Parameter uncertainty analysis of non-point source pollution from different land use types

Accounting for the annual variability when assessing non-point source pollution potential in Mediterranean regulated watersheds

The characterization of non-point source pollution at the watershed scale difficult owing to its distributed nature combined with the lack of suitable measurements for validation. This study proposes the classification of land within a Mediterranean watershed according to its potential source of non-point pollution, considering interannual precipitation variability and dam regulation effects. For this purpose, the potential non-point pollution index (PNPI) developed by the Italian Environmental Protection Agency was modified to include annual local precipitation behavior, named local annual PNPI (APNPI). PNPI and APNPI were computed for the Guadalquivir River (Spain), which has a drainage surface of 57,500 km2 and is highly regulated by >60 reservoirs. The results reflect the vulnerability along the Guadalquivir River in terms of the spatially variable non-point pollutant nature of its contributing watersheds. The annual average nitrate concentration values on the southern side exceeded the average value on the northern side by almost five times and showed a statistically significant power fit with the PNPI, with an R2 of 0.65. Long-term available nitrate data (1981/82-2006/07) on a monthly scale at the outlets of some watersheds allowed us to rank priority pollutant source areas within the watershed. The power fits between the annual average nitrate loads and the APNPI (R2 = 0.51-0.99) were statistically significant, which validated the utility of adding the variability of precipitation at an annual scale as a dynamic factor in the index. The APNPI can constitute a simple dynamic classification index for assessing the relative risk of non-point source pollution across a large area, especially in data-scarce situations.

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.

Anthropogenic impact on long-term riverine CODMn, BOD, and nutrient flux variation in the Pearl River Delta

In the Pearl River Delta (PRD), population growth and economic development have steadily increased the anthropogenic nutrient discharge into coastal waters. In this study, we employed the observed concentration and model reproduced runoff to quantify the interannual variation and the long-term (1985-2021) trends in riverine chemical oxygen demand (COD_Mn), biochemical oxygen demand (BOD), and nutrient fluxes. The annual COD_Mn and BOD fluxes increased slightly between 1999 and 2021. In comparison, the mean annual dissolved inorganic nitrogen (DIN) fluxes of the four eastern outlets increased significantly from 2.05 × 10⁵ t/a in 1985-1995 to 3.11 × 10⁵ t/a in 1999-2011 and then to 3.91 × 10⁵ t/a in 2014-2021. The outlets with the largest contributions to the COD_Mn, BOD, and DIN fluxes were Humen and Modaomen, which are both located near large cities. By calculating the COD_Mn fluxes upstream of the PRD, we found that the COD_Mn fluxes from downstream in the PRD increased faster than the fluxes from upstream. It follows that the increase in COD_Mn at outlets was mostly driven by the contributions of downstream major cities. In addition, the proportion of ammonia nitrogen flux in the DIN flux decreased from over 50 % to under 10 % at most outlets. This indicates that the toxicity of DIN fluxes has been mitigated. The DIN fluxes also showed a positive correlation with surface chlorophyll a and a negative correlation with bottom dissolved oxygen outside the Pearl River Estuary (PRE). This implies that the changes in phytoplankton growth and oxygen levels outside the PRE are closely linked to the variation in river-delivered nutrients, and the increasing riverine nutrient input may result in the expansion of intensified low-oxygen conditions outside the PRE.

Spatial-temporal characteristics of corrected total phosphorus pollution loads from agricultural non-point sources in Tuojiang River watershed, Sichuan Province of southwestern China

Traditional method of estimating pollution loads may neglect the internal spatial heterogeneity of socio-economic driving factors, which can result in overestimate and underestimate of pollution loads. In this study, the corrected approach to estimating total phosphorus (TP) pollution load was proposed to explore its future variation to develop effective phosphorus pollution control strategies for water environment management. As the first-class tributary of the Yangtze River, the TP out of limits in the Tuojiang River is serious. Thus, based on the presently related basic datasets related to TP pollution load estimation, we firstly adopted the GM (1,1) model to predict their varied trends from 2021 to 2025. We then used the pollution emission coefficient method to calculate the TP pollution load. Moreover, considering the temporal and spatial heterogeneity of the pollutant generation coefficient, we further introduced population and GDP factors to further modify the pollutant generation coefficient to correct TP pollution load. Finally, we employed the exploratory spatial data analysis (ESDA) method to explore spatial distribution characteristics and spatial autocorrelation of TP pollution load from diverse pollution sources in 2025. The results showed that the total TP pollution load from diverse pollution sources will increase from 12,194.92 t in 2021 to 12,461.26 t in 2025, an increase of 2.18%. More concretely, the TP pollution load from rural domestic sewage, rural domestic waste and livestock, and poultry pollution sources will separately decrease by 94.24 t, 77.9 t, and 86.52 t. However, the TP pollution load from agricultural runoff and agricultural solid wastes pollution sources will increase by 74.52 t and 451.49 t, respectively. The contribution of TP pollution load from diverse pollution sources to total TP pollution load will be as follows: livestock and poultry (63.49%) > agricultural solid wastes (16.72%) > agricultural runoff (12.26%) > rural domestic sewage (4.12%) > rural domestic waste (3.41%). The difference in the spatial distribution of TP pollution load from diverse pollution sources in 2025 will be prominent. TP pollution from rural domestic sewage and rural domestic waste pollution sources is more serious in the Xindu and Longquanyi districts, and that from agricultural runoff and agricultural solid wastes pollution sources is more prominent in the midstream and downstream. TP pollution load from livestock and poultry pollution source is higher in the Renshou, Anyue, Rongxian, Luxian counties, and Jiangyang district. Additionally, TP pollution load from rural domestic sewage, rural domestic waste, agricultural runoff, and agricultural solid wastes pollution sources in 2025 will show a clear spatial correlation, but the spatial correlation of TP pollution load from livestock and poultry pollution source will be weak. The study is effective to eliminate the influence of temporal and spatial variation of pollutants generates coefficients on TP pollution load estimation. The method can reflect the actual condition of pollution loads in watersheds more objectively, which can be applied to estimate other pollution loads of similar watersheds with intensive socio-economic activities. The findings in this study can provide a critical reference for the stakeholders to balance water environment conservation and socio-economic development.

Distribution of antibiotic resistance genes in the sediments of Erhai Lake, Yunnan-Kweichow Plateau, China: Their linear relations with nonpoint source pollution discharges from 26 tributaries

Erhai Lake, a typical plateau deep water lake, experienced long-term nonpoint source (NPS) pollution discharge from 26 tributaries, which significantly affected the abundance and spread of resistance genes. In this study, 25 antibiotic resistance genes (ARGs), classified into six types, and NPS pollution discharges were investigated throughout around the Erhai basin. FCA (mexF) and sulfonamide resistance genes (sul1, sul2 and sul3) were the most common. Although the absolute overall abundance of ARGs there was low so far, the individual gene like sulfonamide resistance gene was high. Regression analysis using an ordinary least squares model (OLS) showed that the discharge of NPS pollution into Erhai Lake would have an obvious effect on the distribution of ARGs. And the relations between them were linear. Concretely speaking, the total nitrogen (TN) pollution input from tributaries could significantly correlated with the increasing of ARG abundance, while the total phosphorus (TP) pollution input showed the opposite correlation, and ultimately affect the distribution of ARGs. Moreover, the effect of TP on ARG distribution was more significant than TN. This study provides a geographical profile of ARG distribution in a subtropical deep lake on Yunnan-Kweichow Plateau. The results are beneficial for predicting the distribution characteristics of ARGs and controlling their pollution in plateau lakes.

Assessment of Uncertainty in Grid-Based Rainfall-Runoff Model Based on Formal and Informal Likelihood Measures

Damage prevention from the local storms and typhoons in Korea, the development of a rainfall-runoff model reflecting local geological, meteorological and physical characteristics is necessary. The accuracy of the rainfall-runoff model is influenced by the various uncertainty factors that can occur in the modeling processes, including input data, model parameters, modeling simplification, and so on. Thus, the objectives of this study are (1) to estimate runoff for two rainfall events using Grid Rainfall-Runoff Model (GRM); (2) to quantify the uncertainty of the GRM model using the Generalized Likelihood Uncertainty Estimation (GLUE) method, and (3) to assess the uncertainty ranges of the GRM based on different likelihood functions. For this, two rainfall events were implemented to the GRM in the Cheongmicheon watershed, and informal likelihood functions (LNSE, LPBIAS, LRSR, and LLOG) based on the fitness indices (NSE, PBIAS, RSR, and Log-normal) were used for uncertainty analysis and quantification using GLUE method. As a result, the GRM parameters varied according to the different rainfall patterns even in the same watershed. In addition, among the GRM parameters, the CRC (Channel Roughness Coefficient) and CSHC (Correction factor for Soil Hydraulic Conductivity) characteristics are the most sensitive. Moreover, this study showed that the uncertainty range of the GRM model can be changed with the subjective selection of likelihood functions and thresholds. The GRM model is open source and has good accessibility. Especially, this open-source model allows various approaches to disaster prevention plans such as flood forecasting and flood insurance policies. In addition, if the parameter range of GRM is quantified and standardized at domestic watersheds, it is expected that the reliability of the rainfall-runoff simulation can be increased by the reduction of the uncertainty factors.

Prediction and optimization of regional land-use patterns considering nonpoint-source pollution control under conditions of uncertainty

Socioeconomic development, leading to significant changes in land-use patterns, has further influenced the output of regional nonpoint-source (NPS) pollution. Multiple uncertainties exist in the processes of land-use changes and NPS pollution export. These uncertainties can deeply affect the management of regional land-use patterns and control of NPS pollution. In this research, an integrated land-use prediction and optimization (ILUPO) model based on system dynamics, export coefficient, interval linear programming, and fuzzy parameter programming models was proposed. The ILUPO model can provide future land-use patterns and NPS pollution loads, and also help optimize the patterns under multiple pollution reduction scenarios. Interval and fuzzy uncertainties in the processes of land-use changes and NPS pollution output can be effectively addressed. The developed model was applied to a water source area in the central part of northern Guangdong Province in South China. For the prediction period 2020-2030 under the high-speed development scenario, results show that cropland area would decrease, while grassland and waterbody areas would increase. In contrast, these three types of land-use would show opposite variation trends under the low-speed development scenario. Construction land area would decrease, while forestland area would increase under both the low-speed and high-speed development scenarios. Variation of the predicted land-use patterns would lead to an increase of total nitrogen loads under each of the scenario, while the total phosphorus loads would show relatively complex variation trends. Regional land-use patterns should be further optimized to mitigate NPS pollution. However, the pollution loads in the study area cannot be reduced by >5% through land-use adjustment. Because cropland would still be the critical source of NPS pollution after optimization, strictly controlling the areas of cropland would be important for the management of such pollution in the research area. In addition, certain areas of grassland and waterbody would need to be converted into cropland and construction land to balance the economic benefit of the system and NPS pollution control. Multiple results obtained from the model under different scenarios of pollution reduction targets and α-cut levels can provide decision-making supports for the local policy makers. The developed ILUPO model can yield insights useful for the planning and adjustment of regional land-use patterns while considering NPS pollution control under conditions of uncertainty.

A Bibliometric Analysis on Nonpoint Source Pollution: Current Status, Development, and Future

Nonpoint source pollution (NPS) has become the leading factor of global water quality problems, attracting great attention from governments and researchers in various countries. Based on this situation, understanding the current research status of NPS can help guide future research. However, most of the current reviews only describe the research status of some specific aspects but fail to quantify the research hotspots and development trends on the whole, which limits the overall understanding of NPS. In this paper, bibliometrics was used to study the current status, hotspots, and frontiers of NPS research during 1991–2015, and the future research development was predicted. Over the past 15 years, there has been a remarkable growth trend in publication output, and the participation of countries/territories has also increased. Journal of Environmental Quality, Journal of Hydrology, and Total Environmental Science were the top three journals. Sharpley AN and Arnold JG from the USA were the most productive authors with the best quality articles. The major author clusters and research regions are located in North America and Europe, followed by East Asia. The United States dominates this research field, with the largest number of independent and collaborative articles. Chinese authors gained more attention through international cooperation. Keyword analysis confirmed that water quality and nutrients were the main concerns of NPS pollution research, which mainly involved a number of research topics, such as pollutant emission reduction research and the evaluation and simulation of pollutants’ migration and their transformation under different situations, while pesticides were less of a concern, which suggests that the abuse of pesticides has come under control. Meanwhile, SWAT was the dominating model in the last decade partly because it satisfied the growing needs of watershed-scale management.

Responses of surface water quality to future land cover and climate changes in the Neka River basin, Northern Iran

The spatial and temporal dimensions of environmental impacts of climate and land cover changes are two significant factors altering hydrological processes. Studying the effects of these factors on water quality, provides important insight for water resource management and optimizing land planning given increasing water scarcity and water pollution. The impact of land cover and climate changes on surface water quality was assessed for the Neka River basin in Northern Iran. The widely used Soil and Water Assessment Tool (SWAT) was applied for pollutant modeling, and was calibrated using the Sequential Uncertainty Fitting (SUFI-2) algorithm. An ensemble of 17 CMIP5 climate models under two IPCC greenhouse gas emission scenarios were selected, and future land cover change (LCC) was modeled based on the evolution that occurred in the last decades. We simulated the impacts of climate change (CC) and LCC on sediment, nitrate, and phosphate for the 2035-2065 time slice. The annual loads of sediment, phosphate, and nitrate are projected to decrease under both CC scenarios based on the inter-model average, and generally follow a pattern similar to the change in river discharge. Nitrate concentrations show an increase across all seasons, while the sediment and phosphate concentrations increase in winter and autumn under CC conditions. Results indicate that pollutants are expected to increase under LCC alone, mainly due to the expansion of the cultivated areas. Overall, it seems CC has a greater impact than LCC on the variation of water quality variables in the Neka River basin. With a combined change in climate and land cover, the annual nitrate concentrations are expected to increase by + 19.7% and + 17.9%, under RCP 4.5 and RCP 8.5, respectively. The combined impacts of the CC and LCC caused a decline in the annual sediment and phosphate concentrations by -10.1% and -2.2% under RCP 4.5 and -9%, and -3.2% under RCP 8.5, respectively.

Dynamic export coefficient model for evaluating the effects of environmental changes on non-point source pollution

The classic export coefficient model has been questioned due to its fixed coefficient, especially for those large-scale watersheds where great temporal-spatial heterogeneity exists. In this paper, a dynamic export coefficient model (DECM) was proposed for simulating non-point source (NPS) pollution by incorporating the impacts of factors on export coefficients. The relationships between rainfall, slope, soil, land use, other factors and export coefficients were constructed at relatively smaller catchment based on the information of mechanistic-based model, while these dynamic export coefficients were then extended to the large ungauged basins. This new model was tested in the Three Gorges Reservoir Region (TGRR), China. The results indicated the new method improved the accuracy of large-scale NPS prediction as well as reducing the computation burden. The rainfall temporal variability was identified as the major factor influencing the variability of flow and NPS pollution with the coefficient of variation being 0.1678 and 0.2046, respectively. Using the new method, the Long watershed, the Jialing watershed, the Quxi watershed, the Xiangxi watershed and the main stream in the TGRR were identified as those sensitive regions under the changing environment. The DECM could be extended to other large scale to quantify the NPS pollution, especially data-poor watersheds.

Assessment of parameter uncertainty for non-point source pollution mechanism modeling: A Bayesian-based approach

Uncertainty assessment of parameters associated with non-point source pollution mechanism modeling are crucial for improving the effectiveness of pollution controlling. In this study, an approach based on Bayesian inference and integrated Markov chain Monte Carlo and multilevel factorial analysis has been developed, and it can not only apply straightforward Bayesian inference to assess parameter uncertainties, but also quantitatively investigate the main and interactive effects of multiple parameters on the model response variables by measuring the specific variations of model outputs. Its applicability and advantages are presented through the application of the Soil and Water Assessment Tool to Shitoukoumen Reservoir Catchment in northeast China. This study investigated the uncertainties of a set of sensitive parameters and their multilevel effects on model response variables, including average annual runoff (AAR), average annual sediment (AAS) and average annual total nitrogen (AAN). Results revealed that (i) soil conservation service runoff curve number for moisture condition II (CN2) had a positive effect on all response variables; (ii) available water capacity of the soil layer (SOL_AWC) had a negative effect on all response variables; (iii) the universal soil loss equation support practice (USLE_P) had a positive effect on AAS and AAN, and little effect on AAR; while the nitrate percolation coefficient (NPERCO) had a positive effect on AAN, and little effect on AAS and AAR; and (iv) the interactions amongst parameters had obvious interdependent effects on the model response variables, for example, the interaction between CN2 and SOL_AWC had a major impact on AAR. The above findings can improve the simulating and predicting capabilities of non-point source pollution mechanism model. Overall, this study highlights that the proposed approach represents a promising solution for uncertainty assessment of model parameters in non-point source pollution mechanism modeling.

The Influence of Different Forest Characteristics on Non-point Source Pollution: A Case Study at Chaohu Basin, China

Forestland is a key land use/land cover (LULC) type that affects nonpoint source (NPS) pollution, and has great impacts on the spatiotemporal features of watershed NPS pollution. In this study, the forestland characteristics of the Chaohu Basin, China, were quantitatively represented using forestland types (FLTs), watershed forest coverage (WFC) and forest distance from the river (DFR). To clarify the impact of forests on NPS pollution, the relationship between forestland characteristics and watershed nutrient outputs (TN and TP) was explored on a monthly scale using SWAT (Soil and Water Assessment Tool) and the period simulation was 2008-2016. The results showed that: (1) the TN and TP showed similar output characteristics and the rainy season was the peak period of nitrogen and phosphorus output. (2) Among the forestland characteristics of forestland types, watershed forest coverage and forest distance from the river, watershed forest coverage and forest distance from the river had greater effects than forestland types on the control of watershed nutrient outputs (TN and TP). (3) In different forestland types, the watershed nutrient outputs intensity remained at the lowest level when the FLTs was mixed forest, with a TN output of 1244.73kg/km² and TP output of 341.39 kg/km². (4) The watershed nutrient outputs and watershed forest coverage were negatively correlated, with the highest watershed forest coverage (over 75%) reducing the TN outputs by 56.69% and the TP outputs by 53.46% compared to the lowest watershed forest coverage (below 25%), it showed that in areas with high forest land coverage, the non-point source pollution load in the watershed is smaller than in other areas. (5) forest distance from the river had an uncertain effect on the TN and TP output of the basin, the forestland itself is a source of pollution, but it also has the function of intercepting pollution movement; the forest distance from the river in the range of 500-1000 m had the lowest NPS pollution. Considering the different forest characteristics and topographical factors, an optimal allocation mode of differentiated forest land was proposed, these suggestions will provide a scheme for surface source pollution prevention and control in the basin. This research gap is the basis of real forestland optimization. We may optimize the forestland layout for NPS pollution prevention and control by clarifying the internal mechanism.

Non-Point Source Pollutant Load Variation in Rapid Urbanization Areas by Remote Sensing, Gis and the L-THIA Model: A Case in Bao'an District, Shenzhen, China

Urban sprawl is a major driving force that alters local and regional hydrology and increases non-point source pollution. Using the Bao'an District in Shenzhen, China, a typical rapid urbanization area, as the study area and land-use change maps from 1988 to 2014 that were obtained by remote sensing, the contributions of different land-use types to NPS pollutant production were assessed with a localized long-term hydrologic impact assessment (L-THIA) model. The results show that the non-point source pollution load changed significantly both in terms of magnitude and spatial distribution. The loads of chemical oxygen demand, total suspended substances, total nitrogen and total phosphorus were affected by the interactions between event mean concentration and the magnitude of changes in land-use acreages and the spatial distribution. From 1988 to 2014, the loads of chemical oxygen demand, suspended substances and total phosphorus showed clearly increasing trends with rates of 132.48 %, 32.52 % and 38.76 %, respectively, while the load of total nitrogen decreased by 71.52 %. The immigrant population ratio was selected as an indicator to represent the level of rapid urbanization and industrialization in the study area, and a comparison analysis of the indicator with the four non-point source loads demonstrated that the chemical oxygen demand, total phosphorus and total nitrogen loads are linearly related to the immigrant population ratio. The results provide useful information for environmental improvement and city management in the study area.

Assessing the relation of USDA conservation expenditures to suspended sediment reductions in an Iowa watershed

From 1936 to 2010, U.S. Department of Agriculture (USDA) agencies spent $293.7 billion (value adjusted for inflation at the 2009 level) on conservation programs. Of these expenditures, $75.2 billion (26%) were allocated for technical assistance (TA; it is related to costs associated with USDA field staff providing their expert advice to farmers) and $218.5 billion (74%) for financial assistance (FA; monetary incentives for farmers to adopt conservation programs). A major environmental goal of these programs was to reduce soil erosion and sediment leaving the land. In this study, we correlate expenditures on FA and TA programs to a unique long (1937-2009) record of total suspended solids (TSS) and sediment load (SL) for the Raccoon River at Van Meter, Iowa. Study results suggest that three predictors (rainfall, TA and FA) are important in explaining the temporal changes in annual TSS and SL and provide evidence that USDA expenditures helped reduce TSS and SL in the Raccoon River. TA was more effective than FA in reducing TSS levels in the watershed. Our empirical model represents an initial, broad-scale attempt to correlate conservation expenditures to a specific water quality outcome, although more work is needed to disentangle the impacts associated with other unexplored factors.

Using site-specific soil samples as a substitution for improved hydrological and nonpoint source predictions

Soil databases are one of the most important inputs for watershed models, and the quality of soil properties affects how well a model performs. The objectives of this study were to (1) quantify the sensitivity of model outputs to soil properties and to (2) use site-specific soil properties as a substitution for more accurate hydrological and nonpoint source (H/NPS) predictions. Soil samples were collected from a typical mountainous watershed in China, and the impacts of soil sample parameters on H/NPS predictions were quantified using the Soil and Water Assessment Tool (SWAT). The most sensitive parameters related to predicting flow, sediment, and total phosphorus (TP) mainly were the soil hydrological, the channel erosion processes, and the initial soil chemical environment, respectively. When the site-specific soil properties were used, the uncertainties (coefficient of variation) related to predicting the hydrology, sediment and TP decreased by 75∼80 %, 75∼84 %, and 46∼61 %, respectively. Based on changes in the Nash-Sutcliff coefficient, the model performance improved by 4.9 and 19.45 % for the hydrological and sediment model, accordingly. However, site-specific soil properties did not contribute to better TP predictions because of the high spatial variability of the soil P concentrations across the large watershed. Thus, although site-specific soil samples can be used to obtain more accurate H/NPS predictions, more sampling sites are required to apply this method in large watersheds.

SWAT-CS(enm): Enhancing SWAT nitrate module for a Canadian Shield catchment

Nonpoint source modeling using hydrological models has been extensively studied at agriculture and urban watersheds; however, this has not been well addressed in forested ones where agricultural sources are comparatively minimal and nitrogen deposition exerts remarkable impacts on the nutrient cycles of a catchment. Thus it is critically important for hydrological models to incorporate the dynamics of nitrogen deposition and its transport processes, for reasonable nitrogen modeling. This is especially so for the Canadian Shield, which is characterized by a cold climate and special physiographic features. A revision of Soil and Water Assessment Tool for Canadian Shield (SWAT-CS) was proposed by Fu et al. (2014) to better characterize the hydrological features. In this study, more revisions were added to better simulate processes of nitrate by: 1) incorporating the dynamics of nitrogen deposition; and 2) allowing the deposition to distribute along with rapid-moving macropore flows. The newly revised model, SWAT-CS(enm) (SWAT-CS with an Enhanced Nitrate Module), and SWAT-CS were calibrated and tested with data of a subbasin of Harp Lake in south-central Ontario for 1990 to 2007. Modeling performance of nitrate flux rate in the stream for SWAT-CS(enm) was nearly acceptable with maximum daily Nash-Sutcliffe efficiencies (ENSs) for calibration and validation periods of 0.66 and 0.43, respectively; whereas the result of SWAT-CS was generally unsatisfied with maximum daily ENSs of 0.16 and 0.07, respectively. An uncertainty analysis using GLUE (generalized likelihood uncertainty estimation) showed a modest performance as about 50% of observations can be incorporated by the 95% prediction range deriving from the behavioral solutions (ENS≥0.5) for both daily and monthly simulations. It is concluded that the enhanced nitrate module improved the model performance of SWAT-CS on nitrate modeling, since the previous SWAT-CS failed to consider the effect of dynamics of nitrogen deposition and its sequential processes at the investigated site.

Uncertainty analysis of primary water pollutant control in China's pulp and paper industry

The total emission control target of water pollutants (e.g., COD and NH4-N) for a certain industrial sector can be predicted and analysed using the popular technology-based bottom-up modelling. However, this methodology has obvious uncertainty regarding the attainment of mitigation targets. The primary uncertainty comes from macro-production, pollutant reduction roadmap, and technical parameters. This research takes the paper and pulp industry in China as an example, and builds 5 mitigation scenarios via different combinations of raw material structure, scale structure, procedure mitigation technology, and end-of-pipe treatment technology. Using the methodology of uncertainty analysis via Monte Carlo, random sampling was conducted over a hundred thousand times. According to key parameters, sensitive parameters that impact total emission control targets such as industrial output, technique structure, cleaner production technology, and end-of-pipe treatment technology are discussed in this article. It appears that scenario uncertainty has a larger influence on COD emission than NH4-N, hence it is recommended that a looser total emission control target for COD is necessary to increase its feasibility and availability while maintaining the status quo of NH4-N. Consequently, from uncertainty analysis, this research recognizes the sensitive products, techniques, and technologies affecting industrial water pollution.

Evaluating the Effects of Land Use Planning for Non-Point Source Pollution Based on a System Dynamics Approach in China

Urbanization is proceeding rapidly in several developing countries such as China. This accelerating urbanization alters the existing land use types in a way that results in more Non-Point Source (NPS) pollution to local surface waters. Reasonable land use planning is necessary. This paper compares seven planning scenarios of a case study area, namely Wulijie, China, from the perspective of NPS pollution. A System Dynamics (SD) model was built for the comparison to adequately capture the planning complexity. These planning scenarios, which were developed by combining different land use intensities (LUIs) and construction speeds (CSs), were then simulated. The results show that compared to scenario S1 (business as usual) all other scenarios will introduce more NPS pollution (with an incremental rate of 22%-70%) to Wulijie. Scenario S6 was selected as the best because it induced relatively less NPS pollution while simultaneously maintaining a considerable development rate. Although LUIs represent a more critical factor compared to CSs, we conclude that both LUIs and CSs need to be taken into account to make the planning more environmentally friendly. Considering the power of SD in decision support, it is recommended that land use planning should take into consideration findings acquired from SD simulations.

Cost-effectiveness and cost-benefit analysis of BMPs in controlling agricultural nonpoint source pollution in China based on the SWAT model

Best management practices (BMPs) have been widely used in managing agricultural nonpoint source pollution (ANSP) at the watershed level. Most BMPs are related to land use, tillage management, and fertilizer levels. In total, seven BMP scenarios (Reforest1, Reforest2, No Tillage, Contour tillage, and fertilizer level 1-4) that are related to these three factors were estimated in this study. The objectives were to investigate the effectiveness and cost-benefit of these BMPs on ANSP reduction in a large tributary of the Three Gorges Reservoir (TGR) in China, which are based on the simulation results of the Soil and Water Assessment Tool (SWAT) model. The results indicated that reforestation was the most economically efficient of all BMPs, and its net benefits were up to CNY 4.36×10(7) years(-1) (about USD 7.08×10(6) years(-1)). Regarding tillage practices, no tillage practice was more environmentally friendly than other tillage practices, and contour tillage was more economically efficient. Reducing the local fertilizer level to 0.8-fold less than that of 2010 can yield a satisfactory environmental and economic efficiency. Reforestation and fertilizer management were more effective in reducing total phosphorus (TP), whereas tillage management was more effective in reducing total nitrogen (TN). When CNY 10,000 (about USD 162) was applied to reforestation, no tillage, contour tillage, and an 0.8-fold reduction in the fertilizer level, then annual TN load can be reduced by 0.08, 0.16, 0.11, and 0.04 t and annual TP load can be reduced by 0.04, 0.02, 0.01 and 0.03 t, respectively. The cost-benefit (CB) ratios of the BMPs were as follows: reforestation (207 %) > contour tillage (129 %) > no tillage (114 %) > fertilizer management (96 and 89 %). The most economical and effective BMPs can be designated as follows: BMP1 (returning arable land with slopes greater than 25° to forests and those lands with slopes of 15-25° to orchards), BMP2 (implementing no tillage on arable land with slopes less than 15°), and BMP5 (0.8-fold less than that of 2010).

Simulation of spatial and temporal distributions of non-point source pollution load in the Three Gorges Reservoir Region

Non-point source (NPS) pollution has become the largest threat to water quality in recent years. Major pollutants, particularly from agricultural activities, which include nitrogen, phosphorus and sediment that have been released into aquatic environments, have caused a range of problems in the Three Gorges Reservoir Region (TGRR), China. It is necessary to identify the spatial and temporal distributions of NPS pollutants and the highly polluted areas for the purpose of watershed management. In this study, the NPS pollutant load was simulated using the Soil and Water Assessment Tool (SWAT) and the small-scale watershed extended method (SWEM). The simulation results for four typical small catchments were extended to the entire watershed leading to estimates of the NPS load from 2001 to 2009. The results demonstrated that the NPS pollution load in the western area was the highest and that agricultural land was the primary pollutant source. The similar annual variation trends of runoff and sediment loads demonstrated that the sediment load was closely related to runoff. The loads of total nitrogen (TN) and total phosphorus (TP) were relatively stable from 2001 to 2007, except for high loads in 2006. The increase in pollution source strength was an important reason for the significant upward trend of TN and TP loads from 2008 to 2009. The rainfall from April to October contributed to the largest amount of runoff, sediment and nutrient loads for the year. The NPS load intensities in each sub-basin reveal large variations in the spatial distribution of different pollutants. It was shown that the temporal and spatial distributions of pollutant loads were positively correlated with the annual rainfall amounts and with human activities. Furthermore, this finding illustrates that conservation practices and nutrient management should be implemented in specific sites during special periods for the purpose of NPS pollution control in the TGRR.

Uncertainty analyses on the calculation of water environmental capacity by an innovative holistic method and its application to the Dongjiang River

The estimation and allocation of water environmental capacity (WEC) are essential to water quality management and social-economic interests. However, there is inevitable uncertainty in the capacity estimation due to model conceptualization, data collection and parameter calibration. An innovative holistic approach was developed, which took both independence and relevance between parameters into account to analyze the uncertainties in WEC calculation and estimate the margin of safety. The Dongjiang River was taken as the case to demonstrate the method, focusing on the chemical oxygen demand and NH4(+)-N that were the two major water quality problems in the river. The results showed that the proposed holistic approach is very promising and applicable compared to traditional methods of uncertainty analysis.

Land use change impacts on water quality in three lake winnipeg watersheds

Lake Winnipeg eutrophication results from excess nutrient loading due to agricultural activities across the watershed. Estimating nonpoint-source pollution and the mitigation effects of beneficial management practices (BMPs) is an important step in protecting the water quality of streams and receiving waters. The use of computer models to systematically compare different landscapes and agricultural systems across the Red-Assiniboine basin has not been attempted at watersheds of this size in Manitoba. In this study, the Soil and Water Assessment Tool was applied and calibrated for three pilot watersheds of the Lake Winnipeg basin. Monthly flow calibration yielded overall satisfactory Nash-Sutcliffe efficiency (NSE), with values above 0.7 for all simulations. Total phosphorus (TP) calibration NSE ranged from 0.64 to 0.76, total N (TN) ranged from 0.22 to 0.75, and total suspended solids (TSS) ranged from 0.29 to 0.68. Based on the assessment of the TP exceedance levels from 1993 to 2007, annual loads were above proposed objectives for the three watersheds more than half of the time. Four BMP scenarios based on land use changes were studied in the watersheds: annual cropland to hay land (ACHL), wetland restoration (WR), marginal annual cropland conversion to hay land (MACHL), and wetland restoration on marginal cropland (WRMAC). Of these land use change scenarios, ACHL had the greatest impact: TSS loads were reduced by 33 to 65%, TN by 58 to 82%, and TP by 38 to 72% over the simulation period. By analyzing unit area and percentage of load reduction, the results indicate that the WR and WRMAC scenarios had a significant impact on water quality in high loading zones in the three watersheds. Such reductions of sediment, N, and P are possible through land use change scenarios, suggesting that land conservation should be a key component of any Lake Winnipeg restoration strategy.

Assessment of the impacts of land use changes on nonpoint source pollution inputs upstream of the Three Gorges Reservoir

In recent years, land use upstream of the Three Gorges Reservoir (TGR) has changed significantly because of the TGR project. In this study, the Soil and Water Assessment Tool (SWAT) model was examined for its ability to assess relationships between land use changes and nonpoint pollutant indexes upstream of the TGR. Results indicated that the SWAT model, calibrated with the adjusted parameters, could successfully reproduce the nonpoint indexes at the water quality monitoring sites in the two rivers. The different land use change types were shown to be sensitive to nonpoint pollutants in the study area. The land use change type from upland to water was the strongest influence on changes in total nitrogen and total phosphorus. An empirical regression equation between nonpoint indexes and different land use change types was developed for the study area by partial least squares regression (PLSR) as follows: Y = b₀ + ∑_i=1^mb_iX_i. This regression equation was useful for evaluating the influence of land use change types on changes in nonpoint pollutants over a long time period. The results from this study may be useful for the TGR management and may help to reduce nonpoint pollutant loads into downstream water bodies.

Simulation of streamflow and sediment with the soil and water assessment tool in a data scarce catchment in the three gorges region, china

The Three Gorges Region in China is currently subject to a large-scale land use change, which was induced by the construction of the Three Gorges Dam on the Yangtze River. The relocation of towns, villages, and agricultural areas is expected to affect the water balance and increase erosion rates and sediment yields in the affected catchments. Hydrologic and water quality models are frequently used to assess the impact of land use changes on water resources. In this study, the eco-hydrological Soil and Water Assessment Tool (SWAT) model is applied to the Xiangxi Catchment in the Three Gorges Region. This paper presents the calibration and validation of streamflow and sediment loads at Xingshan gauging station. The calibration of daily streamflow resulted in a satisfactory fit of simulated and observed data, which is indicated by Nash-Sutcliffe efficiency (NSE) values of 0.69 and 0.67 for the calibration (1981-1986) and validation (1988-1993) periods, respectively. In contrast, the model was not able to simulate the monthly average sediment loads correctly, as indicated by very low NSE values of 0.47 (calibration) and 0.08 (validation). This might be due to inadequate representation of spatial rainfall variability by the available climate stations, insufficient input data, uncertainties in the model structure, or uncertainties in the observed sediment loads. The discussion of these possible reasons for the incorrect prediction of sediment loads by SWAT reveals the need for further research in the field of hydrological and water quality modeling in China.

Vertical variation of nonpoint source pollutants in the Three Gorges Reservoir Region

Nonpoint source (NPS) pollution is considered the main reason for water deterioration, but there has been no attempt to incorporate vertical variations of NPS pollution into watershed management, especially in mountainous areas. In this study, the vertical variations of pollutant yields were explored in the Three Gorges Reservoir Region (TGRR) and the relationships between topographic attributes and pollutant yields were established. Based on our results, the pollutant yields decreased significantly from low altitude to median altitude and leveled off rapidly from median altitude to high altitude, indicating logarithmic relationships between pollutant yields and altitudes. The pollutant yields peaked at an altitude of 200–500 m, where agricultural land and gentle slopes (0–8°) are concentrated. Unlike the horizontal distributions, these vertical variations were not always related to precipitation patterns but did vary obviously with land uses and slopes. This paper also indicates that altitude data and proportions of land use could be a reliable estimate of NPS yields at different altitudes, with significant implications for land use planning and watershed management.

Assessment of nitrogen and phosphorus loads and causal factors from different land use and soil types in the Three Gorges Reservoir Area

It is important to identify nitrogen (N) and phosphorus (P) from non-point sources (NPS) to protect watershed water quality. However, few studies have been conducted in a large basin to determine the sources and causal factors of N and P from multiple land use and soil types. In this study, the Soil and Water Assessment Tool (SWAT) was applied in support of the Small-scale Watershed Extended Method (SWEM) in the Three Gorges Reservoir Region (TGRR), China. The first-order error analysis (FOEA) was used to identify the key sub-processes that affected the occurrence of NPS pollution. Based on this study, runoff from the dry land and paddy fields was enriched with nutrients, while runoff from purplish soils, paddy soils and yellow earths made up the largest amount of nutrient loads. The results showed that the contributions of individual parameters to the total uncertainty were different among land use and soil types. This study indicated that management efforts for dry land must explicitly account for conservation practices and proper land covers, while conscientious fertilization practices would result in a greater decrease of NPS yields for paddy fields. Grazing practices should be considered for the purpose of N management for yellow earths, while plant density is important to control soil erosion for purple soils.

Multi-angle indicators system of non-point pollution source assessment in rural areas: a case study near Taihu Lake

This study aims to identify key environmental risk sources contributing to water eutrophication and to suggest certain risk management strategies for rural areas. The multi-angle indicators included in the risk source assessment system were non-point source pollution, deficient waste treatment, and public awareness of environmental risk, which combined psychometric paradigm methods, the contingent valuation method, and personal interviews to describe the environmental sensitivity of local residents. Total risk values of different villages near Taihu Lake were calculated in the case study, which resulted in a geographic risk map showing which village was the critical risk source of Taihu eutrophication. The increased application of phosphorus (P) and nitrogen (N), loss vulnerability of pollutant, and a lack of environmental risk awareness led to more serious non-point pollution, especially in rural China. Interesting results revealed by the quotient between the scores of objective risk sources and subjective risk sources showed what should be improved for each study village. More environmental investments, control of agricultural activities, and promotion of environmental education are critical considerations for rural environmental management. These findings are helpful for developing targeted and effective risk management strategies in rural areas.

A topography analysis incorporated optimization method for the selection and placement of best management practices

Best Management Practices (BMPs) are one of the most effective methods to control nonpoint source (NPS) pollution at a watershed scale. In this paper, the use of a topography analysis incorporated optimization method (TAIOM) was proposed, which integrates topography analysis with cost-effective optimization. The surface status, slope and the type of land use were evaluated as inputs for the optimization engine. A genetic algorithm program was coded to obtain the final optimization. The TAIOM was validated in conjunction with the Soil and Water Assessment Tool (SWAT) in the Yulin watershed in Southwestern China. The results showed that the TAIOM was more cost-effective than traditional optimization methods. The distribution of selected BMPs throughout landscapes comprising relatively flat plains and gentle slopes, suggests the need for a more operationally effective scheme, such as the TAIOM, to determine the practicability of BMPs before widespread adoption. The TAIOM developed in this study can easily be extended to other watersheds to help decision makers control NPS pollution.

Modeling agricultural nonpoint source pollution using a geographic information system approach

Agricultural non-point source (NPS) pollution, primarily sediment and nutrients, is the leading source of water-quality impacts to surface waters in North America. The overall goal of this study was to develop geographic information system (GIS) protocols to facilitate the spatial and temporal modeling of changes in soils, hydrology, and land-cover change at the watershed scale. In the first part of this article, we describe the use of GIS to spatially integrate watershed scale data on soil erodibility, land use, and runoff for the assessment of potential source areas within an intensively agricultural watershed. The agricultural non-point source pollution (AGNPS) model was used in the Muddy Creek, Ontario, watershed to evaluate the effectiveness of management strategies in decreasing sediment and nutrient [phosphorus (P)] pollution. This analysis was accompanied by the measurement of water-quality parameters (dissolved oxygen, pH, hardness, alkalinity, and turbidity) as well as sediment and P loadings to the creek. Practices aimed at increasing year-round soil cover would be most effective in decreasing sediment and P losses in this watershed. In the second part of this article, we describe a method for characterizing land-cover change in a dynamic urban fringe watershed. The GIS method we developed for the Blackberry Creek, Illinois, watershed will allow us to better account for temporal changes in land use, specifically corn and soybean cover, on an annual basis and to improve on the modeling of watershed processes shown for the Muddy Creek watershed. Our model can be used at different levels of planning with minimal data preprocessing, easily accessible data, and adjustable output scales.

Assessing the influence of land use and land cover datasets with different points in time and levels of detail on watershed modeling in the North River Watershed, China

Land use and land cover (LULC) information is an important component influencing watershed modeling with regards to hydrology and water quality in the river basin. In this study, the sensitivity of the Soil and Water Assessment Tool (SWAT) model to LULC datasets with three points in time and three levels of detail was assessed in a coastal subtropical watershed located in Southeast China. The results showed good agreement between observed and simulated values for both monthly and daily streamflow and monthly NH(4)+-N and TP loads. Three LULC datasets in 2002, 2007 and 2010 had relatively little influence on simulated monthly and daily streamflow, whereas they exhibited greater effects on simulated monthly NH(4)+-N and TP loads. When using the two LULC datasets in 2007 and 2010 compared with that in 2002, the relative differences in predicted monthly NH(4)+-N and TP loads were -11.0 to -7.8% and -4.8 to -9.0%, respectively. There were no significant differences in simulated monthly and daily streamflow when using the three LULC datasets with ten, five and three categories. When using LULC datasets from ten categories compared to five and three categories, the relative differences in predicted monthly NH(4)+-N and TP loads were -6.6 to -6.5% and -13.3 to -7.3%, respectively. Overall, the sensitivity of the SWAT model to LULC datasets with different points in time and levels of detail was lower in monthly and daily streamflow simulation than in monthly NH(4)+-N and TP loads prediction. This research provided helpful insights into the influence of LULC datasets on watershed modeling.

Assessment and analysis of non-point source nitrogen and phosphorus loads in the Three Gorges Reservoir Area of Hubei Province, China

Eutrophication due to non-point source (NPS) of nitrogen (N) and phosphorus (P) has become a serious pollution problem in many Chinese rivers. In this paper, the export coefficient model (ECM) was used to assess the influence of NPS on N and P loading to the Three Gorges Reservoir Area (TGRA) of Hubei Province, People's Republic of China. Data from the main non-point sources were analyzed from 1995 to 2007, including rural domestic wastes, distributed livestock farms, fertilizers and soil erosion. Additionally, the potential N and P loading from NPS originated from a variety of sources were estimated and analyzed from 1995 to 2007, including runoff from rural domestic waste, livestock farms, land use, and atmospheric deposition, using the ECM. These gave the temporal distributions of the potential NPS loads within the reservoir area. The results indicated that the potential total nitrogen (TN) load was much higher than the potential total phosphorus (TP) load. The calculated TN load was 2.83×10(4) tonnes, while the TP load was 2.14×10(3) tonnes in 2007, with a ratio of TN/TP of 13.23. Record shows that "algae blooms" occurred 8 times in TGRA that year. Therefore, there may be a correlation between the eutrophication potential in the inlet water of TGRA and the TN/TP ratio of potential NPS loads. These findings demonstrate that the export coefficient model could provide a simple and reliable approach to evaluate the potential N and P loading to the Three Gorges Reservoir Area of Hubei Province in the People's Republic of China and may be useful for the planning and management of the local agricultural watersheds.