Effective use of integrated hydrological models in basin-scale water resources management: surrogate modeling approaches

Abstract:

Integrated hydrological models (IHMs) consider surface water and subsurface water as a unified system, and have been widely adopted in basin-scale water resources studies. However, due to IHMs’ mathematical complexity and high computational cost, it is difficult to implement them in an iterative model evaluation process (e.g., Monte Carlo Simulation, simulation-optimization analysis, etc.), which diminishes their applicability for supporting decision-making in real-world situations. Our studies investigated how to effectively use complex IHMs to address real-world water issues via surrogate modeling. Three surrogate modeling approaches were considered, including 1) DYCORS (DYnamic COordinate search using Response Surface models), a well-established response surface-based optimization algorithm; 2) SOIM (Surrogate-based Optimization for Integrated surface water-groundwater Modeling), a response surface-based optimization algorithm that we developed specifically for IHMs; and 3) Probabilistic Collocation Method (PCM), a stochastic response surface approach. Our investigation was based on a modeling case study in the Heihe River Basin (HRB), China’s second largest endorheic river basin. The GSFLOW (Coupled Ground-Water and Surface-Water Flow Model) model was employed. Two decision problems were discussed. One is to optimize, both in time and in space, the conjunctive use of surface water and groundwater for agricultural irrigation in the middle HRB region; and the other is to cost-effectively collect hydrological data based on a data-worth evaluation. Overall, our study results highlight the value of incorporating an IHM in making decisions of water resources management and hydrological data collection. An IHM like GSFLOW can provide great flexibility to formulating proper objective functions and constraints for various optimization problems. On the other hand, it has been demonstrated that surrogate modeling approaches can pave the path for such incorporation in real-world situations, since they can dramatically reduce the computational cost of using IHMs in an iterative model evaluation process. In addition, our studies generated insights into the human-nature water conflicts in the specific study area and suggested potential solutions to address them.