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Article

Untreated Rainfall Runoff Water Quality Characteristics of Different Land Uses in Infilled Lake Areas—The Case of Wuhan Shahu

1
College of Design & Engineering, National University of Singapore, Singapore 119077, Singapore
2
School of Architecture, Southeast University, Nanjing 210096, China
3
School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China
4
College of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China
*
Author to whom correspondence should be addressed.
Water 2024, 16(2), 212; https://doi.org/10.3390/w16020212
Submission received: 15 November 2023 / Revised: 19 December 2023 / Accepted: 3 January 2024 / Published: 7 January 2024
(This article belongs to the Section Hydrogeology)

Abstract

:
Fast urbanization in developing countries contributes to heavier pollution in urban water environments, as urbanization enhances land development and even requires lake filling to meet urban land needs, which produces significant water runoff pollution. Centralized construction brings heavier non-point source pollution, which is one of the most crucial types of pollution in urban areas. However, the pollution caused by urbanization in infilled lake areas is lack of attention. To reduce the negative impact of pollution brought on by urbanization, it is important to monitor the characteristics of runoff water qualities and their relationship with rainfall features. In this study, runoff water quality was monitored from 10 rainfall events, totaling 157 samples in the Wuhan Shahu area, an infilled lake area, to characterize the pollutant event mean concentrations (EMCs) and to explore the different effects of land-use types. COD (chemical oxygen demand), TN (total nitrogen), and TP (total phosphorus) were selected as water quality indicators. The results show that the pollutants have a significant spatial variation. Residential runoff had the largest COD (averaged EMC = 54.02 (mg/L)) and TN (averaged EMC = 2.69 (mg/L)) pollution, while road runoff had the second largest COD (averaged EMC = 48.05 (mg/L)) and TN (2.572 (mg/L)) pollution. The TP pollution level is opposite to COD and TN, as commercial and green spaces have heavier pollution, while the differences in TP pollution levels between the four types of land are not significant. The release of organic matter and nitrogen is closely related to human activities on land types, while phosphorus emission is relatively stable, indicating that it is not easily affected or controlled. In addition, the variation in pollutants between land types is also related to a certain extent. The correlation analysis shows that parameters like antecedent dry days (ADDs), rainfall intensity, and rainfall duration most significantly affect the EMCs of commercial and green spaces. Phosphorus pollutants on roads are harder to reduce. These results may help researchers to identify the specific pollutant source and find an effective method to reduce pollution in infilled lake areas and other areas.

1. Introduction

Under the robust growth of developing economies, the demand for land development has surged, leading some cities to fill in lakes to meet this demand. For example, Huludao City reclaimed land for an industrial area in 2006, and Dongting Lake in Yueyang City has shrunk by two-thirds since it was developed in 1960. In the past 60 years, the number of lakes in Wuhan City has decreased from 127 to 38. Even after China introduced a document banning lake reclamation in 2016, 67 major cases of violation were found in 2022. However, the consequences of this action include worsening water scarcity and the degradation of water environments, which have become prevalent issues in these areas [1,2,3,4]. The increasing number of pollutants introduced by human activities exceeds the capacity of reduced water bodies to contain the pollutants, resulting in not only reduced water sources but also increased pollution, and may cause water bodies to become unusable. This phenomenon is especially evident in infilled lake areas. The purpose of filling in the lake district area is to solve the problem of insufficient land caused by urban population growth. Therefore, the infilled lake district is often characterized by high building density, high population density, and high economic development. For example, the infilled lake area is used to build many residential areas, shopping malls, commercial streets, and other shopping centers. The influx of many residents, coupled with the absorption of the floating population from the nearby population in the business district, puts great pressure on the water environment of the infilled lake area. The quality of storm runoff water will be significantly influenced by urbanization [5,6], as the water will drain into the city’s body of water and destroy the water environment; in turn, this will affect the city’s sustainable development.
Previous studies have characterized stormwater quality, hydrology, and rainfall characteristics and identified various pollutants present in the overland runoff, such as organic matter, heavy metals, suspended solids, and so on [7,8,9]. For example, heavy metals in surface runoff may include zinc, copper, lead, nickel, etc.; the source may be roofs or traffic. There are two common forms of nitrogen pollution: dissolved nitrogen, such as nitrate, and particulate nitrogen, such as particulate organic nitrogen. Nitrogen pollutants might come from vehicle exhaust emissions, fertilizers, or plant rot [10]. The source, types, and forms of pollutants are not simply from one-to-one correspondence, which is one of the reasons why it is difficult to accurately identify pollutants in stormwater runoff. Furthermore, rainfall runoff is a typical non-point source (NPS) pollution, which is well known as an important pollution source of water environments in cities [11,12]. Urban non-point source pollution caused by road runoff is particularly important for infilled lake areas. The extremely high population density of the infilled lake area and the large number of human activities in commercial areas, such as catering, driving, and generating household garbage, will produce many pollutants, ejected into the air or deposited on the road. The impervious water surface of the infilled lake area is directly connected with the water surface of the lake, resulting in the smooth integration of these pollutants into the road runoff when it rains and then, into the lake; as a result, the urban water environment becomes polluted.
Researchers have found that pollutant compositions and runoff process are influenced by rainfall patterns and land characteristics, such as the level of land development and human activities [13,14,15,16]. In rapidly urbanizing cities, stormwater runoff pollution has become a serious issue due to the conversion of forests and water bodies into urban areas, the intensification of human activities, and the increase in impervious surfaces, such as roads and parking lots. A large amount of impervious water is extremely conducive to road runoff formation, and a large amount of rainwater does not penetrate the ground. Additionally, a large amount of pollution produced by human activities, such as domestic waste, car exhaust, and even non-indiscriminate construction waste, will be integrated into the rainwater. Different human behaviors obviously emit different kinds of pollution. These have resulted in significant spatial variations in the runoff quality of different areas and populations as well as variations in the relationship between rainfall characteristics, stormwater runoff quality, and land use. Significant differences were found in TSSs (total suspended solids) and heavy metal concentrations in different urban areas, while TSSs and heavy metals more frequently came from roads [17]. Similar outcomes were found, as researchers pointed out that uncoated zinc-based roofs need more care as they contribute the highest zinc. Atmospheric deposition is an important source of heavy metals [18,19]. This shows that land-use types and human activities in the area influence the rainfall runoff quality, and due to the complex constitution of the pollution source, it is hard to figure out the details [20,21]. Land use influences storm runoff quality and is a feasible way to categorize and find different pollution characteristics [22,23,24]. Rainfall characteristics have an impact on stormwater quality, which is also well known. Parameters such as antecedent dry days and rainfall intensity were found to significantly influence TSS and COD concentrations (longer ADDs and higher rainfall intensity will increase these concentrations) [25]. This may be because a longer ADD allows for more accumulation on the pathway. Weather conditions may also influence the accumulation of pollutants, such as wind velocity being negatively correlated with a heavy metal concentration in stormwater. In winter, heavy snowfall has negative consequences with pollutant wash-off, as snow removal is needed [26,27].
However, there is currently a lack of research on the stormwater quality pattern and its correlation with rainfall characteristics and land-use types in infilled lake areas. This gap in knowledge limits our understanding of the transport properties of pollutants in stormwater runoff from these areas and the impact of rainfall and land-use characteristics on these pollutants. Gaining a comprehensive understanding of the connections between storm runoff quality patterns and different land use types is crucial for formulating effective strategies to mitigate urban stormwater runoff pollution. By examining these interactions, appropriate measures can be implemented to control and manage pollutants in urban areas, ultimately leading to improved water quality and environmental sustainability. Therefore, it is imperative to investigate and analyze these relationships within a rapidly industrialized city, with particular emphasis on the infilled lake area. Such efforts will contribute to enhancing management practices in this specific area, addressing the unique challenges associated with industrialization and reclaimed lakes.
In this study, 10 rainfall events over one year (2015–2016) in the Wuhan Shahu Lake area were tested; in each event, four different types of land use (residential, roads, commercial, and green space) were monitored independently. Composite water quality samples representative of event mean concentrations (EMCs) for COD, TP, and TN were taken. The objectives of this study were to (1) characterize stormwater pollutant EMCs in relation to land-use types and rainfall patterns, and (2) characterize the unique features of the pollution pattern in infilled lake areas by comparing them with other research studies.

2. Materials and Methods

2.1. Study Area

This study was conducted in the Shahu catchment in Wuhan City, China. Wuhan is in the center of the hinterland of China at the intersection of the Yangtze River and the Han River. It is a national historical and cultural city, the central city of central China, and the only subprovincial city. It is an important industrial, science, and education base, a comprehensive transportation hub in the country, and the capital of Hubei Province. Its geographical location is 113°41′~115°05′ east longitude and 29°58′~31°22′ north latitude. The total area is 2,871,525 m2, and it has a subtropical monsoon climate with an average annual temperature of 16.7 °C, the coldest in January, the hottest in July, and an annual precipitation of about 1100 mm. The monitoring point, land-use partition, and area are shown in Figure 1. We selected a sampling site based on land-use type and runoff analysis.
From 1995 to 2010, the lake area in Wuhan’s main urban area decreased by 35.94%. Among the 28 lakes in the main urban area, the water area of South Lake experienced the most significant reduction, followed by Shahu Lake [28]. Shahu Lake, located at 114′36″ E, 30°33′55″ in Xujiapeng Street, Wuchang District, Wuhan City, currently has a water area of 333.1 hectares and is a typical urban lake. Shahu Lake used to be the second largest lake in Wuhan, but people started to enclose the lake and even fill parts of it in for land development due to urbanization driven by population growth. As a result, the water area of the outer Shahu Lake has been reduced by nearly 90%, leading to severe damage to the ecological environment. As early as 1980, the process of infilling Shahu Lake began. For instance, in 1990, Shahu Lake was partially filled in to construct the second Yangtze River Bridge. For decades, the infilling of Shahu Lake rarely stopped. In 1996, the lake was filled with residential buildings. In 2000, a road was built to connect to Hubei University. By 2005, images of Shahu Lake showed that the northeast area of Shahu Lake had completely disappeared. Aquaculture was banned in 2007 due to serious pollution in Shahu Lake. Despite improvements in water quality from the “clean water” project for Shahu Lake during 2007–2009 and the full desilting project in October 2009, the lake is still being filled in. Images show that Shahu Lake has shrunk (Figure 1). Many residential areas were built, mainly in infilled areas. Green land parks and commercial gathering places were built around the lake body to meet the living needs of surrounding residents. The accumulation of many buildings and complex traffic, as well as the direct connection between roads and lake water bodies, make the water of Shahu Lake easily polluted, which also increases the importance of such research for the Shahu Lake infilled land region.
This study selected the Shahu catchment area and divided it into four land-use categories (residential, roads, commercial, and green space) according to Urban land classification and planning construction land standards GB 50137-2011 [29].

2.2. Sample Collection

Composite rain samples were taken at the beginning of each rainfall, describing 100% of the rainfall process. The sample taken during the rainfall on 17 June 2015 in the road area was different. When it began to rain, samples were collected using clean plastic bottles placed flat on the road until the rain subsided. Three samples were collected for each water quality indicator at each collection point to minimize errors. Since the samples represented the entire runoff process, the pollutant concentration represents the EMCs of each pollutant. On 17 June 2015, in a road area, samples were collected at 5-min intervals for the first 40 min and then at 10-min intervals thereafter, with each interval lasting the corresponding interval.
After sampling, all bottles were stored in a portable fridge to preserve temperatures lower than 4 °C and immediately delivered to the lab for analysis. COD, TN, and TP were tested using spectrophotometry with the HACH DR3900 instrument. A known amount of potassium dichromate solution was added for COD testing, and the COD value was determined by spectrophotometry. For TP, persulfate dissolved the sample and oxidized all the phosphorus to orthophosphate under neutral conditions. Under acidic conditions, orthophosphate reacts with ammonium molybdate to form phosphomolybdenum heteropoly acid in the presence of antimony salt, and the acid is immediately reduced by ascorbic acid, resulting in the formation of a blue complex. For TN, the persulfate oxidation method accompanying the instrument was used in accordance with the supporting operating instructions.

2.3. Data Analysis

The data collected were sorted by the date of rainfall event and land-use type (Table 1). For each rainfall event, the average arithmetical value of the EMC value of the same pollutant in the same type of land but in different locations was calculated as the average EMC value of the pollutant in that type of land in the rainfall event. This method simplifies the data analysis process and fulfills the needs for land type analysis. The rainfall characteristics of corresponding events were integrated with the aforementioned data, and Pearson correlation coefficient analysis was conducted using IBM SPSS Statistics 2.

3. Results and Discussion

3.1. Spatial Variation in EMCs

The average arithmetical EMC values of different rainfall events were compared to assess the differences between land-use types (Table 2).
Table 3 shows the average EMCs of four land-use types. Regarding chemical oxygen demand (COD), residential areas had the highest EMC values, followed by roads, green spaces, and commercial areas. A similar trend was observed for total nitrogen (TN), with residential areas having the highest EMC values, followed by roads, commercial areas, and green spaces. The only notable difference was the significantly lower TN pollution in green spaces compared to the other three land-use types. The sources of COD and TN in urban cities are usually cooking and traffic [30,31]. Cooking can release a series of cooking aerosols, which mainly consist of organic matter, and rainfall will bring them to runoff [30,32]. It was proposed that vehicular sources (fossil fuel combustion) were the main cause of the notable increase in total nitrogen [33]. This explains why residential areas exhibit the highest EMC values for COD and TN, followed by roads. The pollution level of total phosphorus (TP) is opposite to that of COD and TN, with commercial and green spaces showing higher pollution levels. However, the differences in TP among the four land-use types are not significant. This trend is predictable, as phosphorus in commercial and green spaces can come from fertilizers, washing detergents, and soaps [34,35]. Moreover, in Shahu Lake’s infilled land area, commercial areas are mostly close to the green spaces, with some even together, which may cause pollutant transfer. As the differences between the four land-use types in COD and TN are more significant than for TP, it can be concluded that the release of organic matter and nitrogen is closely related to human activities on different land types and can be mitigated with policy measures. For example, governments can reduce TN emissions by limiting the number and types of vehicles and by promoting the use of public transport. Through community education, setting up many centralized/decentralized garbage collection points can reduce possible organic pollution. Regular cleaning of green spaces, commercial areas, and street trees on both sides of the road can be performed to prevent the possible accumulation of pollutants. On the other hand, phosphorus emissions are relatively stable, with each land-use type releasing a similar quantity of pollutants, indicating that it is not easily affected or controlled, as it may stem from routine activities. This may cause difficulty in identifying the source and setting targeted policies. The overall tendency variation is similar in some reports [26] but different in others [36,37]. This results in the EMC distribution being specific to different areas, which suggests the importance of conducting surveys in each area. Infilled lake areas, such as Shahu Lake, lack this kind of survey, while the lake’s water quality is menaced by untreated rainfall runoff.
Examining the interannual changes in different indicators revealed some correlations between COD levels in residential and commercial areas and TN levels in residential and road areas (Figure 2). From 19 September 2015 to 31 May 2016, there was an inverse relationship between COD levels in residential and commercial areas. When residential COD levels were relatively high, commercial COD levels tended to be relatively low, and vice versa. Considering the source of pollutants, this correlation may be caused by the migration of people based on their dining choices. During periods when people concentrated on cooking at home, fewer people dined in commercial areas, and vice versa. However, this issue is quite complex and has many influencing factors. All behaviors that may affect the emission of organic matter become possible influencing factors. We tried to find pollution behaviors that could be linked to two different land types. For example, the COD level of the commercial area in winter has increased significantly, and the statistical data of China’s catering industry also show that catering turnover in winter is significantly higher than during the rest of the year. Seasonal factors and travel patterns could influence this phenomenon. The complexity of these phenomena can be seen in the extremely high COD concentrations observed in residential areas in October. This rainfall does not have a very high ADD value; the COD levels of commercial and green areas are very low, but the road is relatively high. This behavioral trait is probably the result of a short influx of people. In general, this part of the content is complex but worthy of discussion and in-depth study. We hope that there will be a detailed study on this in the future; such a study may require the collection of a large amount of data, including questionnaires, continuous observation of rainfall events, surveys of human activities during rainfall, surveys of commodity types in commercial areas, and so on.

3.2. Correlation

We used Pearson’s correlation to analyze the relationships between the EMCs and rainfall characteristics. The storm characteristics include ADDs, rainfall intensity, and rainfall duration. The correlation of EMCs for each type of land use with the rainfall characteristics is shown in Table 4. The rainfall characteristics are related to the EMCs in commercial and green spaces (p < 0.05). For commercial, ADD is positively correlated with the EMC of COD, and rainfall intensity is negatively correlated with TN. Rainfall intensity and rainfall duration are both negatively correlated with the EMC of TP in green space. Other correlations are not obvious (p > 0.05). Except for ADD, other parameters were negatively correlated with EMCs, which is similar to other reports [25,36]. The government can help reduce the pollutant concentration of road runoff during rainfall by introducing policies to regularly clean the road or sprinkle a small amount of water to shock the accumulated pollutants and make them flow into the sewer pipe. ADD allows the accumulation of a series of pollutants that rainfall flow washes away.
However, other studies have presented different opinions, suggesting that higher rainfall intensity contributes to larger pollutant concentrations [35,38]. Vegetation contributes to stormwater runoff pollution in residential areas, especially for phosphorus [39]. Some researchers have found that removing leaves significantly reduces nutrient concentrations in rainfall runoff [40]. The greater intensity of rainfall enhances the ability of rainwater to wash away pollutants, and it is easier to wash away pollutants concentrated on the surfaces of leaves [33]. Nonetheless, the sampling sites in this study were deliberately located far away from areas with dense vegetation (Figure 3). Additionally, in China, the trees in parks and residential buildings are often cleaned and watered by experts, minimizing the accumulation of pollutants on leaves. This might explain the observed negative correlation.

3.3. Concentration Variation

Figure 4 illustrates the changes in pollutant concentrations of different types of pollutants in road runoff during the 17 June rainfall event. The three pollutants exhibit very similar trends, but the peak value of total phosphorus is later than that of COD and total nitrogen. Because the samples collected from the same rainfall have the same rainfall characteristics, the degree of erosion of different pollutants on the road is consistent. The pollutants on the road are affected by the airflow in the car; they are difficult to completely and firmly deposit on the ground and relatively easy to wash, which also leads to a very similar concentration change. Due to the same rainfall characteristics, it is more challenging to wash away the source of phosphorus pollutants. The concentration of TP has the highest variation amplitude (more than seven times), while TN has the lowest variation amplitude (fewer than four times).

4. Conclusions

The Shahu Lake region is experiencing high-intensity engineering construction. The artificial surface takes up 50 percent of the Shahu Lake basin. It is a mixed residential and commercial area, with the commercial area around the lake surrounded by the outer residential area. The innermost layer is a mixed area, with a commercial area and green space. The lake is directly connected to the innermost mixing area, and the impervious pavements in the commercial area and green space are directly connected to the lake. This layout leads to a threat to the lake’s body of water from runoff. Coupled with the reduced total body of water caused by the lake-infilling process, the ability of the body of water to withstand pollutants continues to deteriorate. Understanding the pattern of stormwater runoff pollution in such plots is extremely important. Stormwater was monitored from 10 events over one year in the Wuhan Shahu Lake area. Sampling points are classified into four land-use types: residential, commercial, roads, and green space. We set up sampling points in different land-use types, collected samples in the field during rainfall events and sent them back to the laboratory for testing COD, TN, and TP indexes. Meanwhile, data such as rainfall duration, rainfall intensity, and previous dry days were recorded. Using data collation, mapping, and correlation calculations, we studied some properties of rainfall runoff pollutants in the infilled lake area. Conclusions and comments on this research include the following:
  • Residential and road areas contribute more to the COD and TN pollution in the study area, while TP mainly originates from commercial and green space. The TP concentration fluctuated slightly, indicating that it is more challenging to control. There is a correlation between the concentration of pollutants in the residential area and the commercial area to a certain extent. We considered identifying specific sources of COD and TN (e.g., vehicle emissions, roofing, cooking) before establishing which control regulations would be more effective.
  • Pollutant accumulation patterns and ranks differ in different areas. Monitoring specific pollution emissions and understanding the relationship between pollution and other parameters are important for local pollution control in various locations.
  • In this study, antecedent dry days (ADDs), rainfall intensity, and rainfall duration were found to influence the EMC, with only ADDs showing a positive correlation. Commercial and green space areas are more sensitive to rainfall patterns than residential and road areas. Phosphorus pollutants in road areas are more resistant to removal by rainfall.
The characteristics of pavement runoff pollutants are inconsistent with regional changes, and these characteristics play a crucial role in urban environmental control and management, so it is necessary to detect the characteristics of rainfall pavement runoff in various regions. In the literature, there are few studies on lake infilling. This study summarizes the characteristics of rainfall runoff pollution and its correlation with influencing factors in infilled lake areas and provides information for establishing pollution control policies and further research. At the same time, it provides references and data comparisons for other scholars to help them carry out surveys in similar areas in the future. In future research, researchers can control for more comprehensive variables to precisely determine the pollution source or introduce more variables to explore the impact on the water quality of stormwater runoff.

Author Contributions

Conceptualization, L.W. and Y.Z.; methodology, L.W., Y.Z. and S.L.; data collection, Y.L., S.W. and Y.Z.; analysis, L.W. and Y.Z.; Writing—Original draft preparation, L.W.; Writing—Review and editing, Y.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research work was supported by the China Postdoctoral Science Foundation (2021 M700760).

Data Availability Statement

Available data are contained within this article.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Location and land-use types of study area and sampling points and comparison of water body changes in Shahu basin.
Figure 1. Location and land-use types of study area and sampling points and comparison of water body changes in Shahu basin.
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Figure 2. The interannual changes in different indicators.
Figure 2. The interannual changes in different indicators.
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Figure 3. Sampling point photos. The numbers correspond to the sampling points in Figure 1.
Figure 3. Sampling point photos. The numbers correspond to the sampling points in Figure 1.
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Figure 4. Pollutant concentration variation pattern in rainfall event on 17 June 2015.
Figure 4. Pollutant concentration variation pattern in rainfall event on 17 June 2015.
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Table 1. Rainfall event information.
Table 1. Rainfall event information.
Serial NumberRainfall DateSample Size
117 June 201516
219 September 201514
328 October 201513
415 November 201514
51 December 201516
629 March 201611
720 April 201615
815 May 201617
931 May 201616
1019 June 201616
Table 2. Rainfall pollution data.
Table 2. Rainfall pollution data.
EventsLand-Use TypesDate COD (mg/L)TN (mg/L)TP (mg/L)ADD (d)Rainfall Intensity (mm/h)Duration (h)
1Residential17 June40.52.790.2931.32.3
Roads30.170.500.76
Green space61.140.970.92
Commercial 70.501.23
2Residential19 September75.57.260.5664.26.3
Roads29.674.090.21
Green space9.332.540.78
Commercial 49.6710.760.55
3Residential28 October1372.70.64256.8
Roads742.930.68
Green space32.270.31
Commercial 10.50.950.43
4Residential15 November38.54.150.4143.64.5
Roads622.030.23
Green space42.330.730.54
Commercial 60.52.780.59
5Residential1 December29.251.530.3654.82.5
Roads44.331.970.36
Green space37.672.170.60
Commercial 59.170.520.31
6Residential29 March940.50.2522.73
Roads613.20.49
Green space672.30.98
Commercial 26.831.880.52
7Residential20 April230.470.5226.57
Roads477.130.67
Green space641.070.32
Commercial 47.170.980.46
8Residential15 May15.20.860.26139.59
Roads52.330.70.27
Green space84.330.630.28
Commercial 661.650.77
9Residential31 May52.754.080.6438.58
Roads52.671.830.13
Green space40.3310.30
Commercial 35.720.830.68
10Residential19 June34.52.550.32212.512
Roads28.331.330.53
Green space462.030.24
Commercial 24.580.600.32
Table 3. Average EMCs of four types of land use.
Table 3. Average EMCs of four types of land use.
COD (mg/L)TN (mg/L)TP (mg/L)
Residential54.022.690.42
Road48.052.570.43
Green space45.511.570.53
Commercial38.712.150.58
Table 4. Correlation of EMCs with rainfall characteristics. The numbers with * have p < 0.05.
Table 4. Correlation of EMCs with rainfall characteristics. The numbers with * have p < 0.05.
Land Use TypePollutantADD (d)Rainfall Intensity (mm/h)Rainfall Duration (h)Samples Number
CommercialCOD0.267 *−0.009−0.6755
TN0.191−0.280 *−0.066
TP0.187−0.42−0.009
ResidentialCOD−0.294−0.216−0.11129
TN−0.176−0.115−0.009
TP−0.184−0.060.001
Green spaceCOD0.0840.2−0.05938
TN0.0060.0340.061
TP0.16−0.386 *−0.321 *
RoadsCOD−0.125−0.016−0.335
TN−0.1330.0170.076
TP−0.049−0.134−0.078
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Wu, L.; Zhang, Y.; Wang, S.; Liu, Y.; Liu, S. Untreated Rainfall Runoff Water Quality Characteristics of Different Land Uses in Infilled Lake Areas—The Case of Wuhan Shahu. Water 2024, 16, 212. https://doi.org/10.3390/w16020212

AMA Style

Wu L, Zhang Y, Wang S, Liu Y, Liu S. Untreated Rainfall Runoff Water Quality Characteristics of Different Land Uses in Infilled Lake Areas—The Case of Wuhan Shahu. Water. 2024; 16(2):212. https://doi.org/10.3390/w16020212

Chicago/Turabian Style

Wu, Linhong, Yang Zhang, Shaochen Wang, Yaolin Liu, and Siyu Liu. 2024. "Untreated Rainfall Runoff Water Quality Characteristics of Different Land Uses in Infilled Lake Areas—The Case of Wuhan Shahu" Water 16, no. 2: 212. https://doi.org/10.3390/w16020212

APA Style

Wu, L., Zhang, Y., Wang, S., Liu, Y., & Liu, S. (2024). Untreated Rainfall Runoff Water Quality Characteristics of Different Land Uses in Infilled Lake Areas—The Case of Wuhan Shahu. Water, 16(2), 212. https://doi.org/10.3390/w16020212

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