POTENTIAL EFFECTS OF CLIMATE CHANGE ON GROUND WATER IN LANSING,MICHIGAN1

ABSTRACT: Computer simulations involving general circulation models, a hydrologic modeling system, and a ground water flow model indicate potential impacts of selected climate change projections on ground water levels in the Lansing, Michigan, area. General circulation models developed by the Canadian Climate Centre and the Hadley Centre generated meteorology estimates for 1961 through 1990 (as a reference condition) and for the 20 years centered on 2030 (as a changed climate condition). Using these meteorology estimates, the Great Lakes Environmental Research Laboratory's hydrologic modeling system produced corresponding period streamflow simulations. Ground water recharge was estimated from the streamflow simulations and from variables derived from the general circulation models. The U.S. Geological Survey developed a numerical ground water flow model of the Saginaw and glacial aquifers in the Tri‐County region surrounding Lansing, Michigan. Model simulations, using the ground water recharge estimates, indicate changes in ground water levels. Within the Lansing area, simulated ground water levels in the Saginaw aquifer declined under the Canadian predictions and increased under the Hadley.     

A Regional‐Scale Habitat Suitability Model to Assess the Effects of Flow Reduction on Fish Assemblages in Michigan Streams1

Zorn, Troy G., Paul W. Seelbach, and Edward S. Rutherford, 2012. A Regional‐Scale Habitat Suitability Model to Assess the Effects of Flow Reduction on Fish Assemblages in Michigan Streams. Journal of the American Water Resources Association (JAWRA) 48(5): 871‐895. DOI: 10.1111/j.1752‐1688.2012.00656.x Abstract: In response to concerns over increased use and potential diversion of Michigan’s freshwater resources, and the resulting state legislative mandate, an advisory council created an integrated assessment model to determine the potential for water withdrawals to cause an adverse resource impact to fish assemblages in Michigan’s streams. As part of this effort, we developed a model to predict how fish assemblages characteristic of different stream types would change in response to decreased stream base flows. We describe model development and use in this case study. The model uses habitat suitability information (i.e., catchment size, base‐flow yield, and July mean water temperature) for over 40 fish species to predict assemblage structure in an individual river segment under a range of base‐flow reductions. By synthesizing model runs for individual fish species at representative segments for each of Michigan’s 11 ecological stream types, we developed curves describing how typical fish assemblages in each type respond to flow reduction. Each stream type‐specific, fish response curve was used to identify streamflow reduction levels resulting in adverse resource impacts to characteristic fish populations, the regulatory standard. Used together with a statewide map of stream types, our model provided a spatially comprehensive framework for evaluating impacts of flow withdrawals on biotic communities across a diverse regional landscape.     

EVALUATING POTENTIAL ENVIRONMENTAL IMPACT OF INSECTICIDE APPLICATIONS IN A BOLL WEEVIL ERADICATION PROGRAM1

ABSTRACT: Concerns have been expressed about the potential insecticide contamination of regional water resources from a boll weevil eradication program in Oklahoma. A mathematical model and geographic information system techniques were utilized to evaluate the potential of insecticide leaching and runoff from a major proposed program area in the state. Different but equally likely weather patterns were generated, and potential insecticide losses associated with each pattern were predicted. Soil types and their locations within cotton areas were identified, and potential chemical losses from each soil were delineated. Model simulations indicated that azinphos-methyl and diflubenzuron could leach from some porous soils and that all insecticides suggested for use in the program could be lost to runoff. The predicted chemical movements with runoff were significantly higher on irrigated land than from non-irrigated land. Malathion demonstrated no leaching and low potential of runoff losses among the insecticides evaluated.     

DEVELOPMENT OF A BACTERIAL TRANSPORT MODEL FOR COARSE SOILS1

ABSTRACT: A bacterial transport model, developed to analyze bacterial translocation in coarse-grained soils, is presented. The complex governing equation is presented first, followed by analyses of each of the major processes influencing bacterial transport. These analyses suggest simplification of the governing equation is feasible when input data on specific processes are limited or unavailable. Model parameters, including bacterial die-off, bacterial distribution, input bacterial concentration, and saturated hydraulic conductivity, were randomly generated using a procedure known to produce either a normal or log-normal distribution of random numbers. Monte Carlo simulations were completed, and the resulting output was used to generate cumulative frequency distributions showing the probability of bacterial transport beyond various soil depths. Results from these simulations indicate that bacteria have a high probability of traveling through coarse-grained soils when low clay content and soil water temperatures limit bacterial retention and die-off.     

DEVELOPMENT AND VERIFICATION OF A WATER BALANCE MODEL FOR SUBSURFACE DRAINAGE DESIGN1

ABSTRACT: A water balance model was developed to predict daily water table depths in some corn fields with or without subsurface drainage systems, using pertinent soil and water properties and weather data. The model outputs were compared with the recorded data of observed water table depths. Some statistical parameters such as the mean, standard deviation, the coefficient of correlation, the sum of the squares of deviations, and a nonparametric statistical test were used to study the extent of agreement between the observed and the predicted water table depths. No significant difference was found between the distributions of the observed and the predicted water table depths at the 99% confidence level. The study was conducted on some sand and clay soils of the Ottawa-St. Lawrence Lowlands region in Canada where there is a cool, moist climate and poor natural drainage.     

ESTIMATING NONPOINT SOURCE POLLUTION LOADS WITH A GIS SCREENING MODEL1

ABSTRACT: The St. Johns River Water Management District (SJR-WMD) is using a Geographic Information System (GIS) screening model to estimate annual nonpoint source pollution loads to surface waters and determine nonpoint source pollution problem areas within the SJRWMD. The model is a significant improvement over current practice because it is contained entirely within the district's GIS software, resulting in greater flexibility and efficiency, and useful visualization capabilities. Model inputs consist of five spatial data layers, runoff coefficients, mean runoff concentrations, and stormwater treatment efficiencies. The spatial data layers are: existing land use, future land use, soils, rainfall, and hydrologic boundaries. These data layers are processed using the analytical capabilities of a cell-based GIS. Model output consists of seven spatial data layers: runoff, total nitrogen, total phosphorous, suspended solids, biochemical oxygen demand, lead, and zinc. Model output can be examined visually or summarized numerically by drainage basin. Results are reported for only one of the SJRWMD's ten major drainage basins, the lower St. Johns River basin. The model was created to serve a major planning effort at the SJRWMD; results are being actively used to address nonpoint source pollution problems.     

Operational Evapotranspiration Mapping Using Remote Sensing and Weather Datasets: A New Parameterization for the SSEB Approach

The increasing availability of multi‐scale remotely sensed data and global weather datasets is allowing the estimation of evapotranspiration (ET) at multiple scales. We present a simple but robust method that uses remotely sensed thermal data and model‐assimilated weather fields to produce ET for the contiguous United States (CONUS) at monthly and seasonal time scales. The method is based on the Simplified Surface Energy Balance (SSEB) model, which is now parameterized for operational applications, renamed as SSEBop. The innovative aspect of the SSEBop is that it uses predefined boundary conditions that are unique to each pixel for the “hot” and “cold” reference conditions. The SSEBop model was used for computing ET for 12 years (2000‐2011) using the MODIS and Global Data Assimilation System (GDAS) data streams. SSEBop ET results compared reasonably well with monthly eddy covariance ET data explaining 64% of the observed variability across diverse ecosystems in the CONUS during 2005. Twelve annual ET anomalies (2000‐2011) depicted the spatial extent and severity of the commonly known drought years in the CONUS. More research is required to improve the representation of the predefined boundary conditions in complex terrain at small spatial scales. SSEBop model was found to be a promising approach to conduct water use studies in the CONUS, with a similar opportunity in other parts of the world. The approach can also be applied with other thermal sensors such as Landsat.     

DEVELOPMENT OF A WATER SUPPLY PROTECTION MODEL IN A GIS1

ABSTRACT: As part of a larger model to identify lands suitable for acquisition, a water supply protection model was developed using the Southwest Florida Water Management District's GIS. Several hydrologic and hydrogeologic data layers were overlaid to develop maps showing ground-water supply suitability, protection areas for surface-water supply, protection areas for major public supply wells, susceptibility to ground-water contamination, and recharge to the Floridan aquifer. These intermediate layers were combined into a final map to prioritize protection areas for water supply.     

USING A GIS FOR ESTIMATING INPUT PARAMETERS IN URBAN STORMWATER QUALITY MODELING1

ABSTRACT: Geographic Information Systems (GIS) are being used increasingly as a method of preparing, analyzing, and displaying data for watershed analysis and modeling. Although GIS technology is a powerful tool for integrating and analyzing watershed characteristics, the initial preparation of the necessary database is often a time consuming and costly endeavor. This demonstration project assesses the viability of creating a cost-effective spatial database for urban stormwater modeling from existing digital and hard-copy data sources. The GIS was used to provide input parameters to the Source Loading and Management Model (SLANM), an empirical urban stormwater quality model. Land use characteristics, drainage boundaries, and soils information were geocoded and referenced to a base data layer consisting of transportation features. GIS overlay and data manipulation capabilities were utilized to preprocess the input data for the model. Model output was analyzed through postprocessing by GIS, and results were compared to a similar recent modeling study of the same watershed. The project, undertaken for a small urban watershed located in Plymouth, Minnesota, successfully demonstrates that the use of GIS in stormwater management can allow even small communities to reap the benefits of stormwater quality modeling.     

PRIORITIZING NONPOINT SOURCE PHOSPHORUS LOADING USING A GRASS-MODELING SYSTEM1

ABSTRACT: A UNIX-based windows application was developed to integrate a phosphorus transport model with the Geographic Resources Analysis Support System (GRASS). The system prioritizes potential phosphorus loading from fields or cells in a watershed and can evaluate the effects of alternate management practices on phosphorus yield. The model simulates phosphorus loading by using a daily mass balance on a unit-area basis and incorporates the effects from rainfall, topography, soil properties, fertilizer and animal waste application, and management. Model predictions include dissolved and sediment-bound phosphorus yield, runoff volume, and sediment yield. Within the integrated GRASS-modeling system, the user can obtain model input data, execute the model using various options, rank model input and out. put data, and display them as GRASS-based maps or data tables. All functions are menu driven, developed using C language and X-window tools to run on a SUN workstation platform. The system provides a powerful and efficient tool for prioritizing phosphorus loading from nonpoint sources.     

Groundwater Vulnerability,Brownfield Redevelopment and Land Use Planning

An understanding of groundwater vulnerability in urban watersheds is important for the prevention of both surface water and groundwater contamination and can therefore be a useful tool in brownfield redevelopment and land use planning. Although industrial activity in southeastern Michigan has historically been restricted to the urbanized sections of metropolitan Detroit, new industrial development is rapidly taking place in rural and undeveloped areas. Although environmentalists and urban planners agree that industrial site recycling in urban centres (a.k.a. brownfield redevelopment) is preferable to developing green areas, many older sites remain undeveloped due to real and perceived risks. Using a PC-based geographic information system, a conceptual model of solute transport in soil was developed to evaluate potential impacts to both groundwater and surface water quality resulting from industrial development. The model was used to create a map of groundwater vulnerability within the Rouge River watershed of southeastern Michigan. The map has been used to pin-point several rural and undeveloped areas where groundwater quality is threatened by proposed development. It has also clearly demonstrated that many older brownfield sites, within the City of Detroit, are located on materials that have a much lower vulnerability to groundwater contamination and may therefore be far less costly to redevelop than greenfield sites in undeveloped areas of the watershed.     

LARGE AREA HYDROLOGIC MODELING AND ASSESSMENT PART I: MODEL DEVELOPMENT1

ABSTRACT: A conceptual, continuous time model called SWAT (Soil and Water Assessment Tool) was developed to assist water resource managers in assessing the impact of management on water supplies and nonpoint source pollution in watersheds and large river basins. The model is currently being utilized in several large area projects by EPA, NOAA, NRCS and others to estimate the off-site impacts of climate and management on water use, non-point source loadings, and pesticide contamination. Model development, operation, limitations, and assumptions are discussed and components of the model are described. In Part II, a GIS input/output interface is presented along with model validation on three basins within the Upper Trinity basin in Texas.     

Simulated fate and transport of metolachlor in the unsaturated zone, Maryland, USA

An unsaturated-zone transport model was used to examine the transport and fate of metolachlor applied to an agricultural site in Maryland, USA. The study site was instrumented to collect data on soil-water content, soil-water potential, ground water levels, major ions, pesticides, and nutrients from the unsaturated zone during 2002-2004. The data set was enhanced with site-specific information describing weather, soils, and agricultural practices. The Root Zone Water Quality Model was used to simulate physical, chemical, and biological processes occurring in the unsaturated zone. Model calibration to bromide tracer concentrations indicated flow occurred through the soil matrix. Simulated recharge rates were within the measured range of values. The pesticide transport model was calibrated to the intensive data collection period (2002-2004), and the calibrated model was then used to simulate the period 1984 through 2004 to examine the impact of sustained agricultural management practices on the concentrations of metolachlor and its degradates at the study site. Simulation results indicated that metolachlor degrades rapidly in the root zone but that the degradates are transported to depth in measurable quantities. Simulations indicated that degradate transport is strongly related to the duration of sustained use of metolachlor and the extent of biodegradation.     

Potential Impacts of Climate Change on the Reliability of Water and Hydropower Supply from a Multipurpose Dam in South Korea

Future climate change is a source of growing concerns for the supply of energy and resources, and it may have significant impacts on industry and the economy. Major effects are likely to arise from changes to the freshwater resources system, due to the connection of energy generation to these water systems. Using future climate data downscaled by a stochastic weather generator, this study investigates the potential impacts of climate change on long‐term reservoir operations at the Chungju multipurpose dam in South Korea, specifically considering the reliability of the supply of water and hydropower. A reservoir model, Hydrologic Engineering Center‐Reservoir System Simulation (HEC‐ResSim), was used to simulate the ability of the dam to supply water and hydropower under different conditions. The hydrologic model Soil and Water Assessment Tool was used to determine the HEC‐ResSim boundary conditions, including daily dam inflow from the 6,642 km² watershed into the 2.75 Gm³ capacity reservoir. Projections of the future climate indicate that temperature and precipitation during 2070‐2099 (2080s) show an increase of +4.1°C and 19.4%, respectively, based on the baseline (1990‐2009). The results from the models suggest that, in the 2080s, the average annual water supply and hydropower production would change by +19.8 to +56.5% and by +33.9 to 92.3%, respectively. Model simulations suggest that under the new climatic conditions, the reliability of water and hydropower supply would be generally improved, as a consequence of increased dam inflow.     

STATEWIDE EMPIRICAL MODELING OF BACTERIAL CONTAMINATION OF SURFACE WATERS1

ABSTRACT: Bacterial contamination of surface waters is attributed to both urban and agricultural land use practices and is one of the most frequently cited reasons for failure to meet standards established under the Clean Water Act (CWA) (P.L. 92–500). Statewide modeling can be used to determine if bacterial contamination occurs predominantly in urban or agricultural settings. Such information is useful for directing future monitoring and allocating resources for protection and restoration activities. Logistic regression was used to model the likelihood of bacterial contamination using watershed factors for the state of Maryland. Watershed factors included land cover, soils, topography, hydrography, locations of septic systems, and animal feeding operations. Results indicated that bacterial contamination occurred predominantly in urban settings. Likelihood of bacterial contamination was highest for small watersheds with well drained and erodible soils and a high proportion of urban land adjacent to streams. The number of septic systems and animal feeding operations and the amount of agricultural land were not significant explanatory factors. The urban infrastructure tends to “connect” more of the watershed to the stream network through the creation of roads, storm sewers, and wastewater treatment plants. This may partly explain the relationship between urbanization and bacterial contamination found in this study.     

MODELING WATER UTILIZATION IN LARGE-SCALE IRRIGATION SYSTEMS: A QUALITATiVE RESPONSE APPROACH1

ABSTRACT: Given limited available data and the present state of knowledge on the social aspects of irrigation, there is a need to develop new quantitative methods to measure water management performance in large-scale systems. A qualitative response framework is adapted to formulate a dynamic logit model of weekly field water adequacy and quantify indirectly farmer water utilization. Model parameters are estimated in a weighted least-squares regression using four seasons of data from a Philippine canal system. Estimated coefficients and independent model forecasts indicate greater effective use of rainfall than irrigation in sustaining high levels of water adequacy during the rainy season. Irrigation utilization is two times higher in the dry season, while system location has a much smaller but still significant impact. Utilization rates for both rain and irrigation showed considerable responsiveness to the prevailing scarcity of water. The qualitative response approach is well suited to the aggregated data available for large-scale systems, and allows advances in modeling dynamic water management behavior. Formal evaluation of the model will require further empirical applications.     

A MATHEMATICAL MODEL OF SALMONID SPAWNING HABITAT1

ABSTRACT: A simulation model [Salmonid Spawning Analysis Model (SSAM)] was developed as a management tool to evaluate the relative impacts of stream sediment load and water temperature on salmonid egg survival. The model is useful for estimating acceptable sediment loads to spawning habitat that may result from upland development, such as logging and agriculture. Software in common use in the USA were adapted for use in gravel bedded rivers and linked to simulate water temperature (the USFWS Instream Water Temperature, SNTEMP model) and water and sediment routing (the USAE Scour and Deposition in Rivers and Reservoirs, HEC-6 model, version 3.2). These models drive the redd (spawning nest) model (the USDA-ABS Sediment Intrusion Dissolved Oxygen SIDO model) which simulates sediment intrusion and dissolved oxygen concentration in the redd environment. The SSAM model predictions of dissolved oxygen and water temperature compared favorably with field data from artificial redds containing hatchery chinook salmon eggs.     

Enhancing perspectives on lake impairments using satellite observations: A case study on High Rock Lake,North Carolina

Stakeholders developing water quality improvement plans for lakes and reservoirs are challenged by the sparsity of in-situ data and the uncertainty ingrained in management decisions. This study explores how satellite images can fill gaps in water quality databases and provide more holistic assessments of impairments. The study site is an impaired water body that is serving as a pilot for improving state-wide nutrient management planning processes. An existing in-situ database was used to calibrate semi-analytical models that relate satellite reflectance values to turbidity and total suspended solids (TSS). Landsat-7 images from 1999 to 2020 that overpass High Rock Lake, North Carolina were downloaded and processed, providing 42 turbidity and 39 TSS satellite and in-situ match-ups for model calibration and validation. Model r-squared values for the fitted turbidity and TSS models are 0.72 and 0.74, and the mean absolute errors are 14.6 NTU and 3.2 mg/L. The satellite estimates were compared to the in-situ data and simulated TSS values produced by a calibrated hydrologic-hydrodynamic model. The process-based model is considered less accurate than the satellite model based on statistical performance metrics. Comparisons between data sources are illustrated with time series plots, frequency curves, and aggregate decision metrics to highlight the dependence of lake impairment assessments on the spatial and temporal frequency of available data and model accuracy.     

Identifying sources of fecal contamination inexpensively with targeted sampling and bacterial source tracking

Most bacterial source tracking (BST) methods are too expensive for most communities to afford. We developed targeted sampling as a prelude to BST to reduce these costs. We combined targeted sampling with three inexpensive BST methods, Enterococcus speciation, detection of the esp gene, and fluorometry, to confirm the sources of fecal contamination to beaches on Georgia's Jekyll and Sea Islands during calm and stormy weather conditions. For Jekyll Island, the most likely source of contamination was bird feces because the percentage of Ent. faecalis was high (30%) and the esp gene was not detected. For the Sea Island beach during calm conditions, the most likely sources of fecal contamination were leaking sewer lines and wildlife feces. The leaking sewer lines were confirmed with fluorometry and detection of the esp gene. For the Sea Island beach during stormflow conditions, the most likely sources of fecal contamination were wildlife feces and runoff discharging from two county-maintained pipes. For the pipes, the most likely source of contamination was bird feces because the percentage of Ent. faecalis was high (30%) and the esp gene was not detected. Sediments were also a reservoir of fecal enterococci for both Jekyll and Sea Islands. Combining targeted sampling with two or more BST methods identified sources of fecal contamination quickly, easily, and inexpensively. This combination was the first time targeted sampling was conducted during stormy conditions, and the first time targeted sampling was combined with enterococcal speciation, detection of the esp gene, and fluorometry.     

SENSITIVITY ANALYSIS OF A DRAINAGE SIMULATION MODEL1

A sensitivity analysis of a computer model, simulating major water and nitrogen processes of a soil-water-plant-climatic system on an annual basis, was conducted to determine how the model reacts to the variations in selected hydrologic and nitrogen parameters. Two major output variables (namely, total subsurface drain volume and cumulative nitrate loss with subsurface drain water) were selected for the sensitivity analysis. Model sensitivity analysis shows that the model is most sensitive to hydrologic parameters. The model is very sensitive to variations in the initial water content in the soil profile.