匈牙利降雨侵蚀力变化的估计

G. Mezősi, Teodóra Bata
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引用次数: 12

摘要

摘要:根据许多区域模式(如。REMO, ALADIN, PREGIS),预测降雨事件的数量减少,但它们并不伴随着明显的降水减少。它代表了降雨强度的增加。合乎逻辑的问题是(如果模型的局限性使之成为可能的话)降雨强度可能改变到什么程度,从长远来看,这些变化可能发生在哪里。降雨强度被认为是土壤侵蚀的主要原因之一。如果我们知道哪些地区受到更强烈的雨蚀影响,我们就可以确定哪些地区可能受到更强烈的水土流失影响,我们也可以选择有效的措施来减少侵蚀。这些信息对于实现欧盟所设定的中性侵蚀效果是必要的。我们收集了2000 - 2013年4个站点每30分钟的降水数据,并计算了喀尔巴阡盆地特征的估计强度水平。基于这些数据,我们计算了强度测量数据与MFI指数值的相关性(相关系数为0.75)。根据区域气候模式组合,可以估计到2100年的降水数据,并通过计算前期相关与该数据序列的统计关系,可以估计降水强度的时空变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimation of the Changes in the Rainfall Erosivity in Hungary
Abstract According to the forecasts of numerous regional models (eg. REMO, ALADIN, PREGIS), the number of predicted rainfall events decreases, but they are not accompanied by considerably less precipitation. It represents an increase in rainfall intensity. It is logical to ask (if the limitations of the models make it possible) to what extent rainfall intensity is likely to change and where these changes are likely to occur in the long run. Rain intensity is considered to be one of the key causes of soil erosion. If we know which areas are affected by more intense rain erosion, we can identify the areas that are likely to be affected by stronger soil erosion, and we can also choose effective measures to reduce erosion. This information is necessary to achieve the neutral erosion effect as targeted by the EU. We collected the precipitation data of four stations every 30 minute between 2000 and 2013, and we calculated the estimated level of intensity characterizing the Carpathian Basin. Based on these data, we calculated the correlation of the measured data of intensity with the values of the MFI index (the correlation was 0.75). According to a combination of regional climate models, precipitation data could be estimated until 2100, and by calculating the statistical relationship between the previous correlation and this data sequence, we could estimate the spatial and temporal changes of rainfall intensity.
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