Temporal stability of surface soil moisture in the Little Washita River watershed and its applications in satellite soil moisture product validation

Cosh, Michael H.; Jackson, Thomas J.; Starks, Patrick J.; Heathman, Gary C.

doi:10.1016/j.jhydrol.2005.08.020

Cited by 195 publications

(180 citation statements)

References 25 publications

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“…These findings have corroborating the findings of [33][34][35] i.e. that deviations are usually increasing with decreasing mean soil moisture content.…”

Section: Calculation Of Standard Errors Significance Levels and Optisupporting

confidence: 90%

Analysis of spatial variability of near-surface soilmoisture to increase rainfall-runoff modellingaccuracy in SW Hungary

et al. 2015

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Between September 5, 2008 and September 5, 2009, near-surface soil moisture time series were collected in the northern part of a 1.7 km2 watershed in SW Hungary at 14 monitoring locations using a portable TDR-300 soil moisture sensor. The objectives of this study are to increase the accuracy of soil moisture measurement at watershed scale, to improve flood forecasting accuracy, and to optimize soil moisture sensor density. According to our results, in 10 of 13 cases, a strong correlation exists between the measured soil moisture data of Station 5 and all other monitoring stations; Station 5 is considered representative for the entire watershed. Logically, the selection of the location of the representative measurement point(s) is essential for obtaining representative and accurate soil moisture values for the given watershed. This could be done by (i) employing monitoring stations of higher number at the exploratory phase of the monitoring, (ii) mapping soil physical properties at watershed scale, and (iii) running cross-relational statistical analyses on the obtained data. Our findings indicate that increasing the number of soil moisture data points available for interpolation increases the accuracy of watershed-scale soil moisture estimation. The data set used for interpolation (and estimation of mean antecedent soil moisture values) could be improved (thus, having a higher number of data points) by selecting points of similar properties to the measurement points from the DEM and soil databases. By using a higher number of data points for interpolation, both interpolation accuracy and spatial resolution have increased for the measured soil moisture values for the Pósa Valley.

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“…These findings have corroborating the findings of [33][34][35] i.e. that deviations are usually increasing with decreasing mean soil moisture content.…”

Section: Calculation Of Standard Errors Significance Levels and Optisupporting

confidence: 90%

Analysis of spatial variability of near-surface soilmoisture to increase rainfall-runoff modellingaccuracy in SW Hungary

et al. 2015

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“…It therefore measures the long-term average water content in a profile or catchment and the average deviation in horizon or profile water content from that average. Recent studies applying temporal stability of spatially measured soil water contents to study soil-water relationships are: Vachaud et al (1985), Comegna and Basile (1994), Gómez-Plaza et al (2000), Cosh et al (2004), Martínez-Fernández and Ceballos (2005), Cosh et al (2006), Lin (2006) and Starks et al (2006).…”

Section: Hydrology Of Soil Typesmentioning

confidence: 99%

“…Temporal stability also offers a valuable tool in monitoring site selection (Comegna & Basile, 1994;Ferreyra et al, 2002;Grant et al, 2004;Martínez-Fernández & Ceballos, 2005;Cosh et al, 2006;Starks et al, 2006). This is especially true as mechanistic hydrological models, necessary for solute and sediment transport models drive the need for an increased understanding of the direction and velocity of subsurface water flow (Lin, 2006).…”

Section: Hydrology Of Soil Typesmentioning

confidence: 99%

“…At small scales differences in local topography determine temporal stability. Most temporal stability studies seem to have been made in very small (<50 ha) areas (Comegna & Basile, 1994;Van Pelt & Wierenga, 2001;Lin, 2006), or in very large (>100 km 2 ) areas (Cosh et al, 2004;Martínez-Fernández & Ceballos, 2005;Cosh et al, 2006;Starks et al, 2006), or by utilizing relatively short durations of water content measurements (Van Pelt & Wierenga, 2001;Cosh et al, 2006;Lin 2006).…”

Section: Hydrology Of Soil Typesmentioning

confidence: 99%

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A review of advances in hydropedology for application in South Africa

Huyssteen

2008

South African Journal of Plant and Soil

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Hydropedology is internationally a new and fast-growing science. It is therefore pertinent to take heed of developments in this regard to guide current and future research in South Africa. This paper aims to discuss the initiation and advances in the interdisciplinary science of hydropedology. Hydropedology has been defined to interlink pedology, soil physics, and hydrology to bridge scales and to transform soil survey data into soil hydraulic information. As such hydropedology could contribute to the understanding of various environmental and ecological issues. In this regard pedotransfer functions relate simple soil characteristics (e.g. morphological features) to more complex parameters (e.g. soil hydraulic properties) that are relatively difficult to measure. The hydrology of soil types (HOST), published in the United Kingdom to aid hydrological studies and analyses, is a good working example of a pedotransfer function. HOST is based on three conceptual models of water flow processes in the soil: soil on a permeable substrate with a deep aquifer (>2 m); soil on permeable substrate with a shallow water table (<2 m); and soil with an impermeable or semi permeable layer within 1 m of the surface. The three conceptual models are further subdivided into 11 models, which can be subdivided into 29 HOST classes. A useful tool for the summation of long-term soil water content data is the temporal stability of spatially measured soil water contents which is defined as the time invariant average of spatially measured soil water contents and offers a valuable method to study the relationship between soil and water. It has been used to reduce the number of measurements needed in catchment characterization and is therefore also a valuable tool in site selection. Understanding redox reactions in soil and the influence thereof on the development of redoximorphic colour patterns, are vital in discerning the relationship between soil water regime and soil morphology. Redoximorphic colour patterns are manifested as redox depletions and/or redox accumulations. The former is evident as grey matrices, cutans, mottles, or pore linings, while the latter is evident as Fe masses, pore linings, nodules, or concretions.

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“…Grayson and Western (1998) referred to these locations as catchment average soil moisture monitoring (CASMM) sites. Many other researchers have performed related work by either attempting to estimate a catchment-wide spatial average soil moisture using point-scale observations from a limited number of locations (Brocca et al, 2009;Martinez-Fernandez and Ceballos, 2005) or by attempting to validate coarse-resolution remote sensing estimates by upscaling point soil moisture observations (Cosh et al, 2008;Cosh et al, 2006;Crow et al, 2012;Crow et al, 2005).…”

mentioning

confidence: 99%

Evaluation of sampling techniques to characterize topographically-dependent variability for soil moisture downscaling

Werbylo

Niemann

2014

Journal of Hydrology

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EVALUATION OF SAMPLING TECHNIQUES TO CHARACTERIZE TOPOGRAPHICALLY-DEPENDENT VARIABILITY FOR SOIL MOISTURE DOWNSCALINGSoil moisture patterns are an important consideration in many catchment-scale hydrologic applications. Unfortunately, estimating soil moisture patterns at resolutions that are appropriate for these applications (e.g., grid cells with a linear dimension of 10 to 50 m) is difficult. Downscaling methods can be used to estimate catchment-scale soil moisture patterns from coarser resolution estimates or spatial average soil moisture values. These methods usually infer the fine-scale variability in soil moisture using variations in ancillary variables like topographic attributes that have relationships to soil moisture. Previously, such relationships have been observed in catchments using soil moisture observations taken on uniform grids at hundreds of locations on multiple dates, but collecting data in this manner limits the applicability of this approach. The objective of this paper is to evaluate the effectiveness of two strategic sampling techniques for characterizing the relationships between topographic attributes and soil moisture for the purpose of constraining downscaling methods. The strategic sampling methods considered are conditioned Latin hypercube sampling (cLHS) and stratified random sampling (SRS). Each sampling method is used to select a limited number of locations and/or dates for soil moisture monitoring at three catchments with detailed soil moisture datasets (Tarrawarra, Satellite Station, and Cache la Poudre). These samples are then used to calibrate two available downscaling methods, and the effectiveness of the sampling methods is evaluated by the ability iii of the downscaling methods to reproduce the known soil moisture patterns at the catchments.The results show that cLHS and SRS can characterize the relationships between soil moisture and ancillary topographic variables with many fewer locations and dates than previously used.

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Temporal stability of surface soil moisture in the Little Washita River watershed and its applications in satellite soil moisture product validation

Cited by 195 publications

References 25 publications

Analysis of spatial variability of near-surface soilmoisture to increase rainfall-runoff modellingaccuracy in SW Hungary

Analysis of spatial variability of near-surface soilmoisture to increase rainfall-runoff modellingaccuracy in SW Hungary

A review of advances in hydropedology for application in South Africa

Evaluation of sampling techniques to characterize topographically-dependent variability for soil moisture downscaling

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