A wetland surface water-groundwater conversion quantitative evaluation method based on a multivariate method coupling

Abstract

The application discloses a kind of wetland surface water-groundwater conversion quantitative evaluation method based on coupling of multivariate method, comprising the following steps: comprehensive monitoring and hydrodynamic qualitative analysis;Recharge source identification of hydrochemical tracing method;Surface water-groundwater conversion rate calculation and hydrogeological parameter inversion based on temperature tracing method;Regional scale numerical simulation and verification based on multivariate method constraint.The method constructs the comprehensive analysis framework of hydrodynamic analysis, hydrochemical tracing, temperature tracing and numerical simulation, organically combines high-precision tracing technology at point and regional numerical simulation technology, overcomes the limitation of single method through cross-validation and parameter inversion, so as to realize the high-precision, high-resolution quantitative evaluation of the temporal and spatial dynamic characteristics of wetland surface water and groundwater conversion, and provide decision basis for scientific management of wetland water resources.

Description

Technical Field

[0001] This invention relates to the fields of hydrogeology and ecohydrology, and in particular to a quantitative assessment method for wetland surface water-groundwater conversion based on multi-method coupling. Background Technology

[0002] The interaction between surface water and groundwater is a crucial link in the water cycle, profoundly impacting water resource management and ecosystem protection. Particularly in wetland ecosystems, the conversion relationship between the two directly affects wetland hydrological processes, water balance, water quality evolution, and the health and stability of the ecosystem. Baiyangdian Wetland, the core area of ​​Xiong'an New Area in Hebei Province and the largest freshwater wetland in North China, plays an irreplaceable role in water conservation and maintaining regional ecological security. However, affected by both climate change and human activities, Baiyangdian has historically experienced multiple periods of drying up, resulting in severe ecological degradation. In recent years, through the implementation of multi-source, inter-basin ecological water replenishment projects such as the "Yellow River Diversion to Hebei to Replenish Baiyangdian" and the South-to-North Water Diversion Project, the ecological environment of Baiyangdian has been restored to some extent. Against this backdrop, how to scientifically and accurately quantitatively assess the conversion between surface water and groundwater, elucidate its spatiotemporal dynamics, and reveal the impact mechanisms of ecological water diversion measures on groundwater restoration has become a major technical challenge for achieving sustainable utilization of wetland water resources and ecological environmental protection.

[0003] Currently, the technical methods for studying the interaction between surface water and groundwater are becoming increasingly diversified, mainly including hydrodynamic methods, hydrochemical tracing methods, temperature tracing methods, and numerical simulation methods. However, these methods have the following problems or shortcomings: (1) Error propagation and data dependence: Hydrodynamic methods rely on high-density monitoring networks and accurate permeability coefficient parameters. However, the permeability coefficient is highly heterogeneous in space and difficult to obtain accurately, resulting in significant uncertainty and error propagation effects in the calculation results.

[0004] (2) Spatial limitations: Although temperature tracer and water chemistry tracer methods can provide high-precision vertical one-dimensional exchange characteristics at local "points", their measurement results only represent the local situation near the monitoring point and are difficult to effectively reflect the regional and large-scale ("area") exchange process and spatial distribution heterogeneity of the entire wetland.

[0005] (3) Parameter uncertainty: The accuracy of numerical simulation methods is highly dependent on the accuracy of model parameters (especially the permeability coefficient). In practical applications, due to the limited observation data, parameters are usually calibrated by consulting empirical values ​​or by trial and error, which involves a great deal of subjectivity and uncertainty. This directly leads to a decrease in the reliability of simulation results and makes it difficult to accurately compare and verify with field measured data.

[0006] Therefore, existing single technical solutions are insufficient to achieve high-precision, spatiotemporal dynamic quantitative assessment of the wetland surface water-groundwater conversion process, and cannot form a comprehensive analytical framework that mutually verifies and supports each other.

[0007] The information disclosed in this background section is intended only to enhance the understanding of the general background of the invention and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0008] The purpose of this invention is to provide a quantitative assessment method for wetland surface water-groundwater conversion based on multi-method coupling. Its core is to deeply couple macroscopic hydrodynamic analysis, hydrochemical tracing, temperature tracing, high-precision point parameter inversion, and regional-scale numerical simulation to solve the problems existing in the prior art.

[0009] To achieve the above objectives, the present invention adopts the following technical solution: This invention provides a quantitative assessment method for wetland surface water-groundwater conversion based on multi-method fusion, comprising the following steps: Step 1: Comprehensive monitoring and qualitative hydrodynamic analysis, which includes constructing a monitoring network system and hydrodynamic analysis; wherein, the hydrodynamic analysis is based on long-term water level data obtained by the monitoring network, analyzes the spatiotemporal dynamic change characteristics of surface water and groundwater levels, determines whether there is a significant hydraulic connection between the two, and preliminarily identifies their interaction modes. Step 2: Identification of recharge sources using water chemical tracer methods, by calculating Cl in end-members of surface water and regional groundwater. - The mixing ratio of concentrations is analyzed in detail to determine the sources of groundwater recharge in wetlands. Step 3: Calculation of surface water-groundwater conversion rate and inversion of hydrogeological parameters based on temperature tracing method; Step 4: Regional-scale numerical simulation and verification based on multivariate method constraints. The simulation process includes model construction, boundary condition setting, parameter calibration and model verification, and analysis of the spatiotemporal variation characteristics and influencing factors of surface water-groundwater exchange.

[0010] Furthermore, the specific process for calculating the surface water-groundwater conversion rate based on the temperature tracing method in step three is as follows: From the temperature time series data obtained in step one, time periods in which the temperature changes tend to be stable are selected; using the steady-state analytical solution of the one-dimensional vertical heat conduction equation, the steady-state vertical temperature profile data is fitted to accurately calculate the surface water-groundwater vertical exchange velocity Vz at each monitoring point. The vertical one-dimensional heat conduction equation is: (4-2) In the formula: k e -Effective thermal diffusivity (m 2 / s); T - temperature (°C); z - vertical depth (m); v z - Vertical velocity, positive downwards (m / s); λ - Volumetric heat capacity ratio of sediment to fluid; t - Time (s). When the groundwater temperature is in a steady state, the expression on the right side of Equation 4-2 is 0; combined with the boundary conditions: T| z =0=T0、T| z =L=T L Solving equation 4-2 yields: (4-3) (4-4) In the formula: T0 - Upper boundary temperature (°C); T L - Lower boundary temperature (°C); L - Vertical distance between upper and lower boundaries (m); c w -Specific heat capacity of fluid (J·kg) -1 ·℃ -1 ); ρ w - Bulk density (kg / m³) 3 k - thermal conductivity (W·m) -1 ·℃ -1 Substitute the average temperature at different depths into formula (4-3), adjust the parameter β, and use the least squares method to determine its final value.

[0011] Furthermore, the specific process of hydrogeological parameter inversion in step three is as follows: Combining water level monitoring data, monitoring layer depth, and vertical exchange velocity v z The vertical permeability coefficient K was calculated using Darcy's law. Z ; (4-5) Where: Q - permeation flow rate (m³) 3 / d); A - Cross-sectional area of ​​water passage (m²) 2 ); - Head difference between upstream and downstream cross sections (m); l - Seepage path (m); J - Hydraulic gradient; k - Permeability coefficient (m / d); Since the range of values ​​for the thermodynamic parameter k in the temperature tracer method varies little for different water sediments, often falling within a single order of magnitude, K is obtained by inversion using the thermal conductivity coefficient k. Z It can effectively reduce the error in obtaining KZ from in-situ and indoor tests.

[0012] By adopting the above technical solution, the present invention has the following beneficial effects: 1. Significantly improves the accuracy of quantitative assessment: This invention uses key hydrogeological parameters (vertical permeability coefficient) obtained from in-situ inversion using the temperature tracer method to calibrate the numerical model, providing the model with accurate parameter constraints with a physical basis. This overcomes the huge errors caused by parameter uncertainty in traditional simulation methods, making the calculation results of regional-scale exchange quantities closer to physical reality.

[0013] 2. Achieved multi-scale, full-process evaluation combining "point-surface": This invention organically combines the macroscopic qualitative analysis of hydrodynamics and hydrochemistry, the high-precision advantage of temperature tracer method at the "point" with the macroscopic coverage advantage of numerical simulation at the "surface", forming a complete technical chain from "qualitative discrimination" to "quantitative analysis at the point" and then to "generalization on the surface", solving the problem of spatial limitations of single methods.

[0014] 3. A cross-validated closed-loop technical framework is provided: This invention includes a cross-validation process between simulation results and measured results. The exchange rate results obtained by the two independent methods are highly consistent (error <5%), forming a scientific and rigorous closed-loop evaluation process, which ensures the reliability and credibility of the final evaluation results.

[0015] 4. Enhanced scientific decision support for water resource management: The high-precision quantitative assessment results obtained through this invention (such as the average annual surface water infiltration recharge of 2571.06 × 10⁻⁶) 4 The method (m³ / a) can more accurately analyze the impact of factors such as ecological water diversion (lagging by 1-2 months) and rainfall (lagging by 2-3 months) on groundwater restoration, providing a strong scientific basis for formulating wetland ecological water replenishment plans and optimizing water resource allocation. Attached Figure Description

[0016] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0017] Figure 1 This is a technical roadmap of the present invention; Figure 2 This is a schematic diagram of the surface water and groundwater exchange and transformation monitoring system provided in an embodiment of the present invention. Figure 3 The dynamic curve of surface water level in Baiyangdian Lake provided in this embodiment of the invention; Figure 4 This is a diagram showing the interannual variation of surface water level in Baiyangdian (Shifangyuan) provided in an embodiment of the present invention. Figure 5 This is an annual dynamic curve of the groundwater level at P2 in Baiyangdian Wetland provided in an embodiment of the present invention. Figure 6 This is a dynamic curve of groundwater level at monitoring point P8 in Baiyangdian provided in an embodiment of the present invention. Figure 7 The spatiotemporal dynamic curve of water level in a typical profile of the Baiyangdian lake shoreline provided in this embodiment of the invention; Figure 8 Spatiotemporal dynamic distribution map of water level in a typical profile of the Baiyangdian lake shoreline provided in an embodiment of the present invention; Figure 9 A graph showing the relationship between surface water and rainfall in Baiyangdian Lake (2015-2017) provided for embodiments of the present invention. Figure 10 A graph showing the relationship between rainfall, evaporation, and P8D200 water level in Baiyangdian Lake (2019-2021) provided for embodiments of the present invention. Figure 11 A comparison diagram of the water level relationship between the Baiyangdian P8 monitoring point and the shallow groundwater (a) in Gaoxinzhuang, Zangang Town, Xiongxian County, and the shallow groundwater (b) in Guzhuang Village (Rong 2-2), Chengguan Town, Rongcheng County, provided for embodiments of the present invention; Figure 12 The shallow groundwater flow field (a) and the distribution of the drawdown funnel in Xiong'an New Area in June 2022, provided for embodiments of the present invention; Figure 13 A sampling point distribution diagram provided for an embodiment of the present invention; Figure 14 A spatial variation diagram of chloride ion concentration distribution in Xiong'an New Area and the proportion of lake recharge during the conversion of surface water and groundwater in Baiyangdian Wetland, provided for embodiments of the present invention. Figure 15 Vertical exchange velocity distribution diagrams for each profile during the steady-state period provided in embodiments of the present invention; Figure 16 The vertical exchange velocity obtained by the P8(D50) monitoring well in the embodiment of the present invention during the steady-state period; Figure 17 The vertical exchange velocity of the P10(D50) monitoring well provided in this embodiment of the invention was obtained during the steady-state period. Detailed Implementation

[0018] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0020] This invention proposes a quantitative assessment method for wetland surface water-groundwater conversion based on multi-method fusion. Its core lies in the deep coupling of macroscopic hydrodynamic analysis, source apportionment, high-precision point parameter inversion, and regional-scale numerical simulation. The specific technical solution includes the following steps, combined with… Figure 1 Explanation: Step 1: Comprehensive monitoring and qualitative hydrodynamic analysis (1) Construct a monitoring network system Based on the 1:50,000 hydrogeological survey results of the Baiyangdian watershed plain area and the groundwater resource assessment results of Xiong'an New Area, groundwater monitoring stations were set up at 12 locations around the shoreline of Baiyangdian. Figure 2 a). At each site, two nested monitoring wells are deployed on the inner side of the wetland, perpendicular to the shore. One monitoring well is within 50m of the shore (D50), monitoring shallow groundwater at three different depths. Figure 2 b); Another location approximately 200m from the shore (D200) monitors surface water and shallow groundwater at three different depths. Figure 2 (b) The burial depth of the monitoring layers at each station is based on the lakebed surface. The burial depths of the groundwater monitoring layers (1#, 2#, and 3#) are shown in Table 1, while the burial depth of the surface water monitoring layers is 0m. The monitoring equipment adopts an integrated automatic online transmission system for water level and temperature, with a data acquisition frequency of once per hour, continuously collecting real-time water level and temperature monitoring data from June 1, 2019 to January 31, 2024.

[0021]

[0022] 2) Hydrodynamic analysis Based on long-term water level data obtained from the monitoring network, we analyze the spatiotemporal dynamic changes of surface water and groundwater levels, determine whether there is a significant hydraulic connection between the two, and preliminarily identify their interaction patterns (e.g., long-term unidirectional recharge of groundwater by surface water).

[0023] ① Characteristics of dynamic changes in surface water in Baiyangdian Wetland: (i) Characteristics of annual dynamic changes in surface water in Baiyangdian Wetland: From October 2019 to October 2021, the surface water level of Baiyangdian Lake fluctuated between 6.80 and 7.75 meters. The water level variation was mainly affected by factors such as evaporation, precipitation, and ecological water replenishment. Figure 3Due to the diversion of water from the Yellow River to Baiyangdian Lake and the replenishment of water from the South-to-North Water Diversion Project, the water level of Baiyangdian Lake continued to rise after October 2019, reaching its highest point in late January 2020, and remaining at around 7.5 meters until early March. Subsequently, due to evaporation and downstream water release, the water level began to decline, reaching its lowest point before the flood season. Affected by heavy rainfall in early August 2020, the water level of Baiyangdian Lake rose rapidly. Following this, upstream rivers continuously replenished the water, causing the surface water level to rise continuously, reaching its second peak of the year in mid-September. The water level then remained stable until it declined in March 2021, and this cycle repeated itself.

[0024] (ii) Interannual dynamics of surface water in Baiyangdian Wetland: Changes in the surface water level of Baiyangdian directly reflect fluctuations in its water storage capacity. Based on long-term water level data from 1953 to 2015 collected by the Shifang Institute, this study analyzes the evolution trends of the highest, lowest, and average surface water levels in Baiyangdian. For example... Figure 4 As shown, in years when the highest and lowest water levels are the same or close, Baiyangdian Lake experiences a shorter water storage period, with periods of dryness. Furthermore, for periods with no data for the entire year, it can be inferred that Baiyangdian Lake was in a dry state that year. For example, in 1970, water levels were only recorded from January to March, and the differences between the maximum, minimum, and average water levels were minimal; the other months can be considered as dry.

[0025] The water level changes in Baiyangdian Lake can be divided into five stages. The first stage (before the mid-1960s) saw generally high water levels, with large fluctuations in the highest levels and relatively stable lowest levels. Due to abundant upstream water inflow and large wetland storage capacity, water resources were relatively abundant. However, because upstream reservoirs had not yet played a regulating role, excessive inflow and poor drainage frequently led to flooding disasters such as river overflows and dike breaches. Water levels were significantly affected by rainfall and inflow, exhibiting large interannual variations. Although it had flood control functions, its regulation capacity was limited, posing a threat to downstream areas.

[0026] The second phase (mid-1960s to early 1980s) saw an overall decline in water levels, with smaller fluctuations in peak water levels but larger variations in minimum and average water levels. With the construction and operation of upstream reservoirs, natural runoff was effectively controlled, reducing the amount of water flowing into Baiyangdian. Simultaneously, dredging, river channel improvement, and dike reinforcement projects enhanced drainage capacity, while increased groundwater extraction further weakened the runoff process, particularly noticeable in drought years, with some years experiencing complete desiccation. The 1977 flood caused an abnormal rise in water levels. Despite the decreased water storage capacity, Baiyangdian continues to play a vital role in regional water resource regulation and agricultural irrigation.

[0027] The third stage (early 1980s to late 1980s) was characterized by severe continuous drying up of the lake, with almost no water available from 1983 to 1988. The combination of drought and increased water demand, particularly the large proportion of agricultural water use, led to excessive groundwater extraction and a sharp decrease in water inflow into the lake. Despite several attempts at water diversion, the effects were limited, the ecosystem was damaged, and the lives of residents in the lake area were severely impacted. It wasn't until the torrential rains of the Daqing River in 1988 that water was restored and the ecosystem began to recover.

[0028] In the fourth stage (late 1980s to late 1990s), water levels rebounded somewhat, with all three water levels exceeding those of the previous stage, but fluctuations remained significant. Rapid economic development brought water pressure, leading to a drought-induced runoff crisis. Water pollution worsened, with upstream industrial wastewater and agricultural non-point source pollution contributing to ecological degradation and economic losses. Between 1992 and 1998, COD, BOD, and other pollutants in the water exceeded standards, failing to meet functional zone requirements. To address ecological degradation, a total of 187 million m³ of water was diverted in 1992 and 1997, of which 120 million m³ was diverted to the lake, resulting in some improvement in water quality.

[0029] The fifth stage (since the 21st century) has seen increasingly stronger water resource regulation. From 2001 to 2003, Baiyangdian experienced another period of continuous drought. In 2004, the "Yue River Diversion to Baiyangdian" project was launched. In 2005, multiple reservoirs released water simultaneously, which temporarily alleviated the drought, but the water level quickly receded. In 2007, the inter-basin Yellow River Diversion to Baiyangdian project was implemented. In 2018, the South-to-North Water Diversion Project officially began replenishing Baiyangdian. These multi-source water transfers have, to some extent, alleviated the water crisis, improved water quality, and promoted the restoration and stability of the ecosystem.

[0030] ② Characteristics of groundwater dynamics in Baiyangdian Wetland: (i) Characteristics of annual dynamic changes in groundwater in Baiyangdian Wetland: The dynamic pattern of groundwater level in Baiyangdian Lake is precipitation-infiltration-extraction. The groundwater depth exhibits significant seasonal variations throughout the year, generally consistent with the trend of precipitation. The shallow groundwater around Baiyangdian Lake is mainly affected by surface water seepage and precipitation infiltration. The dynamic changes in groundwater level are closely related to precipitation processes, but there is a certain lag effect in the response to precipitation, with a lag time of approximately 2-3 months. Figure 5 From the beginning of the year to spring (January to May), rainfall is low, and the groundwater level gradually increases in depth and continues to decline. From June to July, due to insufficient rainfall and concentrated agricultural irrigation, the groundwater level reaches its maximum depth for the year and its lowest point, approaching 7.5 meters in July. After entering the main flood season, rainfall increases significantly, groundwater recharge strengthens, and the groundwater level rises again, decreasing to around 7.0 meters by August to September. In autumn and winter (October to December), rainfall decreases and evaporation weakens, causing the groundwater level to increase again, gradually declining until approaching 7.2 meters by the end of the year.

[0031] Seasonal fluctuations in groundwater levels are primarily influenced by precipitation, surface water infiltration, and groundwater extraction. During periods of abundant rainfall (July to September), groundwater recharge is strong, causing water levels to rise. Conversely, during the dry season (January to June) and autumn / winter (October to December), reduced precipitation and the dominance of groundwater extraction and evaporation lead to a gradual decline in groundwater levels. The annual variation in groundwater levels is relatively small, typically around 1 meter. Due to the significant groundwater extraction intensively for agricultural irrigation, shallow groundwater consumption is highest in June and July, resulting in the most pronounced drop in water levels.

[0032] (ii) Interannual dynamics of groundwater in Baiyangdian Wetland: Depend on Figure 6 It is evident that the groundwater level in Baiyangdian exhibits significant dynamic changes on an interannual scale. The fluctuation trends of water levels in different aquifers are basically consistent, showing an overall periodic fluctuation pattern. From August 2019 to May 2021, the groundwater level experienced two significant rises. From August 2019 to February 2020, the water level rose rapidly due to rainfall and water diversion from Baiyangdian (according to data released by the Baoding Water Resources Bureau, approximately 0.47 billion cubic meters of water were diverted from the South-to-North Water Diversion Project in the Puhe River from September to December 2019, and 0.36 billion cubic meters were replenished through the Yellow River Diversion Project from August to November). The water level reached a peak of 7.3m in mid-January to February 2020. Subsequently, due to the cessation of water diversion, the groundwater level fluctuated and declined under the influence of factors such as evaporation, groundwater seepage, and runoff, dropping to 6.35m in August 2020. From July 2020 to early 2021, influenced by increased rainfall and water diversion (according to the Water Resources Management Department of the Ministry of Water Resources, a total of 210 million cubic meters of ecological water replenishment was carried out in 2020, of which approximately 106 million cubic meters were diverted from the Puhe River via the South-to-North Water Diversion Project), groundwater levels showed a fluctuating upward trend, reaching a peak of 7.33 meters in early 2021. After water diversion ceased at the end of the year, the water level fluctuated downward due to factors such as increased evaporation caused by warmer weather. From August 2023 to May 2024, the water level was lower than that of the same period in 2020 and 2021, which may be due to reduced water diversion or increased groundwater extraction in the region. Looking at the characteristics of changes during the wet and dry seasons, groundwater levels decline in winter and spring (dry season) and rise in summer and autumn (wet season), exhibiting a dual regulatory characteristic of precipitation and water diversion. Generally speaking, the lowest water level during the dry season occurs from June to October, while the highest water level during the wet season usually occurs from January to March, reflecting that groundwater has a certain lag in hydrological regulation of water diversion.

[0033] During each water diversion period, the groundwater level gradually rose for a period after the diversion was implemented. However, after the diversion stopped, the level continued to rise for a while before stabilizing or slowly declining, indicating that the water diversion had a delayed response to replenishing the Baiyangdian groundwater system. The first water diversion period, from August to December 2019, saw the groundwater level slowly rise from 6.69m, steadily increasing throughout the diversion process, reaching a peak of 7.3m in January and February 2020, with a maximum rise of 0.91m. After the diversion ended, the groundwater level continued to rise for a period before entering a downward trend in March and April 2020, falling back to around 6.5m. The second water diversion was initiated in February 2020. However, due to the delay in water diversion, the water level only began to rise steadily after reaching its lowest point in July and August 2020, peaking at 7.33m in early 2021, with a maximum increase of 0.98m. After the water diversion ceased, the water level remained high for several months until it gradually declined after April 2021. This process indicates that the cumulative effect of long-term water diversion on the groundwater system is enhanced, and the water level recovery process is more gradual compared to the first water replenishment. The third water diversion was initiated in early October 2023. Before the diversion, the groundwater level was around 6.7m. After the diversion, the groundwater level gradually rose, reaching around 7.1m in early 2024, an increase of about 0.4m compared to before the replenishment. The rise in water level gradually became apparent about 1-2 months after the diversion and maintained a certain upward trend after the replenishment ended. This is similar to the lag effect of the previous two water replenishments, indicating a longer timescale for groundwater recharge response. Therefore, under the multiple rounds of water diversion between 2019 and 2024, the groundwater level of Baiyangdian Lake showed an overall trend of phased recovery. Initially, the water level was approximately 6.5m, and after several rounds of water diversion, the highest water level rose to 7.4m, with a maximum increase of 0.98m. However, after the water diversion ceased, the water level still experienced varying degrees of decline, indicating that the groundwater recovery process was influenced by multiple factors, including aquifer characteristics, groundwater flow conditions, and the scale of water diversion. Overall, under the effect of continuous water diversion, the groundwater level significantly increased compared to before the diversion, demonstrating that water diversion played a positive regulatory role in the groundwater resources of Baiyangdian Lake and the surrounding area.

[0034] ③ Characteristics of surface water-groundwater hydrodynamic exchange on typical wetland profiles of Baiyangdian. The dynamic water level curves of the monitoring wells in Shaochedian (P2), Zaozhaodian (P3), Fanyudian (P7), and Chiyudian (P9) show that ( Figure 7The fluctuation patterns of surface water and groundwater levels in Baiyangdian Wetland are basically consistent, and the fluctuation patterns of water levels in different monitoring wells are also basically consistent. Furthermore, the water level decreases sequentially with increasing aquifer depth. Within the same aquifer depth, the water level in monitoring wells 50m from the shore is generally lower than that in monitoring wells 200m from the shore. This indicates that Baiyangdian exhibits a vertical pattern of continuous surface water replenishing groundwater, with the lake area itself supplying the surrounding area.

[0035] The dynamic water levels of groundwater monitoring wells in the inner and outer lake areas of Shaochedian (where P2 is located), Zaozhaodian (where P3 is located), Fanyudian (where P7 is located), and Chiyudian (where P9 is located) show that ( Figure 8 The surface water level in Baiyangdian Wetland generally follows the same trend as the surrounding groundwater level, indicating a significant replenishment effect of surface water on the surrounding groundwater. The horizontal water level difference ranges from 1 to 5 meters, and the overall infiltration of surface water into the surrounding groundwater is consistent with the flow field distribution. From August 2019 to February 2020, influenced by rainfall and ecological water replenishment, the lake's water level rose rapidly, peaking in January and February 2020. This rise significantly impacted the surrounding groundwater level, demonstrating a strong replenishment effect of the lake on the surrounding groundwater. With the cessation of ecological water replenishment and the influence of evaporation and seepage, the groundwater levels in both the lake and its surrounding areas began to decline. From July 2020 to May 2021, influenced by increased rainfall and the second phase of ecological water replenishment, the lake's water level fluctuated and rose again, causing synchronous changes in the surrounding groundwater level. The water level fluctuation trend is highly correlated with the replenishment process. Overall, the fluctuation patterns of the lake's water level and groundwater level reflect the continuous replenishment of groundwater by the lake, further verifying the water exchange relationship between the lake and groundwater.

[0036] Before the establishment of Xiong'an New Area in 2017, the surface water level of Baiyangdian Wetland was significantly affected by precipitation. Figure 9 Since 2017, the surface water and groundwater levels of Baiyangdian Lake have fluctuated due to multiple factors, with precipitation and ecological replenishment becoming important sources of surface water for the Baiyangdian wetland. Figure 10 It can be seen that from the end of August 2019 to February 2020, as precipitation gradually decreased, surface water and groundwater levels gradually rose, with an increase of 0.7 meters. This rise was mainly due to ecological water replenishment. From March to July 2020, affected by factors such as evapotranspiration, groundwater seepage, and runoff, surface water and groundwater levels gradually and significantly decreased, with a drop of 0.6 meters. From July to September 2020, influenced by increased precipitation and ecological water replenishment, surface water and groundwater levels rose to 7.1 meters and remained stable and slowly increased until March 2021, when the levels began to gradually decline again. The effects of rainfall and external water diversion on groundwater levels have a lag effect. The lag time for the impact of external water diversion on groundwater levels is 1-2 months, while the lag time for the impact of rainfall on groundwater levels is 2-3 months.

[0037] ④ Response analysis of groundwater in Xiong'an New Area and groundwater in Baiyangdian Wetland Equation 1 was used to normalize the groundwater level to its maximum and minimum values ​​to eliminate the influence of dimensions and ensure data comparability. Based on this, Pearson correlation coefficient and coefficient of determination (R²) analyses were performed on the groundwater level. Figure 11 The groundwater level maps of shallow groundwater in Gaoxinzhuang, Zangang Town, Xiong County, and the groundwater level in the shallow monitoring well (Rong 2-2) in Guzhuang Village, Chengguan Town, Rongcheng County, are shown. Figure 2-6 and Figure 2-8 This will not be repeated in this chapter. The results show that there is a significant linear correlation between the groundwater level in Baiyangdian Wetland and the groundwater level in the surrounding area. Among them, the fitting result of the groundwater level at monitoring point P8 in Baiyangdian Wetland and the shallow monitoring well at Gaoxinzhuang, Zangang Town, Xiongxian County is y=0.19x+0.08, with a coefficient of determination R2=0.69 ( Figure 11 a); The fitting result of the groundwater level at monitoring point P8 in Baiyangdian Wetland and the shallow monitoring well at Rong 2-2 in Guzhuang Village, Chengguan Town, Rongcheng County is y=0.71x+0.07, with a coefficient of determination R2=0.73 ( Figure 11 a) This significant correlation indicates a close hydraulic connection between Baiyangdian Wetland and the Xiong'an New Area groundwater system. In other words, changes in the groundwater level of Baiyangdian Wetland are not only influenced by local hydrological processes but also play a significant regulatory role in the Xiong'an New Area groundwater system. Especially during periods of external water input (such as ecological water diversion), the rise in the water level of Baiyangdian Wetland becomes a key factor driving changes in regional groundwater.

[0038] Baiyangdian Wetland is a typical seasonally waterlogged wetland in the North China Plain. Its groundwater recharge process is mainly influenced by rainfall infiltration, surface water seepage, and lateral groundwater inflow. Under long-term average hydrological conditions, the surface water and surrounding groundwater systems of Baiyangdian Wetland generally maintain a dynamic balance. However, this balance can be disrupted by the combined effects of human activities (such as water diversion and groundwater extraction) and natural processes (rainfall and evapotranspiration). Water diversion, as an exogenous recharge measure, not only raises the surface water level of Baiyangdian Wetland but also significantly alters the recharge pattern of the surface water-groundwater system. Specifically, after water diversion, the hydraulic load of the Baiyangdian Wetland water body on the aquifer increases, and the rise in water level leads to a larger hydraulic gradient between surface water and groundwater, thereby enhancing seepage recharge. This process is controlled by the aquifer permeability coefficient and the characteristics of the sediments at the bottom of Baiyangdian Wetland. In areas with high permeability, the groundwater level responds quickly to water diversion, resulting in a synchronous rise in the water level of shallow aquifers. However, in areas with poor permeability, the recharge process may have a lag effect, leading to a time delay in the rise of the groundwater level.

[0039] (1) In the formula: X norm - Normalized data; X - Original data value; X min - The minimum value in the dataset represents the minimum boundary of the data; X max - The maximum value in the dataset represents the maximum boundary of the data.

[0040] From the perspective of regional groundwater flow field characteristics ( Figure 12 a) The Baiyangdian wetland and its surrounding areas mainly consist of Quaternary loose sediment aquifers, with shallow groundwater depths, significantly influenced by surface water-groundwater interactions. The Xiong'an New Area's terrain generally slopes from northwest to southeast, and the regional groundwater flow generally migrates from northwest to southeast. However, in the Baiyangdian wetland and adjacent areas, the area is affected by the drawdown cone formed by long-term excessive groundwater extraction ( Figure 12 (b) Disturbances in the local groundwater dynamics have created a localized reverse groundwater flow pattern, with Baiyangdian Lake as the source and Xiong'an New Area as the catchment area. This hydrodynamic structure allows groundwater from the surrounding wetlands to replenish Baiyangdian Lake through lateral seepage, while simultaneously enhancing the regulatory effect of the wetland's groundwater level on the groundwater system in northern Baiyangdian Lake. Against this backdrop, changes in the groundwater level of Baiyangdian Lake have significantly impacted the shallow groundwater system in Xiong'an New Area, north of Baiyangdian Lake. Figure 11 Regression analysis results show a strong positive correlation between the shallow groundwater levels of Baiyangdian Wetland and Rongcheng and Xiongxian counties. Rongcheng County exhibits a slightly higher goodness of fit and correlation coefficient than Xiongxian County, indicating that it is more sensitive to changes in Baiyangdian's water level. The reasons for this difference are mainly twofold: First, from the perspective of the natural hydraulic structure of the groundwater system, Rongcheng and Xiongxian differ significantly in their hydraulic connectivity. The transmission of groundwater level disturbances typically follows the physical law of "amplitude attenuation with distance," meaning the disturbance gradually weakens during transmission. Rongcheng County, located northwest of Baiyangdian and adjacent to the wetland, lies on the main regional groundwater pathway, resulting in a shorter transmission path and direct hydraulic connectivity, thus leading to a more rapid and significant response to changes in Baiyangdian's water level. Xiongxian County, located northeast of the wetland and off the main flow path, experiences a longer spatial transmission of its groundwater level response to changes in Baiyangdian Lake's water level. Furthermore, the transmission efficiency is reduced due to factors such as topographic relief, hydraulic gradient changes, and aquifer heterogeneity, resulting in a significant lag and attenuation in the water level response. Secondly, from the perspective of the dynamic recovery process of groundwater under human intervention, the spatial distribution of the water diversion path further amplifies the differences in groundwater response between the two locations. Although both Xiongxian and Rongcheng counties possess groundwater drawdown cones to varying degrees (…),… Figure 12(b) However, the recovery effects of the drawdown cone varied significantly, primarily due to spatial differences in the ecological water transfer pathway and recharge efficiency. The overall water transfer flowed from northwest to southeast. Rongcheng County, situated along the transfer path, benefited from continuous groundwater recharge, resulting in some relief of the drawdown cone and faster water level recovery. Xiongxian County, however, deviated from the main recharge path, making it difficult for transferred water to directly infiltrate its groundwater system. This led to limited recharge effects, delayed water level recovery, and a still relatively large drawdown cone. This difference in recovery not only reflects the spatial heterogeneity of the water transfer effect but also further weakens Xiongxian County's responsiveness to changes in Baiyangdian's water level. Furthermore, during the ecological water transfer process, the rise in Baiyangdian's surface water level not only enhanced the seepage recharge to shallow aquifers but also reduced regional groundwater evaporation losses and the intensity of human extraction, thus helping to maintain the water balance and dynamic stability of the regional groundwater system. This process ultimately manifested as a reduction in the amplitude of groundwater level fluctuations and enhanced seasonal stability in Xiong'an New Area, helping to alleviate the problem of continuous water level decline caused by long-term over-extraction.

[0041] In conclusion, there is a close hydraulic connection between Baiyangdian Wetland and the Xiong'an New Area groundwater system. Ecological water diversion can not only significantly raise the wetland water level, but also regulate the shallow groundwater system of Xiong'an New Area through seepage recharge and lateral transport mechanisms. This process has a certain lag and is constrained by regional hydrogeological conditions and the degree of human interference, making it one of the important ways to achieve sustainable utilization of regional groundwater resources.

[0042] Step 2: Identification of the supply source using water chemical tracer method (1) Principle of water chemical tracer method The Cl- concentrations in water bodies from different sources vary significantly. Surface water and regional groundwater are the two main mixing end-members of wetland groundwater. By calculating the mixing ratio of Cl- concentrations in surface water and regional groundwater end-members, the recharge sources of wetland groundwater can be specifically analyzed. Based on the principle of mass conservation, the Cl- concentration of water bodies after mixing with end-members of different Cl- concentrations can be determined by the mass balance equation (Equation 4-1)

[150] . The Cl- concentration values ​​of surface water and wetland groundwater were the measured values ​​of P1-P12, and the Cl- concentration value of regional groundwater was the average value of the Cl- concentration of shallow groundwater samples (n=173) in Xiong'an New Area.

[0043]

[0044] In the formula: 𝜹1, 𝜹2 — 𝜹Cl values ​​of surface water and regional groundwater end-members; K—Cl value of wetland groundwater; n1, n2 — The proportion of different end-member water bodies 1 and 2 in the wetland groundwater.

[0045] (2) Wetland surface water and groundwater sampling and chloride ion concentration testing The recharge ratio of lake water and regional groundwater in Baiyangdian Wetland was calculated using the hydrochemical tracer method to identify the recharge source of Baiyangdian Wetland groundwater. Surface water, Baiyangdian Wetland groundwater, and shallow groundwater samples were collected within the Xiong'an New Area: Surface water samples (n=12) were collected at the surface water monitoring layer (#0) of the P1-P12 monitoring well group; Baiyangdian Wetland groundwater samples (n=36) were collected from three different layers (#1, #2, and #3) of the groundwater monitoring layer of the P1-P12 monitoring well group; and shallow groundwater samples (n=173) of Xiong'an New Area were systematically collected based on a grid-based sampling principle, with sampling points covering the entire New Area, and the water intake layer strictly controlled within the 15-30m depth range of the unconfined aquifer. All samples underwent on-site pretreatment according to the "Technical Specification for Groundwater Environmental Monitoring" (HJ 164-2020), and chloride ion concentration was determined using ion chromatography (referencing HJ84-2016) (this data was obtained from the China Geological Environment Monitoring Institute). For data processing, the geostatistics module integrated into the ArcGIS 10.8.1 platform was used to apply Kriging spatial interpolation technology to create a spatial distribution map of Cl⁻ concentration within the Xiong'an New Area. Simultaneously, using chloride ions as a tracer, the recharge ratio of lake water to regional groundwater at monitoring points P1-P12 was calculated using the mass balance equation, and a spatial distribution map was created.

[0046] (3) Analysis of groundwater recharge sources in Baiyangdian wetland Based on the chloride ion (Cl-) concentrations in surface water and regional groundwater during the monitoring period, the proportion of surface water recharge during the surface water-groundwater conversion process in Baiyangdian Wetland was calculated using Equation 4-1. The calculation results are shown in Table 4-1, and the spatial distribution characteristics are as follows: Figure 14 As shown in the figure, overall, the proportion of surface water recharge in the Baiyangdian wetland's groundwater end-members is generally higher than that of regional groundwater recharge, indicating that surface water plays an important role in the groundwater recharge process. Furthermore, the proportion of surface water recharge in the northwest (upper reaches of the basin) of the Baiyangdian wetland is significantly lower than that in the southeast (lower reaches of the basin). This spatial difference may be closely related to regional sedimentary characteristics and hydrogeological conditions. In the northwest, sediments are mainly composed of coarse-grained materials such as sand and gravel, with high permeability and fast flow velocity. In this area, the exchange between surface water and groundwater is relatively rapid, but due to the high seepage rate, the net recharge efficiency of surface water is low. In contrast, the sediments in the southeast are mainly composed of fine-grained materials such as clay and silt, with low permeability and slow groundwater flow velocity, resulting in longer water retention time underground, thus enhancing the surface water recharge effect on groundwater.

[0047] Therefore, the spatial distribution characteristics of surface water recharge reflect the influence of regional hydrological features and sediment properties on the surface water-groundwater conversion process. Specifically, the downstream area of ​​Baiyangdian Wetland has a higher proportion of surface water recharge due to its lower permeability and slower water flow, while the upstream area has a lower proportion due to its faster water flow. These findings not only reveal the crucial role of surface water in the regional hydrological cycle but also provide an important data foundation for further exploring the hydraulic connections between surface water and groundwater.

[0048]

[0049] Step 3: Calculation of surface water-groundwater conversion rate based on temperature tracer method (at 12 monitoring points) and inversion of hydrogeological parameters. (1) Calculation of vertical exchange velocity From the temperature time-series data obtained in the first step, time periods where temperature changes tend to stabilize were selected. The steady-state analytical solution (Stallman analytical solution) of the one-dimensional vertical heat conduction equation was used to fit the steady-state vertical temperature profile data, accurately calculating the surface water-groundwater vertical exchange velocity (Vz) at each monitoring point. The calculation results show that the downward infiltration velocity ranges from 0.35 to 1.32 cm / d.

[0050] The vertical one-dimensional heat conduction equation is:

[0051] In the formula: k e -Effective thermal diffusivity (m 2 / s); T - Temperature (°C); z - Vertical depth (m); v z - Vertical velocity (positive value downwards) (m / s); λ - The ratio of the volumetric heat capacity of sediment to that of fluid; t - time (s).

[0052] When the groundwater temperature is in a steady state, the expression on the right side of Equation 4-2 is 0. Combined with the boundary conditions: T| z =0=T0、T| z =L=T L Solving equation 4-2 yields:

[0053] In the formula: T0 - Upper boundary temperature (°C); T L -Lower boundary temperature (°C); L - Vertical distance between the upper and lower boundaries (m); c w -Specific heat capacity of fluid (J·kg) -1 ·℃ -1 ); ρ w - Bulk density (kg / m³) 3 ); k - thermal conductivity (W·m) -1 ·℃ -1 ).

[0054] Substituting the average temperature at different depths into formula (Equation 4-3), and adjusting the parameter β, the final value can be determined using the least squares method. Considering the sedimentary lithological characteristics of the strata surrounding the wetland and referring to relevant research results, the parameters in Equation (4-4) are determined as follows: water density ρ w Take 1000 kg / m³, specific heat capacity c w The thermal conductivity is 4180 J / (kg·℃), and the thermal conductivity coefficient k is set to 0.6 W / (m·℃). The vertical exchange velocity ν can be calculated using formula (4-4). z Then, combining the vertical hydraulic gradient, the vertical permeability coefficient k was obtained by inversion using Darcy's law. Z .

[0055] Based on the applicable conditions of Equations 4-2 and 4-3, periods when the temperature is basically in a stable state are selected, and the vertical exchange velocity between surface water and groundwater is calculated. When analyzing the dynamic changes in temperature data, variance is chosen as an indicator of temperature stability. The temperature measurement error of the monitoring equipment is 0.1℃; therefore, when the temperature variance is less than 0.01℃, the temperature is considered to have reached a relatively stable state. The time span for the temperature variance is 3 days. The calculation uses the "least squares method." After obtaining the β value in Equation 4-3, it is substituted into Equation 4-4 to obtain the vertical exchange velocity vz between surface water and groundwater (Table 4-2).

[0056] As shown in Table 4-2, significant differences exist in vertical exchange velocities at different observation locations of approximately 50m and 200m from the shore, with both positive and negative values ​​appearing. This indicates that the transformation between surface water and groundwater in the Baiyangdian lake shoreline is a dynamic process of mutual conversion. Based on the calculation results of seepage velocities from 18 monitoring well groups across 12 monitoring profiles, 9 well groups exhibited both positive and negative seepage velocities during steady-state periods. Most well groups with positive velocities were located near the shoreline, while all well groups with negative velocities were located in the downstream drainage area of ​​Baiyangdian. The positive seepage velocity ranged from 0.35 to 1.32 cm / d, while the negative seepage velocity ranged from -0.28 to -0.01 cm / d. The positive seepage velocity was significantly greater than the negative velocity. Therefore, the transformation relationship between surface water and groundwater in Baiyangdian is primarily driven by surface water seepage replenishing groundwater.

[0057] The monitoring profiles exhibited significant spatial and temporal differences in the positive and negative exchange velocities during the stable period. Spatially, monitoring profiles at wells 50m from the shore primarily showed positive vertical exchange velocities during the stable period, including P1, P3, P4, P6, P8, P9, and P10. In contrast, at wells 200m from the shore, P8 and P12 also showed predominantly positive vertical exchange velocities. Conversely, negative exchange velocities were mainly distributed at P6 and at P8, P9, P10, and P12 in the downstream area of ​​Baiyangdian Lake. Spatially, the monitoring profiles at 50m from the shore primarily showed positive exchange, indicating a significant process of surface water seepage replenishing groundwater near the shoreline. However, at 200m from the shore, some profiles still showed positive exchange velocities, suggesting that surface water seepage continues to influence groundwater within a certain range. On the other hand, the monitoring profile of negative exchange velocity mainly appeared in the downstream area of ​​Baiyangdian Lake. Figure 15 This indicates that during steady-state periods, groundwater in the area may replenish surface water under the influence of the hydraulic gradient, reflecting the phased changes in the groundwater-surface water conversion relationship. In terms of temporal variation, the positive exchange velocity of the P8D50 monitoring well group mainly occurred from July to October 2023, December 2023, and March 2024. Figure 16 The positive exchange flow rate of the P10D50 monitoring well group mainly occurred in September, October, and December 2023, and February and April 2024, while the negative exchange flow rate of the P10D50 monitoring well group mainly occurred from September to November 2023 and March 2024. Figure 17Overall, during the wet season or water diversion period, the surface water-groundwater conversion process in Baiyangdian Wetland is mainly driven by surface water infiltration replenishing groundwater. However, during the dry season or after water diversion ceases, some monitoring profiles show groundwater replenishing surface water, indicating that rainfall and water diversion are important influencing factors in the surface water-groundwater conversion in Baiyangdian, consistent with the previous analysis. In summary, the hydrological processes of Baiyangdian Wetland are not only affected by rainfall and water diversion but also constrained by groundwater dynamics. This finding provides important evidence for a deeper understanding of the interaction between the surface water and groundwater systems in Baiyangdian Wetland.

[0058] (2) Vertical permeability coefficient inversion of Baiyangdian wetland By combining water level monitoring data, the depth of the monitoring layer, and the vertical exchange velocity (vz), the vertical permeability coefficient KZ is calculated using Darcy's law.

[0059]

[0060] In the formula: Q - Permeation flow rate (m) 3 / d); A - Cross-sectional area of ​​the water passage (m2); - The head difference between the upstream and downstream cross sections (m); l - Infiltration path (distance between upstream and downstream cross sections) (m); J-hydraulic gradient; k - Permeability coefficient (m / d).

[0061] Because the range of values ​​for the thermodynamic parameter k in the temperature tracer method varies little across different water sediments, often falling within a single order of magnitude, K can be obtained by inversion using the thermal conductivity coefficient k. Z It can effectively reduce the yield of K in in-situ and indoor experiments. Z The error.

[0062]

[0063] The permeability coefficient is closely related to the lithology of the strata. According to the core logging results from hydrogeological drilling, the shoreline of Baiyangdian Lake is mainly composed of silty clay and silt, with local interlayers of fine sand. Referring to data from *Hebei Groundwater*, the vertical permeability coefficients of shallow (<50m) loose rocks in the Hebei Plain range as follows: sub-clay 0.003–0.01 m / d, sub-sandy soil 0.01–0.05 m / d, and silt 0.05–0.5 m / d. Furthermore, previous studies have shown that the sediments of the Da Ke Po Lake bed consist of clay, silty clay to silt, with a vertical permeability coefficient ranging from 0.002 to 0.011 m / d; Qi Gai Nao Lake is mainly composed of silt and fine sand, with a permeability coefficient ranging from 0.008 to 0.14 m / d. Based on the actual lithological conditions of the Baiyangdian lake shoreline, the vertical permeability coefficients (0.004–0.129 m / d) calculated in Table 4-3 are basically consistent with the empirical values ​​of shallow loose rocks in the Hebei Plain and the measured data of similar lakebeds.

[0064] In terms of spatial distribution, the vertical permeability coefficient of the lake shoreline varies somewhat at different locations, but all are within the same order of magnitude. Within a single monitoring station, the permeability coefficients at locations approximately 50m and 200m from the shore differ slightly, but the differences are small. Furthermore, during extended monitoring periods, the results obtained from multiple iterative calculations of the permeability coefficient were largely consistent with previous data, further validating the feasibility and stability of the seepage velocity inversion method used in this study.

[0065] Step 4: Regional-scale numerical simulation and verification based on multivariate method constraints The surface water-groundwater conversion process in Baiyangdian Wetland is controlled by multiple factors, including regional hydrodynamic conditions, recharge sources, and aquifer structure. Previous studies used hydrodynamic analysis to reveal the exchange characteristics of surface water and groundwater, identified the main recharge sources of groundwater using hydrochemical tracer methods, and calculated the local vertical exchange rate using temperature tracer methods, obtaining key parameters such as the vertical permeability coefficient. To achieve a quantitative assessment of the surface water-groundwater conversion process, this chapter, based on the above findings, constructs a model of surface water-groundwater exchange in Baiyangdian Wetland and uses numerical simulation methods for quantitative calculations. The simulation process includes model construction, boundary condition setting, parameter calibration, and model validation, and analyzes the spatiotemporal variation characteristics and influencing factors of surface water-groundwater exchange.

[0066] Preferably, in the second step, "Calculation of Vertical Exchange Rate and Parameter Inversion at Location," other high-precision physical or chemical tracer methods can be used instead of the temperature tracer method. For example, radon-222 (²²²Rn) can be used as a tracer, and the exchange flow rate can be calculated by measuring the radon concentration distribution in the vertical profile, thereby inverting the permeability coefficient. The radon tracer method also has the characteristic of high location accuracy and can achieve similar technical objectives.

[0067] In the third step, “numerical simulation,” in addition to the MODFLOW-LAK module, other numerical modeling software with similar functions that can simulate surface water-groundwater coupling processes can be used, such as HydroGeoSphere, GSFLOW, or SWAT-MODFLOW. These models differ in their solution mechanisms, but they can all construct regional-scale coupling models and accept the permeability coefficient parameters obtained from the inversion in the second step.

[0068] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A quantitative assessment method for wetland surface water-groundwater conversion based on multi-method fusion, characterized in that, Includes the following steps: Step 1: Comprehensive monitoring and qualitative hydrodynamic analysis, which includes constructing a monitoring network system and hydrodynamic analysis; wherein, the hydrodynamic analysis is based on long-term water level data obtained by the monitoring network, analyzes the spatiotemporal dynamic change characteristics of surface water and groundwater levels, determines whether there is a significant hydraulic connection between the two, and preliminarily identifies their interaction modes. Step 2: Identification of recharge sources using water chemical tracer methods, by calculating Cl in end-members of surface water and regional groundwater. - The mixing ratio of concentrations is analyzed in detail to determine the sources of groundwater recharge in wetlands. Step 3: Calculation of surface water-groundwater conversion rate and inversion of hydrogeological parameters based on temperature tracing method; Step 4: Regional-scale numerical simulation and verification based on multivariate method constraints. The simulation process includes model construction, boundary condition setting, parameter calibration and model verification, and analysis of the spatiotemporal variation characteristics and influencing factors of surface water-groundwater exchange.

2. The quantitative assessment method for wetland surface water-groundwater conversion based on multi-method fusion as described in claim 1, characterized in that, The specific process for calculating the surface water-groundwater conversion rate based on the temperature tracing method in step three is as follows: From the temperature time series data obtained in step one, time periods in which the temperature changes tend to be stable are selected; using the steady-state analytical solution of the one-dimensional vertical heat conduction equation, the steady-state vertical temperature profile data is fitted to accurately calculate the surface water-groundwater vertical exchange velocity Vz at each monitoring point. The vertical one-dimensional heat conduction equation is: ； In the formula: k e -Effective thermal diffusivity (m 2 / s); T - temperature (°C); z - vertical depth (m); v z - Vertical velocity, positive downwards (m / s); λ - Volumetric heat capacity ratio of sediment to fluid; t - Time (s). When the groundwater temperature is in a steady state, the expression on the right side of Equation 4-2 is 0; combined with the boundary conditions: T| z =0=T0、T| z =L=T L Solving equation 4-2 yields: ； Where: T0 - upper boundary temperature (°C); T L - Lower boundary temperature (°C); L - Vertical distance between upper and lower boundaries (m); c w -Specific heat capacity of fluid (J·kg) -1 ·℃ -1 ); ρ w - Bulk density (kg / m³) 3 k - thermal conductivity (W·m) -1 ·℃ -1 Substitute the average temperature at different depths into formula (4-3), adjust the parameter β, and use the least squares method to determine its final value.

3. The quantitative assessment method for wetland surface water-groundwater conversion based on multi-method coupling according to claim 1, characterized in that, The specific process of hydrogeological parameter inversion in step three is as follows: Combining water level monitoring data, monitoring layer depth, and vertical exchange velocity v z The vertical permeability coefficient K was calculated using Darcy's law. Z ; ； Where: Q - permeation flow rate (m³) 3 / d); A - Cross-sectional area of ​​water passage (m²) 2 ); - Head difference between upstream and downstream cross sections (m); l - seepage path (m); J - hydraulic gradient; k - permeability coefficient (m / d). Since the range of values ​​for the thermodynamic parameter k in the temperature tracer method varies little for different water sediments, often falling within a single order of magnitude, K is obtained by inversion using the thermal conductivity coefficient k. Z It can effectively reduce the yield of K in in-situ and indoor experiments. Z The error.

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