Abstract
Soil moisture plays an important role in land-atmosphere interactions, agricultural drought monitoring, and water resource management, particularly across arid regions. However, it is challenging to simulate soil moisture of high spatial resolution and to evaluate soil moisture at fine spatial resolution in arid regions in Northwest China due to considerable uncertainties in forcing data and limited in situ measurements. Then, the data set was used to produce the 1 km high-resolution atmospheric forcing datasets and to drive the Community Land Model version 3.5 (CLM3.5) for simulating spatiotemporally continuous surface soil moisture. The capabilities of soil moisture simulation using CLM3.5 forced by the XJLDAS-driven field were validated against data obtained at three soil layers (0–10, 0–20, and 0–50 cm) from 54 soil moisture stations in Xinjiang. Results show that the simulated soil moisture agreed well with the observations [CORR > 0.952], and the intra-annual soil moisture in Xinjiang gradually increased during May through August. The main factors that affect changes in soil moisture across the study region were precipitation and snowmelt. The overall finding of this study is that an XJLDAS, high-resolution forcing data driven CLM3.5 can be used to generate accurate and continuous soil moisture of high resolution (1km) in Xinjiang. This study can help understand the spatiotemporal features of the soil moisture, and provide important input for hydrological studies and agricultural water resources management over the arid region.
Highlights
Soil moisture plays an important role in land-atmosphere interactions, agricultural drought monitoring, and water resource management, across arid regions
At present, published studies based on observation stations have mostly been focusing on the characteristics of soil moisture levels (SMLs) changes at singular points or in small areas, and it is difficult to conduct climatological studies on SMLs at the global or continental scale[17]
This study aimed to investigate the SML component in detail because SML changes can indirectly reflect a region’s hydrological and climatic conditions and SMLs are regularly used for numerical meteorological forecasts, prediction of mountain torrents, and monitoring of droughts that affect agricultural soils
Summary
Soil moisture plays an important role in land-atmosphere interactions, agricultural drought monitoring, and water resource management, across arid regions. These were macroscopic evaluations on a regional scale Both studies concluded that the spatiotemporal distribution of China’s soil temperatures and SMLs can be reproduced by using driving data to force land models. There is an urgent need for reliable and high-precision atmospheric forcing datasets that can drive land models for China’s Xinjiang Region with scarce observation stations and vast spatiotemporal differences. When such an atmospheric forcing datasets is used to force CLM3.5, the continuous evolutionary processes of related terrestrial surface components (such as snowmelt and SMLs) in Xinjiang can be properly simulated
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