Responses of soil moisture to regional climate change over the Three Rivers Source Region on the Tibetan Plateau

Abstract

In this study, soil moisture data from two reanalysis datasets (ERA‐Interim, ERA5), a satellite soil moisture product from the European Space Agency (ESA) and three assimilation datasets from the Global Land Data Assimilation System (GLDAS), that is, GLADS‐NOAH025, GLADS‐NOAH10, and GLDAS‐CLM were compared with the observed soil moisture data in Maqu and Maduo stations over the Three Rivers Source Region (TRSR) on the Tibetan Plateau in China. Comparative statistical parameters between the soil moisture observations and the products, including the root mean square error, correlation coefficient (R), and standard deviation ratio were calculated to evaluate the products in different seasons. It was found that most products overestimated the soil moisture values, among which GLADS‐NOAH025 had relatively good consistency with the observations in the surface soil layer (0–10 cm), whereas GLDAS‐CLM agreed well with the observations in the 10–40 cm layer. Both ERA5 and ERA‐interim soil moisture overestimated soil moisture at all levels. The responses of soil moisture to regional climate change over the TRSR were also investigated by using the GLDAS‐NOAH025 soil moisture product, the ESA soil moisture product, and the observations during the nonfreezing period. The results show that the trends of soil moisture are consistent with the precipitation changes in the main central part of the TRSR. A significant positive correlation was found between soil moisture and precipitation in most regions of the TRSR, which indicates that soil moisture increases with the increase of precipitation, except in the northwest TRSR, where the variation of soil moisture was possibly influenced by both the precipitation changes and the increase of evapotranspiration.

Numerical modeling of the responses of soil temperature and soil moisture to climate change over the Tibetan Plateau, 1961–2010

“…Deng et al . (2019) assessed the reliability of satellite microwave remote sensing SM products in the Three Rivers Source region on the TP using the in‐suit measurements, showing that most products overestimated the SM values. Extensive numerical analysis, such as parameter optimization, datasets upgrade, is needed to investigate SM and ST changes accurately and to explain the mechanism of these changes between the two variables and such meteorological elements as Pr and surface evaporation (Ev) that affect the ST and SM variations significantly under the climate change scenario.…”

An integration of gauge, satellite, and reanalysis precipitation datasets for the largest river basin of the Tibetan Plateau

“…Precipitation plays a very important role in the research of hydrology, meteorology, ecology, and even social economics as it is a critical input factor for various models (e.g., hydrological and land surface models; Qi et al, 2016;L. Wang et al, 2017;Fang et al, 2019;Miri et al, 2019;. Specifically, precipitation is a key part of the water balance and energy cycle and will directly impact runoff generation and soil moisture movement (Su et al, 2008).…”

“…However, there are still problems in estimating daily (Meng et al, 2014;Bai and Liu, 2018) and extreme precipitation (Funk et al, 2015;Y. Zhou et al, 2015;Fang et al, 2019), especially in mountainous regions with high elevations and fewer ground measurements, such as the upper Brahmaputra (Xia et al, 2015;Xu et al, 2017;Qi et al, 2018). Additionally, there are several reanalysis datasets that have been widely used by researchers, such as the Global Land Data Assimilation System (GLDAS; Rodell et al, 2004;Zaitchik et al, 2010;Wang et al, 2011) and the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA2) dataset (Savtchenko et al, 2015;Gelaro et al, 2017;Reichle et al, 2017a, b).…”

“…Most studies have focused on evapotranspi- ration, soil moisture, and groundwater products derived from GLDAS or MERRA2 (Bibi et al, 2019;Deng et al, 2019;; meanwhile, to the best of our knowledge, there has been less focus on the evaluation of methods of precipitation estimation and little work on the corresponding river discharge simulations within the upper Brahmaputra River basin. These precipitation products generally have the advantage of wide and consistent coverage and have shown great potential in many applications (Li et al, 2015;Zhang et al, 2017;Fang et al, 2019) but also suffer from large uncertainties over the upper Brahmaputra River basin due to indirect observations, insufficient gauge calibration, and complex topography (Tong et al, 2014;Yong et al, 2015;Xu et al, 2017). In this study, we focus on integrating gauge, satellite, and reanalysis precipitation datasets to generate a new dataset over the upper Brahmaputra, suitable for use in hydrological simulations and other scientific research related to climate change.…”

Predicting the Suitable Geographical Distribution of Sinadoxa Corydalifolia under Different Climate Change Scenarios in the Three-River Region Using the MaxEnt Model

“…Because alpine plants in this region are highly sensitive to abnormal surface climates, their evolution is often associated with surface climate changes, life history, and human origin and evolution. In addition, the three-river region has served as an ideal laboratory for research in ecology, geology, and evolutionary biology because of its unique geology and geographical environment [ 21 , 22 , 23 ]. Therefore, the study of the species distribution in the three-river region and its relationship with environmental factors is helpful to understand the processes and mechanisms of biological adaptation and diffusion under complex climatic and environmental conditions, and the results of such a study would provide a theoretical basis and supporting data for biodiversity conservation and agricultural production management in this region.…”