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991.
The EPIC (Erosion Productivity Impact Calculator) crop model, developed by scientists of the United States Department of Agriculture (USDA), has been successfully applied to the study of erosion, water pollution, crop growth and production in the US but is yet to be introduced for serious research purposes in other countries or regions. This paper reports on the applicability of the EPIC 8120 crop model for the assessment of the potential impacts of climate variability and climate change on crop productivity in sub‐Saharan West Africa, using Nigeria as the case study. Among the crops whose productivity has been successfully simulated with this model are five of West Africa's staple food crops: maize, millet, sorghum (guinea corn), rice and cassava. Thus, using the model, the sensitivities of maize, sorghum and millet to seasonal rainfall were demonstrated with coefficients of correlation significant at over 98 per cent confidence limits. The validation tests were based on a comparison of the observed and the model‐generated yields of rice and maize. The main problems of validation relate to the multiplicity of crop varieties with contrasting performances under similar field conditions. There are also the difficulties in representing micro‐environments in the model. Thus, some gaps appear between the observed and the simulated yields, arising from data or model deficiencies, or both. Based on the results of the sensitivity and validation tests, the EPIC crop model could be satisfactorily employed in assessing the impacts of and adaptations to climate variability and climate change. Its use for the estimation of production and the assessment of vulnerabilities need to be pursued with further field surveys and field experimentation.  相似文献   
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The aim of this paper is to investigate the feasibility of using Landsat TM data to retrieve leaf area index (LAI). To get a LAI retrieval model based ground reflectance and vegetation index, detailed field data were collected in the study area of eastern China, dominated by bamboo, tea plant and greengage. Plant canopy reflectance of Landsat TM wavelength bands has been inversed using software of 6S. LAI is an important ecological parameter. In this paper, atmospheric corrected Landsat TM imagery was utilized to calculate different vegetation indices (VI), such as simple ratio vegetation index (SR), shortwave infrared modified simple ratio (MSR), and normalized difference vegetation index (NDVI). Data of 53 samples of LAI were measured by LAI-2000 (LI-COR) in the study area. LAI was modeled based on different reflectances of bands and different vegetation indices from Landsat TM and LAI samples data. There are certainly correlations between LAI and the reflectance of Tm3, TM4, TM5 and TM7. The best model through analyzing the results is LAI = 1.2097*MSR + 0.4741 using the method of regression analysis. The result shows that the correlation coefficient R2 is 0.5157, and average accuracy is 85.75%. However, whether the model of this paper is suitable for application in subtropics needs to be verified in the future.  相似文献   
998.
From water to tillage erosion dominated landform evolution   总被引:3,自引:1,他引:3  
While water and wind erosion are still considered to be the dominant soil erosion processes on agricultural land, there is growing recognition that tillage erosion plays an important role in the redistribution of soil on agricultural land. In this study, we examined soil redistribution rates and patterns for an agricultural field in the Belgian loess belt. 137Cs derived soil erosion rates have been confronted with historical patterns of soil erosion based on soil profile truncation. This allowed an assessment of historical and contemporary landform evolution on agricultural land and its interpretation in relation to the dominant geomorphic process. The results clearly show that an important shift in the relative contribution of tillage and water erosion to total soil redistribution on agricultural land has occurred during recent decades. Historical soil redistribution is dominated by high losses on steep midslope positions and concavities as a result of water erosion, leading to landscape incision and steepening of the topography. In contrast, contemporary soil redistribution is dominated by high losses on convex upperslopes and infilling of slope and valley concavities as a result of tillage, resulting in topographic flattening. This shift must be attributed to the increased mechanization of agriculture during recent decades. This study shows that the typical topographical dependency of soil redistribution processes and their spatial interactions must be accounted for when assessing landform and soil profile evolution.  相似文献   
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Optimal parametrization of tomographic models   总被引:1,自引:0,他引:1  
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