Adaptive hydrologic modeling approaches for optimizing water infrastructure design and management under nonstationarity

Abstract

Traditional hydrologic design often assumes stationary climate conditions, limiting its ability to address changing precipitation patterns, evolving land use, and competing basin objectives such as water supply, recreation, energy production, and environmental flows. This study presents an adaptive hydrologic modeling approach for water infrastructure design and management under nonstationary conditions. The framework is demonstrated through a case study of the Buckhorn Creek Basin in North Carolina, a multi-use basin that includes key infrastructure such as Shearon Harris Lake, Sharon Harris Dam, and Buckhorn Dam. The methodology involved collecting terrain, land cover, soils, rainfall, infrastructure, and observed hydrologic data; developing future rainfall inputs from downscaled General Circulation Model projections; and building a two-dimensional HEC-RAS model to simulate basin conditions. Results comparing traditional and adaptive approaches show that the traditional method failed to meet several basin needs under future wet and dry scenarios, particularly for water supply, recreation, and environmental flows. In contrast, the adaptive approach satisfied basin requirements across all tested scenarios. The findings demonstrate that regularly updated hydrologic modeling, supported by revised climate projections and changing stakeholder priorities, can improve infrastructure decision-making and support resilient water management under uncertainty.