Net radiation plays an essential role in determining the thermal conditions of the Earth’s surface and is an important parameter for the study of land-surface processes and global climate change. In this paper, an improved satellite-based approach to estimate the daily net radiation is presented, in which sunshine duration were derived from the geostationary meteorological satellite (FY-2D) cloud classification product, the monthly empirical as and bs Angstrom coefficients for net shortwave radiation were calibrated by spatial fitting of the ground data from 1997 to 2006, and the daily net longwave radiation was calibrated with ground data from 2007 to 2010 over the Heihe River Basin in China. The estimated daily net radiation values were validated against ground data for 12 months in 2008 at four stations with different underlying surface types. The average coefficient of determination (R2) was 0.8489, and the averaged Nash-Sutcliffe equation (NSE) was 0.8356. The close agreement between the estimated daily net radiation and observations indicates that the proposed method is promising, especially given the comparison between the spatial distribution and the interpolation of sunshine duration. Potential applications include climate research, energy balance studies and the estimation of global evapotranspiration.

Advanced Very High Resolution Radiometer (AVHRR)-derived Normalized Difference Vegetation Index (NDVI) data are widely used in global-change research, yet relationships between the NDVI and ecoclimatological variables are not fully understood. This study attempts to model climate-driven vegetation dynamics through the integration of satellite-derived NDVI data with climate data collected from ground-based meteorological stations in the US Great Plains. Monthly maximum value composites of NDVI data (8-km resolution) and monthly temperature and precipitation records from 305 stations were collected from 1982 to 2001. Analyses involving deseasonalized datasets supported temperature as the dominant climate regime, demonstrating a higher average NDVI-temperature correlation (r50.73) than the NDVI-precipitation relationship (r50.38). Cluster analysis was used to develop a climate regionalization scheme based primarily on temperature, and NDVI characteristics of each subregion were compared. In the context of global climate change, findings from this study emphasize the influence of temperature and precipitation variability over vegetation cover in the Great Plains region.

Evapotranspiration (ET) involves actual water consumption directly from the land surface; however, regional ET maps are usually neglected during water management and allocation. In this study, an integrated satellite-based ET monitoring approach with two spatial resolutions is proposed over an extremely arid basin in China that has experienced crop area expansion and has been the focus of a water-saving project since 2012. The proposed ETWatch approach combined with an empirical downscaling strategy based on vegetation condition was employed to produce monthly ET maps. This method achieves satisfactory accuracy and is validated by its reasonable spatial and temporal pattern results. Yearly results exhibit an increasing ET trend before 2012, which subsequently gradually decrease. This trend fits well with the dynamics of the basin-wide vegetation condition, indicating that there is a stronger correlation between water consumption and vegetation than between other environmental indicators. The average ET over three main crop types in the region (grape, cotton, and melon) decreased by approximately 5% due to optimizations of the irrigation timeline during the project, while 13% of the water savings can be attributed to the fallowing of crop areas. Based on the irrigation distribution in 2012, a comparison between drip and border irrigation that achieves water savings of 3.6% from grape and 5.8% from cotton is conducted. However, an afforestation project that involved planting young trees led to an approximate 25% increase in water consumption. Overall, since 2012, the water-saving project has achieved satisfactory performance regarding excessive groundwater withdrawal, showing a reduction trend of 3 million m3/year and an increase in Lake Aiding water levels since 2011. The results reveal the potential of the ET monitoring strategy as a basis for basin-scale water management.