A two-level attribution method for water resource changes based on water budget balance and distributed simulation

Abstract

Attribution of water resource changes is crucial for revealing the evolutionary laws of water resource systems and improving the efficiency of water resource management. This study conducts systematic research through theoretical interpretation, methodological development and case application. First, the water balance principle and water budget balance theory are integrated to clarify an attribution framework centered on the water cycle process. Second, a water budget balance equation and a distributed human-water relationship model covering the entire “input-transformation-consumption-output” chain are constructed. Third, a two-level attribution system is established by coupling the balance equation, distributed model, control variable method and contribution rate quantification: the first level quantifies the driving contributions of climate change and human activities to changes in natural runoff; the second level analyzes the driving effects of precipitation, incoming surface runoff, natural evapotranspiration, human water consumption, external transferred water and water storage on actual runoff changes. Finally, the method is applied to the Qin River Basin in China across multi-temporal (multi-year average, annual, monthly) and spatial (entire basin, basin divisions) scales. Results show that the method integrates multi-source information to clarify the driving mechanisms of water resource changes, with strong effectiveness and applicability across scales; basin runoff changes during 2001–2022 were dominated by climatic factors, while human activities promoted natural runoff increase but reduced actual runoff; the basin’s natural runoff decreased by 0.982 × 10⁸ m³ when comparing the periods 2001–2010 and 2011–2020, with the contribution rates of climate change and human activities being −118.0% and 18.0%, respectively; the combined effects of reduced precipitation, decreased natural evapotranspiration, increased human water consumption, increased external transferred water, and increased water storage led to a 0.508 × 10⁸ m³ decrease in actual runoff, with the corresponding contribution rates of −47.3%, 276.4%, −173.5%, −1.1%, and −154.5%. The primary novelty lies in a hierarchical framework that distinguishes between natural and actual runoff drivers, providing finer attribution resolution compared with conventional methods.