Soil Moisture for Hydrological Applications: Open  Questions and New Opportunities

Brocca, Luca; Ciabatta, Luca; Massari, Christian; Camici, Stefania; Tarpanelli, Angelica

doi:10.3390/w9020140

Cited by 240 publications

(182 citation statements)

References 153 publications

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“…Also, the number of applications already using these products has grown in the last years, providing an indirect assessment of their quality. In this regard, a broad and non-exhaustive list of applications that will potentially benefit from the use of satellite soil moisture information includes hydrology [67][68][69], meteorology [70,71] and water resource management [72,73]. The reader is referred to [74] for a comprehensive review of operational applications using satellite soil moisture retrievals.…”

Section: Operational Retrievals Of Ssm From Eomentioning

confidence: 99%

Earth Observation-Based Operational Estimation of Soil Moisture and Evapotranspiration for Agricultural Crops in Support of Sustainable Water Management

et al. 2018

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Abstract:Global information on the spatio-temporal variation of parameters driving the Earth's terrestrial water and energy cycles, such as evapotranspiration (ET) rates and surface soil moisture (SSM), is of key significance. The water and energy cycles underpin global food and water security and need to be fully understood as the climate changes. In the last few decades, Earth Observation (EO) technology has played an increasingly important role in determining both ET and SSM. This paper reviews the state of the art in the use specifically of operational EO of both ET and SSM estimates. We discuss the key technical and operational considerations to derive accurate estimates of those parameters from space. The review suggests significant progress has been made in the recent years in retrieving ET and SSM operationally; yet, further work is required to optimize parameter accuracy and to improve the operational capability of services developed using EO data. Emerging applications on which ET/SSM operational products may be included in the context specifically in relation to agriculture are also highlighted; the operational use of those operational products in such applications remains to be seen.

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Section: Operational Retrievals Of Ssm From Eomentioning

confidence: 99%

Earth Observation-Based Operational Estimation of Soil Moisture and Evapotranspiration for Agricultural Crops in Support of Sustainable Water Management

et al. 2018

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“…The variability of the near‐surface atmospheric conditions (e.g., humidity, dust particles, and temperature profiles) have demonstrated high correlation with extreme climate events such as droughts, dust outbreaks, floods, and wildfires. In addition, soil moisture plays an indirect but important role is that latent and sensible heat fluxes are controlled by surface soil moisture, which affects boundary layer stability and low‐altitude atmospheric conditions (Brocca et al, ; Crow et al, ; Delworth & Manabe, ; Haarsma et al, ; Kim et al, ). Even though surface soil moisture can be decoupled from root‐zone soil moisture over dry‐environment conditions (Hirschi et al, ), surface soil moisture can be a good indicator of the variability of deeper soil moisture in many cases (Choi & Jacobs, ; Dong & Crow, ; Qiu et al, ; Zohaib et al, ).…”

Section: Introductionmentioning

confidence: 99%

Global Dynamics of Stored Precipitation Water in the Topsoil Layer From Satellite and Reanalysis Data

Kim

Lakshmi

2019

Water Resources Research

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The amount of soil water in the topsoil layer (from 0 to 10 cm) has been regarded as a key factor in controlling land‐atmosphere interaction by determining the fraction of net radiation. In the present study, we investigate spatial trends of the stored precipitation fraction in the topsoil layer for varying vegetation and aridity indices by utilizing four satellites and two reanalysis data sets on a global scale. Using the Budyko framework, we relate climate regimes to the stored precipitation fraction on a global scale. A positive relation between the stored precipitation fraction with aridity index and a negative relation between the stored precipitation fraction and free parameter, vegetation optical depth, and isohydric slope are discovered. Even though the stored precipitation fraction values were calculated from different soil moisture and precipitation sources, they share an similar spatial trend: the drier and less vegetated the soil is, the more precipitation is retained in the top layer of the soil. Specifically, the topsoil retains 37% ± 11% of precipitated water three days after a rainfall event where the aridity index was greater than 5. Over wet and forest areas, due to large runoff fluxes and plants intercepting water before the precipitated water reached the ground, the topsoil retains 21% ± 2% of precipitated water three days after a rainfall event. Furthermore, by using the modeled data sets in the calculation of the stored precipitation fraction metric, we are able to conduct a sensitivity analysis of FP(f) metrics with respect to different sampling frequency values.

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“…Although recent decades have seen great advances in remote sensing applications for mapping surface soil moisture (Jackson, 1993;Njoku et al, 2003;Mohanty et al, 2017), most hydrological studies that make use of soil moisture data require integrated values over a certain soil depth (Brocca et al, 2017). Extrapolation of surface soil moisture from remote sensing techniques to depths beyond the sensor's capacity (up to 5 cm) is not a trivial task given the spatiotemporal variability of soil moisture.…”

Section: Introductionmentioning

confidence: 99%

Using lagged dependence to identify (de)coupled surface and subsurface soil moisture values

Carranza

Ploeg

Torfs

2018

Hydrol. Earth Syst. Sci.

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Abstract. Recent advances in radar remote sensing popularized the mapping of surface soil moisture at different spatial scales. Surface soil moisture measurements are used in combination with hydrological models to determine subsurface soil moisture values. However, variability of soil moisture across the soil column is important for estimating depthintegrated values, as decoupling between surface and subsurface can occur. In this study, we employ new methods to investigate the occurrence of (de)coupling between surface and subsurface soil moisture. Using time series datasets, lagged dependence was incorporated in assessing (de)coupling with the idea that surface soil moisture conditions will be reflected at the subsurface after a certain delay. The main approach involves the application of a distributed-lag nonlinear model (DLNM) to simultaneously represent both the functional relation and the lag structure in the time series. The results of an exploratory analysis using residuals from a fitted loess function serve as a posteriori information to determine (de)coupled values. Both methods allow for a range of (de)coupled soil moisture values to be quantified. Results provide new insights into the decoupled range as its occurrence among the sites investigated is not limited to dry conditions.

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Soil Moisture for Hydrological Applications: Open Questions and New Opportunities

Cited by 240 publications

References 153 publications

Earth Observation-Based Operational Estimation of Soil Moisture and Evapotranspiration for Agricultural Crops in Support of Sustainable Water Management

Earth Observation-Based Operational Estimation of Soil Moisture and Evapotranspiration for Agricultural Crops in Support of Sustainable Water Management

Global Dynamics of Stored Precipitation Water in the Topsoil Layer From Satellite and Reanalysis Data

Using lagged dependence to identify (de)coupled surface and subsurface soil moisture values

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