HESSD Hydrology and Earth System Sciences Discussions HESSD Hydrol. Earth Syst. Sci. Discuss. 1812-2116 Göttingen, Germany 10.5194/hessd-6-6335-2009 Spatial modelling of the variability of the soil moisture regime at the landscape scale in the southern Qilian Mountains, China Zhao C.-Y. 1 Qi P.-C. 2 Feng Z.-D. 2 Key laboratory of arid and grassland agroecology (Ministry of Education), Lanzhou University, Lanzhou 730000, China Key laboratory of western China's environment systems (Ministry of Education), Lanzhou University, Lanzhou 730000, China 09 10 2009 6 5 6335 6358 Copyright: © 2009 C.-Y. Zhao et al. 2009 This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/ This article is available from https://hess.copernicus.org/preprints/6/6335/2009/hessd-6-6335-2009.html The full text article is available as a PDF file from https://hess.copernicus.org/preprints/6/6335/2009/hessd-6-6335-2009.pdf

The spatial and temporal variability of the soil moisture status gives an important base for the assessment of ecological (for restoration) and economic (for agriculture) conditions at micro- and meso-scales. It is also an essential input into many hydrological processes models. However, there has been a lack of effective methods for its estimation in the study area. The aim of this study was to determine the relationship between the soil moisture status and precipitation and topographic factors. First, this study compared a linear regression model with interpolating models for estimating monthly mean precipitation and selected the linear regression model to simulate the temporal-spatial variability of precipitation in the southern Qilian Mountainous areas of the Heihe River Basin. Combining topographic index with the distribution of precipitation, we calculated the soil moisture regime in the Pailugou catchment, one representative comprehensive research catchment. The modeled results were tested by the observed soil water content for different times. The correlation coefficient between the modeled soil moisture status and the observed soil water content is quite high (e.g. <i>R</i><sup>2</sup>=0.76 in June), assuring our confidence in the spatially-modeled results of the soil moisture status. The method was applied to the southern Qilian Mountainous regions. The results showed that the modelled distribution of the soil moisture status reflected the interplay of the local and landscape climate processes. The driest sites occur on some ridges in northern part and western part of the study area, which are very small catchment areas and of low precipitation rates; the wettest are registered in the low river valley of the Heihe River and its major tributaries are in the eastern part due to large accumulating flow areas and higher precipitation rates. Temporally, the bigger variation of the soil moisture status in the study occurs in July and smaller difference appears in May.

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