Whether land greening in different geomorphic units are beneficial to water yield in the Yellow River Basin?

Abstract

Understanding the impacts of climate and land use/land cover (LULC) changes on water yield has great importance for water resource management and policy development, especially in arid and semi-arid areas. However, it is unclear whether land greening under the human land management is beneficial to the water yield of different geomorphic units under the unique climate models. Here, we used InVEST model to estimate the water yield of the Yellow River Basin (YRB) in 2000, 2010 and 2019 and selected different scenarios to analyse the contribution of LULC changes to water yield. The results showed that the water yield of the YRB increased during the study period. The mean depth of water yield (MDWY) of grassland, cultivated land, shrubland and forest decreased in turn, while the annual MDWY of each type increased. Cultivated land and grassland were the main contribution types of water yield in the YRB accounting for about 84% of the total, and the annual water yield of LULC types covered by vegetation increased except for cultivated land. The annual water yield of the Qinghai Tibet Plateau (region Ⅰ) and the Loess Plateau (region III) in the YRB accounted for more than 80% of the total YRB water yield and showed an interannual increasing trend with part of the Mongolia Plateau (region Ⅱ) in the basin. The contribution of LULC to water yield in the whole YRB was small compared with that of precipitation, but LULC changes resulted in benefits for water yield in recent years, especially in region III that is controlled by a warm-temperate semi-arid continental climate and region I that is controlled by a plateau cold climate. However, in region Ⅱ, which is controlled by a mid-temperate semi-arid continental climate, revegetation further weakened the water yield ecosystem service. The results can provide references for land use management to enhance water yield under the background of global climate change.