Cui et al. (2025) Study on the climate impacts on the reservoir waterlevel

Identification

• Journal: Scientific Reports
• Year: 2025
• Date: 2025-12-10
• Authors: Xiaoyu Cui, Lu Liu
• DOI: 10.1038/s41598-025-29847-w

Research Groups

• School of Economics, Southwestern University of Finance and Economics, Chengdu, China (Xiaoyu Cui, Lu Liu)

Short Summary

This study quantifies the nonlinear impact of temperature and precipitation on reservoir water level fluctuations in Sichuan Province, China, by enhancing a benchmark model with quadratic functions. It reveals critical thresholds and dynamic dependencies in the Marginal Rate of Substitution (MRS) between these climatic factors, offering insights for resilient water resource management.

Objective

• To assess and quantify the nonlinear impact of temperature and precipitation variations on reservoir water level dynamics, focusing on their synergistic effects and the Marginal Rate of Substitution (MRS) to enhance hydropower system resilience.

Study Configuration

• Spatial Scale: 17 large and medium-sized reservoirs in Sichuan Province, China.
• Temporal Scale: Daily observations from June 11, 2023, to December 31, 2023 (approximately 6.5 months).

Methodology and Data

• Models used:
  • Linear regression model (fixed effects, two-way individual-time fixed effects).
  • Quadratic regression model (incorporating quadratic terms for temperature and precipitation).
  • Bivariate quadratic regression model (for synergistic effects of temperature and precipitation).
  • Marginal Rate of Substitution (MRS) analysis derived from the bivariate quadratic model.
• Data sources:
  • Hydrological data: Daily reservoir water level, inflow, and outflow for 17 reservoirs from the Sichuan Hydrological and Water Resources Survey Center (http://www.schwr.com:8088/rsvr).
  • Climate data: Daily rainfall, daily mean temperature, daily maximum temperature, daily minimum temperature, horizontal visibility, and mean atmospheric pressure from the Reliable Prognosis (RP5) weather website (https://rp5.ru/).

Main Results

• Both temperature and precipitation significantly and nonlinearly drive reservoir water level fluctuations.
• Temperature exhibits an inverted U-shaped relationship with the first-order difference of reservoir water level, peaking at approximately 13.5 °C.
• Precipitation also shows an inverted U-shaped relationship with the first-order difference of reservoir water level, with an optimal level around 22.5 cm.
• A bivariate quadratic model combining both factors indicates that the first-order difference of reservoir water level is maximized when the average temperature is 13.5 °C and precipitation is 17 cm.
• The Marginal Rate of Substitution (MRS) between temperature and precipitation is dynamic, depending on their specific levels.
• Critical turning points for MRS trends occur when precipitation reaches 17 cm and temperature is 13.5 °C. For example, at 10 cm precipitation and 20 °C, an MRS of 1.077 indicates that a 1 °C temperature rise requires 1.077 cm of compensatory precipitation to maintain water level stability.
• The sensitivity of MRS to temperature increases with temperature when precipitation is below 17 cm, and decreases when precipitation exceeds 17 cm.
• The sensitivity of MRS to precipitation decreases with precipitation when temperature is below 13.5 °C, and increases when temperature surpasses 13.5 °C.

Contributions

• Provides empirical evidence for the nonlinear relationship between climate change (temperature and precipitation) and reservoir water level using daily, real-time observational data from 17 reservoirs, addressing limitations of previous modeling-based or single-reservoir studies.
• Enhances analytical precision by employing daily-scale reservoir data, offering a more detailed understanding compared to studies relying on annual data.
• Establishes a precise nonlinear functional relationship between climatic factors and reservoir water level changes, improving the accuracy of water level predictions.
• Conducts a detailed analysis of the Marginal Rate of Substitution (MRS) between temperature and rainfall, revealing their relative marginal contributions and substitution potential under varying climatic conditions.
• Identifies critical climate early warning thresholds (e.g., 13.5 °C for temperature and 17 cm for precipitation) and develops an MRS trend table, providing practical references and technical support for reservoir operators and managers to adjust strategies, optimize operations, and build climate-resilient water resource management systems.

Funding

• Guanghua Talent Project of Southwestern University of Finance and Economics.

Citation

@article{Cui2025Study,
  author = {Cui, Xiaoyu and Liu, Lu},
  title = {Study on the climate impacts on the reservoir waterlevel},
  journal = {Scientific Reports},
  year = {2025},
  doi = {10.1038/s41598-025-29847-w},
  url = {https://doi.org/10.1038/s41598-025-29847-w}
}