Untreated Rainfall Runoff Water Quality Characteristics of Different Land Uses in Infilled Lake Areas—The Case of Wuhan Shahu
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Sample Collection
2.3. Data Analysis
3. Results and Discussion
3.1. Spatial Variation in EMCs
3.2. Correlation
3.3. Concentration Variation
4. Conclusions
- 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.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Serial Number | Rainfall Date | Sample Size |
---|---|---|
1 | 17 June 2015 | 16 |
2 | 19 September 2015 | 14 |
3 | 28 October 2015 | 13 |
4 | 15 November 2015 | 14 |
5 | 1 December 2015 | 16 |
6 | 29 March 2016 | 11 |
7 | 20 April 2016 | 15 |
8 | 15 May 2016 | 17 |
9 | 31 May 2016 | 16 |
10 | 19 June 2016 | 16 |
Events | Land-Use Types | Date | COD (mg/L) | TN (mg/L) | TP (mg/L) | ADD (d) | Rainfall Intensity (mm/h) | Duration (h) |
---|---|---|---|---|---|---|---|---|
1 | Residential | 17 June | 40.5 | 2.79 | 0.29 | 3 | 1.3 | 2.3 |
Roads | 30.17 | 0.50 | 0.76 | |||||
Green space | 61.14 | 0.97 | 0.92 | |||||
Commercial | 7 | 0.50 | 1.23 | |||||
2 | Residential | 19 September | 75.5 | 7.26 | 0.56 | 6 | 4.2 | 6.3 |
Roads | 29.67 | 4.09 | 0.21 | |||||
Green space | 9.33 | 2.54 | 0.78 | |||||
Commercial | 49.67 | 10.76 | 0.55 | |||||
3 | Residential | 28 October | 137 | 2.7 | 0.64 | 2 | 5 | 6.8 |
Roads | 74 | 2.93 | 0.68 | |||||
Green space | 3 | 2.27 | 0.31 | |||||
Commercial | 10.5 | 0.95 | 0.43 | |||||
4 | Residential | 15 November | 38.5 | 4.15 | 0.41 | 4 | 3.6 | 4.5 |
Roads | 62 | 2.03 | 0.23 | |||||
Green space | 42.33 | 0.73 | 0.54 | |||||
Commercial | 60.5 | 2.78 | 0.59 | |||||
5 | Residential | 1 December | 29.25 | 1.53 | 0.36 | 5 | 4.8 | 2.5 |
Roads | 44.33 | 1.97 | 0.36 | |||||
Green space | 37.67 | 2.17 | 0.60 | |||||
Commercial | 59.17 | 0.52 | 0.31 | |||||
6 | Residential | 29 March | 94 | 0.5 | 0.25 | 2 | 2.7 | 3 |
Roads | 61 | 3.2 | 0.49 | |||||
Green space | 67 | 2.3 | 0.98 | |||||
Commercial | 26.83 | 1.88 | 0.52 | |||||
7 | Residential | 20 April | 23 | 0.47 | 0.52 | 2 | 6.5 | 7 |
Roads | 47 | 7.13 | 0.67 | |||||
Green space | 64 | 1.07 | 0.32 | |||||
Commercial | 47.17 | 0.98 | 0.46 | |||||
8 | Residential | 15 May | 15.2 | 0.86 | 0.26 | 13 | 9.5 | 9 |
Roads | 52.33 | 0.7 | 0.27 | |||||
Green space | 84.33 | 0.63 | 0.28 | |||||
Commercial | 66 | 1.65 | 0.77 | |||||
9 | Residential | 31 May | 52.75 | 4.08 | 0.64 | 3 | 8.5 | 8 |
Roads | 52.67 | 1.83 | 0.13 | |||||
Green space | 40.33 | 1 | 0.30 | |||||
Commercial | 35.72 | 0.83 | 0.68 | |||||
10 | Residential | 19 June | 34.5 | 2.55 | 0.32 | 2 | 12.5 | 12 |
Roads | 28.33 | 1.33 | 0.53 | |||||
Green space | 46 | 2.03 | 0.24 | |||||
Commercial | 24.58 | 0.60 | 0.32 |
COD (mg/L) | TN (mg/L) | TP (mg/L) | |
---|---|---|---|
Residential | 54.02 | 2.69 | 0.42 |
Road | 48.05 | 2.57 | 0.43 |
Green space | 45.51 | 1.57 | 0.53 |
Commercial | 38.71 | 2.15 | 0.58 |
Land Use Type | Pollutant | ADD (d) | Rainfall Intensity (mm/h) | Rainfall Duration (h) | Samples Number |
---|---|---|---|---|---|
Commercial | COD | 0.267 * | −0.009 | −0.67 | 55 |
TN | 0.191 | −0.280 * | −0.066 | ||
TP | 0.187 | −0.42 | −0.009 | ||
Residential | COD | −0.294 | −0.216 | −0.111 | 29 |
TN | −0.176 | −0.115 | −0.009 | ||
TP | −0.184 | −0.06 | 0.001 | ||
Green space | COD | 0.084 | 0.2 | −0.059 | 38 |
TN | 0.006 | 0.034 | 0.061 | ||
TP | 0.16 | −0.386 * | −0.321 * | ||
Roads | COD | −0.125 | −0.016 | −0.3 | 35 |
TN | −0.133 | 0.017 | 0.076 | ||
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
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 StyleWu, 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 StyleWu, 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