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Next Generation Large Basin Runoff ModelsPrimary Investigator:Brent Lofgren - NOAA/GLERL Co-Investigators:Carlo DeMarchi - Case Western
Researve University* Executive Summary of RationaleContamination of water resources is an area of concern throughout the Great Lakes Basin. Water pollution results from both non-point sources (soil erosion, animal manure, and pesticides) and point sources (combined sewer outflows). Soil erosion and sediment buildup reduce soil quality and agricultural productivity, decrease the life of reservoirs and lakes, and increase flooding and costs for treating wastewater. As fertilizers, pesticides, and animal and human wastes accumulate, surface and groundwater levels of nitrogen, phosphorus, and toxic substances increase. Eutrophication, the excessive growth of plants in lakes, takes place because of nutrient overload. Plant growth, including harmful algal blooms, leads to oxygen depletion in receiving lakes. Concurrently, beaches may be closed due to viral, bacterial, and toxin delivery to affected sites. Prediction of ecological variables or consequences (such as beach closings) and effective management of pollution requires an estimation of point and non-point material transport through a watershed by hydrological processes. A model is necessary to study these hydrological processes. The Great Lakes Environmental Research Laboratory (GLERL), Western Michigan University, and the Cooperative Institute for Limnology and Ecosystems Research (CILER) are developing an integrated, spatially distributed, physically-based water quality model to evaluate agricultural non-point source pollution and point source pollution loadings at the watershed level. We are updating GLERL’s current model, the Distributed Large Basin Runoff Model (DLBRM), by adding transport capabilities for sediments, animal and human wastes, agricultural chemicals, and nutrients. We will expand the DLBRM from a daily to an hourly model. Proposed WorkThe expansion of the DLBRM is an applied, service-oriented research project started on January 1, 2005 and continuing tentatively through December 31, 2009. Figure 1. Maumee River resource sheds on January 1, 1950 for 1, 7, and 31 days’ of loading. In Figure 1, the brightest areas correspond to cells contributing about 0.015% of the total flow on January 1, 1950. The darkest areas are close to zero. Note several things about this figure. The southern and western ridgelines are prominent as is a line to the north that marks the boundary between Ohio and Michigan (line AB). This boundary reflects the differences in the two States’ definitions of some soil properties and so is an artifact of data standard differences. Point C identifies the mouth of the watershed. The first map in shows a little response from the previous day’s light rain near the mouth of the watershed. The second and third maps show most response along the edges of the watershed furthest from the mouth. Inspection of rainfall maps shows there is not much rainfall over the prior 4 days but there is a large amount 5 days prior in the southwest area. Also, spatially uniform rainfall fell over the entire watershed 7 days prior, 11-13 days prior, 15 days prior, 21-22 days prior, and 29 days prior. We can see the bright spot corresponding to the large peak 5 days earlier; the area closer to the mouth is relatively dark in the second and third maps because the only supplies there (seven or more days earlier) had already run off and are not part of the flow on this day. Note also that what happens prior to 7 days changes the picture very little (compare the last two maps). This is because the response of the watershed to supply is quick, on the order of 1 to 6 or 7 days, depending on location within the watershed. Most rain or snow falling more than 6 or 7 days ago have already left the watershed and do not form a part of the flow on this day. Current/Ongoing Recent GLERL Project Application of DLBRM:
GLERL is currently coordinating its DLBRM project with another project, River Discharge as a Predictor of Lake Erie Yellow Perch Recruitment. The purpose of this collaboration is to analyze Perch recruitment (both larval and 2-yr olds) as the Maumee River outflow fluctuates. There are two types of forecasts required by this project. The first involves determining climate change impacts on Perch recruitment. Results for the Maumee watershed (particularly outflow into Lake Erie) will be extracted and used to estimate Perch recruitment impacts. This is a short-term goal. The second type of forecast, a long-term goal, is to calculate daily probabilistic outlooks in real time of Perch recruitment up to two years from the present. GLERL’s Advanced Hydrologic Prediction System will formulate likely outlooks of Maumee River flow for spring months to estimate Perch recruitment impacts 2 years ahead. Actual or simulated flows will be obtained for the past 2 years to estimate Perch recruitment impacts up to a year in the future. The original watershed calibrated, the Maumee, will be recalibrated based on recent SF6 field surveys. Work continues to develop near real time resource shed mappings for the seventeen remaining target watersheds already calibrated [Kalamazoo, Sandusky, Saginaw, AuGres-Rifle, Kawkawlin-Pine, Pigeon-Wiscoggin, Tahquamenon, Grand (Ohio), Genesee, Grand (Michigan), Muskegon, Clinton, Huron, Raisin, Fox, St. Joseph, and Milwaukee] and for as many as possible of the twelve as-yet-uncalibrated watersheds. Develop resource sheds for materials other than water for eight of the already calibrated watersheds. Link the other target watersheds to lake circulation models. Possibly assess climate change scenario nutrient/microbe impacts for selected watersheds. The DLBRM is being expanded by adding material transport capabilities to it (conservative pollutant). This process involves adding first approximation transport models to the DLBRM and sub-calibrating sediment erosion and transport, nutrients and microbes, and water temperatures in various watersheds in support of GLERL’s project, Improving the DLBRM Capability to Forecast Hydrological and Water Quality Impacts of Land Use Changes, led by Dr. DeMarchi. We also began modifying the model from a daily time step to an hourly one and gathering information on Saginaw Bay watershed pollutants. Resource shed analysis will be used to aid in the NOAA/CSCOP/COP Saginaw Bay project: Adaptive Integrated Framework (AIF): a new methodology for managing impacts of multiple stressors in coastal ecosystems. Resource shed analysis will also by applied to various projects supported by the Center of Excellence for Great Lakes and Human Health and also a NOAA EcoFor project on Ensemble Forecasts of Hypoxia And Its Ecological Effects via an Integrated Assessment Framework. Timeline for proposed DLBRM projects in 2008: Calibrations
Surveys
Transport
Resource Sheds
Forecasting
Past Accomplishments 2006
2005
2004
Figure 2. LBRM Tank Cascade Schematic with Lateral Flow Additions Other GLERL Projects
Scientific RationalLarge-scale watershed models are necessary for estimating basin runoff to the Great Lakes and other basins for use in routing determinations, water resource decisions, hydrology studies, and long-term forecasting. Detailed watershed models cannot be used for large applications because they are designed for small-scale use and are costly for sizeable basins. GLERL developed the LBRM and applied it to 121 riverine watersheds draining into the Laurentian Great Lakes. The LBRM was used as a forecasting tool of hydrological variables such as lake levels at U.S. and Canadian agencies concerned with operational decisions, and at GLERL in their climate change assessments and management evaluations. To manage water resources, better representation and simulation of the Great Lakes water flow system is required. The DLBRM is better able to represent flow cells in the watershed, instead of the LBRM’s lumped-parameter definition of the entire watershed, as analyzed through its application to the Kalamazoo River. In the LBRM, flows were considered between adjacent cells’ surface storages while keeping the upper soil zone, lower soil zone, and groundwater zones independent. Surface zones connect between adjacent cells, but upper soil zones, lower soil zones, and groundwater zones do not. After LBRM application to the Kalamazoo River watershed, flow documented in soil and groundwater zones were judged unrealistic because water did not flow between these cells, except at the surface zone. Runoff estimates are best made with accurate data accounting for soil water storage and spatial variation. In order to account for the water flow between cells, the LBRM was modified to allow subsurface cell flows in the upper, lower, and groundwater soil zones. Surface and subsurface flows now have the ability to interact with each other and adjacent-cells’ surface/subsurface storages. Flows were added out of the subsurface storage and into the subsurface storages (from upstream cells). GLERL organized LBRM into a flow network by identifying the flow cascade and arranging cell computations accordingly. The model was applied to investigate alternatives and to demonstrate surface/subsurface interactions in a distributed, spatial context. The Large Basin Runoff Model was calibrated by calculating averages of 15 parameters that best minimized the standard error between observed and modeled daily watershed outflows. Each parameter was fixed to match selected observable watershed characteristics. Parameters included upper and lower soil zone permeability, upper soil zone water capacity, surface slope and Manning’s roughness coefficient. LBRM calibration updates were applied to the Maumee River watershed in Ohio which lacks a strong base flow, and also reapplied to the Kalamazoo River watershed in Michigan, characterized by a strong base flow. In both applications, the model calibration agreed with the observed water flow. The Kalamazoo River was found to have a surface flow dominated by groundwater storage, allowing delayed flow response to rainfall. However, the Maumee was found to lack any significant groundwater storage; its response to rainfall governed by its large surface network. Figure 3. Alternate Spatial Interpolations: a) Thiessen, b) inverse distance, c) inversed distance squared. Discretization is the mathematical process of transferring continuous models and equations into discrete counterparts. GLERL has discretized 18 watersheds. Databases were compiled for each watershed at 1 km2 resolution for elevation, slope, flow direction, soil texture, upper and lower soil thickness, water holding capacity, permeability, and land use/cover. The 18 watersheds included: Kalamazoo, Maumee, Sandusky, Saginaw, AuGres-Rifle, Kawkawlin-Pine, Pigeon-Wiscoggin, Tahquamenon, Grand (Erie), Genesee, Grand (Michigan), Muskegon, Clinton, Huron, Raisin, Fox, St. Joseph, and Milwaukee. Daily meteorology and flow records from 1948-2004 were assembled for each square kilometer of each watershed. After compiling and calibrating the data from 1950-1964 for all 18 watersheds and from 1999-2002 for six Michigan sub-watersheds, animations of water movement on 8 of the watersheds were produced. Databases were also acquired for animal manure, fertilizers, and pesticides in the Grand River and Kalamazoo watersheds (Lake Michigan), for the Maumee watershed (Lake Erie), and for the four Saginaw Bay watersheds (Lake Huron). Erosion and sedimentation mechanics, flow regulation points, combined sewer overflows, and sanitary sewer outflows for each of the watersheds were reviewed. GLERL replaced the analytical solution of the LBRM with a numerical one, creating the DLBRM. The DLBRM will be expanded by adding material transport capabilities (conservative pollutant) and by modifying from a daily to hourly model. Additional equations will be added to represent material transport. DLBRM will also gather information on Saginaw Bay watershed pollutants, serving as a water quality predictor. Also, model predictions on the Maumee will be compared with an experimental field study of the movement of SF6. Finally, the DLBRM is heavily relied upon by other projects including NOAA’s Center of Excellence for Great Lakes and Human Health and projects that are part of GLERL’s Lake Erie integrated effort. Governmental/Societal RelevanceThe DLBRM research coordinates with NOAA’s Center of Excellence for Great Lakes and Human Health, based at the Great Lakes Environmental Research Laboratory in Ann Arbor, Michigan. Understanding the relationship between human health and Great Lakes health is critical to the millions of people who rely on the Great Lakes for their livelihood and enjoyment. Using a multidisciplinary approach, the primary role of the center is to predict the formation of toxic algal blooms, beach closings, and water quality in the Great Lakes basin. The goal of the Center is to use GLERL’s broad scientific expertise to significantly reduce threats to human health through ecological forecasting, which uses scientific understanding and models of climate, weather, circulation patterns, hydrology, land use, and biology to predict the location and severity of toxins in the water and overall water quality conditions. Such information will allow Great Lakes managers and users to respond to changes and inform the public of potential health risks. The information will aid decision-makers in planning to minimize human health hazards. Small-scale time and space distributed-parameter runoff models also enable improved forecasts of Great Lakes basin riverine flooding, and improve existing US and Canadian Great Lakes water level outlooks for both Federal governments and National Weather Service River Forecast Centers. The proposed— model developments would also benefit climate change impact studies by increasing detail available to assess areas. This has potential in the upcoming International Joint Commission study of Lake Superior Regulation. The distributed-parameter runoff model will be of interest to ongoing Environment Canada Great Lakes—Ottawa River —St. Lawrence River distributed modeling and GLERL’s own Great Lakes Advanced Hydrologic Prediction System. The DLBRM addresses NOAA’s goal to “Protect, Restore, and Manage Use of Ocean and Coastal Resources through Ecosystem Management Approaches,” and “Protect Restore and Manage use of coastal, ocean and Great Lakes resources.” In particular it addresses the strategy to “Assess and Predict” as measured by the “increased number and accuracy of models to understand and predict the interactions of species and their environment.” This project is especially relevant to GLERL’s emphasis on Ecosystem Forecasting. The DLBRM will complement many other investigations. A two-dimensional runoff model defined at appropriate time scales could be used to estimate flow, sediment, and pollutant loadings to a lake. When coupled with lake circulation, biology, and chemical models, impacts of land-use change or basin developments could be assessed in terms of impacts on a lake environment to which the watershed drains. Relevance to Ecosystem Forecasting
ProductsSoftware Large Basin Runoff Model Software Data GLERL’s Advanced Hydrologic Prediction System (AHPS) Products: Links to plots for monthly values of inflow, outflow, total supply and mean lake level for each of the Great Lakes and Lake St. Clair. For each lake there is also a page (accessed by clicking on the lake name) with many other hydrology and meteorology variables. Publications Croley, T. E., II, and C. He, 2008. Spatially Distributed Watershed Model of Water and Materials Runoff. In Wetland and Water Resource Modeling and Assessment: A Watershed Perspective (W. Ji, Ed.), CRC Press, Taylor and Francis Group, Boca Raton, Florida, 2008. He, C. and T. E. Croley II, 2008. Estimating Nonpoint Source Pollution Loadings in the Great Lakes Watersheds. In Wetland and Water Resource Modeling and Assessment: A Watershed Perspective (W. Ji, Ed.), CRC Press, Taylor and Francis Group, Boca Raton, Florida, 2008. Hook, T. O., E. S. Rutherford, T. E. Croley II, D. M. Mason, and C. P. Madenjian, 2008. Annual variation in habitat-specific recruitment success: implications from an individual-based model of Lake Michigan alewife (Alosa Pseudoharengus). Canadian Journal of Fisheries and Aquatic Sciences, 65:1402-1412. Croley, T. E., II, D. F. Raikow, C. He, and J. F. Atkinson, 2008. Hydrological resource sheds. Journal of Hydrologic Engineering, ASCE, 13(9). He, C., and T. E. Croley II, 2007. Integration of GIS and Visualization for Distributed Watershed Modeling of the Great Lakes Watersheds. In Environmental Change and Rational Water Use (O. E. Scarpati and J. A. A Jones, Eds.) Orientación Gráfica Editora, 2007. CROLEY, T. E. II, and C. He. 2006. Watershed surface and subsurface spatial intraflows model. Journal of Hydraulic Engineering 11(1):12-20. Croley, T. E., II, 2005. Using Climate Predictions in Great Lakes Hydrologic Forecasts. In Climatic Variations, Climate Change, and Water Resources Management (J. Garbrecht and T. Piechota, Eds.), ASCE, Arlington, Virginia, pp. 166-187. Croley, T. E., II, and C. He, 2005. Distributed-parameter large basin runoff model I: model development. Journal of Hydrologic Engineering, 10(3):173-181. Croley, T. E., II, C. He, and D. H. Lee, 2005. Distributed-parameter large basin runoff model II: application. Journal of Hydrologic Engineering, 10(3):182-191. Croley, T. E., II, and C. He, 2005. Great Lakes Spatially Distributed Watershed Model of Water and Materials Runoff. Proceedings of the International Conference on Poyang Lake Wetland Ecological Environment, Jiangxi Normal University, Nanchang, Jiangxi, P.R. China, June 27, 2005, 12 pp. He, C., and T. E. Croley II, 2005. Estimating Nonpoint Source Pollution Loadings in the Great Lakes Watersheds. Proceedings of the International Conference on Poyang Lake Wetland Ecological Environment, Jiangxi Normal University, Nanchang, Jiangxi, P.R. China, June 27, 2005, 12 pp. Compact Disc. He, C. and T. E. Croley II, 2005. Integration of GIS and visualization for distributed water-shed modeling of the Great Lakes basin. Proceedings of The International Geographical Union Commission for Water Sustainability International Conference on Environmental Change and Rational Water Use, Buenos Aires, Argentina, August 29-September 1, 2005, (in review). He, C., and T. E. Croley II, 2004. Development of a 2-d large basin operational hydrologic model. Proceedings of the Workshop on Modeling and Control for Participatory Planning and Managing Water Systems, September 29-October 1, 2004, Venice, Italy, International Federation for Automatic Control, 12 pp. Compact Disc. Croley, T. E., II, 2004. Spatially Distributed Model of Interacting Surface and Groundwater Storages. Proceedings, World Water and Environmental Resources Congress 2004, June 27—July 1, 2004, Salt Lake City, Utah, Environmental Water Resources Institute, American Society of Civil Engineers, Washington DC, 10 pp., Compact Disc. Croley, T. E., II, 2002. Large basin runoff model. In Mathematical Models in Watershed Hydrology (V. Singh, D. Frevert, and S. Meyer, Eds.), Water Resources Publications, Littleton, Colorado, 717-770. Croley, T. E., II, and R. A. Assel, 2002. Great Lakes evaporation model sensitivities and errors. Proceedings, Second Federal Interagency Hydrologic Modeling Conference, Subcommittee on Hydrology of the Interagency Advisory Committee on Water Data, Las Vegas, 28 July-1 August, 12 pp., Compact Disc. Croley, T. E., II, and C. He, 2002. Great Lakes large basin runoff model. Proceedings, Second Federal Interagency Hydrologic Modeling Conference, Subcommittee on Hydrology of the Interagency Advisory Committee on Water Data, Las Vegas, 28 July-1 August, 12 pp., Compact Disc. He, C., and T. E. Croley II, 2002. A development framework for two-dimensional large basin operational hydrologic models. Proceedings, Second Federal Interagency Hydrologic Modeling Conference, Subcommittee on Hydrology of the Interagency Advisory Committee on Water Data, Las Vegas, 28 July-1 August, 12 pp., Compact Disc. Milestone ReportsApply GLERL's Large Basin Runoff Model in a distributed-parameter fashion for the Kalamazoo River Basin and calibrate and adjust the model to account for difference in soil characteristics *Link leads off GLERL's website |
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