2 resultados para Rainfall simulation

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Within the scope of a comprehensive assessment of the degree of soil erosion in Switzerland, common methods have been used in the past including test plot measurements, artificial rainfall simulation, and erosion modelling. In addition, mapping guidelines for all visible erosion features have been developed since the 1970s and are being successfully applied in many research and soil conservation projects. Erosion damage has been continuously mapped over a period of 9 years in a test region in the central Bernese plateau. In 2005, two additional study areas were added. The present paper assesses the data gathered and provides a comparison of the three study areas within a period of one year (from October 2005 to October 2006), focusing on the on-site impacts of soil erosion. During this period, about 11 erosive rainfall events occurred. Average soil loss rates mapped at each study site amounted to 0.7 t ha-1, 1.2 t ha-1 and 2.3 t ha-1, respectively. About one fourth of the total arable land showed visible erosion damage. Maximum soil losses of about 70 t ha-1 occurred on individual farm plots. Average soil erosion patterns are widely used to underline the severity of an erosion problem (e.g. impacts on water bodies). But since severe rainfall events, wheel tracks, headlands, and other “singularities” often cause high erosion rates, analysis of extreme erosion patterns such as maximum values led to a more differentiated understanding and appropriate conclusions for planning and design of soil protection measures. The study contains an assessment of soil erosion in Switzerland, emphasizing questions about extent, frequency and severity. At the same time, the effects of different types of land management are investigated in the field, aiming at the development of meaningful impact indicators of (un-)sustainable agriculture/soil erosion risk as well as the validation of erosion models. The results illustrate that conservation agriculture including no-till, strip tillage and in-mulch seeding plays an essential role in reducing soil loss as compared to conventional tillage.

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Besides its primary role in producing food and fiber, agriculture also has relevant effects on several other functions, such as management of renewable natural resources. Climate change (CC) may lead to new trade-offs between agricultural functions or aggravate existing ones, but suitable agricultural management may maintain or even improve the ability of agroecosystems to supply these functions. Hence, it is necessary to identify relevant drivers (e.g., cropping practices, local conditions) and their interactions, and how they affect agricultural functions in a changing climate. The goal of this study was to use a modeling framework to analyze the sensitivity of indicators of three important agricultural functions, namely crop yield (food and fiber production function), soil erosion (soil conservation function), and nutrient leaching (clean water provision function), to a wide range of agricultural practices for current and future climate conditions. In a two-step approach, cropping practices that explain high proportions of variance of the different indicators were first identified by an analysis of variance-based sensitivity analysis. Then, most suitable combinations of practices to achieve best performance with respect to each indicator were extracted, and trade-offs were analyzed. The procedure was applied to a region in western Switzerland, considering two different soil types to test the importance of local environmental constraints. Results show that the sensitivity of crop yield and soil erosion due to management is high, while nutrient leaching mostly depends on soil type. We found that the influence of most agricultural practices does not change significantly with CC; only irrigation becomes more relevant as a consequence of decreasing summer rainfall. Trade-offs were identified when focusing on best performances of each indicator separately, and these were amplified under CC. For adaptation to CC in the selected study region, conservation soil management and the use of cropped grasslands appear to be the most suitable options to avoid trade-offs.