Abstract
Abstract. Vertisols are clay soils that are common in the monsoonal and dry warm regions of the world. One of the characteristics of these soil types is to form deep cracks during periods of extended dry, resulting in significant variation of the soil and hydrologic properties. Understanding the influence of these varying soil properties on the hydrological behavior of the system is of considerable interest, particularly in the retrieval or simulation of soil moisture. In this study we compare surface soil moisture (θ in m3 m−3) retrievals from AMSR-E using the VUA-NASA (Vrije Universiteit Amsterdam in collaboration with NASA) algorithm with simulations from the Community Land Model (CLM) over vertisol regions of mainland Australia. For the three-year period examined here (2003–2005), both products display reasonable agreement during wet periods. During dry periods however, AMSR-E retrieved near surface soil moisture falls below values for surrounding non-clay soils, while CLM simulations are higher. CLM θ are also higher than AMSR-E and their difference keeps increasing throughout these dry periods. To identify the possible causes for these discrepancies, the impacts of land use, topography, soil properties and surface temperature used in the AMSR-E algorithm, together with vegetation density and rainfall patterns, were investigated. However these do not explain the observed θ responses. Qualitative analysis of the retrieval model suggests that the most likely reason for the low AMSR-E θ is the increase in soil porosity and surface roughness resulting from cracking of the soil. To quantitatively identify the role of each factor, more in situ measurements of soil properties that can represent different stages of cracking need to be collected. CLM does not simulate the behavior of cracking soils, including the additional loss of moisture from the soil continuum during drying and the infiltration into cracks during rainfall events, which results in overestimated θ when cracks are present. The hydrological influence of soil physical changes are expected to propagate through the modeled system, such that modeled infiltration, evaporation, surface temperature, surface runoff and groundwater recharge should be interpreted with caution over these soil types when cracks might be present. Introducing temporally dynamic roughness and soil porosity into retrieval algorithms and adding a "cracking clay" module into models are expected to improve the representation of vertisol hydrology.
Highlights
Soil moisture is a key variable in the water and energy cycles and its accurate representation and measurement is required for estimation and prediction of infiltration, evaporation, runoff and latent, sensible and ground heat fluxes
Global Inventory Monitoring and Modeling Studies (GIMMS) was used in this study to examine vegetation density, together with the monthly Advanced Microwave Scanning Radiometer (AMSR-E) vegetation optical depth (τ ) that is simultaneously retrieved with AMSR-E θ
This section focuses on the effects of topography, land use, vegetation density, and precipitation pattern on the AMSR-E soil moisture retrievals over the vertisols
Summary
Soil moisture is a key variable in the water and energy cycles and its accurate representation and measurement is required for estimation and prediction of infiltration, evaporation, runoff and latent, sensible and ground heat fluxes. Soil moisture products such as ground observations, models or other remote sensing techniques (McCabe et al, 2008; Scipal et al, 2008; Draper et al, 2009) allows for better understanding of soil moisture estimates derived by different approaches (Wagner et al, 2003; McCabe et al, 2005a). In the absence of detailed in situ measurements, remote sensing and land surface modeling approaches offer the only means to obtain estimates of the soil moisture state Identifying whether these approaches are capable of reflecting the expected responses of vertisol soils is required. The divergence between the land surface model and AMSR-E starts at the end of the rainy season, keeps increasing through the dry season and peaks at the beginning of the rainy season (Fig. 3) Explaining these differing responses is the key motivation of the current paper. Employed to discriminate the possible reasons for the differing soil moisture responses observed between these two estimation techniques, and identify where improvements in descriptions of the soil physical processes might be required to improve estimation over vertisol soil types
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