Comprehensive Evaluation of Water Resource Characteristics in the Northern Yangtze River Delta, China

: The Yangtze River Delta is one of the most economically developed regions on the eastern coast of China. However, a local imbalance currently exists between its water resource environment and economic and social development due to its rapid urbanization. Thus, the reasonable evaluation and protection of local water resources are necessary. This study explores the northern Yangtze Delta, which is a more developed water system, as a pilot area. The temporal and spatial variation characteristics of rainfall and evaporation and their inﬂuencing factors were analyzed on the basis of 29 surface water sampling points, 16 rainfall stations, and three evaporation stations in the ﬁeld from 1956 to 2019. Accordingly, the overall water supply quality of the river basin, the availability of different water resources, and the application of evaluation methods were assessed. Results show that local precipitation and evaporation are characterized by uneven spatial and temporal distributions in local areas, which, in turn, leads to the uneven temporal distribution of runoff, increasing the imbalance between the availability and demand of the limited local water resources. Nevertheless, the overall performance of local water quality is good. Surface water quality is mostly II to III, and locally IV. Most noncompliant months are during the non-ﬂood season, and all values exceed the standard permanganate index. Groundwater is Class III or better, and the hydrochemistry type is predominantly calcium bicarbonate, sodium bicarbonate, and magnesium bicarbonate. By exploring the evaluation model of the Yangtze River Delta watershed characteristics, this study aims to provide a helpful reference for extending water resource evaluation in the Yangtze River Delta. Accordingly, this study can promote the sustainable development of the economic and social sectors of the Yangtze River Delta and the construction of its ecological environment


Introduction
Water is a fundamental resource for human survival, an economic resource for social development, and an essential ecological resource for supporting the cyclical operation of ecological systems [1]. As the birthplace of the "two mountains" theory (i.e., clear water and green mountains are gold and silver mountains), the Yangtze River Delta region is currently one of the most urbanized, economically developed, and densely populated regions in China. In addition, the Yangtze River Delta is the source of the eastern route of China's South-to-North Water Transfer Project [2,3]. However, the rapid development of society has posed a serious challenge to the local water environment [4,5]. Therefore, encouraging the sustainable use of water resources and ensuring the coordinated development of the basin require a comprehensive evaluation of the Yangtze River Delta's water resource features [6,7]. The amount of water in transit was calculated on the basis of the established nationa hydrological stations as control sections. Groundwater information was obtained from the natural resource department for monitoring groundwater wells, monitoring information from the Yangzhou Branch of the Jiangsu Provincial Water Resource Survey Bureau, and

Data Sources 2.2.1. Underlying Surface and Groundwater Level
Data on the underlying surface of the pilot area were provided by the Natural Resources Bureau of Baoying County, Yangzhou City, Jiangsu Province, China. To reflect the consistent characteristics of the runoff series, the underlying surface was divided into individual types in accordance with flow production characteristics, and then flow production models were developed separately. In addition, surface water resources were calculated daily. The various types of land areas in the production flow model were adopted from the latest survey statistics of local land administration authorities. The results basically reflect the condition of the recent (horizontal year 2019) underlying surface of the pilot area, as indicated in Table 1. The amount of water in transit was calculated on the basis of the established national hydrological stations as control sections. Groundwater information was obtained from the natural resource department for monitoring groundwater wells, monitoring information from the Yangzhou Branch of the Jiangsu Provincial Water Resource Survey Bureau, and data from the current water quality survey.

Rainfall and Evaporation
When studying the characteristics of rainfall in the region, 16 rainfall stations in the pilot area were selected for the analysis by considering the length of the data series and the principle of uniform distribution of rainfall stations, with a time series of 1956 to 2019. For rainfall stations with less than 64 years of data series, synchronous data from rainfall stations adjacent to them with at least 64 years of data series were used to establish a correlation, interpolate, and extend to 64 years. Furthermore, the observed data from 1980 to 2019 (40 years) from three evaporation stations in Liuzha, Xinghua, and Huangqiao were used to analyze the evaporation capacity of the pilot area. However, the three evaporation stations have evaporators other than E 601 and ∅80. Considering that the evaporation measured by the E 601 evaporator better reflects evaporation capacity and facilitates analysis and comparison, the observed values of different evaporator models were converted and unified into the E 601 model in the current assessment. The rainfall and evaporation stations are spatially distributed as shown in Figure 2.

Synchronous Series Representative Correlation Methods
A stochastic series of meteorological data generally has one or more complete cycles of abundance and depletion. The relative stability of the series depends crucially on the relative stability of the statistical parameters, the coefficient of variation (Cv), and the bias coefficient (CS) [36]. A representative analysis of the series is required to reduce the error due to the potential for sampling error in the Cv and statistical parameters over the course of a long series. By using the comparative analysis method of long and short series statistical parameters, one to three long series (n > 60) observation stations in the city (county) area were selected for comparative analysis to determine the stability of the proposed series statistical parameters. The rainfall modal ratio coefficient cumulative difference product curve method was used. First, a good representative long series of observation station data was selected, and then the mean value of the series ( ) was determined. Finally, the rainfall modal ratio coefficient was calculated separately for each year. The formula is as follows: where is the mean value of the rainfall series, is the annual rainfall for each year, and n is the length of the series for each year. Then, to calculate the cumulative yearly value C from the beginning to the end of the data, the formula is as follows: Lastly, the C-t (year) cumulative curve was plotted. Rising cycles in the cumulative difference curve are periods of abundance, while falling cycles are periods of depletion. By using the cumulative annual average method, each year's average was determined and

Synchronous Series Representative Correlation Methods
A stochastic series of meteorological data generally has one or more complete cycles of abundance and depletion. The relative stability of the series depends crucially on the relative stability of the statistical parameters, the coefficient of variation (Cv), and the bias coefficient (C S ) [36]. A representative analysis of the series is required to reduce the error due to the potential for sampling error in the Cv and statistical parameters over the course of a long series. By using the comparative analysis method of long and short series statistical parameters, one to three long series (n > 60) observation stations in the city (county) area were selected for comparative analysis to determine the stability of the proposed series statistical parameters. The rainfall modal ratio coefficient cumulative difference product curve method was used. First, a good representative long series of observation station data was selected, and then the mean value of the series (P) was determined. Finally, the rainfall modal ratio coefficient was calculated separately for each year. The formula is as follows: where P is the mean value of the rainfall series, Pi is the annual rainfall for each year, and n is the length of the series for each year. Then, to calculate the cumulative yearly value C from the beginning to the end of the data, the formula is as follows: Lastly, the C-t (year) cumulative curve was plotted. Rising cycles in the cumulative difference curve are periods of abundance, while falling cycles are periods of depletion. By using the cumulative annual average method, each year's average was determined and then analyzed. When the average no longer exhibits a large trend of changes is representative. The calculation formulas are as follows: where P1, P2, P3, ···, Pn are the annual rainfall amounts in order of precession from the status quo year; while P1, P2, P3, ···, Pn are the cumulative annual averages of rainfall. The analysis can generally be broken down into periodic and stochastic characterization, with periodic characterization generally for longer series.

Water Interpolation Calculation Methods
When calculating the diversion volume along a river, if the sluice gates have hydrological stations, then the measured water level and flow rate are used to determine the relevant line and deduce the diversion volume of each gate. Interpolation calculations are performed when encountering years of missing information or locks without information [37][38][39].
For medium-sized gates with a long series of data, the correlation analysis method is used for interpolating the diversion and drainage volume. For example, when the characteristics and functions of the sectional gates are similar, the missing stations are extrapolated from the information of actual stations.
For small and medium-sized gates without data, the interpolation of the diversion capacity is performed using the unit net width diversion capacity extrapolation method. By utilizing data on the characteristics of the gates, the limited number of measurements in certain years of these gates is compared with the simultaneous measured data of the controlled medium-sized gates. The conversion factor (c) between the uninformed small and medium-sized gates and the controlled medium-sized gates is determined to derive the drainage capacity of the uninformed small and medium-sized gates.

Water Availability Estimation Method
Surface water resource availability estimates can be divided into reverse calculation and positive methods [40]. Southern regions with more abundant water resources and coastal solitary rivers into the sea are generally used for positive methods. For mountainous areas where the development and utilization of water resources in the upper reaches of large rivers or tributaries are more difficult, the utilization of water resources is largely restricted by the construction of water supply projects. Meanwhile, water supply capacity is also limited to a certain extent. The formula for calculating the number of water resources available is as follows: W surface water availability = k water consumption factor × W maximum water supply .
For the lower reaches of large rivers, the major factor that determines the extent of their water use is the magnitude of demand, and the corresponding formula is as follows: W surface water availability = k water consumption factor × W maximum water demand (7)

Water Quality Analysis Method
Within the pilot area, the surface water pH of the Grand Canal, Yunxi River, Baoying Lake, and Baima Lake was tested, along with the groundwater pH of 23 groundwater wells. The assay was commissioned to the Analysis and Testing Center of Nanjing Normal University. The assay was performed with an inductively coupled plasma atomic emission spectrometer (00304214), an ultraviolet-visible absorption spectrometer (20060475), and an ion chromatograph ThermoICS-900 (00185109). By using the single-factor evaluation method, the water quality categories of the surface water and groundwater were determined by implementing the criteria of the Surface Water Environmental Quality Standard (GB3838-2002) for evaluation. In addition, several evaluation indicators were selected for Na + , K + , Ca 2+ , Mg 2+ , Cu 2+ , Fe, Pb, Cd, Cr, As, fluoride, chloride, sulfate, nitrite, nitrate, ammonia N, hexavalent Cr, total P, bicarbonate, carbonate, mineralization, and total hardness. Then, Alyokin and Shukarev classifications were combined to determine the water chemistry types of the surface water and groundwater.

Rainfall Characteristic Analysis
As shown in Figure 3, the multiyear average annual rainfall contour maps for 1956-2019 and 1980-2019 were derived from line spacing contours of 20 mm and combined with multiyear rainfall data for the pilot area. The range of rainfall contours in the Yangtze River Delta region from 1956 to 2019 was between 960 mm and 1020 mm, with the range of annual average rainfall contours less than 980 mm and a decreasing trend of annual average rainfall from east to west. The range of rainfall contours from 1980 to 2019 was 960-1040 mm. The range of contours was still less than 980 mm, with a higher average annual rainfall in the east than in the west, and a decreasing trend in average annual rainfall from east to west. In addition, the shape and position of the 1000 mm contour changed in a completely different manner, but the shape and position of the 1020 mm contour remained largely unchanged.
Water 2023, 15, x FOR PEER REVIEW 7 University. The assay was performed with an inductively coupled plasma atomic sion spectrometer (00304214), an ultraviolet-visible absorption spectrometer (20060 and an ion chromatograph ThermoICS-900 (00185109). By using the single-factor ev tion method, the water quality categories of the surface water and groundwater wer termined by implementing the criteria of the Surface Water Environmental Quality S ard (GB3838-2002) for evaluation. In addition, several evaluation indicators were sel for Na + , K + , Ca 2+ , Mg 2+ , Cu 2+ , Fe, Pb, Cd, Cr, As, fluoride, chloride, sulfate, nitrite, ni ammonia N, hexavalent Cr, total P, bicarbonate, carbonate, mineralization, and total ness. Then, Alyokin and Shukarev classifications were combined to determine the w chemistry types of the surface water and groundwater.

Rainfall Characteristic Analysis
As shown in Figure 3, the multiyear average annual rainfall contour maps for 1 2019 and 1980-2019 were derived from line spacing contours of 20 mm and comb with multiyear rainfall data for the pilot area. The range of rainfall contours in the Ya River Delta region from 1956 to 2019 was between 960 mm and 1020 mm, with the r of annual average rainfall contours less than 980 mm and a decreasing trend of an average rainfall from east to west. The range of rainfall contours from 1980 to 2019 960-1040 mm. The range of contours was still less than 980 mm, with a higher av annual rainfall in the east than in the west, and a decreasing trend in average annual fall from east to west. In addition, the shape and position of the 1000 mm contour cha in a completely different manner, but the shape and position of the 1020 mm contou mained largely unchanged. Using Baoying Station as the representative rainfall station in the pilot area, stati analysis was performed on its rainfall data by month over the years. Presenting the s from 1956 to 2019 as an example, the maximum four consecutive months of rainfa curred from June to September, with 63.31% of the annual rainfall. Although the flood period was seven months, the rainfall at that time accounted for less than 36.69 the annual rainfall.
As shown in Figure 4, the data from 16 rainfall stations in the pilot area were sel and combined using the simultaneous series representative correlation method to duce a map of the cumulative mean and difference distribution of rainfall in the pilot Using Baoying Station as the representative rainfall station in the pilot area, statistical analysis was performed on its rainfall data by month over the years. Presenting the series from 1956 to 2019 as an example, the maximum four consecutive months of rainfall occurred from June to September, with 63.31% of the annual rainfall. Although the nonflood period was seven months, the rainfall at that time accounted for less than 36.69% of the annual rainfall.
As shown in Figure 4, the data from 16 rainfall stations in the pilot area were selected and combined using the simultaneous series representative correlation method to produce a map of the cumulative mean and difference distribution of rainfall in the pilot area.

Evaporation Characteristic Analysis
The multiyear average monthly maximum water surface evaporation in the pilot evaluation area accounts for 12.9% of the annual evaporation, and the monthly minimum evaporation accounts for 3.1% of the annual evaporation. In addition, the maximum four consecutive months of evaporation totaled 432.0 mm, accounting for 47.9% of the annual evaporation.
As shown in Figure 5, given that evaporation in the pilot area was less before 1980 compared with after 1980, the Six Gate station was used as a representative to analyze the simulated process map of evaporation capacity in the pilot area by utilizing trend simulation. In general, evaporation factors are closely related to meteorological elements, such as temperature, rainfall, humidity, sunshine, and wind speed. However, the regional and interannual variations of evaporation are relatively small compared with the rainfall factor. Therefore, the station network density of evaporation stations is considerably smaller than that of rainfall stations. To analyze evaporation capacity under recent subsurface conditions, 40 years of evaporation data from 1980 to 2019 were used.

Evaporation Characteristic Analysis
The multiyear average monthly maximum water surface evaporation in the pilot evaluation area accounts for 12.9% of the annual evaporation, and the monthly minimum evaporation accounts for 3.1% of the annual evaporation. In addition, the maximum four consecutive months of evaporation totaled 432.0 mm, accounting for 47.9% of the annual evaporation.
As shown in Figure 5, given that evaporation in the pilot area was less before 1980 compared with after 1980, the Six Gate station was used as a representative to analyze the simulated process map of evaporation capacity in the pilot area by utilizing trend simulation. In general, evaporation factors are closely related to meteorological elements, such as temperature, rainfall, humidity, sunshine, and wind speed. However, the regional and interannual variations of evaporation are relatively small compared with the rainfall factor. Therefore, the station network density of evaporation stations is considerably smaller than that of rainfall stations. To analyze evaporation capacity under recent subsurface conditions, 40 years of evaporation data from 1980 to 2019 were used.

Evaporation Characteristic Analysis
The multiyear average monthly maximum water surface evaporation in the pilot evaluation area accounts for 12.9% of the annual evaporation, and the monthly minimum evaporation accounts for 3.1% of the annual evaporation. In addition, the maximum four consecutive months of evaporation totaled 432.0 mm, accounting for 47.9% of the annual evaporation.
As shown in Figure 5, given that evaporation in the pilot area was less before 1980 compared with after 1980, the Six Gate station was used as a representative to analyze the simulated process map of evaporation capacity in the pilot area by utilizing trend simulation. In general, evaporation factors are closely related to meteorological elements, such as temperature, rainfall, humidity, sunshine, and wind speed. However, the regional and interannual variations of evaporation are relatively small compared with the rainfall factor. Therefore, the station network density of evaporation stations is considerably smaller than that of rainfall stations. To analyze evaporation capacity under recent subsurface conditions, 40 years of evaporation data from 1980 to 2019 were used.

Available Surface Water
Surface water resources in the pilot area are mostly formed by local rainfall. The multiyear average annual rainfall for the region is 977.40 mm, with a total rainfall of 262 million m 3 , a surface runoff depth of 244.0 mm, and a water resource volume of 64 million m 3 . Calculated using positive and negative algorithms, surface water resources available in the pilot evaluation area are 14 million m 3 , with a usable rate of 21.4%. The natural runoff volume from 1956 to 2019 is shown in Figure 6.

Available Surface Water
Surface water resources in the pilot area are mostly formed by local rainfall. The multiyear average annual rainfall for the region is 977.40 mm, with a total rainfall of 262 million m 3 , a surface runoff depth of 244.0 mm, and a water resource volume of 64 million m 3 . Calculated using positive and negative algorithms, surface water resources available in the pilot evaluation area are 14 million m 3 , with a usable rate of 21.4%. The natural runoff volume from 1956 to 2019 is shown in Figure 6.

Available Groundwater
The total amount of groundwater resources is the sum of various recharge amounts entering the pilot evaluation area. In particular, atmospheric rainfall naturally recharges about 58.16% of groundwater volume, with the concentration of rainfall during the flood season accounting for about 67% of the annual rainfall. Therefore, this situation results in groundwater recharge during the flood season accounting for 36.33% of the annual recharge. The pilot area is located on a plain, and no baseflow recharge occurs from rivers in the hilly areas in groundwater resource quantity. Thus, no duplicate amount is deducted when determining the amount of groundwater resources. The pilot region has 32.75 million m 3 of groundwater resources, and 58.16% of atmospheric rainfall naturally infiltrates into those resources. The amount of groundwater available in the pilot evaluation region is 0.026 billion m 3 in accordance with the coefficient approach used to determine the extractable amount of groundwater resources.

Available Transit Water
The amount of water in transit is divided into two parts in accordance with the type of water source: Yangtze River and Huai River. The amount of river water that can be used is estimated by calculating the actual use of river water. In the pilot area, the actual available quantity of Yangtze River water includes the amount of water abstracted directly from the Yangtze River for industrial, agricultural production, and domestic use and the amount of river water available in the abdomen area of the Lixia River. On the basis of the actual volume of water abstracted from the Yangtze River, the amount of water available for use by the Yangtze River is estimated by cutting off the amount of water replenished to the river under the guarantee of the downstream water consumption target. By contrast, the water level control method is used to calculate the available quantity of Huai River water. The multiyear average available water resources are determined by

Available Groundwater
The total amount of groundwater resources is the sum of various recharge amounts entering the pilot evaluation area. In particular, atmospheric rainfall naturally recharges about 58.16% of groundwater volume, with the concentration of rainfall during the flood season accounting for about 67% of the annual rainfall. Therefore, this situation results in groundwater recharge during the flood season accounting for 36.33% of the annual recharge. The pilot area is located on a plain, and no baseflow recharge occurs from rivers in the hilly areas in groundwater resource quantity. Thus, no duplicate amount is deducted when determining the amount of groundwater resources. The pilot region has 32.75 million m 3 of groundwater resources, and 58.16% of atmospheric rainfall naturally infiltrates into those resources. The amount of groundwater available in the pilot evaluation region is 0.026 billion m 3 in accordance with the coefficient approach used to determine the extractable amount of groundwater resources.

Available Transit Water
The amount of water in transit is divided into two parts in accordance with the type of water source: Yangtze River and Huai River. The amount of river water that can be used is estimated by calculating the actual use of river water. In the pilot area, the actual available quantity of Yangtze River water includes the amount of water abstracted directly from the Yangtze River for industrial, agricultural production, and domestic use and the amount of river water available in the abdomen area of the Lixia River. On the basis of the actual volume of water abstracted from the Yangtze River, the amount of water available for use by the Yangtze River is estimated by cutting off the amount of water replenished to the river under the guarantee of the downstream water consumption target. By contrast, the water level control method is used to calculate the available quantity of Huai River water. The multiyear average available water resources are determined by calculating the difference between the volume under the monthly multiyear average water level of Gaoyou Lake and Shaobo Lake and the volume under the normal water storage level. The total available volume of water in transit in the pilot area is calculated to be 356 million m 3 . Of which, 210 million m 3 is available for the Yangtze River and 146 million m 3 for the Huai River.

Total Available Water
The calculation of total water resource availability includes surface water availability, groundwater availability, and transit water availability. In particular, the sum of surface water availability and groundwater availability minus the amount of reuse provides the total amount of local water resources available for use. In accordance with the calculation result, the total amount of water resources available in the pilot area is 359 million m 3 .

Water Quality Analysis
Within the pilot area, pH assay results yielded pH values of 7.18 for the Grand Canal (DBS6, DBS4), 7.40 for Baoying Lake (DBS3, DBS2), 6.91 for Baima Lake (DBS1), and 7.26 for the Yunxi River (DBS5). Furthermore, the total hardness of the Grand Canal is 141.25-149.00 mg/L, (soft water). The total hardness of Baoying Lake is 90.25-101.25 mg/L, (soft water). The total hardness of Yunxi River is 161.00 mg/L, (soft water). The total hardness of Baima Lake is 158.25 mg/L, (soft water). One of the surface water information tables is provided in Table 2, with the Yue Tang Reservoir having the smallest content of all ions, followed by the Yangtze River and the Grand Canal, whereas Gaoyou Lake has the largest. Moreover, the mineralization of the Grand Canal, Baoying Lake, the Yunxi River, and Baima Lake was 332.46-341.36, 270.92-365.42, 331.34, and 342.37 mg/L, respectively. This study shows that surface water in the pilot area largely exhibits low mineralization. The water chemistry type of the surface water is mostly calcium bicarbonate, sodium bicarbonate, and magnesium bicarbonate. The water body predominantly contains bicarbonate with a certain amount of Na and K ions. It exhibits low mineralization and total hardness. Most of the monitored 23 groundwater wells have pH values between 7.00 and 7.50, which is water quality Classes I-III. Point JC11 is not informative because the data and assays are unavailable given that they were cleared by external factors after the point was set. Groundwater information is provided in Table 3. The total hardness monitoring values for groundwater range from 106.75 mg/L to 342.00 mg/L, with an average value of 216.20 mg/L. The lowest value for total hardness is 106.75 mg/L, which occurs at point JC21, while the highest value is 342.00 mg/L, which occurs at point JC13. Moreover, mineralization monitoring values range from 208.67 mg/L to 1003.94 mg/L, with an average value of 517.81 mg/L. The lowest mineralization value of 308.67 mg/L occurs at point JC5, while the highest value of 1003.94 mg/L occurs at point JC20. The distributions of total groundwater hardness and mineralization contours in the pilot evaluation area are shown in Figure 7. Combined with the single-factor evaluation method, groundwater chemistry types in the pilot evaluation area are predominantly calcium bicarbonate, sodium bicarbonate, and magnesium bicarbonate.

Uneven intra-annual distribution of rainfall and high interannual variability
Water resources in the pilot evaluation area are largely formed by atmospheric rainfall. Rainfall varies considerably from year to year, with an annual maximum value of 1420.30 mm (1991) and a minimum value of 496.80 mm (1978). The ratio of maximum to minimum rainfall is 2.87. Within a year, rainfall is unevenly distributed and mostly concentrated during the flood season, with May to September accounting for 67.17% of the annual rainfall.

2.
Uneven intra-annual distribution of evaporation and decreasing total year by year The intra-annual distribution of evaporation from the water surface is highly uneven due to temperature changes, i.e., high in summer and low in winter. Moreover, evaporation in the northern Yangtze River Delta has exhibited a decreasing trend over the years, decreasing by an average of 3.3 mm per year. On the one hand, the greenhouse effect caused by a large amount of industrialized pollution in the region over the past years has led to global warming, and temperature rise will, to a certain extent, lead to an increase in evaporation. On the other hand, the interaction between atmospheric pollution and specific climatic conditions creates a huge amount of hazy weather, which considerably reduces the intensity of insolation, and consequently, water surface evaporation. Therefore, the intensity of insolation exerts a greater influence on evaporation trend.

3.
Uneven temporal distribution and low availability of local runoff with high levels of transit water Consistent with rainfall, local runoff is highly variable from year to year. The incoming water from the upper and middle reaches of the basin is largely concentrated during the flood season and mostly discharges into the river and sea, forming abandoned water without being utilized. In addition, transit water is an important part of local water resource utilization, primarily from the upper reaches of Yangtze River and Huai River rainfall and flood water disposal. The abundance of water in transit has been the greatest resource advantage of the region, providing unique conditions for its development.

4.
Overall good surface water and groundwater quality The water quality of the Baoying section of the Grand Canal is relatively stable, i.e., II to III, and mostly II. The water quality of Baoying Lake and Baima Lake is III to IV, and the water quality of Yunxi River is III toIV. Most substandard months are during the non-flood season, and all of their values exceed the standard for permanganate index. Groundwater in the pilot evaluation area is Class III or better, with mineralization monitoring values ranging from 208.67 mg/L to 924.65 mg/L, and an average value of 517.81 mg/L. Therefore, this water is classified as freshwater, and water chemistry type is predominantly HCO 3 -Ca·Na and HCO 3 -Ca·Mg.

Conclusions
The northern Yangtze River Delta experiences significant variations in rainfall over time, in accordance with the analysis of multiyear rainfall and evaporation monitoring data. About 50% of the annual rainfall falls between June and August, causing frequent flooding. Floods and droughts still pose a hazard to the area, although water conservation projects have helped avert and alleviate disasters to a certain extent. The calculation of total water resources in the area shows that low local runoff and high transit water are the basic characteristics of water resources in the pilot area. Local water resources cannot meet water requirements, and although transit water is high, it varies considerably from year to year and cannot guarantee water security. Moreover, some problems with water wastage persist in the area. Meanwhile, the demand for water resources is constantly increasing with the rapid development of the local economy and society. Therefore, to guarantee sustainable development, drawing a red line for the development and use of water resources and strictly enforcing control on total water consumption are necessary.
In accordance with the water quality analysis of groundwater, the overall water quality assessment results are relatively good, indicating that water pollution control measures have been implemented well in recent years under the national "14th Five-Year Plan." However, as human living conditions continue to improve, the demands for water resources will increase in quantity and quality, and thus, laxity should have no room in water resource management. A comprehensive evaluation of water resources is a prerequisite for securing regional water resource management. In this regard, this study systematically presents the entire evaluation process by using the pilot area as an example. Future research will extend to the entire Yangtze River Delta, laying a solid foundation for the effective management of water resources and promoting the sustainable and healthy development of Yangtze River Delta.