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  • Wiley  (2)
  • Paasche, Hendrik  (2)
  • 2015-2019  (2)
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  • Wiley  (2)
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  • 2015-2019  (2)
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  • 1
    In: Vadose Zone Journal, Wiley, Vol. 14, No. 11 ( 2015-11), p. 1-16
    Abstract: Accurate characterization of spatial soil moisture patterns and their temporal dynamics is important to infer hydrological fluxes and flow pathways and to improve the description and prediction of hydrological models. Recent advances in ground‐based and remote sensing technologies provide new opportunities for temporal information on soil moisture patterns. However, spatial monitoring of soil moisture at the small catchment scale (0.1–1 km 2 ) remains challenging and traditional in situ soil moisture measurements are still indispensable. This paper presents a strategic soil moisture sampling framework for a low‐mountain catchment. The objectives were to: (i) find a priori a representative number of measurement locations, (ii) estimate the soil moisture pattern on the measurement date, and (iii) assess the relative importance of topography for explaining soil moisture pattern dynamics. The fuzzy c‐means sampling and estimation approach (FCM SEA) was used to identify representative measurement locations for in situ soil moisture measurements. The sampling was based on terrain attributes derived from a digital elevation model (DEM). Five time‐domain reflectometry (TDR) measurement campaigns were conducted from April to October 2013. The TDR measurements were used to calibrate the FCM SEA to estimate the soil moisture pattern. For wet conditions the FCM SEA performed better than under intermediate conditions and was able to reproduce a substantial part of the soil moisture pattern. A temporal stability analysis shows a transition between states characterized by a reorganization of the soil moisture pattern. This indicates that, at the investigated site, under wet conditions, topography is a major control that drives water redistribution, whereas for the intermediate state, other factors become increasingly important.
    Type of Medium: Online Resource
    ISSN: 1539-1663 , 1539-1663
    Language: English
    Publisher: Wiley
    Publication Date: 2015
    detail.hit.zdb_id: 2088189-7
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  • 2
    In: Vadose Zone Journal, Wiley, Vol. 16, No. 10 ( 2017-10), p. 1-21
    Abstract: The FCM SEA was used for sampling and spatial estimation of soil moisture patterns. Multispectral remote sensing and terrain data were combined to guide the sampling and estimation. Selected vegetation patterns and terrain data provided reasonable estimates of soil moisture. The FCM SEA was stable to explain about 50% of the total observed variance. The FCM SEA was superior to an approach driven solely by terrain data. Detailed information on the temporal and spatial evolution of soil moisture patterns is of fundamental importance to improve runoff prediction, optimize irrigation management and to enhance crop forecasting. However, obtaining representative soil moisture measurements at the catchment scale is challenging because of the dynamic spatial and temporal behavior of soil moisture. High‐resolution remote sensing data provide detailed spatial information about catchment characteristics (e.g., terrain and land use) that can be used as proxies to estimate soil moisture. We assessed the potential use of combined multitemporal multispectral remote sensing (RS) and terrain data for estimating spatial soil moisture patterns at the small catchment scale. The fuzzy c ‐means sampling and estimation approach (FCM SEA) was applied to conduct a sensor (proxy) directed (guided) sampling and to reconstruct multitemporal soil moisture patterns based on time domain reflectometry measurements. A comprehensive soil moisture database for the Schäfertal catchment, located in central Germany, was used to test, validate, and compare the FCM SEA performances of the combined remote sensing data with those of a benchmark approach driven solely by terrain data. Results from the study show that a FCM SEA model that integrates bi‐temporal RS imagery and terrain data was more effective in estimating spatial soil moisture patterns relative to the benchmark model. It outperformed the benchmark model in 58% of the cases and was stable to explain about 50% of the total observed variance for a range of different catchment moisture conditions. This was achieved with only a small sample size ( n = 30). The results of this study are promising because they highlight the importance of considering multitemporal RS and terrain data and demonstrate how in situ sensors can be optimally placed to enable cost‐efficient monitoring and prediction of spatial soil moisture patterns at the small catchment scale.
    Type of Medium: Online Resource
    ISSN: 1539-1663 , 1539-1663
    Language: English
    Publisher: Wiley
    Publication Date: 2017
    detail.hit.zdb_id: 2088189-7
    Library Location Call Number Volume/Issue/Year Availability
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