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

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

Global water resources and the role of groundwater in a resilient water future

Water is a critical resource, but ensuring its availability faces challenges from climate extremes and human intervention. In this Review, we evaluate the current and historical evolution of water resources, considering surface water and groundwater as a single, interconnected resource. Total water storage trends have varied across regions over the past century. Satellite data from the Gravity Recovery and Climate Experiment (GRACE) show declining, stable and rising trends in total water storage over the past two decades in various regions globally. Groundwater monitoring provides longer-term context over the past century, showing rising water storage in northwest India, central Pakistan and the northwest United States, and declining water storage in the US High Plains and Central Valley. Climate variability causes some changes in water storage, but human intervention, particularly irrigation, is a major driver. Water-resource resilience can be increased by diversifying management strategies. These approaches include green solutions, such as forest and wetland preservation, and grey solutions, such as increasing supplies (desalination, wastewater reuse), enhancing storage in surface reservoirs and depleted aquifers, and transporting water. A diverse portfolio of these solutions, in tandem with managing groundwater and surface water as a single resource, can address human and ecosystem needs while building a resilient water system

Global water resources and the role of groundwater in a resilient water future

Water is a critical resource, but ensuring its availability faces challenges from climate extremes and human intervention. In this Review, we evaluate the current and historical evolution of water resources, considering surface water and groundwater as a single, interconnected resource. Total water storage trends have varied across regions over the past century. Satellite data from the Gravity Recovery and Climate Experiment (GRACE) show declining, stable and rising trends in total water storage over the past two decades in various regions globally. Groundwater monitoring provides longer-term context over the past century, showing rising water storage in northwest India, central Pakistan and the northwest United States, and declining water storage in the US High Plains and Central Valley. Climate variability causes some changes in water storage, but human intervention, particularly irrigation, is a major driver. Water-resource resilience can be increased by diversifying management strategies. These approaches include green solutions, such as forest and wetland preservation, and grey solutions, such as increasing supplies (desalination, wastewater reuse), enhancing storage in surface reservoirs and depleted aquifers, and transporting water. A diverse portfolio of these solutions, in tandem with managing groundwater and surface water as a single resource, can address human and ecosystem needs while building a resilient water system

Author Correction: Global water resources and the role of groundwater in a resilient water future

In the version of this article originally published, reference 9 was incorrectly cited in the last sentence of the second paragraph under ‘Introduction’ and in the first sentence of the second paragraph under the ‘Water scarcity’ subsection. Scanlon et al. (Environ. Res. Lett. https://doi.org/ 10.1088/1748-9326/ac3bfc, 2022) was incorrectly cited in the last sentence under ‘Drivers of water-resource variability’ but is now replaced with reference 38, and Figure 3 was wrongly stated to be adapted from reference 19 instead of reference 36. Reference 40 was mistakenly cited in the last sentence of the second paragraph under the ‘Increasing water access and supplies’ subsection, and reference 37 was inadvertently duplicated in the reference list. References 28 (now reading ‘Winter, T. C., Harvey, J. W., Franke, O. L. and Alley, W. M. Ground Water and Surface Water: A Single Resource. Circular 1139 (United States Geological Survey, 1998)’) and 94 (now reading ‘Scanlon, B. R., Reedy, R. C., Faunt, C. C., Pool, D. and Uhlman, K. Enhancing drought resilience with conjunctive use and managed aquifer recharge in California and Arizona. Environ. Res. Lett. 11, 035013 (2016)’) initially referred to incorrect sources. Lastly, the name of author Hannes Müller Schmied was incorrectly spelled Hannes Mueller Schmied, and an affiliation for him was missing: Senckenberg Leibniz Biodiversity and Climate Research Centre (SBiK-F), Frankfurt am Main, Germany. The errors have been corrected in the HTML and PDF versions of the article

Author Correction: Global water resources and the role of groundwater in a resilient water future

In the version of this article originally published, reference 9 was incorrectly cited in the last sentence of the second paragraph under ‘Introduction’ and in the first sentence of the second paragraph under the ‘Water scarcity’ subsection. Scanlon et al. (Environ. Res. Lett. https://doi.org/ 10.1088/1748-9326/ac3bfc, 2022) was incorrectly cited in the last sentence under ‘Drivers of water-resource variability’ but is now replaced with reference 38, and Figure 3 was wrongly stated to be adapted from reference 19 instead of reference 36. Reference 40 was mistakenly cited in the last sentence of the second paragraph under the ‘Increasing water access and supplies’ subsection, and reference 37 was inadvertently duplicated in the reference list. References 28 (now reading ‘Winter, T. C., Harvey, J. W., Franke, O. L. and Alley, W. M. Ground Water and Surface Water: A Single Resource. Circular 1139 (United States Geological Survey, 1998)’) and 94 (now reading ‘Scanlon, B. R., Reedy, R. C., Faunt, C. C., Pool, D. and Uhlman, K. Enhancing drought resilience with conjunctive use and managed aquifer recharge in California and Arizona. Environ. Res. Lett. 11, 035013 (2016)’) initially referred to incorrect sources. Lastly, the name of author Hannes Müller Schmied was incorrectly spelled Hannes Mueller Schmied, and an affiliation for him was missing: Senckenberg Leibniz Biodiversity and Climate Research Centre (SBiK-F), Frankfurt am Main, Germany. The errors have been corrected in the HTML and PDF versions of the article