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Abstract Climate vulnerability assessments rely on water infrastructure system models that imperfectly predict performance metrics under ensembles of future scenarios. There is a benefit to reduced complexity system representations to support these assessments, especially when large ensembles are used to better characterize future uncertainties. An important question is whether the total uncertainty in the output metrics is primarily attributable to the climate ensemble or to the systems model itself. Here we develop a method to address this question by combining time series error models of performance metrics with time‐varying Sobol sensitivity analysis. The method is applied to a reduced complexity multi‐reservoir systems model of the Sacramento‐San Joaquin River Basin in California to demonstrate the decomposition of flood risk and water supply uncertainties under an ensemble of climate change scenarios. The results show that the contribution of systems model error to total uncertainty is small (∼5%–15%) relative to climate based uncertainties. This indicates that the reduced complexity systems model is sufficiently accurate for use in the context of the vulnerability assessment. We also observe that climate uncertainty is dominated by the choice of general circulation model and its interactive effects with the representative concentration pathway (RCP), rather than the RCP alone. This observation has implications for how climate vulnerabilities should be interpreted.
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Adaptation of Multiobjective Reservoir Operations to Snowpack Decline in the Western United States
Long-term snowpack decline is among the best-understood impacts of climate change on water resources systems. This trend has been observed for decades and is projected to continue even in climate projections in which total runoff volumes do not change significantly. For basins in which snowpack has historically provided intra-annual water storage, snowpack decline creates several issues that may require adaptation to infrastructure, operations, or both. This study develops an approach to analyze vulnerabilities and adaptations specifically focused on the challenge of snowpack decline, using the northern California reservoir system as a case study. We first introduce an open-source daily time-step simulation model of this system, which is validated against historical observations of operations. Multiobjective vulnerabilities to snowpack decline are then examined using a set of downscaled climate scenarios to capture the physically based effects of rising temperatures. A statistical analysis shows that the primary impacts include water supply shortage and lower reservoir storage resulting from the seasonal shift in runoff timing. These challenges identified from the vulnerability assessment inform proposed adaptations to operations to maintain multiobjective performance across the ensemble of plausible future scenarios, which include other uncertain hydrologic changes. To adapt seasonal reservoir management without the cost of additional infrastructure, we specifically propose and test adaptations that parameterize the structure of existing operating policies: a dynamic flood control rule curve and revised snowpack-to-streamflow forecasting methods to improve seasonal runoff predictability given declining snowpack. These adaptations are shown to mitigate the majority of vulnerabilities caused by snowpack decline across the scenario ensemble, with remaining opportunities for improvement using formal policy search and dynamic adaptation techniques. The coupled approach to vulnerability assessment and adaptation is generalizable to other snowmelt-dominated water resources systems facing the loss of seasonal storage due to rising temperatures.
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- Award ID(s):
- 1639268
- PAR ID:
- 10314238
- Date Published:
- Journal Name:
- Journal of water resources planning and management
- Volume:
- 146
- Issue:
- 12
- ISSN:
- 1943-5452
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Reservoirs are designed and operated to mitigate hydroclimatic variability and extremes to fulfill various beneficial purposes. Existing reservoir infrastructure capacity and operation policies derived from historical records are challenged by hydrologic regime change and storage reduction from sedimentation. Furthermore, climate change could amplify the water footprint of reservoir operation (i.e. non-beneficial evaporative loss), further influencing the complex interactions among hydrologic variability, reservoir characteristics, and operation decisions. Disentangling and quantifying these impacts is essential to assess the effectiveness of reservoir operation under future climate and identify the opportunities for adaptive reservoir management (e.g. storage reallocation). Using reservoirs in Texas as a testing case, this study develops data-driven models to represent the current reservoir operation policies and assesses the challenges and opportunities in flood control and water supply under dynamically downscaled climate projections from the Coupled Model Intercomparison Project Phase 6. We find that current policies are robust in reducing future flood risks by eliminating small floods, reducing peak magnitude, and extending the duration for large floods. Current operation strategies can effectively reduce the risk of storage shortage for many reservoirs investigated, but reservoir evaporation and sedimentation pose urgent needs for revisions in the current guidelines to enhance system resilience. We also identify the opportunities for reservoir storage reallocation through seasonal-varying conservation pool levels to improve water supply reliability with negligible flood risk increase. This study provides a framework for stakeholders to evaluate the effectiveness of the current reservoir operation policy under future climate through the interactions among hydroclimatology, reservoir infrastructure, and operation policy.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1061/(ASCE) WR.1943-5452.0001300
