Total Phosphorus Loads Research Articles

Correlation between Different Factors of Non-point Source Pollution in Yangtze River Basin

This research used the improved export coefficient model to estimate non-point source load in sub-watersheds and a self-organizing map model to identify the correlation relationship of factors, that can be affected by non-point source load in Yangtze River Basin. Research results indicate that total nitrogen load is 4.87 - 15.53 kg/ha; total phosphorus load is 0.18 - 0.51 kg/ha; Dong Ting Lake sub-basin has the lowest contribution value of total nitrogen and phosphorus; Tai Lake sub-basin has the highest contribution load of total nitrogen and total phosphorus; Jinsha River sub-basin reveals the highest value of total nitrogen and phosphorus contribution on grassy land and desert land; Tai Lake sub-basin has the highest total nitrogen and total phosphorus load on forest, agricultural land, and urban construction land. The correlation relationship of factors reveals a very close correlation with each other as precipitation, total nitrogen load, and total phosphorus load factors have correlation in the highest value, in which total nitrogen load and total phosphorus load factors have a close correlation with each other from the lowest value to highest value; wetland and barren land factors correlate with the lowest value and the highest value; agricultural land, forestland, and grassy land factors correlate with one another in the high value and the highest value. The forest cover rate factor, as well as the population factor, does not correlate with other factors.

Combining SWAT with Machine Learning to Identify Primary Controlling Factors and Their Impacts on Non-Point Source Pollution

Non-point source (NPS) pollution has a complex formation mechanism, and identifying its primary controlling factors is crucial for effective pollution treatment. In this study, the Baixi Reservoir Watershed, characterized by low-intensity development, was selected as the study area. A new methodology combining the Soil and Water Assessment Tool (SWAT) with the Random Forest (RF) algorithm was proposed to comprehensively identify the primary controlling factors of NPS pollution and analyze the interaction between factors. The results of the validated SWAT model showed that the annual intensity of total nitrogen (TN) load range was 0.677–11.014 kg ha−1 yr−1, and the total phosphorus (TP) load per unit area range was 0.020–0.110 kg ha−1 yr−1. Loads of sediment, TP, and TN exhibited significant seasonal variations, particularly in the Baixi basin, where sediment yield had the highest absolute change rate, with a value of up to 232.26. Random Forest models for TN and TP displayed high accuracy (R2 > 0.99) and robust generalization ability. Fertilization, sediment yield, and terrain slope were identified through RF models as the primary factors affecting TN and TP. By graphing partial dependency plots (PDPs) based on the results of the RF models to analyze the interaction between factors, the findings suggest a strong synergistic effect of two combined factors: fertilization and sediment yield. When fertilizer application exceeds 15 kg ha−1 yr−1 and sediment yield exceeds 3 kg ha−1 yr−1, there is a sharp increase in nitrogen and phosphorus load. Through the identification and analysis of the primary controlling factors of NPS pollution, this study provides a solid scientific foundation for developing effective watershed management strategies.

Seasonally varying contributions of contemporaneous and lagged sources of instream total nitrogen and phosphorus load across the Illinois River basin

Quantifying nutrient sources in streams, their temporal and spatial variability, and drivers of that variability can support effective water resources management. Yet a lack of data and modeling capabilities has previously prevented comprehensive quantification across both space and time. Here a dynamic SPARROW (Spatially Referenced Regressions on Watershed attributes) model that accounts for a lagged delivery of nutrients to streams was developed and applied to simulate seasonal and source-specific total nitrogen (TN) and total phosphorus (TP) loads in streams across the Illinois River basin (IRB). Dynamic load predictions from 2000 through 2020 revealed that a third of the TN and a quarter of the TP instream load originated from non-point sources that were lagged in their delivery from land-application to streams by more than a season. This lagged mass was the largest overall TN source—which was estimated as a lagged expression of previous seasonal non-point sources including fertilizer, manure, atmospheric deposition and fixation, and urban land use. Treated wastewater effluent was the largest TP source exported from the basin, contributing 39 % of the TP load and 15 % of the TN load, and dominated the load in the upper Illinois River near Chicago. Loads in the lower river during this period, conversely, were attributed primarily to a mix of agricultural sources and their lagged fractions from headwater tributaries. Instream processes removed 10 % of the TN load while only 4 % of the TP load was removed during instream transport. With appropriate datasets, the models could be extended to other basins or time periods and used to forecast future seasonal nutrient loads.

Subsurface influences on watershed nutrient concentrations and loading in a clay dominated agricultural system

Water quality issues in the Great Lakes Basin persist despite management and monitoring efforts. With changing land use and climatic conditions, the need for improved understanding of nutrient loss from agricultural field to surface water is imperative to reduce consequences on human and aquatic life, such as perpetual algal blooms and contaminated drinking water. There remains a gap in holistic rural water management studies that investigate the understanding of the water cycle in rural settings and the interconnections between different components of the water cycle, including artificial drainage. In the current study, a year-round paired investigation of subsurface and nutrient dynamics was conducted in a small, intensively managed agricultural watershed within southwestern Ontario, Canada. Nutrients (Nitrate and Phosphorus) and stable isotopes of water (δ2H and δ18O) were sampled at varying scales (i.e., field and watershed), from multiple hydrologic components (e.g., groundwater, surface water, tile flow, and soil water), from 2020 to 2022. Results indicate that nutrient concentrations in surface water were elevated during the growing season, while nutrient loading was greater during the non-growing season in surface water. Monthly nitrate loads were found to be significantly (p < 0.01) related to groundwater elevation, soil moisture and tile flow, whereas total phosphorus loading was found to be significantly (p < 0.01) related to soil moisture and tile flow. δ2H and δ18O signatures revealed that during the growing season nutrient movement was predominantly through interflow pathways (including tile drainage) comprised of event-water. In the non-growing season, there was an increased subsurface influence on nutrient transport. This study highlights the importance of including subsurface characterization in nutrient management studies. A comprehensive understanding of varying seasonal hydrologic mechanisms that control nutrient movement within an agricultural watershed is essential to sustain growing rural communities.

Impacts of climate change on urban stormwater runoff quantity and quality in a cold region

Climate change poses significant challenges to urban environments affecting both flood risks and stormwater pollutant loadings. However, studies on variations in stormwater runoff quantity and quality in cold regions, which are highly sensitive to climate change, are notably limited. Integrating climatic, hydrologic, and hydraulic modelling, the study assesses the potential impacts of climate change on stormwater runoff volume and pollutant dynamics in a Canadian urban watershed (Calgary). A two-year field program was conducted to support the calibration and validation of the Storm Water Management Model (SWMM). Intensity–duration–frequency curves were employed to evaluate the impacts of climate change on peak flow rate and flooding duration. In addition, typical dry, average, and wet years were applied to continuously simulate stormwater runoff quantity and quality during the 2050s and 2080s. The results suggest substantial increases in peak flow rates and flooding durations, particularly for the 5-year return period rainfall, with 1-h, 4-h, and 24-h peak inflow rates increasing by 74.3% (170.7%), 89.2% (158.4%), and 64.1% (102.8%) in the 2050s (2080s) Furthermore, the runoff quantity is projected to rise by 2.4–10.2% in the 2050s and 11.8–17.5% in the 2080s. Total suspended solids (TSS), total nitrogen (TN), and total phosphorus (TP) loadings are anticipated to increase by 2.0–36.1%, 3.1–21.4%, and 4.1–20.7%, respectively. As a result, the current stormwater system could overload and stormwater quality is likely to deteriorate under the impact of climate change. The findings are beneficial for cold regions to develop adaptive strategies that enhance urban water security and environmental sustainability under climate change.

Effectiveness of diluting Moses Lake, Washington, with low phosphorus Columbia River water

Welch, EB and Brattebo SK. 2024. Effectiveness of diluting Moses Lake, Washington, with low phosphorus Columbia River water. Lake Reserv. Manage. 40:xxxx-xxxx. Moses Lake has been rehabilitated by dilution with low total phosphorus (TP) inflow to improve lake quality in 46 of the past 47 years. Inflows of low TP (7 µg/L) Columbia River water (CRW), which enters during April–September, have ranged from around 75 to over 400 × 106 m3 (mcm), representing 0.5–2.5 total lake volumes annually. The CRW inflows substantially lowered the May–September average lower lake TP from 152 µg/L during 1969–1970 before dilution to 25 µg/L during the past 24 years when CRW input averaged 250 mcm. Total P decreased to an average of 65 µg/L during 11 of the first 12 years following the start of large CRW inputs with the Clean Lakes Project in 1977. Increased CRW inflow since 2000 reduced TP to less than 30 µg/L and has greatly improved lake quality and lowered the cyanobacteria fraction of phytoplankton biomass. Cyanobacteria were minimal at 5–22% of phytoplankton biomass in 2 years (2001, 2021) with 284 mcm of CRW inflow and average TPs of 19 and 20 µg/L. Average TP was 20 and 25 µg/L and cyanobacteria were 12 and 22% in 2022 and 2023 with less CRW (235 and 197 mcm). Even in the more enriched upper lake, TP in 2021–2023 averaged about half that of the previous 4 years (39 vs. 73 µg/L) and cyanobacteria averaged 33% of phytoplankton biomass. Unless the internal TP load is reduced substantially, CRW input should be at least 250 mcm to dilute external and internal loading and to hold TP below 30 µg/L and minimize cyanobacteria, as occurred in 2021–2023.

One third of African rivers fail to meet the ’good ambient water quality’ nutrient targets

The ambition of Sustainable Development Goal (SDG) target 6.3 is to improve global water quality by 2030. SDG indicator 6.3.2 monitors progress towards this target by assessing water bodies against ‘good’ ambient water quality criteria, with nutrients (nitrogen and phosphorus) as part of the key metrics. However, large data gaps present a fundamental challenge, especially for Africa on how to assess the progress being made with respect to both the current and desired future situations. Here, a continental water quality model for Africa is presented to simulate river sediment load, Total Nitrogen (TN) and Total Phosphorus (TP) loads and concentrations. Furthermore, critical areas and hotspots of TN and TP pollution are mapped for the period 2017 – 2019, in relation to the United Nations Environment Programme (UNEP) target thresholds used for the assessment of SDG indicator 6.3.2. Utilizing the UNEP’s criteria, which designates a water body as having “good ambient water quality” if 80% or more of its monitored values meet their targets, it is estimated that 44 % and 15 % of African rivers fail to meet the set water quality thresholds for simulated TP and TN, respectively. When synthesizing data for both TP and TN, 34 % of the rivers do not qualify as having “good ambient water quality”. Geographically, the most pronounced nutrient pollution hotspots were in North Africa, Niger River Delta, Nile River basin, Congo River basin and specific zones in Southern Africa. These areas correlate with regions characterized by high inputs of fertilizers, manure and wastewater discharge.

Carrying Capacity of Water Environment and the Associated Optimization of Socioeconomic Structure of Yangzong Lake Basin, China

Yangzong Lake is the third largest deep-water plateau lake in Yunnan, China. Rapid socioeconomic development of the basin has resulted in pollution of water environment. This study aimed to identify the carrying capacity of water environment and to conduct the associated optimization of socioeconomic development. The results of this study showed that: (1) The carrying capacities of tributary rivers were small in relation to that of the lake. The maximum allowable annual loads of chemical oxygen demand (COD), ammonia nitrogen (NH3-N), and total phosphorus (TP) into the main rivers of the basin were 449.37, 24.73, and 5.38 tons, respectively. (2) Under the planning scenario, COD and NH3-N loads remain the primary constraints on economic and social development in the watershed. (3) In further optimizing the structure of the plantation industry, focusing on strengthening the collection and treatment capacity of rural domestic sewage, the watershed can achieve high-quality development of the tourism industry. The tourism output value in 2025 and 2035 can carry up to 20.28 billion CNY (growth rate: around 15.44%) and 76.80 billion CNY (growth rate: around 14.64%), respectively. This study can provide basic support for the future economic and social development of the watershed for decision-makers.

Long-term responses of internal environment dynamics in a freshwater lake to variations in external nutrient inputs: A model simulation approach

Lake restoration usually focuses on reducing external nutrient sources. However, when sediments contain nutrients accumulated over multiple years, internal nutrient release can delay restoration progress. In lake restoration and management, it is important to understand the dynamic relationship between nutrient concentrations in a lake and internal and external nutrient sources. In this study, we quantified external nutrient inputs through measurements and compared them with internal sediment release from simulation using the PCLake+ model. Additionally, we evaluated alterations in the internal nutrient release, lake nutrient concentrations, and algae biomass (chlorophyll-a) within the lake following varying degrees of reduction in external nutrient loads. The results demonstrate that the PCLake+ effectively simulated the lake's nutrient concentration and algae biomass. Based on the PCLake+ estimates, internal nutrient loads accounted for 51 % of the total nitrogen (N) and 80 % of the total phosphorus (P) loadings in Lake Erhai in 2019. In 2020, the total contributions were 43 % for TN and 72 % for TP. We simulated four scenarios where external nutrient inputs were reduced to 25 %, 50 %, 75 %, and 99.99 % of their original levels. The 40-year simulation showed that the lake's ecological system initially exhibited a fast internal response but reached equilibrium after eight years. P concentrations took longer to reach equilibrium compared to N concentrations, probably due to the stronger binding characteristics of P. To meet the water quality target in the future, it is necessary to reduce external N and P inputs into Lake Erhai by at least 23 % and 15 %, respectively, under current conditions. Although reducing external nutrient loads can indirectly lower internal nutrient loads, water management should address both external and internal loads simultaneously, as internal release cannot be effectively reduced by external reductions alone. Additionally, the lake's internal release may continue for several years, even with reductions in external inputs.

A hybrid approach to improvement of watershed water quality modeling by coupling process-based and deep learning models.

Watershed water quality modeling to predict changing water quality is an essential tool for devising effective management strategies within watersheds. Process-based models (PBMs) are typically used to simulate water quality modeling. In watershed modeling utilizing PBMs, it is crucial to effectively reflect the actual watershed conditions by appropriately setting the model parameters. However, parameter calibration and validation are time-consuming processes with inherent uncertainties. Addressing these challenges, this research aims to address various challenges encountered in the calibration and validation processes of PBMs. To achieve this, the development of a hybrid model, combining uncalibrated PBMs with data-driven models (DDMs) such as deep learning algorithms is proposed. This hybrid model is intended to enhance watershed modeling by integrating the strengths of both PBMs and DDMs. The hybrid model is constructed by coupling an uncalibrated Soil and Water Assessment Tool (SWAT) with a Long Short-Term Memory (LSTM). SWAT, a representative PBM, is constructed using geographical information and 5-year observed data from the Yeongsan River Watershed. The output variables of the uncalibrated SWAT, such as streamflow, suspended solids (SS), total nitrogen (TN), and total phosphorus (TP), as well as observed precipitation for the day and previous day, are used as training data for the deep learning model to predict the TP load. For the comparison, the conventional SWAT model is calibrated and validated to predict the TP load. The results revealed that TP load simulated by the hybrid model predicted the observed TP better than that predicted by the calibrated SWAT model. Also, the hybrid model reflects seasonal variations in the TP load, including peak events. Remarkably, when applied to other sub-basins without specific training, the hybrid model consistently outperformed the calibrated SWAT model. In conclusion, application of the SWAT-LSTM hybrid model could be a useful tool for decreasing uncertainties in model calibration and improving the overall predictive performance in watershed modeling. PRACTITIONER POINTS: We aimed to enhance process-based models for watershed water-quality modeling. The Soil and Water Assessment Tool-Long Short-Term Memory hybrid model's predicted and total phosphorus (TP) matched the observed TP. It exhibited superior predictive performance when applied to other sub-basins. The hybrid model will overcome the constraints of conventional modeling. It will also enable more effective and efficient modeling.

Dynamics and correlations of maximum water age zones and nutrients in the Changjiang Estuary, China

The hydrological process dominates the spatial and temporal concentrations of nutrients and other biogeochemical compounds in the large estuary where river and ocean meet. Water age is a measure of water renewal timescale and a characteristic parameter of hydrodynamics and contaminant transport. A large-scale river-sea linked and multi-process coupled 2D EFDC model was constructed from Datong hydrometric station of Changjiang River to the East China Sea. The effects of changes in river discharge on hydrodynamics and nutrients in the Changjiang Estuary were simulated and analyzed. Pollutant loads to the Changjiang Estuary are mainly from upstream inflows and local inputs. The proportion of total phosphorus (TP) loads from upstream is greater than the total nitrogen (TN) loads, accounting for about 90% and 78%, respectively. As the river discharge decreases, TN concentrations decrease in most regions, except for near large sewage discharges where TN concentrations increase while TP concentrations show a decreasing trend. When the river flow drops from over 60000 m3/s to a relatively low value of 10000 m3/s, the average TN concentration in the southern channel of the Shanghai section of the Changjiang Estuary increases by nearly 13%, while TP concentration decreases by nearly 5%. The model results show that the water age inside the river mouth is inversely proportional to the flow rate. In contrast, the water age outside the mouth is negatively with the river discharge. The water age maximum zones (WAMZ) are found in the estuary, ranging from within the estuary to 90 km from the mouth, and are likely to coincide with the positions of the turbidity maximum zones (TMZ), which move seawards or landwards with the increase or decrease of river discharge in the Changjiang Estuary. In addition to location, the value of water age maxima varies negatively with river discharge, which is also relevant to turbidity intensity likely. Water age and WAMZ can be the indicators to predict the changes in the water environment and nutrient sinks in the Changjiang Estuary.

Improvements in the InVEST water purification model for detecting spatio-temporal changesintotal nitrogen and total phosphorus discharges in the Huai river watershed, China

Improving water quality to provide freshwater is an urgent requirement for regional and even global social development. More accurate simulation of non-point sources pollution, monitored mainly by total nitrogen (TN) and total phosphorus (TP), has always been a challenge for InVEST water purification model, particularly in agricultural areas. This can be attributed to the fact that there is no reference data for TN and TP to rectify the outcomes modelled by this model. This paper provided these data to rectify simulation results of TN and TP to ensure their accuracy. The Huai River watershed (HRW) is an important grain production area with slow economic development, and non-point source pollution has exceeded point-source pollution. There is an urgent need for water management authorities to obtain complete spatio-temporal data on TN and TP loads and their exports to improve water quality. The reference data onloads and exports of TN and TP were estimated for the entire watershed and its sub-watersheds through an investigation-evaluation technique during 1980–2018. TN and TP loads generated from the agricultural sector were the major pollution sources in the HRW and had similar time trends during the same period. The spatial distribution of TN and TP exports was modelled byusingthe InVEST water purification model, and it was found that the temporal trends for the final exports of TN and TP into river systems were similar to those for TN and TP loads in the HRW for 1980–2018. Key driving factors were detected using the Geo-detector method to quantify the contribution rates of factors to the spatiotemporal exports of TN and TP. Our results showed that individual factors, such as precipitation and land use/cover, were the most important factors driving spatio-temporal variations in TN and TP exports in the HRW from 1980 to 2018. Meanwhile, the contribution rates of interactions between land use/cover and other factors were consistently highest in this watershed during the same period. In this study, we estimated the loads and exports of TN and TP, and modelled their spatial patterns in this watershed from 1980 to 2018, providing important information on TN and TP for water-related management authorities. We also provide a method for other river systems to calibrate the parameters in the biophysical table of InVEST water purification model based on final exports of TN and TP.

Groundwater inputs could be a significant but often overlooked source of phosphorus in lake ecosystems

Freshwater lakes are severely threatened, due largely to excess inputs of nutrients and other contaminants. Phosphorus (P) is receiving renewed attention due to recent increases in toxic cyanobacteria blooms in lakes worldwide. We investigated groundwater seepage for its role in P loading dynamics at Oneida Lake, New York, USA—one of the most well-studied lakes globally. P loading was measured at representative sites along the 88 km shoreline over three summers by directly measuring groundwater flow using seepage meters and porewater samplers. Groundwater seepage was a continuous and significant source of dissolved P over the summer months, comparable to tributary sources to the lake during that time. This constant input has enriched the concentrations of P in the nearshore surface waters, significantly above levels in the pelagic zone. Pore Total Phosphorus (TP) concentrations and loads reached extremely high values (up to 100 mg/L), with inorganic P representing only ~ 10% of TP per site. Groundwater seepage flows and P loadings were highly variable across space and time, partially explained by adjacent land uses and precipitation. Our research concludes that groundwater seepage is a significant, but overlooked, source of dissolved P and a crucial factor driving summer primary production at Oneida Lake, and likely other temperate lakes.

How to Achieve a 50% Reduction in Nutrient Losses From Agricultural Catchments Under Different Climate Trajectories?

AbstractUnder persistent eutrophication of European water bodies and a changing climate, there is an increasing need to evaluate best‐management practices for reducing nutrient losses from agricultural catchments. In this study, we set up a daily discharge and water quality model in Hydrological Predictions of the Environment for two agricultural catchments representative for common cropping systems in Europe's humid continental regions to forecast the impacts of future climate trajectories on nutrient loads. The model predicted a slight increase in inorganic nitrogen (IN) and total phosphorus (TP) loads under RCP2.6, likely due to precipitation‐driven mobilization. Under RCP4.5 and RCP8.5, the IN loads were forecasted to decrease from 16% to 26% and 21%–50% respectively, most likely due to temperature‐driven increases in crop uptake and evapotranspiration. No distinct trends in TP loads were observed. A 50% decrease in nutrient loads, as targeted by the European Green Deal, was backcasted using a combination of management scenarios, including (a) a 20% reduction in mineral fertilizer application, (b) introducing cover crops (CC), and (c) stream mitigation (SM) by introducing floodplains. Target TP load reductions could only be achieved by SM, which likely results from secondary mobilization of sources within agricultural streams during high discharge events. Target IN load reductions were backcasted with a combination of SM, fertilizer reduction, and CC, wherein the required measures depended strongly on the climatic trajectory. Overall, this study successfully demonstrated a modeling approach for evaluating best‐management practices under diverging climate change trajectories, tailored to the catchment characteristics and specific nutrient reduction targets.

Total nitrogen and phosphorus loads in surface runoff from urban land use (city of Lublin) under climate change

An expansion of impervious surfaces in urban areas leads to increases of nutrient loads discharged with the surface runoff to receivers. A study of a different density of urban development impact on total nitrogen (TN) and phosphorus (TP) loads from the city of Lublin (eastern Poland) with the use of the SWAT (Soil & Water Assessment Tool) model was performed. To distinguish between areas with high and low density of urban development (UHD and ULD), a special analysis of hydrological parameters has been proposed. Moreover, to investigate the impact of climate change, four variant scenarios were taken into account, combining the RCP (representative concentration pathway) 4.5 and 8.5 forecasts and the adopted time horizons (2026–2035 and 2046–2055). The results showed a much higher share of TN and TP from UHD compared to ULD (86%—32 022 kg/year and 89%—2574 kg/year, respectively). In addition, the variant scenarios showed that the forecasted increase in precipitation and temperature will result in increased loads of nutrients from UHD and ULD up to 30%. Furthermore, the current increase of inhabitant number, due to the Ukrainian war migration and the common tendency to convert agricultural land to residential areas, could contribute to further expansion of UHD and ULD areas and an additional increase of nutrient loads.Graphical abstract

Can the best management practices resist the combined effects of climate and land-use changes on non-point source pollution control?

Climate and land-use changes have an overlying impact on non-point source (NPS) pollution in river basins. However, the control effect of Best Management Practices (BMPs) for NPS pollution is not yet clear under future scenarios. The Soil and Water Assessment Tool (SWAT) model was coupled with the entropy-weighted method, global climate patterns and land-use data to explore the dynamic variations in total nitrogen (TN) and total phosphorus (TP) loads in the Jing River Basin during the baseline (2000−2020) and future periods (2021–2065), evaluate the pollution reduction effectiveness of individual and combined BMPs, and propose practical BMP configurations. Results indicate that a future trend of urban land expansion, particularly in the economic scenario (LU_SSP585), leads to weakened environmental ecosystems, while the sustainable scenario (LU_SSP126) exhibits more balanced land development. The MIROC-ES2L model demonstrates higher Taylor skill scores, forecasted significant increases in precipitation, maximum, and minimum temperatures under the SSP585 scenario. Spatial heterogeneity in TN and TP loads is notable, showing an upward trajectory in the future. The interaction between land-use and climate change has complex effects on TN and TP loads, with land-use-induced TN changes being relatively small (4.6 %) and TP changes substantial (24.3 %). The spatial distribution, under overlying effects, leans towards the influence of climate change, emphasizing its dominant role in TN and TP load variations. Distinct differences exist in the reduction of NPS pollution loads among different BMPs, with combined BMPs demonstrating superior effectiveness. The environmental-cost effectiveness trends of BMPs remain consistent across various future scenarios. RG (Return agricultural land to grass), RG + TT (Terracing), and RG + FR10 (Fertilizer reduction: 10 %) + GW (Grassed waterway) + FS (Filter strip) + TT emerge as the most effective single, double, and multiple BMP combinations, respectively. The results offer valuable insights for preventing and mitigating future NPS pollution risks, optimizing land-use layouts, and enhancing watershed management decisions.

Is comprehensive event sampling necessary for constraining process models of water quality? A comparison of high and low frequency phosphorus sampling programs for constraining the HYPE water quality model

Model parameter calibration is an important step in process-based watershed water quality modelling. Calibration is commonly performed using readily available water quality data from long-term monitoring programs that collect samples periodically at a relatively low frequency (i.e. monthly). Higher frequency synoptic and targeted event data is becoming available from more intensive monitoring programs, yet there remains little consensus on whether relatively lower frequency data are sufficient to constrain process-based watershed water quality models. To investigate the effects of using water quality data from differing sampling regimes for calibration, we use an implementation of HYPE (HYdrological Predictions for the Environment), a process-based watershed water quality model, in Southern Ontario, Canada. HYPE was calibrated with two stream water quality datasets, one associated with the long-term Ontario Provincial (Stream) Water Quality Monitoring Network and characterized by routine approximately monthly sampling frequency, and one associated with the Multi-Watershed Nutrient Study and characterized by semi-regular synoptic sampling during baseflow and at increased frequency (∼4 to 8 h) during event flow. Performances varied widely between sites, with validation ranges of daily predictions having Nash-Sutcliffe Efficiencies (NSE) from > −1 to 0.48 for flow and > −1 to 0.98 for total Phosphorus. Medians for daily data during validation ranged from 0.15 to 0.24 for flow and from 0.19 to 0.36 for total phosphorus. We found that model performance and simulated total phosphorus loads were similar for the two calibration datasets, potentially suggesting that the dataset with approximately monthly water quality sampling was adequate to constrain the HYPE model. We attribute this to a combination of similar levels of statistical variability in the calibration datasets and prior knowledge in the HYPE model structure. Furthermore, while model performance was similar when HYPE was calibrated with datasets of differing sampling strategies, there was a large range in model performance within each modelling domain. Results suggest that this range in performance could be due in part to poor representation of cold-weather processes in the HYPE model, as sites with higher mean annual temperature and fewer freezing days had better model performance.

Application of improved risk assessment methods to best management practices research for non-point source pollution: From a hilly mountainous-dominated region of Southern China

Non-point source pollution (NPSP) significantly affects regional water environments worldwide. Identifying critical source areas (CSAs) and implementing best management practices (BMPs) are essential to prevent and control NPSP. This study used the Soil and Water Assessment Tool model to simulate and evaluate the characteristics of NPSP in the Gongjiang Watershed, a typical, hilly mountainous area in Southern China. The study identified CSAs of NPSP using total nitrogen (TN), total phosphorus (TP), water quality level, and population density factors. The reduction effect of different BMPs on the NPSP load was evaluated, and the cost-effectiveness (CE) of various BMPs was evaluated for the control of NPSP in the watershed. The interannual variation in NPSP load was high from 2013 to 2018, with the largest pollution load in 2016 (wet year) and the smallest in 2018 (dry year). The pollution load fluctuated throughout the year and was related to fertilization and precipitation runoff. The spatial heterogeneity of NPSP was large, with TN and TP losses showing a spatial pattern of high in the south, low in the north, and highest in the center. The CSAs of the NPSP covered 1566.66 km2, representing 9.77 % of the total watershed area. However, TN and TP loads accounted for 19.39 % and 23.53 % of total watershed production. The order of effectiveness of individual management measures in reducing TN was stubble coverage (SC) > vegetative buffer strips (VBS) > terrace engineering (TE) > grassed waterways (GW) > 20 % fertilizer reduction (FR20) > 10 % fertilizer reduction (FR10). The order of effectiveness of TP reduction was SC > VBS > TE > FR20 > GW > FR10. Combined management measures were much more effective in reducing TN and TP than individual measures, with an average increase in TN and TP reduction of 20.59 % and 25.23 %, respectively. Based on the results of the CE evaluation of BMPs, a combination of FR20, GW, and VBS was more effective than individual measures. We suggest a combination of FR20, GW, and VBS measures for effective NPSP prevention and control in Southern China’s typical, hilly mountainous areas.

Optimizing Sampling Strategies for Estimating Riverine Nutrient Loads in the Yiluo River Watershed, China

Accurately estimating nutrient loads is crucial for effective management and monitoring of aquatic ecosystems. This study evaluated the uncertainty in different sampling frequencies and calculation methods for estimating total nitrogen (TN) and total phosphorus (TP) loads in the Yiluo River watershed, a tributary of the Yellow River in China. Using daily TN and TP concentration data from 2019 to 2020, we conducted a bootstrapping analysis to evaluate the accuracy of nine different load estimation methods at different sampling frequencies. Our results showed that Method 3 (M_3, constant concentration interpolation) and Method 7 (M_7, flow-weighted concentration method), when used with a biweekly sampling frequency, had the lowest Standard Deviation of the Percentage errors (STD) (7.70% and 8.60% for TN, 12.0% and 18.8% for TP, respectively) and Mean Relative Error (MRE) values (0.078% and −1.60% for TN, 0.305% and 2.33% for TP, respectively) on an annual scale. For monthly TN and TP load estimates, M_7 can control the MRE within ±20% at a biweekly sampling frequency. Furthermore, the uncertainty in TN and TP load estimates was generally larger during the summer months (June–September), emphasizing the important role of storm events in nutrient export. Extreme events (&lt;10% of the time) contributed approximately 50% of the annual nutrient loads. The findings of this study provide a scientific basis for optimizing water quality monitoring schemes and management strategies in agricultural watersheds.

Assessing the impacts of rice terraces and ponds on the sediment and phosphorus loads in a typical hilly watershed of three gorge reservoir, China

Phosphorus is the primary eutrophication cause of river, lake, reservoir and estuary and it may be one of the principal pollutants for the agricultural watershed with middle and small cities. The sediment and phosphorus loads, related migration paths and contribution of source regions to receiving waters at different sections of a river basin are not clear. The modified Soil and Water Assessment Tool (SWAT) model was utilized to investigate the phosphorus loads and the relationships among water resources, sediment, and phosphorus loads in one of the important tributaries of the Three Gorge Reservoir (TGR) of China, and to investigate the retention dynamics of phosphorus in the river continuum and the influencing factors. It showed that under the scenario of rice terraces and ponds, the annual sediment loss and total phosphorus load were 125t and 2.5t, being reduced by 40%–80% compared to the natural slope scenario; the daily peak value of suspended sediment load was reduced by 30%–75%, and the relationship between the rainfall and runoff was weakened slightly; the retention rate of phosphorus sources reached 40%–78%. The results confirm that the rice terraces and ponds have altered local hydrological conditions, enhanced a substantial water, sediment, and phosphorus retention capacity that is highly consistent over time and space scales, thereby altering the predominant forms of phosphorus and improving the environmental resilience in soil and nutrition loss for the hilly watershed of the TGR.