技术领域Technical field
本发明属于洪水预报技术，尤其是一种用于城市防洪的智慧预警方法及系统。The invention belongs to flood forecasting technology, especially a smart early warning method and system for urban flood control.
背景技术Background technique
洪水预报预警是指根据已知或预测的降雨、融雪、土壤湿度等水文气象条件，利用数学模型或统计方法，对未来一定时间内某一地点或区域的水文要素（如河流水位、流量、洪峰到达时间等）进行预测的过程。洪水预报是防汛抗旱工作的重要依据，也是水资源管理、水利工程运行、生态环境保护等领域的基础技术。目前，洪水预报主要有两类方法：基于物理机制的确定性模型和基于数据关系的经验统计模型。Flood forecasting and early warning refers to the use of mathematical models or statistical methods to predict hydrological elements (such as river water levels, flows, flood peaks, etc.) arrival time, etc.). Flood forecasting is an important basis for flood control and drought relief, and is also a basic technology in the fields of water resources management, water conservancy project operation, and ecological environment protection. Currently, there are two main methods for flood forecasting: deterministic models based on physical mechanisms and empirical statistical models based on data relationships.
首先，基于物理机制的确定性模型是根据流域产汇流过程和河道波动过程的物理规律建立的数学模型，通过求解控制方程和边界条件，模拟洪水发生、发展和消退的过程。这类模型可以反映流域内各种因素对洪水过程的影响，具有较强的物理意义和适应性，但也存在一些问题，如参数较多难以确定，计算量较大难以实时应用，数据要求较高难以满足等。其次，基于数据关系的经验统计模型是根据历史观测数据分析洪水过程与各种因子之间的统计关系，并建立相应的数学表达式或概率分布函数，用于预测未来可能发生的洪水情况。这类模型可以充分利用已有数据，简化计算过程，提高预报效率，但也存在一些问题，如不能反映流域内各种因素对洪水过程的物理机制，缺乏通用性和稳定性，对数据质量和数量要求较高等。再次，随着大数据、人工智能等新技术的发展和应用，为洪水预报提供了新的思路和手段。人工智能是一种让机器具有智能行为的技术，其中机器学习是人工智能的核心技术之一，主要通过让机器自主学习数据中蕴含的规律，并利用这些规律进行分类、回归、聚类等任务。机器学习可以处理海量、复杂、非线性的数据，具有高效、稳定、客观等优势。目前，在气象灾害识别预测、天气指标分类、天气预报预测等方面已经取得了较好的应用效果。将机器学习应用于洪水预报预警，可以克服传统方法的局限性，提高预报的精度和灵敏度。但是机器学习还存在缺乏足够的可解释性，不能反应实际的物理机制和原理，同时，对数据质量和数量要求比较高，数据质量存在问题，会降低可靠性和鲁棒性。First of all, the deterministic model based on physical mechanisms is a mathematical model established based on the physical laws of the basin's flow generation and confluence process and the river channel fluctuation process. It simulates the process of flood occurrence, development and subsidence by solving the governing equations and boundary conditions. This type of model can reflect the impact of various factors in the basin on the flood process and has strong physical significance and adaptability. However, there are also some problems, such as too many parameters that are difficult to determine, a large amount of calculation that is difficult to apply in real time, and relatively large data requirements. High and difficult to satisfy, etc. Secondly, the empirical statistical model based on data relationships analyzes the statistical relationship between the flood process and various factors based on historical observation data, and establishes corresponding mathematical expressions or probability distribution functions to predict possible future flood conditions. This type of model can make full use of existing data, simplify the calculation process, and improve forecast efficiency. However, there are also some problems, such as being unable to reflect the physical mechanism of flood processes caused by various factors in the basin, lacking versatility and stability, and affecting data quality and quality. Quantity requirements are higher. Thirdly, with the development and application of new technologies such as big data and artificial intelligence, new ideas and methods have been provided for flood forecasting. Artificial intelligence is a technology that allows machines to behave intelligently. Machine learning is one of the core technologies of artificial intelligence. It mainly allows machines to autonomously learn the rules contained in data and use these rules to perform tasks such as classification, regression, and clustering. . Machine learning can handle massive, complex, and nonlinear data, and has the advantages of efficiency, stability, and objectivity. At present, good application results have been achieved in meteorological disaster identification and prediction, weather indicator classification, weather forecast and prediction, etc. Applying machine learning to flood forecasting and early warning can overcome the limitations of traditional methods and improve the accuracy and sensitivity of forecasts. However, machine learning still lacks sufficient interpretability and cannot reflect actual physical mechanisms and principles. At the same time, it has relatively high requirements on data quality and quantity, and there are problems with data quality, which will reduce reliability and robustness.
最后，对于城市防洪而言，在时间和空间上的预报，要求精度更高，速度更快，当前的预报方法，难以满足要求。因此需要研发创新，提供新的解决方案。Finally, for urban flood control, forecasting in time and space requires higher accuracy and faster speed. Current forecasting methods are difficult to meet the requirements. Therefore, R&D and innovation are needed to provide new solutions.
发明内容Contents of the invention
发明目的：提供一种用于城市防洪的智慧预警方法，以解决现有技术存在的上述问题。并进一步提供一种用于城市防洪的智慧预警系统，以实现上述方法。Purpose of the invention: Provide a smart early warning method for urban flood control to solve the above problems existing in the existing technology. And further provide a smart early warning system for urban flood control to implement the above method.
技术方案Technical solutions
根据本申请的一个方面，用于城市防洪的智慧预警方法，包括如下步骤：According to one aspect of this application, a smart early warning method for urban flood control includes the following steps:
步骤S1、确定研究区域范围，并获取研究数据；Step S1: Determine the scope of the research area and obtain research data;
步骤S2、从研究数据中提取历史降雨数据，获得降雨特征形成降雨特征集合；采用趋势分析法对降雨数据进行分析，分成至少两个时段；Step S2: Extract historical rainfall data from the research data, obtain rainfall characteristics and form a rainfall feature set; use the trend analysis method to analyze the rainfall data and divide it into at least two periods;
步骤S3、从研究数据中提取城市洪水数据，提取城市洪水特征形成城市洪水特征集合；采用趋势分析法对城市洪水进行分析；Step S3: Extract urban flood data from the research data, extract urban flood characteristics to form an urban flood feature set, and use trend analysis method to analyze urban floods;
步骤S4、构建降雨和城市洪水的关联性分析模型，基于降雨数据和城市洪水数据，针对每场降雨和城市洪水，计算降雨和城市洪水的相关性，并降序排列；Step S4: Construct a correlation analysis model between rainfall and urban floods. Based on the rainfall data and urban flood data, calculate the correlation between rainfall and urban floods for each rainfall and urban flood, and arrange them in descending order;
步骤S5、针对每一城市洪水，构建预警措施集合，形成研究区域的降雨与预警措施映射关系；Step S5: Construct a set of early warning measures for each urban flood to form a mapping relationship between rainfall and early warning measures in the study area;
步骤S6、构建水文水动力模型并基于研究数据进行率定，以当前实测降雨和城市洪水数据作为输入数据，进行模拟和预测，给出智慧预警信息和预警措施，并推送至各个终端。Step S6: Construct a hydrological and hydrodynamic model and calibrate it based on research data. Use the current measured rainfall and urban flood data as input data to simulate and predict, provide intelligent early warning information and early warning measures, and push them to various terminals.
根据本申请的一个方面，所述步骤S1进一步为：According to one aspect of the present application, the step S1 further includes:
步骤S11、获取城市所在流域的研究数据，所述研究数据至少包括数字高程模型、坡度、流向、流量、排水管网参数、降雨数据和城市洪水数据；Step S11: Obtain research data on the watershed where the city is located. The research data at least includes digital elevation model, slope, flow direction, flow, drainage pipe network parameters, rainfall data and urban flood data;
步骤S12、基于数字高程模型，获取第一边界和第二边界，其中第一边界为城市所在流域的流域边界；第二边界为城市防洪区域边界；第二边界包含于第一边界；Step S12: Obtain the first boundary and the second boundary based on the digital elevation model, where the first boundary is the boundary of the watershed where the city is located; the second boundary is the boundary of the urban flood control area; the second boundary is included in the first boundary;
步骤S13、将研究区域栅格化，并基于防洪目标提取第二边界内的重点区域，针对每一重点区域，查找重点区域对应的栅格并构建重点栅格集合；Step S13: Rasterize the study area, and extract key areas within the second boundary based on the flood control target. For each key area, find the grid corresponding to the key area and build a key grid set;
步骤S14、基于数字高程模型，提取城市水网结构，并逐一提取重点区域的水网和汇流数据。Step S14: Based on the digital elevation model, extract the urban water network structure, and extract water network and confluence data in key areas one by one.
根据本申请的一个方面，所述步骤S2进一步包括：According to one aspect of the present application, the step S2 further includes:
步骤S21、从研究数据中提取历史降雨数据，从降雨数据获得包括降雨中心、降雨半径、最大N天降雨量、降雨天数和累计降雨量在内的降雨特征；其中，N为1、3、5、7；Step S21: Extract historical rainfall data from the research data, and obtain rainfall characteristics including rainfall center, rainfall radius, maximum N-day rainfall, number of rainfall days and cumulative rainfall from the rainfall data; where N is 1, 3, 5 ,7;
步骤S22、构建趋势分析法集合，所属趋势分析法至少包括MK检验法和Sen’s斜率法；Step S22: Construct a set of trend analysis methods. The trend analysis methods include at least the MK test method and Sen’s slope method;
步骤S23、逐一采用趋势分析法进行趋势检测；Step S23: Use the trend analysis method to detect trends one by one;
其中，MK检验法的过程包括：首先计算每一对年份降雨量的差值，并采用正负号赋予符号值；计算每个年份的累积符号值并求出总和、方差、标准差和标准化统计量；基于标准化统计量与阈值的比较结果，判断是否存在显著的趋势；采用二分法查找降雨突变点，Among them, the process of the MK test method includes: first calculating the difference in rainfall for each pair of years, and assigning sign values using positive and negative signs; calculating the cumulative sign value for each year and finding the sum, variance, standard deviation and standardized statistics quantity; based on the comparison results of standardized statistics and thresholds, determine whether there is a significant trend; use the dichotomy method to find rainfall mutation points,
步骤S24、基于降雨突变点，将降雨数据分成至少两个时段。Step S24: Divide the rainfall data into at least two periods based on rainfall mutation points.
根据本申请的一个方面，所述步骤S3进一步为：According to one aspect of this application, the step S3 further includes:
步骤S31、从研究数据中提取城市洪水数据，采集城市洪水特征并形成城市洪水特征集合，所述城市洪水特征至少包括淹没范围、淹没时间、淹没深度、洪水总量、洪水历时、洪峰流量、峰现时间、起涨流量和涨峰段洪量；Step S31: Extract urban flood data from the research data, collect urban flood characteristics and form an urban flood characteristic set. The urban flood characteristics at least include inundation range, inundation time, inundation depth, total flood volume, flood duration, flood peak flow, and peak flow. Current time, rising flow rate and peak flood volume;
步骤S32、构建趋势分析法集合，所述趋势分析法至少包括MK检验法和移动平均法；Step S32: Construct a set of trend analysis methods, which at least include the MK test method and the moving average method;
其中，采用移动平均法进行趋势分析的过程包括：获取城市洪水数据并构建洪水时间序列，选择合适的时间窗口长度，并根据时间窗口长度计算每期的移动平均值；根据移动平均值绘制平滑曲线，并观察曲线的变化趋势，判断是否存在显著的上升或下降趋势；根据移动平均值和原始数据计算残差，即两者之间的差值，根据残差的绝对值或标准差判断是否存在洪水突变点，并确定其位置；Among them, the process of using the moving average method for trend analysis includes: obtaining urban flood data and constructing a flood time series, selecting an appropriate time window length, and calculating the moving average of each period based on the time window length; drawing a smooth curve based on the moving average , and observe the changing trend of the curve to determine whether there is a significant upward or downward trend; calculate the residual based on the moving average and the original data, that is, the difference between the two, and determine whether there is a significant upward or downward trend based on the absolute value or standard deviation of the residual. Flood mutation points and determining their locations;
所述移动平均值包括简单移动平均值SMA和指数移动平均值EMA，简单移动平均值SMA指时间窗口内各期数据的算术平均值；指数移动平均EMA指时间窗口内各期数据按照指数权重进行加权平均；The moving average includes a simple moving average SMA and an exponential moving average EMA. The simple moving average SMA refers to the arithmetic mean of the data in each period within the time window; the exponential moving average EMA refers to the data in each period within the time window based on exponential weights. Weighted average;
步骤S33、基于洪水突变点的情况，对城市洪水进行分期。Step S33: Stage the urban flood based on the sudden change point of the flood.
根据本申请的一个方面，所述步骤S4进一步为：According to one aspect of this application, the step S4 further includes:
步骤S41、构建降雨和城市洪水的关联性分析模型，所述关联性分析模型至少包括降雨分布分析单元；Step S41: Construct a correlation analysis model between rainfall and urban floods, where the correlation analysis model at least includes a rainfall distribution analysis unit;
步骤S42、针对每个时段的每一降雨，根据降雨中心的轨迹及降雨半径，查找影响的重点区域；建立各场降雨与重点区域的映射关系；Step S42: For each rainfall in each period, find the key areas affected according to the trajectory of the rainfall center and the rainfall radius; establish a mapping relationship between each rainfall and the key areas;
步骤S43、针对每一时期的每一洪水，查找每一重点区域发生的洪水与预定时间内每一降雨的关联关系，建立各个重点区域的城市洪水与关联的降雨之间的映射集合，并计算各场降雨对该重点区域的城市洪水的贡献度，并降序排列；获得每场城市洪水和各场降雨之间的相关性；Step S43: For each flood in each period, find the correlation between the floods in each key area and each rainfall within the predetermined time, establish a mapping set between urban floods in each key area and the associated rainfall, and calculate The contribution of each rainfall to the urban floods in the key area is sorted in descending order; the correlation between each urban flood and each rainfall is obtained;
步骤S44、基于重点区域之间的水网结构关系，对城市洪水和降雨的相关性进行关联性分析。Step S44: Perform correlation analysis on the correlation between urban floods and rainfall based on the water network structure relationship between key areas.
根据本申请的一个方面，所述步骤S5进一步为：According to one aspect of this application, the step S5 further includes:
步骤S51、构建预警措施总集；Step S51: Construct a collection of early warning measures;
步骤S52、建立洪水分级标准，并对每场洪水进行分类；Step S52: Establish flood classification standards and classify each flood;
步骤S53、根据洪水类型，形成对应给类型洪水的预警措施集合，形成研究区域内各类型洪水与预警措施之间的映射关系。Step S53: According to the flood type, form a set of early warning measures corresponding to the type of flood, and form a mapping relationship between various types of floods and early warning measures in the study area.
根据本申请的一个方面，所述步骤S6进一步为：According to one aspect of the present application, the step S6 further includes:
步骤S61、获取研究数据并进行预处理，使之符合水文水动力模型的要求；Step S61: Obtain research data and perform preprocessing to make it meet the requirements of the hydrological and hydrodynamic model;
步骤S62、构建水文水动力模型，采用GIS模块对研究区域的水网和管网进行概化；简化管网结构和拓扑关系；Step S62: Construct a hydrological and hydrodynamic model, and use the GIS module to generalize the water network and pipe network in the study area; simplify the pipe network structure and topological relationship;
步骤S63、利用DEM数据对研究区域的子集水区进行划分，确定各子集水区的参数，包括面积、坡度、土壤类型、建筑情况和植被覆盖；Step S63: Use DEM data to divide the sub-catchments of the study area and determine the parameters of each sub-catchment, including area, slope, soil type, construction conditions and vegetation coverage;
步骤S64、采用有限体积法对研究区域进行二维网格划分，并赋予各网格的网格参数，包括高程、粗糙度和边界条件；Step S64: Use the finite volume method to divide the study area into two-dimensional grids, and assign grid parameters to each grid, including elevation, roughness and boundary conditions;
步骤S65、采用包括同频率分析法、芝加哥法和暴雨时面深关系法在内的降雨设计方法，构建训练输入数据，对水文水动力模型进行率定；Step S65: Use rainfall design methods including the same frequency analysis method, the Chicago method and the heavy rain surface depth relationship method to construct training input data and calibrate the hydrological and hydrodynamic model;
步骤S66、获取当前的实测降雨和城市洪水数据，作为输入数据，进行模拟和预测，给出智慧预警信息和预警措施，推送至预定的各个终端。Step S66: Obtain the current measured rainfall and urban flood data as input data, conduct simulation and prediction, provide intelligent early warning information and early warning measures, and push them to various predetermined terminals.
根据本申请的一个方面，所述步骤S4还包括：According to one aspect of this application, the step S4 also includes:
步骤S40、基于降雨突变点和洪水突变点对重点区域的洪水进行标注：Step S40: Mark floods in key areas based on rainfall mutation points and flood mutation points:
分别判断降雨突变点和洪水突变点的数量是否超过各自的阈值；Determine whether the number of rainfall mutation points and flood mutation points exceeds their respective thresholds;
若是，分别进行聚类处理，直至断降雨突变点和洪水突变点的数量不高于预定的阈值；If so, perform clustering processing separately until the number of discontinuous rainfall mutation points and flood mutation points is no higher than the predetermined threshold;
若否，获取最近一段时期的降雨数据和洪水数据；If not, obtain rainfall data and flood data for the most recent period;
根据最近一段时期的降雨和洪水建立映射关系，并获得第一映射权重；Establish a mapping relationship based on rainfall and floods in the most recent period, and obtain the first mapping weight;
以第一映射权重重置其他各个时期的降雨与洪水的映射关系，更新映射权重，并进行检验。Use the first mapping weight to reset the mapping relationship between rainfall and floods in other periods, update the mapping weight, and conduct testing.
根据本申请的一个方面，所述步骤S42还包括：According to an aspect of the present application, the step S42 also includes:
获取降雨数据并生成栅格化降雨分布图；Obtain rainfall data and generate rasterized rainfall distribution map;
对降雨数据进行分割、识别和定位，提取出降雨中心、平均降雨量和降雨半径，将其转换为坐标系下的位置信息；Segment, identify and locate the rainfall data, extract the rainfall center, average rainfall and rainfall radius, and convert them into position information in the coordinate system;
利用时间序列分析方法对位置信息进行拟合、预测和平滑操作，得到降雨中心的运动轨迹，并根据降雨半径的变化情况，判断是否发生了降雨强度的变化；Use the time series analysis method to fit, predict and smooth the location information to obtain the movement trajectory of the rainfall center, and determine whether the rainfall intensity has changed based on the changes in the rainfall radius;
利用地理信息系统GIS将运动轨迹与重点区域的地图进行叠加，分析降雨中心的运动方向、速度和范围，并计算和评估其对重点防洪区域的影响程度。The geographic information system GIS is used to overlay the movement trajectory with the map of key areas, analyze the movement direction, speed and range of the rainfall center, and calculate and evaluate its impact on key flood control areas.
根据本申请的另一个方面，一种用于城市防洪的智慧预警系统，包括：According to another aspect of this application, a smart early warning system for urban flood control includes:
至少一个处理器；以及at least one processor; and
与至少一个所述处理器通信连接的存储器；其中，a memory communicatively connected to at least one of the processors; wherein,
所述存储器存储有可被所述处理器执行的指令，所述指令用于被所述处理器执行以实现上述任一项技术方案所述的用于城市防洪的智慧预警方法。The memory stores instructions that can be executed by the processor, and the instructions are used by the processor to implement the smart early warning method for urban flood control described in any of the above technical solutions.
有益效果：本申请克服了现有技术存在的缺陷，提高了机器学习的可解释性和鲁棒性，同时根据实际项目的测试结果来看，大大提高了预报预警的速度和精度。部分优势将在下文结合具体实施例来说明。Beneficial effects: This application overcomes the shortcomings of the existing technology, improves the interpretability and robustness of machine learning, and at the same time, according to the test results of actual projects, greatly improves the speed and accuracy of forecast and warning. Some of the advantages will be explained below in conjunction with specific embodiments.
附图说明Description of the drawings
图1是本发明的流程图。Figure 1 is a flow chart of the present invention.
图2是本发明步骤S1的流程图。Figure 2 is a flow chart of step S1 of the present invention.
图3是本发明步骤S2的流程图。Figure 3 is a flow chart of step S2 of the present invention.
图4是本发明步骤S3的流程图。Figure 4 is a flow chart of step S3 of the present invention.
图5是本发明步骤S4的流程图。Figure 5 is a flow chart of step S4 of the present invention.
图6是本发明步骤S5的流程图。Figure 6 is a flow chart of step S5 of the present invention.
图7是本发明步骤S6的流程图。Figure 7 is a flow chart of step S6 of the present invention.
具体实施方式Detailed ways
如图1所示，提供一种用于城市防洪的智慧预警方法，包括如下步骤：As shown in Figure 1, a smart early warning method for urban flood control is provided, including the following steps:
步骤S1、确定研究区域范围，并获取研究数据；Step S1: Determine the scope of the research area and obtain research data;
步骤S2、从研究数据中提取历史降雨数据，获得降雨特征形成降雨特征集合；采用趋势分析法对降雨数据进行分析，分成至少两个时段；Step S2: Extract historical rainfall data from the research data, obtain rainfall characteristics and form a rainfall feature set; use the trend analysis method to analyze the rainfall data and divide it into at least two periods;
步骤S3、从研究数据中提取城市洪水数据，提取城市洪水特征形成城市洪水特征集合；采用趋势分析法对城市洪水进行分析；Step S3: Extract urban flood data from the research data, extract urban flood characteristics to form an urban flood feature set, and use trend analysis method to analyze urban floods;
步骤S4、构建降雨和城市洪水的关联性分析模型，基于降雨数据和城市洪水数据，针对每场降雨和城市洪水，计算降雨和城市洪水的相关性，并降序排列；Step S4: Construct a correlation analysis model between rainfall and urban floods. Based on the rainfall data and urban flood data, calculate the correlation between rainfall and urban floods for each rainfall and urban flood, and arrange them in descending order;
步骤S5、针对每一城市洪水，构建预警措施集合，形成研究区域的降雨与预警措施映射关系；Step S5: Construct a set of early warning measures for each urban flood to form a mapping relationship between rainfall and early warning measures in the study area;
步骤S6、构建水文水动力模型并基于研究数据进行率定，以当前实测降雨和城市洪水数据作为输入数据，进行模拟和预测，给出智慧预警信息和预警措施，并推送至各个终端。Step S6: Construct a hydrological and hydrodynamic model and calibrate it based on research data. Use the current measured rainfall and urban flood data as input data to simulate and predict, provide intelligent early warning information and early warning measures, and push them to various terminals.
在本实施例中，通过分析城市降雨和洪水的历史变化趋势，揭示两者之间的关系和规律，为城市防洪排涝提供参考依据。通过从研究数据中提取历史降雨数据和城市洪水数据，采用趋势分析法对两者进行分析，可以发现城市降雨和洪水的变化特征、时空分布、频率强度等，并判断是否存在显著的上升或下降趋势，以及是否存在突变点或异常事件。通过基于降雨数据和城市洪水数据，针对每场降雨和城市洪水，计算降雨和城市洪水的相关性，并降序排列，可以找出影响城市洪水最大的降雨因素，如降雨强度、持续时间、分布范围等，并根据不同重现期的降雨场景，评估不同程度的城市洪水风险。通过针对每一场城市洪水，构建预警措施集合，如切断低洼地带电源、转移危险地带人员、检查排水系统、实行联排联调等，并根据不同程度的城市洪水风险，选择合适的预警措施，可以有效地减少城市内涝造成的人员伤亡和财产损失。通过构建水文水动力模型并基于研究数据进行率定，可以描述雨水在管网中的流动状态和地表漫流并形成积水的过程，并根据当前实测降雨和城市洪水数据作为输入数据，进行模拟和预测，可以实时地监测和预报城市内涝的发生、发展、消退等过程，并给出智慧预警信息和预警措施，并推送至各个终端。In this embodiment, by analyzing the historical trends of urban rainfall and floods, the relationship and rules between the two are revealed, providing a reference for urban flood control and drainage. By extracting historical rainfall data and urban flood data from the research data, and using the trend analysis method to analyze the two, we can discover the changing characteristics, spatiotemporal distribution, frequency intensity, etc. of urban rainfall and floods, and determine whether there is a significant increase or decrease. trends, and whether there are any sudden changes or unusual events. By calculating the correlation between rainfall and urban floods based on rainfall data and urban flood data, and arranging them in descending order, we can find out the rainfall factors that have the greatest impact on urban floods, such as rainfall intensity, duration, and distribution range. etc., and evaluate different levels of urban flood risks based on rainfall scenarios with different return periods. By building a set of early warning measures for each urban flood, such as cutting off power in low-lying areas, moving people in dangerous areas, checking drainage systems, implementing joint drainage and debugging, etc., and selecting appropriate early warning measures based on different levels of urban flood risks, It can effectively reduce casualties and property losses caused by urban waterlogging. By constructing a hydrological and hydrodynamic model and calibrating it based on research data, the flow state of rainwater in the pipe network and the process of surface overflow and accumulation of water can be described. Simulation and simulation can be carried out based on the current measured rainfall and urban flood data as input data. Forecasting can monitor and predict the occurrence, development, and subsidence of urban waterlogging in real time, and provide intelligent early warning information and early warning measures, and push them to various terminals.
可以提高城市防洪排涝的科学性和精确性，为城市规划、建设、管理提供支撑。通过利用数据分析和模型模拟的方法，可以更全面、更深入地了解城市降雨和洪水的特征、规律、风险等，为城市防洪排涝提供科学依据和精确信息，从而为城市规划、建设、管理提供支撑，提高城市的防灾减灾能力。提高城市防洪排涝的实时性和智能性，为城市应急响应提供保障。通过利用数据分析和模型模拟的方法，可以更及时、更智能地监测和预报城市内涝的情况，为城市应急响应提供保障，从而减少城市内涝造成的损失，提高城市的应急响应能力。It can improve the scientific nature and accuracy of urban flood control and drainage, and provide support for urban planning, construction, and management. By using data analysis and model simulation methods, we can gain a more comprehensive and in-depth understanding of the characteristics, patterns, and risks of urban rainfall and flooding, and provide scientific basis and accurate information for urban flood control and drainage, thus providing information for urban planning, construction, and management. Support and improve the city’s disaster prevention and reduction capabilities. Improve the real-time and intelligence of urban flood control and drainage to provide guarantee for urban emergency response. By using data analysis and model simulation methods, urban waterlogging can be monitored and forecasted in a more timely and intelligent manner to provide guarantee for urban emergency response, thereby reducing losses caused by urban waterlogging and improving the city's emergency response capabilities.
如图2所示，根据本申请的一个方面，所述步骤S1进一步为：As shown in Figure 2, according to one aspect of the present application, step S1 further includes:
步骤S11、获取城市所在流域的研究数据，所述研究数据至少包括数字高程模型、坡度、流向、流量、排水管网参数、降雨数据和城市洪水数据；可以从公开数据源获取研究数据，例如中国气象数据集、全球降水测量任务、国家地理信息公共服务平台等。上述数据可以帮助分析城市所在流域的地形地貌、水文水力特征、降雨洪水情况等。Step S11: Obtain research data on the watershed where the city is located. The research data at least includes digital elevation model, slope, flow direction, flow, drainage pipe network parameters, rainfall data and urban flood data; research data can be obtained from public data sources, such as China Meteorological data sets, global precipitation measurement tasks, national geographic information public service platform, etc. The above data can help analyze the topography, hydrology and hydraulic characteristics, rainfall and flood conditions of the watershed where the city is located.
步骤S12、基于数字高程模型，获取第一边界和第二边界，其中第一边界为城市所在流域的流域边界；第二边界为城市防洪区域边界；第二边界包含于第一边界；Step S12: Obtain the first boundary and the second boundary based on the digital elevation model, where the first boundary is the boundary of the watershed where the city is located; the second boundary is the boundary of the urban flood control area; the second boundary is included in the first boundary;
步骤S13、将研究区域栅格化，并基于防洪目标提取第二边界内的重点区域，针对每一重点区域，查找重点区域对应的栅格并构建重点栅格集合；可以基于防洪目标，提取第二边界内的重点区域，例如低洼地带、易积水路段、重要设施设备；重点栅格集合可以帮助分析重点区域的排涝风险和防治措施。Step S13: Rasterize the study area, and extract the key areas within the second boundary based on the flood control objectives. For each key area, find the grid corresponding to the key area and construct a key grid set; you can extract the second boundary based on the flood control objectives. Key areas within the second boundary, such as low-lying areas, road sections prone to water accumulation, and important facilities and equipment; key grid collections can help analyze drainage risks and prevention measures in key areas.
步骤S14、基于数字高程模型，提取城市水网结构，并逐一提取重点区域的水网和汇流数据。可以利用GIS等工具，基于数字高程模型，提取城市水网结构，包括河道、湖泊、排水管网等，并赋予各水网元素的长度、宽度、深度、截面形状等参数。上述水网和汇流数据可以帮助分析重点区域的排涝能力和影响因素。Step S14: Based on the digital elevation model, extract the urban water network structure, and extract water network and confluence data in key areas one by one. Tools such as GIS can be used to extract the urban water network structure, including rivers, lakes, drainage pipe networks, etc., based on digital elevation models, and assign parameters such as length, width, depth, and cross-sectional shape to each water network element. The above water network and catchment data can help analyze the drainage capacity and influencing factors of key areas.
在本实施例中，In this embodiment,
如图3所示，根据本申请的一个方面，所述步骤S2进一步包括：As shown in Figure 3, according to one aspect of the present application, the step S2 further includes:
步骤S21、从研究数据中提取历史降雨数据，从降雨数据获得包括降雨中心、降雨半径、最大N天降雨量、降雨天数和累计降雨量在内的降雨特征；其中，N为1、3、5、7；Step S21: Extract historical rainfall data from the research data, and obtain rainfall characteristics including rainfall center, rainfall radius, maximum N-day rainfall, number of rainfall days and cumulative rainfall from the rainfall data; where N is 1, 3, 5 ,7;
降雨中心指某一时段内，平均降雨量最大的区域。可以利用GIS等工具，根据每日的空间分布数据，计算出每个时段的平均降雨量，并找出最大值所在的区域。The rainfall center refers to the area with the highest average rainfall during a certain period of time. Tools such as GIS can be used to calculate the average rainfall in each period based on daily spatial distribution data and find the area where the maximum value is located.
降雨半径：指以降雨中心为圆心，平均降雨量为半径的圆形区域。可以利用GIS等工具，根据每日的空间分布数据，计算出每个时段的平均降雨量，并以其为半径画出圆形区域。Rainfall radius: refers to the circular area with the rainfall center as the center and the average rainfall as the radius. Tools such as GIS can be used to calculate the average rainfall in each period based on daily spatial distribution data, and draw a circular area with its radius.
最大N天降雨量指某一时段内，连续N天的累计降雨量最大值。可以利用Excel等工具，根据每日的累计降雨量数据，计算出每个时段内连续N天的累计降雨量，并找出最大值。其中，N为1、3、5、7。The maximum N-day rainfall refers to the maximum cumulative rainfall for N consecutive days within a certain period of time. You can use Excel and other tools to calculate the cumulative rainfall for N consecutive days in each period based on the daily cumulative rainfall data, and find the maximum value. Among them, N is 1, 3, 5, 7.
降雨天数指某一时段内，日降雨量大于等于0.1毫米的天数。可以利用Excel等工具，根据每日的日降雨量数据，统计出每个时段内满足条件的天数。Rainfall days refer to the number of days with daily rainfall greater than or equal to 0.1 mm within a certain period of time. You can use Excel and other tools to calculate the number of days that meet the conditions in each period based on daily rainfall data.
累计降雨量指某一时段内，所有日降雨量之和。可以利用Excel等工具，根据每日的日降雨量数据，求和得到每个时段的累计降雨量。Cumulative rainfall refers to the sum of all daily rainfall within a certain period of time. You can use Excel and other tools to sum up the daily rainfall data to get the cumulative rainfall for each period.
步骤S22、构建趋势分析法集合，所属趋势分析法至少包括MK检验法和Sen’s斜率法；Step S22: Construct a set of trend analysis methods. The trend analysis methods include at least the MK test method and Sen’s slope method;
MK检验法是用来检测时间序列是否存在显著趋势的方法。它的基本思想是将时间序列按时间顺序排列，并比较任意两个时期之间的差异，并根据正负号赋予符号值。然后计算累积符号值并求出总和、方差、标准差和标准化统计量。基于标准化统计量与阈值（如1.96）的比较结果，判断是否存在显著的趋势。如果标准化统计量绝对值大于阈值，则认为存在显著趋势；如果小于阈值，则认为不存在显著趋势；如果等于阈值，则认为趋势不确定。此外，还可以采用二分法查找降雨突变点，即在时间序列中找出使标准化统计量绝对值最大的分割点，作为降雨突变的时间。The MK test is a method used to detect whether there is a significant trend in a time series. Its basic idea is to arrange the time series in chronological order and compare the difference between any two periods and assign a sign value based on the sign. Then calculate the cumulative sign values and find the sum, variance, standard deviation, and standardized statistics. Based on the comparison between the standardized statistic and the threshold (such as 1.96), determine whether there is a significant trend. If the absolute value of the standardized statistic is greater than the threshold, it is considered that there is a significant trend; if it is less than the threshold, it is considered that there is no significant trend; if it is equal to the threshold, the trend is considered uncertain. In addition, the dichotomy method can also be used to find the rainfall mutation point, that is, the split point that maximizes the absolute value of the standardized statistics is found in the time series as the time of rainfall mutation.
Sen’s斜率法是用来估计时间序列的中位数斜率的方法。它的基本思想是将时间序列按时间顺序排列，并计算任意两个时期之间的斜率，并求出所有斜率的中位数作为整个时间序列的中位数斜率。中位数斜率可以反映时间序列的平均变化速率，如果中位数斜率大于零，则认为存在正向趋势；如果小于零，则认为存在负向趋势；如果等于零，则认为趋势不变。Sen’s slope method is a method used to estimate the median slope of a time series. Its basic idea is to arrange the time series in chronological order and calculate the slope between any two periods and find the median of all slopes as the median slope of the entire time series. The median slope can reflect the average rate of change of the time series. If the median slope is greater than zero, it is considered that there is a positive trend; if it is less than zero, it is considered that there is a negative trend; if it is equal to zero, the trend is considered unchanged.
步骤S23、逐一采用趋势分析法进行趋势检测；Step S23: Use the trend analysis method to detect trends one by one;
其中，MK检验法的过程包括：首先计算每一对年份降雨量的差值，并采用正负号赋予符号值；计算每个年份的累积符号值并求出总和、方差、标准差和标准化统计量；基于标准化统计量与阈值的比较结果，判断是否存在显著的趋势；采用二分法查找降雨突变点。Among them, the process of the MK test method includes: first calculating the difference in rainfall for each pair of years, and assigning sign values using positive and negative signs; calculating the cumulative sign value for each year and finding the sum, variance, standard deviation and standardized statistics quantity; based on the comparison results of standardized statistics and thresholds, determine whether there is a significant trend; use the dichotomy method to find rainfall mutation points.
例如，2001年和2000年的差值为-5.6，符号值为-1；2002年和2000年的差值为-3.2，符号值为-1；以此类推，得到所有符号值。For example, the difference between 2001 and 2000 is -5.6, and the sign value is -1; the difference between 2002 and 2000 is -3.2, and the sign value is -1; and so on, all sign values are obtained.
2000年的累积符号值为0；2001年的累积符号值为-1；2002年的累积符号值为-2；以此类推，得到所有累积符号值。总和为-21，方差为105，标准差为10.25，标准化统计量为-2.05。基于标准化统计量与阈值（如1.96）的比较结果，判断是否存在显著的趋势。由于标准化统计量绝对值大于阈值，因此认为存在显著的负向趋势，即降雨量呈现下降趋势。采用二分法查找降雨突变点，即在时间序列中找出使标准化统计量绝对值最大的分割点，作为降雨突变的时间。例如，将时间序列分成两部分:2000年至2010年和2011年至2020年，分别计算两部分的标准化统计量，发现前半部分为-2.58，后半部分为-1.41，因此认为2010年是降雨突变点。The cumulative symbol value in 2000 is 0; the cumulative symbol value in 2001 is -1; the cumulative symbol value in 2002 is -2; and so on, all cumulative symbol values are obtained. The sum is -21, the variance is 105, the standard deviation is 10.25, and the standardized statistic is -2.05. Based on the comparison between the standardized statistic and the threshold (such as 1.96), determine whether there is a significant trend. Since the absolute value of the standardized statistic is greater than the threshold, it is considered that there is a significant negative trend, that is, the rainfall shows a downward trend. The dichotomy method is used to find the rainfall mutation point, that is, the split point that maximizes the absolute value of the standardized statistics is found in the time series as the time of rainfall mutation. For example, divide the time series into two parts: 2000 to 2010 and 2011 to 2020, calculate the standardized statistics of the two parts respectively, and find that the first half is -2.58 and the second half is -1.41, so it is considered that 2010 was the year of rainfall Discontinuity.
采用二分法查找降雨突变点，即在时间序列中找出使标准化统计量绝对值最大的分割点，作为降雨突变的时间。例如，将时间序列分成两部分:2000年至2010年和2011年至2020年，分别计算两部分的标准化统计量，发现前半部分为-2.58，后半部分为-1.41，因此认为2010年是降雨突变点。由于中位数斜率小于零，因此认为存在负向趋势，即降雨量呈现下降趋势。The dichotomy method is used to find the rainfall mutation point, that is, the split point that maximizes the absolute value of the standardized statistics is found in the time series as the time of rainfall mutation. For example, divide the time series into two parts: 2000 to 2010 and 2011 to 2020, calculate the standardized statistics of the two parts respectively, and find that the first half is -2.58 and the second half is -1.41, so it is considered that 2010 was the year of rainfall Discontinuity. Since the median slope is less than zero, a negative trend is considered to exist, i.e., rainfall is showing a downward trend.
步骤S24、基于降雨突变点，将降雨数据分成至少两个时段。Step S24: Divide the rainfall data into at least two periods based on rainfall mutation points.
如图4所示，根据本申请的一个方面，所述步骤S3进一步为：As shown in Figure 4, according to one aspect of the present application, the step S3 further includes:
步骤S31、从研究数据中提取城市洪水数据，采集城市洪水特征并形成城市洪水特征集合，所述城市洪水特征至少包括淹没范围、淹没时间、淹没深度、洪水总量、洪水历时、洪峰流量、峰现时间、起涨流量和涨峰段洪量。Step S31: Extract urban flood data from the research data, collect urban flood characteristics and form an urban flood characteristic set. The urban flood characteristics at least include inundation range, inundation time, inundation depth, total flood volume, flood duration, flood peak flow, and peak flow. Current time, peak flow rate and peak flow volume.
为了获取城市洪水数据，可以使用遥感技术或社会感知技术来监测和提取洪水淹没范围。遥感技术利用卫星或无人机拍摄的影像，通过图像处理和分析方法，识别出水体和非水体区域，从而得到淹没范围和深度。社会感知技术利用社交媒体或其他网络平台上的用户发布的信息，通过自然语言处理和地理信息系统方法，提取出含有洪涝地点的文本或图片，从而得到淹没范围。可以根据数据的可用性和质量，选择合适的技术或结合使用多种技术来获取更准确的结果。To obtain urban flood data, remote sensing technology or social sensing technology can be used to monitor and extract flood inundation extent. Remote sensing technology uses images taken by satellites or drones to identify water and non-water areas through image processing and analysis methods to obtain the extent and depth of flooding. Social sensing technology uses information posted by users on social media or other online platforms, and uses natural language processing and geographic information system methods to extract text or pictures containing flood locations to obtain the flooding range. Depending on the availability and quality of data, you can choose the appropriate technique or use a combination of techniques to get more accurate results.
为了采集城市洪水特征，可以使用水文站点或传感器网络来监测和记录洪水过程中的各项参数，如流量、水位、降雨量等。可以利用历史数据或统计模型来估计或推断这些参数。可以根据数据的可用性和精度，选择合适的方法或结合使用多种方法来获取更完整的数据。In order to collect urban flood characteristics, hydrological stations or sensor networks can be used to monitor and record various parameters during the flood process, such as flow, water level, rainfall, etc. These parameters can be estimated or inferred using historical data or statistical models. Depending on the availability and accuracy of the data, an appropriate method can be selected or a combination of methods can be used to obtain more complete data.
为了形成城市洪水特征集合，可以将提取或采集到的数据进行整理和归纳，按照不同的时间尺度（如年、月、日等）或空间尺度（如流域、区域、街道等）进行分类和汇总，从而得到不同层次的城市洪水特征。可以根据分析目的和需求，选择合适的尺度或结合使用多种尺度来获取更有意义的特征。In order to form a collection of urban flood characteristics, the extracted or collected data can be organized and summarized, and classified and summarized according to different time scales (such as years, months, days, etc.) or spatial scales (such as watersheds, regions, streets, etc.) , thereby obtaining urban flood characteristics at different levels. Depending on the analysis purpose and needs, you can choose an appropriate scale or use multiple scales in combination to obtain more meaningful features.
步骤S32、构建趋势分析法集合，所述趋势分析法至少包括MK检验法和移动平均法；Step S32: Construct a set of trend analysis methods, which at least include the MK test method and the moving average method;
其中，采用移动平均法进行趋势分析的过程包括：获取城市洪水数据并构建洪水时间序列，选择合适的时间窗口长度，并根据时间窗口长度计算每期的移动平均值；根据移动平均值绘制平滑曲线，并观察曲线的变化趋势，判断是否存在显著的上升或下降趋势；根据移动平均值和原始数据计算残差，即两者之间的差值，根据残差的绝对值或标准差判断是否存在洪水突变点，并确定其位置；Among them, the process of using the moving average method for trend analysis includes: obtaining urban flood data and constructing a flood time series, selecting an appropriate time window length, and calculating the moving average of each period based on the time window length; drawing a smooth curve based on the moving average , and observe the changing trend of the curve to determine whether there is a significant upward or downward trend; calculate the residual based on the moving average and the original data, that is, the difference between the two, and determine whether there is a significant upward or downward trend based on the absolute value or standard deviation of the residual. Flood mutation points and determining their location;
所述移动平均值包括简单移动平均值SMA和指数移动平均值EMA，简单移动平均值SMA指时间窗口内各期数据的算术平均值；指数移动平均EMA指时间窗口内各期数据按照指数权重进行加权平均；The moving average includes a simple moving average SMA and an exponential moving average EMA. The simple moving average SMA refers to the arithmetic mean of the data in each period within the time window; the exponential moving average EMA refers to the data in each period within the time window based on exponential weights. Weighted average;
在某个实施例中，首先，选择一个或多个城市洪水特征作为分析对象，如年最大日降雨量、年最大洪峰流量等；其次，选择一个或多个时间尺度作为分析单位，如年、季、月等；然后，选择一个或多个趋势分析法作为分析方法，如MK检验法和移动平均法等；最后，对每个分析对象在每个时间尺度上应用每个分析方法，得到趋势分析结果，并进行综合比较和评价。In an embodiment, first, one or more urban flood characteristics are selected as the analysis object, such as annual maximum daily rainfall, annual maximum peak flow, etc.; secondly, one or more time scales are selected as the analysis unit, such as year, Quarterly, monthly, etc.; then, select one or more trend analysis methods as analysis methods, such as MK test method and moving average method; finally, apply each analysis method to each analysis object on each time scale to obtain the trend Analyze the results and make comprehensive comparisons and evaluations.
步骤S33、基于洪水突变点的情况，对城市洪水进行分期。Step S33: Stage the urban flood based on the sudden change point of the flood.
在某个实施例中，选择一个或多个突变检测法作为分析方法，如累积和法、滑动t检验法、Mann-Kendall-Sneyers法等；对每个分析对象在每个时间尺度上应用每个分析方法，得到突变检测结果，并根据突变点的位置和数量，将城市洪水划分为不同的阶段。In a certain embodiment, one or more mutation detection methods are selected as the analysis method, such as cumulative sum method, sliding t test method, Mann-Kendall-Sneyers method, etc.; each analysis object is applied on each time scale. An analysis method is used to obtain mutation detection results, and urban floods are divided into different stages according to the location and number of mutation points.
如图5所示，根据本申请的一个方面，所述步骤S4进一步为：As shown in Figure 5, according to one aspect of the present application, the step S4 further includes:
步骤S41、构建降雨和城市洪水的关联性分析模型，所述关联性分析模型至少包括降雨分布分析单元；可以利用GIS等工具，根据降雨数据的空间分布，将研究区域划分为若干个网格单元，并计算每个单元的平均降雨量、最大降雨量、降雨频率等参数，形成降雨分布分析单元。这些单元可以帮助描述降雨的空间异质性和变化规律。Step S41: Construct a correlation analysis model of rainfall and urban floods. The correlation analysis model at least includes a rainfall distribution analysis unit; GIS and other tools can be used to divide the study area into several grid units according to the spatial distribution of rainfall data. , and calculate the average rainfall, maximum rainfall, rainfall frequency and other parameters of each unit to form a rainfall distribution analysis unit. These units can help describe the spatial heterogeneity and variation patterns of rainfall.
步骤S42、针对每个时段的每一降雨，根据降雨中心的轨迹及降雨半径，查找影响的重点区域；建立各场降雨与重点区域的映射关系；Step S42: For each rainfall in each period, find the key areas affected according to the trajectory of the rainfall center and the rainfall radius; establish a mapping relationship between each rainfall and the key areas;
可以利用GIS等工具，根据每场降雨的中心位置、移动方向、移动速度和半径，绘制出每场降雨的轨迹，并与重点区域的边界进行叠加，找出被影响的重点区域，并记录下每场降雨对每个重点区域的影响时间和影响程度，形成各场降雨与重点区域的映射关系。这些关系可以帮助识别出不同降雨对不同重点区域的影响范围和强度。Tools such as GIS can be used to draw the trajectory of each rainfall based on its center position, moving direction, moving speed and radius, and overlay it with the boundaries of key areas to identify the affected key areas and record them. The impact time and degree of each rainfall on each key area forms a mapping relationship between each rainfall and the key areas. These relationships can help identify the range and intensity of impacts of different rainfalls on different focus areas.
步骤S43、针对每一时期的每一洪水，查找每一重点区域发生的洪水与预定时间内每一降雨的关联关系，建立各个重点区域的城市洪水与关联的降雨之间的映射集合，并计算各场降雨对该重点区域的城市洪水的贡献度，并降序排列；获得每场城市洪水和各场降雨之间的相关性；Step S43: For each flood in each period, find the correlation between the floods in each key area and each rainfall within the predetermined time, establish a mapping set between urban floods in each key area and the associated rainfall, and calculate The contribution of each rainfall to the urban floods in the key area is sorted in descending order; the correlation between each urban flood and each rainfall is obtained;
利用Excel等工具，根据每一重点区域发生的洪水时间和持续时间，确定与之相关联的预定时间内（如前后24小时）的所有降雨，并记录下每一洪水与每一降雨之间的时间差和空间距离，形成各个重点区域的城市洪水与关联的降雨之间的映射集合。然后，可以利用相关性分析或回归分析等方法，计算各场降雨对该重点区域的城市洪水的贡献度，并按照贡献度大小进行排序，得到每场城市洪水和各场降雨之间的相关性。这些相关性可以帮助评估不同降雨对不同重点区域造成城市洪水风险的大小和敏感性。Use tools such as Excel to determine all rainfall within a predetermined time period (such as 24 hours before and after) based on the time and duration of flooding in each key area, and record the time between each flood and each rainfall. The time difference and spatial distance form a set of mappings between urban floods and associated rainfall in each key area. Then, methods such as correlation analysis or regression analysis can be used to calculate the contribution of each rainfall to the urban floods in the key area, and sort them according to the contribution, to obtain the correlation between each urban flood and each rainfall. . These correlations can help assess the magnitude and susceptibility of urban flooding risks posed by different rainfalls to different focus areas.
步骤S44、基于重点区域之间的水网结构关系，对城市洪水和降雨的相关性进行关联性分析。Step S44: Perform correlation analysis on the correlation between urban floods and rainfall based on the water network structure relationship between key areas.
利用GIS等工具，根据重点区域之间的水网结构关系，如河道、排水管网、涵洞等，确定重点区域之间的水流方向和水流量，并记录下每个重点区域的入流量和出流量，形成重点区域之间的水网结构关系矩阵。然后，可以利用网络分析或系统动力学等方法，分析重点区域之间的水网结构关系对城市洪水和降雨的相关性的影响，并得到重点区域之间的城市洪水和降雨的关联性。这些关联性可以帮助理解不同重点区域之间的城市洪水传播和扩散机制和路径。Use GIS and other tools to determine the water flow direction and flow rate between key areas based on the water network structural relationship between key areas, such as rivers, drainage pipe networks, culverts, etc., and record the inflow and outflow of each key area. Flow forms a water network structure relationship matrix between key areas. Then, methods such as network analysis or system dynamics can be used to analyze the impact of the water network structural relationship between key areas on the correlation between urban floods and rainfall, and obtain the correlation between urban floods and rainfall between key areas. These correlations can help understand urban flood propagation and diffusion mechanisms and pathways between different focus areas.
如图6所示，根据本申请的一个方面，所述步骤S5进一步为：As shown in Figure 6, according to one aspect of the present application, the step S5 further includes:
步骤S51、构建预警措施总集；Step S51: Construct a collection of early warning measures;
分析研究区域的洪水特征、防洪责任、防洪能力和防洪需求，确定防洪目标和预警目标；参考国家和地方的相关标准和规范，确定洪水等级和预警级别的划分依据和标准；根据洪水等级和预警级别，设计不同的预警信息内容、发布渠道、发布时机和发布频率；根据洪水等级和预警级别，制定不同的防洪组织指挥体系、职责分工、协调机制和信息沟通方式；根据洪水等级和预警级别，制定不同的人员转移疏散计划、安置点设置、物资准备和交通保障措施；根据洪水等级和预警级别，制定不同的工程设施运行调度方案、运行参数、运行模式和运行效果评估方法；根据洪水等级和预警级别，制定不同的应急救援队伍配置、救援物资储备、救援方案制定和救援效果评估方法。Analyze the flood characteristics, flood control responsibilities, flood control capabilities and flood control needs in the study area, and determine flood control goals and early warning goals; refer to relevant national and local standards and regulations to determine the basis and criteria for classifying flood levels and early warning levels; according to flood levels and early warning levels level, design different early warning information content, release channels, release timing and release frequency; according to the flood level and early warning level, formulate different flood control organization command systems, division of responsibilities, coordination mechanisms and information communication methods; according to the flood level and early warning level, Formulate different personnel transfer and evacuation plans, resettlement site settings, material preparation and traffic support measures; formulate different engineering facility operation scheduling plans, operating parameters, operation modes and operation effect evaluation methods according to flood levels and early warning levels; according to flood levels and early warning levels, According to the early warning level, different emergency rescue team configurations, rescue material reserves, rescue plan formulation and rescue effect evaluation methods are formulated.
步骤S52、建立洪水分级标准，并对每场洪水进行分类；Step S52: Establish flood classification standards and classify each flood;
收集研究区域的历史或模拟的洪水要素数据，进行频率分析或极值分析，计算不同重现期或可能最大值对应的洪水要素值；参考国家或地方的相关规范，确定适用于研究区域的重现期或可能最大值范围，以及相应的洪水等级划分标准；根据洪水等级划分标准，对每场历史或模拟的洪水进行分类，并统计各个等级的出现频率和占比。Collect historical or simulated flood element data in the study area, conduct frequency analysis or extreme value analysis, and calculate the flood element values corresponding to different return periods or possible maximum values; refer to relevant national or local regulations to determine the important values applicable to the study area. The current or possible maximum value range, and the corresponding flood grade classification standards; classify each historical or simulated flood according to the flood grade classification standards, and count the frequency and proportion of each grade.
步骤S53、根据洪水类型，形成对应给类型洪水的预警措施集合，形成研究区域内各类型洪水与预警措施之间的映射关系。Step S53: According to the flood type, form a set of early warning measures corresponding to the type of flood, and form a mapping relationship between various types of floods and early warning measures in the study area.
形成对应给类型洪水的预警措施集合的步骤包括：分析研究区域的洪水类型特征，如发生条件、发展规律、影响程度、持续时间等；根据洪水类型特征，从预警措施总集中选择适合的预警措施，如预警信息内容、发布时机、人员转移路线、工程设施运行模式等；根据洪水类型和预警措施的匹配程度，确定不同类型洪水的预警措施优先级和执行顺序。The steps to form a set of early warning measures corresponding to a given type of flood include: analyzing the characteristics of the flood type in the study area, such as occurrence conditions, development patterns, degree of impact, duration, etc.; and selecting appropriate early warning measures from the total set of early warning measures based on the characteristics of the flood type. , such as early warning information content, release timing, personnel transfer routes, engineering facility operation modes, etc.; determine the priority and execution order of early warning measures for different types of floods based on the matching degree of flood types and early warning measures.
形成研究区域内各类型洪水与预警措施之间的映射关系的步骤包括：建立一个二维表格，横轴为洪水类型，纵轴为预警措施；在表格中填写每个洪水类型对应的预警措施集合，以及优先级和执行顺序；将表格转换为一种便于理解和使用的图形或符号表示，如流程图、树形图、矩阵图等。The steps to form the mapping relationship between various types of floods and early warning measures in the study area include: establishing a two-dimensional table, with the horizontal axis being flood types and the vertical axis being early warning measures; filling in the set of early warning measures corresponding to each flood type in the table , as well as priority and execution order; convert the table into a graphical or symbolic representation that is easy to understand and use, such as flow charts, tree diagrams, matrix diagrams, etc.
如图7所示，根据本申请的一个方面，所述步骤S6进一步为：As shown in Figure 7, according to one aspect of the present application, the step S6 further includes:
步骤S61、获取研究数据并进行预处理，使之符合水文水动力模型的要求；Step S61: Obtain research data and perform preprocessing to make it meet the requirements of the hydrological and hydrodynamic model;
可以使用遥感技术、水文站点、传感器网络、社会感知技术等方法，收集研究区域的降雨数据、流量数据、水位数据、水质数据、地形数据、土壤数据、植被数据等。也可以利用历史数据或统计模型来估计或推断这些数据。Remote sensing technology, hydrological sites, sensor networks, social sensing technology and other methods can be used to collect rainfall data, flow data, water level data, water quality data, terrain data, soil data, vegetation data, etc. in the study area. Historical data or statistical models may also be used to estimate or extrapolate these data.
步骤S62、构建水文水动力模型，采用GIS模块对研究区域的水网和管网进行概化；简化管网结构和拓扑关系；Step S62: Construct a hydrological and hydrodynamic model, and use the GIS module to generalize the water network and pipe network in the study area; simplify the pipe network structure and topological relationship;
可以使用Excel、ArcGIS、MATLAB等工具，对收集到的数据进行清洗、校正、插补、转换、抽样等操作，使之符合水文水动力模型的要求。You can use Excel, ArcGIS, MATLAB and other tools to clean, correct, interpolate, convert, sample and other operations on the collected data to make it meet the requirements of the hydrological and hydrodynamic model.
可以使用SWMM、HEC-HMS等专业软件，或者自行编写基于有限体积法的数值模拟程序，实现对研究区域的地表径流和管网排水过程的模拟计算。You can use professional software such as SWMM, HEC-HMS, or write your own numerical simulation program based on the finite volume method to simulate the surface runoff and pipe network drainage processes in the study area.
可以使用ArcGIS等工具，根据研究区域的地理信息和工程信息，绘制出水网和管网的空间分布，并赋予各个元素（如河道、排水管道、涵洞、泵站等）相应的属性（如长度、宽度、深度、粗糙度、容量等）。You can use tools such as ArcGIS to draw the spatial distribution of water networks and pipe networks based on the geographical information and engineering information of the study area, and assign corresponding attributes (such as length, length, etc.) to each element (such as rivers, drainage pipes, culverts, pumping stations, etc.). width, depth, roughness, capacity, etc.).
为了简化管网结构和拓扑关系，可以使用SWMM等软件，根据管网排水过程中的流量分配规律和压力平衡原则，对管网中的冗余元素（如无流量或无压力变化的管道）进行剔除或合并，并调整相邻元素之间的连接关系。可以根据模型的计算效率和稳定性，选择合适的软件或结合使用多种软件来进行更合理和简洁的简化。In order to simplify the pipe network structure and topological relationship, software such as SWMM can be used to analyze redundant elements in the pipe network (such as pipes with no flow or pressure changes) based on the flow distribution rules and pressure balance principles in the pipe network drainage process. Eliminate or merge, and adjust connections between adjacent elements. Based on the computational efficiency and stability of the model, appropriate software can be selected or a combination of multiple software can be used for more reasonable and concise simplification.
步骤S63、利用DEM数据对研究区域的子集水区进行划分，确定各子集水区的参数，包括面积、坡度、土壤类型、建筑情况和植被覆盖；Step S63: Use DEM data to divide the sub-catchments of the study area and determine the parameters of each sub-catchment, including area, slope, soil type, construction conditions and vegetation coverage;
使用ArcGIS等工具，根据DEM数据的高程信息，利用流向分析和流累积分析等方法，识别出研究区域的汇水分界线，并按照一定的标准（如面积、形状、位置等）将研究区域划分为若干个子集水区。使用ArcGIS等工具，根据DEM数据、土壤数据、建筑数据、植被数据等，利用统计分析和空间分析等方法，计算出各子集水区的面积、坡度、土壤类型、建筑情况和植被覆盖等参数。Use tools such as ArcGIS, based on the elevation information of DEM data, and use methods such as flow direction analysis and flow accumulation analysis to identify the catchment lines of the study area, and divide the study area into Several sub-catchments. Use tools such as ArcGIS to calculate parameters such as area, slope, soil type, building conditions, and vegetation coverage of each sub-catchment based on DEM data, soil data, building data, vegetation data, etc., and using statistical analysis and spatial analysis methods. .
步骤S64、采用有限体积法对研究区域进行二维网格划分，并赋予各网格的网格参数，包括高程、粗糙度和边界条件；Step S64: Use the finite volume method to divide the study area into two-dimensional grids, and assign grid parameters to each grid, including elevation, roughness and boundary conditions;
使用MATLAB等工具，根据研究区域的地形特征和计算需求，利用三角剖分或四边形剖分等方法，将研究区域划分为若干个有限体积单元，并记录下各单元的顶点坐标、邻接关系和控制面信息。使用ArcGIS等工具，根据DEM数据、粗糙度数据、边界条件数据等，利用插值分析和空间分析等方法，计算出各单元的高程、粗糙度和边界条件等参数，并将其导入到MATLAB等工具中。Use tools such as MATLAB to divide the study area into several finite volume units according to the terrain characteristics and computing requirements of the study area, using methods such as triangulation or quadrilateral division, and record the vertex coordinates, adjacency relationships and controls of each unit. face information. Use tools such as ArcGIS to calculate the elevation, roughness, boundary conditions and other parameters of each unit based on DEM data, roughness data, boundary condition data, etc., using methods such as interpolation analysis and spatial analysis, and import them into tools such as MATLAB middle.
步骤S65、采用包括同频率分析法、芝加哥法和暴雨时面深关系法在内的降雨设计方法，构建训练输入数据，对水文水动力模型进行率定；Step S65: Use rainfall design methods including the same frequency analysis method, the Chicago method and the heavy rain surface depth relationship method to construct training input data and calibrate the hydrological and hydrodynamic model;
使用ArcGIS等工具，根据DEM数据、粗糙度数据、边界条件数据等，利用插值分析和空间分析等方法，计算出各单元的高程、粗糙度和边界条件等参数，并将其导入到MATLAB等工具中。使用SWMM等软件，根据构建好的模型和生成好的训练输入数据，进行模拟计算，并将计算结果与实测结果进行对比和评价，利用优化算法或人工调整等方法，调整模型中的参数或结构，使模拟结果与实测结果尽可能接近，并达到预定的精度和稳定性。Use tools such as ArcGIS to calculate the elevation, roughness, boundary conditions and other parameters of each unit based on DEM data, roughness data, boundary condition data, etc., using methods such as interpolation analysis and spatial analysis, and import them into tools such as MATLAB middle. Use software such as SWMM to perform simulation calculations based on the constructed model and generated training input data, compare and evaluate the calculation results with the measured results, and use optimization algorithms or manual adjustments to adjust parameters or structures in the model. , so that the simulation results are as close as possible to the actual measurement results, and achieve predetermined accuracy and stability.
步骤S66、获取当前的实测降雨和城市洪水数据，作为输入数据，进行模拟和预测，给出智慧预警信息和预警措施，推送至预定的各个终端。Step S66: Obtain the current measured rainfall and urban flood data as input data, conduct simulation and prediction, provide intelligent early warning information and early warning measures, and push them to various predetermined terminals.
使用遥感技术、水文站点、传感器网络、社会感知技术等方法，实时或定时收集研究区域的降雨数据、流量数据、水位数据、水质数据等，并将其转换为适合模型输入的格式。使用SWMM等软件，根据率定好的模型和获取到的输入数据，进行模拟计算，并根据一定的规则或算法，给出当前或未来一段时间内研究区域内各个重点区域的城市洪水情况和风险等级。使用Excel等工具，根据模拟和预测结果与预警措施总集中的映射关系，确定适用于当前或未来一段时间内研究区域内各个重点区域的城市洪水情况和风险等级的预警信息内容、发布渠道、发布时机和发布频率以及预警措施内容、执行主体、执行时机和执行顺序。使用微信、短信、广播等工具，根据预警信息内容、发布渠道、发布时机和发布频率，将预警信息发送给预定的各个终端，如政府部门、防洪单位、媒体机构、公众等，并根据反馈信息进行调整和优化。Use remote sensing technology, hydrological sites, sensor networks, social sensing technology and other methods to collect rainfall data, flow data, water level data, water quality data, etc. in the study area in real time or regularly, and convert them into a format suitable for model input. Use software such as SWMM to perform simulation calculations based on the calculated model and acquired input data, and provide urban flood conditions and risk levels for each key area in the current or future study area based on certain rules or algorithms. . Using Excel and other tools, based on the mapping relationship between simulation and prediction results and the total concentration of early warning measures, determine the early warning information content, release channels, and release applicable to urban flood conditions and risk levels in various key areas in the study area currently or in the future. Timing and release frequency, as well as the content of early warning measures, execution subjects, execution timing and execution sequence. Use WeChat, SMS, broadcast and other tools to send early warning information to various predetermined terminals, such as government departments, flood control units, media organizations, the public, etc., based on the content of the early warning information, release channels, release timing and release frequency, and based on the feedback information Make adjustments and optimizations.
根据本申请的一个方面，所述步骤S4还包括：According to one aspect of this application, the step S4 also includes:
步骤S40、基于降雨突变点和洪水突变点对重点区域的洪水进行标注：Step S40: Mark floods in key areas based on rainfall mutation points and flood mutation points:
分别判断降雨突变点和洪水突变点的数量是否超过各自的阈值；Determine whether the number of rainfall mutation points and flood mutation points exceeds their respective thresholds;
若是，分别进行聚类处理，直至断降雨突变点和洪水突变点的数量不高于预定的阈值；If so, perform clustering processing separately until the number of discontinuous rainfall mutation points and flood mutation points is no higher than the predetermined threshold;
若否，获取最近一段时期的降雨数据和洪水数据；If not, obtain rainfall data and flood data for the most recent period;
根据最近一段时期的降雨和洪水建立映射关系，并获得第一映射权重；Establish a mapping relationship based on rainfall and floods in the most recent period, and obtain the first mapping weight;
以第一映射权重重置其他各个时期的降雨与洪水的映射关系，更新映射权重，并进行检验。Use the first mapping weight to reset the mapping relationship between rainfall and floods in other periods, update the mapping weight, and conduct testing.
本实施例，通过上述方案，可以有效地识别出重点区域的洪水发生的时间和范围，为洪水预警和防治提供依据；利用降雨和洪水之间的映射关系，反推出不同时期的降雨情况，为降雨监测和分析提供数据支持；根据不同时期的降雨和洪水数据，动态更新映射权重，提高模型的精度和适应性；能够通过聚类处理，减少降雨突变点和洪水突变点的数量，降低计算复杂度和存储空间。解决了由于气候变化和下垫面变化造成降雨和洪水序列发生变化，从而根据当前的参数进行预报，大大提高了预报的准确率。In this embodiment, through the above solution, the time and scope of flood occurrence in key areas can be effectively identified, providing a basis for flood warning and prevention; using the mapping relationship between rainfall and floods, the rainfall conditions in different periods can be deduced to provide Rainfall monitoring and analysis provide data support; dynamically update mapping weights based on rainfall and flood data in different periods to improve the accuracy and adaptability of the model; it can reduce the number of rainfall mutation points and flood mutation points through clustering processing, and reduce computational complexity degree and storage space. It solves the changes in rainfall and flood sequences caused by climate change and underlying surface changes, thereby making forecasts based on current parameters and greatly improving the accuracy of forecasts.
根据本申请的一个方面，所述步骤S42还包括：According to an aspect of the present application, the step S42 also includes:
获取降雨数据并生成栅格化降雨分布图；Obtain rainfall data and generate rasterized rainfall distribution map;
对降雨数据进行分割、识别和定位，提取出降雨中心、平均降雨量和降雨半径，将其转换为坐标系下的位置信息；Segment, identify and locate the rainfall data, extract the rainfall center, average rainfall and rainfall radius, and convert them into position information in the coordinate system;
利用时间序列分析方法对位置信息进行拟合、预测和平滑操作，得到降雨中心的运动轨迹，并根据降雨半径的变化情况，判断是否发生了降雨强度的变化；Use the time series analysis method to fit, predict and smooth the location information to obtain the movement trajectory of the rainfall center, and determine whether the rainfall intensity has changed based on the changes in the rainfall radius;
利用地理信息系统GIS将运动轨迹与重点区域的地图进行叠加，分析降雨中心的运动方向、速度和范围，并计算和评估其对重点防洪区域的影响程度。The geographic information system GIS is used to overlay the movement trajectory with the map of key areas, analyze the movement direction, speed and range of the rainfall center, and calculate and evaluate its impact on key flood control areas.
在本实施例中，利用栅格化降雨分布图，更精确地描述降雨的空间分布和变化，为洪水标注提供更细致的数据基础；通过分割、识别和定位降雨数据，提取出降雨中心、平均降雨量和降雨半径等关键参数，为洪水标注提供更有效的特征信息；利用时间序列分析方法，对降雨中心的位置信息进行拟合、预测和平滑操作，得到降雨中心的运动轨迹，并根据降雨半径的变化情况，判断是否发生了降雨强度的变化，为洪水标注提供更动态的过程信息；利用地理信息系统GIS，将降雨中心的运动轨迹与重点区域的地图进行叠加，分析降雨中心的运动方向、速度和范围，并计算和评估其对重点防洪区域的影响程度，为洪水标注提供更全面的影响信息。In this embodiment, a rasterized rainfall distribution map is used to more accurately describe the spatial distribution and changes of rainfall, providing a more detailed data basis for flood annotation; by segmenting, identifying and locating rainfall data, the rainfall center, average Key parameters such as rainfall amount and rainfall radius provide more effective feature information for flood annotation; use time series analysis methods to fit, predict and smooth the location information of the rainfall center to obtain the movement trajectory of the rainfall center and calculate Changes in the radius can be used to determine whether changes in rainfall intensity have occurred, providing more dynamic process information for flood labeling; using the geographic information system GIS, the movement trajectory of the rainfall center is superimposed on the map of key areas to analyze the movement direction of the rainfall center. , speed and scope, and calculate and evaluate its impact on key flood control areas to provide more comprehensive impact information for flood labeling.
根据本申请的另一个方面，一种用于城市防洪的智慧预警系统，包括：According to another aspect of this application, a smart early warning system for urban flood control includes:
至少一个处理器；以及at least one processor; and
与至少一个所述处理器通信连接的存储器；其中，a memory communicatively connected to at least one of the processors; wherein,
所述存储器存储有可被所述处理器执行的指令，所述指令用于被所述处理器执行以实现上述任一项技术方案所述的用于城市防洪的智慧预警方法。The memory stores instructions that can be executed by the processor, and the instructions are used by the processor to implement the smart early warning method for urban flood control described in any of the above technical solutions.
以上详细描述了本发明的优选实施方式，但是，本发明并不限于上述实施方式中的具体细节，在本发明的技术构思范围内，可以对本发明的技术方案进行多种等同变换，这些等同变换均属于本发明的保护范围。The preferred embodiments of the present invention have been described in detail above. However, the present invention is not limited to the specific details of the above embodiments. Within the scope of the technical concept of the present invention, various equivalent transformations can be made to the technical solutions of the present invention. These equivalent transformations All belong to the protection scope of the present invention.
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