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Modelling soil quality changes in Europe. An impact assessment of land use change on soil quality in Europe

机译:模拟欧洲的土壤质量变化。欧洲土地利用变化对土壤质量的影响评估

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摘要

Soil is one of the most important and most complex natural resources, but current developments (urbanisation, erosion and climate change) increasingly threaten this valuable resource in Europe and worldwide. The main objective of this paper is to introduce how changes in soil quality were modelled in the SENSOR project through two indicators: soil carbon content and soil water erosion. Indicators were calculated using state variables and model variables that were mainly derived from the CLUE model which predicts land use change in response to policy scenarios. In the case of erosion, accuracy of the calculations was evaluated by comparing CIS data with the results of the PESERA project. The PESERA and SENSOR models predicted comparable soil loss for the first year in the NUTS-X regions of Europe that were analysed. The higher resolution national soil-loss prediction USLE map largely overestimated the amount of soil loss compared to the PESERA and the SENSOR models in the NUTS-X regions of Hungary. This discrepancy may result from technical or methodological differences such as the spatial reference framework (NUTS-X regions), spatial resolution or levels of data aggregation. The soil organic carbon loss predictions for the NUTS-X regions of Europe are displayed on maps and background data are given in tables. The greatest decreases in soil carbon content may be expected in some regions of Poland, Latvia, Lithuania, south-eastern UK and eastern Germany. The greatest increases in soil carbon content may be expected in central and eastern parts of the UK, in Ireland, in northern and central Sweden and Estonia, in Greece, in central and southern Italy, in the island of Sardinia and in some regions of Spain. As erosion strongly reduces soil productivity these predictions have not only environmental but also socio-economic implications. The results presented in this paper could be used at EU level to locate regions where negative changes in soil quality can be expected.
机译:土壤是最重要,最复杂的自然资源之一,但是当前的发展(城市化,侵蚀和气候变化)正日益威胁着欧洲乃至全球的这种宝贵资源。本文的主要目的是介绍如何通过两个指标(土壤碳含量和土壤水蚀)在SENSOR项目中模拟土壤质量的变化。指标是使用状态变量和模型变量计算的,这些变量主要来自于CLUE模型,该模型预测了土地用途随政策情景的变化。在侵蚀的情况下,通过将CIS数据与PESERA项目的结果进行比较来评估计算的准确性。 PESERA和SENSOR模型预测,在分析的欧洲NUTS-X地区,第一年的土壤流失相当。与匈牙利NUTS-X地区的PESERA和SENSOR模型相比,高分辨率的全国土壤流失预测USLE地图大大高估了土壤流失量。这种差异可能是由于技术或方法上的差异而引起的,例如空间参考框架(NUTS-X区域),空间分辨率或数据聚合级别。欧洲NUTS-X地区的土壤有机碳损失预测显示在地图上,背景数据列在表格中。预计波兰,拉脱维亚,立陶宛,英国东南部和德国东部的某些地区土壤碳含量将出现最大的下降。预计在英国中部和东部,爱尔兰,瑞典中部和北部和爱沙尼亚,希腊,意大利中部和南部,撒丁岛和西班牙的某些地区,土壤碳含量将增加最大。由于侵蚀严重降低了土壤生产力,因此这些预测不仅具有环境意义,而且具有社会经济意义。本文介绍的结果可用于欧盟一级的地区,以预见土壤质量可能发生负面变化的地区。

著录项

  • 来源
    《Ecological indicators》 |2011年第1期|p.4-15|共12页
  • 作者单位

    Institute for Environmental and Landscape Management, Szent Istvan University (IELM-SIU),Pater K. U. 1, 2103 Godollo. Hungary;

    rnInstitute for Environmental and Landscape Management, Szent Istvan University (IELM-SIU),Pater K. U. 1, 2103 Godollo. Hungary;

    rnInstitute for Environmental and Landscape Management, Szent Istvan University (IELM-SIU),Pater K. U. 1, 2103 Godollo. Hungary;

    rnInstitute for Environmental and Landscape Management, Szent Istvan University (IELM-SIU),Pater K. U. 1, 2103 Godollo. Hungary;

    rnInstitute for Environmental and Landscape Management, Szent Istvan University (IELM-SIU),Pater K. U. 1, 2103 Godollo. Hungary;

    Institute for Environmental and Landscape Management, Szent Istvan University (IELM-SIU),Pater K. U. 1, 2103 Godollo. Hungary;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    soil erosion; soil carbon content; sustainability; sensor project; GIS;

    机译:水土流失;土壤碳含量;可持续性;传感器项目;地理信息系统;

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