Retrieving Soil Moisture in the Permafrost Environment by Sentinel-1/2 Temporal Data on the Qinghai–Tibet Plateau

Abstract

Soil moisture (SM) products presently available in permafrost regions, especially on the Qinghai–Tibet Plateau (QTP), hardly meet the demands of evaluating and modeling climatic, hydrological, and ecological processes, due to their significant bias and low spatial resolution. This study developed an algorithm to generate high-spatial-resolution SM during the thawing season using Sentinel-1 (S1) and Sentinel-2 (S2) temporal data in the permafrost environment. This algorithm utilizes the seasonal backscatter differences to reduce the effect of surface roughness and uses the normalized difference vegetation index (NDVI) and the normalized difference moisture index (NDMI) to characterize vegetation contribution. Then, the SM map with a grid spacing of 50 m × 50 m in the hinterland of the QTP with an area of 505 km × 246 km was generated. The results were independently validated based on in situ data from active layer monitoring sites. It shows that this algorithm can retrieve SM well in the study area. The coefficient of determination (R2) and root-mean-square error (RMSE) are 0.82 and 0.06 m3/m3, respectively. This study analyzed the SM distribution of different vegetation types: the alpine swamp meadow had the largest SM of 0.26 m3/m3, followed by the alpine meadow (0.23), alpine steppe (0.2), and alpine desert (0.16), taking the Tuotuo River basin as an example. We also found a significantly negative correlation between the coefficient of variation (CV) and SM in the permafrost area, and the variability of SM is higher in drier environments and lower in wetter environments. The comparison with ERA5-Land, GLDAS, and ESA CCI showed that the proposed method can provide more spatial details and achieve better performance in permafrost areas on QTP. The results also indicated that the developed algorithm has the potential to be applied in the entire permafrost regions on the QTP.

Analysis and partitioning of terrestrial water storage in the Yellow River source region

“…The increasing rates in SWE successively decreased from northwest to southeast, with SM and GWS exhibiting the same pattern. The YRSR is located on the permafrost boundary in the northeastern QTP, which is highly sensitive to climate change (Li et al, 2023). Areas with a decreasing PM trend accounted for 94.7% of the YRSR subareas.…”

“…The mean annual T of −2.5°C and P of 532.5 mm have been calculated using the inverse distance‐weighted average method and elevation correction. Permafrost is widely distributed in the YRSR, and accounts for approximately 43.8% of the total area, while seasonally frozen ground accounts for approximately 56.2% of the total area (Li et al, 2023). However, glacier area constitutes only 0.1% of the YRSR's total area and melting ice flow accounts for just 0.35% of the total runoff in the region (He et al, 2021).…”

Land-Atmosphere Interactions and Effects on the Climate of the Tibetan Plateau and Surrounding Regions

“…Surface characteristic parameters are significant factors affecting the accuracy of surface process assessments. Li et al [17] developed an algorithm to generate high-spatialresolution soil moisture during the thawing season in the permafrost environment using Sentinel-1 and Sentinel-2 data. The comparison with ERA5-Land, Global Land Data Assimilation System (GLDAS), and European Space Agency Climate Change Initiative (ESA CCI) products indicated that this proposed method is able to provide more spatial details and achieve better performance in permafrost areas over the TP.…”

“…The comparison with ERA5-Land, Global Land Data Assimilation System (GLDAS), and European Space Agency Climate Change Initiative (ESA CCI) products indicated that this proposed method is able to provide more spatial details and achieve better performance in permafrost areas over the TP. The typical land cover types, alpine desert, alpine steppe, alpine meadow, and alpine swamp meadow, displayed distinct differences in soil moisture, with mean values of 0.16, 0.20, 0.23, and 0.26 m 3 /m 3 , respectively [17]. The soil's apparent thermal diffusivity (k) is also vital for investigating soil surface heat transfer.…”