Water conservancy project waterlogging removal effect evaluation method based on full life cycle

Abstract

The invention discloses a water conservancy project waterlogging removal effect evaluation method based on a full life cycle. The method comprises the following steps: S1, simulating the submerging condition of a research area where a water conservancy project encounters rainstorm in each recurrence period through hydrodynamic simulation software; s2, calculating economic and life loss of the research area caused by rainstorm in each recurrence period before and after the construction of the water conservancy project; s3, calculating the waterlogging removal effect of the water conservancy project in the datum year through a frequency method in combination with economic loss and life loss; and S4, calculating the waterlogging removal effect of the hydraulic engineering in each year in the full life cycle of the hydraulic engineering by utilizing the waterlogging removal effect of the hydraulic engineering in the reference year and combining the economic and population change coefficients of the research area. According to the method, the traditional calculation of the waterlogging removal effect of the reference year is amplified to the waterlogging removal effect of the full life cycle of the water conservancy project through calculation, so that the waterlogging removal effect generated by the project is more intuitively displayed, and a decision maker can more accurately measure the waterlogging removal effect generated by the project; the method is of guiding significance for decision makers' project scale and project construction effect evaluation.

Description

Technical Field

[0001] The present invention belongs to the technical field of evaluation of the impact of water projects on rainstorms, and specifically relates to a method for evaluating the waterlogging removal effect of a water project over its entire life cycle. Background Art

[0002] The main task of river water conservancy projects is to reduce flood disasters and protect the lives and property of the country and the people. At the same time, water conservancy projects also include a part of the drainage function. When encountering heavy rains, timely diverting rainwater into the river to minimize the accumulation of water on land, which can reduce the damage of heavy rains to the lives and property of the people. The essence of the drainage effect is the difference between the economic and life losses caused by heavy rains before and after the implementation of river management projects, and is measured by the reduced economic and life losses.

[0003] At present, the mainstream evaluation method for water conservancy project drainage effect usually selects a certain year after the project construction as the base year, and uses the economic data, population information and rainstorm conditions of that year to calculate the drainage effect of the project. However, this evaluation method is limited to the situation in the base year and fails to fully reflect the comprehensive drainage effect of the water conservancy project throughout its life cycle. In fact, the operation of water conservancy projects runs through the entire life cycle, and the drainage benefits at each stage may fluctuate significantly with changes in time, environment and socio-economic conditions. Therefore, the evaluation method based solely on the base year has limitations and cannot fully and dynamically reflect the long-term benefits of the project. Summary of the invention

[0004] The purpose of the present invention is to provide a method for risk assessment of waterlogging removal effect over the entire life cycle of a water conservancy project, so as to solve the technical problem that in the prior art, a certain year after the construction of the water conservancy project is used as a base year, and the economic data, population information and rainstorm conditions of that year are used to evaluate the waterlogging removal effect of the project, which fails to fully reflect the comprehensive waterlogging removal effect of the water conservancy project over its entire life cycle.

[0005] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0006] A method for evaluating the waterlogging removal effect of a water conservancy project based on the entire life cycle includes the following steps:

[0007] Step S1: Using hydrodynamic simulation software to simulate the flooding situation of the study area where the water conservancy project is located when encountering heavy rains of various return periods;

[0008] Step S2: Calculate the economic and life losses caused by heavy rains of each return period before and after the construction of water conservancy projects in the study area;

[0009] Step S3: Calculate the waterlogging removal effect of the water conservancy project in the base year by combining economic losses and life losses through the frequency method;

[0010] Step S4: Utilize the waterlogging removal effect of the water conservancy project in the base year and combine it with the economic and population change coefficients of the study area to calculate the waterlogging removal effect of each year in the entire life cycle of the water conservancy project.

[0011] Further optimization, the step S1 specifically includes the following steps:

[0012] Step S1.1: Extract the boundary data of the study area from the BIGMAP software, obtain the elevation of the study area from the geospatial data cloud, and grid the simulation area using the hydrodynamic simulation software;

[0013] Step S1.2: In the hydrodynamic simulation software, rainfall with different return periods is added to the study area. The rainstorm levels and frequencies with different return periods are shown in Table 1;

[0014] Table 1 Rainstorm levels and occurrence frequency according to return period

[0015]

[0016] Step S1.3: Set the corresponding outlet flow at the outlet of the river grid in the study area, and set gates at different locations of the river according to the design requirements of the water conservancy project to simulate the maximum flooding depth and maximum flow rate of each grid in the study area before and after the project under heavy rains with different recurrence periods, and obtain the flood inundation simulation results of the study area under different rainfall levels.

[0017] Further optimization, in step S2, the economic and life losses caused by heavy rains in each return period before and after the construction of the water conservancy project in the study area are calculated, specifically including:

[0018] Step S2.1: Calculate the losses caused by different levels of rainstorms before the construction of water conservancy projects, including economic losses and loss of life, specifically:

[0019] Step S2.1.1: Level R j Economic losses caused by heavy rains 前j , including direct economic losses L 前j and indirect economic losses 前j , that is, N 前j =L 前j +M 前j ;

[0020] The direct economic loss is calculated using the following formula (1):

[0021]

[0022] In the above formula: L 前j For the construction of water conservancy projects, the previous level is R j The direct economic losses caused by heavy rain in the study area;前ji Before the construction of the water conservancy project, the i-th grid unit is at level R j The economic loss rate in the rainstorm; 前ji is the economic value of the i-th grid unit before the construction of the water conservancy project, n means that the study area is divided into n grid units, and j = 1, 2, 3, 4, 5.

[0023] Indirect economic losses are calculated using the following formula (2):

[0024] M 前j =L 前j ·a (2)

[0025] In the above formula, M 前j For the construction of water conservancy projects, the previous level is R j The indirect economic losses caused by heavy rain in the study area; a is the conversion factor, which is 16%.

[0026] Step S2.1.2: Calculate the loss of life in the study area caused by different levels of rainstorms before the construction of the water conservancy project using the following formula (3):

[0027]

[0028] In the above formula: LOL 前j For the construction of water conservancy projects, the previous level is R j Heavy rains caused loss of life in the study area; LOL jmin and LOL jmax Before the construction of water conservancy projects, the level was R j The lower and upper bounds of the life loss interval in a rainstorm; PAR 前ji Indicates that before the construction of water conservancy projects, the level is R j The number of people at risk within the flood inundation range of the i-th grid cell in the study area during a heavy rain, f 前ji Indicates that before the construction of water conservancy projects, the level is R j is the life loss mortality rate interval of the ith grid cell in the study area caused by the main factors in the rainstorm; c is the correction coefficient caused by the secondary influencing factors.

[0029] Step S2.2: Calculate the losses caused by different levels of rainstorms after the construction of water conservancy projects

[0030] The same method as in step S2.1.1 is used to calculate the level R after the construction of the water conservancy project. j The direct economic losses caused by heavy rain in the study area 后j and indirect economic losses 后j , the level after the construction of water conservancy project is R j The economic losses caused by heavy rain in the study area are N 后j=L 后j +M 后j .

[0031] Similarly, the same method as in step S2.1.2 is used to calculate the level R after the construction of the water conservancy project. j Heavy rains caused LOL in the study area 后j .

[0032] Further optimization, in step S2.1, the economic loss rate of different grid units is determined according to the disaster-prone body type corresponding to the grid unit in the study area. Different disaster-prone body types correspond to different loss rate curves. By substituting the selected time year into the corresponding loss rate curve, the economic loss rate of the corresponding grid unit and that year can be obtained.

[0033] By consulting the existing literature, the loss rate curve of the study area was obtained.

[0034] Further optimization, in step S2.1.1, the economic value of the grid unit is obtained by the following method, specifically:

[0035] First, the geographical location, industry classification, disaster-prone body type, and flooded water depth information are added to each grid cell to form a spatial information grid.

[0036] Secondly, based on the statistical yearbook data of the city where the study area is located, the economic data is spatialized on the basis of considering the degree of social and economic contribution of the study area, thereby completing the spatial distribution of economic data; after the economic data is spatialized, each grid unit has multiple information such as "economic value", "water depth", "type of disaster-prone body" and "industry type", thus determining the economic value of each grid.

[0037] Further optimization, in step S2.1.2, the population density distribution map of the city in the study area in that year is superimposed with the rainstorm inundation simulation result map of each return period before the construction of the water conservancy project through GIS software, and the inundation area and population density of each grid unit in the inundation area are counted to determine the level R before the construction of the water conservancy project. j The number of people at risk within the flood inundation range of the i-th grid cell in the study area during a heavy rain PAR 前ji .

[0038] Similarly, according to the above method, after the construction of water conservancy projects, the level is R j The number of people at risk within the flood inundation range of the i-th grid cell in the study area during a heavy rain PAR 后ji .

[0039] Further optimization, in step S2.1.2, the mortality rate affecting the loss of life mainly depends on the severity of the flood caused by the heavy rain before and after the project construction, and the severity of the flood is determined by the maximum flood depth and the maximum flood flow rate, as shown in formula (4);

[0040] S Fji =D ji ×V ji (4)

[0041] In the above formula: S Fji Indicates that the level is R j The flood severity of the i-th grid cell in the study area during the heavy rain, D ji Indicates that the level is R j The maximum flooding depth of the ith grid cell in the study area during a heavy rain, m; V ji Indicates that the level is R j The maximum flood velocity of the ith grid cell in the study area during the rainstorm, m / s;

[0042] At level R j The life loss mortality rate of the i-th grid cell in the study area during a heavy rain is shown in formula (5);

[0043] f ji =f(S Fji,VB ) (5)

[0044] In the above formula: VB is the building vulnerability; f ji Indicates that the level is R j The mortality rate interval of life loss in the i-th grid cell of the study area caused by the main factors in the rainstorm is composed of f1 and f2. f1 is the risk population exposure rate interval affected by the warning time and the degree of understanding of dam failure, and f2 is the exposed population mortality rate interval affected by the severity of floods and the vulnerability of buildings.

[0045] The correction coefficient c caused by secondary influencing factors is calculated using the following formula (6):

[0046] c= c1×c2×c3 (6)

[0047] In the above formula: c1, c2 and c3 are the correction coefficients caused by the time of rainstorm, rescue capacity and age distribution respectively; the ranges of c1, c2 and c3 are shown in formula (7);

[0048] {c1,c2,c3}∈{[0.80,1.20],[0.80,1.00],[1.00,1.20]} (7).

[0049] Further optimization, in step S3, calculating the waterlogging removal effect of the water conservancy project in the base year specifically includes:

[0050] Step S3.1: Economic drainage effect of water conservancy projects in the base year

[0051] Step S3.1.1: Calculate the level before and after the construction of the water conservancy project, R j The difference in economic losses in the study area caused by heavy rains is S j , as shown in formula (8);

[0052] S j =N 前j -N 后j (8)

[0053] Step S3.1.2: Calculate the economic drainage effect of the water conservancy project in the base year using the frequency method. The specific calculation process is shown in formula (9);

[0054]

[0055] In the above formula: S0 represents the economic drainage value of the water conservancy project in the study area in the base year, P j R j The frequency of heavy rain.

[0056] Step S3.2: Life drainage effect of water conservancy projects in the base year

[0057] Step S3.2.1: Calculate the level before and after the construction of the water conservancy project, R j The difference in life loss caused by heavy rain in the study area is T j , as shown in formula (10);

[0058] T j =LOL 前j -LOL 后j (10)

[0059] Step S3.2.2: Calculate the waterlogging removal effect of the water conservancy project in the base year using the frequency method, as shown in formula (11);

[0060]

[0061] In the above formula, T0 is the life drainage value of the water conservancy project in the study area in the base year, P j R j The frequency of heavy rain.

[0062] Further optimization, in step S4, the economic drainage effect in the base year is compared with the predicted economic change coefficient α k Combined with the above, the economic drainage effect in any year in the whole life cycle is obtained, as shown in formula (12);

[0063] Uk =S0·[(1+α1)·(1+α2), ...., (1+α k )] (12)

[0064] In the above formula: U k is the economic drainage value of the kth year relative to the base year in the life cycle of the water conservancy project; α k It is the coefficient of change of the economic data of the study area where the water conservancy project is located in the kth year relative to the k-1th year.

[0065] The life effect of the base year and the life change coefficient β i Combined, the life dewatering effect in any year of the whole life cycle is obtained, as shown in formula (13);

[0066] V k =T0·[(1+β1)·(1+β2), ...., (1+β k )] (13)

[0067] In the above formula: V k is the life drainage effect of the kth year relative to the base year in the life cycle of the water conservancy project; T0 is the life drainage loss in the base year of the water conservancy project; β k It is the coefficient of change of the population data in the study area where the water conservancy project is located in the kth year relative to the k-1th year, k = 0, 1, 2, 3, 4..., k = 0 for the base year, and k = 1 for the first year after the base year.

[0068] Further optimization is carried out by using the AMIRA model to predict the economic data of the study area in each year during the life cycle of the water conservancy project, and comparing the economic data of each year with the economic data of the previous year to obtain the economic data change coefficient α of the study area k According to the population forecast data of the urban area where the study area is located, the population data of each year is compared with the population data of the previous year to obtain the change coefficient β of the population in the study area k .

[0069] Compared with the prior art, the present invention has the following beneficial effects:

[0070] 1. The waterlogging removal effect of the traditional calculation base year is amplified to the waterlogging removal effect of the entire life cycle of the water conservancy project through calculation, which more intuitively shows the waterlogging removal effect produced by the project, enabling decision makers to more accurately measure the waterlogging removal effect produced by such projects, which has guiding significance for decision makers to scale projects and evaluate the construction effects of projects.

[0071] 2. The statistical yearbook of the research area and related economic data are used to predict the changes in economic and population data during the life of the project, so as to derive the coefficient of change of the drainage effect every year during the life of the project, and thus calculate the drainage effect of the water conservancy project throughout its life cycle. This is expected to provide a reference for the evaluation of flood control effects of other river management projects. DETAILED DESCRIPTION

[0072] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the examples of the present invention are clearly and completely described below. Obviously, the described examples are only examples of a part of the present invention, rather than all examples.

[0073] A method for evaluating the waterlogging removal effect of a water conservancy project based on the entire life cycle includes the following steps:

[0074] Step S1: Using hydrodynamic simulation software to simulate the flooding situation of the study area where the water conservancy project is located when encountering heavy rains of various return periods; specifically, the steps include:

[0075] Step S1.1: Extract the boundary data of the study area from the BIGMAP software, obtain the elevation of the study area from the geospatial data cloud, and grid the simulation area using the hydrodynamic simulation software.

[0076] In this example, the Qingshui River and Luxin Canal basins in Henan Province were selected as the research area.

[0077] The MIKE21 two-dimensional hydrodynamic model was used to simulate floods of different frequencies. Before the numerical simulation, the calculation boundary and the boundary data of the river bank were extracted from the BIGMAP software. The 30m precision DEM elevation was obtained from the geospatial data cloud, and the elevation scatter points in the study area were extracted from the DEM elevation. The study area was divided into regular triangular grids. Considering the simulation accuracy and operation stability, the maximum grid in the river was 200m. 2 , the maximum outside the river is 30000m 2 , the minimum angle is 30°.

[0078] Step S1.2: In the hydrodynamic simulation software, add rainfall with different return periods to the study area, and select rainfall return periods of three years, five years, ten years, twenty years, and fifty years, as shown in Table 1.

[0079] Table 1 Rainstorm levels and occurrence frequency according to return period

[0080]

[0081] Step S1.3: Set the corresponding outlet flow at the outlet of the river grid in the study area, and set gates at different locations of the river according to the design requirements of the water conservancy project to simulate the maximum flooding depth and maximum flow rate of each grid in the study area before and after the project under heavy rains with different recurrence periods, and obtain the flood inundation simulation results of the study area under different rainfall levels.

[0082] In this embodiment, the roughness of the main channel of the river is 0.025, and the roughness of the beach is 0.035. In the simulation results of the 20-year flood of Qingshui River and Luxin Canal, the maximum flood depth of most inundated areas is 1-3m and the maximum flow rate is 0-1.5m / s 2 The total area of ​​the flooded area is 1108.363km 2 .

[0083] Step S2: Calculate the economic and life losses caused by heavy rains in each return period before and after the construction of water conservancy projects in the study area. According to existing research and combined with the characteristics of the project, the economic losses are calculated based on the loss rate curve and economic data spatialization method, and the life losses are calculated based on the interval theory. Specifically include:

[0084] Step S2.1: Calculate the losses caused by different levels of rainstorms before the construction of water conservancy projects, including economic losses and loss of life, specifically:

[0085] Step S2.1.1: Level R j Economic losses caused by heavy rains 前j , including direct economic losses L 前j and indirect economic losses 前j , that is, N 前j =L 前j +M 前j ;

[0086] The direct economic loss is calculated using the following formula (1):

[0087]

[0088] In the above formula: L 前j For the construction of water conservancy projects, the previous level is R j The direct economic losses caused by heavy rain in the study area; 前ji Before the construction of the water conservancy project, the i-th grid unit is at level R j The economic loss rate in the rainstorm; 前ji is the economic value of the i-th grid unit before the construction of the water conservancy project, n means that the study area is divided into n grid units, and j = 1, 2, 3, 4, 5.

[0089] The economic distribution within the flood inundation area is calculated using the economic density method. Using GIS software, the 2020 Henan Province economic density distribution map is overlaid with the flood inundation simulation result maps of various frequencies, and the inundated area and economic density of each grid unit in the inundation area are counted to determine the economic loss data within the flood inundation area.

[0090] The economic loss rate of different grid units is determined according to the type of disaster-prone body corresponding to the grid unit in the study area. Different types of disaster-prone bodies correspond to different loss rate curves. By substituting the selected time year into the corresponding loss rate curve, the economic loss rate of the corresponding grid unit and that year can be obtained.

[0091] In this embodiment, the loss rate curve of the study area is obtained by consulting the following existing literature. The area studied in this literature is geographically similar to the area studied in this implementation, so it can be directly cited. Reference: Zhan Wenkai. Research on economic loss assessment in northern Henan under flood disasters [D]. [Master's thesis]. Zhengzhou University, 2021.

[0092] The economic loss rate is mainly determined according to different types of disaster-prone bodies. In this embodiment, the classification of disaster-prone bodies adopts the land use classification method. The Land Use Status Classification (GB / T 21010-2017) divides the current land use types in my country into 12 primary land uses and 73 secondary land uses. For the area to be studied this time, the main disaster-prone bodies involve 5 primary land uses and 16 secondary land uses. Taking into account that many public management buildings are adjacent to urban commercial buildings in reality, in order to appropriately simplify the workload, the present invention regards commercial facilities and public management facilities as a type of disaster-prone body and adopts a unified loss rate function. Different loss rate curves are selected for different disaster-prone bodies, as shown in Table 2. In Table 2, h is the depth of water flooding caused by rainfall.

[0093] Table 2 Summary of loss rate curves

[0094] Disaster-prone body type Loss rate curve body Residential property 5.528sin(1.055h-0.786)+4.582sin(1.17h+2.116) Rural area before 1990 <h2 style=";text-align:left;direction:ltr"><![CDATA[-0.1714h <h2 style=";text-align:left;direction:ltr"> 2 <h2 style=";text-align:left;direction:ltr"> +0.9961h-0.3783]]><h2 style=";text-align:left;direction:ltr"> Residents 1990s 0.9642sin(0.5501h-0.3933)+0.1275sin(2.618h+0.4103) Housing after 2000 4.368sin(0.0731h-0.0423)+0.07186sin(2.491h+0.5184) Urban residential buildings <![CDATA[-0.0219h 2 +0.1421h+0.0250]]> crop <![CDATA[0.01805h 2 +0.6655h-0.07318]]> Industrial Heavy Industry <![CDATA[0.01h 4 -0.08407h 3 +0.1814h 2 +0.1101h+0.1083]]> Light industry facilities <![CDATA[-0.02221h 3 -0.07381h 2 +0.1796h+0.1]]> Commercial facilities <h2 style=";text-align:left;direction:ltr"><![CDATA[-0.0291h <h2 style=";text-align:left;direction:ltr"> 4 <h2 style=";text-align:left;direction:ltr"> +0.223h<h2 style=";text-align:left;direction:ltr"> 3 <h2 style=";text-align:left;direction:ltr"> -0.6212h<h2 style=";text-align:left;direction:ltr"> 2 <h2 style=";text-align:left;direction:ltr"> +0.8869h+0.0014]]><h2 style=";text-align:left;direction:ltr"> Public service facilities <h2 style=";text-align:left;direction:ltr"><![CDATA[-0.0291h <h2 style=";text-align:left;direction:ltr"> 4 <h2 style=";text-align:left;direction:ltr"> +0.223h<h2 style=";text-align:left;direction:ltr"> 3 <h2 style=";text-align:left;direction:ltr"> -0.6212h<h2 style=";text-align:left;direction:ltr"> 2 <h2 style=";text-align:left;direction:ltr"> +0.8869h+0.0014]]><h2 style=";text-align:left;direction:ltr">

[0095] The economic value of the grid unit is obtained in the following ways:

[0096] First, add the geographical location, industry classification, disaster-prone body type, and flooded water depth information to each grid cell to form a spatial information grid.

[0097] Secondly, based on the statistical yearbook data of the city where the study area is located, the economic data is spatialized on the basis of considering the degree of social and economic contribution of the study area, thereby completing the spatial distribution of economic data; after the economic data is spatialized, each grid unit has multiple information such as "economic value", "water depth", "type of disaster-prone body" and "industry type", thus determining the economic value of each grid.

[0098] Indirect economic losses are calculated using the following formula (2):

[0099] M 前j =L 前j ·a (2)

[0100] In the above formula, M 前j For the construction of water conservancy projects, the previous level was R j The indirect economic losses caused by heavy rain in the study area; a is the conversion factor, which is 16%.

[0101] Step S2.1.2: Calculate the loss of life in the study area caused by different levels of heavy rain before the construction of water conservancy projects. When calculating the loss of life, each grid in the MIKE two-dimensional hydrodynamic model is calculated separately. First, extract the heavy rain simulation results, superimpose the inundation map with the population density map through GIS software, and extract the maximum water depth D, maximum instantaneous flow velocity V, area A and population density ρ of each grid cell; calculate the risk population PAR and S of each grid cell respectively. Fji value, and according to S Fji The value determines the flood severity impact interval; the life loss of each grid is calculated and summed according to the formula. Specifically, the following formula (3) is used for calculation:

[0102]

[0103] In the above formula: LOL 前j For the construction of water conservancy projects, the previous level is R j Heavy rains caused loss of life in the study area; LOL jmin and LOL jmax Before the construction of water conservancy projects, the level was R j The lower and upper bounds of the life loss interval in a rainstorm; PAR 前ji Indicates that before the construction of water conservancy projects, the level is R j The number of people at risk within the flood inundation range of the i-th grid cell in the study area during a heavy rain, f 前ji Indicates that before the construction of water conservancy projects, the level is R j is the life loss mortality rate interval of the ith grid cell in the study area caused by the main factors in the rainstorm; c is the correction coefficient caused by the secondary influencing factors.

[0104] The mortality rate that affects life loss mainly depends on the severity of floods caused by heavy rains before and after the construction of the project. The severity of floods is determined by the maximum flood depth and the maximum flood flow rate, as shown in formula (4);

[0105] S Fji =D ji ×V ji (4)

[0106] In the above formula: S Fji Indicates that the level is R j The flood severity of the i-th grid cell in the study area during the heavy rain, D ji Indicates that the level is R j The maximum flooding depth of the ith grid cell in the study area during a heavy rain, m; V ji Indicates that the level is R j The maximum flood velocity of the ith grid cell in the study area during the rainstorm, m / s;

[0107] At level R j The life loss mortality rate of the i-th grid cell in the study area during a heavy rain is shown in formula (5);

[0108] f ji =f(S Fji,VB ) (5)

[0109] In the above formula: VB is the building vulnerability; f ji Indicates that the level is R j The mortality rate interval of life loss in the i-th grid cell of the study area caused by the main factors in the rainstorm is composed of f1 and f2. f1 is the risk population exposure rate interval affected by the warning time and the degree of understanding of dam failure, and f2 is the exposed population mortality rate interval affected by the severity of floods and the vulnerability of buildings.

[0110] In this embodiment, the population density distribution map of Henan Province in 2020 is superimposed with the rainstorm inundation simulation result map of each return period through GIS software, and the inundation area and population density of each grid in the inundation area are counted to determine the number of people at risk within the flood inundation range. The number of people at risk within the rainstorm inundation range of each return period is 462,273.

[0111] The range of factors affecting life loss and the warning time T W The population exposure rate and understanding of rainfall B Exposure rate impact coefficient caused by flood severity S F It is related to the range of values ​​of the mortality rate of the exposed population affected by the vulnerability of buildings. Through analysis, the mortality rate of the risk population mainly depends on the severity of the flood caused by the heavy rain before and after the construction of the project. Fji .

[0112] The correction coefficient c caused by secondary influencing factors is calculated using the following formula (6):

[0113] c=c1×c2×c3 (6)

[0114] In the above formula: c1, c2 and c3 are the correction coefficients caused by the time of rainstorm, rescue capacity and age distribution respectively; the ranges of c1, c2 and c3 are shown in formula (7);

[0115] {c1,c2,c3}∈{[0.80,1.20],[0.80,1.00],[1.00,1.20]} (7).

[0116] Step S2.2: Calculate the losses caused by different levels of rainstorms after the construction of water conservancy projects

[0117] The same method as in step S2.1.1 is used to calculate the level R after the construction of the water conservancy project. j The direct economic losses caused by heavy rain in the study area 后j and indirect economic losses 后j , the level after the construction of water conservancy project is R j The economic losses caused by heavy rain in the study area are N 后j =L 后j +M 后j .

[0118] Similarly, the same method as in step S2.1.2 is used to calculate the level R after the construction of the water conservancy project. j Heavy rains caused LOL in the study area 后j .

[0119] Step S3: Calculate the waterlogging removal effect of the water conservancy project in the base year by combining economic losses and life losses through the frequency method, including:

[0120] Step S3.1: Economic drainage effect of water conservancy projects in the base year

[0121] Step S3.1.1: Calculate the level before and after the construction of the water conservancy project, R j The difference in economic losses in the study area caused by heavy rains is S j , as shown in formula (8);

[0122] S j =N 前j -N 后j (8)

[0123] Step S3.1.2: Calculate the economic drainage effect of the water conservancy project in the base year using the frequency method. The specific calculation process is shown in formula (9);

[0124]

[0125] In the above formula: S0 represents the economic drainage value of the water conservancy project in the study area in the base year, P j R jThe frequency of heavy rain.

[0126] In this embodiment, the frequency curve method is used to calculate the economic waterlogging removal effect of the Qingshui River and Luxin Canal water conservancy projects in the base year. The multi-year average effect of the water conservancy project is the waterlogging removal effect in the base year, that is, for the different rainstorm recurrence periods that the water conservancy project may encounter, the direct economic losses and indirect economic losses with and without the water conservancy project are calculated for each frequency, and the sum of the two is the economic loss value of different rainstorm recurrence periods. Then, the multi-year economic loss value with and without the water conservancy project is calculated with the frequency as the weight, and the difference is the multi-year average economic effect of the water conservancy project. The calculation results are shown in Table 3.

[0127] Table 3 Economic effect of flood control in the base year of Qingshui River and Luxin Canal water conservancy projects (unit: 10,000 yuan)

[0128]

[0129] Step S3.2: Life drainage effect of water conservancy projects in the base year

[0130] Step S3.2.1: Calculate the level before and after the construction of the water conservancy project, R j The difference in life loss caused by heavy rain in the study area is T j , as shown in formula (10);

[0131] T j =LOL 前j -LOL 后j (10)

[0132] Step S3.2.2: Calculate the waterlogging removal effect of the water conservancy project in the base year using the frequency method, as shown in formula (11);

[0133]

[0134] In the above formula, T0 is the life drainage value of the water conservancy project in the study area in the base year, P j R j The frequency of heavy rain.

[0135] In this embodiment, the frequency curve method is used to calculate the life dewatering effect of the Qingshui River and Luxin Canal water conservancy projects in the base year. According to the different rainstorm recurrence periods that the water conservancy projects may encounter, the life loss with and without the water conservancy projects at each frequency is calculated respectively, and then the multi-year life loss value with and without the water conservancy projects is calculated respectively with the frequency as the weight. The difference is the life dewatering effect of the water conservancy projects in the base year. The calculation results are shown in Table 4.

[0136] Table 4 The life effect of flood control in the Qingshui River and Luxin Canal water conservancy projects in the base year (unit: person)

[0137]

[0138] Step S4: Utilize the waterlogging removal effect of the water conservancy project in the base year and combine it with the economic and population change coefficients of the study area to calculate the waterlogging removal effect of each year in the entire life cycle of the water conservancy project.

[0139] For the full life cycle evaluation of economic effects, the ARIMA model is used to predict the dynamic changes of economic data in the study area, calculate its change coefficient compared with the base year, and then multiply the economic effect of the base year by the change coefficient to obtain the economic effect of each year in the life cycle of the water conservancy project. Specifically, the economic drainage effect in the base year is multiplied by the predicted economic change coefficient α k Combined with the above, the economic drainage effect in any year in the whole life cycle is obtained, as shown in formula (12);

[0140] U k =S0·[(1+α1)·(1+α2), ...., (1+α k )] (12)

[0141] In the above formula: U k is the economic drainage value of the kth year relative to the base year in the life cycle of the water conservancy project; α k It is the coefficient of change of the economic data of the research area where the water conservancy project is located in the kth year relative to the k-1th year, k = 0, 1, 2, 3, 4..., k = 0 for the base year, and k = 1 for the first year after the base year.

[0142] In this embodiment, the economic data of recent years are obtained by consulting the Zhoukou City Yearbook (2020) and the China County Statistical Yearbook (2020). And predictions are made based on the economic data of recent years. The specific prediction results are shown in Table 5.

[0143] Table 5 Economic data forecast table (unit: 100 million yuan)

[0144]

[0145]

[0146] After consulting relevant literature, we learned that the predicted growth rate of China's economy from 2031 to 2035 is 4.7%. The economic growth rate predicted by this model is 3.3%, with an error within 2%. It is believed that the prediction of this model is reasonable.

[0147] For the full life cycle assessment of life effects, reference is made to the changes in China's future population in the "World Population Prospects 2022: Summary of Results", which is made to change linearly over the life cycle of the water conservancy project. The coefficient of change is calculated and multiplied by the life effect of the base year to obtain the life effect of the water conservancy project in each year over the life cycle.

[0148] Specifically, the life effect of the base year and the life change coefficient β i Combined, the life dewatering effect in any year of the whole life cycle is obtained, as shown in formula (13);

[0149] V k =T0·[(1+β1)·(1+β2), ...., (1+β k )] (13)

[0150] In the above formula: V k is the life drainage effect of the kth year relative to the base year in the life cycle of the water conservancy project; T0 is the life drainage loss in the base year of the water conservancy project; β k It is the coefficient of change of the population data in the study area where the water conservancy project is located in the kth year relative to the k-1th year, k = 0, 1, 2, 3, 4..., k = 0 for the base year, and k = 1 for the first year after the base year.

[0151] In this embodiment, according to the forecast of World Population Prospects 2022: Summary of Results, China's population will be 1.426 billion in 2022 and 1.317 billion in 2050. Based on this data, the population changes linearly, as shown in Table 6.

[0152] Table 6 Population data forecast table (unit: 100 million people)

[0153]

[0154]

[0155] In this embodiment, based on the economic data predicted above and the changes in population data, the effects of the Qingshui River and Luxin Canal water conservancy projects over the entire life cycle are predicted with the base year as the unit. The economic effect of the base year is calculated to be 18.8641 million yuan from Table 3, and the life effect of the base year is calculated to be 1.595 people from Table 4. The economic change coefficient is assigned to the economic effect of the base year, and the economic effect of each year in the life cycle of the water conservancy project is obtained according to formula (12); the population change coefficient is assigned to the life effect of the base year, and the life effect of each year in the life cycle of the water conservancy project is obtained according to formula (13). The specific calculation results are shown in Table 7.

[0156] Table 7 Flood control effect of Qingshui River and Luxin Canal water conservancy projects Flood control effect over the entire life cycle

[0157] years Economic effect (ten thousand yuan) Life Effect (Human) 2020 188.641 1.595 2021 193.507 1.590661 2030 292.760 1.590553 2040 395.683 1.590425 2050 491.383 1.590290 2060 580.363 1.590147 2070 663.104 1.589994

[0158] To sum up, in the past, the calculation results based on the base year were mostly used to evaluate the drainage effect. The drainage effect evaluation based on the entire life cycle of the water conservancy project adopted in the present invention reflects the drainage benefits of the water conservancy project in every year of the entire life cycle, providing a scientific basis for evaluating the construction effects of such projects.

Claims

1. A method for evaluating the waterlogging removal effect of a water conservancy project based on the entire life cycle, characterized in that: The steps include: Step S1: Using hydrodynamic simulation software to simulate the flooding situation of the study area where the water conservancy project is located when encountering heavy rains of various return periods; Step S2: Calculate the economic and life losses caused by heavy rains of each return period before and after the construction of water conservancy projects in the study area; Step S3: Calculate the waterlogging removal effect of the water conservancy project in the base year by combining economic losses and life losses through the frequency method; Step S4: Utilize the waterlogging removal effect of the water conservancy project in the base year and combine it with the economic and population change coefficients of the study area to calculate the waterlogging removal effect of each year in the entire life cycle of the water conservancy project.

2. The method for evaluating the waterlogging removal effect of a water conservancy project based on the entire life cycle according to claim 1 is characterized in that: The step S1 specifically includes the following steps: Step S1.1: Extract the boundary data of the study area from the BIGMAP software, obtain the elevation of the study area from the geospatial data cloud, and grid the simulation area using the hydrodynamic simulation software; Step S1.2: In the hydrodynamic simulation software, rainfall with different return periods is added to the study area. The rainstorm levels and frequencies with different return periods are shown in Table 1; Table 1 Rainstorm levels and occurrence frequency according to return period Step S1.3: Set the corresponding outlet flow at the outlet of the river grid in the study area, and set gates at different locations of the river according to the design requirements of the water conservancy project to simulate the maximum flooding depth and maximum flow rate of each grid in the study area before and after the project under heavy rains with different recurrence periods, and obtain the flood inundation simulation results of the study area under different rainfall levels.

3. The method for evaluating the waterlogging removal effect of a water conservancy project based on the entire life cycle according to claim 2 is characterized in that: In step S2, the economic and life losses caused by rainstorms in each return period before and after the construction of the water conservancy project in the study area are calculated, specifically including: Step S2.1: Calculate the losses caused by different levels of rainstorms before the construction of water conservancy projects, including economic losses and loss of life, specifically: Step S2.1.1: Level R j Economic losses caused by heavy rains 前j , including direct economic losses L 前j and indirect economic losses 前j , that is, N 前j =L 前j +M 前j ; The direct economic loss is calculated using the following formula (1): In the above formula: L 前j For the construction of water conservancy projects, the previous level is R j The direct economic losses caused by heavy rain in the study area; 前ji Before the construction of the water conservancy project, the i-th grid unit is at level R j The economic loss rate in the rainstorm; 前ji is the economic value of the i-th grid unit before the construction of the water conservancy project, n means that the study area is divided into n grid units, j = 1, 2, 3, 4, 5; Indirect economic losses are calculated using the following formula (2): M 前j =L 前j ·a (2) In the above formula, M 前j For the construction of water conservancy projects, the previous level was R j The indirect economic losses caused by heavy rain in the study area; a is the conversion factor, which is 16%; Step S2.1.2: Calculate the loss of life in the study area caused by different levels of rainstorms before the construction of the water conservancy project using the following formula (3): In the above formula: LOL 前j For the construction of water conservancy projects, the previous level was R j Heavy rains caused loss of life in the study area; LOL jmin and LOL jmax Before the construction of water conservancy projects, the level was R j The lower and upper bounds of the life loss interval in a rainstorm; PAR 前ji Indicates that before the construction of water conservancy projects, the level is R j The number of people at risk within the flood inundation range of the i-th grid cell in the study area during a heavy rain, f 前ji Indicates that before the construction of water conservancy projects, the level is R j The life loss mortality rate interval of the ith grid cell in the study area caused by the main factors in the rainstorm; c is the correction coefficient caused by the secondary influencing factors; Step S2.2: Calculate the losses caused by different levels of rainstorms after the construction of water conservancy projects The same method as in step S2.1.1 is used to calculate the level R after the construction of the water conservancy project. j The direct economic losses caused by heavy rain in the study area 后j and indirect economic losses 后j , the level after the construction of water conservancy project is R j The economic losses caused by heavy rain in the study area are N 后j =L 后j +M 后j ; Similarly, the same method as in step S2.1.2 is used to calculate the level R after the construction of the water conservancy project. j Heavy rains caused LOL in the study area 后j .

4. The method for evaluating the waterlogging removal effect of a water conservancy project based on the entire life cycle according to claim 3 is characterized in that: In step S2.1, the economic loss rate of different grid units is determined according to the disaster-prone body type corresponding to the grid unit in the study area. Different disaster-prone body types correspond to different loss rate curves. By substituting the selected time year into the corresponding loss rate curve, the economic loss rate of the corresponding grid unit in that year can be obtained; By consulting the existing literature, the loss rate curve of the study area was obtained.

5. The method for evaluating the waterlogging removal effect of a water conservancy project based on the entire life cycle according to claim 4 is characterized in that: In step S2.1.1, the economic value of the grid unit is obtained by: First, add the geographical location, industry classification, disaster-prone body type, and flooded water depth information to each grid cell to form a spatial information grid. Secondly, based on the statistical yearbook data of the city where the study area is located, the economic data is spatialized on the basis of considering the degree of social and economic contribution of the study area, thereby completing the spatial distribution of economic data; after the economic data is spatialized, each grid unit simultaneously has multiple information such as "economic value", "water depth", "type of disaster-prone body" and "industry type", thus determining the economic value of each grid.

6. The method for evaluating the waterlogging removal effect of a water conservancy project based on the entire life cycle according to claim 5 is characterized in that: In step S2.1.2, the population density distribution map of the city in the study area in that year is superimposed with the rainstorm inundation simulation result map of each return period before the construction of the water conservancy project through GIS software, and the inundation area and population density of each grid unit in the inundation area are counted to determine the level of R before the construction of the water conservancy project. j The number of people at risk within the flood inundation range of the i-th grid cell in the study area during a heavy rain PAR 前ji ; Similarly, according to the above method, after the construction of water conservancy projects, the level is R j The number of people at risk within the flood inundation range of the i-th grid cell in the study area during a heavy rain PAR 后ji .

7. The method for evaluating the waterlogging removal effect of a water conservancy project based on the entire life cycle according to claim 6 is characterized in that: In step S2.1.2, the mortality rate that affects the loss of life mainly depends on the severity of the flood caused by the heavy rain before and after the project construction. The severity of the flood is determined by the maximum flood depth and the maximum flood flow rate, as shown in formula (4); S Fji =D ji ×V ji (4) In the above formula: S Fji Indicates that the level is R j The flood severity of the i-th grid cell in the study area during the heavy rain, D ji Indicates that the level is R j The maximum flooding depth of the ith grid cell in the study area during a heavy rain, m; V ji Indicates that the level is R j The maximum flood velocity of the ith grid cell in the study area during the rainstorm, m / s; At level R j The life loss mortality rate interval of the i-th grid cell in the study area during a heavy rain is shown in formula (5); f ji =f(S Fji,VB ) (5) In the above formula: VB is the building vulnerability; f ji Indicates that the level is R j The mortality rate interval of life loss in the i-th grid cell of the study area caused by the main factors in the rainstorm is composed of f1 and f2. f1 is the risk population exposure rate interval affected by the warning time and the degree of understanding of dam failure, and f2 is the exposed population mortality rate interval affected by the severity of floods and the vulnerability of buildings. The correction coefficient c caused by secondary influencing factors is calculated using the following formula (6): c=c1×c2×c3 (6) In the above formula: c1, c2 and c3 are the correction coefficients caused by the time of rainstorm, rescue capacity and age distribution respectively; the ranges of c1, c2 and c3 are shown in formula (7); {c1,c2,c3}∈{[0.80,1.20],[0.80,1.00],[1.00,1.20]} (7).

8. The method for evaluating the waterlogging removal effect of a water conservancy project based on the entire life cycle according to claim 7 is characterized in that: In step S3, calculating the waterlogging removal effect of the water conservancy project in the base year specifically includes: Step S3.1: Economic drainage effect of water conservancy projects in the base year Step S3.1.1: Calculate the level before and after the construction of the water conservancy project, R j The difference in economic losses in the study area caused by heavy rains is S j , as shown in formula (8); S j =N 前j -N 后j (8) Step S3.1.2: Calculate the economic drainage effect of the water conservancy project in the base year using the frequency method. The specific calculation process is shown in formula (9); In the above formula: S0 represents the economic drainage value of the water conservancy project in the study area in the base year, P j R j frequency of heavy rains; Step S3.2: Life drainage effect of water conservancy projects in the base year Step S3.2.1: Calculate the level before and after the construction of the water conservancy project, R j The difference in life loss caused by heavy rain in the study area is T j , as shown in formula (10); T j =LOL 前j -LOL 后j (10) Step S3.2.2: Calculate the waterlogging removal effect of the water conservancy project in the base year using the frequency method, as shown in formula (11); In the above formula, T0 is the life drainage value of the water conservancy project in the study area in the base year, P j R j The frequency of heavy rain.

9. The method for evaluating the waterlogging removal effect of a water conservancy project based on the entire life cycle according to claim 8 is characterized in that: In step S4, the economic flood control effect in the base year is compared with the predicted economic change coefficient α. k Combined with the above, the economic drainage effect in any year in the whole life cycle is obtained, as shown in formula (12); U k =S0·[(1+α1)·(1+α2),....,(1+α k )] (12) In the above formula: U k is the economic drainage value of the kth year relative to the base year in the life cycle of the water conservancy project; α k is the coefficient of change of the economic data of the research area where the water conservancy project is located in the kth year relative to the k-1th year; The life effect of the base year and the life change coefficient β i Combined, the life dewatering effect in any year of the whole life cycle is obtained, as shown in formula (13); V k =T0·[(1+β1)·(1+β2),....,(1+β k )] (13) In the above formula: V k is the life drainage effect of the kth year relative to the base year in the life cycle of the water conservancy project; T0 is the life drainage loss in the base year of the water conservancy project; β k It is the coefficient of change of the population data in the study area where the water conservancy project is located in the kth year relative to the k-1th year, k = 0, 1, 2, 3, 4..., k = 0 for the base year, and k = 1 for the first year after the base year.

10. The method for evaluating the waterlogging removal effect of a water conservancy project based on the entire life cycle according to claim 9, characterized in that: The economic data of the study area in each year during the life cycle of the water conservancy project are predicted by the AMIRA model. The economic data of each year are compared with the economic data of the previous year to obtain the economic data change coefficient α of the study area. k ; According to the population forecast data of the urban area where the study area is located, the population data of each year is compared with the population data of the previous year to obtain the change coefficient β of the population in the study area. k .

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