Abstract
Abstract. The soil water stored in the root zone is a critical variable for many applications, as it plays a key role in several hydrological and atmospheric processes. Many studies have been conducted to obtain reliable information on soil water in the root zone layer. However, most of them are mainly focused on the soil moisture within a certain depth rather than the water stored in the entire rooting system. In this work, a hydrological model named the Water And ecosYstem Simulator (WAYS) is developed to simulate the root zone water storage (RZWS) on a global scale. The model is based on a well-validated lumped model and has now been extended to a distribution model. To reflect the natural spatial heterogeneity of the plant rooting system across the world, a key variable that influences RZWS, i.e., root zone storage capacity (RZSC), is integrated into the model. The newly developed model is first evaluated based on runoff and RZWS simulations across 10 major basins. The results show the ability of the model to mimic RZWS dynamics in most of the regions through comparison with proxy data, the normalized difference infrared index (NDII). The model is further evaluated against station observations, including flux tower and gauge data. Despite regional differences, generally good performance is found for both the evaporation and discharge simulations. Compared to existing hydrological models, WAYS's ability to resolve the field-scale spatial heterogeneity of RZSC and simulate RZWS may offer benefits for many applications, e.g., agriculture and land–vegetation–climate interaction investigations. However, the results from this study suggest an additional evaluation of RZWS is required for the regions where the NDII might not be the correct proxy.
Highlights
Soil moisture is one of the critical variables in Earth system dynamics (Sheffield and Wood, 2008) and is claimed to be an essential climate variable by the World Meteorological Organization due to its key role in several hydrological and atmospheric processes (Legates et al, 2011)
The land cover data that we used are the global mosaics of the standard Moderate Resolution Imaging Spectroradiometer (MODIS) land cover type data product (MCD12Q1) with a spatial resolution of 0.5◦ in the year 2001, which are derived from the International Geosphere–Biosphere Programme (IGBP) land cover type classification (17 classes) and are reprojected into geographic coordinates of latitude and longitude on the World Geodetic System (WGS) 1984 coordinate reference system (Friedl et al, 2010)
A global hydrological model has been developed that aims to simulate the soil water volume stored in the entire root zone, a critical variable for ecohydrology-related studies, by considering the global spatial heterogeneity of the plant rooting system
Summary
Soil moisture is one of the critical variables in Earth system dynamics (Sheffield and Wood, 2008) and is claimed to be an essential climate variable by the World Meteorological Organization due to its key role in several hydrological and atmospheric processes (Legates et al, 2011). Many studies estimate RZSM by combining remotely sensed soil moisture with different models using data assimilation techniques (Rebel et al, 2012; Renzullo et al, 2014a, b) All these studies estimated the root zone soil moisture until a certain depth, e.g., 100 cm, still retaining the drawback of being unable to accurately calculate the water stored in the entire root zone layer. While the ability to predict RZWS, usually by employing models, is still missing, which is crucial for impact studies, e.g., agricultural drought analysis (Keyantash and Dracup, 2002), the work of Sriwongsitanon et al (2016) provided enlightenment for future RZWS-related studies, as their findings support NDII as a potential proxy for RZWS This is critical for mitigating the major challenge, i.e., the lack of direct observation of root zone water storage for evaluation, in the field of hydrological modeling. The ultimate goal of this study is to test the feasibility of WAYS for RZWS simulation on a global scale, an added-value feature useful for many applications
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