Sunkara et al. (2026) Adaptation Triggers and Indicator Interpretability for Dynamic Reoptimization of Reservoir Control Policies Under Climate Change

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Water Resources Research
• Year: 2026
• Date: 2026-01-01
• Authors: Sai Veena Sunkara, Jonathan D. Herman
• DOI: 10.1029/2025wr040531

Research Groups

Not specified in the provided abstract.

Short Summary

This study develops a dynamic, two-level framework for reservoir control and adaptation policies, demonstrating its effectiveness for Oroville Reservoir, California. The framework, which uses observed data to trigger reoptimization, provides performance equal to or better than historical benchmarks and identifies demand, flood cost, and mean annual flow as primary drivers for adaptation decisions.

Objective

• To develop a framework for identifying dynamic decisions on two levels: an "outer loop" adaptation policy that establishes indicator thresholds for reoptimization based on recently observed data, and an "inner loop" control policy that undergoes reoptimization according to these thresholds.

Study Configuration

• Spatial Scale: Oroville Reservoir, California (regional/local scale).
• Temporal Scale: Short-term (5-day inflow forecast) to long-term (long-term statistics of climate and demand, recent system performance, fixed time interval for reoptimization).

Methodology and Data

• Models used: Heuristic policy search, Shapley Additive Explanations (SHAP), global sensitivity analysis.
• Data sources: Ensemble of climate model projections, recently observed data, storage, day of year, 5-day inflow forecast, long-term statistics of climate and demand, recent system performance.

Main Results

• The adaptation solutions provide equal or better performance compared to the historical benchmark.
• The proposed solutions are robust to out-of-sample scenarios.
• The decision to reoptimize the control policy is primarily driven by demand, flood cost, and mean annual flow indicators across different timescales.

Contributions

• Development of a novel two-level dynamic decision framework for reservoir management that integrates adaptation and control policies.
• Identification of specific observed thresholds (climate, demand, system performance) that can dynamically trigger control policy reoptimization to improve adaptation under future uncertainty.
• Demonstration of the framework's robustness and superior performance compared to historical benchmarks for a real-world reservoir system.

Funding

Not specified in the provided abstract.

Citation

@article{Sunkara2026Adaptation,
  author = {Sunkara, Sai Veena and Herman, Jonathan D. and Giuliani, Matteo},
  title = {Adaptation Triggers and Indicator Interpretability for Dynamic Reoptimization of Reservoir Control Policies Under Climate Change},
  journal = {Water Resources Research},
  year = {2026},
  doi = {10.1029/2025wr040531},
  url = {https://doi.org/10.1029/2025wr040531}
}