Abstract
Abstract. In the present work, we developed a new formulation for the estimation of the soil moisture in the root zone based on the measured value of soil moisture at the surface. It was derived from a simplified soil water balance equation for semiarid environments that provides a closed form of the relationship between the root zone and the surface soil moisture with a limited number of physically consistent parameters. The method sheds lights on the mentioned relationship with possible applications in the use of satellite remote sensing retrievals of soil moisture. The proposed approach was used on soil moisture measurements taken from the African Monsoon Multidisciplinary Analysis (AMMA) and the Soil Climate Analysis Network (SCAN) databases. The AMMA network was designed with the aim to monitor three so-called mesoscale sites (super sites) located in Benin, Mali, and Niger using point measurements at different locations. Thereafter the new formulation was tested on three additional stations of SCAN in the state of New Mexico (US). Both databases are ideal for the application of such method, because they provide a good description of the soil moisture dynamics at the surface and the root zone using probes installed at different depths. The model was first applied with parameters assigned based on the physical characteristics of several sites. These results highlighted the potential of the methodology, providing a good description of the root-zone soil moisture. In the second part of the paper, the model performances were compared with those of the well-known exponential filter. Results show that this new approach provides good performances after calibration with a set of parameters consistent with the physical characteristics of the investigated areas. The limited number of parameters and their physical interpretation makes the procedure appealing for further applications to other regions.
Highlights
Soil moisture information is critical for weather and climate prediction, hydrological forecast applications, and watershed management (e.g. Walker and Houser, 2004; Moran et al, 2004; Manfreda and Fiorentino, 2008; Seneviratne et al, 2010)
A viable alternative strategy for obtaining spatial fields of soil moisture is from satellite remote sensing, which can provide continuous and largescale monitoring of the surface soil moisture state
Our preliminary application has been carried out using soil moisture observations taken from the African Monsoon Multidisciplinary Analysis (AMMA) and the Soil Climate Analysis Network (SCAN) databases
Summary
Soil moisture information is critical for weather and climate prediction, hydrological forecast applications, and watershed management (e.g. Walker and Houser, 2004; Moran et al, 2004; Manfreda and Fiorentino, 2008; Seneviratne et al, 2010). The authors suggested that the SWI methodology should benefit from a soil texture differentiation Another attempt to give a physical interpretation of the recession constant (T ) was carried out by Albergel et al (2008), who investigated the correlation of the parameter, T , with soil properties and climate conditions over France. Our preliminary application has been carried out using soil moisture observations taken from the African Monsoon Multidisciplinary Analysis (AMMA) and the Soil Climate Analysis Network (SCAN) databases These two networks represent valuable sources of soil moisture data measured at different depths that is shared via the web with the entire scientific community.
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