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Soil and water conservation are cross-sectional assignments. The respective objectives of the individual interest groups cause conflicts of use and lead to different assessments of the soil's potential. Necessary decisions and the practical implementation of soil and water conservation measures require the use of data. These data, which are both spatial and temporal, characterise past, present and, in the case of predictions, also future environmental conditions. The multitude of relevant data necessitates the use of geographic information systems as an instrument for successful resource management. With the use of problem-oriented case studies, it was possible to show that an improved understanding of the system is necessary for both optimisation of the site-specific resource management within the framework of Precision Farming and for the assessment of local to regional conflicts of use with regard to land usage and soil and water conservation. By changing the method, sufficient respective measures regarding documentation, prevention and risk assessment were able to be introduced and implemented. With the objective of practical implementation of a sustainable resource management, the possibilities of short- to long-term initiation of self-organised systems through the networking of available (geo-)information as well as the respective interest groups involved in the conflict of use formed the focal point of this investigation. The creation of networks linking agriculture, water extractors and nature conservation promotes necessary synergies and emergences, due to increased communication. Not the conveyance of knowledge alone, but rather new forms of understanding cause the interest groups involved to change their behaviour, thus facilitating efficient resource management for the interests of soil and water conservation.
Considering actual climatic and land use changes the problem of available water resources or the estimation of potential flood risks gain eco-political and economical relevance. Adequate assessments, thus, require precise process-based hydrological knowledge. Spatially distributed hydrological modelling enables a both abstractive and realistic description of hydrological processes, and therefore contributes to the understanding of the hydrological system- responses. Referring to the example of the mesoscale Ruwer basin (a tributary to the Mosel river), a modified version of the distributive modelling system PRMS/MMS (Precipitation Runoff Modeling System/Modular Modeling System) is applied to calculate spatially and temporally explicit water budgets. To achieve modelling results as precise as possible, integration of detailed land use information (spatial distribution of the existing land use classes, crop- and site-specific growth patterns) is necessary. This information is derived here by analysis of multitemporal, geometrically and radiometrically pre-processed Landsat TM-data. This enables separation of different land use classes and differentiated quantification of the leaf area index (LAI). The LAI is estimated by a spectral unmixing approach using statistically optimized endmember sets, referring to the example of winter grain and grassland plots. As a result, numerical inputs (coefficients for calculating evapotranspiration, interception storages) and extracted non-numerical (classified) information can be provided for hydrological modelling. The version of PRMS applied in this study allows important land use terms to be parameterized in high temporal resolution. Using model input derived from the available satellite data, simulation results are obtained that prove to be realistic compared to gauge data and with respect to their spatial differentiation. Results differ significantly from those obtained by using parameters from literature or by experience without distinguishing specific and site-dependent growth patterns. It can be concluded that the quality of modelling results notably improves by integration and quantitative analysis of remote sensing data; thus, these methods are a significant contribution to physically-based hydrological modelling.
