English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The spatial and temporal variability of the soil moisture status gives an important base for the assessment of ecological (for forest restoration) and economic (for agriculture) conditions at micro- and meso-scales. It is also an essential input into many distributed hydrological models. However, there has been a lack of effective methods for its estimation at the landscape scale in the study area. The objective of this study is to model the variability of the soil moisture regime in the southern Qilian Mountains with an area of 10,009 km 2 . First, a small catchment named Pailugou catchment (area of 10 km 2 ) is selected. A modified wetness index, including the topographic wetness index, solar radiation and the monthly mean precipitation, is developed. Based on GIS-assisted regionalization of parameters, the soil moisture status at the grid scale of 1×1 m 2 can be estimated using the modified wetness index in Pailugou catchment. Secondly, we validate the method with a collection of 15 points within the small catchment. The results show that soil moisture status estimations are significantly improved of using the modified wetness index. 77% of the spatial variability of soil moisture can be explained by the index in Pailugou catchment. That assures our confidence in the modified wetness index to estimate the soil moisture status. Finally, the method is applied to the southern Qilian Mountainous regions, northwestern China. At the landscape scale, the parameters needed by the index are regionalized. For instance, the temporal-spatial distribution of monthly mean precipitation is simulated by the linear regression model. The slope and special upslope area are extracted from the DEM of southern Qilian Mountains with a 10 m resolution. Based on the modified wetness index, the variability of the soil moisture regime in the region has been simulated. From the study, the conclusion can be drawn that: A¢Â‘Â  the soil moisture status shows higher at the gentle bases of long hill-slopes than at the steep short sites, higher in the north-facing slope than in the south-facing slope. A¢Â‘Âi the driest sites occurred on some ridges in the northern part and the western part of the study area, the wettest sites were registered in the low valleys of the Heihe River and its major tributaries in the eastern part. Comparing the spatial distribution pattern of vegetation with that of soil moisture status modeled in the study area, we found the spatial distribution pattern of vegetation has nearly relative with that of soil moisture status.

Spatial Modelling of the Variability of the Soil Moisture Regime at the Landscape Scale in the Southern Qilian Mountains, China