50 results about "Groundwater storage" patented technology

The invention discloses a gravity satellite groundwater storage variable vertical signal separation method based on a physical model, and the method comprises the steps: S1, building a physical response model of ground surface deformation and gravity change and groundwater storage variables, and enabling the physical response model to comprise a ground surface deformation response model and a gravity change response model; the method specifically comprises the following steps: step S2, constructing a gravity satellite and InSAR data joint inversion framework, and establishing an observation equation set; s3, regularization constraint conditions are introduced, and a weighted least square method is adopted for solving; and S4, carrying out groundwater reserve vertical separation and verification based on a mass conservation principle. The method overcomes the defect that an existing method depends on dense well observation data, fine monitoring of groundwater storage variables is achieved through physical model constraints, and the method can be widely applied to regional groundwater resource monitoring and management.

The invention relates to the technical field of satellite hydrological data processing, and particularly discloses a GRACE data super-resolution network space downscaling method fusing geographic information and environmental variables, which comprises the following steps: S1, acquiring original resolution GRACE data and original GLDAS data of a research area, and preprocessing the data; s2, dividing the data obtained by preprocessing in the step S1 into a training set and a test set, and training the GRACE data space downscaling model by using the training set to obtain a trained discriminator and a trained generator; and S3, inputting the GRACE low-resolution data in the test set and the high-resolution environment variable at the moment corresponding to the data into the generator trained in the step S2, and finally obtaining a downscaled high-resolution GRACE image. The method not only can be used for dynamic monitoring of regional scale underground water reserves and flood risk assessment, but also can be expanded and applied to scenes such as agricultural drought monitoring and ecological hydrological process simulation.

The invention relates to the technical field of hydrological monitoring, and discloses a regional groundwater reserve change dynamic monitoring method based on gravity satellite time series data analysis. According to the method, the multi-source data scale effect and observation noise are effectively eliminated, the physical reliability and resolution of groundwater signal extraction are improved, and the recognition precision and early warning perspectiveness of the abnormal loss trend are enhanced. A full-chain monitoring closed loop of multi-source satellite observation, high-precision physical inversion and dynamic statistical benchmark is constructed, multi-dimensional environment data is aligned, a component separation strategy based on multi-element physical mechanism constraint is established based on a water balance principle, and anomaly diagnosis is performed in combination with a self-adaptively updated long-time-sequence historical database.

The invention discloses an intelligent groundwater storage variable prediction system based on multi-source data fusion and parameter optimization, and relates to the technical field of groundwater storage change prediction, and the system comprises a data collection module, a hydrological sensor connected with the Internet of Things, a satellite remote sensing data interface and a meteorological data interface. According to the intelligent groundwater storage variable prediction system based on multi-source data fusion and parameter optimization, the problem of prediction time lag caused by data updating lag, data spatial-temporal scale inconsistency and parameter stiffness of a groundwater storage change evaluation system is solved by constructing a double-circulation collaborative architecture of a real-time assimilation ring and a parameter evolution ring. High-frequency assimilation is used for fusing multi-source real-time data, and it is ensured that model input is synchronous with a real environment state; the prediction system continuously tracks the transient process of an underground water system, and the timeliness and reliability of underground water storage volume change prediction under the scenes of extreme rainfall, extreme drought, high-intensity mining and the like are effectively improved.

The invention discloses an arid region groundwater reserve estimation method and system based on multi-source remote sensing data, and relates to the technical field of groundwater monitoring, and the method comprises the steps: collecting land water reserve data and remote sensing image data of a target arid region, obtaining a land water reserve change sequence according to the land water reserve data, carrying out the region weighting of the target arid region, and obtaining a target arid region groundwater reserve change sequence; obtaining a land water reserve change sequence of the target arid region; based on the remote sensing image data of the target arid region, using a digital elevation model to obtain a surface water reserve change sequence of the target arid region, using a land surface process model to obtain a soil water reserve change sequence of the target arid region, and establishing an underground water reserve model of the target arid region; and performing error analysis on an output result of the groundwater reserve model by using a Monte Carlo simulation method. According to the method, through collaborative inversion of multi-source remote sensing data and integration of the groundwater reserve models, accurate quantification of spatial-temporal dynamic of the groundwater reserves in the arid region is realized.

The invention discloses a physical constraint fused deep learning gravity satellite groundwater vertical signal separation method, which comprises the following steps: S1, acquiring and preprocessing basic data: calculating to obtain total groundwater reserve abnormities needing vertical separation, unifying all data to a preset temporal-spatial resolution, and removing abnormal values; s2, constructing a deep learning model, which is configured to receive the preprocessed time sequence including the total groundwater reserve abnormality and meteorological data as input, and output shallow groundwater reserve abnormality and deep groundwater reserve abnormality at corresponding time; s3, the deep learning model is trained, optimization is carried out by adopting a composite loss function, and the composite loss function comprises a data-driven loss item Ldata and a physical constraint loss item Lwater based on water balance; and S4, after training is completed, inputting a total groundwater reserve abnormal signal into the deep learning model for processing, and outputting a separated shallow groundwater reserve abnormal time sequence and a separated deep groundwater reserve abnormal time sequence.

The invention discloses a method for estimating the burial depth distribution of regional underground water based on Bayesian deep learning, and the method comprises the steps: employing discrete observation well position data, and combining the multi-source data, such as rainfall, evapotranspiration, temperature, gradient, distance to a nearest surface water body, soil type, land utilization type, and underground water reserve, as input factors; and establishing a nonlinear mapping relation between the underground water burial depth and the input factors through a Bayesian deep learning model. According to the method, the model is trained and verified by using the measured data at the observation points, and then the regional groundwater burial depth distribution is estimated based on the input factor data of the research area, so that the problem of insufficient coverage of a traditional groundwater monitoring network can be effectively solved, and the regional groundwater burial depth distribution characteristics can be described with relatively high spatial resolution; and scientific support is provided for sustainable utilization and ecological protection of regional underground water resources. The method has universality and is suitable for underground water burial depth prediction in different areas and under various data conditions.

The invention provides a basin scale groundwater reserve GWS long-term reconstruction method and system. The method comprises the steps that long-term meteorological and hydrological data in 1960-2023 and short-term land total water storage TWS after 2002 are acquired, fused and calibrated; according to a watershed scale water balance equation deltaTWS = deltaSWS + deltaSMS + deltaGWS, a short-term groundwater GWS sequence is obtained through calculation; using a short-term groundwater GWS sequence and a part after 2002 in the fused long-term meteorological and hydrological data as target data and driving data, and training a random forest RF sub-model of an RF-KF coupling model; inputting the fused long-term meteorological hydrological data into the trained random forest RF sub-model to obtain a groundwater reserve GWS long-term prediction result; and replacing the output of the prediction module of the Kalman filtering KF sub-model with the groundwater reserve GWS long-term prediction result, simulating time dynamic and correcting long-term prediction accumulation errors by using an updating module of the Kalman filtering KF sub-model, and obtaining a final groundwater reserve GWS long-term reconstruction result. According to the invention, GWS long-term reconstruction can be carried out.

This invention provides a groundwater safety monitoring method and system based on GRACE satellite data, belonging to the field of groundwater safety monitoring technology. The method includes: collecting multi-source data of a target area; separating non-groundwater signals from the multi-source data to obtain anomaly sequences of groundwater storage in the target area; calculating the difference between the anomaly sequence of groundwater storage in the target area and the natural baseline groundwater storage change sequence to determine the annual rate of change of groundwater storage caused by human activities in the target area; and conducting a two-dimensional safety risk early warning based on the determined annual rate of change of groundwater storage caused by human activities, combined with the dynamic shallow groundwater depth simulated by the SPHY model. This invention achieves multi-angle and multi-level comprehensive identification and early warning of regional groundwater safety risks, significantly improving the scientific nature and practical application value of the monitoring method.

The invention relates to the technical field of groundwater refilling, in particular to a groundwater refilling dynamic balance intelligent control device, which comprises a data acquisition module for collecting feature data of groundwater in a target area through i observation wells in the target area, analyzing the feature data of the groundwater in the target area, and calculating the dynamic balance of the groundwater in the target area; the underground water level of the target area at the future P moment is predicted, the underground water loss rate of the target area at the future P moment is obtained according to the underground water level of the target area at the future P moment, and then the underground water storage capacity coefficient of the target area is calculated by obtaining the thickness, area and porosity of the aquifer of the target area in combination with the permeability coefficient. Inputting the obtained groundwater loss rate, the groundwater storage capacity coefficient and the groundwater level of the target area acquired in real time into the trained machine learning model to predict groundwater supplement amount; the control precision of the groundwater supplement amount is guaranteed, and dynamic balance of groundwater is achieved.

The invention belongs to the technical field of groundwater reserve prediction, and particularly relates to a physical logic driven groundwater reserve intelligent prediction method and system. Comprising the following steps: performing complementation and physical verification on multi-source heterogeneous observation data related to groundwater reserves in a target area to obtain a physical verification complete data set conforming to physical logic; performing space-time decoupling causal contribution analysis on the physical verification complete data set to generate a causal contribution matrix; according to the causal contribution matrix, constructing and training a physical constraint emergence type space-time prediction model; applying a physical anchoring adversarial migration strategy to adapt the trained emergence type prediction model to the target new region to obtain a region adaptive prediction model; and inputting the future scene conditions into the regional adaptation prediction model for simulation, and generating a groundwater reserve prediction result. According to the method, intelligent prediction with high precision, high robustness and physical interpretability on groundwater reserves can be realized, and scientific decision support is provided for water resource management.

The present application belongs to the technical field of hydrology, and particularly relates to a method for improving spatial resolution of groundwater storage based on settlement characteristic weighted fusion. The technical scheme of the present application is based on extraction of settlement characteristics and derivation of weight algorithm, and the new settlement characteristic weighted fusion method fully considers the influence of two data characteristics of surface settlement and water level change on the change of groundwater storage. Through weighted fusion of the groundwater storage anomaly inverted by GRACE and InSAR data, a brand-new fusion image is obtained. The fusion result is more sensitive to the surface settlement characteristics, can better show the detail characteristics of water storage change, and can more accurately provide information services for the utilization of water resources.

Embodiments of a method and system for inversion of high-resolution aquifer storage coefficient based on gravity satellite data are disclosed. The method comprises: acquiring gravity satellite data, soil moisture storage data, surface water storage data and other non-groundwater component data, based on a preset region. The method also comprises: obtaining monthly time series of terrestrial water storage anomalies, by inversing the gravity satellite data; obtaining monthly time series of soil moisture storage anomalies, surface water storage anomalies, and other non-groundwater component anomalies; obtaining monthly time series of groundwater storage anomalies; and obtaining monthly time series of groundwater level anomalies in different aquifers. The method yet comprises: obtaining random sample values of storage coefficient by a stochastic simulation; obtaining correlation coefficient and Nash-Sutcliffe efficiency coefficient between random value of groundwater storage trend after a forward modeling and groundwater storage trend in the gravity satellite time-variable signal; and obtaining an inversion result.

The application discloses a gravity satellite underground water storage variable vertical signal separation method based on a physical model, and comprises the following steps: S1, constructing a physical response model of surface deformation and gravity change and underground water storage variable, wherein the physical response model comprises a surface deformation response model and a gravity change response model; S2, constructing a joint inversion framework of a gravity satellite and InSAR data, and establishing an observation equation set; S3, introducing a regularization constraint condition, and solving by using a weighted least square method; and S4, performing underground water storage vertical separation and verification based on the principle of mass conservation. The application overcomes the dependence of the prior art method on dense water well observation data, realizes fine monitoring of the underground water storage variable through the physical model constraint, and can be widely applied to regional underground water resource monitoring and management.

The application discloses a kind of coupling physical mechanism's monthly runoff prediction method and system, the method is inputed to monthly runoff prediction model with last month's hydro-meteorological data, and the runoff of current month's watershed export section is obtained;Monthly runoff prediction model includes surface runoff module, soil module, underground module and confluence module connected in turn, with elevation, previous precipitation, previous temperature, soil moisture, groundwater storage, inflow runoff and the like as forecast factor input monthly runoff prediction model, each module is with convolutional encoder as basic architecture, combined with encoder-decoder structure, the spatial correlation characteristics of elements such as precipitation-runoff are described.Further, water balance constraint is used as the penalty term of loss function, to increase the physical rule penalty term constraint except data fitting error for model, to improve the logical inference reliability of model.

Storage system for hydrogen in groundwater, comprising - electrolysis equipment (102) designed to electrolyze water using the energy of an energy source, having an oxygen-producing anode chamber (119) and a hydrogen-producing cathode chamber (118); - at least one ground probe containing — a side wall (201) closed at the bottom and defining an internal space filled with groundwater up to the groundwater level (203), the sidewall (201) is provided with a discharge opening below the groundwater level (203) near the groundwater level: and — a cartridge (202) having a closed end (214), an open end opposite the closed end (214) and a closed sidewall extending between the ends, where the ends and sidewall together form an internal space; — wherein the cartridge (202) is mounted below the groundwater level (203) in the interior of the side wall (201) in a position where the closed end (214) is positioned closer to the groundwater level (203) than the open end, and the side wall of the cartridge (202) is perforated (see 217) near the open end; — wherein the cartridge (202) is designed to retain tire hydrogen gas generated in the cathode chamber (118) during operation of tire electrolysis equipment (102) against the hydrostatic pressure of the groundwater.

This invention provides a geological-based water resource exploration reserve compensation algorithm and system, relating to the field of groundwater exploration technology. The compensation system is used to compensate for the water resource exploration reserves in the exploration area. The compensation system includes a stratigraphic database, a stratigraphic water storage acquisition module, a surface water acquisition module, a water storage testing module, and a reserve compensation processing module. The stratigraphic database stores the materials of different stratigraphic layers and the permeability of different materials. The stratigraphic water storage acquisition module is used to acquire stratigraphic data of groundwater storage in the exploration area. The surface water acquisition module is used to acquire the total surface water runoff in the exploration area at the current exploration time point. By comprehensively considering geological loss and water replenishment factors, this invention can improve the accuracy of groundwater exploration reserve calculation, thereby solving the problem of insufficient accuracy in existing groundwater exploration reserve calculations.

The present application relates to satellite hydrological data processing technical field, specifically disclose a kind of GRACE data super-resolution network spatial downscaling method of fusion geographic information and environmental variable, comprising: S1, the original resolution GRACE data and original GLDAS data of research area are obtained, and these data are preprocessed;S2, the data obtained in step S1 is divided into training set and test set, and the training set is used to train GRACE data spatial downscaling model, to obtain the discriminator and generator after training;S3, the low-resolution data of GRACE in test set and the high-resolution environmental variable corresponding to the data at the moment are input into the generator trained in step S2, and finally the high-resolution GRACE image after downscaling is obtained.The present application can be used not only for regional scale groundwater storage dynamic monitoring, flood risk assessment, but also can be applied to agricultural drought monitoring, ecological hydrological process simulation and other scenes.

The invention discloses a rapid assessment method for groundwater resource stock in a hilly area based on a gravity satellite and river base flow, and relates to the technical field of groundwater resource stock assessment, and the method comprises the steps: collecting GRACE data, WGHM hydrological model data, soil humidity data and runoff data, and filling and processing a data blank; calculating the base flow by adopting a digital filtering algorithm; according to the principle of water balance, non-groundwater signals are removed from the land water signals inverted by GRACE to obtain a groundwater stock change value; calculating underground water resource stock offset and absolute stock by constructing a linear correlation between an underground water stock change value and base flow; and the actually-measured groundwater level data is used for calculating the actually-measured groundwater storage amount, and the absolute groundwater resource storage amount obtained through evaluation is verified. Technical support can be provided for rapid assessment of groundwater resource stock in the hilly region, and the method has positive significance in protection and utilization of groundwater.

The present application belongs to the technical field of hydrological remote sensing, and relates to a groundwater recharge degree collaborative inversion method and system based on multi-source remote sensing and intelligent algorithm. The method comprises: collecting data and performing pretreatment to obtain a monthly groundwater storage change sequence, a monthly actual evapotranspiration, a surface runoff and a net drainage; reconstructing a vertical direction water balance equation on a monthly scale; calculating a monthly water surplus of each pixel; data downscaling; recharge event identification and estimation of the value of recharge amount; verification of the error of monthly precipitation, monthly actual evapotranspiration and monthly groundwater storage change sequence, and evaluation of the inversion result. The present application avoids a large number of hypothetical parameters of a black box model, does not need an expensive dense ground monitoring network, and has strong realization; realizes spatial explicit estimation of the recharge amount; can generate a monthly or seasonal groundwater recharge amount time sequence, reflects the dynamic change of the recharge process, is superior to a static annual average value provided by a traditional method, and has strong dynamic monitoring capability.

The invention discloses an underground water reserve abrupt change point detection method combining signal decomposition and a sequential test method, which comprises the following steps: firstly, acquiring a gravity satellite spherical harmonic coefficient product and GLDAS hydrological mode data of a to-be-detected area, and performing inversion to obtain underground water reserve abnormal data of the to-be-detected area; missing data interpolation and signal decomposition are carried out on groundwater reserve abnormal data obtained through inversion, and a non-linear trend term, a seasonal period term and a signal decomposition residual term which do not contain data missing are obtained; and finally, performing underground water reserve abrupt change point identification and detection by using the nonlinear trend term and the signal residual term of the signal decomposition. According to the method, residual terms of signal decomposition are utilized to construct the break variable test threshold value, robust mutation point recognition and detection are carried out, in the actual application process, the break variable test threshold value well eliminates false alarm points of mutation point recognition, and the accuracy and robustness of mutation point detection are guaranteed.

This invention belongs to the field of groundwater storage prediction technology, and particularly relates to a physical logic-driven intelligent prediction method and system for groundwater storage. It includes: completing and physically verifying multi-source heterogeneous observation data related to groundwater storage in a target area to obtain a physically verified complete dataset; performing spatiotemporally decoupled causal contribution analysis on the physically verified complete dataset to generate a causal contribution matrix; constructing and training a physically constrained emergent spatiotemporal prediction model based on the causal contribution matrix; applying a physical anchoring adversarial migration strategy to adapt the trained emergent prediction model to the new target area to obtain a regionally adapted prediction model; and inputting future scenario conditions into the regionally adapted prediction model for simulation to generate groundwater storage prediction results. This invention can achieve high-precision, highly robust, and physically interpretable intelligent prediction of groundwater storage, and provides scientific decision support for water resource management.

The application discloses a kind of groundwater reserves abnormal space-time evolution characteristic analysis method, it is related to groundwater monitoring technical field.The method includes: constructing GRACE data coordination processing flow, and fusing multiple-source hydrological climate factor generates training and target dataset.Constructs random forest and TabPFN parallel model, executes TWSA downscaling and optimization, and outputs two sets of high-resolution dataset.Subtract soil moisture and runoff, based on water balance extraction groundwater reserves anomaly, establishes three-level verification system to verify;The three-level verification system includes model accuracy, spatial consistency and measured water level comparison.The application can improve the inversion accuracy of groundwater reserves.

The invention relates to the field of satellite gravity detection and application, in particular to a method for inverting groundwater reserves by combining GNSS, GRACE and InSAR technologies, which comprises the following steps: acquiring GNSS vertical displacement data, GRACE equivalent water height data and InSAR vertical deformation rate data; the GNSS vertical displacement data, the GRACE equivalent water height data and the InSAR vertical deformation rate data are associated to the total water reserve change, and a joint inversion equation set is constructed; the uncertainty of GNSS, InSAR and GRACE observation trends is quantified, weight coefficients corresponding to GNSS vertical displacement data, GRACE equivalent water height data and InSAR vertical deformation rate data are determined, and observation data vectors are constructed; laplacian roughness constraint is introduced, a joint inversion equation set is solved through step-by-step iterative calculation according to a weighted least square method by observing data vectors, and high-resolution groundwater reserve changes are determined. By combining GNSS, GRACE and InSAR technologies, the limitation of a traditional single technology is overcome, advantage complementation of multi-source data is realized, and the accuracy of underground water reserve inversion is remarkably improved.

The present invention relates to a method for storing and utilizing water in a mining area covered with loess. The present invention mainly applies the following principles: First, the groundwater storage area is selected in the mining area, taking into account the groundwater impact radius of coal mining and the depth of coal mining floor damage, and the vertical and horizontal areas are determined. Second, in order to control the water quality, the actual soil and water loss in the loess area is taken into account, and a surface water storage system is adopted. Third, by using water replenishment drilling holes to limit the water storage height of the underground aquifer, the minimum distance between the selected groundwater storage area and the area where coal has been mined is determined. At the same time, the harm of the loess water level to the surface ecology and the safety issues of coal mines are taken into consideration. Fourth, since the water levels before and after replenishment are functions of time, the amount of available water resources is determined based on the first observation data and the second observation data, so as to replenish groundwater by collecting surface water, effectively improve the amount of available water resources in the mining area, and do not affect the ecological environment and coal mine safety production.

This invention discloses a method for predicting and attributing the spatiotemporal variation of groundwater storage based on a Transformer-LSTM hybrid network. The method includes collecting and analyzing groundwater storage variation data and various potential factors influencing these variations in a target area; constructing a Transformer-LSTM hybrid deep learning model using high-dimensional driving factors as input and the spatiotemporal variation of groundwater storage as output; training and validating the Transformer-LSTM model; deeply interpreting the temporal evolution and spatial distribution characteristics of groundwater storage based on the prediction results of the Transformer-LSTM model; and quantifying the influence of potential driving factors on groundwater storage variation using the interpretable SHAP method to identify key driving elements. This method can effectively capture the strong spatiotemporal heterogeneity and complex nonlinear variation characteristics of groundwater storage at a large regional scale.

The present invention discloses a method for evaluating the applicability of groundwater reserve anomaly inversion products, comprising the following steps: Step S1: generating a regional groundwater reserve anomaly inversion product by inversion based on the GRACE / GRACE-FO total water reserve anomaly product and surface water reserve and soil water reserve anomaly products simulated by a hydrological model; calculating the cross-correlation coefficient, phase difference coefficient of variation, and amplitude ratio coefficient of variation between a pixel-scale measured water level time series and a groundwater reserve anomaly time series; and evaluating the applicability of the groundwater reserve anomaly inversion product from multiple perspectives, including trend, phase, and amplitude. The present invention comprehensively evaluates the applicability of the groundwater reserve anomaly inversion product using three evaluation indicators, namely the cross-correlation coefficient, phase difference coefficient of variation, and amplitude ratio coefficient of variation, to improve the accuracy of the evaluation result.

The application relates to a test device and a test method for studying the influence of extreme rainfall on a water diversion channel, which comprises a channel filling box, a channel model filled in the channel filling box, the channel model comprising two side channel slopes and a channel lining plate between the two side channel slopes, and a drainage body filled on one side of the channel model close to a first drainage hole; a rainfall simulation assembly simulating a channel rainfall scene; a channel water supply assembly simulating a channel water supply scene; a groundwater water supply assembly located on one side of the simulation box, the groundwater water supply assembly comprising a groundwater storage tank, water in the groundwater storage tank seeping into the channel model through a water permeable hole to simulate groundwater; and a sensor assembly buried in the channel model to collect channel bottom, channel slope pore water pressure and channel slope displacement. The application considers the influence of water, groundwater level and rainfall in the channel on the channel, and has important significance for further clarifying the channel slope disaster mechanism and disaster prevention under the extreme rainfall working condition.

To disclose a groundwater water level elevation measurement method, groundwater storage measurement system, and application.SOLUTION: According to a groundwater water level elevation measurement method in one aspect of the present invention, after boring at a measurement site, a permeable cylinder is placed therein so as to ensure that groundwater water enters the permeable cylinder, a water inlet of an aqueduct extends at or below a liquid level in the cylinder, a water outlet is led to the ground, a stable drainage flow rate is detected, and a water level elevation at the water inlet is measured and calculated according to a formula. A groundwater storage monitoring and measurement system according to one aspect of the present invention layouts a matrix of water level monitoring point matrix, measures and collects groundwater level elevations at all sites and related data, and constructs water storage feature data of a groundwater measurement space. The present invention is a new technological plan that makes it possible to measure a groundwater level elevation by using a groundwater flow rate, has high technological adaptability, and enables a direction of groundwater monitoring technological improvement to be changed.SELECTED DRAWING: Figure 2

The present application relates to the technical field of hydrology, and discloses a kind of high-cold frozen soil area hot melt lake pond's regulating function evaluation method, comprising: obtaining the multiple monitoring data of target permafrost region basin, after correction and uniform time processing, effective rainfall event and its event window division are carried out;In event window, calculate the change amount of soil storage, the change amount of groundwater storage, hot melt lake pond storage change amount;Calculate the normalized water storage efficiency index;Get hysteresis curve, peak time lag, hysteresis loop area, dynamic connectivity index, statistical connectivity index;According to hysteresis curve, judge the function mode of hot melt lake pond, divide the rainfall threshold of hot melt lake pond function conversion;Calculate comprehensive regulating index, carry out regulating capacity analysis, realize the regulating function evaluation of hot melt lake pond;The present application can not only finely identify the water storage, water supply and regulation behavior of hot melt lake pond under the event scale, but also accurately evaluate the dynamic hydrological function of hot melt lake pond.