Selection of Calibration and Verification Data for the HEC-HMS Hydrologic Model PDF Download
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Author: Juraj M. Cunderlik
Publisher:
ISBN: 9780771426247
Category :
Languages : en
Pages : 29
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Book Description
Author: Juraj M. Cunderlik
Publisher:
ISBN: 9780771426247
Category :
Languages : en
Pages : 29
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Book Description
Author: William J. Charley
Publisher:
ISBN:
Category : HEC-HMS (Computer program)
Languages : en
Pages : 16
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Book Description
Author: Yong Tang
Publisher:
ISBN:
Category :
Languages : en
Pages : 225
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Book Description
Study 4 demonstrates a methodology that balances the computational constraints posed by global sensitivity analysis with the need to fully characterize the HL-RDHM's sensitivities. The model's sensitivities were assessed for long-term (annual and monthly) as well as short-term (events) forecasting periods. Overall, the results reveal that storage variations, spatial trends in forcing, cell-connectivity, and cell proximity to the gauged outlet are the four primary factors that control the HL-RDHM's behavior. This study suggests that operational forecasts would benefit from the joint use of a robust sensitivity analysis framework directly integrated into new calibration methodologies. Overall, this thesis advances the analysis, formulation, and solution of hydrologic model evaluation and identification problems using multiple performance objectives and state-of-the-art algorithms implemented to exploit high-performance computing.
Author: Artur Radecki-Pawlik
Publisher: MDPI
ISBN: 3039364510
Category : Technology & Engineering
Languages : en
Pages : 286
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Book Description
After publishing the famous “Fluvial Processes in Geomorphology” in the early 1960s, the work of Luna Leopold, Gordon Wolman, and John Miller became a key for opening the door to understanding rivers and streams. They first illustrated the problem to geomorphologists and geographers. Later, Chang, in his “Fluvial Processes in River Engineering”, provided a basis for engineers, showing this group of professionals how to deal with rivers and how to understand them. Since then, more informative studies have been published. Many of the authors started to combine fluvial geomorphology knowledge and river engineering needs, such as “Tools in Fluvial Geomorphology” by G. Mathias Kondolf and Hervé Piégay, or focused more on river engineering tasks, such as “Stream Restoration in Dynamic Fluvial Systems: Scientific Approaches” by Andrew Simon, Sean Bennett, and Janine Castro. Finally, Luna Leopold summarized river and stream morphologies in the beautiful “A view of the river”. It appears that we continue to explore this subject in the right direction. We better understand rivers and streams, and as engineers and fluvial geomorphologists, we can establish tools to help bring rivers alive. However, there is still a hunger for more scientific tools that we could use to further understand rivers and to support the development of healthy streams and rivers with high biodiversity in the present world, which has started to face water scarcity.
Author: Hongjing Wu
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
The successful performance of a hydrological model is usually challenged by the quality of the sensitivity analysis, calibration and uncertainty analysis carried out in the modeling exercise and subsequent simulation results. This is especially important under changing climatic conditions where there are more uncertainties associated with climate models and downscaling processes that increase the complexities of the hydrological modeling system. In response to these challenges and to improve the performance of the hydrological models under changing climatic conditions, this research proposed five new methods for supporting hydrological modeling. First, a design of experiment aided sensitivity analysis and parameterization (DOE-SAP) method was proposed to investigate the significant parameters and provide more reliable sensitivity analysis for improving parameterization during hydrological modeling. The better calibration results along with the advanced sensitivity analysis for significant parameters and their interactions were achieved in the case study. Second, a comprehensive uncertainty evaluation scheme was developed to evaluate three uncertainty analysis methods, the sequential uncertainty fitting version 2 (SUFI-2), generalized likelihood uncertainty estimation (GLUE) and Parameter solution (ParaSol) methods. The results showed that the SUFI-2 performed better than the other two methods based on calibration and uncertainty analysis results. The proposed evaluation scheme demonstrated that it is capable of selecting the most suitable uncertainty method for case studies. Third, a novel sequential multi-criteria based calibration and uncertainty analysis (SMC-CUA) method was proposed to improve the efficiency of calibration and uncertainty analysis and control the phenomenon of equifinality. The results showed that the SMC-CUA method was able to provide better uncertainty analysis results with high computational efficiency compared to the SUFI-2 and GLUE methods and control parameter uncertainty and the equifinality effect without sacrificing simulation performance. Fourth, an innovative response based statistical evaluation method (RESEM) was proposed for estimating the uncertainty propagated effects and providing long-term prediction for hydrological responses under changing climatic conditions. By using RESEM, the uncertainty propagated from statistical downscaling to hydrological modeling can be evaluated. Fifth, an integrated simulation-based evaluation system for uncertainty propagation analysis (ISES-UPA) was proposed for investigating the effects and contributions of different uncertainty components to the total propagated uncertainty from statistical downscaling. Using ISES-UPA, the uncertainty from statistical downscaling, uncertainty from hydrological modeling, and the total uncertainty from two uncertainty sources can be compared and quantified. The feasibility of all the methods has been tested using hypothetical and real-world case studies. The proposed methods can also be integrated as a hydrological modeling system to better support hydrological studies under changing climatic conditions. The results from the proposed integrated hydrological modeling system can be used as scientific references for decision makers to reduce the potential risk of damages caused by extreme events for long-term water resource management and planning.
Author: Matthew James Fleming
Publisher:
ISBN:
Category : Dale Hollow Lake (Tenn. and Ky.)
Languages : en
Pages : 186
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Book Description
Author: D. Michael Gee
Publisher:
ISBN:
Category : Calibration
Languages : en
Pages : 32
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Book Description
Author: Alexandre Daniel Remnek
Publisher:
ISBN:
Category :
Languages : en
Pages : 590
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Book Description
Author: Gary W. Brunner
Publisher:
ISBN:
Category : HEC-RAS (Computer program)
Languages : en
Pages : 16
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Book Description
Author: Mohammad Semnani
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
A new method for efficient calibration of complex hydrological models that combines Dynamically Dimensioned Search (DDS) global optimization algorithm with Global Sensitivity Analysis (GSA) methods is introduced. This approach, which is called sensitivity-informed DDS, utilizes sensitivity indices to increase the probability of perturbation for the most sensitive parameters, while giving low chance to least sensitive ones. This feature improves the efficiency and effectiveness of optimization by finding good quality solutions in a shorter time. Three different implementations of sensitivity-informed DDS are considered. The first approach is named as GSA↔DDS, in which GSA toolboxes (Morris or Sobol) are performed initially and throughout the optimization process to constantly update the sensitivity information. The second approach is called GSA→DDS. In this method, the GSA methods are only performed initially to include the results of GSA within optimization process. The final implementation is called VARS→DDS. In this method, to enhance the efficiency of sensitivity analysis and optimization, VARS toolbox is performed outside the optimization to provide the sensitivity information. The performances of GSA↔DDS, GSA→DDS and VARS→DDS are compared with original DDS by solving various optimization problems (test functions and model calibration case studies). According to the results, when calibrating complex hydrological models with enough computational budget, VARS→DDS is significantly more efficient and effective than original DDS. However, the results also show that GSA→DDS and GSA↔DDS methods do not substantially improve the convergence rate and the final best solution compared to DDS. Thus, VARS→DDS is the recommended approach for sensitivity-informed DDS in calibration of distributed and semi-distributed models, when enough computational resources are available.
