Impacts of land use and land cover change and reforestation on summer rainfall in the Yangtze River basin

Abstract

Abstract. Land use and cover have been significantly changed all around the world during the last decade. In particular, the Grain for Green (GG) program has resulted in significant changes in regional land use and cover, especially in China. Land use and cover change (LULCC) may lead to changes in regional climate. In this study, we take the Yangtze River basin as a case study and analyze the impacts of LULCC and reforestation on summer rainfall amounts and extremes based on the Weather Research and Forecasting model. Firstly, two observed land use and cover scenarios (1990 and 2010) were chosen to investigate the impacts of LULCC on summer rainfall during the last decade. Secondly, two hypothetical reforestation scenarios (i.e., scenarios of 20 % and 50 % cropland changed to forest) were taken based on the control year of 2010 to test the sensitivity of summer rainfall (amounts and extremes) to reforestation. The results showed that average summer rainfall and extreme summer daily rainfall decreased in the Yangtze River basin between 1990 and 2010 due to LULCC. Reforestation could increase summer rainfall amount and extremes, and the effects were more pronounced in populated areas than over the whole basin. Moreover, the effects of reforestation were influenced by the reforestation proportion. In addition, the summer rainfall increased less conversely, with the transform proportion of cropland to forest increased from 20 % to 50 %. By analyzing the changes in water vapor mixing ratio, upward moisture flux, and 10 m wind, it is suggested that this result might be caused by the horizontal transportation processes of moisture. Although a comprehensive assessment of the impacts of LULCC on summer rainfall amounts and extremes was conducted, further studies are needed to investigate the uncertainty better.

Seasonal variation in landcover estimates reveals sensitivities and opportunities for environmental models

“…Environmental models incorporating landuse/landcover (LULC) data are common in many fields including hydrology, biogeochemistry, ecology, and climate science, often with decision-making implications (Hu et al, 2021;Baumgartner and Robinson, 2017;Naha et al, 2021;Li et al, 2021). Studies relating hydrology and water quality to LULC often use an LULC dataset developed primarily from growing season data, such as the United States National Landcover Database (NLCD; Jin et al, 2019) or Cropland Data Layer (CDL; Boryan et al, 2011), and/or use an LULC dataset available at an annual time step (Sulla-Menashe and Friedl, 2018;Buchhorn et al, 2020;Gray et al, 2022).…”