CN115700634A - Rainfall flood regulation and storage space optimization layout method based on future risks - Google Patents
Rainfall flood regulation and storage space optimization layout method based on future risks Download PDFInfo
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Abstract
The invention discloses a rainfall flood regulation and storage space optimization layout method based on future risks, which comprises the following steps of: s1, identifying a high-flooding area and a potential rainwater gallery of a current research area; s2, primarily optimizing the current rainfall flood storage space by reserving an area with high current storage capacity; s3, predicting the current situation high flooding area and the normally planned future land use distribution in the step S2; s4, calculating the waterlogging risks and the actual flooding capacity of different scenes, and verifying the primary optimization effect; and S5, optimizing layout of the current rainfall flood regulation and storage space based on the future waterlogging risk of the reserved current high-flooding area. The method utilizes the SCS model and the PLUS model, utilizes the PLUS model to predict the future land utilization change distribution by combining the planning requirement and the SCS model to have the advantages of less data demand and dynamically calculating the risk based on the land use condition, and predicts the future land use through the PLUS model under the condition of ensuring that the total amount of the future construction land use reaches the planning requirement.
Description
Technical Field
The invention relates to the field of waterlogging prediction and planning, in particular to a rainfall flood regulation and storage space optimization layout method based on future risks.
Background
Along with the rapid development of urbanization, the scale of cities is continuously enlarged, the original natural storage water bodies, low-lying lands and the like of the cities are buried by the impervious ground due to inappropriate development in the urban construction process, and a natural drainage system formed by flood storage is replaced by a drainage system taking an ergonomic pipe network as a main part and taking a green land as an auxiliary part instead of being cut off by roads and hard ground surfaces. In recent years, china advocates sponge cities, inland inundation risks are relieved to a certain extent through greenbelts with sponge functions, but the layout of greenbelts is mostly in green insertion at intervals under the current situation, natural surface runoff trend is not considered, and the layout is carried out systematically, so that the current greenbelts are poor in energy regulation and storage capacity. In the face of river flood season and extreme rainstorm, the problem of urban waterlogging cannot be solved in sponge cities; furthermore, the construction of the existing urban artificial pipe network mainly adopts quick drainage, and the municipal pipe network is required to discharge rainwater in a short time. When the river is in flood season and extreme rainstorm comes, a large amount of rainwater is discharged into a pipe network, so that drainage facilities such as the pipe network and a pump station are full of load and cannot be discharged outside to play a role. A lot of researches show that urban planning can really relieve urban waterlogging risks, and prediction of future waterlogging risks by predicting the future waterlogging risks in advance is beneficial to relieving the urban waterlogging risks. The future risks are predicted in advance before urban planning, and the current rainfall flood regulation and storage space planning is adjusted according to the future waterlogging risks, so that the future urban waterlogging risks are relieved.
At present, a lot of researches are carried out on optimizing the rainfall flood storage space. On a small scale, simulating a rainfall flood inundation area and a rainfall flood corridor of extreme rainfall by adopting ArcGIS and SCS hydrological models, and simulating and determining the position and the scale of a low-impact development facility according to the total annual runoff quantity target of a sponge city in a research area and in combination with a model; on a large scale, a water system and a water collecting area are extracted just by applying the Strahcrr-Horton law and the ArcGIS technology, the positions of the wetlands are preliminarily determined by comprehensively considering factors such as land utilization and the like, and the scale of the wetlands is determined by the annual runoff total amount of sponge cities and flood control targets of the cities, so that the regulation and storage of rainfall flood in small watersheds are realized; and quantizing the existing rainfall flood regulation target capacity into a touchable rainfall flood regulation space planning scheme by taking the subcollection areas as units and combining the production confluence process.
In the aspect of forecasting waterlogging risks by using a forecasting model, the relation between the current LULC change situation and urban waterlogging and the influence of future land utilization change on urban waterlogging are mainly focused. Scholars predict future risk of waterlogging by coupling a maximum entropy (MAXENT) model with a Future Land Utilization Simulation (FLUS) model. Yankeexin takes the haining city as an example, and a land use prediction model (CLUMondo) is utilized to obtain a 2030-year land use simulation result. Simulating future urban inland inundation by using a hydrodynamic model (InfoWorks ICM); larsson simulated and predicted the spatial distribution of land use in the 2030 Shanghai city using a Terraset CA-Markov model, calculated surface runoff using an SCS model, and predicted and analyzed the effect of future land use changes on surface runoff (larsson, 2018). However, few researches combine the optimized layout of the rainfall flood storage space with the predicted future urban risk, and the current urban waterlogging risk is relieved based on the future waterlogging risk. Therefore, the optimal layout of the rainfall flood storage space is combined with the predicted future urban risk through the SCS model and the PLUS model, and the urban waterlogging risk is relieved based on the future waterlogging risk.
Disclosure of Invention
The invention aims to provide a rainfall flood storage space optimization layout method based on future risks, so as to solve the problems in the background art.
In order to achieve the purpose, the invention provides the following technical scheme: a rainfall flood regulation and storage space optimization layout method based on future risks comprises the following steps:
s1, identifying a high-flooding area and a potential rainwater gallery of a current research area;
s2, reserving an area with high current rainfall flood storage capacity, and primarily optimizing a current rainfall flood storage space;
according to the current situation submerging depth map, an ARCGIS space analysis tool is used for extracting a current situation high submerging area, the area determined as the high submerging area is overlapped with a current situation non-construction land, the rainfall flood storage space with high current situation regulation potential is obtained and serves as a flood storage and detention place, and the current situation rainfall flood storage space is preliminarily optimized by reserving the area with high current situation rainfall flood regulation capacity; converting the format of the limiting factor into 'unknown char' data through a PLUS model, and defining the rainfall flood storage space scenario with high storage potential at the reserved current situation as scenario one and the area rainfall flood storage space with high storage potential at the non-reserved current situation as scenario two;
s3, predicting the future land distribution of the scene one and the scene two in the step S2;
s4, calculating the waterlogging risks and the actual flooding capacity of different scenes, and verifying the primary adjustment effect;
and S5, adjusting the layout of the current rainfall flood regulation and storage space based on the future risk.
Preferably, the rainfall flood storage space optimization layout method based on future risks provided by the application, wherein the specific process of step S1 is as follows:
s1.1 identifying potential rain galleries of a present city new area and determining the width thereof
Extracting the flow and the flow direction of a surface runoff model, generating a depression-free DEM, extracting a river network, extracting the current situation potential rainwater gallery by combining the actual river condition and determining the widths of the potential rainwater galleries at different levels in the research area by utilizing an ArcGIS hydrological analysis tool based on the current situation DEM data;
s1.2 determining rainfall in a study area
Determining rainfall situations of rainstorm intensity according to urban waterlogging prevention and control design standards published by the latest urban building department, and determining rainfall through a rainstorm intensity formula of the city and a Chicago curve formula or local rainfall data;
s1.3 inputting rainfall into SCS model to determine direct runoff quantity Q
The determined rainfall of the high flooding area is calculated by a grid calculator to obtain a direct runoff quantity Q;
s1.4 sub-catchment area division
Dividing the watershed of the research area after extracting the river network based on hydrological analysis to obtain a sub-catchment area map, then calculating the total amount of water in the current situation, counting the total amount of runoff of each sub-catchment area in the ARCGIS through 'partition statistics', using a conversion tool 'Spatial analysis-mathematical analysis-conversion into integer', and then counting the total amount of water of each grid by using a grid calculator;
s1.5 calculating the current land submerging depth by using an isometric method
The inland inundation depth is classified into 3 grades according to the existing research and specifications, the grading mode is as follows,
when the depth of the accumulated water is less than 15cm, the children are difficult to walk, the life of residents is influenced, and the low-submerged area is defined without causing economic loss;
when the depth of the accumulated water exceeds 15cm, the water enters the house to cause property loss and is divided into a middle submerged area;
when the average water accumulation depth is more than 40cm, traffic is paralyzed, the life safety of children is threatened, the water inlet property loss of the lower layer of the building is huge, water accumulation is serious, the safety of children is threatened, and a high flooding area is defined.
Preferably, in the step S13, the SCS model is established based on a water balance equation and two basic assumptions, that is, a proportional equivalence assumption and an initial loss value relationship assumption;
the main equations for the SCS model are as follows:
P＝I a +F+Q
I a ＝λ·S
wherein, P is total rainfall (mm), ia is initial loss (mm) including closure and surface impoundment, F is accumulated infiltration (mm) excluding Ia, Q is direct runoff (mm), S is the maximum possible retention (mm) at that time, and lambda is a regional parameter (lambda is more than or equal to 0.1 and less than or equal to 0.3), and a common value lambda =0.2 is adopted in the module;
when P is more than or equal to 0.2S:
when P < 0.2S:
Q＝0
introducing a parameter CN for calculating the maximum water storage capacity of the soil;
CN is a curve numerical value, a dimensionless parameter, a theoretical value range is [0, 100], CN reflects the runoff yield capability of the underlying surface unit of the drainage basin, the CN value of the underlying surface is determined according to key requirements in the runoff model, and the CN value is determined according to the land utilization class and the soil type of the research area.
Preferably, the rainfall flood storage space optimization layout method based on future risks is provided in the present application, wherein the step S3 specifically includes the following steps:
s3.1 determining the drive factor, contribution analysis
Collecting driving factors of different years according to prediction requirements, preprocessing driving data and land utilization data of different years, extracting an expansion part, and performing contribution analysis of different land utilization types on the expansion part;
s3.2 model simulation and precision evaluation
Under the condition of meeting the requirement of planning construction land, repeatedly debugging field parameters and transformation rules in the PLUS model during model simulation until the precision requirement of the model is met;
s3.3 predicting future land use of different scenes
And under the condition of meeting the planning requirement of the construction land, respectively predicting the future land use by using a PLUS model based on the parameters of the step S3.2 to obtain the future land use distribution in the first scenario and the second scenario.
Preferably, the optimal layout method for the rainfall flood storage space based on the future risk is provided in the present application, wherein the step S4 specifically includes the following steps: calculating the future urban waterlogging risks of the scenario I and the scenario II, dividing the waterlogging risk levels, and verifying the risks of the two scenarios and the land of each scenario by superposition through an ARCGIS space analysis tool to preliminarily adjust the waterlogging reduction effect of the rainfall flood regulation and storage space.
Preferably, the application provides a rainfall flood regulation space optimization overall arrangement method based on future risk, wherein, based on the waterlogging risk of sight one in step S5, to future rainfall flood regulation space overall arrangement, adjust present rainfall flood regulation space planning according to future rainfall flood regulation space overall arrangement, the rainfall flood regulation space that will reserve the present situation regulation potentiality is high is as the addressing region in rainfall flood regulation space, and the whole formation is taken care of with rainfall flood regulation space regulation as the main, and other ecological land use regulation capacity is for the rainfall flood regulation mode of assisting.
Compared with the prior art, the invention has the beneficial effects that:
(1) According to the method, before urban expansion or urban new area construction, an SCS model and a PLUS model are applied, the PLUS model can be used for predicting the advantage of future land utilization change distribution by combining planning requirements and the advantage that the data demand of the SCS model is less and the risk can be dynamically calculated based on land conditions, under the condition that the total amount of future construction land reaches the planning requirements, the future land is predicted through the PLUS model based on the initial terrain and the two-stage land utilization data, the future land risk is calculated through the SCS model, and the problem that the urban inland inundation risk of the future land is predicted in advance before the urban expansion or the urban new area construction is solved.
(2) The method is based on the predicted waterlogging risk of the future land, and is superposed with the type of the future land and the position of a potential rainwater gallery; then, combine the three state of surface runoff "source-process-end", carry out the structure to rainfall flood regulation space and comb, give the different functions in future rainfall flood regulation space, optimize current situation rainfall flood regulation space based on the future rainfall flood regulation spatial layout of optimization.
(3) The method is easy to learn and master, low in cost, small in data demand and beneficial to popularization, and simultaneously provides reference for exploring greenbelt planning and urban waterlogging prevention and control of cities with rainfall flood regulation and storage functions in extreme climates.
Drawings
Fig. 1 is a schematic overall flow chart of the rain flood regulation and storage space optimization provided in the embodiment of the present invention;
FIG. 2 is a technical flow diagram of high flooding zone and potential rain corridor identification provided by an embodiment of the present invention;
FIG. 3 is a 2000 potential rain corridor diagram provided by an embodiment of the present invention;
FIG. 4 is a distribution diagram of the rainfall flood inundation space of the non-construction land in 2000 according to an embodiment of the invention;
FIG. 5 is a diagram of a preliminary optimized current rainfall flood storage space provided by an embodiment of the present invention;
FIG. 6 is a restriction factor graph provided by an embodiment of the present invention;
FIG. 7 is a 2020 year old map of a scenario provided by an embodiment of the present invention;
fig. 8 is a real use map of a scenario of 2020 provided by an embodiment of the present invention;
FIG. 9 is a scenario of prediction provided by an embodiment of the present invention-a risk graph in 2020;
fig. 10 is a two 2020 year risk map of a true planning scenario provided by an embodiment of the present invention;
fig. 11 is a diagram of a current rainfall flood storage space optimization layout according to an embodiment of the present invention;
fig. 12 is a reference diagram of an optimized current rainfall flood storage space provided by an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
The invention provides the following technical scheme: a rainfall flood regulation and storage space optimization layout method based on future risks comprises the following steps:
s1, identifying a high-flooding area and a potential rainwater gallery of a current research area;
s2, reserving an area with high current rainfall flood regulation and storage capacity, and primarily optimizing a current rainfall flood regulation and storage space;
according to the current situation submerging depth map, an ARCGIS space analysis tool is used for extracting a current situation high submerging area, the area determined as the high submerging area is overlapped with a current situation non-construction land, the rainfall flood storage space with high current situation regulation potential is obtained and serves as a flood storage and detention place, and the current situation rainfall flood storage space is preliminarily optimized by reserving the area with high current situation rainfall flood regulation capacity; converting the format of the limiting factor into 'unknown char' data through a PLUS model, and defining the rainfall flood storage space scenario with high reserved current situation storage potential as scenario one and the area rainfall flood storage space without high reserved current situation storage potential as scenario two;
s3, predicting the future land distribution of the scene one and the scene two in the step S2;
s4, calculating the waterlogging risks and the actual flooding capacity of different scenes, and verifying the primary adjustment effect;
and S4, finally, adjusting the layout of the current rainfall flood storage space based on the future risk.
As shown in fig. 1, the rainfall flood storage space optimization layout method based on future risks is applied to the new Hunan-river region of Changshan, hunan, and the area of the research region is about 1200 square kilometers. In order to accurately verify the effectiveness of the method and elaborate the principle and process of the method, land which is not planned to be constructed in the Xinjiang province in 2000 is selected, the current rainfall flood regulation and storage space is optimized by using the method in 2000, and the primary optimization effect is verified by comparing the current waterlogging risk in 2020 with the risk in 2020 after using the method.
According to the research hypothesis, under the condition that the number of construction land used before and after development (the predicted 2020 land) is basically consistent, the 2000-year high-flooding area and the potential rainwater gallery in the Xiangjiang new area are firstly identified, and the 2000-year high-flooding area is reasonably reserved. Secondly, superposing a 2000-year high flooding area and a 2000-year non-construction land in the ARCGIS to obtain a 2000-year high-regulation-storage-capacity flooding area as a storage and stagnation flood place for primarily optimizing a rainfall flood regulation and storage space, namely limiting factors in the PLUS model, on one hand, threats of the high flooding area to human and property under extreme conditions are avoided, on the other hand, the regulation and storage capacity of future land is favorably improved, the limiting factors are input into the PLUS model, 2020 land is predicted, 2020-year land with reserved limiting factors is defined as scenario one, 2020-year current land is defined as scenario two, and the situation is the current land under a real planning state; then, carrying out inundation analysis on the land used for the first scenario and the second scenario 2020, obtaining a preliminarily optimized rainfall flood regulation and storage space map according to a simulation result, comparing the waterlogging risks of the two scenarios, and verifying the waterlogging reduction effect of the preliminarily optimized rainfall flood regulation and storage; and finally, the rainfall flood storage space is reasonably distributed according to the simulation condition, so that reference is provided for planning of the current rainfall flood storage space and planning of a green land system. The experimental procedure is as follows:
s1, identifying a high-flooding area and potential rainwater galleries in a Xiangjiang new district in 2000 years as shown in a specific step in a figure 2:
s1.1 identifying potential rain galleries of a 2000 year urban new district and determining their widths
An ARCGIS hydrological analysis tool is used, flow and flow direction of a surface runoff model are extracted based on DEM data with the precision of 30 meters in the Hunan river New district in 2000, a depression-free DEM is generated, a river network is extracted, potential rainwater galleries are extracted by combining with actual river conditions, and the widths of the potential rainwater ecological galleries at different levels in a research district are determined. And determining the width map 3 of the potential rainwater ecological corridors, the nodes and the connectivity according to the river network grade in principle.
S1.2 determining rainfall of high flooding area
According to the flood prevention standard in Xiangjiang new district, which is specified in the technical guide of sponge city construction in Xiangjiang new district (review article) for 50 years, the rainfall situation is set to be a 24-hour rainfall situation in 50 years, and the design rainfall capacity in 24 hours in 50 years is determined to be 232.54mm through the technical guide of design of low-impact development rainwater control utilization system in Changsha (trial implementation).
S1.3 inputting rainfall into SCS model, determining Q direct runoff
And (3) determining the rainfall of the high flooding area determined in the step (S1.2), and completing the calculation of an SCS model by a grid calculator to obtain a direct runoff quantity Q, wherein the principle of the SCS model is as follows, the direct runoff quantity Q meeting 24 hours in 50 years is determined, and the principle of the SCS model is as follows:
the SCS model is built based on the water balance equation and two basic assumptions, namely the proportional equality assumption and the initial loss value (the maximum potential hold-up at that time) relationship assumption.
The main equations for the SCS model are as follows:
P＝I a +F+Q
I a ＝λ·S
wherein, P is total rainfall (mm), ia is initial loss (mm) including closure, surface impoundment and the like, F is accumulated infiltration (mm) excluding Ia, Q is direct runoff (mm), S is the maximum possible retention (mm) at that time, and lambda is a regional parameter (lambda is more than or equal to 0.1 and less than or equal to 0.3), and a common value lambda =0.2 is adopted in the module.
When P is more than or equal to 0.2S:
when P < 0.2S:
Q＝0
for calculating S, a parameter CN maximum water holding capacity of soil is introduced.
CN is a curve numerical value, a dimensionless parameter, a theoretical value range is [0, 100], and CN reflects the flow producing capability of the basin underlying surface unit. The key requirement in the runoff model is to determine the CN value of the underlying surface, and the CN value is determined according to the land type and the soil type of the research area.
S1.3 sub-catchment area division
After extracting river network based on hydrological analysis, dividing the watershed of the research area, and the like to obtain a sub-catchment area map; and then, calculating the total amount of accumulated water in the Xin district of Hunan river in 2000 years, and counting the total amount of runoff of each sub-catchment area in the ARCGIS through 'partition counting', wherein the used data is the data of the well-made sub-catchment areas. The conversion tool 'Spatial analysis-mathematical analysis-conversion into integer' is used, and then a grid calculator is used for counting the accumulated water amount of each grid.
S1.4 calculating the land inundation depth of 2000 years by using an isometric method
Dividing the inland inundation depth into 3 grades according to the existing research and specifications, wherein the specific division rule is as follows:
when the depth of the accumulated water is less than 15cm, the children are difficult to walk, the traffic is not affected basically, and the children have certain influence on the life of residents, but the children are divided into a low-submerging area (low-risk area) without causing economic loss; when the depth of the accumulated water exceeds 15cm, water enters the house to cause certain property loss; the average height of the exhaust ports of the urban automobiles is about 15, so that the automobiles are partially blocked by fire in law, and the residential property loss is also enlarged to be defined as a middle submerged area (middle danger area); when the average water accumulation depth is more than 40cm, traffic is paralyzed, the life safety of children is threatened, the loss of water inlet property at the lower layer of the building is huge, water accumulation is serious, the safety of children is threatened, and a high-submerging area (high-risk area) is defined, wherein the area which is more than 40cm and generates danger to people is defined as the high-submerging area.
And (4) rapidly approaching the current terrain by using an isometric method to obtain a submerging depth map of the research area in 2000. The equal-volume method realizes the idea that the accumulated water flows from high to low under the action of gravity, so that the distribution condition of the stormwater waterlogging water can be simulated by using the principle that the total accumulated water volume (obtained by calculating the runoff generating simulation part) in a certain time step is equal to the total accumulated water volume in the water submerging range in the time step according to the topographic distribution condition of a research area, and the calculation formula of the equal-volume method is as follows:
W＝∫∫[E w (x，y)-E g (x，y)]dσ
in the formula: w total water volume within the water accumulation submergence range; e w (x, y) surface elevation of the standing water; e g (x, y) surface elevation of the standing water; d sigma water accumulation area infinitesimal.
S2, primarily optimizing the current rainfall flood regulation and storage space:
before urban development, according to the 2000-year flooding depth map obtained in the step S1.4, an ARCGIS space analysis tool is used, a high flooding area with the flooding depth larger than 0.4m is superposed with a non-construction land to obtain a 2000-year rainfall flood regulation and storage capacity area, the 2000-year rainfall flood regulation and storage capacity area is reserved to serve as a storage and flood stagnation place, a preliminary optimization current-situation rainfall flood regulation and storage space map 5 is obtained, the area cannot be used for construction and development, and the function of the area is the flood storage function when extreme rainfall comes. The data are combined with basic farmland red lines and water areas to serve as limiting factors in a PLUS model, and are reclassified to be '0' through ARCGIS, are forbidden zones and are '1' in other areas, so that a graph 6 is obtained. The format of the limiting factor is converted into 'unknown char' data through a PLUS model, and before the experiment begins, the rainfall flood storage space with high storage potential under the reserved current situation is defined as a scene one, and the rainfall flood storage space without the reserved high flooding area is defined as a scene two.
S3 forecast scenario-2020 land use:
the situation of the 2020-year land is predicted through the PLUS model, the situation of the 2020-year land under the real planning situation is not predicted, and the situation of the 2020-year land is obtained by performing multiple simulation in stages for improving the model precision. The specific process is as follows:
s3.1 determining the drive factor, contribution analysis
According to the prediction needs, collecting driving factors of different years as shown in the table 1, preprocessing the data, extracting an expansion part, and performing characteristic contribution analysis of different land utilization types on the expansion part.
TABLE 1 Driving factor data for different years
| Factor type | Data of |
| Natural environment(s) | Elevation, slope, distance to major river (2000, 2020) |
| Social economy | GDP, population Density (2000, 2020) |
| Central radiation | Distance to government agencies, distance to central urban areas (2000, 2020) |
| Spill-over effect | Population, GDP, major roads, railways, high speed (2000, 2020) |
| Limiting factor | Permanent basic farmland, ecological protection red line data, river (2000, 2020) |
| Land utilization | 2000. 2020 land use data and image |
S3.2 model simulation and precision evaluation
In a PLUS model, land utilization data and driving factors in New Hunan river district 2000 and 2010 are used for predicting land utilization in 2010; then, model precision, field parameters and conversion rules from 2000 to 2010 are repeatedly debugged by calculating Kappa and FOM values until the model precision is reached; model parameters of Kappa 0.732287, overall accuracy 0.821425, foM =,0.224514, from 2000 to 2010 were obtained. Performing model simulation on the land used in 2010-2020 in the same step, and performing precision evaluation; finally, parameters of a Kappa index of 0.8287, an overall accuracy of 0.890536 and FoM =0.329438 in 2010-2020 are calculated according to formulas, and the parameters of the two stages show that the simulation result has high consistency with the real land.
S3.3 prediction scene land used for 2020
Based on the parameters of the step S3.2, as the research assumes that the first scenario meets the requirement of the construction land under the real planning scenario of 2020, the grid calculator is used to calculate the second scenario of the map 8 for 2020, so that the requirement of the construction land under the real planning scenario of 2020 is 290771 pixels; under the condition that the requirements of the construction land for the two scenes are consistent, the map 7 for the scene in 2020 is predicted, and the grid calculator can know that the scene-construction land is 290771 pixels, so that the research hypothesis requirement is met.
S4, calculating the waterlogging risk and the actual flooding capacity of different scenes, and verifying the primary optimization effect
Calculating the risk of waterlogging for the scenario year-first 2020 land and the scenario year-second 2020 land according to steps S1.2 to S1.4 in step S1 respectively leads to fig. 9 and 10 respectively. Overlapping the risks of the two scenes with the land use of the respective scenes through an ARCGIS space analysis tool, preliminarily verifying and optimizing the waterlogging reduction effect of the current rainfall flood regulation and storage space, and knowing that the waterlogging risk of the construction land is reduced in scene one 728.2649777 hectares; then, the actual storage capacity of the two scenes of the rainflood inundation patches is respectively calculated through the ARCGIS, and the capacity of the catchment area is increased by 657 ten thousand meters in the first scene 3 . According to the results, the area with high rainfall flood storage capacity in 2000 years is reserved, and the method is favorable for preventing and controlling waterlogging risks in extreme scenes.
S5, optimizing current situation of rainfall flood storage space planning based on situation one in 2020 in risk area
On the basis of S2 preliminary optimization current situation rainfall flood regulation and storage space, other waterlogging risks are further alleviated. The rainfall flood regulation and storage mode which is mainly formed by regulating and storing rainfall flood space and assisted by regulating and storing capacity of other ecological land is shown in figure 11, and the specific optimization method is as follows:
firstly, erasing the risk area in the step S2 from the risk area in a scene of 2020 by using an ARCGIS spatial analysis tool; and then, superposing the scene-risk area and the 2000-year ecological land to obtain a site selection area of the current-state 2000-year rainfall flood regulation and storage space, wherein the site selection area is suitable for the arrangement of the future rainfall flood regulation and storage space, and the optimal layout of a rainfall flood regulation and storage facility or a green land with the rainfall flood regulation and storage function can be carried out according to the submerging depth and the area of rainfall flood patches and the three states of 'source-process-tail end' of surface runoff.
Secondly, the residual risk area is overlapped with the future construction land, the partial area should preferentially avoid the area when the future construction land is selected, the waterlogging risk of the area is focused, the waterlogging risk of the area is reduced through the sponge city as much as possible, and the activities of people in the area are reduced.
Finally, the potential rainwater gallery is superposed with the 2020 situational one land, a natural drainage channel is reserved, and if the current situation potential rainwater gallery is located on the construction land, green land arrangement in the construction land is preferentially considered; and then, optimizing the current rainfall flood storage space based on the future rainfall flood storage space optimized based on the future risk, obtaining the reference map of the optimized current rainfall flood storage space as figure 12 by the method, further adjusting the rainfall flood storage space according to the actual condition or planning requirement in the actual planning process, and verifying the waterlogging reduction effect by the method for the adjusted land.
In conclusion, before city expansion or city new area construction, the invention applies the SCS model and the PLUS model, the PLUS model can be used for predicting the advantage of future land utilization change distribution and the advantage of less data demand of the SCS model and dynamically calculating risk based on land conditions by combining planning requirements, under the condition of ensuring that the total amount of land for future construction reaches the planning requirements, the future land is predicted through the PLUS model based on initial terrain and two-stage land utilization data, the SCS model calculates the future land risk, and the problem that the urban inland water logging risk of the future land is predicted in advance before the city expansion or the city new area construction is solved; the method is based on the predicted waterlogging risk of the future land, and is superposed with the type of the future land and the position of a potential rainwater gallery; then, combining three states of surface runoff source-process-tail end, performing structural combing on the rainfall flood regulation and storage space, endowing the rainfall flood regulation and storage space with different functions in the future, and optimizing the current rainfall flood regulation and storage space based on the optimized future rainfall flood regulation and storage space layout; the method is easy to learn and master, low in cost, small in data demand and beneficial to popularization, and provides a reference function for exploring greenbelt planning and urban waterlogging prevention and control with a rainfall flood regulation and storage function in an urban in extreme climate.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (6)
1. A rainfall flood regulation and storage space optimization layout method based on future risks is characterized by comprising the following steps:
s1, identifying a high-flooding area and a potential rainwater gallery of a current research area;
s2, reserving an area with high current rainfall flood storage capacity, and primarily optimizing a current rainfall flood storage space;
according to the current situation submerging depth map, an ARCGIS space analysis tool is used for extracting a current situation high submerging area, the area determined as the high submerging area is overlapped with a current situation non-construction land, the rainfall flood storage space with high current situation regulation potential is obtained and serves as a flood storage and detention place, and the current situation rainfall flood storage space is preliminarily optimized by reserving the area with high current situation rainfall flood regulation capacity; converting the format of the limiting factor into 'unknown char' data through a PLUS model, and defining the rainfall flood storage space scenario with high reserved current situation storage potential as scenario one and the area rainfall flood storage space without high reserved current situation storage potential as scenario two;
s3, predicting the future land distribution of the scene one and the scene two in the step S2;
s4, calculating the waterlogging risks and the actual flooding capacity of different scenes, and verifying the primary adjustment effect;
and S5, adjusting the layout of the current rainfall flood regulation and storage space based on the future risk.
2. The method for optimizing layout of rainfall flood storage space based on future risks according to claim 1, wherein the specific process of step S1 is as follows:
s1.1 identifying potential rain galleries of a present city new area and determining the width thereof
Based on the current situation DEM data, extracting the flow and the flow direction of the surface runoff model by utilizing an ArcGIS hydrological analysis tool, generating a depression-free DEM, extracting a river network, extracting current situation potential rainwater galleries by combining with the actual river condition, and determining the widths of the potential rainwater galleries at different levels in the research area;
s1.2 determining rainfall in a study area
Determining rainfall situations of rainstorm intensity according to urban waterlogging prevention and control design standards published by the latest urban building department, and determining rainfall through a rainstorm intensity formula of the city and a Chicago curve formula or local rainfall data;
s1.3 inputting rainfall into SCS model to determine direct runoff quantity Q
The determined rainfall capacity of the high inundated area is calculated by a grid calculator to obtain direct runoff Q;
s1.4 sub-catchment area division
Dividing the watershed of the research area after extracting the river network based on hydrological analysis to obtain a sub-catchment area map, then calculating the total amount of the ponding in the current situation, counting the total amount of the runoff of each sub-catchment area in the ARCGIS through 'partition statistics', using a conversion tool 'spatialanalysis-mathematical analysis-conversion into integer', and counting the total amount of the ponding of each grid by using a grid calculator;
s1.5 calculating the current land inundation depth by using an isovolumetric method
The depth of inland inundation is classified into 3 grades according to the existing research and specifications, and the grading mode is as follows,
when the depth of the accumulated water is less than 15cm, the children are difficult to walk, the lives of residents are influenced, and the children are divided into low-submerging areas without economic loss;
when the depth of the accumulated water exceeds 15cm, the water enters the house to cause property loss and is divided into a middle submerged area;
when the average water accumulation depth is more than 40cm, traffic paralysis and life safety of children are threatened, the water inflow property loss of the lower layer of the building is huge, water accumulation is serious, the safety of children is threatened, and a high-submerged area is defined.
3. The rainfall flood storage space optimization layout method based on the future risk according to claim 2, wherein: in step S13, the SCS model is established based on the water balance equation and two basic assumptions, i.e., the proportional equivalence assumption and the initial loss value relationship assumption;
the main equations of the SCS model are as follows:
P＝l a +F+Q
I a ＝λ·S
wherein, P is total rainfall (mm), ia is initial loss (mm) and comprises interception and surface layer water storage, F is accumulated seepage (mm) without Ia, Q is direct runoff (mm), S is the maximum possible retention (mm) at that time, and lambda is a regional parameter (lambda is more than or equal to 0.1 and less than or equal to 0.3), and a common value lambda =0.2 is adopted in the module;
when P is more than or equal to 0.2S:
when P < 0.2S:
Q＝0
introducing a parameter CN for calculating the maximum water storage capacity of the soil;
CN is a curve numerical value, a dimensionless parameter, a theoretical value range is [0, 100], CN reflects the runoff yield capability of the underlying surface unit of the drainage basin, the CN value of the underlying surface is determined according to key requirements in the runoff model, and the CN value is determined according to the land utilization class and the soil type of the research area.
4. The optimal layout method for rainfall flood storage space based on future risks according to claim 2, wherein the specific method in step S3 is as follows:
s3.1 determining the drive factor, contribution analysis
Collecting driving factors of different years according to the prediction requirement, preprocessing the driving data and the land utilization data of different years, extracting an expansion part, and performing contribution analysis of different land utilization types on the expansion part;
s3.2 model simulation and precision evaluation
Under the condition of meeting the planning requirement of the construction land, repeatedly debugging the field parameters and the transformation rules in the PLUS model during model simulation until the model precision requirement is met;
s3.3 predicting future land use of different scenes
And under the condition of meeting the planning requirement of the construction land, respectively predicting the future land use by using a PLUS model based on the parameters of the step S3.2 to obtain the future land use distribution in the first scenario and the second scenario.
5. The method according to claim 2, wherein the step S4 specifically includes the following steps: calculating the future urban waterlogging risks of the scenario I and the scenario II, dividing the waterlogging risk levels, and verifying the risks of the two scenarios and the land of each scenario by superposition through an ARCGIS space analysis tool to preliminarily adjust the waterlogging reduction effect of the rainfall flood regulation and storage space.
6. The rainfall flood regulation and storage space optimization layout method based on the future risks according to claim 2, wherein in the step S5, based on the waterlogging risk of the first scenario, for the future rainfall flood regulation and storage space layout, the current rainfall flood regulation and storage space planning is adjusted according to the future rainfall flood regulation and storage space layout, and the rainfall flood regulation and storage space with high reserved current regulation and storage potential is used as a site selection area of the rainfall flood regulation and storage space, so that a rainfall flood regulation and storage mode which mainly regulates the rainfall flood regulation and storage space and assists in regulating and storing capacity of other ecological land is integrally formed.
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| CN115860288A (en) * | 2023-03-02 | 2023-03-28 | 江西师范大学 | Wind energy potential area prediction method and prediction system |
| CN116384279A (en) * | 2023-04-07 | 2023-07-04 | 中南林业科技大学 | Flood evolution process simulation method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115860288A (en) * | 2023-03-02 | 2023-03-28 | 江西师范大学 | Wind energy potential area prediction method and prediction system |
| CN116384279A (en) * | 2023-04-07 | 2023-07-04 | 中南林业科技大学 | Flood evolution process simulation method |
| CN116384279B (en) * | 2023-04-07 | 2023-10-17 | 中南林业科技大学 | Flood evolution process simulation method |
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