Many-objective design of reservoir systems - Applications to the Blue Nile

This work proposes a multi-criteria optimization-based approach for supporting the negotiated design of multireservoir systems. The research addresses the multi-reservoir system design problem (selecting among alternative options, reservoir sizing), the capacity expansion problem (timing the activation of new assets and the filling of new large reservoirs) and management of multi-reservoir systems at various expansion stages. The aim is to balance multiple long and short-term performance objectives of relevance to stakeholders with differing interests. The work also investigates how problem re-formulations can be used to improve computational efficiency at the design and assessment stage and proposes a framework for post-processing of many objective optimization results to facilitate negotiation among multiple stakeholders. The proposed methods are demonstrated using the Blue Nile in a suite of proof-of-concept studies. Results take the form of Pareto-optimal trade-offs where each point on the curve or surface represents the design of water resource systems (i.e., asset choice, size, implementation dates of reservoirs, and operating policy) and coordination strategies (e.g., cost sharing and power trade) where further benefits in one measure necessarily come at the expense of another. Technical chapters aim to offer practical Nile management and/or investment recommendations deriving from the analysis which could be refined in future more detailed studies

Assessing river basin development given water-energy-food-environment interdependencies

Many river basins in the Global South are undergoing rapid development with major implications for the interdependent water-energy-food-environmental (WEFE) ‘nexus’ sectors. A range of views on the extent to which such natural-human systems should be developed typically exist. The perceived best investments in river basins depend on how one frames the planning problem. Therefore, we propose an approach where the best possible (optimised) implementations of different river basin development scenarios are assessed by comparing their WEFE sector trade-offs. We apply the approach to Tanzania’s river basin, an area with multiple WEFE interdependencies and high development potential (irrigation and hydropower) and ecosystem services. Performance indicators are identified through stakeholder consultation and describe WEFE sector response under scenarios of river basin development. Results show considerable potential exists for energy and irrigation expansion. Designs that prioritise energy production adversely affect environmental performance, however, part of the negative impacts can be minimised through release rules designed to replicate the natural variability of flow. The reliability of monthly energy generation is more sensitive to environmental-oriented management than the cumulative annual energy production. Overall results highlight how sectoral trade-offs change depending on the extent of development, something that may be difficult to regulate in the future, and that there are important basin-scale interdependencies. Benefits and limitations of the approach and its application are discussed

Sensitivity of projected climate impacts to climate model weighting: multi-sector analysis in eastern Africa

Uncertainty in long-term projections of future climate can be substantial and presents a major challenge to climate change adaptation planning. This is especially so for projections of future precipitation in most tropical regions, at the spatial scale of many adaptation decisions in water-related sectors. Attempts have been made to constrain the uncertainty in climate projections, based on the recognised premise that not all of the climate models openly available perform equally well. However, there is no agreed ‘good practice’ on how to weight climate models. Nor is it clear to what extent model weighting can constrain uncertainty in decision-relevant climate quantities. We address this challenge, for climate projection information relevant to ‘high stakes’ investment decisions across the ‘water-energy-food’ sectors, using two case-study river basins in Tanzania and Malawi. We compare future climate risk profiles of simple decision-relevant indicators for water-related sectors, derived using hydrological and water resources models, which are driven by an ensemble of future climate model projections. In generating these ensembles, we implement a range of climate model weighting approaches, based on context-relevant climate model performance metrics and assessment. Our case-specific results show the various model weighting approaches have limited systematic effect on the spread of risk profiles. Sensitivity to climate model weighting is lower than overall uncertainty and is considerably less than the uncertainty resulting from bias correction methodologies. However, some of the more subtle effects on sectoral risk profiles from the more ‘aggressive’ model weighting approaches could be important to investment decisions depending on the decision context. For application, model weighting is justified in principle, but a credible approach should be very carefully designed and rooted in robust understanding of relevant physical processes to formulate appropriate metrics

Climate variability affects water-energy-food infrastructure performance in East Africa

The need to assess major infrastructure performance under a changing climate is widely recognized yet rarely practiced, particularly in rapidly growing African economies. Here, we consider high-stakes investments across the water, energy, and food sectors for two major river basins in a climate transition zone in Africa. We integrate detailed interpretation of observed and modeled climate-system behavior with hydrological modeling and decision-relevant performance metrics. For the Rufiji River in Tanzania, projected risks for the mid-21st century are similar to those of the present day, but for the Lake Malawi-Shire River, future risk exceeds that experienced during the 20th century. In both basins a repeat of an early-20th century multi-year drought would challenge the viability of proposed infrastructure. A long view, which emphasizes past and future changes in variability, set within a broader context of climate-information interpretation and decision making, is crucial for screening the risk to infrastructure

Evaluating the sensitivity of robust water resource interventions to climate change scenarios

Water resource system planning is complicated by uncertainty on the magnitude and direction of climate change. Therefore, developments such as new infrastructure or changed management rules that would work acceptably well under a diverse set of future conditions (i.e., robust solutions) are preferred. Robust multi-objective optimisation can help identify advantageous system designs which include existing infrastructure plus a selected subset of new interventions. The method evaluates options using simulated water resource performance metrics statistically aggregated to summarise performance over the climate scenario ensemble. In most cases such ‘robustness metrics’ are sensitive to scenarios under which the system performs poorly and so results may be strongly influenced by a minority of unfavorable climate scenarios. Understanding the influence of specific climate scenarios on robust optimised decision alternatives can help better interpret their results. We propose an automated multi-criteria design-under-uncertainty sensitivity analysis formulation that uses multi-objective evolutionary algorithms to reveal robust and efficient designs under different samples of a climate scenario ensemble. The method is applied to a reservoir management problem in the Rufiji River basin, Tanzania, which involves the second largest dam in Africa. We find that solutions optimised for robustness under alternative groups of climate scenarios exhibit important differences. This becomes particularly decision-relevant if analysts and/or decision-makers have differing confidence levels in the relevance of certain climate scenarios. The proposed approach motivates continued research on how climate model credibility should inform climate scenario selection because it demonstrates the influence scenario selection has on recommendations arising from robust optimisation design processes