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  • 1
    In: Vadose Zone Journal, Wiley, Vol. 14, No. 4 ( 2015-04), p. 1-16
    Abstract: Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying spatial scales. The objectives of this study were to: (i) develop an efficient strategy for monitoring soil moisture dynamics at the hillslope scale using a wireless sensor network; and (ii) characterize spatial patterns of soil moisture and infer hydrological processes controlling the dynamics of such patterns, using a method of analysis that allows the identification of the relevant hydrological dynamics within large data sets. We combined soil hydrological and pedological expertise with geophysical measurements and methods from digital soil mapping for designing the monitoring setup for a grassland hillslope in the Schäfertal catchment, central Germany. Hypothesizing a wet and a dry soil moisture state to be characteristic of the spatial pattern of soil moisture, we described the spatial and temporal evolution of such patterns using a method of analysis based on the Spearman rank correlation coefficient. We described the persistence and switching mechanisms of the two characteristic states, inferring the local properties that control the observed spatial patterns and the hydrological processes driving the transitions. The spatial organization of soil moisture appears to be controlled by different processes in different soil horizons, and the topsoil's moisture does not mirror processes that take place within the soil profile. The results will help to improve conceptual understanding for hydrological model studies at similar or smaller scales and to transfer observation concepts and process understanding to larger or less instrumented areas.
    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. 1-12
    Abstract: PCA identified patterns within collocated time‐lapse measurements of θ and ECa. The factors controlling the observed spatial patterns of θ and ECa were quantified. Results demonstrate the nonstationary control of the spatial pattern of θ and ECa. Characterizing the spatial and temporal patterns of soil properties and states such as soil moisture (θ) remains an important challenge in environmental monitoring. At the Schäfertal hillslope site, the spatial patterns of θ measured by a distributed monitoring network and those of apparent electrical conductivity (ECa) measured by electromagnetic induction were characterized based on an integrated monitoring approach, and their possible controlling factors were investigated. With this study, we aimed to quantify the factors controlling the observed spatial patterns of θ and ECa and their interrelation. A principal component analysis was used to identify patterns within a data set comprising θ measured on seven dates within one hydrological year at 40 locations (three depths each) and ECa extracted from spatial maps for the same positions and dates. The first three independent principal components were all important for characterizing the spatial organization of topsoil moisture and its temporal changes. The dominant pattern responded to time‐invariant soil attributes such as spatial soil properties and terrain attributes and could explain the spatial organization of ECa only on four of the seven measurement dates. The second and third principal components described the spatial reorganization of the patterns in response to θ dynamics within the soil profile and water removal processes, respectively, and showed distinct time‐varying effects on the spatial pattern of θ and ECa. Our results can help with designing field monitoring campaigns and improving modeling approaches by providing insights into the nonstationary control of static and dynamic attributes on the spatial pattern of θ and ECa.
    Type of Medium: Online Resource
    ISSN: 1539-1663 , 1539-1663
    Language: English
    Publisher: Wiley
    Publication Date: 2017
    detail.hit.zdb_id: 2088189-7
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  • 3
    In: Land Degradation & Development, Wiley, Vol. 29, No. 9 ( 2018-09), p. 3112-3126
    Abstract: Bioeconomy strategies have been adopted in many countries around the world. Their sustainable implementation requires a management of soils that maintains soil functions and avoids land degradation. Only then, ecosystem services can be maintained and resources used efficiently. We present an analytical framework for impact assessment that links policy and technology driving forces for soil management decisions to soil processes, soil functional changes, and their impacts on ecosystem services and resource use efficiency, both being targets that have been set by society and are anchored in bioeconomy policy strategies and sustainable development goals. Although the resource use efficiency concept has a long‐term tradition, most studies of agricultural management do not address the role of soils in their efficiency assessment. The concept of ecosystem services has received increasing attention over the last years; however, its link to soil functions and soil management practices is still not well established. This study is the first to conceptually link the socioeconomic processes of external drivers for soil management with the natural processes of soil functions and connect them back to impacts on the social system. Application of the framework helps strengthen the science‐policy interface and to systemically assess and compare the opportunities and threats of soil management practices from the perspective of goals set by society at different spatial and temporal scales. Insights gained in this way can be applied in stakeholder decision‐making processes and used to inform the design of governance instruments aimed at sustainable soil management within a bioeconomy.
    Type of Medium: Online Resource
    ISSN: 1085-3278 , 1099-145X
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2018
    detail.hit.zdb_id: 2021787-0
    detail.hit.zdb_id: 1319202-4
    SSG: 14
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  • 4
    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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  • 5
    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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