Dual Objective Control of Nutrient Loading into a Lake1

ABSTRACT: The control of nutrient loading into a water body is approached from a multiobjective viewpoint. The example of phosphorus (P) loading into Lake Balaton, Hungary, is used as a case study. The element P is chosen because it appears to be the limiting factor of eutrophication in the lake considered, as in many other lakes. About one-half of P loading originates from nonpoint sources; furthermore, the mechanism is poorly known and only few observation data are available. The objective of eutrophication control is to minimize P loading, while the objective of watershed management is to maximize agricultural revenue. These two objectives often appear to be in conflict. A discrete set of alternative control methods is defined, consisting in controlling a mix of the following elements: point sources, runoff, fertilizer type and application, cropping management, erosion, and sedimentation. The system dynamics is provided by a previously developed stochastic model, whose output is an empirical prohability density function (pdf) of P-loading reflecting the control policy. A compromise solution of “satisfactum” can then be chosen as a mix of the best ranked policies.     

AN INTERACTWE MODELING ENVIRONMENT FOR NON-POINT SOURCE POLLUTION CONTROL1

ABSTRACT: Non-point source pollution cuntinues to be an important environmental and water quality management problem. For the moat part, analysis of non-point source pollution in watersheds has depended on the use of distributed models to identify potential problem areas and to assess the effectiveness of alternative management practices. To effectively use these models for watershed water quality management, users depend on integrated geographic information systems (GIS)-based interfaces for input/output data management. However, existing interfaces are ad-hoc and the utility of GIS is limited to organization of input data and display of output data. A highly interactive water quality modeling interface that utilizes the functional components and analytical capability of GIS is highly desirable. This paper describes the tight coupling of the Agricultural Non-point Source (AGNPS) water quality model and ARC/INFO GIS software to provide an interactive hybrid modeling environment for evaluation of non-point source pollution in a watershed. The modeling environment is designed to generate AGNPS input parameters from user-specified GIS coverages, create AGNPS input data files, control AGNPS model simulations, and extract and organize AGNPS model output data for display. An example application involving the estimation of pesticide loading in a southern Iowa agricultural watershed demonstrates the capability of the modeling environment. Compared with traditional methods of watershed water quality modeling using the AGNPS model or other ad-hoc interfaces between a distributed model and GIS, the interactive modeling environment system is efficient and significantly reduces the task of watershed analysis using tightly coupled GIS databases and distributed models.     

EXPORT COEFFICIENT MODELING TO ASSESS PHOSPHORUS LOADING IN AN URBAN WATERSHED1

ABSTRACT: An export coefficient modeling approach was used to assess the influence of land use on phosphorus loading to a Southern Ontario stream. A model was constructed for the 1995–1996 water year and calibrated within ± 3 percent of the observed mean concentration of total phosphorus. It was found that runoff from urban areas contributed most to the loading of phosphorus to the stream. When the model was assessed by running it for the 1977–1978 water year, using water quality and land use data collected independently, agreement within ± 7 percent was obtained. The model was then used to forecast the impact of future urban development proposed for the watershed, in terms of phosphorus loading, and to evaluate the reduction in loading resulting from several urban best management practices (BMP). It was determined that phosphorus removal will have to be applied to all the urban runoff from the watershed to appreciably reduce stream phosphorus concentration. Of the BMP designs assessed, an infiltration pond system resulted in the greatest phosphorus load reduction, 50 percent from the 1995–1996 baseline.     

A Multilevel Model of the Impact of Farm‐Level Best Management Practices on Phosphorus Runoff1

Abstract: Multilevel or hierarchical models have been applied for a number of years in the social sciences but only relatively recently in the environmental sciences. These models can be developed in either a frequentist or Bayesian context and have similarities to other methods such as empirical Bayes analysis and random coefficients regression. In essence, multilevel models take advantage of the hierarchical structure that exists in many multivariate datasets; for example, water quality measurements may be taken from individual lakes, lakes are located in various climatic zones, lakes may be natural or man‐made, and so on. The groups, or levels, may effectively yield different responses or behaviors (e.g., nutrient load response in lakes) that often make retaining group membership more effective when developing a predictive model than when working with either all of the data together or working separately with the individuals. Here, we develop a multilevel model of the impact of farm level best management practices (BMPs) on phosphorus runoff. The result of this research is a model with parameters which vary with key practice categories and thus may be used to evaluate the effectiveness of these practices on phosphorus runoff. For example, it was found that the effect of fertilizer application rate on farm‐scale phosphorus loss is a function of the application method, the hydrologic soil group, and the land use (crop type). Further, results indicate that the most effective method for controlling fertilizer loss is through soil injection. In summary, the resultant multilevel model can be used to estimate phosphorus loss from farms and hence serve as a useful tool for BMP selection.     

Effects of calibration on L-THIA GIS runoff and pollutant estimation

Urbanization can result in alteration of a watershed's hydrologic response and water quality. To simulate hydrologic and water quality impacts of land use changes, the Long-Term Hydrologic Impact Assessment (L-THIA) system has been used. The L-THIA system estimates pollutant loading based on direct runoff quantity and land use based pollutant coefficients. The accurate estimation of direct runoff is important in assessing water quality impacts of land use changes. An automated program was developed to calibrate the L-THIA model using the millions of curve number (CN) combinations associated with land uses and hydrologic soil groups. L-THIA calibration for the Little Eagle Creek (LEC) watershed near Indianapolis, Indiana was performed using land use data for 1991 and daily rainfall data for six months of 1991 (January 1-June 30) to minimize errors associated with use of different temporal land use data and rainfall data. For the calibration period, the Nash-Sutcliffe coefficient was 0.60 for estimated and observed direct runoff. The calibrated CN values were used for validation of the model for the same year (July 1-December 31), and the Nash-Sutcliffe coefficient was 0.60 for estimated and observed direct runoff. The Nash-Sutcliffe coefficient was 0.52 for January 1, 1991 to December 31, 1991 using uncalibrated CN values. As shown in this study, the use of better input parameters for the L-THIA model can improve accuracy. The effects on direct runoff and pollutant estimation of the calibrated CN values in the L-THIA model were investigated for the LEC. Following calibration, the estimated average annual direct runoff for the LEC watershed increased by 34%, total nitrogen by 24%, total phosphorus by 22%, and total lead by 43%. This study demonstrates that the L-THIA model should be calibrated and validated prior to application in a particular watershed to more accurately assess the effects of land use changes on hydrology and water quality.     

LAKE QUALITY DISCRIMINANT ANALYSIS1

ABSTRACT: Despite the fact that lake phosphorus loading criteria have proven to be valuable tools in lake management, they are generally subjective in nature or incomplete in form. In order to address these shortcomings, the oxic-anoxic transition point was selected as an objective quality criterion and discriminant analysis was used to construct a lake classification function. This function is dependent upon lake phosphorus loading, mean depth, and overflow rate. The value of the function may be expressed as a probability of classification (as either oxic or anoxic). When used in prediction, inclusion of the input error permits the estimation of the change in classification probability as input uncertainty is reduced. Further, the form of the discriminant function suggests that the annual volumetric loading is a more informative term for the expression of phosphorus loading than is the annual areal loading.     

EFFECTS OF SLUDGE AND CHEMICAL FERTILIZER APPLICATION ON RUNOFF WATER QUALITY1

ABSTRACT: Simulated rainfall was used on experimental field plots to compare the effect of chemical fertilizer and sludge application on sediment, nitrogen, and phosphorus in runoff from no-till and conventional tillage systems. Chemical fertilizer application under the no-till system resulted in the least amount of total N and P in surface runoff. However, sludge application under the no-till system resulted in the least amount of NO₃-N and sediment in surface runoff. The worst water quality scenarios were observed when either sludge or chemical fertilizer were surface-applied under a conventional tillage system. Nitrogen losses from the conventional tillage system were minimized when sludge was incorporated into the soil. However, phosphorus and sediment yield from such a system were significantly higher when compared to phosphorus and sediment yield from the no-till system. The results from this study indicate that the use of sludge on agricultural land under a no-till system can be a viable alternative to chemical fertilizer for nitrogen and phosphorus control in runoff. A more cautious approach is recommended when the sludge is incorporated into the soil in a conventional tillage system because of potential for high sediment and phosphorus yield in surface runoff.     

PREDICTIVE MODELS FOR THE BIOMASS OF BLUE-GREEN ALGAE IN LAKES1

In lakes which experience water quality problems due to the nuisance growth of blue-green algae, summer concentrations of chlorophyll a may not always be a meaningful measure of water quality for making management decisions. Models for the prediction of summer mean blue-green algal biomass were thus developed from data collected from five systems located in North America and Sweden. It is suggested that the model of choice is log BG =?0.142 + 0.596 log TP – 0.963 log Z, where BG is the biomass of blue-green algae (g m^?3), TP is the concentration of total phosphorus (mg m^?3), and Z is the mean depth of the lake (m). When coupled to current loading models, this model can potentially be used to assess the impacts of phosphorus loading reductions on threshold odor in water supplies.     

Development of a Quantitative Pasture Phosphorus Management Tool Using the SWAT Model1

Abstract: Assessment tools to evaluate phosphorus loss from agricultural lands allow conservation planners to evaluate the impact of management decisions on water quality. Available tools to predict phosphorus loss from agricultural fields are either: (1) qualitative indices with limited applicability to address offsite water quality standards, or (2) models which are prohibitively complex for application by most conservation planners. The purpose of this research was to develop a simple interface for a comprehensive hydrologic/water quality model to allow its usage by farmers and conservation planners. The Pasture Phosphorus Management (PPM) Calculator was developed to predict average annual phosphorus (P) losses from pastures under a variety of field conditions and management options. PPM Calculator is a vastly simplified interface for the Soil and Water Assessment Tool (SWAT) model that requires no knowledge of SWAT by the user. PPM Calculator was validated using 33 months of data on four pasture fields in northwestern Arkansas. This tool has been extensively applied in the Lake Eucha/Spavinaw Basin in northeastern Oklahoma and northwestern Arkansas. PPM Calculator allows conservation planners to take advantage of the predictive capacity of a comprehensive hydrologic water quality model typically reserved for use by hydrologists and engineers. This research demonstrates the applicability of existing water quality models in the development of user friendly P management tools.     

A STATISTICAL MODEL FOR SMALL LAKE WATER QUALITY MANAGEMENT1

ABSTRACT: Phosphorus loading tolerances of small lakes are analyzed by means of a statistical model of lake eutrophication based upon the work of Vollenweider and Dillon. Using a sample of 195 midwestern and eastern U. S. lakes, it was found that Vollenweider and Dillon's method of predicting the trophic status of relatively deep, slow-flushing lakes can be applied to shallower lakes with much shorter retention times. The statistical model used to replicate the results of Vollenweider and Dillon is stated in detail, for convenience of application to small lake water quality management problems. The model extends the Vollenweider and Dillon results by associating each alternative phosphorous loading with a probability that a given lake can achieve or maintain noneutrophis status. It is applicable to lakes for which only minimal data are available. The major policy conclusion is that the highly variable tolerance for phosphorus loading must be considered in legislating efficient effluent limitations. The paper concludes with a comparison to a recent contribution employing a similar approach.     

湖泊蓝藻水华数字化预警系统构建探讨

构造湖泊蓝藻水华数字化预警系统是我国湖泊水环境管理的一个重要方向。本文探讨了构建湖泊蓝藻水华数字化预警系统的若干技术问题,包括：（1）数字化预警数学模式。提出需重视流域尺度的氮磷营养物和沉积动态输入以及营养物、沉积物对水生态结构动力过程的影响,建立非点源模型和湖泊生态结构动力学模型相耦合的预警数学模型模式;在此基础上提出了各种数学模型的可借鉴模式。（2）湖泊蓝藻水华预警监测技术。总结了常规水质监测的数据筛选方法,探讨了遥感技术和实时传输监测技术在水质监测中的应用模式,提出了实时监测和遥感监测需解决的技术难题和实现方法。（3）湖泊蓝藻数字化预警系统的设计。提出了数学模型系统、水质监控系统的网络化集成设计模式,提出了基于网络化地理信息系统的计算机应用软件实现模式。     

EVALUATION OF RUNOFF,EROSION, AND PHOSPHORUS MODELING SYSTEM—SIMPLE1

ABSTRACT: The purpose of this study was to evaluate the performance of Spatially Integrated Models for Phosphorus Loading and Erosion (SIMPLE) in predicting runoff volume, sediment loss, and phosphorus loading from two watersheds. The modeling system was applied to the 334 ha QOD subwatershed, part of the Owl Run watershed, located in Fauquier County, Virginia, and to the 2240 ha watershed, Battle Branch, located in Delaware County, Oklahoma. Simulation runs were conducted at cell and field scales, and simulation results were compared with observed data. Runoff volume and dissolved phosphorus loading were measured at the Battle Branch watershed. Runoff volume, sediment yield, and total phosphorus loading were measured at the QOD site. SIMPLE tended to underestimate runoff volumes during the dormant period, from November to March. The comparison between observed and predicted dissolved phosphorus showed better correlation than for observed and predicted total phosphorus loading. Cell level simulations provided similar estimates of runoff volume and phosphorus loading when compared to field level simulations for both watersheds. However, observed sediment yields better compared with the values predicted from the cell level simulation when compared to field level simulation. Finally, results of model evaluation indicated that SIMPLE's predictive ability is acceptable for screening applications but not for site-specific quantitative predictions.     

Ecological scenarios analyzed and evaluated by a shallow lake model

We applied the complex ecosystem model EMMO, which was adopted to the shallow lake Müggelsee (Germany), in order to evaluate a large set of ecological scenarios. By means of EMMO, 33 scenarios and 17 indicators were defined to characterize their effects on the lake ecosystem. The indicators were based on model outputs of EMMO and can be separated into biological indicators, such as chlorophyll-a and cyanobacteria, and hydro-chemical indicators, such as phosphorus. The question to be solved was, what is the ranking of the scenarios based on their characterization by these 17 indicators? And how can we handle high quantities of complex data within evaluation procedures? The scenario evaluation was performed by partial order theory which, however, did not provide a clear result. By subsequently applying the hierarchical cluster analysis (complete linkage) it was possible to reduce the data matrix to indicator and scenario representatives. Even though this step implies losses of information, it simplifies the application of partial order theory and the post processing by METEOR. METEOR is derived from partial order theory and allows the stepwise aggregation of indicators, which subsequently leads to a distinct and clear decision. In the final evaluation result the best scenario was the one which defines a minimum nutrient input and no phosphorus release from the sediment while the worst scenario is characterized by a maximum nutrient input and extensive phosphorus release from the sediment. The reasonable and comprehensive results show that the combination of partial order, cluster analysis and METEOR can handle big amounts of data in a very clear and transparent way, and therefore is ideal in the context of complex ecosystem models, like that we applied.     

Understanding the anthropogenic phosphorus pathway with substance flow analysis at the city level

Excessive input of phosphorus into natural water bodies as a result of anthropogenic processes is an escalating factor that leads to eutrophication. Hence, quantifying the pathway of phosphorus throughout the socioeconomic system is essential for the selection of appropriate measures to mitigate phosphorus discharge. The study develops an analytical model of anthropogenic phosphorus flows within a socioeconomic system based on substance flow analysis. The model consists of five major subsystems: the phosphorous chemical industry, agriculture, animal feeding, human consumption, and waste management. The results show that the total input and output of phosphorus in Chaohu City over 2008 are 8517.70 ton (t) and 4682.76 t, respectively. The estimation of phosphorus discharged into local surface water is 544.22 t, which primarily comes from agriculture (391.99 t, 72.03%), followed by large-scale farming (55.70 t, 10.23%), rural consumption (56.81 t, 10.44%), urban consumption (30.42 t, 5.59%), and waste management (9.30 t, 1.71%). Intensive input of fertilizers in agricultural practices was identified as the most important source of phosphorus load on local surface water. Hence, we propose that the eutrophication of local water bodies could be addressed by optimizing local industrial structure, developing ecological and organic-based agriculture, and improving waste collection and disposal practices.     

VALIDATION OF AGNPS FOR SMALL WATERSHEDS USING AN INTEGRATED AGNPS/GIS SYSTEM1

ABSTRACT: The AGNPS (AGricultural NonPoint Source) model was evaluated for predicting runoff and sediment delivery from small watersheds of mild topography. Fifty sediment yield events were monitored from two watersheds and five nested subwater-sheds in East Central Illinois throughout the growing season of four years. Half of these events were used to calibrate parameters in the AGNPS model. Average calibrated parameters were used as input for the remaining events to obtain runoff and sediment yield data. These data were used to evaluate the suitability of the AGNPS model for predicting runoff and sediment yield from small, mild-sloped watersheds. An integrated AGNPS/GIS system was used to efficiently create the large number of data input changes necessary to this study. This system is one where the AGNPS model was integrated with the GRASS (Geographic Resources Analysis Support System) GIS (Geographical Information System) to develop a decision support tool to assist with management of runoff and erosion from agricultural watersheds. The integrated system assists with the development of input GIS layers to AGNPS, running the model, and interpretation of the results.     

MODELING SEDIMENT AND PHOSPHORUS LOSSES IN AN AGRICULTURAL WATERSHED TO MEET TMDLs1

ABSTRACT: This paper studies the effectiveness of alternative farm management strategies at improving water quality to meet Total Maximum Daily Loads (TMDLs) in agricultural watersheds. A spatial process model was calibrated using monthly flow, sediment, and phosphorus (P) losses (1994 to 1996) from Sand Creek watershed in south‐central Minnesota. Statistical evaluation of predicted and observed data gave r² coefficients of 0.75, 0.69, and 0.49 for flow (average 4.1 m³/s), sediment load (average 0.44 ton/ha), and phosphorus load (average 0.97 kg/ha), respectively. The calibrated model was used to evaluate the effects of conservation tillage, conversion of crop land to pasture, and changes in phosphorus fertilizer application rate on pollutant loads. TMDLs were developed for sediment and P losses based on existing water quality standards and guidelines. Observed annual sediment and P losses exceeded these TMDLs by 59 percent and 83 percent, respectively. A combination of increased conservation tillage, reduced application rates of phosphorus fertilizer, and conversion of crop land to pasture could reduce sediment and phosphorus loads by 23 percent and 20 percent of existing loads, respectively. These reductions are much less than needed to meet TMDLs, suggesting that control of sediment using buffer strips and control of point sources of phosphorus are needed for the remaining reductions.     

Role of wetlands in reducing phosphorus loading to surface water in eight watersheds in the Lake Champlain Basin

A landscape-level approach was applied to eight rural watersheds to assess the role that wetlands play in reducing phosphorus loading to surface waters in the Lake Champlain Basin. Variables summarizing various characteristics of wetlands within a watershed were calculated using a geographic information system and then compared to measured phosphorus loading through multiple regression analyses. The inclusion of a variable based on the area of riparian wetlands located along low- and medium-order streams in conjunction with the area of agricultural and nonwetland forested lands explained 88% of the variance in phosphorus loading to surface waters. The best fit model coefficients (P_load = 0.86Ag + 0.64For – 30Ripwet + 160) suggest that a hectare of riparian wetland may be many times more important in reducing phosphorus than an agricultural hectare is in producing phosphorus. These results provide additional support for the concept that protection of riparian wetlands is an important management strategy for controlling stream water quality in multiuse landscapes.     

Agricultural Land Use and Best Management Practices to Control Nonpoint Water Pollution

In recent years, improvements in point-source depuration technologies have highlighted the problems regarding agricultural nonpoint (diffuse) sources, and this issue has become highly relevant from the environmental point of view. The considerable extension of the areas responsible for this kind of pollution, together with the scarcity of funds available to local managers, make minimizing the impacts of nonpoint sources on a whole basin a virtually impossible task. This article presents the results of a study intended to pinpoint those agricultural areas, within a basin, that contribute most to water pollution, so that operations aimed at preventing and/or reducing this kind of pollution can be focused on them. With this aim, an innovative approach is presented that integrates a field-scale management model, a simple regression model, and a geographic information system (GIS). The Lake Vico basin, where recent studies highlighted a considerable increase in the trophic state, mainly caused by phosphorus (P) compounds deriving principally from the intensive cultivation of hazelnut trees in the lake basin, was chosen as the study site. Using the management model Groundwater Loading Effects of Agricultural Management Systems (GLEAMS), the consequences, in terms of sediment yield and phosphorus export, of hazelnut tree cultivation were estimated on different areas of the basin with and without the application of a best management practice (BMP) that consists of growing meadow under the trees. The GLEAMS results were successively extended to basin scale thanks to the application of a purposely designed regression model and of a GIS. The main conclusions can be summarized as follows: The effectiveness of the above-mentioned BMP is always greater for erosion reduction than for particulate P reduction, whatever the slope value considered; moreover, the effectiveness with reference to both particulate P and sediment yield production decreases as the slope increases. The proposed approach, being completely distributed, represents a considerable step ahead compared to the semidistributed or lumped approaches, which are traditionally employed in research into tools to support the decision-making process for land-use planning aimed at water pollution control.     

Application of nutrient loading models to the analysis of trophic conditions in Lake Okeechobee,Florida

Lake Okeechobee (surface area = 1830 km², mean depth = 3.5 m), the largest lake in Florida, is eutrophic and has nitrogen and phosphorus loading rates in excess of nearly all established criteria. The lake is not homogeneous regarding trophic conditions, and spatial and temporal variations occur regarding nutrient limitation. Nonetheless, phosphorus loading rate and trophic state data fit reasonably well to various input-output models developed for temperate lakes. Modification of the models by regression analysis to fit data for Florida lakes resulted in improved predictions for most parameters. Analysis of nutrient management alternatives for the lake indicates that a 75% reduction of phosphorus loading from the largest source (the Taylor Creek-Nubbins Slough watershed) would reduce the average chlorophyll a concentration by less than 20%. Complete elimination of inputs from the largest nitrogen source (the Everglades Agricultural Area) would decrease the average nitrogen concentration in the lake by about 20%. Limitations of nutrient inputoutput models regarding analysis of trophic conditions and management alternatives for the lake are discussed.     

Predicting Debris Yield From Burned Watersheds: Comparison of Statistical and Artificial Neural Network Models1

Abstract: Alluvial fans in southern California are continuously being developed for residential, industrial, commercial, and agricultural purposes. Development and alteration of alluvial fans often require consideration of mud and debris flows from burned mountain watersheds. Accurate prediction of sediment (hyper‐concentrated sediment or debris) yield is essential for the design, operation, and maintenance of debris basins to safeguard properly the general population. This paper presents results based on a statistical model and Artificial Neural Network (ANN) models. The models predict sediment yield caused by storms following wildfire events in burned mountainous watersheds. Both sediment yield prediction models have been developed for use in relatively small watersheds (50‐800 ha) in the greater Los Angeles area. The statistical model was developed using multiple regression analysis on sediment yield data collected from 1938 to 1983. Following the multiple regression analysis, a method for multi‐sequence sediment yield prediction under burned watershed conditions was developed. The statistical model was then calibrated based on 17 years of sediment yield, fire, and precipitation data collected between 1984 and 2000. The present study also evaluated ANN models created to predict the sediment yields. The training of the ANN models utilized single storm event data generated for the 17‐year period between 1984 and 2000 as the training input data. Training patterns and neural network architectures were varied to further study the ANN performance. Results from these models were compared with the available field data obtained from several debris basins within Los Angeles County. Both predictive models were then applied for hind‐casting the sediment prediction of several post 2000 events. Both the statistical and ANN models yield remarkably consistent results when compared with the measured field data. The results show that these models are very useful tools for predicting sediment yield sequences. The results can be used for scheduling cleanout operation of debris basins. It can be of great help in the planning of emergency response for burned areas to minimize the damage to properties and lives.