Abstract

Abstract. Interactions between soil moisture and terrestrial evaporation affect water cycle behaviour and responses between the land surface and the atmosphere across scales. With strong heterogeneities at the land surface, the inherent spatial variability in soil moisture makes its representation via point-scale measurements challenging, resulting in scale mismatch when compared to coarser-resolution satellite-based soil moisture or evaporation estimates. The Cosmic Ray Neutron Probe (CRNP) was developed to address such issues in the measurement and representation of soil moisture at intermediate scales. Here, we present a study to assess the utility of CRNP soil moisture observations in validating model evaporation estimates. The CRNP soil moisture product from a pasture in the semi-arid central west region of New South Wales, Australia, was compared to evaporation derived from three distinct approaches, including the Priestley–Taylor (PT-JPL), Penman–Monteith (PM-Mu), and Surface Energy Balance System (SEBS) models, driven by forcing data from local meteorological station data and remote sensing retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Pearson's correlations, quantile–quantile (Q–Q) plots, and analysis of variance (ANOVA) were used to qualitatively and quantitatively evaluate the temporal distributions of soil moisture and evaporation over the study site. The relationships were examined against nearly 2 years of observation data, as well as for different seasons and for defined periods of analysis. Results highlight that while direct correlations of raw data were not particularly instructive, the Q–Q plots and ANOVA illustrate that the root-zone soil moisture represented by the CRNP measurements and the modelled evaporation estimates reflect similar distributions under most meteorological conditions. The PT-JPL and PM-Mu model estimates performed contrary to expectation when high soil moisture and cold temperatures were present, while SEBS model estimates displayed a disconnect from the soil moisture distribution in summers with long dry spells. Importantly, no single evaporation model matched the statistical distribution of the measured soil moisture for the entire period, highlighting the challenges in effectively capturing evaporative flux response within changing landscapes. One of the outcomes of this work is that the analysis points to the feasibility of using intermediate-scale soil moisture measurements to evaluate gridded estimates of evaporation, exploiting the independent, yet physically linked nature of these hydrological variables.

Highlights

  • Land surface evaporation and soil moisture play major roles in defining the water cycle behaviour of landscapes as well as controlling the feedback from the land surface to the atmosphere at a range of spatial and temporal scales (Manfreda et al, 2007; Seneviratne et al, 2010)

  • Given that modelled evaporation estimates are generally validated against observations from eddy-covariance towers (Ershadi et al, 2014), an initial step in our study was to query the relationship between the Cosmic Ray Neutron Probe (CRNP) soil moisture retrieval and the tower-based evaporation observations

  • Relationships between soil moisture observations from a CRNP sensor and evaporation estimates derived from three distinct model structures using a combination of tower and satellite-based data were examined across a semi-arid grassland site

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Summary

Introduction

Land surface evaporation and soil moisture play major roles in defining the water cycle behaviour of landscapes as well as controlling the feedback from the land surface to the atmosphere at a range of spatial and temporal scales (Manfreda et al, 2007; Seneviratne et al, 2010). Jana et al.: Relationship between intermediate-scale soil moisture and terrestrial evaporation derived soil moisture improved model estimates of terrestrial evaporation at the continental scale. Land–atmosphere coupling studies have investigated, among others aspects, the impact of soil moisture on precipitation (Eltahir 1998; Koster et al, 2004; Schär et al, 1999) and how this knowledge can be an indicator of climate change (Seneviratne et al, 2006); the links between soil moisture and cloud cover (Betts, 2004); and how the ENSO cycle influences the coupling and the surface–atmosphere feedbacks (Miralles et al, 2014)

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