FACTORS CONTROLLING RUNOFF NUTRIENT LOSS FROM CULTIVATED LAND IN EASTERN SOUTH DAKOTA1

ABSTRACT A stepwise multiple regression was used to evaluate the relative importance of antecedent-, event-, and high-intensity-precipitation amounts; runoff volume; and precipitation nutrient contents and concentrations in determining nutrient losses in runoff. Plots were fertilized at high, medium, and low rates and had cultivation ridges oriented up-and-down slope or on the contour. Runoff volume was the important factor in determining the loss of NO₃, soluble PO₄, total PO₄, and soluble K ions in runoff from fallow, corn, or soybean plots. NH₄-N loss was controlled mainly by the precipitation content and antecedet precipitation since fertilizer had been applied. Nutrient losses were greater from plots fertilized at the high rate and from plots with cultivation ridges oriented up-and-down slope rather than on the contour.     

FLOOD FREQUENCY ANALYSIS FOR SMALL WATERSHEDS IN SOUTHERN ILLINOIS1

ABSTRACT: Twenty-two gaging stations were selected for developing a regional flood frequency curve for small (area less than 2 square miles) watersheds in southern Illinois. Five probability functions were compared, and the extreme value type I function was selected to develop the regional flood curve. The curve was generated with the index flood method and also another empirical method that related the function parameters to the watershed area. Estimated peak discharges with various return periods were compared with the results obtained from multiple regression analysis.     

A study of compliance with environmental regulations of ISO 14001 certified companies in Korea

This article investigates the impact of ISO 14001 certification on the compliance with environmental regulations by Korean companies. The impact of ISO 14001 certification on the industry was studied through a questionnaire survey and the compliance of environmental regulations were investigated using government-released data. The motivation for an environment management system was a result of the current international situation and the need to maintain fair competition. ISO 14001 certification has been recognized as an essential strategy for industrial competition and to improve company/product recognition. The certified and non-certified companies' environmental regulation violation (ERV) rates were 3.5% and 11.6%, respectively, in 1997. In 1998, the ERV rate had an eight-time difference with 1.0% and 8.5% for certified and non-certified companies, respectively. Annual regulation violation rates were reduced from 3.5% in 1997 to 1.0% in 1998 with certified companies and from 11.6% in 1997 to 8.5% in 1998 with their non-certified counterparts, respectively. ISO 14001 certified companies showed more improvement than non-certified companies in regards to environmental performance.     

Refuse treatment options: a case study

Records in public archives were evaluated for the period 1981-1991. Simple surveys of peoples and of technology and physical premises provided insight to gauge the attitudes of a local community in the Melbourne municipality and the Melbourne City Council towards composting of organic waste materials. There is a lag in perception and attitudes between the local community and the local government towards composting of organic refuse as a solid waste treatment option. The simple methodology of the study still made it possible to verify past and present perceptions and attitudes.     

Estimation of the shadow prices of pollutants with production/environment inefficiency taken into account: a nonparametric directional distance function approach

This paper deals with the estimation of the shadow prices of pollutants with a nonparametric directional distance function approach, where the inefficiency involved in the production process is taken into account unlike the previous studies. The directional vector, which is critical to the estimation and subject to the criterion for an appropriate efficiency rule proposed here, is calculated by using the annual plans of power plants in terms of production and environment. In the empirical study for Korea's electric power industry during the period of 1990-1995, we find that the average shadow prices of sulfur oxides (SOx), nitrogen oxides (NOx), and total suspended particulates (TSP) are approximately 10% lower than those calculated under the assumption of full efficiency. The methodology we propose and the findings obtained in the empirical study allow us to undertake better decision-making over a broad range of environmental policy issues.     

ARCGIS‐SWAT: A GEODATA MODEL AND GIS INTERFACE FOR SWAT1

This paper presents ArcGIS‐SWAT, a geodata model and geographic information system (GIS) interface for the Soil and Water Assessment Tool (SWAT). The ArcGIS‐SWAT data model is a system of geodatabases that store SWAT geographic, numeric, and text input data and results in an organized fashion. Thus, it is proposed that a single and comprehensive geodatabase be used as the repository of a SWAT simulation. The ArcGIS‐SWAT interface uses programming objects that conform to the Component Object Model (COM) design standard, which facilitate the use of functionality of other Windows‐based applications within ArcGIS‐SWAT. In particular, the use of MS Excel and MATLAB functionality for data analysis and visualization of results is demonstrated. Likewise, it is proposed to conduct hydrologic model integration through the sharing of information with a not‐model‐specific hub data model where information common to different models can be stored and from which it can be retrieved. As an example, it is demonstrated how the Hydrologic Modeling System (HMS) ‐ a computer application for flood analysis ‐ can use information originally developed by ArcGIS‐SWAT for SWAT. The application of ArcGIS‐SWAT to the Seco Creek watershed in Texas is presented.     

MODELING FECAL COLIFORM CONTAMINATION IN THE RIO GRANDE1

This study examines sources of fecal coliform in Segment 2302 of the Rio Grande, located south of the International Falcon Reservoir in southern Texas. The watershed is unique because the contributing drainage areas lie in Texas and Mexico. Additionally, the watershed is mostly rural, with populated communities known as “colonias.” The colonias lack sewered systems and discharge sanitary water directly to the ground surface, thus posing an increased health hazard from coliform bacteria. Monitoring data confirm that Segment 2302 is not safe for contact recreation due to elevated fecal coliform levels. The goal of the study was to simulate the observed exceedences in Segment 2302 and evaluate potential strategies for their elimination. Fecal coliform contributions from ranching and colonia discharges were modeled using the Hydrologic Simulation Program‐Fortran (HSPF). Model results indicated that the regulatory 30‐day geometric mean fecal coliform concentration of 200 colony forming units (cfu) per 100 milliliters is exceeded approximately three times per year for a total of 30 days. Ongoing initiatives to improve wastewater facilities will reduce this to approximately once per year for 14 days. Best management practices will be necessary to reduce cattle access to streams and eliminate all exceedences. The developed model was limited by the relatively sparse flow and fecal coliform data.     

APPLICATION OF GREY MODEL AND ARTIFICIAL NEURAL NETWORKS TO FLOOD FORECASTING1

The main focus of this study was to compare the Grey model and several artificial neural network (ANN) models for real time flood forecasting, including a comparison of the models for various lead times (ranging from one to six hours). For hydrological applications, the Grey model has the advantage that it can easily be used in forecasting without assuming that forecast storm events exhibit the same stochastic characteristics as the storm events themselves. The major advantage of an ANN in rainfall‐runoff modeling is that there is no requirement for any prior assumptions regarding the processes involved. The Grey model and three ANN models were applied to a 2,509 km² watershed in the Republic of Korea to compare the results for real time flood forecasting with from one to six hours of lead time. The fifth‐order Grey model and the ANN models with the optimal network architectures, represented by ANN1004 (34 input nodes, 21 hidden nodes, and 1 output node), ANN1010 (40 input nodes, 25 hidden nodes, and 1 output node), and ANN1004T (14 input nodes, 21 hidden nodes, and 1 output node), were adopted to evaluate the effects of time lags and differences between area mean and point rainfall. The Grey model and the ANN models, which provided reliable forecasts with one to six hours of lead time, were calibrated and their datasets validated. The results showed that the Grey model and the ANN1010 model achieved the highest level of performance in forecasting runoff for one to six lead hours. The ANN model architectures (ANN1004 and ANN1010) that used point rainfall data performed better than the model that used mean rainfall data (ANN1004T) in the real time forecasting. The selected models thus appear to be a useful tool for flood forecasting in Korea.     

COMPARISON OF PROCESS‐BASED AND ARTIFICIAL NEURAL NETWORK APPROACHES FOR STREAMFLOW MODELING IN AN AGRICULTURAL WATERSHED1

ABSTRACT: The performance of the Soil and Water Assessment Tool (SWAT) and artificial neural network (ANN) models in simulating hydrologic response was assessed in an agricultural watershed in southeastern Pennsylvania. All of the performance evaluation measures including Nash‐Sutcliffe coefficient of efficiency (E) and coefficient of determination (R²) suggest that the ANN monthly predictions were closer to the observed flows than the monthly predictions from the SWAT model. More specifically, monthly streamflow E and R² were 0.54 and 0.57, respectively, for the SWAT model calibration period, and 0.71 and 0.75, respectively, for the ANN model training period. For the validation period, these values were ?0.17 and 0.34 for the SWAT and 0.43 and 0.45 for the ANN model. SWAT model performance was affected by snowmelt events during winter months and by the model's inability to adequately simulate base flows. Even though this and other studies using ANN models suggest that these models provide a viable alternative approach for hydrologic and water quality modeling, ANN models in their current form are not spatially distributed watershed modeling systems. However, considering the promising performance of the simple ANN model, this study suggests that the ANN approach warrants further development to explicitly address the spatial distribution of hydrologic/water quality processes within watersheds.