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1000
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Abstract/Summary
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<jats:p>Abstract. There is an urgent need to develop sustainable agricultural land use schemes. Intensive crop production has induced increased greenhouse gas emissions and enhanced nutrient and pesticide leaching to groundwater and streams. Climate change is also expected to increase drought risk as well as the frequency of extreme precipitation events in many regions. Consequently, sustainable management schemes require sound knowledge of site-specific soil water processes that explicitly take into account the interplay between soil heterogeneities and crops. In this study, we applied a principal component analysis to a set of 64 soil moisture time series from a diversified cropping field featuring seven distinct crops and two weeding management strategies. Results showed that about 97 % of the spatial and temporal variance of the data set was explained by the first five principal components. Meteorological drivers accounted for 72.3 % of the variance and 17.0 % was attributed to different seasonal behaviour of different crops. While the third (4.1 %) and fourth (2.2 %) principal components were interpreted as effects of soil texture and cropping schemes on soil moisture variance, respectively, the effect of soil depth was represented by the fifth component (1.7 %). However, neither topography nor weed control had a significant effect on soil moisture variance. Contrary to common expectations, soil and rooting pattern heterogeneity seemed not to play a major role. Findings of this study highly depend on local conditions. However, we consider the presented approach generally applicable to a large range of site conditions.
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1000
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Hinweis
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DeepGreen-ID: 69668f116c2f443aad064288d7e28e6f ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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