A Time-Based Framework for Evaluating Hydrologic Routing Methodologies Using Wavelet Transform
نویسندگان
چکیده
In this study we explore a method which provides an insight into the effectiveness of various hydrologic models’ routing components based on their ability to accurately represent flood peak times and shapes. The method is based on using Cross-Wavelet Transforms to estimate the phase (time) difference between the time series of the observed and the simulated discharges. In this article we evaluate two routing components, the Routing Application for Parallel Computation of Discharge (RAPID), which is based on the simplified Muskingum routing method, and the routing component of the nonlinear Hillslope-Link hydrologic Model (HLM) produced in the Iowa Flood Center (IFC). Both routing components are driven by the same source of runoff and used the same channel network to ensure that the discrepancies between the simulated stream discharges are due to channel routing alone. We also explore the suitability of different wavelet shapes for our application, and how the difference in wavelet shape can affect our evaluation results. Unlike the conventional statistical skill scores used to evaluate model performance (e.g. Root Mean Squared Error, correlation coefficient, and Nash Sutcliff efficiency index), which give an estimate of the overall hydrograph performance, our method conveniently provides time-localized information with higher resolution at peak location. We perform our evaluation at multiple stream gauge locations, covering a wide range of scales (700 to 16,862 km), located in the eastern part of the state of Iowa. Our results show that the proposed wavelet method is effective in evaluating the performance of the routing components in simulating peak times across spatial scales. Generally, the non-linear routing method employed in the HLM outperformed the Muskingum based method employed in RAPID. In addition, our results suggest that the Paul wavelet is more effective in detecting and separating individual peaks than the Morlet wavelet, which in turn leads to a more accurate evaluation of the routing components. How to cite this paper: ElSaadani, M. and Krajewski, W.F. (2017) A Time-Based Framework for Evaluating Hydrologic Routing Methodologies Using Wavelet Transform. Journal of Water Resource and Protection, 9, 723-744. https://doi.org/10.4236/jwarp.2017.97048 Received: April 6, 2017 Accepted: June 6, 2017 Published: June 9, 2017 Copyright © 2017 by authors and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY 4.0). http://creativecommons.org/licenses/by/4.0/
منابع مشابه
The Urban Path Routing Adjustable Optimization by Means of Wavelet Transform and Multistage Genetic Algorithm
This paper introduces the optimization algorithm to improve search rate in urban path routing problems using viral infection and local search in urban environment. This algorithm operates based on two different approaches including wavelet transform and genetic algorithm. The variables proposed by driver such as degree of difficulty and difficulty traffic are of the essence in this technique. W...
متن کاملThe Effect of Rainfall Parameters on Runoff Using Wavelet Coherence Measure
In this research wavelet coherence measure is implemented for evaluating the relations and effect of rainfall parameters over many years on runoff fluctuations that is for testing proposed linkages between two time series. In this way, monthly Hydro climatological as 3 rainfall stations, one runoff in the outlet of Ardabil plain were used. The results illustrate that 8-12 and 8-16 month modes o...
متن کاملImage Retrieval Using Dynamic Weighting of Compressed High Level Features Framework with LER Matrix
In this article, a fabulous method for database retrieval is proposed. The multi-resolution modified wavelet transform for each of image is computed and the standard deviation and average are utilized as the textural features. Then, the proposed modified bit-based color histogram and edge detectors were utilized to define the high level features. A feedback-based dynamic weighting of shap...
متن کاملTexture Classification of Diffused Liver Diseases Using Wavelet Transforms
Introduction: A major problem facing the patients with chronic liver diseases is the diagnostic procedure. The conventional diagnostic method depends mainly on needle biopsy which is an invasive method. There are some approaches to develop a reliable noninvasive method of evaluating histological changes in sonograms. The main characteristic used to distinguish between the normal...
متن کاملA combined Wavelet- Artificial Neural Network model and its application to the prediction of groundwater level fluctuations
Accurate groundwater level modeling and forecasting contribute to civil projects, land use, citys planning and water resources management. Combined Wavelet-Artificial Neural Network (WANN) model has been widely used in recent years to forecast hydrological and hydrogeological phenomena. This study investigates the sensitivity of the pre-processing to the wavelet type and decomposition level in ...
متن کامل