Scholarlink

<p>The SCS-CN approach constitutes a straightforward, reliable, and consistent approach for estimating runoff from precipitation events. In the present work we introduce the CN-panEU, an innovative online tool (<a href="http://cn-paneu.survey.ntua.gr/main.html">http://cn-paneu.survey.ntua.gr/main.html</a>) for CN data collection throughout European countries. The pan-European CN gridded dataset was developed based on the Harmonized World Soil Database (HWSD) and the land use/land cover data from the Corine Land Cover (2018). The CN was estimated using ArcMap 10.5.1, based on the hydrologic soil group category, the Corine land cover and the tabulated CN values reported by SCS (<CitationRef CitationID="CR36">1972</CitationRef>). The CN values vary according to the Antecedent Moisture Conditions (AMC), thus three datasets were developed, i.e., for AMC I (dry conditions), AMC II (average conditions) and AMC III (wet conditions), respectively. The dataset covers 38 European countries. The CN values for ten river basins across Europe, estimated with the CN-panEU, were compared to the CN values reported and estimated using the GCN250 dataset. GCN250 dataset is a global dataset developed by Jaafar et al. (<CitationRef CitationID="CR16">2019</CitationRef>) based on the Hydrological Soils Group dataset developed by Ross et al. (<CitationRef CitationID="CR35">2018</CitationRef>) and the global land cover data developed by the European Space Agency (2015). Our results revealed that the newly proposed dataset is in good agreement with the GCN250 dataset and the main differences can be attributed to different soil groups and land cover data. Overall, the CN-panEU dataset and the application can be potentially applied in hydrologic design, land management, flood risk assessment, and groundwater recharge modeling.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

An online tool and open database for curve number (CN) data retrieval in Europe used for estimating runoff from precipitation events

  • 期刊论文

  • 发表日期：

    2025年11月1日

查看全文
  • Ioannis M. Kourtis,
  • Martha Perdikaki,
  • Ioannis Zacharakis,
  • Ioanna Zotou,
  • Harris Vangelis,
  • Andreas Kallioras,
  • Vassilios A. Tsihrintzis

摘要

The SCS-CN approach constitutes a straightforward, reliable, and consistent approach for estimating runoff from precipitation events. In the present work we introduce the CN-panEU, an innovative online tool (http://cn-paneu.survey.ntua.gr/main.html) for CN data collection throughout European countries. The pan-European CN gridded dataset was developed based on the Harmonized World Soil Database (HWSD) and the land use/land cover data from the Corine Land Cover (2018). The CN was estimated using ArcMap 10.5.1, based on the hydrologic soil group category, the Corine land cover and the tabulated CN values reported by SCS (1972). The CN values vary according to the Antecedent Moisture Conditions (AMC), thus three datasets were developed, i.e., for AMC I (dry conditions), AMC II (average conditions) and AMC III (wet conditions), respectively. The dataset covers 38 European countries. The CN values for ten river basins across Europe, estimated with the CN-panEU, were compared to the CN values reported and estimated using the GCN250 dataset. GCN250 dataset is a global dataset developed by Jaafar et al. (2019) based on the Hydrological Soils Group dataset developed by Ross et al. (2018) and the global land cover data developed by the European Space Agency (2015). Our results revealed that the newly proposed dataset is in good agreement with the GCN250 dataset and the main differences can be attributed to different soil groups and land cover data. Overall, the CN-panEU dataset and the application can be potentially applied in hydrologic design, land management, flood risk assessment, and groundwater recharge modeling.