在本数据集中，基于空间变化的 FHG 参数，我们绘制了一幅分辨率为 90 米的全球洪泛区地图，命名为 “通过地形分析改进空间异质性洪泛区”（SHIFT），该地图以水文校正后的 MERIT Hydro 数据集作为 DEM 输入，以最近排水沟以上高度（HAND）作为地形属性。结果表明，SHIFT 与参考地图的验证效果优于水动力建模方法和基于 DEM 的通用参数方法。改进后的划界主要包括更好地区分了主要流域的干流和支流，以及更全面地表示了汇集流域的溪流网络。
", "ds_source": "1、地形数据
\n（1）MERIT 水文地图：从 MERIT Hydro 数据集zh中获取，是一个 90 米分辨率的全球数据集，采用 WGS84 和 EGM96 大地测量参考系，空间分辨率为 3 弧秒（赤道处约 90 米）；
\n（2）HydroBASINS 全球流域：应用了三级 HydroBASINS 数据集的流域边界数据，这是一个多级全球流域数据集，来自 SRTM DEM 数据；
\n（3）MERIT-Basins.： 是一个全球矢量水文地理数据库，由 90 米 MERIT Hydro 产品衍生而来，基于 25 平方公里的排水区阈值。
\n2、参考和基准数据集
\n（1）JRC 洪水图：欧洲委员会 JRC 绘制的洪水灾害图被选为参考和验证数据集的一部分，时间跨度为 1980 年至 2013 年，分辨率为 0.1°；
\n（2）GAR 洪水图：联合国减少灾害风险办公室（UNDRR）和 CIMA 基金会的 GAR 中选择了水动力模型的 500 年一遇洪水图作为参考和验证数据集，该数据集的特点是重现期为 25、50、100、200、500 和 1000 年，覆盖范围为北纬 60°至南纬 60°，原始分辨率为 SRTM DEM 的 90 米，后汇总为 1 公里；
\n（3）GFPLAIN250 米洪泛区地图：GFPLAIN250m 洪水泛滥区地图被用作基准和另一个验证数据集，该数据集的覆盖范围与 GAR 相同；
\n（4）全球湖泊和湿地数据集（GLWD）湖泊和水库数据集：使用由世界自然基金会（WWF）和卡塞尔大学环境系统研究中心联合开发的全球湖泊和湿地数据集（GLWD），该数据集参考了多个来源的数据，并通过美国地质调查局的独立数据以及大量的目测和质量控制进一步完善。
\n3、相关数据集
\n（1）全球干旱指数数据库：使用全球干旱指数和潜在蒸散量数据库（Global-AI_PET_v3）中的干旱指数（AI）来评估其与 FHG 参数的联系。该数据库提供 30 弧秒全球潜在蒸散量 (ET0) 和 AI 数据；
\n（2）叶面积指数气候学：提供了全球 0.25° × 0.25° 的网格化月平均叶面积指数，其平均值为 1981 年 8 月至 2015 年 8 月。
", "ds_process_way": "\n在本研究中，我们为基于大尺度 DEM 的洪泛区划分开发了一种改进的阈值方案，其核心是洪泛区水力几何（FHG）参数的逐步估算框架，该框架在尊重幂律的同时，更好地整合了来自两张公开水动力洪水地图的空间异质性。我们在相当于 HydroBASINS 3 级流域的尺度上应用了该框架，以得出本地化的洪泛区水力几何参数，作为对之前未考虑影响洪泛区范围的异质因素的全局参数的更新。
", "ds_quality": "\n在 FHG 中，优化后的经验指数 b 与水文气候条件，尤其是主要流域的水文气候条件，呈现出统计学上显著的正相关关系。基于所提出的框架，我们利用 90 米 MERIT 水文数据集的地形输入创建了名为 SHIFT（通过地形分析改善洪泛区空间异质性）的全球地貌洪泛区地图，结果表明 SHIFT 能够很好地捕捉地貌洪泛区的全球模式和区域细节。以下几点证明了我们框架的有效性：
\n这些参数与水文气候变量（如 AI、LAI）之间的关系在统计上有意义但相对较弱，这表明在流域层面上增强了对空间异质性水文和地貌信息的表示。
\n过滤后的数据符合相对稳定的幂律，表明区域化的比例关系非常稳健。
\n参数的改变提高了与现有地图的一致性，更好地区分了主要流域中的干流和支流，更全面地反映了聚合流域中的溪流网络。
", "ds_acq_start_time": null, "ds_acq_end_time": null, "ds_acq_place": "全球", "ds_acq_lon_east": 180.0, "ds_acq_lat_south": 90.0, "ds_acq_lon_west": -180.0, "ds_acq_lat_north": -90.0, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 965762778, "ds_files_count": 7, "ds_format": ".tif", "ds_space_res": "90/1000", "ds_time_res": "", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "6d981a90-4e02-4b27-8480-0097c5817261.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "0a4269e1-65f4-45f1-aeba-88ea3068eebf", "ds_serv_man": "敏玉芳", "ds_serv_phone": "09314967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.40", "170.4510" ], "quality_level": 3, "publish_time": "2024-12-27 15:58:15", "last_updated": "2026-01-14 10:55:16", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.ZENODO.DB6695.2024", "i18n": { "en": { "title": "Improved Mapping of Spatial Heterogeneity of Global Geomorphic Floodplain Based on DEM", "ds_format": ".tif", "ds_source": "1. Terrain data
\n(1) MERIT Hydrological Map: obtained from the MERIT Hydro dataset, which is a 90 meter resolution global dataset using WGS84 and EGM96 geodetic reference frames, with a spatial resolution of 3 arc seconds (approximately 90 meters at the equator);
\n(2) HydroBASINS Global Watershed: Watershed boundary data from the three-level HydroBASINS dataset was applied, which is a multi-level global watershed dataset derived from SRTM DEM data;
\n(3) MERIT Basins is a global vector hydrogeology database derived from the 90 meter MERIT Hydro product, based on a drainage threshold of 25 square kilometers.
\n2. Reference and benchmark datasets
\n(1) JRC Flood Map: The flood hazard map drawn by the European Commission JRC has been selected as part of the reference and validation dataset, covering the period from 1980 to 2013, with a resolution of 0.1 °;
\n(2) GAR Flood Map: The GAR of the United Nations Office for Disaster Risk Reduction (UNDP) and CIMA Foundation selected the 500 year flood map of the hydrodynamic model as the reference and validation dataset. The characteristics of this dataset are a recurrence interval of 25, 50, 100, 200, 500, and 1000 years, covering the range from 60 ° N to 60 ° S latitude, with an original resolution of 90 meters for SRTM DEM and later summarized as 1 kilometer;
\n(3) GFPLIN250m Flood Zone Map: The GFPLIN250m Flood Zone Map was used as a benchmark and another validation dataset with the same coverage as GAR;
\n(4) Global Lakes and Wetlands Dataset (GLWD) Lakes and Reservoirs Dataset: Using the Global Lakes and Wetlands Dataset (GLWD) jointly developed by the World Wildlife Fund (WWF) and the Environmental Systems Research Center at Kassel University, this dataset references data from multiple sources and is further refined through independent data from the United States Geological Survey and extensive visual and quality control.
\n3. Related datasets
\n(1) Global Drought Index Database: Use the Drought Index (AI) from the Global Drought Index and Potential Evapotranspiration Database (Global-AI-PET-v3) to evaluate its association with FHG parameters. This database provides global potential evapotranspiration (ET0) and AI data for 30 arc seconds;
\n(2) Leaf Area Index Climatology: Provides a gridded monthly average leaf area index of 0.25 °× 0.25 ° globally, with an average value from August 1981 to August 2015.
", "ds_quality": "\nIn FHG, the optimized empirical index b shows a statistically significant positive correlation with hydrological and climatic conditions, especially in the main watersheds. Based on the proposed framework, we created a global geomorphic floodplain map called SHIFT (Improving Spatial Heterogeneity of Floodplain through Terrain Analysis) using terrain input from the 90 meter MERIT hydrological dataset. The results showed that SHIFT can effectively capture the global patterns and regional details of geomorphic floodplain. The following points demonstrate the effectiveness of our framework:
\nThe relationship between these parameters and hydroclimatic variables (such as AI, LAI) is statistically significant but relatively weak, indicating an enhanced representation of spatially heterogeneous hydrological and geomorphological information at the watershed level.
\nThe filtered data conforms to a relatively stable power law, indicating that the proportional relationship of regionalization is very robust.
\nThe change in parameters has improved consistency with existing maps, better distinguishing between the main streams and tributaries in the main watershed, and more comprehensively reflecting the stream network in the aggregated watershed.
", "ds_ref_way": "", "ds_abstract": "In this dataset, based on spatially varying FHG parameters, we created a global floodplain map with a resolution of 90 meters, named \"Improving Spatial Heterogeneity Floodplain through Terrain Analysis\" (SHIFT). The map takes the hydrological corrected MERIT Hydro dataset as the DEM input and the height above the nearest drainage ditch (HAND) as the terrain attribute. The results indicate that the validation effect of SHIFT with reference maps is superior to that of hydrodynamic modeling methods and DEM based general parameter methods. The improved delineation mainly includes better differentiation of the main streams and tributaries of the main watershed, as well as a more comprehensive representation of the stream network that gathers the watershed.
", "ds_time_res": "", "ds_acq_place": "Global", "ds_space_res": "90/1000", "ds_projection": "", "ds_process_way": "\nIn this study, we developed an improved threshold scheme for flood zone partitioning based on large-scale DEM. The core of this scheme is a progressive estimation framework for flood zone hydraulic geometry (FHG) parameters, which better integrates spatial heterogeneity from two public hydrodynamic flood maps while respecting power law. We applied this framework at a scale equivalent to HydroBASINS Level 3 watershed to derive localized hydraulic geometric parameters of the floodplain, as an update to the global parameters that did not previously consider heterogeneous factors affecting the extent of the floodplain.
", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "doi_reg_from": "reg_outside", "cstr_reg_from": "reg_outside", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "ds_topic_tags": [ "基于 DEM", "全球地貌", "洪泛区", "空间异质性" ], "ds_subject_tags": [ "地图学", "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "全球" ], "ds_time_tags": [], "ds_contributors": [ { "true_name": "林佩蓉", "email": "peironglinlin@pku.edu.cn", "work_for": "北京大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "林佩蓉", "email": "peironglinlin@pku.edu.cn", "work_for": "北京大学", "country": "中国" } ], "ds_managers": [ { "true_name": "林佩蓉", "email": "peironglinlin@pku.edu.cn", "work_for": "北京大学", "country": "中国" } ], "category": "水文" }