Multi-Objective Optimization for Analysis of Changing Trade-Offs in the Nepalese Water–Energy–Food Nexus with Hydropower Development

Abstract

Abstract:While the water-energy-food nexus approach is becoming increasingly important for more efficient resource utilization and economic development, limited quantitative tools are available to incorporate the approach in decision-making. We propose a spatially explicit framework that couples two well-established water and power system models to develop a decision support tool combining multiple nexus objectives in a linear objective function. To demonstrate our framework, we compare eight Nepalese power development scenarios based on five nexus objectives: minimization of power deficit, maintenance of water availability for irrigation to support food self-sufficiency, reduction in flood risk, maintenance of environmental flows, and maximization of power export. The deterministic multi-objective optimization model is spatially resolved to enable realistic representation of the nexus linkages and accounts for power transmission constraints using an optimal power flow approach. Basin inflows, hydropower plant specifications, reservoir characteristics, reservoir rules, irrigation water demand, environmental flow requirements, power demand, and transmission line properties are provided as model inputs. The trade-offs and synergies among these objectives were visualized for each scenario under multiple environmental flow and power demand requirements. Spatially disaggregated model outputs allowed for the comparison of scenarios not only based on fulfillment of nexus objectives but also scenario compatibility with existing infrastructure, supporting the identification of projects that enhance overall system efficiency. Though the model is applied to the Nepalese nexus from a power development perspective here, it can be extended and adapted for other problems.

Achieving water security in Nepal through unravelling the water-energy-agriculture nexus

“…Using the nexus concept in water security means unravelling the whole to reveal specific linkages between the sectors that affect water security, identifying challenges that have their source in sectors beyond simple water issues, and using these as a basis for developing specific recommendations for action. The nexus can be used to explore the interlinkages between the uses of water in different sectors (Rakhmatullaev, Abdullaev, & Kazbekov, 2017) and problems with ensuring water availability for different uses, such as hydropower and food production (Dhaubanjar, Davidsen, & Bauer-Gottwein, 2017;Rasul, 2014). Looking at water security from a nexus perspective can help us understand the wider implications and broaden the scope of interventions to include such things as water demand management, investment frameworks for public funding for improved surface irrigation, groundwater management, irrigation technologies and agricultural practices, as well as food procurement and trade policies (FAO, 2014).…”

Multi-Criteria Decision-Making Methods to Address Water Allocation Problems: A Systematic Review

“…Furthermore, different types of mathematical models are implemented to solve water use management problems, e.g., a multi-stage fuzzy stochastic programming (MFSP) is applied by Li C et al [93] to solve complex water resource management problems in the northwest of China. Goal programming is applied by Li Yet al [94] on the South-to-North Water Diversion Project in China; LP [95] is employed to analyze the trade-offs in the water-energy-food nexus in Nepal and compound cloud model (CCM) to solve a water allocation problem in Nanjing [96]. In addition, a hybrid of TLFWM (mathematical model) and STLFCWM (mathematical model) is applied by Li M et al [97] to allocate the limited water resources to different water users in the Northwest of China.…”

A Bibliometric Analysis of Food-Energy-Water Nexus Literature

“…Early papers in this literature called for the need to better understand the complex interactions among these resource systems in order to "to co-balance the costs of tradeoffs and identify the synergies" [8] (p. 618). Numerous studies sought to understand synergies and trade-offs using simulation models, system dynamics models, case studies and other tools [42][43][44][45][46][47][48][49][50][51]. The frameworks used within this theme were, for the most part, based on disciplinary perspectives such as chemical engineering, chemistry [52], and process system engineering [53].…”