Unraveling Effects of Reservoir Operation on Daily Flow Regime in Thailand Using a Distributed Hydrological Model with Global Data

Abstract:

The Greater Chao Phraya River basin in Thailand is highly regulated by multipurpose reservoirs for intensive irrigation. Understanding quantitative effects of such regulation is crucial for effective water resource and agricultural management. Therefore, this study aims to assess the effects of reservoir operations on the water balance, daily flow regime and extreme flows in this basin. For this purpose, we reconstructed daily streamflow in the naturalized (no reservoir) and baseline operation scenarios using the distributed (1 km) wflow_sbm model. To overcome data scarcity, which is a common challenge in Southeast Asia, we ran the model with global data. The model was forced by the MSWEP V2 precipitation and eartH2Observe potential evapotranspiration datasets. Seamless distributed parameter maps based on pedotransfer functions (PTFs) and literature review were applied, leaving only one sensitive parameter to be calibrated. A target storage-and-release-based reservoir operation module (ROM) was implemented to simulate reservoir releases in the baseline operation scenario. The model results were analyzed in comparison to observations in the years 1989-2014. Our study shows that the global-data-driven wflow_sbm model can reconstruct daily streamflow in the basin, especially for natural catchments (KGE = 0.78). The ROM can capture the seasonal variability of reservoir releases, but not very accurately at the daily timescale (KGE = 0.43) since the actual reservoir operations are too complex. We found that the reservoir operation caused more evaporation loss of the catchment water. It inverted the natural flow seasonality and smoothed the daily flow regime with decreasing high flows, increasing mean flows and low flows, greater baseflow contribution, and lower flashiness. It prevented or mitigated many historical extreme flow incidents, but their timing became more variable and difficult to predict. Altogether, the results highlighted the importance of effective decision making for real-time operation, which remain challenging both in the reservoir system modeling and in practice.