Effect of Land Use Changes on Water Quality in an Ephemeral Coastal Plain: Khambhat City, Gujarat, India

Evaluating the impact of urban sprawl on the urban ecological status using GIS and remote sensing from 2000 to 2021: a case study of Herat City, Afghanistan

Urbanization often incurs environmental costs, as fertile agricultural and forested lands are converted into urban areas. Herat City is currently undergoing significant urban transformation. This research aims to assess the impact of urban sprawl on Herat City's urban ecological status during 2000, 2013, and 2021, using GIS and remote sensing. The urban expansion intensity index was used to measure urban sprawl. The Mean Remote Sensing Ecological Index (MRSEI), integrating known granulation entropy (KGE) and comprehensive distance-based ranking (COBRA) algorithms, was utilized to evaluate urban ecological status. The random forest (RF) supervised machine learning-based algorithm was used to classify the study area into four categories (Built-up, Bare-land, Water, and Vegetation). Findings indicate rapid development from 2000 to 2013, followed by moderate expansion until 2021. Urban ecological quality degradation is observed in various directions over time, with the southeast consistently demonstrating excellent status. Interestingly, while good and excellent urban ecological status decreases over two decades, poor and very poor conditions improve. The research underscores an inverse relationship between urban expansion intensity and ecological status, highlighting the need for improved strategies to mitigate environmental decline. These findings will inform Afghan governmental bodies and international organizations, enabling them to better address resource consumption, ecological disruptions, social inequalities, and foster sustainable development.

Assessing the impact of water-sediment factors on water quality to guide river-connected lake water environment improvement

The substantial impacts of exogenous pollutants on lake water quality have been extensively reported. Water-sediment factors, which are essential for regulating water quality in river-connected lakes, have not been studied in depth under different hydrological conditions. This study has combined a 31-year water environmental dataset (1991-2021) regarding Dongting Lake and a vector autoregression model (VAR) in order to investigate the impulse response characteristics and contributions of water quality caused by water-sediment factors across different periods. Our analysis suggests that total nitrogen (TN) exhibited a significant increasing trend, whereas total phosphorus (TP) increased to 0.17 mg/L, and then decreased to 0.07 mg/L from 1991 to 2021. The inflow of suspended sediment discharge (SSD) decreased significantly during the study period, mainly because of the decrease in SSD in the three channels (TC). In the pre-Three Gorges Dam (TGD) period, water discharge (WD) and SSD were the Granger causes of TN and TP. In the post-TGD periods this relationship disappeared because of the construction of the TGD, which reduced the inflow of SSD and WD into the lake. Water quality indicators showed an instant response to the shock from themselves with high values, whereas the impulse response of the water quality to water-sediment factors exhibited lagged variations. This meant that the water quality indicators displayed a high impact by themselves across the different periods, with values varying from 67 % to 95 %. Water level (WL) and SSD were the predominant water-sediment factors for TP in the pre-TGD period, with the impact on TP changes accounting for 11 % and 9 %, respectively, whereas the contribution of SSD decreased to 2 % in the post-TGD period. WL was the most crucial water-sediment factor for CODMn during the different periods, with contributions varying from 17 % to 20 %. To improve the water quality of Dongting Lake, in addition to the implementation of strict controls on excessive external nutrient loading, regulating water-sediment factors according to the hydrological features of Dongting Lake during different periods is vital.

Land use change in rapidly developing economies-a case study on land use intensification and land fallowing in Kochi, Kerala, India

The land use/land cover change is a local driver of environmental change having cascading impacts and implications at the global level, and therefore requires appreciable consideration when perceived from sustainability perspectives. Kerala, the southernmost state of India, has undergone a dramatic transition from a traditional agrarian economy to a modern thriving economy involving the irrational exploitation of natural resources, precisely, land and its components. The present study addresses how land is being changed along an urbanization gradient in the most agglomerative city in the state, Kochi, during the last one and half decades. High-resolution remote sensing data available from the Google Earth Pro pertaining to the four time periods, i.e., 2005, 2010, 2015, and 2020, representing urban, suburban, and rural areas, were analysed to estimate the changes in land use land cover. A semi-structured interview was conducted at the household level to identify the major drivers of land use change. The results indicated the presence of two major and divergent trends; the first one is the intensification of land use activities at the rate of 1.37% per annum, primarily driven by urbanization and infrastructure developments, and the second one is the fallowing and abandonment of land (at the rate of 0.21% per annum) driven by the increased cost of cultivation. The rates of change are more prominent in the rural areas while the urban grids are nearing saturation occupying nearly two-thirds of the area with urban features at the expense of greenery. Though the progression with respect to urbanization and infrastructure developments is expected, the fallowing and abandonment of land is unanticipated, raising serious questions in the developmental pathways to achieve Sustainable Development Goals in the State of Kerala.

Implementation and evaluation of different techniques to modify DRASTIC method for groundwater vulnerability assessment: a case study from Bouficha aquifer, Tunisia

Groundwater vulnerability assessment has nowadays evolved into an essential tool towards proper groundwater protection and management, while the DRASTIC method is included among the most widely applied vulnerability assessment methods. However, the high uncertainty of the DRASTIC method mainly associated with the subjectivity in assigning parameters ratings and weights has driven many researchers to apply various methods for improving its efficiency. In this context, in the present study, different techniques were implemented with the aim of modifying the DRASTIC framework and thus enhancing its performance for groundwater vulnerability assessment in the Bouficha aquifer, Tunisia. In a first stage, the land use type (L) was incorporated as an additional parameter in the typical DRASTIC framework, thus taking into consideration the impact of anthropogenic activities on groundwater vulnerability. Subsequently, the rating and weighting systems of the developed DRASTIC-L framework were modified through the application of statistical methods (DRASTIC-L-SA) and genetic algorithms (GA) (DRASTIC-L-GA) in an attempt to investigate and compare both linear and nonlinear modifications. To evaluate the various vulnerability frameworks, correlation between vulnerability values and nitrate concentrations, expressed as Spearman's rank correlation coefficient (ρ) and Correlation Index (CI), was examined. The results revealed that the DRASTIC-L-GA framework developed by applying a fully GA-based optimization procedure provided the highest values in terms of the performance metrics used, making it the most suitable for the study area. In addition, the aquifer under study was found to be less vulnerable to pollution when employing the typical DRASTIC framework instead of the modified ones, leading to the conclusion that the former substantially underestimates pollution potential in the study area.

Assessing the impact of land use and land cover on river water quality using water quality index and remote sensing techniques

The impact of land use on water quality is becoming a global concern due to the increasing demand for freshwater. This study aimed to assess the effects of land use and land cover (LULC) on the surface water quality of the Buriganga, Dhaleshwari, Meghna, and Padma river system in Bangladesh. To determine the state of water, water samples were collected from twelve locations in the Buriganga, Dhaleshwari, Meghna, and Padma rivers during the winter season of 2015 and collected samples were analysed for seven water quality indicators: pH, temperature (Temp.), conductivity (Cond.), dissolved oxygen (DO), biological oxygen demand (BOD), nitrate nitrogen (NO₃-N), and soluble reactive phosphorus (SRP) for assessing water quality (WQ). Additionally, same-period satellite imagery (Landsat-8) was utilised to classify the LULC using the object-based image analysis (OBIA) technique. The overall accuracy assessment and kappa co-efficient value of post-classified images were 92% and 0.89, respectively. In this research, the root mean squared water quality index (RMS-WQI) model was used to determine the WQ status, and satellite imagery was utilised to classify LULC types. Most of the WQs were found within the ECR guideline level for surface water. The RMS-WQI result showed that the "fair" status of water quality found in all sampling sites ranges from 66.50 to 79.08, and the water quality is satisfactory. Four types of LULC were categorised in the study area mainly comprised of agricultural land (37.33%), followed by built-up area (24.76%), vegetation (9.5%), and water bodies (28.41%). Finally, the Principal component analysis (PCA) techniques were used to find out significant WQ indicators and the correlation matrix revealed that WQ had a substantial positive correlation with agricultural land (r = 0.68, P < 0.01) and a significant negative association with the built-up area (r =  - 0.94, P < 0.01). To the best of the authors' knowledge, this is the first attempt in Bangladesh to assess the impact of LULC on the water quality along the longitudinal gradient of a vast river system. Hence, we believe that the findings of this study can support planners and environmentalists to plan and design landscapes and protect the river environment.

Geophysical investigation for seawater intrusion in the high-quality coastal aquifers of India: a review

Around the globe, seawater intrusion in the coastal aquifer is a significant problem. Excessive groundwater extraction because of population growth, industrialization, tourism, and other anthropogenic activities and geogenic processes initiates and accelerates this problem. The contaminated groundwater impacts the health, economic activities, and social and cultural development of coastal regions. This work aims to explore the current status and a holistic comprehending review of geophysical studies applied to delineate the seawater intrusion in the high-quality coastal aquifers in India, as well as its origin and causes, mitigation strategies, and recent advancements in geophysical techniques to access the qualitative and quantitative properties of the complex aquifer system. In the future, it is recommended to do a detailed subsurface imaging of the entire coastal belt of India to decipher the lateral and vertical variation of the lithological conditions and seawater intrusion in space and time with improved/advanced geophysical techniques, which can lead toward sustainable development.

Predicting Potential Climate Change Impacts on Groundwater Nitrate Pollution and Risk in an Intensely Cultivated Area of South Asia

One of the potential impacts of climate change is enhanced groundwater contamination by geogenic and anthropogenic contaminants. Such impacts should be most evident in areas with high land-use change footprint. Here, we provide a novel documentation of the impact on groundwater nitrate (GWNO3 ) pollution with and without climate change in one of the most intensely groundwater-irrigated areas of South Asia (northwest India) as a consequence of changes in land use and agricultural practices at present and predicted future times. We assessed the probabilistic risk of GWNO3 pollution considering climate changes under two representative concentration pathways (RCPs), i.e., RCP 4.5 and 8.5 for 2030 and 2040, using a machine learning (Random Forest) framework. We also evaluated variations in GWNO3 distribution against a no climate change (NCC) scenario considering 2020 status quo climate conditions. The climate change projections showed that the annual temperatures would rise under both RCPs. The precipitation is predicted to rise by 5% under RCP 8.5 by 2040, while it would decline under RCP 4.5. The predicted scenarios indicate that the areas at high risk of GWNO3 pollution will increase to 49 and 50% in 2030 and 66 and 65% in 2040 under RCP 4.5 and 8.5, respectively. These predictions are higher compared to the NCC condition (43% in 2030 and 60% in 2040). However, the areas at high risk can decrease significantly by 2040 with restricted fertilizer usage, especially under the RCP 8.5 scenario. The risk maps identified the central, south, and southeastern parts of the study area to be at persistent high risk of GWNO3 pollution. The outcomes show that the climate factors may impose a significant influence on the GWNO3 pollution, and if fertilizer inputs and land uses are not managed properly, future climate change scenarios can critically impact the groundwater quality in highly agrarian areas.

Study on the threshold relationship between landscape pattern and water quality considering spatial scale effect-a case study of Dianchi Lake Basin in China

It is of great significance to analyze the threshold relationship between landscape pattern and water quality for watershed water environment treatment. However, previous studies did not consider the influence of spatial scale on threshold. Therefore, this study proposed the idea of the relationship between landscape pattern and water quality threshold considering the spatial scale effect to solve the above problems. Firstly, the percentage of landscape composition area under 9 spatial scales (riparian buffer zone and sub-basin) of 20 rivers entering the lake in Dianchi Lake Basin was extracted to identify the optimal spatial scale of landscape pattern and water quality by redundant analysis (RDA). Then, a variety of nonlinear regression models such as power regression, exponential regression, quadratic regression, and segmented regression are used to quantitatively detect the thresholds of landscape pattern and water quality. The results show that (1) the spatial scale has a significant influence on the threshold relationship between landscape pattern and water quality, and the total interpretation rate of landscape pattern on water quality is the largest at the buffer scale of 1100 m riparian zone, which is an effective buffer for river governance. (2) Different spatial scales have different effects on the threshold relationship between landscape pattern and water quality. In the nonlinear regression model of landscape pattern and water quality in the buffer zone of 1100 m riparian zone, the significance and R² of the equation are better than those of the sub-basin. (3) From the nonlinear relationship between landscape pattern and water quality, it is found that the landscape threshold can be quantitatively identified when the water quality changes abruptly or reaches the I ~ V water quality standard. Among them, the type-1 landscape threshold at the water quality mutation point can be used as the long-term goal of water quality protection in Dianchi Lake Basin, and the type-2 landscape threshold can be used as the short-term goal of water quality adjustment. The research results can provide a scientific basis for the governance of water environment and the rational planning of landscape pattern in Dianchi Lake Basin, and have practical significance for guiding the sustainable development of cities.

Integrated seawater intrusion and groundwater quality assessment of a coastal aquifer: GALDIT, geospatial and analytical approaches

The pressure and dependence on coastal aquifers are on the rise in many parts of the globe. These lead to overexploitation, aggravated levels of groundwater pollution, and seawater intrusion. Integrated analyses can create holistic insights into the quality and the vulnerability of aquifers to seawater intrusion. In this study, Mombasa North coast's coastal aquifer was characterized by integrating multiple approaches-GALDIT overlay index, seawater intrusion groundwater quality index GQI_SWI, total hardness, water quality index (WQI)-and the results were further explored and interpreted with geospatial analysis techniques. The study suggests that the predominant water type in areas under moderate or high vulnerabilities to seawater intrusion is the Na-Cl water type. However, similar Na-Cl water types can produce a range of total hardness from soft to hard. GQI_SWI classification can be used to narrow down the observations from Stuyfzand's TH-based classification system. In the aquifer studied, the results of the GALDIT overlay index, a weighted aggregation of intrinsic parameters contributing to seawater intrusion, show that 29%, 59%, and 12% of the aquifer have low, moderate, and high vulnerabilities, respectively. The GQI_SWI analysis indicates that the groundwater is largely brackish (68%) but saline towards the southern end of the aquifer at 32%. Total hardness values indicate that 67% of the aquifer's coverage falls under the "moderately hard" category. The geodatabase creation introduced in the study provides a template for similar studies and a baseline for future WQI and water quality monitoring. However, temporal studies on chronological timescales are recommended for sustainable management of the aquifer.

Vulnerability of groundwater from elevated nitrate pollution across India: Insights from spatio-temporal patterns using large-scale monitoring data

Agriculture-sourced, non-point groundwater contamination (e.g., nitrate) is a serious concern from the drinking water crisis aspect across the agrarian world. India is one of the largest consumers of nitrogen fertilizers in South-Asia as well as in the world but groundwater nitrate lacks critical attention as a wide-scale drinking water pollutant in the country. Our study provides the first documentation of the distribution of groundwater nitrate and the extent of elevated nitrate contamination across India, along with the delineation of the temporal trends and the natural and anthropogenic factors that influence such occurrence of groundwater nitrate. High resolution, annual-scale spatio-temporal variability of groundwater nitrate concentration and consequent contamination was delineated using groundwater nitrate measurements from ~3 million drinking water wells spread across 7038 administrative blocks between 2010 and 2017 in India. An average 8% of the studied blocks were found affected by elevated groundwater nitrate (> 45 mg/L). Depth-dependent trend demonstrated that nitrate concentrations were about 14% higher in shallow water wells (≤ 35 m) than deep wells (>35 m). The overall temporal trend of groundwater nitrate concentration was decreasing slightly nationwide in the study period. The correlation tests and causality test results indicated that the spatial distribution of groundwater nitrate was significantly associated with agricultural N-fertilizer usage, whereas the decreasing temporal trend corresponded with the overall reduced N-fertilizer usage during the study period. Spatial autocorrelation analysis identified the clustering of high nitrate areas in central, north, and southern India, specifically in areas with higher fertilizer usage. We estimate about 71 million Indians possibly exposed to elevated groundwater nitrate concentrations and the majority of them reside in rural areas. Thus, this study provides the previously unrecognized, wide-scale, anthropogenic, diffused groundwater nitrate contamination across India.

Impact of land use/land cover changes on water quality and human health in district Peshawar Pakistan

The quality and quantity of groundwater resources are affected by landuse/landcover (LULC) dynamics, particularly the increasing urbanization coupled with high household wastewater discharge and decreasing open lands. This study evaluates temporal changes of groundwater quality for 2012 and 2019, its relation to Landuse/landcover, and its impact on Peshawar's residents (study area), Pakistan. A total of 105 and 112 groundwater samples were collected from tube wells in 2012 and 2019. Samples were then analyzed for seven standard water quality parameters (i.e., pH, electric conductivity (EC), turbidity, chloride, calcium, magnesium, and nitrate). Patient data for waterborne diseases were also collected for the years 2012 and 2019 to relate the impact of groundwater quality on human health. Landsat satellite images were classified for the years 2012 and 2019 to observe landuse/landcover dynamics concerning groundwater quality. Results manifested a decrease in groundwater quality for the year 2019 compared to 2012 and were more highlighted in highly populated areas. The nitrate concentration level was found high in the vicinity of agricultural areas due to the excessive use of nitrogenous fertilizers and pesticides, and thus the methemoglobinemia patients ratio increased by 14% (48-62% for the year 2012 and 2019, respectively). Besides, Urinary Tract Infections, Peptic Ulcer, and Dental Caries diseases increased due to the high calcium and magnesium concentration. The overall results indicate that anthropogenic activities were the main driver of Spatio-temporal variability in groundwater quality of the study area. The study could help district health administration understand groundwater quality trends, make appropriate site-specific policies, and formulate future health regulations.

Effect of land use changes on non-carcinogenic health risks due to nitrate exposure to drinking groundwater

This study aimed to determine the effect of land-use changes on the non-carcinogenic health risk of nitrate ion exposure of underground drinking water resources in Shiraz (Iran). To this end, 175 chemical samples for the nitrate analysis were regularly taken from 35 drinking water wells of Shiraz from 2013 to 2017, and their results were zoned using GIS. Hazard quotient (HQ) induced by nitrate ion exposure was determined in four age groups: infants, children, adolescents, and adults. Area changes of four types of land-use, including residential, agricultural and green space, industrial, and bare land within a radius of 400 m of drinking water wells, were determined using the GIS and Google Earth software. Then, all data was imported to Matlab 2018 for statistical analysis. The results showed that mean nitrate concentration increased by 2.5 mg L^-1 from 2013 to 2017. According to the zoning map, 5 and 11.4% of the area in 2013 and 2017, respectively, exceeded the drinking water standard set by nitrate (i.e., 50 mg/L). Air temperature and precipitation variations also influenced nitrate concentrations and HQ changes (R_temperature = 0.67). Children's age group was the most vulnerable, and during the study period, this vulnerability was an increasing trend, so that the HQ from 0.93 in 2013 to 0.97 in 2017 has increased. The rate of land-use changes in agricultural, industrial, bare, and urban was -1.8%, 1.3%, -4.6%, and 2.1%, respectively, and the highest correlation was observed between HQ and Diff.l residential land use (R_infant = 0.55). According to the results, the most influential factor in HQ was air temperature (R = 0.66), and urban land-use change (R > 0.44). To sum up, this study's results showed that land-use changes, especially urban and residential development, significantly affect groundwater nitrate concentration and its degree of HQ. Moreover, increasing temperature and decreasing annual precipitation can also increase the severity of this risk.

Changes in Stream–Aquifer Interactions Due to Gate Opening of the Juksan Weir in Korea

The Juksan weir, installed in the Yeongsan river in South Korea from 2010 to 2012, has secured sustainable water resources and helped control flooding. However, low river flow velocities due to the weir have deteriorated the quality of the river water. For natural river restoration, the water gate was opened in 2017. In this study, the three-dimensional finite difference model Visual MODFLOW was used to analyze the effects of gate opening on stream–aquifer interactions. A conceptual model was developed to simulate the stream–aquifer dynamics caused by the operation of the water gate at the Juksan weir. Groundwater data were also analyzed to determine the impacts of weir operations on groundwater quality. Our results indicate that a lower river level due to the weir opening changed the groundwater flow, which then affected the water balance. The change in groundwater flow increased the variability of the groundwater quality which had homogenized because of induced recharge after the construction of the weir. This could affect groundwater use in agricultural areas near the weir. Therefore, further groundwater monitoring and hydrodynamic analyses are required to anticipate and address any potential issues.

Scenario-Based Hydrological Modeling for Designing Climate-Resilient Coastal Water Resource Management Measures: Lessons from Brahmani River, Odisha, Eastern India

Widespread urban expansion around the world, combined with rapid demographic and climatic changes, has resulted in serious pollution issues in many coastal water bodies. To help formulate coastal management strategies to mitigate the impacts of these extreme changes (e.g., local land-use or climate change adaptation policies), research methodologies that incorporate participatory approaches alongside with computer simulation modeling tools have potential to be particularly effective. One such research methodology, called the “Participatory Coastal Land-Use Management” (PCLM) approach, consists of three major steps: (a) participatory approach to find key drivers responsible for the water quality deterioration, (b) scenario analysis using different computer simulation modeling tools for impact assessment, and (c) using these scientific evidences for developing adaptation and mitigation measures. In this study, we have applied PCLM approach in the Kendrapara district of India (focusing on the Brahmani River basin), a rapidly urbanizing area on the country’s east coast to evaluate current status and predict its future conditions. The participatory approach involved key informant interviews to determine key drivers of water quality degradation, which served as an input for scenario analysis and hydrological simulation in the next step. Future river water quality (BOD and Total coliform (Tot. coli) as important parameters) was simulated using the Water Evaluation and Planning (WEAP) tool, considering a different plausible future scenario (to 2050) incorporating diverse drivers and pressures (i.e., population growth, land-use change, and climate change). Water samples (collected in 2018) indicated that the Brahmani River in this district was already moderately-to-extremely polluted in comparison to the desirable water quality (Class B), and modeling results indicated that the river water quality is likely to further deteriorate by 2050 under all of the considered scenarios. Demographic changes emerged as the major driver affecting the future water quality deterioration (68% and 69% for BOD and Tot. coli respectively), whereas climate change had the lowest impact on river water quality (12% and 13% for BOD and Tot. coli respectively), although the impact was not negligible. Scientific evidence to understand the impacts of future changes can help in developing diverse plausible coastal zone management approaches for ensuring sustainable management of water resources in the region. The PCLM approach, by having active stakeholder involvement, can help in co-generation of the coastal management options followed by open access free software, and models can play a relevant cost-effective approach to enhance science-policy interface for conservation of natural resources.

Salient to Whom? The Positioning of German Political Parties on Agricultural Pollutants in Water Bodies

Scholars have increasingly argued for an integration of policies on agriculture and water due to their strong interlinkage. The entry of agricultural pollutants into water represents one of the main pressures on Europe’s ground and surface waters. This not only poses a risk to the environment and human health but also jeopardizes meeting the targets set by the EU Water Framework Directive. Research on the political agenda setting has shown that issue salience is key for triggering policy change. Nevertheless, Germany has repeatedly failed to adopt adequate policy measures despite the salience of the issue among the German public and increasing pressure by the EU. In this study, I shed light on the positioning of political parties in Germany on agricultural pollutants to explain the absence of policy change. More specifically, I ask whether there is an ideological division between political parties that hampers the adoption of effective, integrated policy measures. A qualitative content analysis of election manifestos published between 1998 and 2018 finds that political parties’ policy positions are predominantly influenced by their placement on an environmental and an economic ideological dimension. As a result, political parties in Germany advocate conflictive policy approaches, which is detrimental to the adoption of effective policy measures.

Land use impact on the water quality of large tropical river: Mun River Basin, Thailand

Globally, rivers and streams are experiencing declining water quality. Anthropogenic activities largely contribute to surface water pollution. Understanding human-induced influence on river water quality remains a challenge owing to spatiotemporal variations. In this study, we assessed the influence of various land uses (LU) on 16 water quality parameters of the Mun River, a tributary of the Mekong River, at different scales. Water quality was statistically analyzed both spatially and temporally (1995-2010). Seasonal and annual effect of LU on water quality was evaluated at buffer zone scale and sub-basin scale (i.e., catchment scale) using multiple regression analysis. The result showed that urban LU extensively adds to the nutrient concentration [i.e., total phosphorus (TP), ammonia nitrogen (NH₃-N)] followed by agriculture LU at the sub-basin scale. Site-specific variability of TP is explained by urban LU and biological oxygen demand (BOD) by agriculture LU at the 5-km buffer in Upper and Middle Mun whereas at Lower Mun, the 20-km buffer explains the variability of suspended solids (SS) and total suspended solids (TSS), suggesting a more localized effect on the parameters upstream. The high concentration of parameters was noted in the dry season whereas the opposite was true for fecal coliform bacteria (FCB), SS, and TP. The maximum parameter concentration of NH₃-N, FCB, and total coliform bacteria exceeds the permissible surface water quality standards of the Pollution Control Department (PCD) of Thailand in all three sub-basins. The study suggests the need for multi-scale interventions and effective pollution control measures focusing on nutrient, pathogenic bacteria, and solids pollution to improve the river water quality of large river basin.