NON-ZERO LOWER LIMIT IN LOW FLOW FREQUENCY ANALYSIS?1

ABSTRACT: The implications of fitting distributions with non-zero lower limits to low flow data are examined. The 3-parameter Weibull distribution is fitted to annual minimum flow series from 60 long term stations in Canada. The relations between the estimated lower limit and three sampling variables (skewness, smallest, and largest observations) were investigated. The lower limit strongly depends on the sample skewness; it varies directly with the sample skewness, which in turn is highly influenced by the largest observation. For a given skewness, the value of the estimated lower limit is determined by the value of the smallest observation. Therefore, the lower limit cannot be accurately determined, and the resulting low flow estimates will be either too small or too high.     

ESTIMATION OF COASTAL WATER CONTAMINATION LONG-TERM TREND USING SEASONAL LINEAR MODELS1

ABSTRACT: Bivalves are used as bioindicators to assess trends of the chemical quality of coastal and marine environments due to their ability to concentrate chemicals. These shellfish are subject to seasonal physiological changes influencing the chemical concentration. Using quarterly data, we model concentration via linear regression with a biologically based seasonal component. This was applied to cadmium concentration measured in the blue mussel (Mytilus edulis) at three sites in the Seine estuary (Normandy, France). In this case we have a high concentration season from January to June and a “low concentration” season from July to December. This season definition was checked a posteriori, using box-and-whisker plots and a statistical test of comparison of pair-wise adjusted least-squares mean differences, and it appears to be very reasonable. We averaged data by season and across sites. Our final model (R²= 0.846 with N= 27 observations) includes highly significant terms: a season effect, which accounts for 45% of the total variability, a linear and a quadratic time term. Outliers were identified by high Studentized residual values and attributed to bias in the temporal sampling schemes. The methodology developed will further be used with other shellfish and/or other trace elements and organic chemicals.     

SIMULATING THREE-DIMENSIONAL GROUND WATER RESPONSE IN A SMALL MOUNTAINOUS WATERSHED1

ABSTRACT: Snowmelt from deep mountainous snowpacks is seldom rapid enough to exceed infiltration rates; thus, the source of streamflow in many mountainous watersheds is snowmelt recharge through shallow ground water systems. The hydrologic response and interaction between surface and sub-surface flow processes in these watersheds, which is controlled by basin structure, the spatial distribution of snowmelt, and the hydrogeology of the subsurface, are not well understood. The purpose of this study was to test a three-dimensional ground water model using simulated snowmelt input to simulate ground water response to spatially distributed snowmelt on the Upper Sheep Creek Watershed located within the Reynolds Creek Experimental Watershed in Southwestern Idaho. The model was used to characterize the mountainous aquifer and to delineate the subsurface flow mechanisms. Difficulty in finding a reasonable combination of grid spacing and time stepping within the model was encountered due to convergence problems with the Picard solution to the non-linear variably saturated ground water flow equations. Simulation results indicated that flow may be either unconfined or confined depending on inflow rate and hydrogeologic conditions in the watershed. The flow mechanism had a much faster response time when confined flow occurred. Response to snowmelt from a snow drift approximately 90 m away took only a few hours when flow was confined. Simulated results showed good agreement with piezometer measurements both in magnitude and timing; however, convergence problems with the Picard solution limited applicability of the model.     

EFFECT OF SIMULATED CLIMATE CHANGE ON SNOWMELT RUNOFF MODELING IN SELECTED BASINS1

ABSTRACT: The projected increase in the concentration of CO₂ and other greenhouse gases in the atmosphere is likely to result in a global temperature increase. This paper reports on the probable effects of a temperature increase and changes in transpiration on basin discharge in two different mountain snowmelt regions of the western United States. The hydrological effects of the climate changes are modeled with a relatively simple conceptual, semi-distributed snowmelt runoff model. Based on the model results, it may be concluded that increased air temperatures will result in a shift of snowmelt runoff to earlier in the snowmelt season. Furthermore, it is shown that it is very important to include the expected change in climate-related basin conditions resulting from the modeled temperature increase in the runoff simulation. The effect of adapting the model parameters to reflect the changed basin conditions resulted in a further shift of streamflow to April and an even more significant decrease of snowmelt runoff in June and July. If the air temperatures increase by approximately 5°C and precipitation and accumulated snow amounts remain about the same, runoff in April and May, averaged for the two basins, is expected to increase by 185 percent and 26 percent, respectively. The runoff in June and July will decrease by about 60 percent each month. Overall, the total seasonal runoff decreases by about 6 percent. If increased CO₂ concentrations further change basin conditions by reducing transpiration by the maximum amounts reported in the literature, then, combined with the 5°C temperature increase, the April, May, June, and July changes would average +230 percent, +40 percent, ?55 percent, and ?45 percent, respectively. The total seasonal runoff change would be +11 percent.     

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.     

INTEGRATING GEOGRAPHIC INFORMATION SYSTEMS AND MODFLOW FOR GROUND WATER RESOURCE ASSESSMENTS1

ABSTRACT: The Floridan Aquifer is the primary source of water in the coastal area of Santa Rosa County, Florida. In order to optimize well field design and analyze aquifer stress problems, the USGS MODFLOW code (McDonald and Harbaugh, 1988) is applied to develop a numerical computer model of the aquifer. The Geographical Information System (GIS) is the primary tool used in the development of the model grid, performance of the modeling procedure, and model analysis. The GIS is used in generating multiple grids in which to simulate both regional scale and local scale flow. The grid topology is recorded in geographic coordinates which facilitates geo-referencing and orientation of the grid to base maps and data coyerages. The GIS allows data transfer from various coverages to the nodes of the block centered grid where hydrogeologic information is stored as attributes to the grid coverage. From this grid coverage, pertinent information is queried within the GIS environment and used to generate the input files for the MODFLOW simulation. After MODFLOW execution, simulated heads and drawdown are imported into the grid coverage where residual error and recharge rates can be calculated. Contoured surfaces are then created for selected data sets including simulated heads, drawdown, residual error, and recharge rates. Model calibration is conducted utilizing the GIS to generate and process data sets associated with model simulations.     

THE INFLUENCE OF (x,y) UNCERTAINTY ON PREDICTION ERROR AND CONTOUR LINES FROM A THREE-DIMENSIONAL SURFACE1

ABSTRACT: In geohydrology, three-dimensional surfaces are typically represented as a series of contours. Water levels, saturated thickness, precipitation, and geological formation boundaries are a few examples of this practice. These surfaces start as point measurements that are then analyzed to interpolate between the known point measurements. This first step typically creates a raster or a set of grid points. In modeling, subsequent processing uses these to represent the shape of a surface. For display, they are usually converted to contour lines. Unfortunately, in many field applications, the (x, y) location on the earth's surface is much less confidently known than the data in the z dimension. To test the influence of (x, y) locational accuracy on z dimension point predictions and their resulting contours, a Monte Carlo study was performed on water level data from northwestern Kansas. Four levels of (x, y) uncertainty were tested ranging in accuracy from one arc degree-minute (± 2384 feet in the x dimension and ± 3036 feet in the y dimension) to Global Positioning Systems (GPS) accuracy (± 20 feet for relatively low cost systems). These span the range of common levels of locational uncertainty in data available to hydrologists in the United States. This work examines the influence that locational uncertainty can have on both point predictions and contour lines. Results indicate that overall mean error exhibits a small sensitivity to locational uncertainty. However, measures of spread and maximum errors in the z domain are greatly affected. In practical application, this implies that estimates over large regions should be asymptotically consistent. However, local errors in z can be quite large and increase with (x, y) uncertainty.     

GEOGRAPHIC INFORMATION SYSTEM BASED NONPOINT POLLUTION MODELING1

ABSTRACT: The reauthorization of the Clean Water Act reemphasizes the need for regional scale monitoring and management of nonpoint pollution loads. The magnitude of the task will require that local governments and their consultants integrate information systems and modeling if they are to manage the massive data sets and conduct the array of simulations that will be needed to support the decision making processes. Interfacing geographic information systems (GIS) and nonpoint pollution modeling is a logical approach. The objective of the present study was to use the 37,000-acre area defined by the Kensington Quadrangle sheet in Montgomery County, Maryland, to show that GIS-supported nonpoint pollution modeling is practical and economically attractive. The purpose of the GIS is to estimate the spatial distribution of nonpoint nitrogen, phosphorous, zinc, lead, BOD, and sediment using a model developed by the Northern Virginia Planning District Commission. The system allows the user to change land uses in subareas to simulate the consequences of additional development or alternate management strategies. The tests show that in-house development of this type of special purpose GIS is a practical alternative to vendor supplied systems and that the required databases can be developed quite reasonably.     

Human behavior incorporation into ecological computer simulations

The responses of ecological computer simulations are significantly changed by the inclusion of human behavior patterns. Two computer simulations illustrate this principle for internal and external decision making. The Northwest Educational Trawler Simulation (NETS) models the interaction between fish populations, fishing effort, markets, and a fishing community. This simulation includes an internal decision making submodel for changing fishing effort based on observed behaviors of fishermen. NOGERO, a simulation of a mythical coastal fishing culture, uses external decision making where simulation users act as stewards. The patterns of model response vary depending on the attitudes and goals of decision makers. This shows how human behavior interacts with ecosystem dynamics to produce a variety of results.     

FACTORS INVOLVED IN EVALUATING GROUND WATER IMPACTS OF DEEP COAL MINE DRAINAGE1

ABSTRACT: The determination of probable ground water impacts of proposed deep coal mining is required as part of permit applications. Impact prediction generally involves well production test analysis and modeling of ground water systems associated with coal seams. Well production tests are often complicated due to the relatively low permeabilities of sandstones and shales of ground water systems. The effects of the release of water stored within finite diameter production wells must be considered. Well storage capacity appreciably affects early well production test time drawdown or time recovery data. Low pumping rates, limited cones of depression, and length of required pumping periods ate important well production test design factors. Coal seam ground water system models are usually multilayered and leaky artesian. Mine drafts partially penetrate the ground water system. Simulation of coal mine drainage often involves the horizontal permeability and storage coefficient of the coal seam zone, vertical permeabilities of sandstones and shales (aquitard) above and below the coal seam zone, and the hydrologic properties of the source bed above the aqultard overlying the coal seam zone. Ground water level declines in both the coal seam zone and source bed near land surface are necessary factors in impact analysis. An example of evaluation studies in southwest Indiana will illustrate factors involved in deep coal mine drainage modeling efforts.