Assessment of Wastewater Reuse Effects on Nutrient Loads from Paddy Field Using Field-Scale Water Quality Model

CREAMS-PADDY, a modified version of the field-scale CREAMS model, simulates the hydrologic, sediment, and nutrient cycles in paddy fields. The CREAMS-PADDY model was applied to estimate the effects of using wastewater for irrigation on nutrient loads from paddy fields in Republic of Korea. The model was calibrated and validated using data from two rice paddy fields. The coefficient of determination between observed and simulated total nitrogen and total phosphorus were 0.92 and 0.57, respectively, for the calibration period and 0.84 and 0.73 for the validation period. Simulations showed that when using wastewater for irrigation, the total nitrogen loads increased by 210% and total phosphorus by 1,270% when compared with conventional water irrigation. The total nitrogen and total phosphorus concentration in the ponded water increased by 254 and 534%, respectively, when compared with conventional water irrigation. The effect of reducing N and P fertilizer application rates by 10, 30, and 50% on nutrient loads exiting a paddy field were also simulated using the validated CREAMS-PADDY model. These simulations indicated that total phosphorus loads from the paddy were reduced only slightly by reducing the fertilizer, while total nitrogen loads were reduced by as much as 8.8, 16.6, and 24.4% when N ferlitizer rates were reduced by 10, 30, and 50%, respectively. An erratum to this article can be found at     

A Spatially Explicit Model for Estimating Annual Average Loads of Nonpoint Source Nutrient at the Watershed Scale

The overloaded nonpoint source (NPS) nutrients in upper streams always result in the nutrient enrichment at lakes and estuaries downstream. As NPS pollution has become a serious environmental concern in watershed management, the information about nutrient output distribution across a watershed has been critical in the designing of regional development policies. But existing watershed evaluation models often encounter difficulties in application because of their complicated structures and strict requirements for the input data. In this paper, a spatially explicit and process-based model, Integrated Grid’s Exporting and Delivery model, was introduced to estimate annual in-stream nutrient levels. Each grid cell in this model was regarded as having potentials of both exporting new nutrients and trapping nutrients passing by. The combined nutrient dynamics of a grid is mainly determined by the grid’s features in land use/land cover, soil drainage, and geomorphology. This simple-concept model was tested at some basins in north Georgia in the USA. Stations in one basin were used to calibrate the model. Then an external validation was employed by applying the calibrated model to stations in the other neighbor basins. Model evaluation statistics implied the model’s validity and good performance in estimating the annual NPS nutrients’ fluxes at the watershed scale. This study also provides a promising prospect that in-stream annual nutrient loads can be accurately estimated from a few public available datasets.     

Modeling of non-point source pollution in a Mediterranean drainage basin

SWAT ver. 2000 was used to predict hydrographs, and sediment, nitrate and total phosphorus loadings from a 1349 km² mountainous/agricultural watershed in Northern Greece. The model was calibrated and verified using continuous meteorological data from eight stations within the drainage area, and runoff, sediment and nutrient concentrations measured at nine stations located within the main tributaries of the watershed, for the time period from May 1st, 1998 to January 31st, 2000. Model validation methodology and resulting input parameters appropriate for Mediterranean drainage basins are presented. Predicted by the model hydrographs, sedimentographs and pollutographs are plotted against observed values and show good agreement. Model performance is evaluated using the root mean square error computation and scattergrams of predicted versus observed data. The validated model is also used to test the effectiveness of three alternative cropping scenarios in reducing nutrient loadings from the agricultural part of the watershed. The study showed that this model, if properly validated, can be used effectively in testing management scenarios in Mediterranean drainage basins.     

A water quality monitoring network design methodology for the selection of critical sampling points: Part II

In order to resolve the spatial component of the design of a water quality monitoring network, a methodology has been developed to identify the critical sampling locations within a watershed. This methodology, called Critical Sampling Points (CSP), focuses on the contaminant total phosphorus (TP), and is applicable to small, predominantly agricultural-forested watersheds. The CSP methodology was translated into a model, called Water Quality Monitoring Station Analysis (WQMSA). It incorporates a geographic information system (GIS) for spatial analysis and data manipulation purposes, a hydrologic/water quality simulation model for estimating TP loads, and an artificial intelligence technology for improved input data representation. The model input data include a number of hydrologic, topographic, soils, vegetative, and land use factors. The model also includes an economic and logistics component. The validity of the CSP methodology was tested on a small experimental Pennsylvanian watershed, for which TP data from a number of single storm events were available for various sampling points within the watershed. A comparison of the ratios of observed to predicted TP loads between sampling points revealed that the model's results were promising.     

Role of Geographic Information System (GIS) in Watershed Simulation By Winvast Model

The uncertainty of modeling input will increase the simulation error, and this situation always happens in a model without user-friendly interface. WinVAST model, developed by the University of Virginia in 2003, treats an entire multi-catchment by a tree-view structure. Its extra computer programs can connect geographic information system (GIS). Model users can prepare all the necessary information in ArcGIS. Extracting information from GIS interface can not only decrease the inconvenience of data input, but also lower the uncertainty due to data preparation. The Daiyuku Creek and Qupoliao Creek in the Fei-tsui reservoir watershed in Northern Taiwan provided the setting for the case study reported herein. The required information, including slope, stream length, subbasin area, soil type and land-use condition, for WinVAST model should be prepared in a Microsoft Access database, which is the project file of WinVAST with extension mdb. In ArcGIS interface, when the soil layer, land-use layer, and Digital Elevation Model (DEM) map are prepared, all the watershed information can be created as well. This study compared the simulation results from automatically generated input and manual input. The results show that the relative simulation error resulting from the rough process of data input can be around 30% in runoff simulation, and even reach 70% in non-point source pollution (NPSP) simulation. It could conclude that GIS technology is significant for predicting watershed responses by WinVAST model, because it can efficiently reduce the uncertainty induced by input errors.     

Sensitivity of Simulated Conservation Practice Effectiveness to Representation of Field and In-Stream Processes in the Little River Watershed

Evaluating the effectiveness of conservation practices (CPs) is an important step to achieving efficient and successful water quality management. Watershed-scale simulation models can provide useful and convenient tools for this evaluation, but simulated conservation practice effectiveness should be responsive to parameter values used to represent the practices in the modeling. The objectives of this study were to (1) assess the impacts of a set of conservation practices on hydrology and water quality of a watershed and (2) evaluate the sensitivity of Soil and Water Assessment Tool (SWAT) modeling outputs and simulated conservation practice effectiveness to parameters. The modeling study was conducted in an agricultural watershed, the subwatershed K (16.9 km²) of the Little River Experimental watershed located in the South Atlantic Coastal Plain of the USA. Sensitivity analysis showed that hydrologic response unit (HRU) and watershed-scale simulations for water quality were most sensitive to CN and FILTERW parameters. Load reduction rates as a function of increased aerial coverage of the conservation practices were greatest for total phosphorus (TP), followed by sediment and total nitrogen (TN). The results indicated that conservation practices would have a limited impact on stream flow volume but could have a significant impact on sediment and TP loads within this region. Watershed-scale TN and TP loads were also sensitive to an in-stream nutrient transformation process represented using the QUAL2E algorithm in SWAT. The study clearly demonstrated the most sensitive model parameters and the optimal conservation practices for this watershed.     

Impact of phosphorus load reduction on water quality in a stratified reservoir-eutrophication modeling study

Monitoring data collected from the Mingder Reservoir in Taiwan indicate that the water quality is between mesotrophic and eutrophic. Chlorophyll a concentration is higher in the summer and anoxic conditions occur in the bottom. The data also reveal that a pronounced vertical thermal gradient in summer and vertical mixing the end of fall. A vertical two-dimensional, laterally averaged hydrodynamic and water quality model (CE-QUAL-W2) was adopted to simulate the water surface elevation, water temperature, and water quality conditions in the water column. The modeling effort was supported with monitoring data collected in the field for a 2-year period in the reservoir. The hydrodynamic model reproduced the time series water surface elevation. Spatial and temporal distributions of temperature in the water column of the reservoir were also well reproduced by the hydrodynamic model. Model-calculated concentrations of key water quality constituents such as nutrients, dissolved oxygen, and algal biomass matched the measured values closely in the reservoir. The calibrated model was then applied to simulate water quality response to various nutrient reduction scenarios. Results of the model scenario runs reveal that a 20% and 80% reduction of the phosphorus loads will improve the water quality from eutrophic to mesotrophic and oligotrophic conditions, respectively. The modeling effort has yielded valuable information that can be used by decision makers for the evaluation of different management strategies of reducing watershed nutrient loads.     

The Impacts of Different Meteorology Data Sets on Nitrogen Fate and Transport in the SWAT Watershed Model

In this study, we investigated how different meteorology data sets impacts nitrogen fate and transport responses in the Soil and Water Assessment Tool (SWAT) model. We used two meteorology data sets: National Climatic Data Center (observed) and Mesoscale Model 5/Weather Research and Forecasting (simulated). The SWAT model was applied to two 10-digit hydrologic unit code watersheds in the Coastal Plain and Piedmont zones of North Carolina. Nitrogen cycling and loading response to these meteorological data were investigated by exploring 19 SWAT nitrogen outputs relating to landscape delivery, biogeochemical assimilation, and atmospheric deposition. The largest difference in model output using both meteorology data sets was for large loads/fluxes. Landscape delivery outputs (e.g., NO^? ₃ watershed discharge, groundwater NO^? ₃ flux, soil NO^? ₃ percolation) showed the largest difference across all values. Use of the two weather data sources resulted in a nearly twofold difference in NO^? ₃ watershed discharge and groundwater NO^? ₃ flux. Differences for many nitrogen outputs were greater than those for sub-basin flow. Nitrogen outputs showed the greatest difference for agricultural land covers and there was no flow-related pattern in output differences across sub-basins or over time (years). In general, nitrogen parameter models that had a greater number of nitrate concentration, flow, and temperature terms (equation variables) in each transport model showed the greatest difference between both meteorology applications.     

Application of integrated GIS and multimedia modeling on NPS pollution evaluation

In Taiwan, nonpoint source (NPS) pollution is one of the major causes of the impairment of surface waters. I-Liao Creek, located in southern Taiwan, flows approximately 90 km and drains toward the Kaoping River. Field investigation results indicate that NPS pollution from agricultural activities is one of the main water pollution sources in the I-Liao Creek Basin. Assessing the potential of NPS pollution to assist in the planning of best management practice (BMP) is significant for improving pollution prevention and control in the I-Liao Creek Basin. In this study, land use identification in the I-Liao Creek Basin was performed by properly integrating the skills of geographic information system (GIS) and global positioning system (GPS). In this analysis, 35 types of land use patterns in the watershed area of the basin are classified with the aid of Erdas Imagine process system and ArcView GIS system. Results indicate that betel palm farms, orchard farms, and tea gardens dominate the farmland areas in the basin, and are scattered around on both sides of the river corridor. An integrated watershed management model (IWMM) was applied for simulating the water quality and evaluating NPS pollutant loads to the I-Liao Creek. The model was calibrated and verified with collected water quality and soil data, and was used to investigate potential NPS pollution management plans. Simulated results indicate that NPS pollution has significant contributions to the nutrient loads to the I-Liao Creek during the wet season. Results also reveal that NPS pollution plays an important role in the deterioration of downstream water quality and caused significant increase in nutrient loads into the basin's water bodies. Simulated results show that source control, land use management, and grassy buffer strip are applicable and feasible BMPs for NPS nutrient loads reduction. GIS system is an important method for land use identification and waste load estimation in the basin. Linking the information of land utilization with the NPS pollution simulation model may further provide essential information of potential NPS pollution for all subregions in the river basin. Results and experience obtained from this study will be helpful in designing the watershed management and NPS pollution control strategies for other similar river basins.     

Geospatial approaches to characterizing agriculture in the Chincoteague Bay Subbasin

Most agricultural information is reported by government sources on a state or county basis. The purpose of this study was to demonstrate use of geospatial data, the 2002 Agricultural Cropland Data Layer (CDL) for the mid-Atlantic region, to characterize agricultural, environmental, and other scientific parameters for the Chincoteague Bay subbasin using geographic information systems. This study demonstrated that agriculture can be characterized accurately on subbasin and subwatershed bases, thus complimenting various assessment technologies. Approximately 28% of the dry land of the subbasin was cropland. Field corn was the largest crop. Soybeans, either singly or double-cropped with wheat, were the second most predominant crop. Although the subbasin is relatively small, cropping practices in the northern part were different from those in the southern portion. Other crops, such as fresh vegetables and vegetables grown for processing, were less than 10% of the total cropland. A conservative approximation of the total pesticide usage in the subbasin in 2002 was over 277,000 lbs of active ingredients. Herbicides represented the most frequently used pesticides in the subbasin, both in number (17) and in total active ingredients (over 261,000 lbs). Ten insecticides predominated in the watershed, while only small quantities of three fungicides were used. Total pesticide usage and intensity were estimated using the CDL. Nutrient inputs to cropland from animal manure, chemical fertilizer, and atmospheric deposition were modeled at over 30 million pounds of nitrogen and over 7 million pounds of phosphorous. Crops under conservation tillage had the largest input of both nutrients.     

Modeling of land use and reservoir effects on nonpoint source pollution in a highly agricultural basin

Nonpoint source (NPS) pollution is tightly linked to land use activities that determine the sources and magnitudes of pollutant loadings to stream water. The pollutant loads may also be alleviated within reservoirs because of the physical interception resulting from changed hydrological regimes and other biochemical processes. It is important but challenging to assess the NPS pollution processes with human effects due to the measurement limitations. The objective of this study is to evaluate the effects of human activities such as land uses and reservoir operation on the hydrological and NPS pollution processes in a highly agricultural area-the Iowa River Basin-using the Soil and Water Assessment Tool (SWAT). The evaluation of model performance at multiple sites reveals that SWAT can consistently simulate the daily streamflow, and monthly/annual sediment and nutrient loads (nitrate nitrogen and mineral phosphorus) in the basin. We also used the calibrated model to estimate the trap efficiencies of sediment (～78%) and nutrients (～30%) in the Coralville Reservoir within the basin. These non-negligible effects emphasize the significance of incorporating the sediment and nutrient removal mechanisms into watershed system studies. The spatial quantification of the critical NPS pollution loads can help identify hot-spot areas that are likely locations for the best management practices.     

Using watershed characteristics,sediment, and tissue of resident mollusks to identify potential sources of trace elements to streams in a complex agricultural landscape

Trace elements used in animal feed additives can be introduced to aquatic environments through application of manures from animal feeding operations to agricultural land as fertilizer. The use of poultry feed additives containing arsenic (As) is of particular concern in the Shenandoah River watershed (Virginia, USA), an agricultural landscape with a high density of poultry operations. This study investigated the relationship between watershed characteristics of Shenandoah River tributaries and trace element concentrations in streambed sediment and tissue of resident mollusks, including: Asian clams (Corbicula fluminea), which are commonly used biomonitors, and pleurocerid snails (Leptoxis carinata), which are generally understudied. Results failed to support the primary hypothesis of a predictive relationship between watershed densities of poultry operations and As concentrations in sediment and mollusk tissue. However, there were statistical relationships between land use in tributary watersheds and other trace elements in sediment (Cu, Mn, Pb, Zn) and tissue (Cd, Hg, Pb). Principal components analysis of the sediment data suggested a possible geologic source of As at some sites. Tissue concentrations of As were significantly higher in snails than in clams, but clams accumulated higher concentrations of other trace elements (Cd, Cr, Hg, Pb, Se). Snails may be useful biomonitors of environmental As, but appear to be less suitable than clams for studies of landscape sources of other trace elements.     

Critical Sampling Points Methodology: Case Studies of Geographically Diverse Watersheds

Only with a properly designed water quality monitoring network can data be collected that can lead to accurate information extraction. One of the main components of water quality monitoring network design is the allocation of sampling locations. For this purpose, a design methodology, called critical sampling points (CSP), has been developed for the determination of the critical sampling locations in small, rural watersheds with regard to total phosphorus (TP) load pollution. It considers hydrologic, topographic, soil, vegetative, and land use factors. The objective of the monitoring network design in this methodology is to identify the stream locations which receive the greatest TP loads from the upstream portions of a watershed. The CSP methodology has been translated into a model, called water quality monitoring station analysis (WQMSA), which integrates a geographic information system (GIS) for the handling of the spatial aspect of the data, a hydrologic/water quality simulation model for TP load estimation, and fuzzy logic for improved input data representation. In addition, the methodology was purposely designed to be useful in diverse rural watersheds, independent of geographic location. Three watershed case studies in Pennsylvania, Amazonian Ecuador, and central Chile were examined. Each case study offered a different degree of data availability. It was demonstrated that the developed methodology could be successfully used in all three case studies. The case studies suggest that the CSP methodology, in form of the WQMSA model, has potential in applications world-wide.     

A hydrologic network supporting spatially referenced regression modeling in the Chesapeake Bay Watershed

The U.S. Geological Survey has developed a methodology for statistically relating nutrient sources and land-surface characteristics to nutrient loads of streams. The methodology is referred to as SPAtially Referenced Regressions On Watershed attributes (SPARROW), and relates measured stream nutrient loads to nutrient sources using nonlinear statistical regression models. A spatially detailed digital hydrologic network of stream reaches, stream-reach characteristics such as mean streamflow, water velocity, reach length, and travel time, and their associated watersheds supports the regression models. This network serves as the primary framework for spatially referencing potential nutrient source information such as atmospheric deposition, septic systems, point-sources, land use, land cover, and agricultural sources and land-surface characteristics such as land use, land cover, average-annual precipitation and temperature, slope, and soil permeability. In the Chesapeake Bay watershed that covers parts of Delaware, Maryland, Pennsylvania, New York, Virginia, West Virginia, and Washington D.C., SPARROW was used to generate models estimating loads of total nitrogen and total phosphorus representing 1987 and 1992 land-surface conditions. The 1987 models used a hydrologic network derived from an enhanced version of the U.S. Environmental Protection Agency's digital River Reach File, and course resolution Digital Elevation Models (DEMs). A new hydrologic network was created to support the 1992 models by generating stream reaches representing surface-water pathways defined by flow direction and flow accumulation algorithms from higher resolution DEMs. On a reach-by-reach basis, stream reach characteristics essential to the modeling were transferred to the newly generated pathways or reaches from the enhanced River Reach File used to support the 1987 models. To complete the new network, watersheds for each reach were generated using the direction of surface-water flow derived from the DEMs. This network improves upon existing digital stream data by increasing the level of spatial detail and providing consistency between the reach locations and topography. The hydrologic network also aids in illustrating the spatial patterns of predicted nutrient loads and sources contributed locally to each stream, and the percentages of nutrient load that reach Chesapeake Bay.     

Stream sediment and nutrient loads in the Tahoe Basin—estimated vs monitored loads for TMDL “crediting”

Total maximum daily load (TMDL) programs utilize pollutant load reductions as the primary strategy to restore adversely affected waters of the USA. Accurate and defensible “crediting” for TMDL reductions of sediment and nutrients requires stream monitoring programs capable of quantitative assessment of soil erosivity and the “connectivity” between erosive areas and stream channels across the watershed. Using continuous (15-min) stream monitoring information from typical alpine, snowmelt-driven watersheds [Ward (2,521 ha), Blackwood (2,886 ha), and Homewood (260 ha, Homewood Mountain Resort—HMR) Creeks] on the west shore of the Lake Tahoe Basin, daily sediment (and nutrient for HMR) loads are determined and compared with those developed from estimated load–flow relationships developed from grab sampling data. Compared to the previously estimated sediment load–discharge relationships, measured curves were slightly below those estimated, though not significantly so at Blackwood and Ward Creeks in the period 1997–2002. Based on average daily flowrates determined from calibrated hydrologic modeling during the period 1994–2004, average daily flowrate frequency distributions per year are determined from which load reduction “crediting” towards TMDL targets can be evaluated. Despite seemingly similar estimated and measured sediment load–flow relationships, annual “estimated” loads exceeded those “measured” by about 40 % for Ward and Blackwood Creeks and over 300 times for HMR Creek. Similarly, though less dramatic, estimated annual nutrient loads at HMR Creek exceeded those measured by 1.7 and 6 times for total nitrogen and total phosphorus, respectively. Such results indicate that actual measured load–flow relationships are likely necessary for realistic quantitative and defensible TMDL crediting.     

Nonpoint Source Pollution Assessment of Wujiang RiverWatershed in Guizhou Province,SW China

The amount of pollution from nonpoint sources flowing in the streams of the Wujiang River watershed in Guizhou Province, SW China, is estimated by a geographic information system (GIS)-based method using rainfall, surface runoff and land use data. A grid of cells of 100 m in size is laid over the landscape. For each cell, mean annual surface runoff is estimated from rainfall and percent land use, and expected pollutant concentration is estimated from land use. The product of surface runoff and concentration gives expected pollutant loading from that cell. These loadings are accumulated going downstream to give the expected annual pollutant loadings in streams and rivers. By dividing these accumulated loadings by the similarly accumulated mean annual surface runoff, the expected pollutant concentration from nonpoint sources is determined for each location in a stream or river. Observed pollutant concentrations in the watershed are averaged at each sample point and compared to the expected concentrations at the same locations determined from the grid cell model. In general, annual nonpoint source nutrient loadings in the Wujiang River watershed are seen to be predominantly from the agricultural and meadow areas. The total annual loadings through the outlet of the watershed are 40,309 and 2,607 tons for total nitrogen (TN) and total phosphorus (TP), respectively.     

Wheat yield functions for analysis of land-use change in China

CERES-Wheat, a dynamic process crop growth model, is specified and validated for eight sites in the major wheat-growing regions of China. Crop model results are then used to test the Mitscherlich-Baule and the quadratic functional forms for yield response to nitrogen fertilizer, irrigation water, temperature, and precipitation. The resulting functions are designed to be used in a linked biophysical-economic model of land-use and land-cover change in China. While both functions predict yield responses adequately, the Mitscherlich-Baule function is preferable to the quadratic function because its parameters are biologically and physically realistic. Variables explaining a significant proportion of simulated yield variance are nitrogen, irrigation water, and precipitation; temperature was a less significant component of yield variation within the range of observed year-to-year variability at the study sites. Crop model simulations with a generic soil with median characteristics of the eight sites compared to simulations with site-specific soils showed that agricultural soils in China have similar and, in general, low-to-moderate water-holding capacities and organic matter contents. The validated crop model is useful for simulating the range of conditions under which wheat is grown in China, and provides the means to estimate production functions when experimental field data are not available.     

Exploring the Relationship Between Hydrologic Parameters and Nutrient Loads Using Digital Elevation Model and GIS – A Case Study from Sugarcreek Headwaters, Ohio, U.S.A.

Ohio is typical among the Midwestern and Eastern United States with high levels of water pollutants, the main sources being from agriculture. In this study, we used a digital elevation model in conjunction with hydrological indices to determine the role of landscape complexity affecting the spatial and temporal variation in pollutant levels, in one of the most impaired headwater streams in Ohio. More than eighty five percent of the study area is dominated by agriculture. Spatial distribution of slope (S), altitude and wetness index along with other watershed parameters such as flow direction, flow accumulation, stream networks, flow stream orders and erosion index were used within a Geographic Information Systems framework to quantify variation in nitrate and phosphate loads to headwater streams. Stream monitoring data for nutrient loads were used to correlate the observed spatial and temporal patterns with hydrological parameters using multiple linear regressions. Results from the wetness index calculated from a digital elevation model suggested a range of 0.10–16.39, with more than 35% having values less than 4.0. A Revised Universal Soil Loss Equation (RUSLE) predicted soil loss in the range of 0.01–4.0 t/ha/yr. Nitrate nitrogen levels in the study area paralleled precipitation patterns over time, with higher nitrate levels corresponding to high precipitation. Atmospheric deposition through precipitation could explain approximately 35% of total nitrate levels observed in streams. Among the different topographic variables and hydrological indices, results from the step-wise multiple regression suggested the following best predictors, (1) elevation range and upstream flow length for nitrate, (2) flow direction and upstream flow length for ammonia-nitrogen and slope, and (3) elevation range for phosphate levels. Differences in the landscape models observed for nitrate, phosphate and ammonia-nitrogen in the surface waters were attributed partly to differences in the chemical activity and source strengths of the different forms of these nutrients through agricultural management practices. The results identify geomorphologic and landscape characteristics that influence pollutant levels in the study area.     

Identification of spatiotemporal nutrient patterns in a coastal bay via an integrated k-means clustering and gravity model

This study presents an integrated k-means clustering and gravity model (IKCGM) for investigating the spatiotemporal patterns of nutrient and associated dissolved oxygen levels in Tampa Bay, Florida. By using a k-means clustering analysis to first partition the nutrient data into a user-specified number of subsets, it is possible to discover the spatiotemporal patterns of nutrient distribution in the bay and capture the inherent linkages of hydrodynamic and biogeochemical features. Such patterns may then be combined with a gravity model to link the nutrient source contribution from each coastal watershed to the generated clusters in the bay to aid in the source proportion analysis for environmental management. The clustering analysis was carried out based on 1 year (2008) water quality data composed of 55 sample stations throughout Tampa Bay collected by the Environmental Protection Commission of Hillsborough County. In addition, hydrological and river water quality data of the same year were acquired from the United States Geological Survey's National Water Information System to support the gravity modeling analysis. The results show that the k-means model with 8 clusters is the optimal choice, in which cluster 2 at Lower Tampa Bay had the minimum values of total nitrogen (TN) concentrations, chlorophyll a (Chl-a) concentrations, and ocean color values in every season as well as the minimum concentration of total phosphorus (TP) in three consecutive seasons in 2008. The datasets indicate that Lower Tampa Bay is an area with limited nutrient input throughout the year. Cluster 5, located in Middle Tampa Bay, displayed elevated TN concentrations, ocean color values, and Chl-a concentrations, suggesting that high values of colored dissolved organic matter are linked with some nutrient sources. The data presented by the gravity modeling analysis indicate that the Alafia River Basin is the major contributor of nutrients in terms of both TP and TN values in all seasons. With this new integration, improvements for environmental monitoring and assessment were achieved to advance our understanding of sea-land interactions and nutrient cycling in a critical coastal bay, the Gulf of Mexico.     

Assessing the impact of irrigation treatments on thiram residual trends: Correspondence with numerical modelling and field-scale experiments

The present study was undertaken to study the trends of transport of thiram, a dithiocarbamate pesticide, at different time and depth in the fields under real field conditions for wheat crop. Numerical simulations were carried out by solving the coupled soil–water content movement and mass transport equations using HYDRUS- 1D. The supplementary data used for paramaterization of HYDRUS-1D comprise of irrigation treatments, climatic conditions, and soil characteristics. Results focus on the effects and influence of irrigation treatments on pesticide persistence and mobility. Modelling results were in good agreement with the experimentally determined thiram concentrations. Application of the model to measured field data of thiram movement indicates that the modelling approach can provide reliable and useful estimates of the mass flux of water and non-volatile pesticide in vadose zone. For policy-makers and planners, some regulation strategies are suggested for controlling inappropriate pesticide application under deficit irrigation or rain-fed conditions.