Abstract
Monitoring of soil moisture dynamics provides valuable information about grassland degradation, since soil moisture directly affects vegetation cover. While the Mongolian soil moisture monitoring network is limited to the urban and protected natural areas, remote sensing data can be used to determine the soil moisture status elsewhere. In this paper, we determine whether in situ and remotely sensed data in the unaccounted areas of Southwestern Mongolia are consistent with each other, by comparing Soil Moisture and Ocean Salinity (SMOS) first passive L-band satellite data with in situ measurements. To evaluate the soil moisture products, we calculated the temporal, seasonal, and monthly average soil moisture content. We corrected the bias of SMOS soil moisture (SM) data using the in situ measured soil moisture with both the simple ratio and gamma methods. We verified the bias-corrected SMOS data with Nash–Sutcliffe method. The comparison results suggest that bias correction (of the simple ratio and gamma methods) enhances the reliability of the SMOS data, resulting in a higher correlation coefficient. We then examined the correlation between SMOS and Normalized Difference Vegetation Index (NDVI) index in the various ecosystems. Analysis of the SMOS and in situ measured soil moisture data revealed that spatial soil moisture distribution matches the rainfall events in Southwestern Mongolia for the period 2010 to 2015. The results illustrate that the bias-corrected, monthly-averaged SMOS data has a high correlation with the monthly-averaged NDVI (R2 > 0.81). Both NDVI and rainfall can be used as indicators for grassland monitoring in Mongolia. During 2015, we detected decreasing soil moisture in approximately 30% of the forest-steppe and steppe areas. We assume that the current ecosystem of land is changing rapidly from forest to steppe and also from steppe to desert. The rainfall rate is the most critical factor influencing the soil moisture storage capacity in this region. The collected SMOS data reflects in situ conditions, making it an option for grassland studies.
Highlights
Soil moisture (SM) is an essential indicator of the hydrologic cycle that can affect the vegetation growth, impacting both global agriculture and grassland condition [1,2]
The monthly averaged Soil Moisture and Ocean Salinity (SMOS) SM data were strongly correlated with the average in situ SM measurements in the steppe and forest-steppe areas
These findings demonstrate that SM in these areas is relatively higher than SM in dry regions
Summary
Soil moisture (SM) is an essential indicator of the hydrologic cycle that can affect the vegetation growth, impacting both global agriculture and grassland condition [1,2]. These impacts significantly concern herders in Mongolia, who depend on the pastureland for their livelihood. Mongolia is located in the Silk Road Economic Belt and has a high amount of grassland, most of which is used for pastoral purposes, which makes up a significant amount of the economic activity there [3]. Soil moisture can be used to evaluate drought risk and grassland condition in these arid lands. Accurate soil moisture data is necessary for short and long-term monitoring of grassland development. One previous study determined that 90% of pastureland in Mongolia is vulnerable to land degradation and desertification, and that 72% of that total territory is degraded to some degree; slight, moderate, Land 2019, 8, 142; doi:10.3390/land8090142 www.mdpi.com/journal/land
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