Soil temperature plays a key role in the land surface processes because this parameter affects a series of physical, chemical, and biological processes in the soil, such as water and heat fluxes. However, observation of soil temperature is quite limited, especially at the regional scale. Therefore, this study is to investigate the spatiotemporal features of soil temperature in Xinjiang, China, using the Community Land model 3.5 (CLM3.5) with the atmospheric near-surface forcing data of the China Meteorological Administration Land Data Assimilation System (CLDAS). We use the observed soil temperature data collected from 105 national automatic stations during 2009 through 2012 in the study area to verify the simulation capability. The comparison results indicate that the CLM3.5 with the CLDAS driving field could well simulate the spatiotemporal patterns of the soil temperature at hourly, daily, and monthly time scales and at three depths (5 cm, 20 cm, and 80 cm). We also produce a soil temperature database of the region that is continuous both in time and space with high resolution (about 6.25 km). Overall, this study could help understand the regional and vertical characteristics of the soil temperature and provide an important scientific basis for other land-surface processes.

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Ecological conservation and restoration have increasingly captured attention worldwide due to the degradation of ecosystems. As one of the most ecologically fragile areas, the Tarim River Basin, of Xinjiang, China, encountered serious decline of desert riparian forests. The Chinese government has implemented the “Ecological Water Conveyance Project” (EWCP) since 2000, protecting and restoring the dominant natural species of the desert riparian forests, i.e., Populus euphratica Oliv. The regenerative effect after the water conveyance was noteworthy. For the purpose of clarifying the mechanism of P . euphratica forest regeneration to find a better prescription for the ecological restoration works in the Tarim River Basin, we investigated the relationship between the distribution of P . euphratica and soil salinity. Experimentally evaluated the effects of surface soil salinity on P . euphratica seed germination and the influence of river flooding on the salinity of surface soils. The results showed that (1) P . euphratica trees mainly spread along the river channel within 2 km; with increasing vertical distance to the channel, the number of trees declined significantly; (2) where the salinity of the surface soil is high, there are less living P . euphratica trees; (3) the germination of P . euphratica seeds decreases with increased soil conductivity; when the soil conductivity was higher than 7 ms/cm, the germination of P . euphratica seeds was severely curtailed. (4) Flooding regimes were a pre-condition of P . euphratica restoration; they had profound effects on improving the germination of the seeds via ameliorating water conditions and reducing salinity. Our results point out that the most efficient ecological prescription for restoring and protecting desert riparian forests is to induce flooding twice yearly during June to August with 10- to 15-day durations each time. Such a plan (especially in the Tarim River Basin) should prioritize the protection of seedlings.

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Central Asia is a region that has a large land mass, yet meteorological stations in this area are relatively scarce. To address this data issues, in this study, we selected two reanalysis datasets (the ERA40 and NCEP/NCAR) and downscaled them to 40 × 40 km using RegCM. Then three gridded datasets (the CRU, APHRO, and WM) that were extrapolated from the observations of Central Asian meteorological stations to evaluate the performance of RegCM and analyze the spatiotemporal distribution of precipitation and air temperature. We found that since the 1960s, the air temperature in Xinjiang shows an increasing trend and the distribution of precipitation in the Tianshan area is quite complex. The precipitation is increasing in the south of the Tianshan Mountains (Southern Xinjiang, SX) and decreasing in the mountainous areas. The CRU and WM data indicate that precipitation in the north of the Tianshan Mountains (Northern Xinjiang, NX) is increasing, while the APHRO data show an opposite trend. The downscaled results from RegCM are generally consistent with the extrapolated gridded datasets in terms of the spatiotemporal patterns. We believe that our results can provide useful information in developing a regional climate model in Central Asia where meteorological stations are scarce.

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The inability to conduct hydrological simulations in areas that lack historical meteorological data is an important factor limiting the development of watershed models, understanding of watershed water resources, and ultimate development of effective sustainability policies. This study focuses on the Manas River Basin (MRB), which is a high-altitude area with no meteorological stations and is located on the northern slope of the Tianshan Mountains, northern China. The hydrological processes were simulated using the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) using the Soil and Water Assessment Tool (SWAT) model. Simulated runoff was corrected using calibration/uncertainty and sensitivity program for the SWAT. Through parameter sensitivity analysis, parameter calibration, and verification, the Nash–Sutcliffe efficiency (NSE), adjusted R-square ({R}_{\text{adj}}^{2}), and percentage bias (\text{PBIAS}) were selected for evaluation. The results were compared with statistics obtained from Kenswat Hydrological Station, where the monthly runoff simulation efficiency was \text{NSE}\hspace{.25em}=0.64, {R}_{\text{adj}}^{2}\hspace{.25em}=0.69, and \text{PBIAS}\hspace{.25em}=\mbox{--}0.9, and the daily runoff simulation efficiency was \text{NSE}\hspace{.25em}=0.75, {R}_{\text{adj}}^{2} = 0.75, \text{PBIAS} = −1.5. These results indicate that by employing CMADS data, hydrological processes within the MRB can be adequately simulated. This finding is significant, as CMADS provide continuous temporal, detailed, and high-spatial-resolution meteorological data that can be used to build a hydrological model with adequate accuracy in areas that lack historical meteorological data.