本数据集收集的2012-2013年、2013-2014年、2015-2016年凌汛期主要区间来水过程、区间引水过程、各水库起始水位，基于黄河勘测规划设计研究院有限公司研究提出的黄河上游防凌控制指标体系设计的安全下泄流量控制指标，自主开发的黄河上游水库群与分凌区联合防凌优化调度模型计算设定的种群规模、迭代次数等。采用自主开发的黄河上游水库群与分凌区联合防凌优化调度模型进行模拟，该软件采用matlab R2018a软件开发，主要输出结果包括2012-2013年、2013-2014年、2015-2016年凌汛期各水库水位过程、出库流量过程、兰州至头道拐主要水文站流量过程、河段槽蓄水增量过程等。本数据集共包含1个excel文件。", "ds_source": "
该数据集数据来源于收集、数值模拟。龙羊峡入库、龙刘区间、刘兰区间来自黄河上游唐乃亥、民和、享堂、红旗、折桥等水文站实测流量成果，石嘴山站、巴彦高勒站、三湖河口站、包头站、头道拐站气温及封开河日期来自黄河上游石嘴山站、巴彦高勒站、三湖河口站、包头站、头道拐站实测气温及封开河日期资料，各站均为国家基本水文站，测验严格按规范要求进行，资料经整编发布，数据可靠。下河沿到头道拐区间引退水数据来源于历年水利部黄河水利委员会印发的黄河可供耗水量分配及非汛期水量调度计划中各各省（区）用水计划。水库最小、最大下泄流量指标为本次研究分析提出的防凌控制运用指标范围。龙羊峡、刘家峡、海勃湾初始水位来源于各水库实测水位。海勃湾11月20日末水位、海勃湾12月31日末水位、海巴区间分凌区最大分凌流量、三包区间分凌区最大分凌流量、种群规模、迭代次数为自主开发的黄河上游水库群与分凌区联合防凌优化调度模型计算自由设定参数。各水库水位过程、出库流量过程、兰州至头道拐主要水文站流量过程、河段槽蓄水增量过程等模型输出数据为采用自主开发的黄河上游水库群与分凌区联合防凌优化调度模型模拟计算得到。", "ds_process_way": "
龙羊峡入库、龙刘区间、刘兰区间来自黄河上游唐乃亥、民和、享堂、红旗、折桥等水文站实测流量成果，石嘴山站、巴彦高勒站、三湖河口站、包头站、头道拐站气温及封开河日期，下河沿到头道拐区间引退水数据，龙羊峡、刘家峡、海勃湾初始水位等数据采用摘录方法。水库最小、最大下泄流量指标在本次研究成果基础上，结合河道不同的边界条件分析得出。\n
各水库水位过程、出库流量过程、兰州至头道拐主要水文站流量过程、河段槽蓄水增量过程等模型输出数据采用自主开发的黄河上游水库群与分凌区联合防凌优化调度模型模拟计算。模型以头道拐断面最大流量最小、凌汛期内上游水库群总发电量最大、龙刘水库3月末蓄水量之和最大为目标建立目标函数，采用带精英策略非支配排序遗传算法（NSGA-Ⅱ）求解，在求解得到的多目标Pareto非劣解集的基础上，对2000个非劣解分别进行优选，得到样本最优解，作为推荐的优化调度结果。", "ds_quality": "
水文气象资料均为国家基本水文站，测验严格按规范要求进行，资料经整编发布，数据可靠；采用的引退水计划已经审批；使用的模型为自主研发，已经过率定和验证，技术人员使用过程中操作规范，数据可靠，质量良好。", "ds_acq_start_time": "2012-01-01 00:00:00", "ds_acq_end_time": "2016-12-31 00:00:00", "ds_acq_place": "黄河勘测规划设计研究院有限公司", "ds_acq_lon_east": null, "ds_acq_lat_south": null, "ds_acq_lon_west": null, "ds_acq_lat_north": null, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 240427, "ds_files_count": 3, "ds_format": "Excel", "ds_space_res": null, "ds_time_res": "", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "b03982f9-7d24-471b-9d2e-c433b9fc89da.jpg", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "c55e1118-387b-4a0c-8dc5-70aa438c430d", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "10.12072/ncdc.iceflood.db2358.2022", "subject_codes": [ "170.45" ], "quality_level": 3, "publish_time": "2022-07-30 14:39:59", "last_updated": "2025-06-30 15:58:58", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.iceflood.db2358.2022", "i18n": { "en": { "title": "Data set of optimal dispatching model for joint ice prevention in ice flood season (2012-2016)", "ds_format": "Excel", "ds_source": "
The data of this data set comes from collection and numerical simulation. The inflow of Longyang Gorge, longliu section and Liulan section are from the measured flow results of Tangnaihai, Minhe, Xiangtang, Hongqi, Zheqiao and other hydrological stations in the upper reaches of the Yellow River, the temperature and the date of closure and opening of the river at Shizuishan station, Bayan Gaole station, Sanhu Hekou station, Baotou Station and Toudaoguai station are from the measured temperature and the date of closure and opening of the river at Shizuishan station, Bayan Gaole station, Sanhu Hekou station, Baotou Station and Toudaoguai station in the upper reaches of the Yellow River, All stations are national basic hydrological stations, and the test is carried out in strict accordance with the specification requirements. The data are compiled and released, and the data are reliable. The data of withdrawal water from xiaheyan to Toudaoguai are from the water use plans of all provinces (regions) in the available water consumption distribution and non flood season water regulation plan of the Yellow River issued by the Yellow River Water Conservancy Commission of the Ministry of water resources over the years. The minimum and maximum discharge indicators of the reservoir are the range of ice control indicators proposed in this study. The initial water levels of Longyang Gorge, Liujia gorge and Haibo Bay come from the measured water levels of each reservoir. The water level of Haibo bay at the end of November 20, the water level of Haibo bay at the end of December 31, the maximum diversion flow of the ice diversion area in Haiba section, the maximum diversion flow of the ice diversion area in Sanbao section, the population size, and the number of iterations are free to set parameters for the calculation of the self-developed optimal operation model for the joint ice prevention of the reservoirs in the upper Yellow River and the ice diversion area. The output data of the models such as the water level process of each reservoir, the outflow flow process, the flow process of the main hydrological station from Lanzhou to Toudaoguai, and the water storage increment process of the river channel are simulated and calculated by using the self-developed optimal operation model of the joint anti icing of the reservoirs in the upper reaches of the Yellow River and the sub icing area.", "ds_quality": "
The hydrometeorological data are all national basic hydrometric stations, and the test is carried out in strict accordance with the specification requirements. The data are compiled and released, and the data are reliable; The adopted retirement water plan has been approved; The model used is self-developed and has been calibrated and verified. The technicians operate in a standardized way, with reliable data and good quality.", "ds_ref_way": "", "ds_abstract": "
The water inflow process, water diversion process and initial water level of each reservoir in the main sections during the ice flood seasons in 2012-2013, 2013-2014 and 2015-2016 collected in this data set are based on the safe discharge control index designed by the ice control index system in the upper reaches of the Yellow River proposed by the Yellow River Survey, planning, design and Research Institute Co., Ltd., and the self-developed optimal operation model for the joint ice control of reservoirs and ice diversion areas in the upper reaches of the Yellow River Iterations, etc. The self-developed optimal operation model of the upper Yellow River reservoir group and the sub ice flood area is used for simulation. The software is developed by MATLAB r2018a software. The main output results include the water level process of each reservoir during the ice flood seasons of 2012-2013, 2013-2014 and 2015-2016, the outflow flow process, the flow process of Lanzhou Toudaoguai main hydrological station, the water storage increment process of the river channel, etc. This data set contains 1 excel file.
", "ds_time_res": "", "ds_acq_place": "Yellow River survey, planning, design and Research Institute Co., Ltd", "ds_space_res": "", "ds_projection": "", "ds_process_way": "Longyang Gorge storage, longliu section, Liulan section are from the measured flow results of Tangnaihai, Minhe, Xiangtang, Hongqi, Zheqiao and other hydrological stations in the upper reaches of the Yellow River, Shizuishan station, Bayan Gaole station, sanhuhekou station, Baotou Station, Toudaoguai station temperature and the date of closure and opening of the river, the diversion water data from xiaheyan to Toudaoguai section, and the initial water levels of Longyang Gorge, Liujiaxia and Haibowan are extracted. The minimum and maximum discharge indexes of the reservoir are obtained on the basis of the research results, combined with the analysis of different boundary conditions of the river.\n
The model output data of the water level process of each reservoir, the outflow flow process, the flow process of the main hydrological station from Lanzhou to Toudaoguai, and the water storage increment process of the river channel are simulated by the self-developed optimal operation model of the combined anti icing of the reservoirs in the upper reaches of the yellow River and the sub icing area. The objective function of the model is to minimize the maximum flow at Toudaoguai section, maximize the total power generation of the upstream reservoir group during the ice flood season, and maximize the sum of the water storage of longliu reservoir at the end of March. The model is solved by using the non dominated sorting genetic algorithm with elite strategy (nsga- Ⅱ). On the basis of the multi-objective Pareto non inferior solution set, 2000 non inferior solutions are optimized respectively, and the sample optimal solution is obtained as the recommended optimal operation result.", "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, "ds_topic_tags": [ "联合防凌优化调度模型", "输入", "输出" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "黄河上游" ], "ds_time_tags": [ 2012, 2013, 2014, 2015, 2016 ], "ds_contributors": [ { "true_name": "蔺冬", "email": "llfldd@163.com", "work_for": "黄河勘测规划设计研究院有限公司", "country": "中国" }, { "true_name": "张志红", "email": "zhangzhh@yrec.cn", "work_for": "黄河勘测规划设计研究院有限公司", "country": "中国" }, { "true_name": "赵梦龙", "email": "mlzhao1314@163.com", "work_for": "黄河勘测规划设计研究院有限公司", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "蔺冬", "email": "llfldd@163.com", "work_for": "黄河勘测规划设计研究院有限公司", "country": "中国" } ], "ds_managers": [ { "true_name": "蔺冬", "email": "llfldd@163.com", "work_for": "黄河勘测规划设计研究院有限公司", "country": "中国" } ], "category": "其他" }