Responses of seasonal hydrological processes to vegetation change in the Yellow River basin

Abstract

China’s extensive ecological restoration initiatives have greatly impacted land surface hydrological processes. While the effect of vegetation change on hydrological processes has been well documented for annual hydrological processes, its impacts on the seasonal ones remain poorly understood. Using a newly developed ecohydrological model (SWAT-PML), here we quantify the effects of vegetation change on seasonal hydrological processes in the Yellow River Basin (YRB). We show that the relative changes in hydrological processes due to vegetation change exhibit a high degree of consistency across different seasons, similar to those observed at the annual scale. In terms of the whole YRB, vegetation change during 1998–2020 has resulted in an ∼8 % increase in evapotranspiration, along with decreases of ∼6 % in runoff, ∼9% in soil moisture, ∼8% in surface runoff, and ∼4 % in groundwater across all seasons. However, the relative impacts of vegetation change on each seasonal hydrological process were spatially heterogeneous across the YRB, closely following the spatial pattern of the magnitude of vegetation changes. This is because vegetation changes that are more pronounced at either seasonal or annual scales typically exert greater influences on hydrological processes. Unlike the relative impacts, the sensitivity of hydrological processes to changes in leaf area index (LAI)—i.e., the absolute change in a hydrological variable when LAI changes by one unit—varies substantially across different seasons, with the highest sensitivity occurring in summer. Nevertheless, summer experiences the lowest relative sensitivity (i.e., the relative change in a hydrological variable due to each unit change in LAI) when comparing with other seasons. Spatially, the sensitivity of hydrological variables to LAI also varies considerably across the YRB, with higher (lower) sensitivity in more arid (humid) regions, a pattern linked to the climatic aridity. Our results provide valuable insights into understanding the impacts of vegetation changes on the water cycle at varying temporal scales.