annys et al., 2020a). Implementation of operation and maintenance cost recovery supported with research and extension services is expected to be a possible solution to financial problems of local institutions and/or WUAs. ...
In spite of the investment and efforts made for irrigation development, many irrigation schemes in Ethiopia are performing below design expectations leaving huge areas and many beneficiaries out of irrigation. In this study, a systematic literature review was conducted on management practices, problems and future directions of community managed small-scale irrigation schemes in Ethiopia. Out of 1282 published research reports retrieved from the data bases of Web of Science and Scopus, eventually 83 publications fulfilled the inclusion criteria. Failure and under-performance of irrigation schemes in Ethiopia is reported to mostly relate to problems during design and implementation and/or operation and maintenance. Low level of community participation, lack of site specific reliable hydrological data, poorly designed irrigation infrastructures, high construction cost and delayed project completion are most mentioned problems during the design and implementation phases of irrigation projects. Presence of weak local scheme managing institutions and users’ exclusion in management decisions are among the main problems of small-scale irrigation management practices in Ethiopia. Regardless of their water sources, irrigation schemes face similar problems in Ethiopia. Adoption of a holistic development and management strategy that integrates technical, socio-economic and environmental aspects is needed to overcome problems and sustainability challenges of community managed irrigation schemes in Ethiopia. Supporting the irrigation sector via research-based findings and adoption of advanced technologies needs further investments and efforts to narrow challenges of irrigation schemes sustainability gaps.
... We used the SIE framework ( Fig. 2), based on Luedeling and Shepherd (2016) to simulate FLR outcomes. SIE is a mixed methods approach that has been widely used to simulate outcomes under uncertainty and risk for investments in honey value chains (Wafula et al., 2018), water supply (Luedeling et al., 2015), irrigation development (Yigzaw et al., 2019), management of reservoir sedimentation (Lanzanova et al., 2019), and to determine the value of ecosystem services in rangelands (Favretto et al., 2017). In this study, we applied SIE as an iterative five-step process that supports decisions by integrating evidence and expert opinion in quantitative simulations of decision impact pathways (Fig. 2). ...
... Sequence of activities in the Stochastic Impact Evaluation approach (adapted fromYigzaw et al., 2019). ...
Forest and Landscape Restoration (FLR) is carried out with the objective of regaining ecological functions and enhancing human well-being through intervention in degrading ecosystems. However, uncertainties and risks related to FLR make it difficult to predict long-term outcomes and inform investment plans. We applied a Stochastic Impact Evaluation framework (SIE) to simulate returns on investment in the case of FLR interventions in a degraded dry Afromontane forest while accounting for uncertainties. We ran 10,000 iterations of a Monte Carlo simulation that projected FLR outcomes over a period of 25 years. Our simulations show that investments in assisted natural regeneration, enrichment planting, exclosure establishment and soil-water conservation structures all have a greater than 77% chance of positive returns. Sensitivity analysis of these outcomes indicated that the greatest threat to positive cashflows is the time required to achieve the targeted ecological outcomes. Value of Information (VOI) analysis indicated that the biggest priority for further measurement in this case is the maturity age of exclosures at which maximum biomass accumulation is achieved. The SIE framework was effective in providing forecasts of the distribution of outcomes and highlighting critical uncertainties where further measurements can help support decision-making. This approach can be useful for informing the management and planning of similar FLR interventions.
... Smallholder research conducted in LMICs has reported a range of challenges for smallholder agriculture. Key among these are difficulty accessing land and equipment, limited access to markets with fair and consistent prices, financial constraints and lack of access to credit, climate impacts including water scarcity and infestations of invasive species (see for example Abokyi et al., 2020;Bahta and Myeki, 2022;Castellanos-Navarrete et al., 2021;Cechin et al., 2021;CFS, 2015;Chatrchyan et al., 2018;Donatti et al., 2019;FAO, 2016;Fuchigami et al., 2021;Gwebu and Matthews, 2018;HLPE, 2013;Jamal et al., 2022;Karakara et al., 2021;Li et al., 2018;Macfarlan and Remiker, 2018;Musalia et al., 2010;Mwamakamba et al., 2017;Ncube, 2018;Negash et al., 2021;Nyabako et al., 2020;Phiri et al., 2019;Silberg et al., 2021;Sims and Kienzle, 2015;Sorgho et al., 2020;Tsujimoto et al., 2019;Uduji et al., 2021;Wangu, 2021;Yigzaw et al., 2019). There have also been studies describing government policies and initiatives supporting smallholder agriculture in LMICs, for example, programs to promote the uptake of particular crop or livestock species, smallholder training and education programs, grants and subsidies, institutional procurement policies, tailored financial services solutions and information and decision tools (see for example Abokyi et al., 2020;Arvidsson et al., 2022;Castellanos-Navarrete et al., 2021;Clarkson et al., 2022;Fuchigami et al., 2021;Iddrisu et al., 2018;Karakara et al., 2021;Kephe et al., 2021;LaFevor et al., 2021;Madsen et al., 2021). ...
... e. El protocolo de entrenamiento está basado en resultados de investigaciones relacionadas con el sesgo cognitivo que han mostrado su efecto en la mejora de la capacidad de eliminar el sesgo por exceso de confianza (Hubbard & Millar, 2014;Luedeling et al., , 2015Yigzaw et al., 2019). Las distribuciones de probabilidad subjetiva resultante representan explícitamente la incertidumbre como probabilidades de eventos o estados de la naturaleza (los estados del tomador de decisiones) (Anderson et al., 1977). ...
Introducción / objetivo: Hoy en día, la sociedad requiere de los sistemas agrícolas no solo el aprovisionamiento de bienes sino también la prestación de servicios ambientales y sociales. Esta transformación es un desafío complejo ya que requiere implementar acciones en un sistema de muchas variables, y bajo condiciones de riesgo e incertidumbre que no garantizan los beneficios de las acciones. Este artículo de perspectiva describe la aplicación del Análisis de Decisiones (AD) en tales escenarios de decisión de los sistemas agrícolas.
Metodología: Este trabajo presenta un protocolo general para la implementación de AD, y desarrolla una perspectiva espacio-temporal para la aplicación de AD en los sistemas agrícolas usando conceptos extraídos de las áreas de Teoría de Decisiones y planificación estratégica, e introduce un estudio de caso para mostrar cómo esta perspectiva puede ser introducida en los sistemas de innovación del sector agrícola.
Resultados: Los problemas de los sistemas agrícolas pueden describirse como una tipología de modelos de decisión usando escalas de planificación estratégica. Esta perspectiva tiene el potencial de permitir la aplicación de AD en los esfuerzos de planificación del Sistema Nacional de Innovación Agropecuaria (SNIA) de Colombia, especialmente en la implementación de los Sistemas Territoriales de Innovación (STI).
Conclusión: Este artículo presenta una perspectiva extendida de AD orientada a proveer una base conceptual para su aplicación en la búsqueda de soluciones en el contexto de complejidad de los sistemas agrícolas, en la planificación de las actividades de ciencia, tecnología, e innovación en el sector agrícola, y para apoyar el proceso transformación hacia la sostenibilidad de los sistemas agrícolas.
... Involving experts through collaborative modeling approaches is crucial for development of credible decision support systems, and it allows accounting for agricultural risks (Oliver et al., 2012). Probabilistic model simulations using collaborative workshops to generate input data based on expert estimates have been applied in several studies to support stakeholders' risk management in production systems around the globe (Do et al., 2020;Rosenstock et al., 2014;Tamba et al., 2017;Wafula et al., 2018;Yigzaw et al., 2019). In horticultural production, similar approaches have been applied to predict the outcome of risk management strategies in sweet cherry production (Rojas et al., 2021). ...
Many farmers hesitate to adopt new management strategies with actual or perceived risks and uncertainties. Especially in ornamental plant production, farmers often stick to current production strategies to avoid the risk of economically harmful plant losses, even though they may recognize the need to optimize farm management. This work focused on the economically important and little-researched production system of ornamental heather (Calluna vulgaris) to help farmers find appropriate measures to sustainably improve resource use, plant quality, and profitability despite existing risks. Probabilistic cost-benefit analysis was applied to simulate alternative disease monitoring strategies. The outcomes for more intensive visual monitoring, as well as sensor-based monitoring using hyperspectral imaging were simulated. Based on the results of the probabilistic cost-benefit analysis, the expected utility of the alternative strategies was assessed as a function of the farmer's level of risk aversion. The analysis of expected utility indicated that heather production is generally risky. Concerning the alternative strategies, more intensive visual monitoring provides the highest utility for farmers for almost all levels of risk aversion compared to all other strategies. Results of the probabilistic cost-benefit analysis indicated that more intensive visual monitoring increases net benefits in 68% of the simulated cases. The application of sensor-based monitoring leads to negative economic outcomes in 85% of the simulated cases. This research approach is widely applicable to predict the impacts of new management strategies in precision agriculture. The methodology can be used to provide farmers in other data-scarce production systems with concrete recommendations that account for uncertainties and risks.
Supplementary information:
The online version contains supplementary material available at 10.1007/s11119-022-09909-z.
... We elicited this information after experts were subjected to calibration training. Training consisted of increasing awareness of concepts of probability and instruction in techniques to produce accurate estimates of confidence intervals for unknown variables, which reflect the estimator's level of uncertainty (Hubbard and Millar, 2014;Hubbard, 2010;Hubbard Decision Research, 2015;Luedeling et al., 2015;Yigzaw et al., 2019). The resulting subjective probability distributions represent uncertainty explicitly as probabilities of events or states of nature (the states of the decision maker's world) (Anderson et al., 1977). ...
CONTEXT
Even though diversification of horticultural production systems allows farmers to cope with risks and uncertainties, strategies for raising profitability usually aim to improve the productivity of monocultures rather than pursuing diversification. Horticultural production systems are often highly diversified in terms of land use and planted crops.
OBJECTIVE
Assessing the economic prospects of these complex systems requires quantification of productivity and related risks for individual crops as well as an assessment of the benefits from diversification. Here we demonstrate the implementation of a systematic assessment for irrigated production systems in the Sinú Valley of the Colombian Caribbean.
METHODS
We used participatory modeling approaches, focus group discussions and interviews to collect relevant qualitative and quantitative information from farmers. Quantitative information associated with input variables was elicited as probability distributions. Farmers were trained in estimation techniques, enabling them to provide reliable quantitative assessments of production-related variables.
RESULTS AND CONCLUSIONS
The model and elicited values for input variables were used to build a probabilistic simulation that allowed for estimating the expected income from horticultural crops and identifying portfolio strategies based on currently available horticultural options. The irrigated horticultural production systems of the Sinú Valley in Colombia contain four main crops. All farmers cultivate eggplants and sweet peppers but they have specific preferences for yardlong beans and papaya. These preferences reflect two crop diversification strategies attuned to farmers' resources. Yardlong beans are a short-term (3 months), low-risk, and low-profit investment (a tenth of the best crop option) while papaya is a long-term crop (18 months) of high-risk and profit. Yardlong beans are planted by smallholders with limited financial resources as a way to subsist and produce additional cash that can be invested in riskier more profitable crop options (eggplants and sweet peppers). This strategy describes a transition from a secure option (3 standard deviations (SD)) to riskier options (6 SD or more) that can generate greater profits. The second strategy describes actions of wealthier smallholders that can invest in short-lived perennial crops including papaya, sweet pepper and eggplants. This three-crop portfolio cuts production risks roughly in half (from 10 SD for the riskier option to 5 SD in the portfolio).
SIGNIFICANCE
We expect our decision analysis approach to prove useful in assessing other horticultural systems but also for the assessment and identification of new crop options to be incorporated in diversified systems. Our decision analysis approach can also be used to represent diversification in other whole-farm planning scenarios, e.g. when it comes to rotations of field crops, integrated livestock farms, cut-flower farming or agroforestry systems.
... This enables participant farmers to exercise the crop diversification. Similarly, [34,41] stated that food and nutrition status and the overall benefits of local farmers highly improved through the irrigation dam project. ...
... and the impact of having access to irrigation water on poverty[159,160] and food security[161] without considering the differences in the technical efficiency (TE) of smallholder farmers. The results of these studies have shown that irrigation user farmers produce more, earn a better income, have a relatively better life, and are relatively rich and food-secure than the non-user smallholder farmers. ...
... We elicited quantitative information after experts were subjected to a calibration training procedure. Training consisted of increasing the experts' awareness of concepts of probability and instruction in techniques to produce accurate estimates of confidence intervals for unknown variables that reflect the estimator's level of uncertainty (Hubbard 2014;Hubbard and Millar 2014;Luedeling et al. , 2015Yigzaw et al. 2019). The resulting subjective probability distributions constitute explicit representations of the state of certainty about events or states of nature (the states of the decision maker's world) (Anderson et al. 1977). ...
Decision making in pest management is a challenging task. While pest dynamics are often quite uncertain, such decisions are often based on tenuous assumptions of certainty (economic injury levels and marginal utility approximations). To overcome such assumptions and adequately consider uncertainty, we apply decision analysis to evaluate management strategies used by farmers in the Colombian Caribbean against the boll weevil (BW). We represent the decision to protect the crop using partial budget analysis. This allows us to capture key properties of BW control strategies, while accounting for uncertainty about pest infestation pressure, control effectiveness and cotton yield and price. Our results indicate that proactive pest management is more efficient than reactive control given the current BW infestation pressure. However, farmers may prefer the reactive strategy, since they have experienced seasons with low infestation pressure where no insecticide applications were required. The proactive strategy, in contrast, requires scheduled pesticide applications in all years. Results show that in seasons with high infestation pressure the expected revenues of the reactive strategy tend to decrease, mainly because more spray applications are required when fields are heavily infested by the weevil. Value of information analysis revealed that uncertainties related to the start of the infestation, loss damage rate and attainable yield have the greatest influence on the decision recommendation for crop protection. Narrowing these key knowledge gaps may offer additional clarity on the performance of the current management strategies and provide guidance for the development of strategies to reduce insecticide use. This is particularly important for the promotion of the proactive strategy, which, under the current infestation pressure, has potential to reduce insecticide use. While economic injury levels can only be applied to responsive measures, our approach of partial budget analysis under uncertainty allows us to assess and compare both responsive and preventive measures in the same methodological framework. This framework can be extended to non-pesticide control measures.
... Under erratic rainfall and climate variabilities, irrigation use is recommended by different scholars at different times for its contribution in improving household income (Zewdie, et al., 2019;Zewdie, et al., 2020;Mango, et al., 2018), improving the quality of life of the households (Gebrehiwot, et al., 2017, Zewdie, et al., 2019Zewdie, et al., 2020;), contribution in poverty reduction (Hagos, et al., 2017, Adela, et al., 2019 and improving household food security status (Yigzaw, et al., 2019, Muleta, et al., 2021. Irrigation use is also reported to improve household livelihood by increasing income, food security status, poverty reduction, creating employment opportunities, fulfilling social needs, increasing agricultural production and productivity through diversification of crops grown, serving as a source of animal feed, enhanced health status due to accessibility of balanced diet and easy access to medication, reducing soil degradation, and contributing to household asset ownership (Asayehegn 2012). ...
Agricultural sector in Ethiopia is mainly characterized as traditional, subsistent and rainfed system which is highly susceptible to adverse effects of climate variabilities. Under such conditions, small-scale irrigation is recommended as the most effective way of improving agricultural production, productivity, income, food security and household wellbeing. This study was conducted with the objective of assessing the impact of small-scale irrigation on household income using the primary data collected from 220 households of Walmara district. Descriptive and econometric data analyses were executed. Logistic regression and PSM methods were used to measure the impact. The average treatment effect on the treated (ATT) result revealed that participation in irrigation significantly affected household income, and irrigator households get more gross income of Birr 22,161 than non-irrigators, and this result is statistically significant. Finally, sensitivity analysis was done, and the ATT is insensitive to unobserved bias up to 200%. Therefore, policy interventions focusing on installation of new small-scale irrigation schemes and fully utilization of the existing schemes are recommended for their direct contributions in improving household income, and indirect contribution in improving food security and national GDP, especially in erratic rainfall and drought-prone areas.
... The For many countries, large dams have become an ideal infrastructure for supporting water needs either consumption, irrigation or hydropower (Chen et al., 2016). Moreover, irrigation investment in developed countries is seen to have played role in reducing poverty levels (Nguyen et al., 2017;Yigzaw et al., 2019). As a result, attempts to increase the number of large dams continued in accordance with the rise in national and regional economic growth in many countries (Shi et al., 2019). ...
In addition to solving the problem of water shortage for irrigation, energy and consumption, thepolicy of building large dam is also expected to improve population-welfare. However, previousstudies suggest that people living near dams have less benefit from the existence of large dam. Thisstudy aims to provide empirical evidence the effect of large dam development on welfare tohousehold living in sub-districts around large dam placement using National Socio-EconomicSurvey (SUSENAS) data in 2013-2018 from Central Bureau of Statistics and spatial large dam datain Indonesia. Estimated results indicate that addition large dam tend to be negatively correlated by2.4-3.1 % with household consumption implying a tendency of decreasing welfare in localhouseholds. Estimated findings using Indonesia Family Life Survey (IFLS) in 2007 and 2014 shownegative correlation likely to be caused by lower agricultural productivity and work activity. Thisresult show there are economic agents who suffer from large water - infrastructure especiallyhouseholds living in sub-districts close to the dam.
... However, little attempt has been made to understand the performance of large and small-scale irrigation user farmers as compared to the nonuser farmers in Ethiopia. Previous studies focused on the difference between irrigation user and non-user farmers in income [11][12][13], quality of life [11,12,14] and the impact of having access to irrigation on poverty [15,16] and food security [17] without considering the differences in the technical efficiency (TE) of smallholder farmers. The results of these studies have shown that irrigation user farmers produce more, earn a better income, have a relatively better life, and are relatively rich and food-secure than the non-user smallholder farmers. ...
In the past decade, to improve crop production and productivity, Ethiopia has embarked on an ambitious irrigation farming expansion program and has introduced new large- and small-scale irrigation initiatives. However, in Ethiopia, poverty remains a challenge, and crop productivity per unit area of land is very low. Literature on the technical efficiency (TE) of large-scale and small-scale irrigation user farmers as compared to the non-user farmers in Ethiopia is also limited. Investigating smallholder farmers’ technical efficiency (TE) level and its principal determinants is very important to increase crop production and productivity and to improve smallholder farmers’ livelihood and food security. Using 1026 household-level cross-section data, this study adopts a technology flexible stochastic frontier approach to examine agricultural TE of large-scale irrigation users, small-scale irrigation users and non-user farmers in Ethiopia. The results indicate that, due to poor extension services and old-style agronomic practices, the mean TE of farmers is very low (44.33%), implying that there is a wider room for increasing crop production in the study areas through increasing the TE of smallholder farmers without additional investment in novel agricultural technologies. Results also show that large-scale irrigation user farmers (21.05%) are less technically efficient than small-scale irrigation user farmers (60.29%). However, improving irrigation infrastructure shifts the frontier up and has a positive impact on smallholder farmers’ output.
... Significant increases in crop revenues also have been obtained in case of access to irrigation water (e.g. Koga, Zewdie et al., 2019) although large-scale irrigation development can be costly (Yigzaw et al., 2019) and the amount of supplied water is not always sufficient to irrigate the entire irrigation command area, as is the case for the Koga irrigation scheme (Birhanu et al., 2014). ...
In recent years, a renewed interest in large dams and large-scale irrigation schemes has developed, justified by the premise to make the agricultural and energy sectors climate-resilient. Despite this important climate effort, large dams and interbasin water transfers are controversial and have far-reaching impacts for river-dependent communities and the environments on which they depend. Since the year 2000, international standards on dam construction have been developed, but many dam projects currently still fail to meet environmental and social standards in practice as mitigation measures are not legally binding and a follow-up of impacts of large dams is not mandatory.
Drawing on GIS-analyses of remote sensing images, qualitative and quantitative empirical evidence from the field, this PhD dissertation has focused on the impacts of two large dams (Tekeze and Ribb) and an interbasin water transfer (Tana-Beles) on downstream socio-hydrologic systems, consisting of the strongly interconnected and mutually evolving environmental, agricultural and social sub-systems. The research results have indicated that (i) downstream hydrogeomorphic systems have drastically altered after river regulation and are developing a new hydrogeomorphic equilibrium, (ii) small-scale farmer-led irrigation systems have been more efficient in increasing crop productivities than several large-scale irrigation projects, (iii) the newly induced hydrologic regimes have strongly altered downstream social interactions due to impeded river crossing, and (iv) ill-prepared land redistributions and resettlements have left thousands of households with a high risk of impoverishment. With its extensive hydropower potential and ambitious dam building program, Ethiopia has been the perfect case study for this research.
... For decision models to produce accurate information, they must be parameterized with information that reflects the state of knowledge of the decision-makers (MacMillan and Marshall, 2006), or, if possible, the objective uncertainty about input parameters (Sebok et al., 2016). Such uncertainties can be defined by probability distributions for model parameter values (Yigzaw et al., 2019). These distributions can be developed using expert elicitation approaches (Bolger and Wright, 2017) for generating inputs for probabilistic simulations (Lanzanova et al., 2019), either alone or in combination with available data (Jochmann et al., 2010). ...
Agricultural management decisions are usually made without perfect knowledge. Decision Analysis (DA) approaches translate available uncertain information on costs, benefits and risks involved in decisions into actionable management recommendations. We illustrate the use of DA procedures to inform decisions on disease management strategies in ornamental plant production. We worked with heather growers and other stakeholders in North Rhine-Westphalia, Germany, to model the impacts of changing disease management practices and to generate comprehensive forecasts of net returns. Through sensitivity analysis and Value of Information assessment we identified critical uncertainties regarding the feasibility of improved practices. Partial Farm Budgets for decision options ranged from a loss of more than 200,000 € to a gain of nearly 70,000 € per hectare and year. Findings suggest that reducing pesticide applications without additional monitoring may substantially increase production risks (chance of loss of 76%) and that intensified plant monitoring is likely to increase net benefits (chance of gain of 68%) by allowing earlier detection and more focused fungicide application. Our Decision Analysis approach facilitated ex-ante evaluation of innovative management strategies in heather production, and it holds promise for similar evaluations in other agricultural production systems.
... In order to guide the decision, we also computed the total project outcome (i.e. the sum of NPVs for all stakeholders, the implementer and the environment). Additional information about nutritional outcomes is provided in Yigzaw et al. [1]. ...
This data article provides the datasets that are used in the holistic ex-ante impact evaluation of an irrigation dam construction project in Northern Ethiopia [1]. We used an expert knowledge elicitation approach as a means of acquiring the data. The data shared here captures all the parameters considered important in the impact pathway (i.e. the expected benefits, costs, and risks) of the decision to construct an irrigation dam. The dataset is disaggregated for two impact pathway models: one complementing the dam construction with catchment restoration and the other without catchment restoration. Both models are scripted in the R programming language. The data can be used to examine how the construction of an irrigation dam affects the incomes as well as the food and nutritional status of farmers that are affected by the intervention.
This study evaluated the on‐farm performance of two small‐scale irrigation schemes, Furfuro and Bedene Alemtena (hereafter referred to as Bedene), in the Ethiopian Rift Valley. Two sets of performance indicator parameters were used. The first group was internal performance indicators, which included conveyance, water application and application uniformity. The water flow velocity through canals was monitored using the floating method. The amount of irrigation water applied to the fields was measured using a cutthroat flume. The second group was external performance indicators, including agricultural performance, water use performance and physical sustainability indicators. The results indicated that Furfuro had average conveyance, application and uniformity efficiencies of 84%, 59% and 50%, respectively, while that of Bedene were 79%, 63% and 55%, respectively. The overall efficiencies for both schemes were about 49%, which is lower than the minimum permissible values. The outputs per irrigation supply and consumed water for Furfuro were 0.14 and 0.16 US/m ³ for Bedene. The relative irrigation and total water supply of Furfuro were 1.21 and 1.20, respectively, indicating the presence of excess water in the command area during the study season. The relative irrigation and water supply of Bedene was 0.81, which indicated that the scheme was water deficient. Irrigation water management practices need improvement in the two schemes.
Surface water pollution is a global problem and has been evident for a long period of time. Hence, the aim of the study was to evaluate the hydro-geochemical characteristics of Selamko farm reservoir water quality and its suitability for multipurpose uses using GIS-based water quality indices. The water sampling sites and parameters were selected systematically based on the land use, land cover, and anthropogenic activities around Selamko reservoir watershed in Debre Tabor, Ethiopia. Water samples were collected from 11 sampling stations from July 2019 to March 2020 using the composite sampling method and examined using standard procedures. The suitability of the reservoir's water quality for multipurpose use was investigated using drinking and irrigation water quality indices, and other tools. The spatial distribution maps of water quality parameters were prepared using the kriging method in ArcGIS 10.5. The results of the geospatial analysis indicated that the reservoir water quality parameters had spatial variation, which was caused by industrial and household wastewater inflow across the reservoir's watershed. Based on WHO and ES standards, the computed drinking water quality index results revealed that 81.81% and 18.18% of the reservoir's water quality fall into the poor to very poor classes, which indicates that the water in the reservoir is not fit for drinking. However, a Wilcox diagram, irrigation indices, and USEPA regulations revealed that the reservoir water quality is found to be safe and suitable for irrigation, fishing, and livestock purposes. The study concluded that Selamko reservoir's water quality is suitable for irrigation, fishing, and livestock watering with proper management accordingly.
Available options for mitigating the impacts of extreme weather events on temperate fruit trees involve a number of risks and uncertainties, leaving growers hesitant about the benefits of implementing new technologies to protect their orchards. We used Decision Analysis approaches, which account for these risks and uncertainties, to assess investment decisions in sweet cherry production systems in central Chile. We evaluated the adoption of polyethylene covers for orchards in northern-and southern-central Chile. Gathering expert and key stakeholder knowledge, we identified relevant variables for the adoption decision and developed a causal impact pathway model. We parameterized this model by collecting estimates from experts in the form of probability distributions. We implemented the model as a Monte Carlo simulation and projected probability distributions for the Net Present Value and the annual cash flow. Results highlight that farmers in southern-central Chile could expect major benefits from covering their orchards, with a 90% confidence interval for the Net Present Value from − 33,605 USD to 595,447 USD. In northern-central areas, implementing covers did not significantly improve the Net Present Value (90% confidence interval from − 149,597 USD to 433,361 USD). Across zones, our model results were sensitive to market price, crop yield, and fruit quality problems (i.e. low firmness). Cover effectiveness against rain events was relevant only in the southern-central zone, whereas effectiveness against frost events was relevant in both sites. Expected Value of Perfect Information calculations revealed that additional information on yield and market price could substantially help to make a confident decision. Our simulations suggest that orchard protection in southern-central Chile may be necessary for secure and profitable cherry production in the future. In this case study, we demonstrated the applicability of Decision Analysis to support farmers in identifying appropriate and effective strategies in time to overcome future challenges resulting from climate change.
This data article provides the datasets that are used in the holistic ex-ante impact evaluation of an irrigation dam construction project in Northern Ethiopia [1]. We used an expert knowledge elicitation approach as a means of acquiring the data. The data shared here captures all the parameters considered important in the impact pathway (i.e. the expected benefits, costs, and risks) of the decision to construct an irrigation dam. The dataset is disaggregated for two impact pathway models: one complementing the dam construction with catchment restoration and the other without catchment restoration. Both models are scripted in the R programming language. The data can be used to examine how the construction of an irrigation dam affects the incomes as well as the food and nutritional status of farmers that are affected by the intervention.
Ecosystems services (ES) assessment is a significant scientific topic recognized for its potential to address sustainability issues. However, there is an absence of science-policy frameworks in land use planning that lead to the ES science being used in policy. China's Ecological Redline Policy (ERP) is one of the first national policies utilizing multiple ES, but there is no standardized approach for working across the science-policy interface. We propose a transdisciplinary framework to determine ecological redline areas (ERAs) in Shanghai using: ES, biodiversity and ecologically fragile hotspots, landscape structure, and stakeholder opinions. We determine the five criteria to identify ERAs for Shanghai using multi-temporal, high resolution images (0.5 m) and biophysical models. We examine ERP effectiveness by comparing land use scenarios for 2040. Compared to alternative land uses, ES increase significantly under the ERP. The inclusion of ES in spatial planning led stakeholders to increase terrestrial habitat protection by 174% in Shanghai. Our analysis suggests that strategic planning for ES could reduce tradeoffs between environmental quality and development.
p>Designing and implementing biodiversity-based value chains can be a complex undertaking, especially in places where outcomes are uncertain and risks of project failure and cost overruns are high. We used the Stochastic Impact Evaluation (SIE) approach to guide the Intergovernmental Authority on Development (IGAD) on viable investment options in honey value chains, which the agency considered implementing as an economic incentive for communities along the Kenya-Somalia border to conserve biodiversity. The SIE approach allows for holistic analysis of project cost, benefit, and risk variables, including those with uncertain and missing information. It also identifies areas that pose critical uncertainties in the project. We started by conducting a baseline survey in Witu and Awer in Lamu County, Kenya. The aim of the survey was to establish the current farm income from beekeeping as a baseline, against which the prospective impacts of intervention options could be measured. We then developed an intervention decision model that was populated with all cost, benefit and risk variables relevant to beekeeping. After receiving training in making quantitative estimates, four subject-matter experts expressed their uncertainty about the proposed variables in the model by specifying probability distributions for them. We then used Monte Carlo simulation to project decision outcomes. We also identified variables that projected decision outcomes were most sensitive to, and we determined the value of information for each variable. The variable with the highest information value to the decision-maker in Witu was the honey price. In Awer, no additional information on any of the variables would change the recommendation to invest in honey value chains in the region. The analysis demonstrates a novel and comprehensive approach to decision-making for different stakeholders in a project where decision outcomes are uncertain.
Introduction
Governments around the world have agreed to end hunger and food insecurity and to improve global nutrition, largely through changes to agriculture and food systems. However, they are faced with a lot of uncertainty when making policy decisions, since any agricultural changes will influence social and biophysical systems, which could yield either positive or negative nutrition outcomes. We outline a holistic probability modeling approach with Bayesian Network (BN) models for nutritional impacts resulting from agricultural development policy. The approach includes the elicitation of expert knowledge for impact model development, including sensitivity analysis and value of information calculations. It aims at a generalizable methodology that can be applied in a wide range of contexts. To showcase this approach, we develop an impact model of Vision 2040, Uganda's development strategy, which, among other objectives, seeks to transform the country's agricultural landscape from traditional systems to large-scale commercial agriculture. Model results suggest that Vision 2040 is likely to have negative outcomes for the rural livelihoods it intends to support; it may have no appreciable influence on household hunger but, by influencing preferences for and access to quality nutritional foods, may increase the prevalence of micronutrient deficiency. The results highlight the tradeoffs that must be negotiated when making decisions regarding agriculture for nutrition, and the capacity of BNs to make these tradeoffs explicit. The work illustrates the value of BNs for supporting evidence-based agricultural development decisions.
Despite large increases in national cereal production in recent decades, Ethiopia continues to experience regular acute food insecurity crises, often associated with drought events. However, the meteorology of these events is poorly defined and local populations frequently experience food insecurity crises in years when national rainfall and cereal production totals are high. Therefore, looking at national, or even to some extent sub-national, rainfall variability is a misappropriation of climate as a causal factor in food insecurity in Ethiopia. The distinction between ‘drought’ as catch-all driver of food insecurity and a more nuanced view of the relationship between rainfall variability and food security is necessary both for addressing food insecurity now and for interpreting long-term climate model projections. The on-going recurrence of acute food insecurity is a feature of the heterogeneity of climate and climate variability in Ethiopia, but only in the context of a food system dominated by smallholder farming and climate-sensitive livelihoods. Climate variability has the greatest adverse impact in the most marginal livelihood zones in the drier east of the country. Increasing the resilience of smallholder farmers and pastoralists to climate variability and improvements in early warning and disaster risk response could reduce the frequency and severity of food security crises. However, unless the food system in Ethiopia undergoes transformational adaptation, food insecurity crises will continue to occur, and the opportunity to achieve zero hunger by 2030 will be missed.
Ethiopia has been highly affected by drought and climate-related hazards, and millions of people have been left without sustenance every year. To increase productivity and diversify the livelihood scenarios as an option, small-scale irrigation (SSI) schemes have been introduced.This study assessed the impact of SSI in achieving household livelihood improvement and the major challenges of SSI practices in the Gubalafto district. Questionnaires, interviews, focus group discussions, and participant observation data collection tools were used. Proportionally, a total of 374 respondents were included.The collected data was analyzed by descriptive statistics. The application of SSI improved the annual income of irrigator households from 1978.12 to 10,099 Ethiopian Birr (ETB) (1 USD ≈ 20 ETB) before and after using irrigation with a standard deviation of 1534.32 compared to non-irrigators who have an annual average income of 3146.75 ETB with a standard deviation of 1838, respectively. It proved that 32.1% of irrigators increased their frequency of production due to irrigation. Shortage of water, access to improved seeds, marketing, and increment of farm input costs have been hindering SSI practices. Awareness campaigns for non-irrigators and adequate supervision for the irrigators by development agents (DAs) and district officials are important to improve the livelihood of farmers.
Starting in the 1970s, the Senegalese Government invested in the development of irrigated schemes in the Senegalese part of the Senegal River Valley (S-SRV). From that time to 2012, the irrigated schemes increased from 10,000 to more than 110,000 ha. In the meantime, the economic viability of these schemes started to be questioned. It also appeared that the environmental health and social costs might outweigh the benefits of irrigation. Using a life cycle assessment (LCA) approach and project cost-benefits modeling, this study (i) quantified the costs and benefits of the S-SRV irrigated rice production, (ii) evaluated the costs and benefits of its externalities, and (iii) discussed the irrigated rice support policy. The net financial revenues from the irrigated schemes were positive, but not their economic equivalences. The economic return rate (EER) was below the expected 12% and the net present value (NPV) over 20 years of the project represented a loss of about US-572.1 million. Therefore, the results show that to stop the economic loss and alleviate the human suffering, the S-SRV development policy should be revised using an integrated approach and the exploitation technology should aim at environmental sustainability. This paper may offer useful insights for reviewing the current Senegalese policies for the valley, as well as for assessing other similar cases or future projects worldwide, particularly in critical zones of developing countries.
The realisation of the smart grids and markets vision constitutes a substantial transition of electricity systems affecting multiple stakeholders and creating various technical, social, economic, political, and environmental challenges. These need to be considered adequately in decision support tools for agents in electricity systems. Agent-based modelling and simulation as a flexible and rich modelling framework can serve as a testbed for analysing new paradigms in the field of smart grids, such as demand response, distributed generation, distribution grid modelling, and efficient market integration. While so far wholesale electricity markets have been the focus of agent-based modelling and simulation, this paper provides a detailed review of literature using such techniques for analysing smart grids from a systems perspective. For that purpose, a general classification of applying agent-based modelling and simulation techniques to electricity systems is provided. The literature review of specifically using agent-based modelling and simulation for analysing smart grids shows that, although being still a limited field of research, quite different applications are identified with the number of contributions having increased in recent years. Agent-based modelling and simulation can deliver specific insights in how different agents in a smart grid would interact and which effects would occur on a global level. Thereby, the approach can deliver valuable input for decision processes of stakeholders and policy making. Future research could feature more focused analyses of storage systems, local market concepts, interactions with centralised markets, and the role of intermediaries.
This paper deals with the objective of evaluating and enhancing irrigation water management of Koga large scale irrigation scheme located in the Blue Nile basin of Ethiopia. Disturbed and undisturbed Soil samples were collected from selected irrigation blocks within the irrigation system. Soil moisture, texture, field capacity, permanent wilting point and bulk density data were obtained from laboratory analysis of the samples. Results of demand versus supply analysis of the scheme showed that there was excess supply at the beginning of reservoir release and upto 7.13. MCM of excess flow water was estimated in year 2015. Results also showed that crop water requirement value varied for each block and for different crops in the same block, assuming the climatic conditions of the site constant. The crop water requirement variations were caused by differences in soil water holding capacity of each block. Based on crop water demand analysis result with appropriate crop water provision of 50% efficiency, the maximum irrigable area which could be accommodated by the reservoir storage was 5635.8. ha as compared to the design command of 7000. ha. The paper also investigated the status of reservoir water availability as compared to the demand and annual release. The findings of this research will have greater implications in creating awareness to the water user associations, farmers and gate operators of Koga irrigation scheme on how to measure the amount of water they are using during the whole crop growth so that optimum irrigation water shall be delivered to a crop for maintaining water management.
Gathering data that answer particular questions is the most effective way to support the Sustainable Development Goals, say Keith Shepherd and colleagues.
Decision-making in development rarely considers uncertainty in project benefits and costs and the risk of project failure. Lack of appropriate tools for ex-ante analysis under conditions of data scarcity constrains the ability of decision-makers to anticipate project outcomes. Business analysis techniques can help in such situations, but they have rarely been applied in development contexts. We use the principles of Applied Information Economics to develop a decision model for a water supply intervention. In the proposed Habaswein-Wajir Water Supply Project in Northern Kenya, water is to be extracted from a major aquifer near Habaswein and piped to the city of Wajir. A team of eight experts developed a model including all costs, benefits, and risks considered important for project success. After estimation training, these experts expressed their uncertainty for about 100 variables in the model with probability distributions. We used Monte Carlo simulation to project decision outcomes, and Partial Least Squares (PLS) regression to identify critical uncertainties affecting the decision. The project was found to be risky for most stakeholders, mainly due to the risk of political interference caused by water supply concerns in Habaswein and due to unclear profitability of the water supply business. Uncertainties about how to value decreasing infant mortality and reduction in water-borne disease incidence were also critical. The greatest hydrological risk was salt water intrusion into the aquifer. Careful well design, inclusive project planning and benefit sharing could raise the chance of project success. The analysis improved understanding of the decision by all stakeholders, some of which changed their opinions on the pipeline, requested more measurements, or proposed alternative water supply options. Decision analysis can help clarify decision uncertainties and outcome expectations and thereby improve decision-making processes, especially in data-scarce areas.
At present, variable selection turns to prominence since it obviously alleviate a trouble of measuring multiple variables per sample. The partial least squares regression (PLS-R) and the score of Variable Importance in Projection (VIP) are combined together for variable selection. The value of VIP score which is greater than 1 is the typical rule for selecting relevant variables. Due to a constant cutoff threshold is not sometimes suitable for every data structure, a new cutoff threshold for VIP in classification task has been proposed and then compared to the classical one thru the interesting situation simulation. There were 180 situations generated based on four parameters: Percentage of the number of relevant variables, Magnitude of mean difference of relevant variables between two groups, Degree of correlation between relevant variables, and the sample size. The result of this study presents that the new cutoff threshold can improve in identifying relevant variables more than the previous threshold as seeing of good value of the average balanced accuracy in most of situations.
Water scarcity became a common phenomenon in Ethiopia with drought frequency of at least once in three years while the country owns a large irrigation potential that should be exploited sustainably. Various national and international institutions are currently engaged in developing small scale irrigation (SSI) schemes for poverty alleviation. A monitoring and evaluation exercise was conducted in 2004 and in 2006 in four administrative regions of Ethiopia, namely Tigray, Southern regions, Oromia and Amhara, to assess the benefits and associated environmental effects of SSI investments of the International Fund for Agricultural Development (IFAD). A combination of participatory M&E tools namely, individual interviews, group discussions, key informants, review of relevant documents and field observations were used. The mission was supported by an in depth pre-mission socio-economic survey in three representative irrigation schemes. Data from the sites indicated that 50 % of the respondents had improved food security and higher income, while 26% of the respondents did not see any change on their livelihoods. Crop yield under irrigation was by 35% to 200% higher than under rain fed conditions, with much higher benefit obtained from high potential areas and in farms where external inputs (fertilizer, improved seeds and pesticides) are accessible. The positive effect was more visible with horticultural crops. There has been also a shift towards improved varieties with access to irrigation. Farmers replaced early maturing but low yielding varieties with high yielding varieties. Crop diversification increased significantly, in some sites from three to about 15 species, although this decision making process did not favour legumes. The apparent effect was on crop rotation, intercropping and land management with in the order of 79, 42 and 35%, respectively. On the other hand, there is a decline in number of livestock per household, but an increased number of draught oxen. The decline is associated with reduced grazing area due to conversion of dry season fallow to vegetable fields and an increase in area enclosure in the sloppy landscapes. The shift from cereal to vegetable-dominated cropping increased the competition for water between downstream and upstream users and between resource-rich and poor farmers. The impact of irrigation schemes should be evaluated better on long term benefits than short term fixes, as farmers initiated long term investments like planting perennial fruits, bought calves and other retail trade investments. The communities would benefit most from further integration of livestock into the schemes by adopting feed sourcing strategies for dairy and fattening. The paper also presented best-bets for improved irrigation management in Ethiopia.
Drought is one of the major constraints affecting food security and livelihoods of more than two billion people that reside on dry areas which constitute 41% of the world׳s land surface. Drought is defined as deficiency of precipitation over an extended period of time resulting in water scarcity. Our best minds should be concentrated where the greatest challenges lie today – on discoveries and new solutions to cope with the challenges facing dry areas particularly drought and water scarcity. In addition to facing severe natural resource constraints caused by the lack of water in many of the developing world׳s drylands, we also have to cope with rapid growth of the younger segment of the growing population, and high levels of poverty. Coping with drought and water scarcity are critical to address major development challenges in dry areas namely poverty, hunger, environmental degradation and social conflict.
Drought is a climatic event that cannot be prevented, but interventions and preparedness to drought can help to: (i) be better prepared to cope with drought; (ii) develop more resilient ecosystems (iii) improve resilience to recover from drought; and (iv) mitigate the impacts of droughts. Preparedness strategies to drought include: (a) geographical shifts of agricultural systems; (b) climate-proofing rainfall-based systems; (c) making irrigated systems more efficient; (d) expanding the intermediate rainfed–irrigated systems. The paper presents successful research results and case studies applying some innovative techniques where clear impact is demonstrated to cope with drought and contribute to food security in dry areas. The CGIAR Consortium Research Program (CRP) on “Integrated and Sustainable Agricultural Production Systems for Improved Food Security and Livelihoods in Dry Areas” (in short, “Dryland Systems”), led by ICARDA, was launched in May 2013 with many partners and stakeholders from 40 countries. It addresses farming systems in dry areas, at a global level, involving 80 partner institutions. The Dryland Systems Program aims at coping with drought and water scarcity to enhance food security and reduce poverty in dry areas through an integrated agro-ecosystem approach. It will also deliver science-based solutions that can be adopted in regions that are not yet experiencing extreme shocks, but will be affected in the medium to long-term. The approach entails shifting the thinking away from the traditional focus on a small number of research components to take an integrated approach aiming to address agro-ecosystems challenges. Such an approach involves crops, livestock, rangeland, trees, soils, water and policies. It is one of the first global research for development efforts that brings “systems thinking” to farming innovations leading to improved livelihoods in the developing world. The new technique uses modern innovation platforms to involve all stakeholders, adopting the value chain concept along a research-to-impact pathway for enhanced food security and improved livelihoods in dry areas.
Agriculture and the economies of Sub-Saharan Africa (SSA) are highly sensitive to climatic variability. Drought, in particular, represents one of the most important natural factors contributing to malnutrition and famine in many parts of the region. The overall impact of drought on a given country/region and its ability to recover from the resulting social, economic and environmental impacts depends on several factors. The economic, social and environmental impacts of drought are huge in SSA and the national costs and losses incurred threaten to undermine the wider economic and development gains made in the last few decades in the region. There is an urgent need to reduce the vulnerability of countries to climate variability and to the threats posed by climate change. This paper attempts to highlight the challenges of drought in SSA and reviews the current drought risk management strategies, especially the promising technological and policy options for managing drought risks to protect livelihoods and reduce vulnerability. The review suggests the possibilities of several ex ante and ex post drought management strategies in SSA although their effectiveness depends on agro-climatic and socio-economic conditions. Existing technological, policy and institutional risk management measures need to be strengthened and integrated to manage drought ex ante and to minimize the ex post negative effects for vulnerable households and regions. A proactive approach that combines promising technological, institutional and policy solutions to manage the risks within vulnerable communities implemented by institutions operating at different levels (community, sub-national, and national) is considered to be the way forward for managing drought and climate variability.
I Executive summary
IRRIGATION IN ETHIOPIAN AGRICULTURE
This report argues that water resource management in agriculture is a critical contributor to the economic and social development of Ethiopia. If successful, irrigation in Ethiopia could represent a cornerstone of the agricultural development of the country, contributing up to ETB 140 billion to the economy and potentially moving up to 6 million households into food security.
However, irrigation is not a simple silver bullet: first, it can only work if other components of the agricultural system are also effective (e.g., seeds, extension); second, all the tools in the toolkit will be required – from small-scale irrigation to large-scale schemes – to construct a viable solution. Like many countries before it, Ethiopia will have to develop its own spectrum of solutions to serve the needs of smallholder farmers as well those of broader economic development.
Ethiopia has an important opportunity in water-led development, but it needs to address critical challenges in the planning, design, delivery, and maintenance of its irrigation systems if it is to capture its full potential. This report shows how Ethiopia can chart a practical path of initiatives that will allow it to support the scale-up of its irrigated agricultural sector, the growth of its small holder farmers,
This study is an attempt to quantify the actual and expected contribution of
irrigation to the Ethiopian economy for 2005/06 and 2009/10 cropping
seasons using adjusted net gross margin analysis. After obtaining adjusted
gross margin values for rain-fed and irrigation systems under different
typologies, irrigation’s contribution was calculated to be about 5.7 and
2.5 percent to agricultural and overall GDP during the 2005/06 cropping
season. By the year 2009/2010, irrigation’s contribution to agricultural
and overall GDP is estimated to grow to about 9 and 3.7 percent,
respectively. After relaxing some of the underlying assumptions, the future
contribution of irrigation to agricultural GDP will rise to about 12 percent while the contribution to overall GDP will be about 4 percent. Recommendations for enhancing irrigation’s contribution and policy implications for cost recovery and sustainability of irrigation investment are drawn.
Most of the hydro-economic models used for assessing the environmental impact of agricultural policies are deterministic and can only reflect uncertainties through analyses of scenarios. In this article, we propose a methodology to assess uncertainty using Monte Carlo simulations. Taking three different global change scenarios, we vary economic parameters liable to influence the future of agriculture within each scenario. The simulations are based on farming models developed for two French regions (Midi-Pyrenees and Alsace), using linear programming (LP). These are used to simulate the impacts of a "business as usual", "liberal" and "interventionist" scenario, on water abstraction for irrigation (Neste basin) and on nitrate leaching into groundwater (Alsace). The simulations all predict a drop in farm income in both regions, with a stronger effect in the liberal scenario. Water consumed in the Neste basin increases a little (+0.3 to +3.7% in the interventionist scenario). A slight decrease of agricultural nitrate leaching is observed in Alsace, with nearly no difference between the averages for the three scenarios. Considering all Monte Carlo simulations the nitrate leaching should decrease between -28% and -43%, so uncertainty is not very important from the water planning and management point of view. However, the uncertainty on incomes is greater. A comparison between the Monte Carlo results and those from the deterministic approach demonstrates the value of taking uncertainties into account in foresight modelling exercises: and suggest that Monte Carlo associated to LP is a partial response to classical criticism addressed towards basic LP.
Converting degraded grazing lands into exclosures is one option to restore soil nutrients and to sequester carbon from the atmosphere. We estimate the economic value of such a conversion and assess the perception of local communities concerning exclosures in the highlands of Tigray, Ethiopia. Our research combines a soil and vegetation study with a socio-economic survey, and a financial analysis. Over a period of 30 years, sequestered carbon dioxide was 246 Mg ha−1, total soil nitrogen increased by 7·9 Mg ha−1 and additional available phosphorous stocks amounted to 40 kg ha−1. The Net Present Value of exclosure's ecosystem services under consideration was about 28 per cent (837 US $) higher than alternative wheat production. Carbon revenues alone added up to only about 44 per cent of the net revenues of wheat production. This indicates that (i) carbon market revenues only, would not generate sufficient incentives to establish additional exclosures, and (ii) if all benefits are taken into account and financially rewarded, exclosures are competitive to alternatives land uses. We also identified substantial opportunities to mobilize the local communities in efforts to establish exclosures, given that more than 75 per cent had a positive view on exclosures effectiveness to restore degraded soils and vegetation. We conclude that a comprehensive analysis is necessary to consider the ecological as well as economic and social impacts of exclosures. Our findings are important information for local decision makers and may provide incentives for the establishment of further exclosures in the Northern Highlands of Ethiopia, thereby contributing to a sustainable local development process. Copyright © 2010 John Wiley & Sons, Ltd.
In order to plan strategies for adaptation to climate change, the current effects of climate on economic growth need to be
understood. This study reviews evidence of climate effects on economic growth and presents original analysis of the effect
in Sub-Saharan Africa (SSA). Case studies from the literature demonstrate that historically, climate has had significant and
negative effects on household income, agricultural productivity and economic growth in SSA. This study focuses on the effects
hydroclimatic variability on economic growth in the countries of SSA. We utilize a new national level precipitation statistic
that incorporates spatial and temporal variability within each country. Country level economic growth statistics are analyzed
in panel regressions. Persistent negative precipitation anomalies (drought) are found to be the most significant climate influence
on GDP per capita growth. Temperature and precipitation variability show significant effects in some cases. Results imply
the consideration of hydroclimatic risks, namely drought, may be the priority concern for adaptation to a changing climate
for Sub-Saharan Africa. This conclusion is contrary to the premise of many climate change impact assessments that focus on
temperature increases as the primary concern.
Integrated watershed management (IWSM) was implemented to address issues of poverty and land resource degradation in the 14,500 ha upper Agula watershed, in semi-arid Eastern Tigray (Ethiopia), an area known for poverty and resource degradation caused by natural and man-made calamities. The purpose of this study was to assess the impact of IWSM and determine the land use and cover dynamics that it has induced. The change in land use and cover was assessed by integrating remote sensing and geographic information systems (GIS). Two sets of aerial photographs (taken in 1965 and 1994 at scale of 1:50,000) and Landsat ETM+ image (taken in 2000 with 30 m resolution) were used to produce the land use/land cover map and assess land use change.
The results reveal significant modification and conversion of land use and cover of the watershed over the last four decades (1965-2005). A significant portion of the watershed was continuously under intensively cultivated (tainted) land. The area under irrigation increased from 7 ha to 222.4 ha post-intervention. The area under dense forest increased from 32.4 ha to 98 ha.
The study further shows that IWSM decreased soil erosion. increased soil moisture, reduced sedimentation and run off, set the scene for a number of positive knock-on effects Such as stabilization of gullies and river banks, rehabilitation of degraded lands. IWSM also resulted in increased recharge in the subsurface water.
This study reconfirms the importance of IWSM as a key to improve the land cover of watersheds, as a contribution to poverty alleviation and sustainable livelihood.
The Sultan Marshes in the Develi Basin, Anatolia, one of twelve internationally important wetlands of Turkey, have been severely affected by the construction of an irrigation project in 1988. Intensive use of surface and ground water in irrigation has caused more than a 1 m decline in water levels and has affected the wetlands' ecological characteristics. Previous studies indicate that Sultan Marshes will need more water to restore viable ecological conditions. In this study, we analyze how economic benefits from agriculture and wetlands would be affected if moderate amounts of water were diverted from agriculture back to wetlands in the Develi Basin. By estimating total and marginal costs and benefits associated with water diversions, we determined the optimum or economically-efficient amount of water diversion. When only direct-use values of the wetland (animal grazing, plant harvesting, and ecotourism) were included in the analysis, the optimum amount of water diversion to the wetlands was found to be 5.2 million m3 year− 1 (165 L sec− 1), which compares to about 62 million m3 year− 1 (1,957 L sec− 1) used in irrigation. When wastewater treatment benefits (an indirect-use value) were added, the optimum amount rose to 7 million m3 year− 1. Overall, the analysis showed that water diversion from agriculture to the Sultan Marshes is economically preferable.
Water is critically important to the livelihoods of more than 1 billion people living on less than $1 a day, particularly for the 850 million rural poor primarily engaged in agriculture. In many developing countries, water is a major factor constraining agricultural output, and income of the world's rural poor. Improved agricultural water management can contribute to poverty reduction through several pathways. First, access to reliable water improves production and productivity, enhances employment opportunities and stabilizes income and consumption. Secondly, it encourages the utilization of other yield-enhancing inputs and allows diversification into high-value products, enhances nonfarm outputs and employment, and fulfils multiple needs of households. Third, it may contribute either negatively or positively to nutritional status, health, societal equity and environment. The net impact of agricultural water management interventions on poverty may depend individually and/or synergistically on the working of these pathways. Improved access to water is essential, but not sufficient for sustained poverty reduction. Investments are needed in agricultural science and technology, policies and institutions, economic reform, addressing global agricultural trade inequities, etc. But how best to match the agricultural water management technologies, institutions and policies to the needs of the heterogeneous poor living in diverse agro-ecological settings remains unclear. This article provides a menu of promising pathways through which agricultural water management can contribute to sustained poverty reduction.
Agricultural land and water resources are simultaneously declining due to population growth and economic expansion, which emphasizes the need for optimal allocation of these resources to balance socioeconomic development and water conservation. This study develops a framework for allocation of agricultural land-water resources and risk evaluation under uncertainty. The framework is capable of fully reflecting multiple uncertainties expressed as intervals and probability distributions, considering the connections of agricultural water and land resources. The developed framework will be helpful for managers in gaining insights into the tradeoffs between system benefits and constraint-violation risks, permitting an in-depth analysis of risks of agricultural irrigation water shortage under various violating probabilities. The framework is applied for optimization of agricultural water and land resources in the middle reaches of Heihe River basin. A series of water and land allocation results under different flow levels and violating probabilities were obtained and analyzed in detail through optimally allocating limited water and land resources to different irrigation areas and crops. Comparison with actual conditions shows that both the “net benefit per unit water” and “net benefit per unit land” increase which will demonstrate the feasibility and applicability of the developed framework. In addition, probability distributions of water allocation under various flow levels are generated to help decision makers learn detailed water distribution information and thus help make comprehensive irrigation schemes in the planning horizon under uncertainty. Results of evaluation of agricultural irrigation water shortage risks indicate that the water shortage risks in the middle reaches of Heihe River basin are in the category of acceptable risk level or brink risk level. The developed framework can be valuable for providing a reliable decision aid for optimal water and land resources allocation, and can ensure that the management policies and plans are made with reasonable consideration of both system benefits and risks.
Governments around the world seek to create programs that will support sustainable agriculture and achieve food security, yet they are faced with uncertainty, system complexity and data scarcity when making such choices. We propose decision modeling as an innovative approach to help meet these challenges and offer a case study to show the effectiveness of the tool. We use decision analysis tools to model the possible nutrition-related outcomes of the Ugandan government's long term agricultural development plan termed 'Vision 2040'. The analysis indicates potential shifts in household nutritional contributions through the comparison of the current small-scale diverse systems and the envisioned industrial agricultural systems that may replace them. A Monte Carlo simulation revealed that Vision 2040 plans outperform homegardens in terms of energy and some macronutrients, yet homegardens are likely to be better at producing key vitamins and micronutrients, such as Vitamin A. Value of information calculations applied to Monte Carlo outputs further revealed that gathering more data on the annual yields and nutrient contents of staples, pulses, vegetables, and fruits could improve certainty about the nutrition contribution of both scenarios. We conclude that the development of Uganda's agricultural sector should consider the role that agrobiodiversity in the current small-scale agricultural systems plays in national food and nutrition security. Any changes according to Vision 2040 should also include farmers' voices and current crop management systems as guides for a sustainable food supply in the region. This modeling approach may be a tool for governments to consider agricultural policy implications, especially given the data scarcity and agricultural variability in regions such as East Africa.
The study was conducted in the semi-arid areas of northern Ethiopia with the objective of evaluating the effect of surge flow and alternate irrigation on irrigation performance indicators, water use efficiency and crop yield. The experiment consists of two factors, irrigation systems (alternate furrow (Af) and conventional furrow (CF)) and irrigation flow methods (continuous (C), Surge 1 (S1), Surge 2 (S2), and Surge 3 (S3)). Eight treatment combinations replicated three times were arranged in a factorial randomized complete block design. Onion crop was used as indicator crop for the experiment because of its dominant and cash crop in the region. The result of this experiment indicated that the interaction effect of the irrigation system and irrigation flow methods did not show statistically significant difference on the performance indicators, crop yield and water use efficiency. The irrigation system (Af and CF) as a factor has not significant effect on yield of onion. However, the irrigation flow methods (C, S1, S2 and S3) were significantly affected the irrigation performance indicators (application efficiency, distribution uniformity, deep percolation and tail water runoff losses) and likewise, irrigation water use efficiency and yield of onion were significantly different. Higher crop yield (13208 kg/ha), water use efficiency (1.96–2.55 kg/m³), application efficiency (52.9–58.7%) and distribution uniformity (81.4–86.2%) were obtained from both surge flow and alternate irrigation as compared to continuous flow and conventional furrow irrigation (every furrow water application) which was recorded less 10142 kg/ha, 1.36–1.65 kg/m³, 44–54.7%, 67.1–79.6%, respectively. The result of this study explicitly showed that demonstration of these irrigation methods can enhance the poor water management practices in the semi-arid areas of Ethiopia and elsewhere in the world with limited water resources and similar soil characteristics. The authors of this paper recommend the farmers, irrigation experts, water resources managers and decision makers in the region to apply those techniques for improving water use efficiency.
Water scarcity is a key factor in food security and sustainable livelihood in sub-Saharan Africa, particularly in East Africa. The problem is severe in many parts of Ethiopia where water plays a central
role in the country's economy. To alleviate and curb water scarcity different water harvesting technologies were introduced in Ethiopia during the last two decades; nevertheless their sustainability and
livelihood impacts are not well addressed. For the first time a complete and comprehensive inventory of micro-dam reservoirs (MDRs) in Tigray has been established including the geological background and
currently observed problems. The inventory of 92 MDRs in Tigray was conducted using the direct field observational method, selected interviews and secondary data, to understand the overall situation of the
schemes from engineering geological and geo-hydrological perspectives and its implication to sustainability and water availability. Analysis of the inventory shows that sustainability and livelihood impact of
the water harvesting schemes are threatened by siltation, leakage, insufficient run-off, poor water management and structural damages on the dam body as well as on irrigation infrastructure and spillway.
Basic statistical analysis showed that 61% of them are found to have siltation problems, 53% suffer from leakage, 22% from insufficient inflow, 25% have structural damages and 21% have spillway erosion
problems. Furthermore, nearly 70% of the MDRs are founded on carbonate dominant sedimentary terrain at places with intrusion of dolerite sills/dykes and the problems of siltation and leakage are found to
be extremely high in the MDRs located in such geological setting, as compared to those on crystalline metamorphic rocks. Lack of proper water management was observed in most of the reservoirs with
irrigation practices. Future research and analysis on the causes of the bottlenecked problems and monitoring surveillance are recommended.
Value-of-information (VOI) analysis provides an analytical framework to assess whether obtaining additional evidence is worthwhile to reduce decision uncertainty. The reporting of VOI measures, particularly the expected value of perfect parameter information (EVPPI) and the expected value of sample information (EVSI), is limited because of the computational burden associated with typical two-level Monte-Carlo–based solution. Recently, a nonparametric regression approach was proposed that allows the estimation of multiparameter EVPPI and EVSI directly from a probabilistic sensitivity analysis sample.
Objectives: To demonstrate the value of the nonparametric regression approach in calculating VOI measures in real-world cases and to compare its performance with the standard approach of the Monte-Carlo simulation.
Methods: We used the regression approach to calculate EVPPI and EVSI in two models, and compared the results with the estimates obtained via the standard Monte-Carlo simulation.
Results: The VOI values from the two approaches were very close; computation using the regression method, however, was faster.
Conclusion: The nonparametric regression approach provides an efficient and easy-to-implement alternative for EVPPI and EVSI calculation in economic models.
The water-food-energy Nexus has emerged as a new perspective in debates concerned with balancing potentially conflicting sectoral imperatives of large scale development investments concerned with energy, water or food security. Current frameworks are partial as they largely represent a water-centric perspective. Our hypothesis is that a dynamic Nexus framework that attempts to equally weight sectoral objectives provides a new paradigm for diagnosis and investigation. Dynamic refers here to explicitly understanding (or a diagnosis of) the dynamic relationships and ripple effects whereas static-comparative refers to a comparison of states before and after change. This paper proposes a balanced Nexus framework and presents results from an application to the Mekong basin. The analysis identified the advantages of a sectorally balanced, dynamic Nexus approach, in particular the ability to reveal either the emergence of cross-sectoral connections, or changes in those connections, as a consequence of single sector interventions.
There is interest by governments and private organisations in exploring alternative models of irrigation in parts of northern Australia where there has been little irrigation development to date. One alternative is ‘water harvesting’, which is defined here as the practice of pumping or diverting water during streamflow events and either applying directly to a crop or (more commonly) holding water in off-stream storage on a property for later use. This study presents a detailed farm-scale bio-economic analysis of water harvesting using river system modelling to represent the interactions between farm-scale returns, reliability of extraction and scale of development. In doing so the farm-scale viability of irrigation within a whole of catchment is assessed, and uses the Flinders catchment, a large, semi-arid tropical catchment in northern Australia as a case study. Extraction reliability varied spatially across the catchment and decreased with increasing total catchment extraction. The farm-scale profitability of water harvesting enterprises was found to be particularly sensitive to fluctuations in price, reliability of water extraction, discount rate, cost of storage and timing of crop-failure years. For crops requiring off-site processing, the existence of local processing facilities was a major factor. This study also highlighted that for irrigation developments based on water harvesting there is potential for serious mismatches between the timing of streamflow and time at which planting must occur.
This study compares the application of two variable selection methods in partial least squares regression (PLSR), the variable importance in projection (VIP) method and the selectivity ratio (SR) method. For this purpose, three different data sets were analysed: (a) physiochemical water quality parameters related to sensorial data, (b) gas chromatography–mass spectrometry (GC-MS) chemical (organic compound) profiles from fossil sea sediment samples related to sea surface temperature (SST) changes, and (c) exposed genes of Daphnia magna female samples related to their total offspring production. Correlation coefficients (r), levels of significance (p-value) and interpretation of the underlying experimental phenomena allowed the discussion about the best approach for variable selection in each case. The comparison of the two variable selection methods in the first water quality data set showed that the SR method is more accurate for sensorial prediction. For the climate data set, when raw total ion current (TIC) GC-MS chromatograms were considered, variables selected using the VIP method were easier to interpret compared with those selected by the SR method. However, when only some chromatographic peak areas (concentrations) were considered, the SR method was more efficient for prediction, and the VIP method selected the most relevant variables for the interpretation of SST changes. Finally, for the transcriptomic data set, the SR method was found again to be more reliable for prediction purposes. Copyright © 2015 John Wiley & Sons, Ltd.
The main focus of this article is to explore whether access to selected agricultural water management (AWM) technologies has led to significant reduction in poverty and, if they did so, to identify which technologies had higher impacts. In measuring impact we estimated the average treatment effect for the treated on crop income and measured the differences in consumption expenditures per adult equivalent of those with access and without access using matched data. The estimated average treatment effect was significant and amounted to USD 82 per season. Moreover, there was 24 less poverty incidence among users of AWM technologies compared to nonusers. All technologies were found to have significant poverty reducing impacts with micro dams, deep wells, river diversions, and ponds leading to 37%, 26%, 11%, and 9% reduction in poverty incidence compared to rainfed system. Finally, our study identified the most important correlates of poverty on the basis this we made the policy recommendations to build assets (AWM technologies, livestock, etc); to enhance human resource development and improve the functioning of labor markets for enhanced impact of AWM technologies on poverty.
This paper presents a micro-level simulation study on possible impacts of farm level adaptation strategies using a spatial dynamic hydro-economic model called Mathematical Programming based Multi Agent System. The model was validated for the Northern semi-arid region of Ghana. The simulation results revealed that climate variability has substantial impacts on the poverty and food security status of farm households. Policy interventions like the provision of agricultural credit and expansion of irrigation access are found to be highly important in reducing the adverse effects of climate variability for the capital constrained and poor rainfed farm households. However, to achieve significant changes in food security, a mix of adaptation strategies in the form of credit and irrigation has to be provided simultaneously. We also found that farm level adaption through shifting planting date as well as adopting early maturing crop varieties can substantially reduce the adverse impacts of climate variability.
Development programs have typically neglected uncertainty and variability in terms of outcomes and socio-ecological context when promoting conservation agriculture (CA) throughout sub-Saharan Africa. We developed a simple Monte Carlo-based decision model, calibrated to global data-sets and parameterized to local conditions, to predict the range of yield benefits farmers may obtain when adopting CA in two ongoing agricultural development projects in East Africa. Our general model predicts the yield effects of adopting CA-related practices average −0.60 ± 2.05 (sd) Mg maize ha−1 year−1, indicating a near equal chance of positive and negative impacts on yield. When using site-specific, socio-economic, and biophysical data, mean changes in yield were more negative (−1.29 and −1.34 Mg ha−1 year−1). Moreover, practically the entire distributions of potential yield impacts were negative suggesting CA is highly unlikely to generate yield benefits for farmers in the two locations. Despite comparable aggregate effects at both sites, factors such as land tenure, access to information, and livestock pressure contrast sharply highlighting the need to quantify the range of livelihood and landscape effects when evaluating the suitability of the technology. This analysis illustrates the potential of incorporating uncertainty in rapid assessments of agricultural development interventions. Whereas this study examines project-level decisions on one specific intervention, the approach is equally relevant to address decision-making for multiple interventions, at multiple scales, and for multiple criteria (e.g., across ecosystem services), and thus is an important tool that can support linking knowledge with action.
Reservoir siltation is a serious problem that threatens the productivity and sustainability of water-harvesting schemes. Quantification of sediment deposition in reservoirs and understanding of its major drivers are needed to apply targeted management interventions. Most of the techniques used to estimate sediment deposition in reservoirs require extensive measurements on a frequent time basis, as well as being costly and time-consuming. Thus, a rapid and relatively econom-ical means of assessing the erosion susceptibility of catchments and predicting their sediment yield potential is neces-sary. In this study, expert-based rankings and semi-quantitative factorial scoring approaches were applied to assess the siltation severity of 25 reservoirs in the Tigray region of northern Ethiopia. The results were then correlated with quanti-tative sediment yield estimates acquired for representative sites, and a sediment yield predication model was developed for the region. The calibrated model has an efficiency and relative root mean square error (RRMSE) of 79 and 36%, respectively, which is considered adequate to assess erosion susceptibility and siltation risk of reservoirs in similar envi-ronments. The study demonstrates that expert knowledge and rapid characterization of catchments, in terms of suscepti-bility to erosion, are viable options for assessing siltation risks and for analysing controlling factors at a larger number of sites, with minimum costs and acceptable accuracy.
Smallholder irrigation may considerably contribute to agricultural productivity growth in Sub-Saharan Africa. However, the full potential of expanding smallholder irrigation under alternative irrigation technologies is not known. This paper presents a study to assess the irrigation expansion potential for four smallholder irrigation technologies: motor pumps, treadle pumps, communal river diversion, and small reservoirs. An integrated modeling system that combines GIS data analysis, biophysical and economic predictive modeling, and crop mix optimization techniques was developed for the assessment.
The study revealed a large potential for profitable smallholder irrigation expansion in Sub-Sahara Africa. Area expansion potential is 30 million ha for motor pumps, 24 million ha for treadle pumps, 22 million ha for small reservoirs and 20 million ha for communal river diversions. The technologies can benefit between 113 and 369 million rural people in the region generating net revenues of US $ 14–22 billion/yr, depending on technology. Final expansion potential depends on irrigation technology cost and commodity price developments.
Many biological processes produce only one quantitative outcome per year, resulting from temperatures and precipitation during hundreds of days leading up to the event. Traditional regression approaches incur problems in such a setting, because independent variables are highly autocorrelated and their number often greatly exceeds the number of observations. Partial Least Squares Regression (PLS), a statistical analysis tool developed to handle these situations and widely used in hyperspectral remote sensing, was tested for its usefulness for explaining the climate responses of biological processes, using walnut phenology in California as an example.
This paper is about the cost-benefit analysis of a specific soil and water conservation measures, commonly termed as ‘exclosures’ in the case study area of this research, adopted in the Tigray region of northern Ethiopia. The analysis integrated available data on on-site and off-site effects of the conservation measure. Major benefit and cost items related to this specific measure were identified, quantified, and valued. Direct market prices and variants of indirect environmental valuation techniques (cost based and productivity change methods) were employed in valuing the benefit and cost items included in the analysis. Our results indicate that establishing exclosures in degrading marginal lands generate a large positive net present value (NPV) of ETB 5620ha−1. However, putting productive agricultural land under exclosures yields a negative NPV even under some hypothetical scenarios of 50% rise in prices of forest products and a social discount rate halved from the base rate of 8%. Sensitivity analyses indicate that the net present value is quite volatile to changes in biomass production and the social discount rate. Thus, appropriate forest management schemes have to be adopted in order to maximize sustainable biomass production. Furthermore, factors such as credit constraints that affect local people's time preference should be addressed to induce local people to discount the future at lower rate.
Although irrigation in Africa has the potential to boost agricultural productivities by at least 50%, food production on the continent is almost entirely rainfed. The area equipped for irrigation, currently slightly more than 13 million hectares, makes up just 6% of the total cultivated area. More than 70% of Africa’s poor live in rural areas and mostly depend on agriculture for their livelihoods. As a result, agricultural development is key to ending poverty on the continent. Many development organizations have recently proposed to significantly increase investments in irrigation in the region. However, the potential for irrigation investments in Africa is highly dependent upon geographic, hydrologic, agronomic, and economic factors that need to be taken into account when assessing the long-term viability and sustainability of planned projects. This paper analyzes the large, dam-based and small-scale irrigation investment potential in Africa based on agronomic, hydrologic, and economic factors. We find significant profitable irrigation potential for both small-scale and large-scale systems. This type of regional analysis can guide distribution of investment funds across countries and should be a first step prior to in-depth country- and local-level assessment of irrigation potential, which will be important to agricultural and economic development in Africa.
Promotion of smallholder irrigation is cited as a strategy for enhancing income generation and food security for sub-Saharan Africa’s poor farmers, but what makes this technology a successful poverty alleviation tool? In the short run, the technology should pave the way for increased consumption, asset accumulation, and reduced persistent poverty among users. Over the longer run, it should lead to institutional feedbacks that support sustained economic development and nutritional improvements. Our conceptual model and review of case studies reveal the importance of three sub-components of irrigation technology—access, distribution, and use—and the ways in which the design of the technology itself can either bridge, or succumb to, institutional gaps. These critical features are illustrated in an experimental evaluation of a solar-powered drip irrigation project in rural northern Benin, which provides a controlled study of technology impacts in the Sudano-Sahel. The combined evidence highlights the technical and institutional requirements for project success and points to two important areas of research in the scale-up of any small-scale irrigation strategy: the risk behavior of water users, and the evolution of institutions that either support or obstruct project replication over space and time.
The regional government of Tigray has invested millions of dollars to develop irrigation schemes as a strategy of poverty reduction. However, there has been limited attempt to analyze whether these investments have attained their stated objectives of poverty reduction and overall socio-economic enhancement. Therefore, we endeavor to: (1) evaluate the impacts of access to small-scale irrigation on farm household's income and poverty status, (2) contribute to the scant literature on irrigation and poverty reduction in Ethiopia, and (3) provide information for policy makers. We examine a representative sample of 613 farm households (331 irrigators and 282 non-irrigators) drawn using three-stage stratified sampling with Probability Proportional to Size. We find that the average income of non-irrigating households is less than that of the irrigating households by about 50%. The overall average income gain due to access to irrigation ranges from 4000 Birr to 4500 Birr per household per annum. We find also that farming income is more important to irrigating households than to non-irrigating households, and off-farm income is negatively related with access to irrigation.
We examine the distributional impact of large dams on cropland productivity in Africa. As our unit of analysis we use a hydrology based spatial breakdown of the continent that allows one to exactly define regions in terms of their upstream/downstream relationship at a highly disaggregated level. We then use satellite data to derive measures of cropland productivity within these areas. Our econometric analysis shows that while regions downstream benefit from large dams, no beneficial effects accrue to cropland within the vicinity. Moreover, we find that the productivity enhancing impact of upstream dams is dependent on the local climate. Overall our results suggest that upstream dams have quantitatively on average provided up to 12% of the minimum daily per capita amount of kilocalorie needs in downstream communities and increased agricultural production by 1%.
Water resources are essential to human development processes and to achieve the Millennium Development Goals that seek, inter alia, to eradicate extreme poverty and hunger, achieve universal literacy, and ensure environmental sustainability. Expanding irrigation is essential to increase agricultural production, which is needed to achieve economic development and attain food security in much of sub-Saharan Africa. Water resources and irrigated agriculture are not developed to their full potential. Currently less than 4% of renewable water resources in Africa are withdrawn for agriculture. Barriers include the lack of financial and human resources to build irrigation and related rural infrastructure and acquire agricultural technology, and inadequate access to markets. This constrains progress towards poverty reduction. We examine the linkages between agricultural water, education, markets and rural poverty through a review of published studies. We argue that, linking agricultural water, education, and market interventions, which are so often implemented separately, would generate more effective poverty reduction and hunger eradication programs. Investments in agricultural water management and complementary rural infrastructure and related policies are the pathways to break the poverty trap in smallholder African agriculture.
Investments in agricultural water management should complement or strengthen the livelihood and coping systems of the rural poor, and should thus be instrumental for breaking the poverty trap in Ethiopia. Underdeveloped water resources constrain progress towards poverty reduction. We examine linkages and complementarities between agricultural water, education, markets and rural poverty through an empirical study using household level data from selected villages in southern Ethiopia. We show that investments in irrigation can contribute to poverty reduction, but the poverty reducing impacts of irrigation water are greater when human capital and rural markets are well developed. The size of landholding, access to irrigation water, on-farm land and water conservation practices, literacy of the household head, and years of education of adults are all significant determinants of household welfare, and thus potential pathways for reducing poverty. Expansion of cultivated land, particularly irrigated land, universal literacy, and an extra school year for adults all reduce poverty, but reductions in poverty are greater when irrigation is combined with universal literacy. These findings call for simultaneous investments in agricultural water, education, markets and related policy support measures for reducing poverty in smallholder agriculture in Ethiopia.