A first assessment of satellite and reanalysis estimates of surface and root-zone soil moisture over the permafrost region of Qinghai-Tibet Plateau

An in situ observation dataset of soil hydraulic properties and soil moisture in a high and cold mountainous area on the northeastern Qinghai-Tibet Plateau

“…This dataset provides new knowledge about correlations between different soil properties, and about the spatial and vertical distribution of SHPs, and insights into the spatial-temporal variability of SM over large-scale mountainous areas of the QTP. The lack of large-scale field sampling has led to our poor understanding of key soil hydraulic properties (including the soil saturated hydraulic conductivity and soil hydraulic properties related to the soil retention curve) over the QTP (Liu et al, 2021;Tian et al, 2017;Zhao et al, 2018). Large-scale information about key soil hydraulic properties is generally estimated using soil pedotransfer functions and basic soil information, such as soil texture (Fatichi et al, 2020), which is strongly location-dependent (Van Looy et al, 2017;Zhao et al, 2020) and not well known over the QTP (Dai et al, 2019;Lu et al, 2020;Zhang et al, 2018a).…”

“…While this study has explored the relationships between different SHPs, further establishing specific pedotransfer function is appropriate over the QTP. Large-scale SM information is commonly taken from reanalysis and remote sensing products, which have high uncertainty (Xia et al, 2014;Xing et al, 2021;Zhang et al, 2019;Zhang et al, 2021). Our SM dataset provides new accurate in-situ SM measurements covering 2014-2020 over a large-scale mountainous area.…”

“…Field sampling and laboratory measurements are more difficult and time consuming for some key SHPs, such as the soil water retention curve and saturated hydraulic conductivity, than the equivalent investigations for more basic soil parameters, such as texture (He et al, 2021;Tian et al, 2017). To date, very few large-scale studies have provided comprehensive in-situ measurements of both these key soil hydraulic properties and basic soil information, and there are few in situ observations of large-scale soil hydraulic properties available for the QTP (Liu et al, 2021;Tian et al, 2017;Zhao et al, 2018). The relationships between individual SHPs and their large-scale spatial distribution over the QTP remain largely unknown (Tian et al, 2017;Zhao et al, 2018).…”

“…SM can be quantified using in-situ instruments (Dorigo et al, 2021;Vereecken et al, 2008), remote sensing (Mohanty et al, 2017) and land-process models (Muñoz-Sabater et al, 2021). Land-process models have large biases and predictions often vary between different models (Lu et al, 2020;Xia et al, 2014;Xing et al, 2021;Zhang et al, 2021). Remote-sensing observations can be challenging over mountainous regions and SM can generally only be retrieved for the uppermost 5 cm of the soil.…”

“…Remote-sensing observations can be challenging over mountainous regions and SM can generally only be retrieved for the uppermost 5 cm of the soil. (Xing et al, 2021;Zhang et al, 2019). Ground-based SM measurements are the most accurate and important means for developing, validating, and extrapolating spatially-contiguous data derived from satellites or from land-process models (Dorigo et al, 2021;Benninga et al, 2018;Xia et al, 2014).…”