Download or read book Great Lakes Basins Runoff Modeling written by Thomas E Croley and published by . This book was released on 1982 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Great Lakes Basins Runoff Modeling written by Thomas E. Croley and published by . This book was released on 1982 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Great Lakes Basin Framework Study Surface water hydrology written by United States. Great Lakes Basin Commission and published by . This book was released on 1975 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Lake Superior Basin Runoff Modeling written by Thomas E. Croley and published by . This book was released on 1984 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Great Lakes Basin Framework Study written by United States. Great Lakes Basin Commission and published by . This book was released on 1974 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Great Lakes Basin Framework Study written by United States. Great Lakes Basin Commission and published by . This book was released on 1976 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Great Lakes Basin Framework Study Appendix 16 Drainage written by United States. Great Lakes Basin Commission and published by . This book was released on 1975 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Improved Hydrological Modeling of Great Lakes Basin Including Calibration Period Selection and Rain on snow Simulation written by Daniel Thomas Latimer Myers and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hydrological models relate landscape and climate characteristics with the water cycle, extreme events, and the availability of freshwater. However, the use of these models can be impaired by common pitfalls including the arbitrary choice of calibration periods and the omission of physical processes such as rain-on-snow melt, making the models less reliable when used where climate or landscape changes are occurring. This dissertation had three objectives: 1) Assess how much water balance simulations can be influenced by the choice of calibration and validation periods, 2) Analyze the influence of rain-on-snow melt of winter floods and summer hydrological droughts in North America's Great Lakes Basin using a modified Soil and Water Assessment Tool (SWAT) hydrological model, and 3) Investigate the influence of climate change on rain-on-snow melt and hydrology of the Great Lakes Basin.We found that the arbitrary selection of calibration periods can substantially influence simulations of water balance components such as snowmelt, surface runoff, and soil water storage. Thus, modelers using this split-sample approach should choose calibration and validation time periods selectively based on knowledge of changes in climate and hydrological characteristics and document the reasons for their choice. We also found that modifying SWAT to include rain-on-snow led to more extreme simulations of winter floods and summer hydrological droughts in the Great Lakes Basin and improved model performance. The unmodified SWAT could be underestimating hydrological extremes in areas where rain-on-snow events occur. Further, the hydrology of the Great Lakes Basin is expected to change throughout the 21st century, including a decrease in annual rain-on-snow melt amount due to reduction in snowpack. Parts of the basin with mean winter/spring air temperatures around freezing were most sensitive to changing rain-on-snow melt. As the threats of climate change and extreme hydrological events become more severe, it is increasingly important for hydrological modelers to best simulate physical processes such as rain-on-snow melt and avoid common pitfalls with the selection of calibration periods.
Download or read book Great Lakes Basin Framework Study Water supply municipal industrial and rural written by United States. Great Lakes Basin Commission and published by . This book was released on 1975 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Modelling the Great Lakes Hydrologic hydraulic System written by Eric David Loucks and published by . This book was released on 1989 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book PREDICTING THE IMPACTS OF CLIMATE CHANGE ON THE GREAT LAKES WATER LEVELS USING A FULLY COUPLED 3D REGIONAL MODELING SYSTEM written by and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract : The Great Lakes of North America are the largest surface freshwater system in the world and many ecosystems, industries, and coastal processes are sensitive to the changes in their water levels. The recent changes in the Great Lakes climate and water levels have particularly highlighted the importance of water level prediction. The water levels of the Great Lakes are primarily governed by the net basin supplies (NBS) of each lake which are the sum of over-lake precipitation and basin runoff minus lake evaporation. Recent studies have utilized Regional Climate Models (RCMs) with a fully coupled one-dimensional (1D) lake model to predict the future NBS, and the Coordinated Great Lakes Regulating and Routing Model (CGLRRM) has been used to predict the future water levels. However, multiple studies have emphasized the need for a three-dimensional (3D) lake model to accurately simulate the Great Lakes water budget. Therefore, in this study, we used the Great Lakes-Atmosphere Regional Model (GLARM) along with the Large Basin Runoff Model (LBRM) and CGLRRM to predict the changes in NBS and water levels by the mid- and late twenty-first century. GLARM is a 3D regional climate modeling system for the Great Lakes region that is fully coupled to a 3D hydrodynamic lake and ice model. This is the first study to use such an advanced model for water level prediction in the Great Lakes. We found that both annual over-lake precipitation and basin runoff are most likely to increase into the future. We also found that annual lake evaporation is most likely to decrease in Lake Superior but increase in all the other lakes. We posit that the decreases in evaporation are due to decreased wind speed over the lakes and decreased difference between saturated and actual specific humidity over the lakes. Our predicted changes in the three components of NBS would lead to mostly increased NBS and water levels in the future. The ensemble average of our predicted water level changes for Lake Superior, Michigan-Huron, and Erie are +0.14 m, +0.37 m, and +0.23 m by the mid-twenty-first century, respectively, and +0.47 m, +1.29 m, and +0.80 m by the late twenty-first century, respectively. However, due to the multiple sources of uncertainties associated with climate modeling and predictions, the water level predictions from this study should not be viewed as exact predictions. These predictions are unique to our model configuration and methodology. Other studies can easily predict different water level changes through the use of different models and methodologies. Therefore, more predictions from advanced modeling systems like GLARM are needed to generate a consensus on future water level changes in the Great Lakes.
Download or read book Lake Ontario Basin Runoff Modeling written by Thomas E. Croley and published by . This book was released on 1983 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Great Lakes Monthly Hydrologic Data written by Frank H. Quinn and published by . This book was released on 1983 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accurate values of monthly hydrologic data are required for simulation, forecasting, and water resource studies of the Great Lakes and their basins. This report summarizes the monthly hydrologic data currently used by the Great Lakes Environmental Research Laboratory in their hydrologic and water resources studies of the Great Lakes. The data consist of precipitation, runoff, evaporation, connecting channel flows, diversions, beginning-of-month lake levels, and rates of change in storage.
Download or read book Uses Abuses and Future of Great Lakes Modeling written by Great Lakes Science Advisory Board. Modeling Task Force and published by . This book was released on 1986 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Limnological Systems Analysis of the Great Lakes written by Hydroscience, inc and published by . This book was released on 1973 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Great Lakes Basin Framework Study Limnology of lakes and embayments written by United States. Great Lakes Basin Commission and published by . This book was released on 1976 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book An Improved Framework for Watershed Discretization and Model Calibration written by Amin Haghnegahdar and published by . This book was released on 2015 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large-scale (~103-106 km2) physically-based distributed hydrological models have been used increasingly, due to advances in computational capabilities and data availability, in a variety of water and environmental resources management, such as assessing human impacts on regional water budget. These models inevitably contain a large number of parameters used in simulation of various physical processes. Many of these parameters are not measurable or nearly impossible to measure. These parameters are typically estimated using model calibration, defined as adjusting the parameters so that model simulations can reproduce the observed data as close as possible. Due to the large number of model parameters, it is essential to use a formal automated calibration approach in distributed hydrological modelling. The St. Lawrence River Basin in North America contains the largest body of surface fresh water, the Great Lakes, and is of paramount importance for United States and Canada. The Lakes' water levels have huge impact on the society, ecosystem, and economy of North America. A proper hydrological modelling and basin-wide water budget for the Great Lakes Basin is essential for addressing some of the challenges associated with this valuable water resource, such as a persistent extreme low water levels in the lakes. Environment Canada applied its Modélisation Environnementale-Surface et Hydrologie (MESH) modelling system to the Great Lakes watershed in 2007. MESH is a coupled semi-distributed land surface-hydrological model intended for various water management purposes including improved operational streamflow forecasts. In that application, model parameters were only slightly adjusted during a brief manual calibration process. Therefore, MESH streamflow simulations were not satisfactory and there was a considerable need to improve its performance for proper evaluation of the MESH modelling system. Collaborative studies between the United States and Canada also highlighted the need for inclusion of the prediction uncertainty in modelling results, for more effective management of the Great Lakes system. One of the primary goals of this study is to build an enhanced well-calibrated MESH model over the Great Lakes Basin, particularly in the context of streamflow predictions in ungauged basins. This major contribution is achieved in two steps. First, the MESH performance in predicting streamflows is benchmarked through a rather extensive formal calibration, for the first time, in the Great Lakes Basin. It is observed that a global calibration strategy using multiple sub-basins substantially improved MESH streamflow predictions, confirming the essential role of a formal model calibration. At the next step, benchmark results are enhanced by further refining the calibration approach and adding uncertainty assessment to the MESH streamflow predictions. This enhancement was mainly achieved by modifying the calibration parameters and increasing the number of sub-basins used in calibration. A rigorous multi-criteria comparison between the two experiments confirmed that the MESH model performance is indeed improved using the revised calibration approach. The prediction uncertainty bands for the MESH streamflow predictions were also estimated in the new experiment. The most influential parameters in MESH were also identified to be soil and channel roughness parameters based on a local sensitivity test. One of the main challenges in hydrological distributed modelling is how to represent the existing spatial heterogeneity in nature. This task is normally performed via watershed discretization, defined as the process of subdividing the basin into manageable “hydrologically similar” computational units. The model performance, and how well it can be calibrated using a limited budget, largely depends on how a basin is discretized. Discretization decisions in hydrologic modelling studies are, however, often insufficiently assessed prior to model simulation and parameter. Few studies explicitly present an organized and objective methodology for assessing discretization schemes, particularly with respect to the streamflow predictions in ungauged basins. Another major goal of this research is to quantitatively assess watershed discretization schemes for distributed hydrological models, with various level of spatial data aggregation, in terms of their skill to predict flows in ungauged basins. The methodology was demonstrated using the MESH model as applied to the Nottawasaga river basin in Ontario, Canada. The schemes differed from a simple lumped scheme to more complex ones by adding spatial land cover and then spatial soil information. Results reveal that calibration budget is an important factor in model performance. In other words, when constrained by calibration budget, using a more complex scheme did not necessarily lead to improved performance in validation. The proposed methodology was also implemented using a shorter sub-period for calibration, aiming at substantial computational saving. This strategy is shown to be promising in producing consistent results and has the potential to increase computational efficiency of this comparison framework. The outcome of this very computationally intensive research, i.e., the well-calibrated MESH model for the Great Lakes and all the final parameter sets found, are now available to be used by other research groups trying to study various aspects of the Great Lakes System. In fact, the benchmark results are already used in the Great Lakes Runoff Intercomparison Project (GRIP). The proposed comparison framework can also be applied to any distributed hydrological model to evaluate alternative discretization schemes, and identify one that is preferred for a certain case.
