本数据集面向金沙江下游四库—三峡梯级系统防洪风险传递转移机理研究，汇集了在预报误差情景扰动下的关键水文—调度—风险指标数据。数据以预报误差倍比x（-0.9～0.9，步长0.1）构建离散情景，给出各情景下的最大入库流量、库水位与下泄控制指标，以及下游控制断面最大水位/水位标准化指标。同时，数据整理了乌东德、白鹤滩、溪洛渡、向家坝、三峡及李庄、朱沱、寸滩、枝城、沙市、城陵矶等关键对象的三级风险阈值，用于将无量纲风险指标反算至实际水位量纲。数据可用于识别风险转化阈值、下游传递阈值及梯级内风险再分配特征，并为风险约束下的汛限水位动态控制与洪水资源利用方案评估提供支撑。
\n数据文件为Excel工作簿（*.xlsx），Sheet1由三部分组成：\n
1）预报误差情景—水文与调度结果表（A～J列，行2～20）：\n
- 误差x：预报误差倍比（无量纲），取值-0.9～0.9，步长0.1；预报不确定性/%为100x。\n
- 最大入库流量Q_in,max（m³/s）：按Q_in,max = 31648×(1−x)计算得到（基准流量31648 m³/s）。\n
- 水库水位Z_res,max（m）：情景下库水位最大值；并给出对应的标准化值Z_res,norm（0～1），其与实际水位满足 Z_res = (175−145)×Z_res,norm + 145。\n
- 水库最大泄量Q_out,max（m³/s）：情景下最大下泄流量。\n
- 下游最大水位Z_down,max（m）：下游控制断面最大水位；并给出标准化值Z_down,norm（0～1），其与实际水位满足 Z_down = (53.75−48.75)×Z_down,norm + 48.75。\n
注：表中部分“水库水位/m”“下游最大水位/m”列为由标准化值反算的校核列，与原值一致。\n
2）风险阈值表（O～R列，行2～12）：列示11个风险对象的一级/二级/三级风险阈值（单位m），包括乌东德、白鹤滩、溪洛渡、向家坝、三峡以及李庄、朱沱、寸滩、枝城、沙市、城陵矶。\n
3）标准化辅助行（行22～23）：给出关键指标的“变幅/相差”等统计量，用于复现归一化与尺度转换过程。\n
数据精度：流量以m³/s计（多数值保留至0.1～1 m³/s量级），水位以m计（保留至0.01 m及以上精度，具体取决于计算输出的双精度存储）。", "ds_source": "
（1）预报误差情景构建：以误差倍比x（-0.9～0.9，步长0.1）表示预报偏差水平，并按Q_in,max = 31648×(1−x)生成情景最大入库流量。\n
（2）调度与水位指标：在给定情景入库条件下，依据梯级水库汛期运行与防洪调度约束（如汛限水位/防洪高水位与下泄能力约束）计算得到库水位与最大下泄指标；下游控制断面最大水位由调度结果结合水位—流量关系/河道演算确定。\n
（3）风险阈值：库水位阈值来源于水库特征水位及汛期运行控制要求；下游断面阈值来源于防洪控制水位（警戒/保证等）或相应分级标准，用于构建三级风险分级体系。", "ds_process_way": "
数据加工流程如下：\n
1）设置误差倍比x（-0.9～0.9，步长0.1），并计算预报不确定性（%）与情景最大入库流量Q_in,max。\n
2）对每个情景开展调度计算，输出Z_res,max、Q_out,max及Z_down,max等关键指标。\n
3）为便于跨对象比较，将水位指标按给定上下界进行线性标准化（得到Z_res,norm、Z_down,norm），并提供由标准化值反算的校核列。\n
4）整理各对象一级/二级/三级风险阈值，并可按线性映射将无量纲风险值转换为实际水位量纲（如Z = r×(Z_Ⅲ−Z_Ⅰ)+Z_Ⅰ）。", "ds_quality": "
数据由统一的情景构建与计算流程生成，已进行完整性与一致性检查：\n
（1）情景取值完整性：x覆盖-0.9～0.9且步长0.1；\n
（2）量纲一致性：流量单位m³/s，水位单位m；\n
（3）公式一致性：入库流量与误差倍比的线性关系、标准化/反标准化关系在表内可复核；\n
（4）缺失值检查：情景行与风险阈值表无缺测。", "ds_acq_start_time": "2020-01-01 00:00:00", "ds_acq_end_time": "2020-12-31 00:00:00", "ds_acq_place": "中国长江流域金沙江下游—三峡梯级水库系统及其下游控制断面（乌东德、白鹤滩、溪洛渡、向家坝、三峡；李庄、朱沱、寸滩、枝城、沙市、城陵矶等）。", "ds_acq_lon_east": 113.2, "ds_acq_lat_south": 25.8, "ds_acq_lon_west": 102.7, "ds_acq_lat_north": 31.3, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "open-access", "ds_total_size": 9972, "ds_files_count": 0, "ds_format": "*.xlsx", "ds_space_res": "", "ds_time_res": "情景尺度数据：预报误差倍比x间隔0.1；无连续时间序列。", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "edcef5d0-6c13-4549-91d8-bc02c121b8e1.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "在使用数据时，请注明“数据来自国家重点研发计划课题‘水库群汛期运行水位动态控制风险辨识与适应性调控技术’（2022YFC3202803）”。", "ds_from_station": "", "organization_id": "44547705-9513-4685-a641-661bdf406520", "ds_serv_man": "", "ds_serv_phone": "", "ds_serv_mail": "", "doi_value": "", "subject_codes": [ "170.55" ], "quality_level": 0, "publish_time": "2026-07-14 10:52:20", "last_updated": "2026-07-14 11:15:05", "protected": false, "protected_to": "2027-01-01 00:00:00", "lang": "zh", "cstr": "", "i18n": { "en": { "title": "Dataset on the Transmission and Transfer of Flood Risks in the Lower Jinsha River and the Three Gorges Reservoir (2020)", "ds_format": "*.xlsx", "ds_source": "
(1) Construction of forecast error scenarios: The forecast deviation level is expressed by the error multiple ratio x (-0.9 ￣ 0.9, step size 0.1), and the maximum inflow flow of the scenario is generated as Q_in,max = 31648×(1−x).\r\n
(2) Dispatch and water level indicators: Under the inflow conditions of a given scenario, the reservoir water level and maximum discharge indicators are calculated based on the flood season operation of cascade reservoirs and flood control dispatch constraints (such as flood limit water level/flood control high water level and discharge capacity constraints); The maximum water level of the downstream control section is determined by the dispatch results combined with the water-flow relationship/river calculation.\r\n
(3) Risk threshold: The reservoir water level threshold comes from the reservoir's characteristic water level and flood season operation control requirements; the downstream section threshold comes from the flood control control water level (warning/guarantee, etc.) or corresponding grading standards, which is used to build a three-level risk grading system.", "ds_quality": "
Data is generated by a unified scenario construction and calculation process, and has been checked for integrity and consistency:\r\n
(1) Scenario value integrity: x covers-0.9 to 0.9 and the step size is 0.1;\r\n
(2) Dimension consistency: flow unit m³/s, water level unit m;\r\n
(3) Formula consistency: The linear relationship between incoming flow and error times ratio, and the normalized/de-normalized relationship can be reviewed in the table;\r\n
(4) Missing value check: There are no missing tests in the scenario row and risk threshold table.", "ds_ref_way": "", "ds_abstract": "
This dataset is aimed at studying the flood control risk transfer mechanism of the Fourth Reservoir and Three Gorges Cascade System in the lower reaches of the Jinsha River, and collects key hydrologic-dispatch-risk indicator data under the disturbance of forecast error scenarios. The data constructs discrete scenarios based on the forecast error multiples ratio x (-0.9 to 0.9, step size 0.1), and gives the maximum inflow flow, reservoir water level and discharge control indicators under each scenario, as well as the maximum water level/water level standardization indicators of the downstream control section. At the same time, the data compiled the three-level risk thresholds of key objects such as Wudongde, Baihetan, Xiluodu, Xiangjiaba, Three Gorges and Lizhuang, Zhutuo, Cuntan, Zhicheng, Shashi, and Chenglingji, and used to calculate the dimensionless risk indicators back to the actual water level dimension. The data can be used to identify risk transformation thresholds, downstream transfer thresholds and risk redistribution characteristics within the cascade, and provide support for dynamic control of flood limit water levels and evaluation of flood resource utilization plans under risk constraints.
\r\nThe data file is an Excel workbook (*.xlsx) with a total of 3 Sheets, of which Sheet1 contains complete data (Sheet2 and Sheet3 are blank/used for drawing). Sheet1 consists of three parts:\r\n
1) Forecast error scenarios-Hydrology and dispatch results table (columns A to J, rows 2 to 20):\r\n
- Error x: prediction error multiple ratio (dimensionless), taking values of-0.9 to 0.9, step size of 0.1; prediction uncertainty/% is 100x.\r\n
- Maximum incoming flow Q_in,max (m³/s): calculated as Q_in,max = 31648×(1−x)(benchmark flow 31648 m³/s).\r\n
- Reservoir water level Z_res,max (m): the maximum value of the reservoir water level under the scenario; and the corresponding standardized value Z_res,norm (0~1) is given, which satisfies Z_res = (175−145)×Z_res,norm + 145 with the actual water level.\r\n
- Maximum reservoir discharge Q_out,max (m³/s): Maximum discharge flow under the scenario.\r\n
- Maximum downstream water level Z_down,max (m): Maximum water level of downstream control section; and gives a standardized value Z_down,norm (0~1), which satisfies Z_down = (53.75−48.75)×Z_down,norm + 48.75 with the actual water level.\r\n
Note: Some \"reservoir water level/m\" and \"downstream maximum water level/m\" in the table are listed as check columns that are back-calculated from standardized values, which are consistent with the original value.\r\n
2) Risk threshold table (columns O-R, rows 2 - 12): lists the first/second/third risk thresholds (in m) of 11 risk objects, including Wudongde, Baihetan, Xiluodu, Xiangjiaba, Sanxia, Lizhuang, Zhutuo, Cuntan, Zhicheng, Shashi, and Chenglingji.\r\n
3) Standardization auxiliary rows (rows 22 - 23): Give statistics such as \"amplitude change/phase difference\" of key indicators, which are used to reproduce the normalization and scale conversion process.\r\n
Data accuracy: Flow rate is measured in m³/s (multiple values are retained to the order of 0.1 - 1 m³/s), and water level is measured in m (retained to an accuracy of 0.01 m and above, depending on the double precision storage of calculation output).", "ds_time_res": "", "ds_acq_place": "The lower reaches of the Jinsha River in the Yangtze River Basin of China and its downstream control sections (Wudongde, Baihetan, Xiluodu, Xiangjiaba, Three Gorges; Lizhuang, Zhutuo, Cuntan, Zhicheng, Shashi, Chenglingji, etc.).", "ds_space_res": "", "ds_projection": "", "ds_process_way": "
The data processing process is as follows:\r\n
1) Set the error multiple ratio x (-0.9 ￣ 0.9, step size 0.1), and calculate the forecast uncertainty ( %) and the maximum inflow flow of the scenario Q_in,max.\r\n
2) Carry out scheduling calculations for each scenario and output key indicators such as Z_res,max, Q_out,max and Z_down,max.\r\n
3) In order to facilitate cross-object comparison, the water level indicator is linearly normalized according to the given upper and lower boundaries (to obtain Z_res,norm, Z_down,norm), and a check column that is back-calculated from the normalized values is provided.\r\n
4) Organize the primary/secondary/tertiary risk thresholds of each object, and convert the dimensionless risk value into the actual water level dimension according to linear mapping (such as Z = r×(Z_Ⅲ−Z_I)+Z_I).", "ds_ref_instruction": "When using the data, please indicate \"The data comes from the national key research and development plan topic 'Risk Identification and Adaptive Regulation Technology for Dynamic Control of Reservoir Group Operating Water Level in Flood Season'(2022YFC3202803)\"." } }, "submit_center_id": "ncdc", "data_level": 0, "recommendation_value": 0, "license_type": "https://creativecommons.org/licenses/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, "belong_to_nieer": false, "ds_topic_tags": [ "防洪风险", "风险传递转移", "梯级水库", "金沙江下游", "三峡水库", "预报误差情景", "汛限水位动态控制" ], "ds_subject_tags": [ "水文学" ], "ds_class_tags": [], "ds_locus_tags": [ "金沙江下游；三峡库区；长江干流；川江；荆江；城陵矶" ], "ds_time_tags": [ 2020 ], "ds_contributors": [ { "true_name": "王浅宁", "email": "745303874@qq.com", "work_for": "大连理工大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "王浅宁", "email": "745303874@qq.com", "work_for": "大连理工大学", "country": "中国" } ], "ds_managers": [ { "true_name": "王浅宁", "email": "745303874@qq.com", "work_for": "大连理工大学", "country": "中国" } ], "category": "水文" }