Showing papers on "Nonpoint source pollution published in 2014"

Estimating groundwater vulnerability to pollution using a modified DRASTIC model in the Kerman agricultural area, Iran

Abstract: Groundwater contamination from intensive fertilizer application affects conservation areas in a plain. The DRASTIC model can be applied in the evaluation of groundwater vulnerability to such pollution. The main purpose of using the DRASTIC model is to map groundwater susceptibility to pollution in different areas. However, this method has been used in various areas without modification, thereby disregarding the effects of pollution types and their characteristics. Thus, this technique must be standardized and be approved for applications in aquifers and particular types of pollution. In this study, the potential for the more accurate assessment of vulnerability to pollution is achieved by correcting the rates of the DRASTIC parameters. The new rates were calculated by identifying the relationships among the parameters with respect to the nitrate concentration in groundwater. The methodology was implemented in the Kerman plain in the southeastern region of Iran. The nitrate concentration in water from underground wells was tested and analyzed in 27 different locations. The measured nitrate concentrations were used to associate and correlate the pollution in the aquifer to the DRASTIC index. The Wilcoxon rank-sum nonparametric statistical test was applied to determine the relationship between the index and the measured pollution in Kerman plain. Also, the weights of the DRASTIC parameters were modified through the sensitivity analysis. Subsequently, the rates and weights were computed. The results of the study revealed that the modified DRASTIC model performs more efficiently than the traditional method for nonpoint source pollution, particularly in agricultural areas. The regression coefficients showed that the relationship between the vulnerability index and the nitrate concentration was 82 % after modification and 44 % before modification. This comparison indicated that the results of the modified DRASTIC of this region are better than those of the original method.

Land Use and Climate Variability Amplify Carbon, Nutrient, and Contaminant Pulses: A Review with Management Implications

Abstract: Nonpoint source pollution from agriculture and urbanization is increasing globally at the same time climate extremes have increased in frequency and intensity. We review >200 studies of hydrologic and gaseous fluxes and show how the interaction between land use and climate variability alters magnitude and frequency of carbon, nutrient, and greenhouse gas pulses in watersheds. Agricultural and urban watersheds respond similarly to climate variability due to headwater alteration and loss of ecosystem services to buffer runoff and temperature changes. Organic carbon concentrations/exports increase and organic carbon quality changes with runoff. Nitrogen and phosphorus exports increase during floods (sometimes by an order of magnitude) and decrease during droughts. Relationships between annual runoff and nitrogen and phosphorus exports differ across land use. CH4 and N2O pulses in riparian zones/floodplains predominantly increase with: flooding, warming, low oxygen, nutrient enrichment, and organic carbon. CH4, N2O, and CO2 pulses in streams/rivers increase due to similar factors but effects of floods are less known compared to base flow/droughts. Emerging questions include: (1) What factors influence lag times of contaminant pulses in response to extreme events? (2) What drives resistance/resilience to hydrologic and gaseous pulses? We conclude with eight recommendations for managing watershed pulses in response to interactive effects of land use and climate change.

Assessing the relationship between water quality parameters and changes in landuse patterns in the Upper Manyame River, Zimbabwe

Abstract: For the past 30 years, the increases in population pressure and external influences, such as economic growth, have accelerated the demand for land within the Upper Manyame River catchment in Zimbabwe which has caused substantial changes in landuse. The general objective of this research was to assess the impacts of landuse activities on the water quality of the Upper Manyame River which drains the rural and urbanised part of the catchment up to flow gauging station C21. Landcover data for the month of April in years of 1984, 1995, 2003 and 2011 were acquired from available Landsat TM and ETM images and were classified through the maximum likelihood digital image classification using the supervised classification approach. The status of water quality of the Upper Manyame River was also assessed through analyses of historical concentrations and pollution loads for TP, DO, COD, NH 3 -N, SS, Pb, NO 3 , BOD 5 , EC, PO 4 -P and TN at the Environmental Management Agency (EMA) gauging station CR21 sampling point for 1996, 2000/1 and 2008/9. Water quality of 15 monitoring sites comprising 25 water quality parameters were monitored monthly from January to June 2012. These locations were selected to reflect a wide array of landuse for both the dry and wet seasons. The results indicated that there was an increase in pollution load from 1995 to 2012; for TP from 130 kg/day to 376 kg/d, and for TN from 290 kg/day to 494 kg/d. This indicates high pollution levels which have severe impacts on downstream users and also severe sewage contamination. Significant deviations occurred in DO (0.1–6.8) mg/L, COD (11–569) mg/L, BOD 5 (5–341) mg/L, PO 4 -P (0.01–4.45) mg/L, NH 3 -N (0.001–6.800) mg/L and EC (38–642) μS/cm. Hydrologic Response Unit and buffer analysis were used to determine the dominant landuse which contributes to a certain water quality. Results of digital image classification indicate that woodland/forest, grassland and bareland decreased between years 1984 to 2011 by 24.0%, 22.6% and 31.7% respectively. This was mainly due to expansion or increase of agriculture and urban areas by 24.4% and 41.6% respectively over the same time period. It was concluded that settlements and agricultural areas are the ones mainly affecting the water quality in Upper Manyame River with a Pearson’s Correlation Coefficient of r = 0.97 for COD and r = 0.78 for TSS respectively. It was also observed that the water quality status of the Upper Manyame River and its tributaries is very poor and the level of pollution generally increases from upstream to downstream. The results obtained provided baseline information which may be used in the development of appropriate water quality management systems in the catchment. Thus the study recommended a combined programme of point source control and landuse modification.

Nutrient delivery from the Mississippi River to the Gulf of Mexico and effects of cropland conservation

Abstract: Excessive nutrients transported from the Mississippi River Basin (MRB) have created a hypoxic zone within the Gulf of Mexico, with numerous negative ecological effects. Furthermore, federal expenditures on agricultural conservation practices have received intense scrutiny in recent years. Partly driven by these factors, the USDA Conservation Effects Assessment Project (CEAP) recently completed a comprehensive evaluation of nutrient sources and delivery to the Gulf. The modeling framework used in the CEAP Cropland National Assessment, or Cropland CEAP, consists of the Agricultural Policy/ Environmental eXtender (APEX) and Soil and Water Assessment Tool (SWAT) models. This CEAP modeling framework was successfully calibrated for flow, sediment, and nutrients at 38 sites and validated at an additional 17. Simulation results indicated that cultivated cropland was the dominant source of nitrogen (N) and phosphorus (P) to both local waters and the Gulf, but this was not true for each water resource region within the MRB. In addition, the results showed that point sources remain significant contributors of P loads, especially in the Tennessee and Arkansas/Red River basins where point source P loads exceeded those from cultivated cropland. Similarly, urban nonpoint sources were significant nutrient sources. The Upper Mississippi, Lower Mississippi, and Ohio basins contributed the largest amounts of nutrients delivered to the Gulf. The high delivery areas near the Mississippi River main stem, from which 87% of N and 90% of P was predicted to reach the Gulf, also coincided with elevated nutrient yields to local waters. Conservation practices established on agricultural lands within the MRB were predicted to have reduced nutrient loads to the Gulf by 20% as compared with a no conservation condition. The results indicate the importance of targeted implementation of conservation practices and consideration of local water and/or Gulf impacts depending on program goal(s). The present application illustrates the value of the Cropland CEAP modeling framework as a useful, science-based tool to evaluate pollutant sources and delivery and effects of agricultural conservation practices.

Managing agricultural phosphorus for water quality: lessons from the USA and China.

Abstract: The accelerated eutrophication of freshwaters and to a lesser extent some coastal waters is primarily driven by phosphorus (P) inputs. While efforts to identify and limit point source inputs of P to surface waters have seen some success, nonpoint sources remain difficult to identify, target, and remediate. As further improvements in wastewater treatment technologies becomes increasingly costly, attention has focused more on nonpoint source reduction, particularly the role of agriculture. This attention was heightened over the last 10 to 20 years by a number of highly visible cases of nutrient-related water quality degradation; including the Lake Taihu, Baltic Sea, Chesapeake Bay, and Gulf of Mexico. Thus, there has been a shift to targeted management of critical sources of P loss. In both the U.S. and China, there has been an intensification of agricultural production systems in certain areas concentrate large amounts of nutrients in excess of local crop and forage needs, which has increased the potential for P loss from these areas. To address this, innovative technologies are emerging that recycle water P back to land as fertilizer. For example, in the watershed of Lake Taihu, China one of the largest surface fresh waters for drinking water supply in China, local governments have encouraged innovation and various technical trials to harvest harmful algal blooms and use them for bio-gas, agricultural fertilizers, and biofuel production. In any country, however, the economics of remediation will remain a key limitation to substantial changes in agricultural production.

Support vector machine―an alternative to artificial neuron network for water quality forecasting in an agricultural nonpoint source polluted river?

Abstract: Water quality forecasting in agricultural drainage river basins is difficult because of the complicated nonpoint source (NPS) pollution transport processes and river self-purification processes involved in highly nonlinear problems. Artificial neural network (ANN) and support vector model (SVM) were developed to predict total nitrogen (TN) and total phosphorus (TP) concentrations for any location of the river polluted by agricultural NPS pollution in eastern China. River flow, water temperature, flow travel time, rainfall, dissolved oxygen, and upstream TN or TP concentrations were selected as initial inputs of the two models. Monthly, bimonthly, and trimonthly datasets were selected to train the two models, respectively, and the same monthly dataset which had not been used for training was chosen to test the models in order to compare their generalization performance. Trial and error analysis and genetic algorisms (GA) were employed to optimize the parameters of ANN and SVM models, respectively. The results indicated that the proposed SVM models performed better generalization ability due to avoiding the occurrence of overtraining and optimizing fewer parameters based on structural risk minimization (SRM) principle. Furthermore, both TN and TP SVM models trained by trimonthly datasets achieved greater forecasting accuracy than corresponding ANN models. Thus, SVM models will be a powerful alternative method because it is an efficient and economic tool to accurately predict water quality with low risk. The sensitivity analyses of two models indicated that decreasing upstream input concentrations during the dry season and NPS emission along the reach during average or flood season should be an effective way to improve Changle River water quality. If the necessary water quality and hydrology data and even trimonthly data are available, the SVM methodology developed here can easily be applied to other NPS-polluted rivers.

Nonpoint source pollution of urban stormwater runoff: a methodology for source analysis

Abstract: The characterization and control of runoff pollution from nonpoint sources in urban areas are a major issue for the protection of aquatic environments. We propose a methodology to quantify the sources of pollutants in an urban catchment and to analyze the associated uncertainties. After describing the methodology, we illustrate it through an application to the sources of Cu, Pb, Zn, and polycyclic aromatic hydrocarbons (PAH) from a residential catchment (228 ha) in the Paris region. In this application, we suggest several procedures that can be applied for the analysis of other pollutants in different catchments, including an estimation of the total extent of roof accessories (gutters and downspouts, watertight joints and valleys) in a catchment. These accessories result as the major source of Pb and as an important source of Zn in the example catchment, while activity-related sources (traffic, heating) are dominant for Cu (brake pad wear) and PAH (tire wear, atmospheric deposition).

Non‐point source pollution modelling using Soil and Water Assessment Tool and its parameter sensitivity analysis in Xin'anjiang catchment, China

Abstract: Non-point source pollution is a key issue in integrated river basin management around the world and has resulted in water contamination, aquatic ecology deterioration and eutrophication. Xin'anjiang catchment is the key drinking water source area for Hangzhou City, China. A promising model (Soil and Water Assessment Tool) was applied to assess the non-point source pollution and its effect on drinking water. Sensitivity analysis of model parameters was carried out using the Sequential Uncertainty Domain Parameter Fitting 2 sensitivity technique. Water discharge, sediment, total nitrogen and total phosphorus load processes from 2000 to 2010 were simulated, and the spatial distributions of non-point source pollutants were evaluated at the catchment and administrative country levels. The results show that the hydrological parameters of the Soil and Water Assessment Tool were dominantly sensitive for non-point source pollution simulation, including CN2, RCHRG_DP, ALPHA_BF, SOL_AWC, ESCO and SOL_K and the characteristic parameters of sub-basins (viz. HRU_SLP and SLSUBBSN). Also, water quality parameters (viz. CH_EROD, NPERCO, RSDCO and PPERCO, PHOSKD, etc.) have a significant effect on nutrients. The model performance was very satisfactory, especially for runoff, sediment and total phosphorus simulation. The non-point source pollutant load increased from 2001 to 2010 in the whole catchment. Total nitrogen load increased from 3428tons (0.59tonkm(-2)) to 7315tons (1.25tonkm(-2)), and total phosphorus load increased from 299tons (0.05tonkm(-2)) to 867tons (0.15 tonkm(-2)). The contribution of rice land was the largest, accounting for nearly 95%, followed by tea garden (3.56%), winter wheat (1.37%), forest (0.07%) and grassland (0.02%). Moreover, She County and Xiuning County contributed more than half of the non-point source pollutants. This study was expected to provide a method and reference for non-point source pollution quantification and to support water quality management implementation in China. Copyright (c) 2012 John Wiley & Sons, Ltd.

Reversing Property Rights: Practice-Based Approaches for Controlling Agricultural Nonpoint-source Water Pollution When Emissions Aggregate Nonlinearly

Abstract: Nonpoint-source water pollution remains a major issue despite decades of research and sizable conservation programs. We suggest that by taking advantage of contemporary modeling and optimization approaches, good approximations to physical relationships can be constructed so that even in the presence of unobservable field emissions and nonlinear fate and transport relationships, standard economic tools of command-and-control requirements, performance standards, and trading can be implemented. The Boone River Watershed in the U.S. state of Iowa is used for empirical demonstration. Although the approach can be used to construct voluntary conservation policies, the described policies involve imposing requirements on agricultural polluters rather than relying on voluntary actions alone.

Surface water quality and cropping systems sustainability under a changing climate in the Upper Mississippi River Basin

Abstract: Agricultural nonpoint source pollution is the main source of nitrogen (N) and phosphorus (P) in the intensely row-cropped Upper Mississippi River Basin (UMRB) stream system and is considered the primary cause of the northern Gulf of Mexico hypoxic zone according to the US Environmental Protection Agency. A point of crucial importance in this region is therefore how intensive corn (Zea mays L.)-based cropping systems for food and fuel production can be sustainable and coexist with a healthy water environment, not only under existing climate conditions but also under a changed climate in the future. To address this issue, a UMRB integrated modeling system has been built with a greatly refined 12-digit subbasin structure based on the Soil and Water Assessment Tool (SWAT) water quality model, which is capable of estimating landscape and in-stream water and pollutant yields in response to a wide array of alternative cropping and/or management strategies and climatic conditions. The effects of the following four agricultural management scenarios on crop production and pollutant loads exported from the cropland of the UMRB to streams and rivers were evaluated: (1) expansion of continuous corn across the entire basin, (2) adoption of no-till on all corn and soybean (Glycine max L.) fields in the region, (3) substitution of the traditional continuous corn and corn–soybean rotations with an extended five-year rotation consisting of corn, soybean, and three years of alfalfa (Medicago sativa L.), and (4) implementation of a winter cover crop within the baseline rotations. The effects of each management scenario were evaluated both for current climate and a projected midcentury (2046 to 2065) climate from a General Circulation Model (GCM). All four scenarios behaved similarly under the historical and future climate, generally resulting in reduced erosion and nutrient loadings to surface water bodies compared to the baseline agricultural management. Continuous corn was the only scenario which resulted in increased N pollution while no-till was the most environmentally effective and able to sustain production at almost the same levels. Rye (Secale cereale L.) cover crop within the fallow period was also effective in reducing erosion and both sediment-bound and soluble forms of nutrients. The results indicated that alternative management practices could reduce sediment, N, and P exports from UMRB cropland by up to 50% without significantly affecting yields. Results for the climate change scenario showed that the effectiveness of the management scenarios was strongly linked to the reduced water availability predicted under the future climate, which assisted in mitigating pollutant transport, although with a small loss of production.

Relating land use patterns to stream nutrient levels in red soil agricultural catchments in subtropical central China.

Abstract: Land use has obvious influence on surface water quality; thus, it is important to understand the effects of land use patterns on surface water quality. This study explored the relationships between land use patterns and stream nutrient levels, including ammonium-N (NH4 +-N), nitrate-N (NO3 −-N), total N (TN), dissolved P (DP), and total P (TP) concentrations, in one forest and 12 agricultural catchments in subtropical central China. The results indicated that the TN concentrations ranged between 0.90 and 6.50 mg L−1 and the TP concentrations ranged between 0.08 and 0.53 mg L−1, showing that moderate nutrient pollution occurred in the catchments. The proportional areal coverages of forests, paddy fields, tea fields, residential areas, and water had distinct effects on stream nutrient levels. Except for the forest, all studied land use types had a potential to increase stream nutrient levels in the catchments. The land use pattern indices at the landscape level were significantly correlated to N nutrients but rarely correlated to P nutrients in stream water, whereas the influence of the land use pattern indices at the class level on stream water quality differentiated among the land use types and nutrient species. Multiple regression analysis suggested that land use pattern indices at the class level, including patch density (PD), largest patch index (LPI), mean shape index (SHMN), and mean Euclidian nearest neighbor distance (ENNMN), played an intrinsic role in influencing stream nutrient quality, and these four indices explained 35.08 % of the variability of stream nutrient levels in the catchments (p<0.001). Therefore, this research provides useful ideas and insights for land use planners and managers interested in controlling stream nutrient pollution in subtropical central China.

Cleaning Pakistan's Air: Policy Options to Address the Cost of Outdoor Air Pollution

Abstract: Pakistan's urban air pollution is among the most severe in the world and it engenders significant damages to human health and the economy. Air pollution, inadequate water supply, sanitation, and hygiene are the top environmental priority problems in Pakistan. Industrialization and urbanization, in conjunction with motorization, can result in further deterioration of urban air quality. This book examines policy options to strengthen the Pakistan clean air program (PCAP) to better address the cost imposed by outdoor air pollution upon Pakistan's economy and populace. The approach provided in this book recommends that the federal and provincial environmental protection agencies (EPAs) take on a limited number of high return, essential, and feasible interventions drawn largely from the PCAP. The objective of this book is to examine policy options to control outdoor air pollution in Pakistan. The findings of the analysis aim at assisting the Government of Pakistan (GoP) in the design and implementation of reforms to improve the effectiveness and efficiency of Pakistan's ambient air quality institutions. The overarching theme of this book is that prioritizing interventions is essential to address the cost of outdoor air pollution, given current resource limitations. The book also includes a review of secondary sources, focusing on recent analysis of the effects of different air pollutants on human health, as well as lessons learned from ongoing regional and international efforts to improve ambient air quality. This book has seven chapters. Chapter one gives overview. Chapter two identifies major trends in ambient air pollution, including concentration levels of main pollutants and the identification of principal sources. Chapter three examines the evolution of Pakistan's air quality management (AQM) framework over the period 1993 to 2013. Chapter four examines options to control air pollution from mobile sources, the main contributors of several air pollutants, including noxious fine particulate matter (PM) and its precursors. Chapter five addresses measures to tackle pollution from industrial sources. Chapter six identifies synergies of interventions for air pollution control and climate change mitigation. Chapter seven summarizes the main conclusions of the book.

Combining CLUE-S and SWAT models to forecast land use change and non-point source pollution impact at a watershed scale in Liaoning Province, China

Abstract: Non-point source (NPS) pollution has become a major source of water pollution. A combination of models would provide the necessary direction and approaches designed to control NPS pollution through land use planning. In this study, NPS pollution load was simulated in urban planning, historic trends and ecological protection land use scenarios based on the Conversion of Land Use and its Effect at Small regional extent (CLUE-S) and Soil and Water Assessment Tool (SWAT) models applied to Hunhe-Taizi River Watershed, Liaoning Province, China. Total nitrogen (TN) and total phosphorus (TP) were chosen as NPS pollution indices. The results of models validation showed that CLUE-S and SWAT models were suitable in the study area. NPS pollution mainly came from dry farmland, paddy, rural and urban areas. The spatial distribution of TN and TP exhibited the same trend in 57 sub-catchments. The TN and TP had the highest NPS pollution load in the western and central plains, which concentrated the urban area and farm land. The NPS pollution load would increase in the urban planning and historic trends scenarios, and would be even higher in the urban planning scenario. However, the NPS pollution load decreased in the ecological protection scenario. The differences observed in the three scenarios indicated that land use had a degree of impact on NPS pollution, which showed that scientific and ecologically sound construction could effectively reduce the NPS pollution load in a watershed. This study provides a scientific method for conducting NPS pollution research at the watershed scale, a scientific basis for non-point source pollution control, and a reference for related policy making.

SWAT modeling of best management practices for Chungju dam watershed in South Korea under future climate change scenarios

Abstract: Suitable and practicable best management practices (BMPs) need to be developed due to steadily increasing agricultural land development, intensified fertilization practices, and increased soil erosion and pollutant loads from cultivated areas. The soil and water assessment tool model was used to evaluate the present and future proper BMP scenarios for Chungju dam watershed (6,642 km2) of South Korea, which includes rice paddy and upland crop areas. The present (1981–2010) and future (2040s and 2080s) BMPs of streambank stabilization, building recharge structures, conservation tillage, and terrace and contour farming were examined individually in terms of reducing nonpoint source pollution loads by applying MIROC3.2 HiRes A1B and B1 scenarios. Streambank stabilization achieved the highest reductions in sediment and T-N, and slope terracing was a highly effective BMP for sediment and T-P removal in both present and future climate conditions.

A protocol for conducting rainfall simulation to study soil runoff.

Abstract: Rainfall is a driving force for the transport of environmental contaminants from agricultural soils to surficial water bodies via surface runoff. The objective of this study was to characterize the effects of antecedent soil moisture content on the fate and transport of surface applied commercial urea, a common form of nitrogen (N) fertilizer, following a rainfall event that occurs within 24 hr after fertilizer application. Although urea is assumed to be readily hydrolyzed to ammonium and therefore not often available for transport, recent studies suggest that urea can be transported from agricultural soils to coastal waters where it is implicated in harmful algal blooms. A rainfall simulator was used to apply a consistent rate of uniform rainfall across packed soil boxes that had been prewetted to different soil moisture contents. By controlling rainfall and soil physical characteristics, the effects of antecedent soil moisture on urea loss were isolated. Wetter soils exhibited shorter time from rainfall initiation to runoff initiation, greater total volume of runoff, higher urea concentrations in runoff, and greater mass loadings of urea in runoff. These results also demonstrate the importance of controlling for antecedent soil moisture content in studies designed to isolate other variables, such as soil physical or chemical characteristics, slope, soil cover, management, or rainfall characteristics. Because rainfall simulators are designed to deliver raindrops of similar size and velocity as natural rainfall, studies conducted under a standardized protocol can yield valuable data that, in turn, can be used to develop models for predicting the fate and transport of pollutants in runoff.

Identification of river water pollution characteristics based on projection pursuit and factor analysis

Abstract: Human activities contribute different pollutants to receiving waters, often with significant variations in time and space. Therefore, integrating multiple parameters of water quality and their spatiotemporal variations is necessary to identify the pollution characteristics. Based on the water quality monitoring data with 12 parameters for 2 years at 22 sampling sites in the Cao-E River system, eastern China, the projection pursuit method was used to project all parameters and their temporal variations into a one-dimensional vector through two projections. Accordingly, we could easily assess the comprehensive water quality in different sampling sites and then classify their water pollution features. Factor analysis was then used to identify the pollution characteristics and potential sources. Results showed that all sampling sites for the river system could be classified into four groups: headwater sites (HS), agricultural nonpoint sources pollution sites (ANPS), point sources pollution sites (PSPS), and mixed sources pollution sites. Water quality in HS was good, containing only a few nutrients from the woodland runoff and soil erosion. For ANPS, the main pollutants were dissolved phosphorus, total P, and nitrate nitrogen (NO3 −-N), mainly from farming land. For PSPS, ammonium nitrogen (NH4 +-N) and organic pollutants originated from industrial and municipal sewage. In HS and ANPS, NO3 −-N was the main form of nitrogen, and a high ratio of NO3 −-N/NH4 +-N was a remarkable characteristic, whereas NH4 +-N was the main form of nitrogen in PSPS. Except in HS, water quality in the other groups could not meet the local water quality control standard. Finally, suggestions were proposed for water pollution control for the different groups.

Linking Spatial Variations in Water Quality with Water and Land Management using Multivariate Techniques.

Abstract: Most studies using multivariate techniques for pollution source evaluation are conducted in free-flowing rivers with distinct point and nonpoint sources This study expanded on previous research to a managed “canal” system discharging into the Indian River Lagoon, Florida, where water and land management is the single most important anthropogenic factor influencing water quality Hydrometric and land use data of four drainage basins were uniquely integrated into the analysis of 25 yr of monthly water quality data collected at seven stations to determine the impact of water and land management on the spatial variability of water quality Cluster analysis (CA) classified seven monitoring stations into four groups (CA groups) All water quality parameters identified by discriminant analysis showed distinct spatial patterns among the four CA groups Two-step principal component analysis/factor analysis (PCA/FA) was conducted with (i) water quality data alone and (ii) water quality data in conjunction with rainfall, flow, and land use data The results indicated that PCA/FA of water quality data alone was unable to identify factors associated with management activities The addition of hydrometric and land use data into PCA/FA revealed close associations of nutrients and color with land management and storm-water retention in pasture and citrus lands; total suspended solids, turbidity, and NO 3 + NO 2 with flow and Lake Okeechobee releases; specific conductivity with supplemental irrigation supply; and dissolved O 2 with wetland preservation The practical implication emphasizes the importance of basin-specific land and water management for ongoing pollutant loading reduction and ecosystem restoration programs