Effects of Agricultural Production Patterns on Surface Water Quality in Central China’s Irrigation Districts: A Case Study of the Four Lakes Basin
Abstract
1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Sources and Monitoring Point Layout
2.3. Research Methods
- (1)
- Determination of Water Quality
- (2)
- Estimation of Water Yield and Different Pollution Loads in the FLB
Study Area | Pollutants | AFMs | Source | |||
---|---|---|---|---|---|---|
Rice Cultivation (RC) | Rice-Crayfish Farming (RCF) | Freshwater Aquaculture (FA) | Dryland Cropping (DC) | |||
Qianjiang City | TN | - | 9.7 | - | - | [25] |
TP | - | 2.2 | - | - | ||
Qianjiang City | TN | 11.84 | 4.46 | - | - | [33] |
TP | 0.51 | 0.68 | - | - | ||
Honghu City | TN | - | - | 27.61 | - | [34] |
TP | - | - | 7.33 | - | ||
Three Gorges Reservoir Area | TN | - | - | - | 17.1 | [35] |
TP | - | - | - | 2.3 | ||
Xiantao City | TN | 21.60 | - | - | 21.22 | [36] |
TP | 2.50 | - | - | 2.05 | ||
This Research | TN | 16.57 | 7.10 | 28.05 | 18.75 | Observation Data |
TP | 1.49 | 2.55 | 7.41 | 2.09 | ||
Mean | TN | 16.67 | 7.09 | 27.83 | 19.02 | |
TP | 1.5 | 1.81 | 7.37 | 2.15 |
2.4. Statistical Analysis
3. Results
3.1. Dynamics of Land Use Types and AFMs
3.2. Dynamics of N/P-Loads Within Basin
3.3. Inter-Annual Variations in Water Quantity and Quality
3.4. Intra-Annual Variations in Water Quantity and Quality
4. Discussion
4.1. Analysis of Driving Factors for N/P Concentrations Changes in the FLMC
- (1)
- From the perspective of AFMs, RCF, RC, FA and LPB were the four AFMs with the largest proportions and changes in agricultural N/P-loads (Figure 5). Correlation analysis results (Figure 8) show that the N/P-load from AF was negatively correlated with that from RCF, while it was significantly positively correlated with the N/P-loads from FA and LPB (p ≤ 0.001, correlation coefficient > 0.89). Meanwhile, the TN/TP concentrations in the FLMC were also significantly positively correlated with the N/P-loads from AF (p ≤ 0.001, correlation coefficient > 0.84). It can be seen that AFM adjustments in the FLB had promoted a reduction in basin-wide N/P-loads and a decrease in FLMC N/P concentrations to a certain extent. Specifically, from 2017 to 2023, the proportion of FA area decreased by 4%, the proportion of DC area decreased by 11%, and the proportion of RCF area increased by 14% (Figure 3c). Correspondingly, the total N-loads in the FLB decreased by 2432 tons and the total P-loads decreased by 540 tons (Table 2), ultimately driving a continuous decline in N/P concentrations in the FLMC (Figure 9) [19,21]. Notably, although the TN/TP concentrations in the FLMC are negatively correlated with RCF, this does not justify the unlimited expansion of RCF. As of 2023, RCF had become the primary pollution source, contributing approximately 42% of the total N/P-loads (Table 2). Its potential impacts on the regional water environment cannot be overlooked, and the associated pollution risks require further in-depth research.
- (2)
- From the perspective of hydrological conditions, rainfall (P), main canal discharge (S), and branch canal discharge (R) affect N/P concentrations by altering water dynamic conditions. On the one hand, the high runoff caused by the annual peak rainfall (June–July) during the flood season (April–September) can reduce the N/P concentrations in the main canal through a dilution effect [51]. On the other hand, the ecological water supplement from the Yangtze River-Han River Water Diversion Project has increased the multi-year average drainage volume of the main canal from 6.0 billion m3 to 7.2 billion m3, further amplifying the dilution effect [44,46].
- (3)
- From the perspective of spatial differences in pollutant inputs, the N/P concentrations in the main canal exhibit a “first increase, then decrease” trend along the “canal head-middle canal-canal tail” gradient (Figure 10), which essentially reflected the uneven spatial distribution of agricultural pollution in the basin.
4.2. Why Did Honghu Lake’s Water Quality Deteriorate During 2017–2023?
- (1)
- External Inputs: A Reduction in Quantity Does Not Equal Qualitative Safety
- ①
- The background concentrations of N/P in the FLMC remain relatively high. Despite a slight decrease in the FLMC’s N/P concentrations (TN: 5 mg/L to 3 mg/L; TP: 0.21 mg/L to 0.17 mg/L), these concentrations were still much higher than those of Honghu Lake before disturbance (Period 1: TN 0.93 mg/L, TP 0.04 mg/L) (Figure 6). When such relatively polluted water enters Honghu Lake, it still raises the lake’s nutrient background value. Moreover, as a semi-enclosed lake, Honghu Lake has slow water exchange, making it difficult to achieve rapid purification [8,16]. For instance, the TN concentration in the FLMC in 2023 was still 1.5 times that of Honghu Lake in 2017 (Figure 9), which means that even with a reduction in inflow volume, the FLMC still acts as a “nutrient source” rather than a “purification channel” for Honghu Lake.
- ②
- Inadequate control of NSP in the central basin. The central FLB, dominated by RCF and FA, remains the main source of N/P-loads [42]. Agricultural wastewater generated in this region was discharged into Honghu Lake through the FLMC and its tributaries, continuously supplementing the lake’s external nutrient pool and offsetting the improvement effects brought by load reductions from other pollution sources. This was well evidenced by the higher N/P concentrations in the middle section of the FLMC and the northern waters of Honghu Lake (Figure 10).
- ③
- Short-term pollution pulses from the demolition of net enclosures/polders further exacerbate external pressure. Although the two-phase demolition projects (2015–2017, 2019–2021) eliminated direct aquaculture pollution on the lake surface, the high-concentration wastewater (TN ≈ 15 mg/L, TP ≈ 1.2 mg/L) remaining in the abandoned net enclosures was discharged into the lake in a concentrated manner in the short term, causing a 15–20% short-term increase in the lake’s TN/TP concentrations [56,57]. Meanwhile, the disturbance caused by construction machinery also triggers the release of nutrients from surrounding sediments, forming a “legacy pollution effect” that lasts for 3–5 years and further increases the external pollution load [58].
- (2)
- Internal Release: Increment of Hidden Pollution
- (3)
- Other Potential Factors: Unquantified Variables
5. Conclusions and Prospects
- (1)
- Conclusions and Recommendations
- Compared with period 2010–2016, the AFMs of the FLB achieved significant optimization during 2016–2023. The proportion of RC area under sustainable increased by 14%, while the areas of DC with high fertilizer input and FA with high pollution risk decreased by 11% and 4%, respectively.
- Optimization to the AFMs can significantly reduce N/P loads within the basin. This was specifically reflected in the following: NPS N/P loads decreased by 11–13%; N/P loads in the FLMC reduced by 22.94% and 3.15%, respectively; and the N/P inputs into Honghu Lake via the FLMC decreased synchronously by 22.04% and 2.02%. From 2016 to 2023, due to the lower N/P loads in the basin, the water quality of the FLMC was continuously optimized, with the TN/TP concentrations decreasing by approximately 2 mg/L and 0.04 mg/L.
- Despite the reduction in external pollution, the TN/TP concentrations in Honghu Lake still increased by 0.46 mg/L and 0.06 mg/L, respectively. This reflected the constraints from climate variability, natural disasters, internal nutrient release from sediments, and the decline of water environment carrying capacity, highlighting the complexity of lake ecological restoration.
- The pollution control and water environment improvement of the FLB and Honghu Lake can be advanced through three key measures: first, establish an agricultural pollution control system of “source control + process regulation” and promote green agricultural technologies; second, conduct comprehensive pollution prevention and control centered on “external pollution prevention and internal pollution treatment”; third, enhance water environment carrying capacity via the dual-path of “controlling pollution input, and increasing environmental capacity”.
- (2)
- Limitations and Prospects
- The study focused on the impact of changes in agricultural models on the water quality of rivers and lakes, with insufficient consideration of other environmental factors such as atmospheric deposition and climate change. This led to an incomplete analysis of the causes of water quality deterioration in Honghu Lake. It will be necessary to systematically quantify the contribution weights of various factors to the water quality changes in Honghu Lake in the future.
- Dynamic models such as the Soil and Water Assessment Tool (SWAT) and Hydrological Simulation Program-Fortran (HSPF) were not integrated. As a result, the long-term responses of the ecosystem to future agricultural policies cannot be simulated, which limited the predictive ability of the research results.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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LLP | N-Load (t/a) | Load Proportion (%) | P-Load (t/a) | Load Proportion (%) | |||||
---|---|---|---|---|---|---|---|---|---|
AFM | 2016 | 2023 | 2016 | 2023 | 2016 | 2023 | 2016 | 2023 | |
FA | 9120.02 | 5505.36 | 38.3 | 25.9 | 2416.44 | 1471.32 | 58.0 | 40.5 | |
DC | 9382.83 | 6735.64 | 39.4 | 31.6 | 847.37 | 606.48 | 20.3 | 16.7 | |
RCF | 5282.94 | 9045.31 | 22.2 | 42.5 | 905.65 | 1551.37 | 21.7 | 42.8 |
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Hu, Y.; Wang, Z.; Shao, D.; Li, R.; Zhang, W.; Long, M.; Song, K.; Cao, X. Effects of Agricultural Production Patterns on Surface Water Quality in Central China’s Irrigation Districts: A Case Study of the Four Lakes Basin. Sustainability 2025, 17, 8838. https://doi.org/10.3390/su17198838
Hu Y, Wang Z, Shao D, Li R, Zhang W, Long M, Song K, Cao X. Effects of Agricultural Production Patterns on Surface Water Quality in Central China’s Irrigation Districts: A Case Study of the Four Lakes Basin. Sustainability. 2025; 17(19):8838. https://doi.org/10.3390/su17198838
Chicago/Turabian StyleHu, Yanping, Zhenhua Wang, Dongguo Shao, Rui Li, Wei Zhang, Meng Long, Kezheng Song, and Xiaohuan Cao. 2025. "Effects of Agricultural Production Patterns on Surface Water Quality in Central China’s Irrigation Districts: A Case Study of the Four Lakes Basin" Sustainability 17, no. 19: 8838. https://doi.org/10.3390/su17198838
APA StyleHu, Y., Wang, Z., Shao, D., Li, R., Zhang, W., Long, M., Song, K., & Cao, X. (2025). Effects of Agricultural Production Patterns on Surface Water Quality in Central China’s Irrigation Districts: A Case Study of the Four Lakes Basin. Sustainability, 17(19), 8838. https://doi.org/10.3390/su17198838