Modeling method and system suitable for universal rainwater collection system

Abstract

The invention relates to the technical field of hydrological modeling, and discloses a modeling method and system suitable for a universal rainwater collection system, and the method comprises the following steps: carrying out the random simulation of rainfall characteristics based on rainfall parameters including the rainfall depth dr, the rainfall duration tr and the non-rainfall duration tn, and constructing a linear combination of the rainfall characteristics; carrying out random simulation on the runoff collected during the rainfall period to obtain the water volume VC of the runoff intercepted by the roof; simulating the residual water amount in the rainwater storage unit to obtain the range of the residual water amount St when the rainfall cycle starts; performing random simulation on overflow of the rainwater storage unit to obtain overflow Vs; and constructing system reliability parameters. The method solves the problem that the prior art does not consider that the random rainfall characteristics do not conform to the non-memory index distribution, and has the characteristics of accuracy and objectivity.

Description

Technical Field

[0001] The present invention relates to the technical field of hydrological modeling, and more specifically, to a modeling method and system suitable for a universal rainwater harvesting system. Background Art

[0002] Rapid urbanization has led to an increase in the area of impervious surfaces, causing adverse hydrological impacts such as floods and water quality deterioration. With the growth of the population, the diversification of water demand for households, industries, and agriculture has put increasing pressure on water supply. Therefore, under the threats of extreme climate events, intense human activities, rapid urbanization, and population growth, water resource tension and scarcity have become an urgent challenge for many countries in the world. Achieving, enhancing, or maximizing the effectiveness of rainwater harvesting (RWH) in alleviating challenges and promoting green buildings requires scientific design, evaluation, planning, and management of RWH. One of the key foundations is the advanced modeling of hydrological processes in various RWH systems.

[0003] Currently, Stochastic Rainwater Harvesting System Modeling (StRaHaS) can improve the accuracy and applicability of hydrological modeling in the wide application of RWH systems in large areas with scarce data. It reveals the impacts of water demand and rainfall characteristics on system reliability, etc. However, from the perspective of stochastic RWH simulation, the stochastic rainfall characteristics do not fully conform to the memoryless exponential distribution; at the same time, the assumption that the RWSU is filled at the end of each rainfall event is not reasonable in areas with scarce rainfall events. This may cause certain deviations in the modeling of the entire system, affecting its objectivity and accuracy.

[0004] There is a prior art method for comprehensive evaluation of the health of a drainage system. By performing deep learning, mining, and modeling on multi-source data such as meteorology, remote sensing, elevation, pipe networks, and exploration of the research object, indicators for evaluating the health of the urban drainage system are obtained, and the comprehensive weight of each indicator is calculated, thereby reflecting the health degree of the drainage system.

[0005] However, the prior art has the problem of not considering that the stochastic rainfall characteristics do not conform to the memoryless exponential distribution. Therefore, how to invent a modeling method suitable for a universal rainwater harvesting system that considers stochastic rainfall characteristics is a technical problem urgently to be solved in this technical field. Summary of the Invention

[0006] In order to solve the problem that the existing modeling technology does not consider that the stochastic rainfall characteristics do not conform to the memoryless exponential distribution, the present invention provides a modeling method and system suitable for a universal rainwater harvesting system, which have the characteristics of accuracy and objectivity.

[0007] To achieve the above object of the present invention, the following technical solutions are adopted:

[0008] A modeling method applicable to a universal rainwater collection system, comprising the following specific steps:

[0009] Based on rainfall parameters including rainfall depth d r , rainfall duration t r , non-rainfall duration t n , randomly simulate rainfall characteristics and construct a linear combination of rainfall characteristics;

[0010] Based on the linear combination, randomly simulate the runoff collected during rainfall to obtain the amount of water V C intercepted by the roof;

[0011] Based on the linear combination, simulate the remaining water volume in the rainwater storage unit to obtain the range of the remaining water volume S t when the rainfall cycle starts;

[0012] Based on S t , randomly simulate the overflow of the rainwater storage unit to obtain the overflow V s ;

[0013] Integrate the linear combination, V C , V s to construct system reliability parameters.

[0014] Furthermore, based on rainfall parameters including rainfall depth d r , rainfall duration t r , non-rainfall duration t n , randomly simulate rainfall characteristics and construct a linear combination of rainfall characteristics. The specific steps are as follows: Assume that the distributions of d r , t r , t n are composed of the linear combination of two independent exponential distributions with parameter 1. Randomly simulate rainfall characteristics. Based on the obtained sample values, obtain 3 groups of linear combinations:

[0015]

[0016] Among them, P r (*) is the occurrence probability of a random event *, A 1 , A 2 , B 1 , B 2 , C 1 , C 2 are constants, D r , T n , T r respectively represent the samples corresponding to d r , t n , t r , D r1, D r2 , T n1 , T n2 , T r1 , T r2 respectively represent the corresponding sample values.

[0017] Furthermore, when performing random simulation, for any rainfall parameter, assume it satisfies:

[0018]

[0019] where x represents d r , t r , t n any parameter, K 1 , K 2 is the constant corresponding to x, PDFs represents the probability density function of the random variable, and CDFs represents the cumulative distribution function of the random variable.

[0020] Furthermore, the amount of water V intercepted by the roof C is specifically:

[0021]

[0022] where a is the area of the vertical projection of the roof surface, i.e., the drainage area of the rainwater collection system, φ is the runoff coefficient representing the proportion of rainfall converted into runoff, and d f is the depth of the initial runoff diverted by the runoff diversion device or debris flow filter.

[0023] Furthermore, by simulating the remaining water volume in the rainwater storage unit, the range of the remaining water volume S when the rainfall cycle starts is obtained. Specifically: Assume that the rainwater storage unit is full at the beginning, with a volume of V at this time. According to the length t t of its non-rainy period and the water demand d n during the non-rainy cycle, when the rainfall cycle starts, the remaining water volume S 1 is expressed as: t

[0024]

[0025] where the range of S t is from 0 to (V – dt n ), and d is the average water demand during all rainy and non-rainy periods.

[0026] Furthermore, specifically:

[0027]

[0028] where d 2 is the average water demand during rainfall, E(T n)、E(T r ) represent the expected value of T n , T r .

[0029] Furthermore, an overflow V s is obtained. Specifically, a part of the collected runoff is used as the water demand during rainfall and non-rainfall periods, and the remaining part overflows into the municipal sewer system as an overflow, which is a random variable V s :

[0030]

[0031] Among them, E(S t ) represents the expected value of S t .

[0032] Furthermore, after obtaining V s , its corresponding overflow probability is further calculated. Specifically, the probability f of leakage occurring in each rainwater collection cycle is solved:

[0033] f = F(V s = 0).

[0034] Furthermore, by comprehensively considering the linear combination, V C , V s , system reliability parameters are constructed. Specifically, let the random variable T s be the total service time, and R represents the duration of the rainwater collection cycle. The expected value of R is expressed as r = E(R). r represents the average time fraction of the rainwater collected by the rainwater collection system during all rainwater collection processes that meets the total water demand. r is used as the system reliability parameter of the rainwater collection system:

[0035]

[0036] Among them, E(T s ) represents the expected value of T s .

[0037] A modeling system applicable to a universal rainwater collection system includes a random rainfall simulation module, a random runoff simulation module, a random remaining water volume simulation module, a random overflow simulation module, and a system evaluation module:

[0038] The random rainfall simulation module is used to randomly simulate the rainfall characteristics based on rainfall parameters including rainfall depth d r , rainfall duration t r , and non-rainfall duration t n , and construct a linear combination of rainfall characteristics;

[0039] The described random runoff simulation module is used to perform a random simulation of the runoff collected during rainfall based on a linear combination to obtain the amount of water V intercepted by the roof from the runoff. C ;

[0040] The described random remaining water volume simulation module is used to simulate the remaining water volume in the rainwater storage unit based on a linear combination to obtain the remaining water volume S at the start of the rainfall cycle. t range;

[0041] The described random overflow simulation module is used to perform a random simulation of the overflow of the rainwater storage unit based on S t to obtain the overflow V s ;

[0042] The described system evaluation module is used to construct system reliability parameters by comprehensively considering the linear combination, V C and V s .

[0043] The beneficial effects of the present invention are as follows:

[0044] The present invention discloses a modeling method applicable to a general rainwater harvesting system. By considering rainfall parameters including rainfall depth d r , rainfall duration t r , and non-rainfall duration t n , a random simulation of rainfall characteristics is performed, a linear combination of rainfall characteristics is constructed, and further based on the linear combination, a random simulation of the runoff collected during rainfall, the remaining water volume in the rainwater storage unit, and the overflow of the rainwater storage unit is carried out, and system reliability parameters are constructed by comprehensively considering the simulation parameters. On the basis of the existing random RWH simulation, the random rainfall characteristics are fully considered, and it is not assumed that the rainwater storage unit will be filled at the end of each rainfall event. Compared with the existing modeling methods, it can more objectively and accurately reflect the actual situation. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is a schematic flow chart of the modeling method applicable to the general rainwater harvesting system of the present invention.

[0046] Figure 2 is a system block diagram of the modeling system applicable to the general rainwater harvesting system of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0047] The following describes the present invention in detail with reference to the drawings and specific embodiments.

[0048] Embodiment 1

[0049] As Figure 1 shown, a modeling method applicable to a general rainwater harvesting system includes the following specific steps:

[0050] Based on rainfall parameters including rainfall depth d r , rainfall duration t r , and non-rainfall duration t n , randomly simulate rainfall characteristics, and construct a linear combination of rainfall characteristics;

[0051] Based on the linear combination, randomly simulate the runoff collected during rainfall to obtain the amount of water V intercepted by the roof C ;

[0052] Based on the linear combination, simulate the remaining water volume in the rainwater storage unit to obtain the range of the remaining water volume S t when the rainfall cycle starts;

[0053] Based on S t , randomly simulate the overflow of the rainwater storage unit to obtain the overflow V s and the overflow probability f;

[0054] Integrate the linear combination, V C , V s , and construct system reliability parameters.

[0055] Example 2

[0056] In a specific embodiment, based on rainfall parameters including rainfall depth d r , rainfall duration t r , and non-rainfall duration t n , randomly simulate rainfall characteristics and construct a linear combination of rainfall characteristics. The specific steps are as follows: Let d r , t r , and t n be distributed as a linear combination of two independent exponential distributions with parameter 1. Randomly simulate rainfall characteristics, and based on the obtained sample values, obtain 3 groups of linear combinations:

[0057]

[0058] Among them, P r (*) is the occurrence probability of a random event *, A 1 , A 2 , B 1 , B 2 , C 1 , C 2 are constants, D r , T n , T r respectively represent the samples corresponding to d r , t n , and t r , Dr1 , D r2 , T n1 , T nn , T r1 , T r2 respectively represent the corresponding sample values.

[0059] In a specific embodiment, when performing random simulation, for any rainfall parameter, it is assumed to satisfy:

[0060]

[0061]

[0062] where x represents d r , t r , t n any parameter, K 1 , K 2 is the constant corresponding to x, PDFs represents the probability density function of the random variable, and CDFs represents the cumulative distribution function of the random variable.

[0063] In a specific embodiment, the amount of water V intercepted by the roof C is specifically:

[0064]

[0065] where a is the area of the vertical projection of the roof surface, that is, the drainage area of the rainwater collection system, φ is the runoff coefficient representing the proportion of rainfall converted into runoff, and d f is the depth of the initial runoff diverted by the runoff diversion device or debris flow filter.

[0066] In this embodiment, roof area a: 100 m2, runoff coefficient φ: 0.87, first flushing depth d f : 0.4 mm.

[0067] In a specific embodiment, the remaining water volume in the simulated rainwater storage unit is obtained. When the rainfall cycle starts, the range of the remaining water volume S t is specifically: Assuming that the rainwater storage unit is full at the beginning, with a volume of V at this time, according to the length t n of its non-rainy period and the water demand d 1 during the non-rainy cycle, when the rainfall cycle starts, the remaining water volume S t is expressed as:

[0068]

[0069] where the range of S T is from 0 to (V – dt N ), and d is the average water demand for all rainy and non-rainy periods.

[0070] In a specific embodiment, specifically:

[0071]

[0072] where d 2 is the average water demand during rainfall, and E(T N ), E(T R ) respectively represent the expected values of T N , T R .

[0073] In a specific embodiment, the overflow V S is obtained. Specifically: A part of the collected runoff is used as the water demand during rainfall and non-rainfall periods, and the remaining part will overflow as the overflow into the municipal sewer system, which is the random variable V s :

[0074]

[0075] where E(S t ) represents the expected value of S t .

[0076] In a specific embodiment, after obtaining V s , its corresponding overflow probability is further calculated as part of the model. Specifically: The probability f of leakage occurring in each rainwater collection cycle is solved:

[0077] f = F(V s = 0).

[0078] In a specific embodiment, by comprehensively considering the linear combination, V C , V s , the system reliability parameter is constructed. Specifically: Let the random variable T s be the total service time, and R represent the rainwater collection cycle duration. The expected value of R is expressed as r = E(R), and r represents the average time fraction during all rainwater collection processes that the rainwater collected by the rainwater collection system meets the total water demand. r is used as the rainwater collection system reliability parameter:

[0079]

[0080] where E(T s ) represents the expected value of T s .

[0081] Example 3

[0082] Such as Figure 2As shown in the figure, a modeling system applicable to a universal rainwater collection system includes a random rainfall simulation module, a random runoff simulation module, a random remaining water volume simulation module, a random overflow simulation module, and a system evaluation module:

[0083] The described random rainfall simulation module is used to randomly simulate rainfall characteristics based on rainfall parameters including rainfall depth d r , rainfall duration t r , and non-rainfall duration t n to construct a linear combination of rainfall characteristics;

[0084] The described random runoff simulation module is used to randomly simulate the runoff collected during rainfall based on the linear combination to obtain the amount of water V C intercepted by the roof;

[0085] The described random remaining water volume simulation module is used to simulate the remaining water volume in the rainwater storage unit based on the linear combination to obtain the range of the remaining water volume S t at the start of the rainfall cycle;

[0086] The described random overflow simulation module is used to randomly simulate the overflow of the rainwater storage unit based on S t to obtain the overflow V s and the overflow probability f;

[0087] The described system evaluation module is used to comprehensively combine the linear combination, V c , V s to construct system reliability parameters.

[0088] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention and are not limitations on the implementation manners of the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the claims of the present invention.

Claims

1. A modeling method applicable to a universal rainwater collection system, characterized in that: The specific steps include: Based on rainfall depth d r , rainfall duration t r , non-rainfall duration t n The rainfall parameters are used to randomly simulate the rainfall characteristics and construct the linear combination of rainfall characteristics. Based on linear combinations, a random simulation is performed on the runoff collected during rainfall to obtain the amount of water intercepted by the roof V C ; Based on the linear combination, the remaining water volume in the rainwater storage unit is simulated, and the remaining water volume S is obtained when the rainfall cycle begins. t scope; Based on S t , the overflow of the rainwater storage unit is randomly simulated and the overflow V s ; Comprehensive linear combination, V C 、V s , build system reliability parameters.

2. The modeling method applicable to a universal rainwater collection system according to claim 1, characterized in that: Based on rainfall depth d r , rainfall duration t r , non-rainfall duration t n The rainfall parameters are used to randomly simulate the rainfall characteristics and construct the linear combination of rainfall characteristics. The specific steps are as follows: Let d r ,t r ,t n The distribution of is a linear combination of two independent exponential distributions with parameter 1. The rainfall characteristics are randomly simulated, and based on the obtained sample values, three sets of linear combinations are obtained: Among them, P r (*) is the probability of a random event*, A1, A2, B1, B2, C1, C2 are constants, D r , T n , T r Respectively represent the corresponding d r ,t n ,t r Sample, D r1 , D r2 , T n1 , T n2 , T r1 , T r2 They represent the corresponding sample values ​​respectively.

3. The modeling method applicable to the universal rainwater collection system according to claim 2, characterized in that: When performing random simulation, for any rainfall parameter, assume that it satisfies: Where x represents d r ,t r ,t n Any parameter, K1, K2 are constants corresponding to x, PDFs represent the probability density function of the random variable, and CDFs represent the cumulative distribution function of the random variable.

4. The modeling method applicable to a universal rainwater collection system according to claim 2, characterized in that: The amount of water intercepted by the roof v C Specifically: Among them, a is the area of ​​the vertical projection of the roof, that is, the drainage area of ​​the rainwater collection system, φ is the runoff coefficient indicating the proportion of rainfall converted into runoff, and d f It is the depth to which the initial runoff is diverted by the discard flow diverter or debris flow filter.

5. The modeling method applicable to a universal rainwater collection system according to claim 4, characterized in that: Simulate the remaining water volume in the rainwater storage unit and obtain the remaining water volume S when the rainfall cycle begins. T The range is as follows: Assuming that the rainwater storage unit is full at the beginning, the volume is V, according to the length of its non-rainfall period t n and the water demand in the non-rainfall period d1. When the rainfall period begins, the remaining water S t It is expressed as: Among them, S t The range is from 0 to (V–dt n ), d is the average water demand during all rainy and non-rainy periods.

6. The modeling method applicable to the universal rainwater collection system according to claim 5, characterized in that: Specific: Among them, d2 is the average water demand during rainfall, E(T n )、E(T r ) represent T n , T r expected value.

7. The modeling method for a universal rainwater collection system according to claim 6, characterized in that: Get overflow V s Specifically, part of the collected runoff will be used as water demand during rainfall and non-rainfall periods, and the rest will overflow into the municipal sewer system as an overflow, which is a random variable V s : Among them, E(S t ) indicates S t expected value.

8. The modeling method applicable to a universal rainwater collection system according to claim 7, characterized in that: Get V s After that, the corresponding overflow probability f is further calculated. Specifically, the probability f of leakage in each rainwater collection cycle is solved: f=F(V s =0)。 9. The modeling method applicable to a universal rainwater collection system according to claim 7, characterized in that: Comprehensive linear combination, V C 、V s , construct the system reliability parameters, specifically: let the random variable T s is the total service time, R represents the duration of the rainwater collection cycle, and the expected value of R is expressed as r = E(R). r represents the average time fraction of the rainwater collected by the rainwater collection system to meet the total water demand during all rainwater collection processes. r is used as the reliability parameter of the rainwater collection system: Among them, E(T s ) indicates T s expected value.

10. A modeling system suitable for a universal rainwater collection system, characterized in that: Including random rainfall simulation module, random runoff simulation module, random residual water simulation module, random overflow simulation module, system evaluation module: The random rainfall simulation module is used to simulate the rainfall depth d R , rainfall duration t r , non-rainfall duration t n The rainfall parameters are used to randomly simulate the rainfall characteristics and construct the linear combination of rainfall characteristics. The random runoff simulation module is used to perform random simulation on the runoff collected during rainfall based on linear combination to obtain the amount of water V intercepted by the roof. C ; The random residual water simulation module is used to simulate the residual water in the rainwater storage unit based on linear combination, and obtain the residual water volume S when the rainfall cycle starts. T scope; The random overflow simulation module is used to simulate the flow of T , the overflow of the rainwater storage unit is randomly simulated and the overflow V S ; The system evaluation module is used to synthesize linear combinations, V C 、V s , build system reliability parameters.

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