该数据集为长江下游地区洪涝致灾性因子评价基础数据，包含大通径流量数据、气象站点降水数据和吴淞口日高潮位数据。\n
长江下游地区洪涝致灾性因子评价基于1980-2020年间日降水序列完整的88个气象观测站数据，分析长江下游地区的年降水天数和平均连续降水天数、降水集中度、暴雨日数和暴雨量等致灾性因子的变化特征进行分析，为下一步洪涝应对韧性的分析提供了数据支撑，同时使用反距离权重插值法得到0.1°分辨率下的栅格数据，为在空间尺度上分析降水变化提供基础。\n
基于大通站1950-2020年逐日流量资料，分析上游来水量的变化特征；基于吴淞口潮汐站1956-2020年逐日最高潮位数据，分析沿海潮位的变化特征，为分析洪涝致灾性因子的变化特征提供支撑。", "ds_source": "
降水数据为国家气象信息中心（https://data.cma.cn/） 提供的气象站日降水数据；\n
大通站径流量和吴淞口潮汐水位数据来自水文统计年鉴。", "ds_process_way": "
（1）通过matlab软件，使用反距离权重插值法将88个气象站点的降水数据插值得到0.1°分辨率下的空间栅格数据；\n
（2）对于缺测年份的数据采用前后年份数据线性插值的方法获取，以满足指标数据的连贯性。", "ds_quality": "
在降水时程变化方面，长江下游地区1980-2020年年和汛期降水量、年降水天数和平均连续降水天数、降水集中度、暴雨日数和暴雨量均呈现增加的趋势，汛期及7月、8月和9月的降水量占全年降水量的比例呈增加的趋势，一定程度上说明长江下游地区降水有向汛期集中，在空间上降水量自南向北呈减小的趋势，与实际情况贴合.\n
上游来水变化方面，1950-2020年长江下游地区上游来水量在年和汛期尺度上均呈下降的趋势，汛期来水量占全年的比例有所下降，但7月上游来水量占全年上游来水量的比例表现出上升态势，上游来水量在年内呈“单峰”型分布，峰值正处于7月中旬，与实际情况贴合。\n
在潮位变化方面，1995-2020年的平均年最高潮位达到3.67m，大于1956-1991年的3.50m，与实际情况贴合。因此，本数据集可作为长江下游地区洪涝致灾性评价分析的可靠基础数据。", "ds_acq_start_time": "2022-09-01 00:00:00", "ds_acq_end_time": "2022-09-01 00:00:00", "ds_acq_place": "长江下游地区", "ds_acq_lon_east": 121.97, "ds_acq_lat_south": 29.59, "ds_acq_lon_west": 115.47, "ds_acq_lat_north": 32.74, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 6449920, "ds_files_count": 4, "ds_format": "*.xlsx", "ds_space_res": "0.1°", "ds_time_res": "日", "ds_coordinate": "WGS84", "ds_projection": "Albers Equal Area Conic Projection System", "ds_thumbnail": "831e7af1-6d70-4e6c-9523-a83199388f88.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "37eb642a-c117-47e4-a677-07ecffb4b8b7", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.55" ], "quality_level": 3, "publish_time": "2025-02-27 18:55:36", "last_updated": "2025-06-30 11:40:12", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.NHRI.DB6769.2025", "i18n": { "en": { "title": "Dataset for evaluating flood causality factors in the lower reaches of the Yangtze River", "ds_format": "*.xlsx", "ds_source": "
Precipitation data are daily precipitation data from meteorological stations provided by the National Center for Meteorological Information (https://data.cma.cn/);\n
Data on runoff volume at Datong Station and tidal level at Wusongkou are from the Hydrological Statistics Yearbook.", "ds_quality": "
In terms of precipitation time course changes, the annual and flood season precipitation, the annual number of precipitation days and the average number of consecutive precipitation days, the concentration of precipitation, the number of days of heavy rainfall and the amount of heavy rainfall in the lower Yangtze River region from 1980 to 2020 show an increasing trend, and the precipitation during the flood season and in July, August and September show an increasing trend in the ratio of precipitation to annual precipitation, which, to a certain extent, indicates that the lower Yangtze River region has a concentration of precipitation towards the flood season, and the spatial precipitation decreases from south to north, which is consistent with the actual situation. To a certain extent, it shows that the precipitation in the lower reaches of the Yangtze River is concentrated in the flood season, and the precipitation is decreasing from the south to the north in space, which is in line with the actual situation.\n
Upstream water changes, 1950-2020, the lower reaches of the Yangtze River upstream water in the annual and flood season scale are downward trend, flood season water accounted for the proportion of the whole year has declined, but the July upstream water accounted for the proportion of the whole year upstream water showed an upward trend, the amount of upstream water in the year was “single peak” type distribution, the peak value of the “single peak” type distribution, the upstream water in the year was “single peak” type distribution, the peak value of the “single peak” type distribution, the peak value of the “single peak” type distribution. The upstream water inflow in the year shows a “single peak” distribution, with the peak in mid-July, which is in line with the actual situation.\n
In terms of tide level change, the average annual maximum tide level of 1995-2020 reaches 3.67m, which is larger than that of 1956-1991, which is 3.50m, which is in line with the actual situation. Therefore, this dataset can be used as a reliable basic data for the evaluation and analysis of flood causality in the lower reaches of the Yangtze River.", "ds_ref_way": "", "ds_abstract": "
This dataset is the basic data for the evaluation of flooding catastrophicity factors in the lower reaches of the Yangtze River, which contains the Chase runoff data, precipitation data of meteorological stations, and daily high tide level data of Wusongkou.\n
The evaluation of flooding causality factors in the lower reaches of the Yangtze River is based on the data of 88 meteorological stations with complete daily precipitation series during 1980-2020, and the analysis of the change characteristics of the causality factors, such as the number of annual precipitation days and the average number of consecutive precipitation days, the concentration of precipitation, the number of days of torrential rainfall, and the amount of torrential rainfall in the lower reaches of the Yangtze River is carried out to provide the data support for the analysis of the resilience of the response to the floods in the next step. Data support was provided, while raster data at 0.1° resolution was obtained using inverse distance weight interpolation to provide a basis for analyzing precipitation changes on a spatial scale.\n
Based on the day-by-day flow data from 1950 to 2020 at the Datong station, we analyze the change characteristics of the upstream water inflow; based on the day-by-day maximum tide level data from 1956 to 2020 at the Wusongkou tidal station, we analyze the change characteristics of the coastal tide level, which provides support for the analysis of the change characteristics of the flood causative factors.
", "ds_time_res": "日", "ds_acq_place": "Lower Yangtze River region", "ds_space_res": "0.1°", "ds_projection": "", "ds_process_way": "(1) The spatial raster data at 0.1° resolution were obtained by interpolating the precipitation data from 88 meteorological stations by using inverse distance weight interpolation through matlab software;\n
(2) For the data of the missing years of measurements the data of the previous and the previous years of the data were obtained by the method of linear interpolation to satisfy the consistency of the indicator data.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "doi_reg_from": "reg_local", "cstr_reg_from": "reg_local", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "ds_topic_tags": [ "长江下游地区", "洪涝致灾性" ], "ds_subject_tags": [ "水文学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国", "长江下游" ], "ds_time_tags": [ 1950, 1956, 1980, 2020 ], "ds_contributors": [ { "true_name": "卢开东", "email": "lukaidong@outlook.com", "work_for": "南京水利科学研究院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "卢开东", "email": "lukaidong@outlook.com", "work_for": "南京水利科学研究院", "country": "中国" } ], "ds_managers": [ { "true_name": "卢开东", "email": "lukaidong@outlook.com", "work_for": "南京水利科学研究院", "country": "中国" } ], "category": "其他" }