Modeling the sources and retention of phosphorus nutrient in a coastal river system in China using SWAT

Identifying the influence of natural and human factors on seasonal water quality in China: current situation of China's water environment and policy impact

Agricultural production, urbanization, and other anthropogenic activities, the major causes of surface water pollution in China, have dramatically altered hydrological processes and nutrient cycles. Identifying and quantifying the key factors affecting water quality are essential for the better prevention and management of water pollution. However, due to the limitations of traditional statistical analysis methods, it is difficult to evaluate the spatial changes and interactions of influencing factors on water quality. In addition, research on a national scale is difficult, as it involves large-scale and long-term water quality monitoring work. In this study, we collected and collated the monthly average concentrations of four water quality parameters, dissolved oxygen, ammonia nitrogen, chemical oxygen demand, and total phosphorous, based on data from 1547 water quality monitoring stations in China. The combined pollution level of the water quality was assessed using the water quality index. Based on the water quality characteristics, water quality monitoring sites in the dry and wet seasons were grouped using k-means clustering. Eleven environmental factors were evaluated using geodetector software, including six human factors and five natural factors. The results showed that there are high-risk areas for water quality pollution in the eastern and southeastern coastal regions of China in both the dry and wet seasons and that surface water pollution in China is highly spatial heterogenous in both the dry and wet seasons. Among the anthropogenic factors, urban land area is the main factor of water quality pollution in the dry season, and the explanation rate of spatial heterogeneity of integrated water quality pollution index is 20.3%. The number of poultry farms and the area of farmland explained 12.4% and 12.1% of the integrated water quality pollution index in the wet season. The nonlinear relationship between these three anthropogenic and natural factors and their interaction exacerbated water quality pollution. Based on this analysis, we identified the key factors affecting surface water quality in China during the dry and wet seasons, evaluated the achievements of the water environmental protection policies in China in recent years, and proposed future management measures for the effective prevention and control of water quality pollution in high-risk areas.

Dynamic spatiotemporal change of net anthropogenic phosphorus inputs and its response of water quality in the Liao river basin

The Liao river is one of the seven major rivers in China, and the process of phosphorus (P) cycling and change of water quality in this basin are influenced to a considerable extent human activities. In this work, the traditional net anthropogenic phosphorus inputs (NAPI) model was improved by considering the dynamic change of wastewater treatment capacity and P deposition (PDEP) and reclassifying the sources of phosphorus into human P consumption (PHUM), agriculture P consumption (PAGR), livestock P consumption (PANIM) and PDEP to analyze its dynamic spatio-temporal change in the Liao river basin. The results showed that the annual mean NAPI was 785.53 kg P km^-2 yr^-1 (2001-2020), the maximum value was 940.49 kg P km^-2 yr^-1 in 2009, and the minimum value was 586.04 kg P km^-2 yr^-1 in 2001. The temporal variation of NAPI presented an increasing-fluctuation-increasing trend and was basically in line with that of the water quality throughout the three stages, and the spatial distribution of NAPI gradually increased from upstream to downstream. During the two decades, PANIM was the predominant component of NAPI with a share of 64.32%. PHUM, PAGR, and PDEP accounted for 15.97%, 11.54%, and 8.17%, respectively, and the point source NAPI (NAPIP) contributed to 4.95% of NAPI. Further, the INAPI (Improved NAPI) -MR (Multiple Regression) -SWAT (Soil and Water Assessment Tool) model was developed to predict the spatial distribution of P flux under two scenarios. The results showed that the Liao river basin experienced a reduction in P flux to different degrees due to the improvement of the wastewater treatment system, which was more significant in its downstream area. Long-term water quality monitoring is encouraged to develop refined water quality models in the future.

A raster-based estimation of watershed phosphorus load and its impacts on surrounding rivers based on process-based modelling

Quantifying phosphorus (P) load from watersheds at a fine scale is crucial for studying P sources in lake or river ecosystems; however, it is particularly challenging for mountain-lowland mixed watersheds. To address this challenge, we proposed a framework to estimate the P load at the grid scale and assessed its risk to surrounding rivers in a typical mountain-lowland mixed watershed (Huxi Region in Lake Taihu Basin, China). The framework coupled three models: the Phosphorus Dynamic model for lowland Polder systems (PDP), the Soil and Water Assessment Tool (SWAT), and the Export Coefficient Model (ECM). The coupled model performed satisfactory for both hydrological and water quality variables (Nash-Sutcliffe efficiency >0.5). Our modelling practice revealed that polder, non-polder, and mountainous areas had P load of 211.4, 437.2, and 149.9 t yr^-1, respectively. P load intensity in lowlands and mountains was 1.75 and 0.60 kg ha^-1 yr^-1, respectively. A higher P load intensity (>3 kg ha^-1 yr^-1) was mainly observed in the non-polder area. In lowland areas, irrigated cropland, aquaculture ponds and impervious surfaces contributed 36.7%, 24.8%, and 25.8% of the P load, respectively. In mountainous areas, irrigated croplands, aquaculture ponds, and impervious surfaces contributed 28.6%, 27.0%, and 16.4% of the P load, respectively. Rivers with relatively high P load risks were mainly observed around big cities during rice season, owing to a large contribution of P load from the non-point source pollution of urban and agricultural activities. This study demonstrated a raster-based estimation of watershed P load and their impacts on surrounding rivers using coupled process-based models. It would be useful to identify the hotspots and hot moments of P load at the grid scale.

Modeling nutrient flows from land to rivers and seas - A review and synthesis

Water quality modeling facilitates management of nutrient flows from land to rivers and seas, in addition to environmental pollution management in watersheds. In the present paper, we review advances made in the development of seven water quality models and highlight their respective strengths and weaknesses. Afterward, we propose their future development directions, with distinct characteristics for different scenarios. We also discuss the practical problems that such models address in the same region, China, and summarize their different characteristics based on their performance. We focus on the temporal and geographical scales of the models, sources of pollution considered, and the main problems that can be addressed. Summary of such characteristics could facilitate the selection of appropriate models for resolving practical challenges on nutrient pollution in the corresponding scenarios globally by stakeholders. We also make recommendations for model enhancement to expand their capabilities.

Sources and spatiotemporal distribution characteristics of nitrogen and phosphorus loads in the Haihe River Basin, China

Water quality monitoring stations are crucial for detecting excess pollutants in river sections, but identifying the causes of these exceedances can be challenging, especially in heavily polluted rivers with multiple contamination sources. To address this issue, we used the SWAT model to simulate pollution loads from various sources in the Haihe River Basin, analyzing the spatiotemporal distribution of pollutants from seven nitrogen/phosphorus sources in sub-basins. Our results show that crop production is the primary contributor to nitrogen and phosphorus loads in the Haihe River Basin, with the highest loads occurring in summer, followed by fall, spring, and winter. However, industries, atmospheric deposition, and municipal sewage treatment plants have a greater downstream impact on nitrogen/phosphorus contributions due to land use changes. The study highlights the need for targeted prevention and control policies based on the primary sources of pollution loads in different regions.

Predicting phosphorus and nitrate loads by using SWAT model in Vamanapuram River Basin, Kerala, India

Evaluations of probable environmental impacts of point and diffuse source pollution at regional sizes are essential to achieve sustainable development of natural resources such as land and water. This research focused on how nitrate and phosphorus load varied over time and space in the Vamanapuram River Basin (VRB). Phosphorus and nitrate loads have been evaluated in the VRB using the semi-distributed Soil and Water Assessment Tool (SWAT) hydrological model. SWAT Calibration and Uncertainty Programs (SWAT-CUP) have simulated the developed model using the Sequential Uncertainty Fitting, version 2(SUFI-2). The developed model was simulated for 2001 to 2008, and it was split into two-phase calibration and validation phases. Model performance was evaluated by the percentage of bias (PBAIS) and Nash-Sutcliffe efficiency coefficient (NSE). The simulated performance of nitrate was indicated as NSE = 0.22-0.59 and PBIAS = 51.86-65.88. The simulated performance of phosphorus showed NSE = 0.06-0.33 and PBIAS = 15.14-33.97. Total Phosphorus load was most sensitive to the organic Phosphorus enrichment ratio (ERORGP) and CH_N2 for streamflow simulation. This study concluded that the South-western region was a high potential for nutrient loads. This study will explain the nutrient load and guidelines for land management practice in the study area.

Nitrogen and phosphorus emissions to water in agricultural crop-animal systems and driving forces in Hainan Island, China

The NUFER (Nutrient Flow in food chains, Environment and Resources) model has been used to reliably quantify nitrogen (N) and phosphorus (P) emissions from agriculture land to water bodies. However, factors impacting agricultural N and P emissions at the island scale have rarely been studied due to the lack of high-resolution spatialization tools, which are critical for exploring mitigation options. Here, a high-resolution NUFER model was constructed based on geology, meteorology, land-use data, statistical data, and field investigation. The spatial characteristics of N and P emissions in Hainan Island, China, were quantified, and the driving forces were analyzed. We also explored effective measures to reduce emissions by 2035 using scenario analysis. Overall, 98 Gg N from agriculture entered water bodies in 2018, of which crop system contributed 70%; 15 Gg P entered water bodies, of which, animal system contributed 78%. Nitrate (NO₃^-) leaching (65%) and direct discharge of animal manure (69%) accounted for most of the N and P emissions, respectively. Plains contributed 89% of N and 92% of P emissions. Spatial overlay analysis showed that high N and P emissions were mainly concentrated in the western and northeastern plain areas. At the sub-basin scale, the Nandu River basin had the largest agricultural N and P emissions, accounting for more than 20% of all emissions. Scenario analysis showed that N and P emissions were significantly correlated with natural (e.g., elevation, slope, and soil texture) and anthropogenic (e.g., rural income, population density, planting structure, and livestock density) factors. We further analyzed the emissions of N and P can be reduced by 71 Gg and 14 Gg by 2035, respectively, via reducing food chain waste and consumption, importing more food, and improving production efficiency, but especially prohibiting the direct discharge of livestock manure. This high-resolution quantification of agricultural N and P emissions to the water bodies provides an exploration of the most effective options for reducing agricultural non-point source (ANPS) pollution at the island scale.

New insights into identifying sediment phosphorus sources in river-lake coupled system: A framework for optimizing microbial community fingerprints

Identifying sediment phosphorus sources in river-lake coupled system is a question in developing preferential control strategies for phosphorus. As sediments adsorbed phosphorus and microbes would be transported with changing hydrodynamic, the phosphorus source-specific microbial community fingerprints shed light on determining the major sediment phosphorus sources. However, the identification of microbial community fingerprints is a challenge because both microbial succession and hydrological characteristics of river-lake systems would affect the stability of fingerprints. Therefore, this study provided a framework for optimizing phosphorus source-specific microbial community fingerprints, and attempted to identify the major sources of sediment phosphorus in river-lake coupled ecosystem. Meiliang Lake is one of the highly eutrophic area in Taihu Lake, where the sediments, bacterial communities, and phosphorus had a close relationship. Through analyzing the connectivity of microbes along water continuum, a microbial fingerprints candidate database was constructed. The phosphorus-related bacterial communities were screened and optimized by comparing the difference of predicted results between upstream and downstream, forming the stable microbial community fingerprints which consisted of Bacteroidia, Bacilli, Clostridia, and other species at the class level. SourceTracker results that based on the optimized phosphorus source-specific microbial community fingerprints indicated that the major sediment phosphorus sources to Meiliang Lake were Liangxi River, Wujingang River, and Donghuandi River, with the relative standard deviations ranging from 2.59% to 27.56%. The accuracy of phosphorus source apportionments was further confirmed based on the composite pollution index and hydrodynamic condition. This study put forward suggestions on how to improve the stability of microbial community fingerprints, and would help to improve the understanding of applying microbial source tracking method to identify the sources of abiotic pollution like sediment phosphorus.

Metrics Assessment and Streamflow Modeling under Changing Climate in a Data-Scarce Heterogeneous Region: A Case Study of the Kabul River Basin

Due to many uncertainties in hydrological data and modeling, the findings are frequently regarded as unreliable, especially in heterogeneous catchments such as the Kabul River Basin (KRB). Besides, statistical methods to assess the performance of the models have also been called into doubt in several studies. We evaluated the performance of the Soil and Water Assessment Tool (SWAT) model by statistical indicators including the Kling-Gupta efficiency (KGE), Nash–Sutcliffe efficiency (NSE), and the coefficient of determination (R2) at single and multi-outlets in the KRB and assessed the streamflow under changing climate scenarios i.e., Representative Concentration Pathways (RCP) 4.5 and 8.5 (2020–2045). Because of the heterogeneous nature of the KRB, NSE and R2 performed poorly at multi-outlets. However, the KGE, as the basic objective function, fared much better at single-outlet. We conclude that KGE is the most crucial metric for streamflow evaluation in heterogeneous basins. Similarly, the mean and maximum annual streamflow is projected to decrease by 15.2–15.6% and 17.2–41.8% under the RCP 4.5 and 8.5, respectively.

Spatial characteristics of nutrient budget on town scale in the Three Gorges Reservoir area, China

Accurately quantifying nutrient budget is an essential step toward sustainable nutrient management in large watersheds increasingly disturbed by human activity. A town-scale nutrient budget framework based on the Soil and Water Assessment Tool was developed for 2010-2012 in the Three Gorges Reservoir area in China (TGRA). Moran's I spatial correlation test and Geodetector spatial heterogeneity test were employed to systematically analyze the spatial characteristics of the resulting nutrient budget. The Moran's I value of total nitrogen (TN) and total phosphorus (TP) gradually increased from input to output in the range of 0.091-0.232 and 0.102-0.484, respectively. Towns with higher TN and TP inputs were largely concentrated in the main urban area of Chongqing because of its high population density. By contrast, towns with higher TN and TP outputs were concentrated in the head of the TGRA. The Moran's I values of the TN and TP retention coefficients (R) were 0.433 and 0.524, respectively, demonstrating clear spatial consistency. Towns with a "High-high" spatial consistency pattern and positive R value were concentrated in the tail and hinterland, while those with a "Low-low" spatial consistency pattern and negative coefficient value were located mainly in the head of the TGRA. This phenomenon was mostly caused by differences in regional elevation, the normalized difference vegetation index, and soil erosion factor. The interaction effect between any two of these three factors on nutrient retention (Geodetector q-value) was greater than 60%. Therefore, future nutrient management should be based on a full understanding of regional biophysical conditions, especially in large areas. These findings provide a new perspective on fine nutrient management.

Spatiotemporal characteristics of agricultural nitrogen and phosphorus emissions to water and its source identification: A case in Bamen Bay，China

The spatiotemporal characteristics and sources identification of agricultural nitrogen (N) and phosphorus (P) emissions to the gulf are rarely reported in tropical regions of China, mainly due to the lack of local reliable data and quantitative tools for spatiotemporal changes. In this study, we constructed a high-resolution NUFER (NUtrient Flow in food chains, Environment and Resources use) model based on geology, meteorology, land use data, statistical data, and field investigation to quantify the spatiotemporal characteristics and sources of N and P emissions. Bamen Bay (BMB), a bay with a mangrove national wetland Park in the Hainan Island, China, was chosen as a case study. The results showed that agricultural N emission to water in 2018 increased fivefold compared to 1990. Leaching was the main method of agricultural N emission and was mainly distributed in farms in the west and north. The contribution of N emission from crop system to water increased 20.3% in 28 years. Poultry and fruits have contributed the most to N output, and the trend is continuing. P emission to water increased sevenfold compared 1990. The contribution of P emission from animal system to water increased from 86.8% in 1990 to 90.1% in 2018 due to low removal rate of livestock manure. P emission was mainly via direct discharge of manure, mainly distributed in livestock breeding sites near the bay. Poultry has consistently contributed the most to P output in 28 years, accounting for 49.1% in 2018. Fertilizers and fodder were the largest sources of N and P. The average N and P loss rates of BMB were 5.32 t km² yr^-1 and 0.26 t km² yr^-1. The future agricultural transformation is essential, and it is necessary to reduce the application of N fertilizer and increase the removal rate of livestock manure. These results can provide reference for other typical agricultural pollution bays in exploring the spatiotemporal characteristics of N and P emissions to water and the identification of agricultural sources.