Total Phosphorus Loads Research Articles

Spatial optimization of ecological ditches for non-point source pollutants under urban growth scenarios.

Non-point source (NPS) pollution is regarded as the major threat to water quality worldwide, and ecological ditches (EDs) are considered an important and widely used method to collect and move NPS pollutants from fields to downstream water bodies. However, few studies have been conducted to optimize the spatial locations of EDs, particularly when the watershed experiences urbanization and rapid land-use changes. As land-use patterns change the spatial distribution of NPS loads, this study used a cellular automata-Markov method to simulate future land-use changes in a typical agricultural watershed. Three scenarios are included as follows: historical trend, rapid urbanization, and ecological protection scenarios. The spatial distributions of particulate phosphorus loads were simulated using the revised universal soil loss equation and sediment transport distribution model. The results suggested that the total particulate phosphorus (TP) load in the Zhuxi watershed decreased by 10,555.2kg from 2000 to 2020, primarily because the quality and quantity of forests in Zhuxi County improved over the last 20years. The TP load in Zhuxi watershed would be 2588.49, 2639.15, and 2553.32kg in 2040 in historical trend, rapid urbanization, and ecological protection scenarios, respectively, compared with 2308.1kg in 2020. This indicated that urban expansion increases the TP load, and the faster the expansion rate, the more the TP load. Consequently, the optimal locations of EDs were determined based on the intercepted loads and the period during which they existed during land-use changes. The results suggested that rapid urbanization would consequently reduce the space available for building EDs and also increase the cost of building EDs to control the NPS pollution in the watershed.

Performance and sustainability of a multi-stage free water surface constructed wetland under seasonal change and shock loading

Multi-stage constructed wetlands (CWs) are widely used for water quality improvement, especially in the treatment of wastewater. Many studies focus on their treatment efficiency under steady loading, but fewer studies consider their sustainability under variable conditions. This study examines the multi-stage CWs in the Hong Kong Wetland Park for their long-term performance and sustainability in terms of water quality under seasonal changes, storm events, and shock loadings of pollutants. The results show that the multistage design performs well and is stable under these changing conditions. In such multistage CWs, the type of units and some changing conditions (e.g., inflow concentrations, seasonal changes of vegetation, and water levels) also affect the performance of the whole system. Compared to individual CW, a multi-stage CW system could recover more quickly on dissolved oxygen (DO), and ammonia nitrogen (NH4), but slowly on biochemical oxygen demand (BOD) and total phosphorus (TP). A pre-processing and buffering area is necessary to handle the shock loadings of BOD and TP in such a multistage CW system. Although water levels recover quickly in both, it is difficult to return to original water levels in multi-stage CWs compared to single ones. Besides, for sustainable operation, attention should be paid to the DO of the inlet, and aeration measures might be taken.

Evaluation of statistical models: Perspective of water quality load estimation

The accurate representation of the load of water quality constituents, transported by rivers and streams, is crucial to understand the impact on the quality of the lakes, the behavior of the rivers and streams. Statistical models have been developed to predict the water-quality constituent loads from the available data of sampled concentration (low-frequency/grab chemistry data) and continuous discharge (high frequency) at a particular sampled location and to further analyze trends and changes in water quality. However, the performance of statistical models to estimate water quality constituent loads depends on many aspects including the type of water quality constituent, sampling strategy and frequency, and the land use and areas of the watershed. This study evaluates the performance of a wide range of statistical models for the estimation of total suspended solids (TSS) and total phosphorus (TP) loads under various sampling scenarios and monitoring stations in Southern Ontario, Canada. Trends in TSS and TP concentrations and loads were further analyzed in major tributaries. The Weighted Regression on Time, Discharge, and Season Kalman Filter (WRTDS_K) model was found to be the most suitable model (p > 0.05 and Percentage Difference (%) (PDIFF) between ±20) for predicting TSS loads at most sampling stations and under most sampling scenarios, while, the Weighted Regression on Time, Discharge, and Season (WRTDS) model was found to be the most suitable model (p > 0.05 and flux bias statistics (FBS) between ±0.1) for predicting TP loads. The applied statistical models (LOADEST simple and curvilinear models, WRTDS, WRTDS_k, Beale’s estimator, composite and interpolation models) have shown a limited potential to estimate load accurately at monitoring stations covering small drainage areas.

Risk Assessment of Nonpoint Source Pollution in the Huaihe River Basin

After years of treatment, the water pollution situation in the Huaihe River Basin (HRB) is still grim, and agricultural nonpoint source pollution has become the leading cause of the problem. However, agricultural nonpoint source pollution in the HRB is complicated due to the compounding effects of multiple factors. In this study, we first applied the export coefficient model to estimate the total nitrogen (TN) and total phosphorus (TP) loads used as two pollution source indicators in HRB. Then we constructed an index evaluation system of nonpoint source pollution risk by coupling the two source indicators with five additional indicators: rainfall erosion, river network distribution, soil erodibility, slope length, and land use. The primary source of TN and TP loads is fertilizer application (81.96%), followed by livestock and poultry breeding (16.3%) and rural domestic wastes (1.74%). The risk assessment results indicate that 66.43% of the HRB is at medium to high risk of nonpoint source pollution, 12.37% is at high risk, and 11.20% is at low risk. Moreover, the medium-to-high-risk areas are mainly concentrated in the Henan and Anhui provinces. In contrast, the medium-risk regions are mainly distributed along the mainstream of the Huaihe River. Finally, the observed water quality categories were used to verify our findings. The controlling areas of nonpoint source pollution in HRB are identified. This study could provide a scientific basis for effectively preventing and treating water pollution in the HRB.

Effect of alfalfa on subsurface (tile) nitrogen and phosphorus loss in Ohio, USA.

Growing annual crops such as corn (Zea mays L.) can lead to considerable nutrient losses through subsurface drainage in agricultural fields, posing a serious threat to surface water quality in the midwestern United States. Perennial crops have the potential to reduce these nutrient losses. However, more comprehensive data are needed on the nutrient loss effect of perennial crops. We examined the effect of alfalfa (Medicago sativa L.) on nitrate-nitrogen (NO3 - -N), total nitrogen (TN), dissolved reactive phosphorus (DRP), and total phosphorus (TP) in subsurface drainage using a before-after-control-impact (BACI) experimental design with one control field (with annual crops) and one impact field (with alfalfa) each on two farms (Sites A and B) located in northwestern Ohio. The "Before" period (prior to planting alfalfa at the impact field) extended for 4 yr (2013-2017) at Site A and 6 yr (2011-2017) at Site B; the "After" period extended for an additional 2 yr at both sites. Reductions in the mean monthly discharge and loads of NO3 - -N, TN, DRP, and TP were significant at Site A, whereas the only significant change at site B was a reduction in the mean monthly TP load. Significant reductions in NO3 - -N loads were observed during spring and winter at Site A. In addition, alfalfa reduced the variability of discharge and nutrient loads through subsurface drainage at both sites. Our findings suggest that introducing alfalfa into annual crop rotations has the potential to reduce subsurface nutrient loads and increase the resiliency of agricultural systems.

Investigating the influences of concave depths on stormwater runoff and pollution retention of urban grasslands.

In this study, scale-based runoff plots of concave grasslands were designed and simulated rainfall experiments were conducted to investigate their retention effectiveness for runoff volume and pollutant loads, and to analyze the influences of concave depths on runoff and pollution retention of grasslands. Results showed that mean time to runoff of concave grasslands was 88.5 minutes, which was 5.3 times than that of flat grassland. Average peak flow rate of concave grasslands was reduced by 36.2% compared with flat grassland. Concaved grasslands averagely retained 58.2% of stormwater runoff. Deeper concave depths significantly increased runoff detention and retention performance of grasslands. Total suspended solids (TSS) load reduction rates of concave grasslands were ranged from 50.8% to 97.3%. Total nitrogen (TN) load reduction rate was 49.8% for concave depth of 10 cm. Total phosphorus (TP) load reduction rates were 45.0% and 93.9% for grasslands with 5 cm and 10 cm concave depths, respectively. Pollution load reduction rates of TSS, TN and TP enhanced along with the increase in concave depths. The estimated minimum area ratios of upslope impervious surface to grasslands of 5 cm and 10 cm concave depths were approximately 1:1 under 20 mm rainfall events, and 38:1 under 5 mm rainfalls, respectively.

A process-guided hybrid Bayesian belief network to bridge watershed modeling and BMP planning

Planning of Best Management Practices (BMPs) is increasingly dependent on Process-based Watershed Models (PWMs) and suffers from large uncertainties. The large complexity and long runtimes of such models make prudential watershed management a difficult undertaking. In this study, we aimed to bridge the gaps between PWMs and uncertainty-based BMP planning with Bayesian Belief Network (BBNs). A new modeling framework of Process-guided Hybrid BBNs (PH-BBNs) was developed to represent the probabilistic cascade of critical modules in Soil & Water Assessment Tool (SWAT), a widely-used PWM, across external stressors (e.g., weather and various BMPs), parametric uncertainties, and watershed predictors. The PH-BBN modeling framework was used for decision support of Nonpoint Source (NPS) pollution mitigation in an intensively-cultivated area adjacent to Lake Dianchi, one of the three most eutrophic lakes in China. Our findings suggest that PH-BBNs can capture the critical pathways of water, sediment, and Total Phosphorus (TP) loss. Watershed projections are subject to large uncertainties to varying degrees in different landscapes. According to variance-based sensitivity analysis, precipitation accounts for >80% of the projection variability, which underlines watershed vulnerability to climate change. As the effectiveness of parallel terraces, filter strips, and fertilization management would degrade with increasing rainfall intensity, they should be conservatively designed for BMP sustainability. Implementation of parallel terraces and filter strips is recommended as they are projected to reduce 80% of TP loads with >90% compliance confidence. PH-BBNs can render effective decision support for BMP risk assessment and adaptive watershed management under climate change.

Improving estimates of phosphorus loads using hierarchical models

Estimates of nutrient loads are critical for managing the effects of nutrient pollution in receiving waters. An accurate calculation of load requires sub-daily, concurrent measurements of flow and nutrient concentrations. Continuous flow measurements are common, but nutrient concentrations are often measured infrequently, and so, statistical estimates of flow – concentration relationships are often used to infer nutrient concentration on unsampled days. Contributions of diffuse, nonpoint sources to flow – concentration relationships in neighboring sites may be similar, and methods are available to apportion in-stream concentrations to contributions from point and nonpoint sources. Combining a source apportionment model with a hierarchical statistical model may be a useful approach for leveraging information from more intensively sampled sites to improve estimates of relationships at more sparsely sampled sites. The approach is tested using daily measurements of total phosphorus and flow from eight rivers in Ohio, USA. Data from seven of the rivers are randomly subsampled to a single sample from each month, and a hierarchical model fit to estimate flow – concentration relationships for all sites. Hierarchical model estimates of phosphorus loads in subsampled sites were compared with three site-specific models: a linear flow – concentration relationship, a quadratic flow – concentration relationship with seasonal corrections, and Beale’s ratio method. The hierarchical model improved substantially on the precision of estimated total phosphorus loads at sparsely sampled sites, yielding an interquartile range of prediction errors of 22%. Simple linear load – concentration models were the next best performing method with an interquartile range of 33%. The average bias in hierarchical model predictions of phosphorus loads was 8%, whereas the smallest biases associated with the comparison methods were –10% for both the linear load – concentration model and Beale’s ratio. These results suggest that a hierarchical statistical model can be valuable for improving nutrient load estimates when data from a small number of intensively sites are available.

Impacts of different types of El Niño events on water quality over the Corn Belt, United States

Abstract. The United States Corn Belt region, which primarily includes two large basins, namely, the Ohio–Tennessee River basin (OTRB) and the Upper Mississippi River basin (UMRB), is responsible for the Gulf of Mexico hypoxic zone. Climate patterns such as El Niño can affect the runoff and thus the water quality over the Corn Belt. In this study, the impacts of eastern Pacific (EP) and central Pacific (CP) El Niño events on water quality over the Corn Belt region were analyzed using the Soil and Water Assessment Tool (SWAT) models. Our results indicated that, at the outlets, annual total nitrogen (TN) and total phosphorus (TP) loads decreased by 13.1 % and 14.0 % at OTRB and 18.5 % and 19.8 % at UMRB, respectively, during the EP El Niño years, whereas during the CP El Niño years, they increased by 3.3 % and 4.6 % at OTRB and 5.7 % and 4.4 % at UMRB, respectively. On the subbasin scales, more subbasins showed negative (positive) anomalies of TN and TP during EP (CP) El Niño. A seasonal study confirmed that water quality anomalies showed the opposite patterns during EP and CP El Niño years. At the outlet of OTRB, seasonal anomalies in nutrients matched the El Niño–Southern Oscillation (ENSO) phases, illustrating the importance of climate variables associated with the two types of El Niño events on water quality in the region. At the UMRB, TN and TP were also influenced by agricultural activities within the region, and their anomalies became greater in the growing seasons during both EP and CP El Niño years. A quantitative analysis of precipitation, temperature, and their effects on nutrients suggested that precipitation played a more important role than temperature did in altering the water quality in the Corn Belt region during both types of El Niño years. We also found specific watersheds (located in Iowa, Illinois, Minnesota, Wisconsin, and Indiana) that faced the greatest increases in TN and TP loads and were affected by both the precipitation and agricultural activities during the CP El Niño years. The information generated from this study may help proper decision-making for water environment protection over the Corn Belt.

Effects of local land-use policies and anthropogenic activities on water quality in the upstream Sesan River Basin, Vietnam

Study regionThis study focuses on the upstream Sesan River Basin in the Central Highlands of Vietnam. Study focusLocal land-use policies and human activities can significantly affect hydrology and increase the magnitude of erosion and nutrients in downstream areas. The effects in terrestrial regions on water quality of the target area were evaluated during the 2000–2018 period using the SWAT (Soil and Water Assessment Tool) with updated land-use conditions following the local policy decisions and agricultural practices in different periods. New hydrological insights for the regionsThis study indicates that the implementation of the local land-use policies, along with extensive anthropogenic activities, has had significant effects on the downstream aquatic environment as compared with the period before the implementation of the land-use policies. Higher annual sediment, total nitrogen (TN), and total phosphorus (TP) loadings were found upstream from the Poko Watershed, where range land predominated, and in southern and southwestern Dakbla Watershed, where arable land and permanent cropland predominated. Arable land had the highest proportion of sediment and nutrient loadings into the reach, especially in the 2005–2009 period (conducting afforestation, agricultural expansion, and urbanization) and in the 2010–2014 period (applying crop conversion policy involving a shift from mixed forests to rubber forests). Understanding the watershed characteristics along with the combination of spatial land use, local land-use policies, and agricultural practices will support the implementation of regional land use and water resources management strategies more comprehensively.

Nitrogen and phosphorus load estimation of inflow rivers to Yuqiao Reservoir based on GWLF model

Watershed model technology was an important tool for non-point source pollution prevention and control. In order to figure out the total nitrogen (TN) and total phosphorus (TP) load of inflow rivers to Yuqiao Reservoir in 2021, GWLF model was used to simulate the hydrologic process in its sub-basin. Firstly, the hydrological parameters of the model were determined by the measured meteorological and hydrological data. Secondly, the hydrological parameters were extended to the whole basin, and the three main river inflows to Yuqiao Reservoir were simulated in 2021. Lastly, the nutrient loads were estimated by multiplying the simulated inflow as mentioned above by the observed TN and TP concentration data at the same site. The results showed that the TN and TP load of inflow rivers was 7 106.9 t and 80.0 t, respectively, of which the flood period from July to August contributed 55.3% and 69.3%, respectively. GWLF model was effective in simulating hydrological processes in the study area. The Nash efficiency coefficients of the calibration and the validation period were 0.89 and 0.91, respectively. GWLF model was suitable for hydrological simulation and estimation of non-point source pollution load in small and medium-sized basins.

Stream corridor and upland sources of fluvial sediment and phosphorus from a mixed urban-agricultural tributary to the Great Lakes

Like many impaired Great Lakes tributaries, Apple Creek, Wisconsin (119 km2) has Total Maximum Daily Load (TMDL) targets for reducing suspended sediment and total phosphorus by 51.2 % and 64.2 %, respectively. From August 2017 - October 2018, a stream sediment budget and fingerprinting integrated study was conducted to quantify upland and stream corridor sources of suspended sediment and sediment-bound phosphorus. Phosphorus concentrations varied among source groups and fluvial sediments, with higher concentrations among suspended sediment and cropland soils. Eroding streambanks identified in the stream corridor sediment budget accounted for 100 % of the TMDL Soil and Water Assessment Tool (SWAT) suspended sediment load but only 20 % of the total phosphorus load. Fine-grained streambed sediment equated to approximately-three years of modeled suspended sediment load but only one third of total phosphorus load. The two primary sources of fine-grained streambed sediment were streambanks and cropland, with relative streambank contributions increasing with downstream direction and watershed area. The relative proportion of suspended sediment varied by season and streamflow; however, cropland and streambank erosion accounted for 54 % and 23 % of the suspended sediment when weighted by of the proportion for representative streamflow. Urban land was a source in the upper watershed, but the signature was sequestered by a mid-watershed detention basin. Contributions from construction sites were higher in the fall 2018, likely corresponding to increased activity following a wet spring. These integrated techniques helped describe sources, transport, and sinks of fluvial sediment and phosphorus throughout the watershed at a range of spatial and temporal scales.

Seasonal Variations in Water Quality and Algal Blooming in Hypereutrophic Lake Qilu of Southwestern China

Understanding the spatiotemporal distributions and variation characteristics of water quality parameters is crucial for ecosystem restoration and management of lakes, in particular, Lake Qilu (QL), a typical plateau shallow lake on the Yunnan-Guizhou Plateau, southwestern China. To identify the main causes of harmful algal blooming and continuous water quality decline, the total phosphorus (TP), total nitrogen (TN), water temperature (WT), dissolved oxygen (DO), chlorophyll-a (Chl-a), pH, and turbidity in hypereutrophic Lake Qilu from January 2017 to December 2021 were analyzed. The results showed a complex pattern in spatiotemporal distribution and variation. WT showed no significant change in the vertical profile. DO and pH value variations were caused by both physical and biochemical processes, especially at the bottom of Lake QL with an anaerobic environment. The Trophic State Index (TSI) assessment results showed that Lake QL is a eutrophic (70.14% of all samples, 50 < TSI < 70) to a hypereutrophic lake (29.86%, 70 < TSI) with poor water quality (WQI < 25). TP and WT were the main factors controlling harmful algal blooms (HABs) based on the statistical analysis of Principal Component Analysis (PCA), Random Forest Model (RFM), and Correlation Analysis (CA). In lake QL, TP loading reduction and water level increase might be the key strategies for treating HABs in the future. Based on our results, reducing TP loading may be more effective than reducing TN to prevent HABs in the highly eutrophicated Lake Qilu.

Response Model for Urban Area Source Pollution and Water Environmental Quality in a River Network Region.

With the development of cities, urban area source pollution has become more severe and a significant source of water pollution. To study the relationship between urban area source pollution and water environmental quality in a river network, this study uses a city in the Yangtze River Delta, China, as an example. The Storm Water Management Model (SWMM) model and the MIKE11 model were combined into a unified modeling framework and used to simulate dynamic changes in the water quality of a river network under light rain, moderate rain, and heavy rain. In the study period, the annual urban area source input loads of potassium permanganate (CODMn), total phosphorus (TP), and ammonia nitrogen were 29.8, 0.9, and 4.8 t, respectively. The influence of light rain on the water quality of the river network was lagging and temporary, and rainfall area pollution was the primary contributor. Under the scenario of moderate rain, overflow from a pipeline network compounded rainfall runoff, resulting in a longer duration of impact on the water quality in the river. Additionally, the water quality in the river course was worse under moderate rain than under light or heavy rain. Under the scenario of heavy rain, rain mainly served a dilutive function. This research can provide support for urban area source pollution control and management.

Spatiotemporal characteristics of nonpoint source nutrient loads and their impact on river water quality in Yancheng city, China, simulated by an improved export coefficient model coupled with grid-based runoff calculations

Accurately quantifying the spatiotemporal nutrient loads from nonpoint sources (NPSs) is still difficult due to the high spatial heterogeneity and temporal variability in rainfall-runoff processes. The export coefficient model (ECM) is a widely used tool to estimate the NPS nutrient load on an annual time scale, but it hardly considers the spatiotemporal distribution of the export coefficient. To address this issue, the ECM is improved by incorporating a grid-based rainfall-runoff module together with land-use data and analysing the spatiotemporal characteristics of the NPS nutrient loads in Yancheng city located in eastern China. Moreover, the effect of NPS nutrient loads on river water quality is assessed using a conceptual model. The results indicate that the improved ECM can simulate reasonable spatiotemporal variation in NPS nutrient loads, and the relative error in the total phosphorus (TP) load is less than 17.14 %. Precipitation has a considerable influence on both the total nitrogen (TN) and TP loads, which varied greatly from 1990 to 2018, with average annual values of 30.57 × 103 tons and 2.44 × 103 tons, respectively. The spatial distributions of the TN and TP loads were greatly affected by land-use patterns, and bodies of water and rural land had relatively high load intensities. Both TN and TP concentrations in the river exceeded the national standard, but TP was significantly reduced in the past 10 years, while TN was still at high level. This study provides a reference for reducing the river pollution in Yancheng city, especially by identifying pollution sources requiring priority control.

Assessment of Diffuse Pollution Loads in Peri-Urban Rivers—Analysis of the Accuracy of Estimation Based on Monthly Monitoring Data

Diffuse pollution loads are crucial information for water resource management, and yet field data are often scarce, implying questionable accuracy in load estimates made from low-frequency water quality monitoring. This paper aimed to characterize diffuse pollution in a stream of a mixed-land-cover watershed with a significant portion of urbanized areas through intensive monitoring and to perform a comparative analysis between the loads estimated by pollutant rating curves obtained by regression and the estimates using monthly water quality data, which is the method currently used. Continuous rainfall and flow monitoring was conducted between 2019 and 2021, and samples were collected during flood events and the dry period for water quality analysis. Flood events were found to induce an increase in suspended solids (TSS) and COD concentrations, while inorganic nitrogen (Inorg-N) concentrations were higher in the dry season. Flood characteristics showed a positive correlation with solids and COD event mean concentrations (EMCs) and negative with Inorg-N EMCs, while rainfall characteristics, such as antecedent dry days and intensity, correlate positively with all these pollutants. The rating curves performed well for total load estimation in low discharge events (R2 and NSE > 0.8), except for total phosphorus (TP) loads. Estimated annual unit loads found for the watershed were 2 ton TSS/ha.year, 300 kg COD/ha.year, 5 kg Inorg-N/ha.year, and 0.5 kg TP/ha.year, showing high pollution generated in the watershed. Finally, a comparison with estimates based on monthly monitoring data indicated that this method is sufficient for accurate nutrient loads, but not for TSS and COD loads, which require continuous monitoring to improve the accuracy of estimation.

Seasonal and interannual variability of residence time and total phosphorus in a small hypereutrophic lake in the Brazilian northeast

This study evaluates the residence time (RT) and total phosphorus (TP) in a small hypereutrophic lake in the city of Fortaleza, Brazil. The results indicate that RT predicted by a complete-mix model is very similar (R² = 0.83) to that simulated with a 2-D hydrodynamic model (CE-QUAL-W2). Simple power-laws were fitted to describe RT and TP concentration at the lake inlet as functions of lake inflow, yielding correlations of R² = 0.84 and 0.70, respectively. The combination of these correlations with a complete-mix approach provided a comprehensive model that predicted TP values measured at the lake outlet reasonably well (R² = 0.60). In addition, a direct empirical correlation between simulated TP concentration and precipitation was also obtained. The simulations indicate a nearly periodic behaviour of RT and TP, with the seasonal variations being much higher than the interannual ones. Finally, an application of the model showed that a reduction of 99% of the input TP load was required to reach 100% compliance with the required water quality standards; this could be achieved by connecting the residences to the sewage network. The methodology proposed in this research can be easily applied to other lakes in the Brazilian northeast and extended to other tropical regions around the globe.

Brief overview of allochtonous phosphorus load on cascade reservoirs in Citarum River Basin, West Java Indonesia

The Citarum River, Indonesia, has undergone degradation due to the pollutants, including phosphorus, that enters the river and the reservoirs of Saguling, Cirata, and Juanda (The official name of Jatiluhur Reservoir). The observations of total phosphorus (TP) load instantaneously had been carried out on the three reservoirs and TP measurements from 8 to 12 August 2019. The TP concentration in the inlets was generally very high (> 0.3 mg L-1), whereas the average TP concentration in Saguling, Cirata, and Juanda Reservoirs was 0.378 mg L-1, 0.343 mg L-1, and 0.324 mg L-1, respectively. Based on the trophic criteria, the condition of the waters in the three reservoirs was hypertrophic. Meanwhile, the average TP level in the Saguling showed the highest level compared to other reservoirs, which is in line with the TP concentration that enters the Saguling Reservoir, which is generally very high. Based on the instantaneous inputs, the loading TP to Saguling, Cirata, and Juanda Reservoirs were 26.471 g sec-1, 36.241 g sec-1, and 55.573 g sec-1, respectively. This indicates that the loading of phosphorus from upstream to downstream tends to increase.

Agricultural Structures Management Based on Nonpoint Source Pollution Control in Typical Fuel Ethanol Raw Material Planting Area

Increasing the promotion and application of biofuel ethanol has been a national strategy in China, which in turn has affected changes in the raw material planting structure. This study analyzed the effects of agricultural land-use changes on water quality in a typical maize fuel ethanol raw material planting area. The results revealed that an increase in cultivated land and construction land would also increase the load of TN (total nitrogen) and TP (total phosphorus), while an expansion in forest land would reduce the load. As for crop structures, maize might have a remarkable positive effect on TN and TP, while rice and soybean performed in no significant manner. Furthermore, scenarios under the carbon neutralization policy and water pollution control were carried out to forecast the nonpoint source pollutants based on the quantitative relations coefficients. It was proven that maize planting was not suitable for vigorous fuel ethanol development. Reducing maize area in the Hulan River Basin was beneficial to reducing nonpoint source pollution. However, the area of maize should not be less than 187 km2, otherwise, the food security of the population in the basin would be threatened. Under the change in fuel ethanol policy, this study could provide scientific support for local agriculture land-use management in realizing the carbon neutralization vision and set a good example for the development of the fuel ethanol industry in other maize planting countries.

Exploring the Relationship between Cover Crop Adoption and Soil Erosion Severity: A Case Study from the Simcoe Watershed, Ontario, Canada

Runoff from agricultural fields during the nongrowing season is a significant factor leading to phosphorous loading and diminishing water quality in Lake Simcoe, Ontario. Cover crops offer the potential to alleviate phosphorous loss during the nongrowing season by minimizing soil erosional processes and uptaking excess phosphorous; however, recent research suggests that its adoption remains relatively low. More concern lies with the lack of cover crop adoption on areas that are sensitive to soil erosion. This study intends to investigate the likelihood of agricultural productions located on erosive soils to adopt cover crops. Using satellite imagery in corroboration with the Universal Soil Loss Equation (USLE), this study reveals the frequency of cover crop production and associates soil loss sensitivity at a 30 m resolution from 2013 to 2018. Consistent with recent literature, this study reveals that a small portion (18%) of agricultural operations in the south Simcoe Watershed have incorporated cover crops over the past six years. Cover crops tend to be adopted at a low frequency in areas that have a low sensitivity to soil erosion. This study reveals that areas with higher soil erosion sensitivity are consistent with low-frequency adoption, indicating that these areas are less likely to adopt cover crops regularly. Promoting farm-scale benefits associated with cover crops should target areas in the south Simcoe Watershed that are prone to soil erosion to mitigate total phosphorus (TP) loading into Lake Simcoe.