Analysis of surface moisture variations within large‐field sites

Bell, K. R.; Blanchard, B. J.; Schmugge, Thomas J.; Witczak, M W

doi:10.1029/wr016i004p00796

Cited by 173 publications

(141 citation statements)

References 7 publications

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“…2). This result was not consistent with previous findings that heavier rains and higher mean moisture content were often associated with higher variability (Bell et al, 1980;Famiglietti et al, 1998). A possible explanation is that land use reported by them is uniform, whereas we examine multiple land uses in our study.…”

Section: Methodscontrasting

confidence: 56%

The effects of land use on soil moisture variation in the Danangou catchment of the Loess Plateau, China

Wang

Chen

et al. 2003

CATENA

255

118

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Soil moisture plays a critical role in both crop growth and vegetation restoration in semiarid environments. Its spatial and temporal variability results from topography, soils, vegetation and land uses. However, little knowledge exists about the effects of land use structure on soil moisture variability. In order to analyze soil moisture variations in relation to land use patterns, five land use structures and seven land use types were selected to monitor soil moisture. Soil moisture measurements were performed biweekly at 26 locations in a small catchment on the Loess Plateau of China from May to October 1998. The measurements were taken using a Theta-Probe at five depths of soil profile (0 -5, 15 -20, 25 -30, 45 -50 and 70 -75 cm). These data were analyzed for soil moisture variations in space and time for seven land use types. Three peaks and three troughs of soil moisture variations during the growing season were found. The influence of shrubland on mean soil moisture within 0 -70 cm was significantly different from that of cropland, orchard and intercropping land. Three types of soil moisture changes in profile were classified as increasing, decreasing and waving types. An analysis of the differences in soil moisture for five land use structures indicated that the influences of land use patterns on soil moisture were complex. This study provides an insight into the implications for hydrological modeling, runoff and erosion control in this area. D

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Section: Methodscontrasting

confidence: 56%

The effects of land use on soil moisture variation in the Danangou catchment of the Loess Plateau, China

Wang

Chen

et al. 2003

CATENA

255

118

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“…Other early reports on extensive studies of soil moisture variability were made by Bell et al (1980) and Hawley et al (1983). Several authors have noted that, despite the large spatial variability, the soil moisture patterns themselves remain relatively stable over time (e.g.…”

Section: Introductionmentioning

confidence: 99%

Estimating spatial mean root-zone soil moisture from point-scale observations

Teuling

Uijlenhoet

Hupet

et al. 2006

Hydrol. Earth Syst. Sci.

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Abstract. Root zone soil moisture is a key variable in many land surface hydrology models. Often, however, there is a mismatch in the spatial scales at which models simulate soil moisture and at which soil moisture is observed. This complicates model validation. The increased availability of detailed datasets on space-time variability of root-zone soil moisture allows for a posteriori analysis of the uncertainties in the relation between point-scale observations and the spatial mean. In this paper we analyze three comprehensive datasets from three different regions. We identify different strategies to select observation sites. For instance, sites can be located randomly or according to the rank stability concept. For each strategy, we present methods to quantify the uncertainty that is associated with this strategy. In general there is a large correspondence between the different datasets with respect to the relative uncertainties for the different strategies. For all datasets, the uncertainty can be strongly reduced if some information is available that relates soil moisture content at that site to the spatial mean. However this works best if the space-time dynamics of the soil moisture field are known. Selection of the site closest to the spatial mean on a single random date only leads to minor reduction of the uncertainty with respect to the spatial mean over seasonal timescales. Since soil moisture variability is the result of a complex interaction between soil, vegetation, and landscape characteristics, the soil moisture field will be correlated with some of these characteristics. Using available information, we show that the correlation with leaf area index or a wetness coefficient alone is insufficient to predict if a site is representative for the spatial mean soil moisture content.

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“…The coefficient of the variation of each sampling day, CVj, is calculated as follows [29,[51][52][53]:…”

Section: Spatiotemporal Characteristics and Assessment Of Spatiotempomentioning

confidence: 99%

Optimal Nodes Selectiveness from WSN to Fit Field Scale Albedo Observation and Validation in Long Time Series in the Foci Experiment Areas, Heihe

Xiao

Wen

et al. 2015

Remote Sensing

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Abstract:To evaluate and improve the quality of land surface albedo products, validation with ground measurements of albedo is crucial over the spatially and temporally heterogeneous land surface. One of the essential steps for satellite albedo product validation is coarse scale observation technique development with long time ground-based measurements. In this paper, the optimal nodes were selected from the wireless sensor network (WSN) to perform observation at large scale and in longer time series for validation of albedo products. The relative difference is used to analyze the spatiotemporal representativeness of each node. The random combination method is used to assess the number of required sites (NRS) and then to identify the most representative combination (MRC). On this basis, an upscaling OPEN ACCESS Remote Sens. 2015, 7 14758 transform function with different weights for each node in the MRC, which are calculated with the ordinary least squares (OLS) linear regression method, is used to upscale WSN node albedo from point scale to the field scale. This method is illustrated by selecting the optimal nodes and upscaling surface albedo from point observation to the field scale in the Heihe River basin, China. Primary findings are: (a) The method of reducing the number of observations without significant loss of information about surface albedo at field scale is feasible and effective; (b) When only few sensors are available, the most representative locations in time and space should be the first priority; when a number of sensors are available in the heterogeneous land surface, it is preferable to install them in different land surface, rather than the most representative locations; (c) The most representative combination (MRC) combined with the upscaling weight coefficients can give a robust estimate of the field mean surface albedo. These efforts based on ground albedo observations promote the chance to use point information for validation of coarse scale albedo products. Moreover, a preliminary validation of the MODIS (Moderate Resolution Imaging Spectroradiometer) albedo product was performed as the tentative application for upscaling predictions.

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Analysis of surface moisture variations within large‐field sites

Cited by 173 publications

References 7 publications

The effects of land use on soil moisture variation in the Danangou catchment of the Loess Plateau, China

The effects of land use on soil moisture variation in the Danangou catchment of the Loess Plateau, China

Estimating spatial mean root-zone soil moisture from point-scale observations

Optimal Nodes Selectiveness from WSN to Fit Field Scale Albedo Observation and Validation in Long Time Series in the Foci Experiment Areas, Heihe

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