Method, device, equipment and storage medium for assessing composite salt-drought intensity in estuary areas

Abstract

The present invention discloses a method, device, equipment and storage medium for assessing the composite salty drought intensity in an estuary area, which is used to solve the technical problem that the composite salty drought intensity in an estuary area cannot be assessed. The present invention comprises: collecting runoff data and salinity data of a preset estuary area; calculating the optimal marginal distribution function of the runoff sequence according to the runoff data; calculating the optimal marginal distribution function of the salinity sequence according to the salinity data; calculating the standardized runoff index according to the optimal marginal distribution function of the runoff sequence; calculating the standardized salinity index according to the optimal marginal distribution function of the salinity sequence; modeling according to the optimal marginal distribution function of the runoff sequence and the optimal marginal distribution function of the salinity sequence, and selecting the optimal joint distribution function; calculating the composite salty drought index according to the standardized runoff index, the standardized salinity index and the optimal joint distribution function; the composite salty drought index is used to assess the composite salty drought intensity in the estuary area.

Description

Technical Field

[0001] The present invention relates to the technical field of salt drought intensity assessment, and in particular to a method, device, equipment and storage medium for assessing salt drought intensity in estuary areas. Background Art

[0002] Estuarine areas, as key transition zones between river and marine systems, are usually located in the downstream areas of rivers with dense populations and industries, which have a great demand for freshwater. In recent years, climate change and human activities (such as increased upstream freshwater extraction, channel deepening, sand mining, etc.) have led to increasingly serious problems of saltwater upstreaming in estuaries around the world. Traditional environmental monitoring methods usually assess drought or salinity conditions independently. For example, SRI assesses drought conditions based on runoff data, while SSI measures chlorine content in water. These methods have certain effectiveness in single indicators, but fail to consider the combined effects of drought and salinity. Compound salty drought events refer to hydrological droughts and saltwater upstreaming that occur simultaneously or continuously in estuaries, exacerbating the negative impacts caused by single extreme events. Compound salty drought events have received increasing attention due to their potential adverse effects on water resources, crop production and food security. Summary of the invention

[0003] The present invention provides a method, device, equipment and storage medium for evaluating the composite salt-drought intensity in an estuary area, which are used to solve the technical problem that the composite salt-drought intensity in an estuary area cannot be evaluated.

[0004] The present invention provides a method for assessing the composite salt-drought intensity in an estuary area, comprising:

[0005] Collect runoff and salinity data for pre-planned estuary areas;

[0006] Calculating the optimal marginal distribution function of the runoff sequence according to the runoff data;

[0007] Calculating the optimal marginal distribution function of the salinity sequence according to the salinity data;

[0008] Calculating a standardized runoff index according to the optimal marginal distribution function of the runoff sequence;

[0009] Calculating a standardized salinity index according to the optimal marginal distribution function of the salinity sequence;

[0010] Modeling is performed according to the optimal marginal distribution function of the runoff sequence and the optimal marginal distribution function of the salinity sequence, and an optimal joint distribution function is selected;

[0011] A composite salt-drought index is calculated according to the standardized runoff index, the standardized salinity index and the optimal joint distribution function; the composite salt-drought index is used to evaluate the composite salt-drought intensity in estuary areas.

[0012] Optionally, the step of collecting runoff data and salinity data of a preset estuary area includes:

[0013] Collect initial runoff data and initial salinity data for the planned estuary area;

[0014] Converting the initial runoff data into monthly average runoff as runoff data;

[0015] The initial salinity data are converted into monthly average salinity as salinity data.

[0016] Optionally, the step of calculating the optimal marginal distribution function of the runoff sequence according to the runoff data comprises:

[0017] Using a plurality of preset distribution functions to fit the runoff data to obtain a plurality of fitting distribution functions;

[0018] The statistical value of each fitted distribution function was calculated using a preset test method;

[0019] The fitted distribution function with the smallest statistical value is determined as the optimal marginal distribution function of the runoff series.

[0020] Optionally, the step of calculating the standardized runoff index according to the optimal marginal distribution function of the runoff sequence comprises:

[0021] Calculating the marginal probability of the optimal marginal distribution function of the runoff sequence;

[0022] The marginal probabilities were converted into normalized runoff indices by normal distribution.

[0023] Optionally, the step of modeling according to the optimal marginal distribution function of the runoff sequence and the optimal marginal distribution function of the salinity sequence and selecting the optimal joint distribution function comprises:

[0024] Using several joint distribution functions to model the optimal marginal distribution function of the runoff sequence and the optimal marginal distribution function of the salinity sequence;

[0025] Evaluating the goodness of fit of each of the joint distribution functions;

[0026] The joint distribution function with the best goodness of fit is determined as the optimal joint distribution function.

[0027] Optionally, the step of calculating a composite salt-drought index according to the standardized runoff index, the standardized salinity index and the optimal joint distribution function comprises:

[0028] Calculating the probability of simultaneous occurrence of drought and saltwater tide according to the optimal marginal distribution function of runoff, the optimal marginal distribution function of salinity sequence and the optimal joint distribution function;

[0029] The simultaneous occurrence probability is transformed into a normal quantile to obtain a composite salt-drought index.

[0030] Optionally, after the step of calculating the composite salt-drought index according to the standardized runoff index, the standardized salinity index and the optimal joint distribution function, the method further comprises:

[0031] The standardized runoff index and the standardized salinity index are used to verify the applicability of the composite salt-drought index.

[0032] The present invention also provides a device for evaluating the composite salt-drought intensity in an estuary area, comprising:

[0033] Runoff data and salinity data collection module, used to collect runoff data and salinity data of the preset estuary area;

[0034] A runoff sequence optimal marginal distribution function calculation module, used to calculate the runoff sequence optimal marginal distribution function according to the runoff data;

[0035] A salinity sequence optimal marginal distribution function calculation module, used to calculate the salinity sequence optimal marginal distribution function according to the salinity data;

[0036] A standardized runoff index calculation module, used to calculate the standardized runoff index according to the optimal marginal distribution function of the runoff sequence;

[0037] A standardized salinity index calculation module, used to calculate the standardized salinity index according to the optimal marginal distribution function of the salinity sequence;

[0038] An optimal joint distribution function selection module is used to perform modeling based on the optimal marginal distribution function of the runoff sequence and the optimal marginal distribution function of the salinity sequence, and select the optimal joint distribution function;

[0039] The composite salty-drought index calculation module is used to calculate the composite salty-drought index according to the standardized runoff index, the standardized salinity index and the optimal joint distribution function; the composite salty-drought index is used to evaluate the composite salty-drought intensity in the estuary area.

[0040] The present invention also provides an electronic device, the device comprising a processor and a memory:

[0041] The memory is used to store program code and transmit the program code to the processor;

[0042] The processor is used to execute the method for assessing the composite salt-drought intensity in estuary areas as described in any one of the above items according to the instructions in the program code.

[0043] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store program codes, and the program codes are used to execute the method for assessing the composite salt-drought intensity in estuary areas as described in any one of the above items.

[0044] It can be seen from the above technical scheme that the present invention has the following advantages: the present invention provides a method for assessing the intensity of composite salty drought in an estuary area, comprising: collecting runoff data and salinity data of a preset estuary area; calculating the optimal marginal distribution function of the runoff sequence according to the runoff data; calculating the optimal marginal distribution function of the salinity sequence according to the salinity data; calculating the standardized runoff index according to the optimal marginal distribution function of the runoff sequence; calculating the standardized salinity index according to the optimal marginal distribution function of the salinity sequence; modeling based on the optimal marginal distribution function of the runoff sequence and the optimal marginal distribution function of the salinity sequence, and selecting the optimal joint distribution function; calculating the composite salty drought index based on the standardized runoff index, the standardized salinity index and the optimal joint distribution function; the composite salty drought index is used to assess the intensity of composite salty drought in the estuary area.

[0045] The present invention calculates the standardized runoff index, the standardized salinity index and the optimal joint distribution function of runoff and salinity by calculating the optimal marginal distribution function of the runoff sequence and the optimal distribution function of the salinity sequence, thereby calculating the composite salty drought index reflecting the intensity of the composite salty drought according to the standardized runoff index, the standardized salinity index and the optimal joint distribution function, thereby realizing sensitive and effective monitoring of the composite salty drought information in the estuary area. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0047] Figure 1 A flowchart of the steps of a method for assessing the intensity of compound salty drought in estuary areas provided by an embodiment of the present invention;

[0048] Figure 2 A probability distribution function diagram of runoff and salinity at estuaries A and B provided in an embodiment of the present invention;

[0049] Figure 3 QQ diagram of SDSI of estuary A and estuary B provided in an embodiment of the present invention;

[0050] Figure 4 A line graph of the composite salt-drought index sequence of the A estuary and the B estuary provided in the embodiment of the present invention;

[0051] Figure 5An index correlation analysis diagram of estuary A and estuary B provided in an embodiment of the present invention;

[0052] Figure 6 A scatter plot between the SRI and SSI of the B estuary provided by an embodiment of the present invention;

[0053] Figure 7 A structural block diagram of a device for assessing composite salt-drought intensity in estuary areas provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0054] The embodiments of the present invention provide a method, device, equipment and storage medium for evaluating the composite salt-drought intensity in an estuary area, which are used to solve the technical problem that the composite salt-drought intensity in an estuary area cannot be evaluated.

[0055] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] See also Figure 1 , Figure 1 A flowchart of the steps of a method for assessing the intensity of composite salty drought in estuary areas provided by an embodiment of the present invention.

[0057] The present invention provides a method for assessing the composite salt-drought intensity in an estuary area, which may specifically include the following steps:

[0058] Step 101, collecting runoff data and salinity data of a preset estuary area;

[0059] In an embodiment of the present invention, runoff data and salinity data of a preset estuary area may be collected to prepare for distributed fitting.

[0060] In one example, step 101 may include the following sub-steps:

[0061] S11, collect initial runoff data and initial salinity data of the preset estuary area;

[0062] S12, converting the initial runoff data into monthly average runoff as runoff data;

[0063] S13, converting the initial salinity data into monthly average salinity as salinity data.

[0064] In a specific implementation, the collected initial runoff data and initial salinity data can be converted into monthly average runoff and monthly average salinity to serve as runoff data and salinity data for subsequent calculations.

[0065] Step 102, calculating the optimal marginal distribution function of the runoff sequence according to the runoff data;

[0066] In the embodiment of the present invention, after the runoff data is acquired, the optimal marginal distribution function of the runoff sequence can be calculated.

[0067] Marginal distribution, also known as edge distribution, refers to the probability distribution of only some of the variables in a multidimensional random variable in probability theory and statistics.

[0068] In the embodiment of the present invention, step 102 may include the following sub-steps:

[0069] S21, fitting the runoff data using a plurality of preset distribution functions to obtain a plurality of fitting distribution functions;

[0070] S22, calculating the statistical value of each fitted distribution function using a preset test method;

[0071] S23, determining the fitting distribution function with the smallest statistical value as the optimal marginal distribution function of the runoff sequence.

[0072] In the specific implementation, multiple distribution functions, such as Lognorm, Logistic, Normal, Gamma, Weibull, etc., can be selected to fit the runoff data, and then the optimal marginal distribution function is selected based on a preset test method, such as the KS test method. Specifically, when the statistical value obtained by the KS test method is the smallest, the fitted distribution function is the optimal marginal distribution function of the runoff series.

[0073] KS test: a non-parametric test method used to test whether a sample data set conforms to a known theoretical distribution. The basic principle is to compare the maximum difference between the observed data distribution (empirical distribution function) and the cumulative distribution function (CDF) of the theoretical distribution (such as normal distribution or other specific distribution). The KS test method determines whether the sample data comes from the theoretical distribution by calculating the maximum difference between the cumulative distribution function of the sample data and the theoretical distribution function (i.e., the KS statistic). If the KS statistic is large, it indicates that the two CDFs are significantly different, indicating that the two samples may come from different distributions.

[0074] Step 103, calculating the optimal marginal distribution function of the salinity sequence according to the salinity data;

[0075] In the embodiment of the present invention, the optimal marginal distribution function of the salinity sequence may be calculated by referring to the process of calculating the optimal marginal distribution function of the runoff sequence.

[0076] Step 104, calculating a standardized runoff index according to the optimal marginal distribution function of the runoff sequence;

[0077] The standardized runoff index (SRI) is often used to calculate the hydrological drought index. Due to its advantages such as simple calculation, easy acquisition of required data and multi-time scale characteristics, it is widely used in the study of hydrological drought. In one example, step 104 may include the following sub-steps:

[0078] S41, calculate the marginal probability of the optimal marginal distribution function of the runoff series;

[0079] S42, marginal probabilities are converted into standardized runoff indices using normal distribution.

[0080] In the specific implementation, let the runoff volume within a period of time be satisfy Probability density function of a distribution and the probability distribution function for:

[0081]

[0082]

[0083]

[0084] in, is the Gamma function, are the shape parameter and the scale parameter, are greater than 0, It can be calculated by the maximum likelihood method. In the present invention, Replaced by the optimal marginal distribution function.

[0085] Finally, the SRI can be obtained by standardizing the cumulative probability:

[0086]

[0087]

[0088] when hour, ;when hour, ,in , , , , , .

[0089] Step 105, calculating a standardized salinity index according to the optimal marginal distribution function of the salinity sequence;

[0090] In the embodiment of the present invention, the standardized salinity index SSI can be calculated based on the principle of SRI, and a high SSI value represents a high salinity condition. In order to better compare the changing patterns of SRI and SSI, the standardized salinity index and the standardized runoff index SRI are unified, and the SSI value is multiplied by -1, and a negative value represents a drought condition and a high salinity condition, and a positive value represents a wet condition and a freshwater condition.

[0091] Step 106, modeling is performed based on the optimal marginal distribution function of the runoff sequence and the optimal marginal distribution function of the salinity sequence, and an optimal joint distribution function is selected;

[0092] In one example, step 106 may include the following sub-steps:

[0093] S61, modeling the optimal marginal distribution function of the runoff series and the optimal marginal distribution function of the salinity series through several joint distribution functions;

[0094] S62, evaluate the goodness of fit of several joint distribution functions;

[0095] S63, determining the joint distribution function with the best goodness of fit as the optimal joint distribution function.

[0096] In a specific implementation, the optimal marginal distribution function of the runoff sequence and the optimal marginal distribution function of the salinity sequence can be selected.

[0097] Then, the goodness of fit of multiple joint distribution functions is evaluated by AIC, BIC and Log-likelihood (LOGLIK). The smaller the AIC and BIC, and the larger the LOGLIK, the better the goodness of fit. The calculation method is as follows:

[0098] The formula for LOGLIK is as follows:

[0099]

[0100]

[0101] The formula is as follows:

[0102]

[0103] Where n is the sample size, m is the number of Copula parameter estimates, is the calculated value of the Copula function, For experience value.

[0104] The formula is as follows:

[0105]

[0106] Step 107, calculating the composite salt-drought index according to the standardized runoff index, the standardized salinity index and the optimal joint distribution function; the composite salt-drought index is used to evaluate the composite salt-drought intensity in the estuary area.

[0107] The composite event index can reflect the abnormality or severity of the composite event and is the basis for composite disaster risk assessment. A composite salty drought event refers to an event in which insufficient runoff (low SRI) and high salinity (low SSI) occur simultaneously in the same period. The embodiment of the present invention uses the composite salty drought index SDSI to study composite salty drought events.

[0108] In one example, step 107 may include the following sub-steps:

[0109] S71, calculate the probability of simultaneous occurrence of drought and saltwater tide based on the optimal marginal distribution function of runoff, the optimal marginal distribution function of salinity sequence and the optimal joint distribution function;

[0110] S72, perform normal quantile transformation on the probability of simultaneous occurrence to obtain the composite salt-drought index.

[0111] In the specific implementation, assuming that SRI and SSI are two random variables X and Y respectively, the probability of the simultaneous occurrence of drought and saltwater tide is It can be written as:

[0112]

[0113] in yes Copula function.

[0114] right Perform normal quantile transformation (NQT) to obtain SDSI:

[0115]

[0116] in is the standard normal distribution, is the marginal cumulative distribution.

[0117] Furthermore, in the embodiment of the present invention, after the step of calculating the composite salt-drought index according to the standardized runoff index, the standardized salinity index and the optimal joint distribution function, the method further includes:

[0118] The standardized runoff index and standardized salinity index were used to verify the applicability of the composite salt-drought index.

[0119] In specific implementation, the applicability of SDSI can be illustrated by comparing the change trends of SRI and SSI, using the percentile method, typical historical events, and correlation analysis.

[0120] The present invention calculates the standardized runoff index, the standardized salinity index and the optimal joint distribution function of runoff and salinity by calculating the optimal marginal distribution function of the runoff sequence and the optimal distribution function of the salinity sequence, thereby calculating the composite salty drought index reflecting the intensity of the composite salty drought according to the standardized runoff index, the standardized salinity index and the optimal joint distribution function, thereby realizing sensitive and effective monitoring of the composite salty drought information in the estuary area.

[0121] For ease of understanding, the embodiments of the present invention are described below by using specific examples:

[0122] 1) Collect runoff and salinity data at the mouth of River A and the mouth of River B in the United States;

[0123] 2) Calculate the optimal marginal distribution functions of runoff and salinity series respectively; In order to obtain suitable marginal distribution functions, five types of marginal distribution functions are selected to fit the monthly average runoff and salinity data of estuary A and estuary B, and the KS test index is used to test the goodness of fit of the five marginal distribution functions.

[0124] The results are shown in Table 1. The smaller the value of the KS test index, the better the goodness of fit. The best distribution for runoff fitting is Lognorm. The distribution with the smallest KS index value for salinity fitting is Weibull. The KS test measures the goodness of fit between the empirical distribution and the theoretical distribution. In order to more intuitively display the optimal distribution function, Figure 2 The PDF, QQ, CDF and PP plots show that the Normal distribution has a poor fitting effect on runoff and salinity, while the Lognorm distribution has the best fitting effect on runoff. The results show that these distribution functions fit the runoff and salinity data of the two estuaries well, and are used to calculate SRI and SSI based on the optimal distribution function.

[0125] Table 1 Goodness of fit of marginal distribution functions of monthly runoff and salinity (bold indicates minimum value).

[0126]

[0127] 3) Based on the optimization of marginal distribution functions of runoff and salinity data, five common Copula functions were selected to construct a composite salt-drought joint distribution model for estuaries. The results are shown in Table 2. AIC, BIC and LOGLIK were selected to optimize the five candidate Copulas. The Copula function with the smallest AIC and BIC and the largest LOGLIK had the best goodness of fit. In general, the five Copula functions vary greatly in different estuaries. For example, the optimal joint function based on the optimal runoff and salinity marginal distribution function in estuary B is Gaussian copula, while the optimal joint function of runoff and salinity in estuary A is Clayton copula. The optimal Copula function based on runoff and saltwater upstream in the estuary area and the SDSI index were constructed. Figure 3 The relationship between the SDSI and normal distribution in each estuary area is depicted, in which the scattered points are almost scattered on the 45° empirical curve, indicating that the SDSI can be well fitted by the normal distribution.

[0128] Table 2 Goodness of fit of five alternative Copula functions

[0129]

[0130] 4) Applicability assessment of the composite salty drought intensity assessment method. In recent decades, various composite extreme events have occurred in different regions around the world. In order to assess the possibility and dependence of composite salty drought events, the present invention uses the likelihood multiplier method (PMF) for assessment. Similar to the percentile method, the present invention uses the 30th percentile to define drought events and the 70th percentile to define saltwater upwelling events, and the independent joint probability is 0.09.

[0131] Figure 4 (a) and (c) show the PMF of compound salty drought events at estuaries A and B. The results show that higher PMF values ​​were observed at estuaries A and B, which were 2.06 and 2.83, respectively, indicating that compound salty drought events occurred frequently in these estuaries. To better visualize the trends of SRI, SSI, and SDSI values, Figure 4 Taking the A and B estuaries as examples, the SRI, SSI and SDSI values ​​were compared (where 1 indicates a compound event and 0 indicates no compound event). A low and negative SRI indicates drought, a low and negative SSI indicates a more serious saltwater tide, and similarly, a low and negative SDSI indicates a serious saltwater-drought compound situation. Overall, the trends of the three indexes are basically the same. Increases and decreases in the SRI and SSI values ​​will lead to corresponding increases and decreases in the SDSI value, indicating that the SDSI can fully reflect the basic properties of drought and saltwater tide.

[0132] Figure 4The black rectangles in (a) and (c) clearly show two compound salt drought events at the A estuary in January 2005 and the B estuary in June 2002. The SDSI values ​​of these two periods are -1.37 and -1.86, respectively, indicating that the compound extreme drought and salt tide upstream conditions are serious. Figure 4 (b) and (d) show that the time points when the compound salt-drought events determined by the percentile method and the SDSI are more severe are consistent. Although the percentile method can determine the occurrence of compound events, it cannot evaluate the severity of compound events, while the proposed compound index can intuitively show it. Figure 4 The green rectangle in (a) shows that with -1 as the threshold for drought occurrence, neither SRI nor SSI has captured the occurrence of drought, but the composite index SDSI has detected the occurrence of composite events, which shows that the SDSI index combines the two types of information, runoff and saltwater upstream, and can sensitively and effectively capture composite events. Figure 4 In (a) and (c), the red line representing SDSI is generally located below the blue line representing SRI and the yellow line representing SSI. The wet state of SDSI is lower than SRI, and the dry state of SDSI is higher than SRI, which reflects that the SDSI has numerically "exacerbated" the hydrological drought events aggravated by the upstream saltwater tide.

[0133] Since the SDSI is constructed from runoff and salinity data, Figure 5 The correlation analysis of the three indices is depicted. The correlation between SRI and SSI in estuary A is 0.49, while the correlations between SDSI and the single indices (SRI and SSI) are 0.76 and 0.87, respectively. The correlation between SRI and SSI in estuary B is 0.88, while the correlations between SDSI and the single indices (SRI and SSI) are 0.96 and 0.93, respectively. The correlation between the two single drought indices is significantly smaller than the correlation between the constructed composite index SDSI and the single index. This indicates that the hydrological drought index (SRI) cannot reflect the saltwater upwelling well to a certain extent. Similarly, the saltwater upwelling (SSI) cannot assess the hydrological drought well. However, the constructed composite index (SDSI) is relatively more able to reflect the characteristics of multiple events, further demonstrating that the composite index is very sensitive to capturing composite events.

[0134] In order to further illustrate the characteristics of SDSI, the scatter plot of SRI and SSI of estuary B is further selected ( Figure 6 ), where the size of the bubble is represented by the absolute value of SDSI. In general, when the negative value of SRI and the negative value of SSI are both smaller, the corresponding bubble of SDSI is larger and the negative value is smaller, indicating a severe salty-drought compound event. For example, the points in the third quadrant representing the compound salty-drought events of 2002 and 2012 correspond to abnormally low and negative SRI and SSI values, indicating the probability The lower the SDSI value, the smaller the SDSI value. In addition, the SDSI also shows that in the second quadrant, when independent events do not meet extreme conditions, the combination of hydrological drought and saltwater upwelling can still lead to compound events, which is consistent with Figure 4 The green rectangle in (a) is consistent in description, highlighting the sensitivity of SDSI to compound events. In addition, there are few or almost no points in the fourth quadrant, indicating that the probability of severe saltwater inundation is very small without drought. The above results show that SDSI provides a useful measure of the severity of compound extreme drought and saltwater inundation, and provides strong support for decision makers to monitor and prevent compound saltwater drought disasters.

[0135] See also Figure 7 , Figure 7 A structural block diagram of a device for assessing composite salt-drought intensity in estuary areas provided by an embodiment of the present invention.

[0136] The embodiment of the present invention provides a device for evaluating the composite salt-drought intensity in an estuary area, comprising:

[0137] The runoff data and salinity data collection module 701 is used to collect the runoff data and salinity data of the preset estuary area;

[0138] The optimal marginal distribution function calculation module 702 of the runoff sequence is used to calculate the optimal marginal distribution function of the runoff sequence according to the runoff data;

[0139] The optimal marginal distribution function calculation module 703 of the salinity sequence is used to calculate the optimal marginal distribution function of the salinity sequence according to the salinity data;

[0140] A standardized runoff index calculation module 704 is used to calculate the standardized runoff index according to the optimal marginal distribution function of the runoff sequence;

[0141] A standardized salinity index calculation module 705 is used to calculate the standardized salinity index according to the optimal marginal distribution function of the salinity sequence;

[0142] The optimal joint distribution function selection module 706 is used to perform modeling based on the optimal marginal distribution function of the runoff sequence and the optimal marginal distribution function of the salinity sequence, and select the optimal joint distribution function;

[0143] The composite salty-drought index calculation module 707 is used to calculate the composite salty-drought index according to the standardized runoff index, the standardized salinity index and the optimal joint distribution function; the composite salty-drought index is used to evaluate the composite salty-drought intensity in the estuary area.

[0144] In the embodiment of the present invention, the runoff data and salinity data collection module 701 includes:

[0145] The initial runoff data and initial salinity data collection submodule is used to collect the initial runoff data and initial salinity data of the preset estuary area;

[0146] The runoff data generation submodule is used to convert the initial runoff data into the monthly average runoff as the runoff data;

[0147] The salinity data generation submodule is used to convert the initial salinity data into the monthly average salinity as salinity data.

[0148] In the embodiment of the present invention, the runoff sequence optimal marginal distribution function calculation module 702 includes:

[0149] A fitting submodule, used for fitting the runoff data using a plurality of preset distribution functions to obtain a plurality of fitting distribution functions;

[0150] A statistical value calculation submodule is used to calculate the statistical value of each fitted distribution function using a preset test method;

[0151] The submodule for determining the optimal marginal distribution function of the runoff sequence is used to determine the fitting distribution function with the smallest statistical value as the optimal marginal distribution function of the runoff sequence.

[0152] In the embodiment of the present invention, the standardized runoff index calculation module 704 includes:

[0153] The marginal probability calculation submodule is used to calculate the marginal probability of the optimal marginal distribution function of the runoff sequence;

[0154] The standardized runoff index conversion submodule is used to convert marginal probability into a standardized runoff index through normal distribution.

[0155] In the embodiment of the present invention, the optimal joint distribution function selection module 706 includes:

[0156] The joint distribution function modeling submodule is used to generate several joint distribution function modeling by using the optimal marginal distribution function of the runoff sequence and the optimal marginal distribution function of the salinity sequence;

[0157] The goodness of fit evaluation submodule is used to evaluate the goodness of fit of each joint distribution function;

[0158] The optimal joint distribution function selection submodule is used to determine the joint distribution function with the best goodness of fit as the optimal joint distribution function.

[0159] In the embodiment of the present invention, the composite salt-drought index calculation module 707 includes:

[0160] The simultaneous occurrence probability calculation submodule is used to calculate the simultaneous occurrence probability of drought and saltwater tide based on the optimal marginal distribution function of runoff, the optimal marginal distribution function of salinity sequence and the optimal joint distribution function;

[0161] The composite salty-drought index conversion submodule is used to perform normal quantile conversion on the probability of simultaneous occurrence to obtain the composite salty-drought index.

[0162] In an embodiment of the present invention, it also includes:

[0163] The applicability verification module is used to verify the applicability of the composite salt-drought index using the standardized runoff index and the standardized salinity index.

[0164] An embodiment of the present invention further provides an electronic device, the device comprising a processor and a memory:

[0165] The memory is used to store the program code and transmit the program code to the processor;

[0166] The processor is used to execute the method for assessing the composite salt-drought intensity in estuary areas according to the instructions in the program code.

[0167] The embodiment of the present invention further provides a computer-readable storage medium, which is used to store program codes, and the program codes are used to execute the method for assessing the composite salt-drought intensity in estuary areas according to the embodiment of the present invention.

[0168] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0169] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0170] It will be appreciated by those skilled in the art that the embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the embodiments of the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0171] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0172] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0173] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0174] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0175] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0176] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for assessing the composite salt-drought intensity in estuary areas, characterized in that: include: Collect runoff and salinity data for pre-planned estuary areas; Calculating the optimal marginal distribution function of the runoff sequence according to the runoff data; Calculating the optimal marginal distribution function of the salinity sequence according to the salinity data; Calculating a standardized runoff index according to the optimal marginal distribution function of the runoff sequence; Calculating a standardized salinity index according to the optimal marginal distribution function of the salinity sequence; Modeling is performed according to the optimal marginal distribution function of the runoff sequence and the optimal marginal distribution function of the salinity sequence, and an optimal joint distribution function is selected; Calculate a composite salty-drought index according to the standardized runoff index, the standardized salinity index and the optimal joint distribution function; the composite salty-drought index is used to evaluate the composite salty-drought intensity in estuary areas; Wherein, the step of calculating the composite salt-drought index according to the standardized runoff index, the standardized salinity index and the optimal joint distribution function comprises: Calculating the probability of simultaneous occurrence of drought and saltwater tide according to the optimal marginal distribution function of runoff, the optimal marginal distribution function of salinity sequence and the optimal joint distribution function; The simultaneous occurrence probability is transformed into a normal quantile to obtain a composite salt-drought index.

2. The method according to claim 1, characterized in that The step of collecting runoff data and salinity data of a preset estuary area comprises: Collect initial runoff data and initial salinity data for the planned estuary area; Converting the initial runoff data into monthly average runoff as runoff data; The initial salinity data are converted into monthly average salinity as salinity data.

3. The method according to claim 1, characterized in that The step of calculating the optimal marginal distribution function of the runoff sequence according to the runoff data comprises: Using a plurality of preset distribution functions to fit the runoff data to obtain a plurality of fitting distribution functions; The statistical value of each fitted distribution function was calculated using a preset test method; The fitted distribution function with the smallest statistical value is determined as the optimal marginal distribution function of the runoff series.

4. The method according to claim 1, characterized in that: The step of calculating the standardized runoff index according to the optimal marginal distribution function of the runoff sequence comprises: Calculating the marginal probability of the optimal marginal distribution function of the runoff sequence; The marginal probabilities were converted into normalized runoff indices by normal distribution.

5. The method according to claim 1, characterized in that The step of modeling according to the optimal marginal distribution function of the runoff sequence and the optimal marginal distribution function of the salinity sequence and selecting the optimal joint distribution function comprises: Using several joint distribution functions to model the optimal marginal distribution function of the runoff sequence and the optimal marginal distribution function of the salinity sequence; Evaluating the goodness of fit of each of the joint distribution functions; The joint distribution function with the best goodness of fit is determined as the optimal joint distribution function.

6. The method according to any one of claims 1 to 5, characterized in that: After the step of calculating the composite salt-drought index according to the standardized runoff index, the standardized salinity index and the optimal joint distribution function, the method further includes: The standardized runoff index and the standardized salinity index are used to verify the applicability of the composite salt-drought index.

7. A device for assessing the composite salt-drought intensity in estuary areas, characterized in that: include: Runoff data and salinity data collection module, used to collect runoff data and salinity data of the preset estuary area; A runoff sequence optimal marginal distribution function calculation module, used to calculate the runoff sequence optimal marginal distribution function according to the runoff data; A salinity sequence optimal marginal distribution function calculation module, used to calculate the salinity sequence optimal marginal distribution function according to the salinity data; A standardized runoff index calculation module, used to calculate the standardized runoff index according to the optimal marginal distribution function of the runoff sequence; A standardized salinity index calculation module, used to calculate the standardized salinity index according to the optimal marginal distribution function of the salinity sequence; An optimal joint distribution function selection module is used to perform modeling based on the optimal marginal distribution function of the runoff sequence and the optimal marginal distribution function of the salinity sequence, and select the optimal joint distribution function; A composite salty-drought index calculation module, used to calculate the composite salty-drought index according to the standardized runoff index, the standardized salinity index and the optimal joint distribution function; The composite salt-drought index is used to assess the composite salt-drought intensity in estuary areas; Among them, the composite salt-drought index calculation module includes: The simultaneous occurrence probability calculation submodule is used to calculate the simultaneous occurrence probability of drought and saltwater tide based on the optimal marginal distribution function of runoff, the optimal marginal distribution function of salinity sequence and the optimal joint distribution function; The composite salty-drought index conversion submodule is used to perform normal quantile conversion on the probability of simultaneous occurrence to obtain the composite salty-drought index.

8. An electronic device, characterized in that: The device comprises a processor and a memory: The memory is used to store program code and transmit the program code to the processor; The processor is used to execute the method for assessing the composite salt-drought intensity in estuary areas according to any one of claims 1 to 6 according to the instructions in the program code.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store program codes, and the program codes are used to execute the method for assessing the composite salt-drought intensity in estuary areas according to any one of claims 1-6.

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