Using a water balance model to analyze the implications of potential irrigation development in the Upper Blue Nile Basin

Thesis (S.M. in Technology and Policy)-- Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 120-130).More than 200 rivers in the world cross at least one political border. Any development project including hydropower or irrigation that is implemented in a trans-boundary river is in essence a claim on the resource. Managing a trans-boundary resource will require coupling not only of the physical aspect, but also the economics and political state of the region. The goal in this thesis is to study one case of a trans-boundary river: the Nile. The Nile is shared by 10 countries, but the case study will focus on the three countries that constitute the Eastern Nile region: Egypt, Sudan, and Ethiopia. In particular, the paper focuses on Ethiopia's irrigation potential in the Upper Blue Nile basin (UBN) and seeks to understand the physical constraints, the maximum water use, and the downstream hydrological and political impacts of developing irrigation. The approach taken is to construct a physically based optimization model in the General Algebraic Modeling System (GAMS) to determine the upper bound of water withdrawal possible by Ethiopia, paying particular attention to seasonal variability. The results show that both land and climate constraints impose significant limitations on agricultural production in the UBN. Only 25% of the land area is considered arable and suitable for irrigation due to the soil, slope and temperature conditions. When precipitation is also considered, on an annual average, only 11% of current land area could be used in a way that increases water consumption. The results suggest that Ethiopia could consume an additional 3.75 billion cubic meters (bcm) of water per year, through changes in land use and storage capacity, representing a 70 percent increase over existing water use. By exploiting this irrigation potential, Ethiopia could potentially decrease the annual flow downstream of the UBN by 8 percent.by Anjuli Jain Figueroa.S.M.in Technology and Polic

Estimation of evaporation over the upper Blue Nile basin by combining observations from satellites and river flow gauges

Reliable estimates of regional evapotranspiration are necessary to improve water resources management and planning. However, direct measurements of evaporation are expensive and difficult to obtain. Some of the difficulties are illustrated in a comparison of several satellite-based estimates of evapotranspiration for the Upper Blue Nile (UBN) basin in Ethiopia. These estimates disagree both temporally and spatially. All the available data products underestimate evapotranspiration leading to basin-scale mass balance errors on the order of 35 percent of the mean annual rainfall. This paper presents a methodology that combines satellite observations of rainfall, terrestrial water storage as well as river-flow gauge measurements to estimate actual evapotranspiration over the UBN basin. The estimates derived from these inputs are constrained using a one-layer soil water balance and routing model. Our results describe physically consistent long-term spatial and temporal distributions of key hydrologic variables, including rainfall, evapotranspiration, and river-flow. We estimate an annual evapotranspiration over the UBN basin of about 2.55 mm per day. Spatial and temporal evapotranspiration trends are revealed by dividing the basin into smaller subbasins. The methodology described here is applicable to other basins with limited observational coverage that are facing similar future challenges of water scarcity and climate change

Sustainable agricultural management : a systems approach for examining food security tradeoffs

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2019Cataloged from PDF version of thesis.Includes bibliographical references (pages 118-125).Estimates suggest that the world needs a 50% increase in food production to meet the demands of the 2050 global population (Tilman et. al. 2011). Cropland expansion is unlikely to be sufficient, and yield improvements that require more inputs may lead to more environmental damage. This work focuses on reallocating limited land and water resources to optimize cropping patterns. By combining optimization methods, surrogate modeling, global data sources, data assimilation, and hydrologic modeling, we identify opportunities for increasing food-crop production and cash-crop revenue, while maintaining sustainability constraints that limit cropland expansion and prevent groundwater depletion. We apply the framework in India's Krishna river basin and find that reallocating resources to meet or exceed current production can lead to 96% gain in net revenue as resources over an estimated current baseline. Resources in this case are moved to high-yielding cash crops. Imposing a self-sufficient southern diet which depends on rice reduces the gains to 77% while imposing a self-sufficient national diet with more emphasis on wheat eliminates all net revenue gains to the region. The approach described in this thesis, highlights the trade-offs between food production, cost and environmental impacts in achieving specified food-security objectives. This research contributes to the field in two ways: 1) it provides a novel method for combining remotely sensed data, surrogate models and optimization to understand agricultural trade-offs, and 2) it furthers the discussion on food and water security and sustainable resource management by demonstrating that resource reallocation with sustainability constraints provides revenue gains in certain situations.by Anjuli Jain Figueroa.Ph. D.Ph.D. Massachusetts Institute of Technology, Department of Civil and Environmental Engineerin

Water-food-energy challenges in India: political economy of the sugar industry

Sugar is the second largest agro-based industry in India and has a major influence on the country’s water, food, and energy security. In this paper, we use a nexus approach to assess India’s interconnected water-food-energy challenges, with a specific focus on the political economy of the sugar industry in Maharashtra, one of the country’s largest sugar producing states. Our work underscores three points. First, the governmental support of the sugar industry is likely to persist because policymakers are intricately tied to that industry. Entrenched political interests have continued policies that incentivize sugar production. As surplus sugar has been produced, the government introduced additional policies to reduce this excess and thereby protect the sugar industry. Second, although the sugar economy is important to India, sugar policies have had detrimental effects on both water and nutrition. Long-standing government support for sugarcane pricing and sales has expanded water-intensive sugarcane irrigation in low-rainfall areas in Maharashtra, which has reduced the state’s freshwater resources and restricted irrigation of more nutritious crops. Despite its poor nutritional value, empty-calorie sugar has been subsidized through the public distribution system. Third, the Indian government is now promoting sugarcane-based ethanol production. This policy has the benefit of providing greater energy security and creating a new demand for surplus sugar in the Indian market. Our analysis shows that a national biofuel policy promoting the production of ethanol from sugarcane juice versus directly from molasses may help reduce subsidized sugar for human consumption without necessarily expanding water and land use for additional production of sugarcane

Optimizing equity in energy policy interventions: A quantitative decision-support framework for energy justice

This paper presents a quantitative framework to support policy decision-making around equitable energy interventions. By combining sociodemographic and techno-economic models in the energy space, we propose a linear programming model to calculate the optimal portfolio of energy investments that explicitly minimizes the energy burden of a given population of energy insecure households. The model is formulated as a multi-objective optimization suitable to support the decisions on weatherization and deployment of distributed energy resources. We illustrate our methodology with a case study involving a population of 14,043 energy insecure households in Wayne County, Detroit, United States

Mapping Sugarcane in Central India with Smartphone Crowdsourcing

In India, the second-largest sugarcane producing country in the world, accurate mapping of sugarcane land is a key to designing targeted agricultural policies. Such a map is not available, however, as it is challenging to reliably identify sugarcane areas using remote sensing due to sugarcane’s phenological characteristics, coupled with a range of cultivation periods for different varieties. To produce a modern sugarcane map for the Bhima Basin in central India, we utilized crowdsourced data and applied supervised machine learning (neural network) and unsupervised classification methods individually and in combination. We highlight four points. First, smartphone crowdsourced data can be used as an alternative ground truth for sugarcane mapping but requires careful correction of potential errors. Second, although the supervised machine learning method performs best for sugarcane mapping, the combined use of both classification methods improves sugarcane mapping precision at the cost of worsening sugarcane recall and missing some actual sugarcane area. Third, machine learning image classification using high-resolution satellite imagery showed significant potential for sugarcane mapping. Fourth, our best estimate of the sugarcane area in the Bhima Basin is twice that shown in government statistics. This study provides useful insights into sugarcane mapping that can improve the approaches taken in other regions

Capturing Stakeholders’ Challenges of the Food–Water–Energy Nexus—A Participatory Approach for Pune and the Bhima Basin, India

Systems models of the Food–Water–Energy (FWE) nexus face a conceptual difficulty: the systematic integration of local stakeholder perspectives into a coherent framework for analysis. We present a novel procedure to co-produce and systematize the real-life complexity of stakeholder knowledge and forge it into a clear-cut set of challenges. These are clustered into the Pressure–State–Response (PSIR) framework, which ultimately guides the development of a conceptual systems model closely attuned to the needs of local stakeholders. We apply this approach to the case of the emerging megacity Pune and the Bhima basin in India. Through stakeholder workshops, involving 75 resource users and experts, we identified 22 individual challenges. They include exogenous pressures, such as climate change and urbanization, and endogenous pressures, such as agricultural groundwater over-abstraction and land use change. These pressures alter the Bhima basin’s system state, characterized by inefficient water and energy supply systems and regional scarcity. The consequent impacts on society encompass the inadequate provision with food, water, and energy and livelihood challenges for farmers in the basin. An evaluation of policy responses within the conceptual systems model shows the complex cause–effect interactions between nexus subsystems. One single response action, such as the promotion of solar farming, can affect multiple challenges. The resulting concise picture of the regional FWE system serves resource users, policymakers, and researchers to evaluate long-term policies within the context of the urban FWE system. While the presented results are specific to the case study, the approach can be transferred to any other FWE nexus system