Download or read book The Effect of Radar rainfall Uncertainties on Simulation of Different Runoff Processes written by Mohamed Ahmed Fouad Habib and published by . This book was released on 2007 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Runoff Simulation Using Radar Rainfall Data written by John Charles Peters and published by . This book was released on 1996 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Empirically based Modeling of Radar rainfall Uncertainties written by Gabriele Villarini and published by . This book was released on 2008 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Radar Hydrology written by Yang Hong and published by CRC Press. This book was released on 2014-12-19 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Radar Hydrology: Principles, Models, and Applications provides graduate students, operational forecasters, and researchers with a theoretical framework and practical knowledge of radar precipitation estimation. The only text on the market solely devoted to radar hydrology, this comprehensive reference: Begins with a brief introduction to radar Focuses on the processing of radar data to arrive at accurate estimates of rainfall Addresses advanced radar sensing principles and applications Covers radar technologies for observing each component of the hydrologic cycle Examines state-of-the-art hydrologic models and their inputs, parameters, state variables, calibration procedures, and outputs Discusses contemporary approaches in data assimilation Concludes with methods, case studies, and prediction system design Includes downloadable MATLAB® content Flooding is the #1 weather-related natural disaster worldwide. Radar Hydrology: Principles, Models, and Applications aids in understanding the physical systems and detection tools, as well as designing prediction systems.
Download or read book Propagation of Radar Rainfall Uncertainty in Runoff Predictions written by and published by . This book was released on 2001 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: This final report documents the results obtained through the final phase of the research study. It consists of two papers that have been submitted for publication based on the research. The objective of this project is to quantitatively evaluate the worth of radar-rainfall estimates for physically based hydrologic modeling. These two papers contain valuable results. To summarize, our study has shown that the physical relationship between radar reflectivity and rainfall rate begins to disappear at a range of approximately 60 km from the radar site for radars with approximately 1 degree bean width. At farther ranges, radar returns are significantly affected by the horizontal and vertical gradients of cloud water. This result was verified through careful testing using a simulation methodology wherein convective rainfall is simulated using the Advanced Regional Prediction Model (ARPs), a radar simulator, and the two dimensional hydrologic model CASC2D. Techniques to correct runoff predictions for likely errors using a Bayesian approach are suggested.
Download or read book Propagation of Radar rainfall Uncertainty in Runoff Predictions written by Hatim Osman Sharif and published by . This book was released on 2001 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Evaluating the Performance of Process based and Machine Learning Models for Rainfall runoff Simulation with Application of Satellite and Radar Precipitation Products written by Amrit Bhusal and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hydrology Modeling using HEC-HMS (Hydrological Engineering Centre-Hydrologic Modeling System) is accepted globally for event-based or continuous simulation of the rainfall-runoff operation. Similarly, Machine learning is a fast-growing discipline that offers numerous alternatives suitable for hydrology research's high demands and limitations. Conventional and process-based models such as HEC-HMS are typically created at specific spatiotemporal scales and do not easily fit the diversified and complex input parameters. Therefore, in this research, the effectiveness of Random Forest, a machine learning model, was compared with HEC-HMS for the rainfall-runoff process. In addition, Point gauge observations have historically been the primary source of the necessary rainfall data for hydrologic models. However, point gauge observation does not provide accurate information on rainfall's spatial and temporal variability, which is vital for hydrological models. Therefore, this study also evaluates the performance of satellite and radar precipitation products for hydrological analysis. The results revealed that integrated Machine Learning and physical-based model could provide more confidence in rainfall-runoff and flood depth prediction. Similarly, the study revealed that radar data performance was superior to the gauging station's rainfall data for the hydrologic analysis in large watersheds. The discussions in this research will encourage researchers and system managers to improve current rainfall-runoff simulation models by application of Machine learning and radar rainfall data.
Download or read book Towards a Better Representation of Radar rainfall written by Bong Chul Seo and published by . This book was released on 2010 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: Radar-rainfall uncertainty quantification has been recognized as an intricate problem due to the complexity of the multi-dimensional error structure, which is also associated with space and time scale. The error structure is usually characterized by two moments of the error distribution: bias and error variance. Despite numerous efforts to investigate radar-rainfall uncertainties, many questions remain unanswered. This dissertation uses two statistical descriptions (mean and variance) of the error distribution to highlight and describe some of the remaining gaps in representing radar-rainfall uncertainties. The four central issues addressed in this dissertation include: 1. Investigation of radar relative bias caused by radar calibration. 2. Statistical modeling of range-dependent error arising from the radar beam geometry structure. 3. Scale-dependent variability of radar-rainfall and rain gauge error covariance. 4. Scale-dependence of radar-rainfall error variance. The first two issues describe systematic features of main error sources of radar-rainfall. The other two are associated with quantifying radar error variance using the error variance separation (EVS) method, which considers the spatial sampling mismatch between radar and rain gauge data. This study captures the main systematic features (systematic bias arising from radar calibration and range-dependent errors) of radar measurements without using ground reference data and the error variance structure with respect to the spatio-temporal transformation of the measurements for further applications to hydrologic fields. Such consideration of radar-rainfall uncertainties represented by error mean and variance can enhance the characterization of the uncertainty structure and yield a better understanding of the physical process of precipitation.
Download or read book A Kinematic Distributed Watershed Rainfall runoff Model written by Brian Edward Skahill and published by . This book was released on 2000 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Runoff Simulation Using Radar Rainfall Data written by John Charles Peters and published by . This book was released on 1996 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Effects of Changes to Rainfall Estimates Due to Climate Change on Runoff written by Binta Coleman and published by . This book was released on 2013 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent studies show that climate change is occurring and may lead to significant changes in the environment. These changes may directly affect weather patterns and the intensities of storms experienced in California. With the State being heavily dependent on its flood control system, climate change's effects on weather may increase risks of flooding. The State of California's Department of Water Resources (DWR) has begun to focus on the potential increase in risks of flooding due to climate change and increasing the sustainability of the State's flood control systems. The purpose of this study was to examine the effects of increased rainfall on peak runoff magnitudes on the Ulatis Creek Watershed located in California's Central Valley. Analysis was completed using estimated changes in precipitation developed by Das et al. (2011) and a rainfall-runoff model developed for the Central Valley Hydrology Study (CVHS) by the United States Army Corps of Engineers (USACE). Das et al. (2011) used downscaled general circulation models (GCMs) to develop estimates to changes in precipitation. Rainfall runoff modeling was completed using the Hydrologic Modeling System developed by the USACE's Hydrologic Engineering Center (HEC-HMS). Results of this study show that increased precipitation resulted in increased runoff peaks. Using the maximum precipitation estimates of an increase of 10.7 percent in early century epoch, and 3.0 percent in the late century, the resulting runoff increased approximately 13.5 percent and 3.7 percent respectively. Reduced precipitation estimates of -0.5 percent in the early century and -10.1 percent in late century estimates, yielded reduction in flow magnitudes of -0.64 and -12.5 percent, respectively. Further analysis would be needed in order to accurately predict the effects of climate change on peak runoff. With many uncertainties in climate change estimations and modeling assumptions, it is difficult for law makers to develop approaches to planning for future flood risks.
Download or read book Simulation of Rainfall runoff Processes Using Kinetic Wave and GIS Techniques written by Scott M. Ojiri and published by . This book was released on 1995 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Some Uncertainties in the Multiparameter Radar Measurement of Rainfall written by V. Chandrasekar and published by . This book was released on 1987 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Effect of Range on the Radar Measurement of Rainfall written by David Tees and published by . This book was released on 1989 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Mathematical Simulation of the Rainfall runoff Processes written by Frederick Charles Bell and published by . This book was released on 1965 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Evaluating Satellite and Radar Based Precipitation Data for Rainfall runoff Simulation written by Abhiru Aryal and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Climate change and urbanization causes the increasing challenges of flooding in urban watersheds. Even the rivers identified as non-vulnerable are causing catastrophic damage due to heavy flooding. So, several satellite and radar-based precipitation data are considered to study the watersheds with no gauge station or need recent precipitation data. Weather Radar (NEXRAD)arch, the accuracy of satellite-based precipitation data, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Climate Data Record (PERSIANN-CDR), and radar-based precipitation data, Next Generation Weather Radar (NEXRAD), is evaluated in rainfall-runoff simulation considering Hydrological Engineering Centre-Hydrologic Modeling System (HEC-HMS) and Personal Computer Storm Water Management Model (PCSWMM), respectively. The primary research proposes a framework for modeling the rainfall-runoff process using PERSIANN-CDR and a floodplain map in an ungauged urban watershed. The one-dimensional Hydrologic Engineering Centre-River Analysis System (HEC-RAS) model generates a flood inundation map for the pertinent flooding occurrences from the acquired peak hydrograph, providing a quantifiable display of the inundation extent percentage. The second research uses the PCSWMMs to show the extent of flooding. It also employs the compromise programming method (CPM) to rank the most critical sub-catchments based on three parameters: slope, surface area, and impervious area. Three low-impact development (LID) strategies over the watershed determine the best flood management option. Therefore, the overall study presents a comprehensive framework for flood management in urban watersheds that integrates satellite precipitation data, hydrologic modeling, and LID strategies. The framework can provide an accurate flood-prone zone and help prioritize critical sub-catchments for flood management options. The study proposes using HEC-HMS and PCSWMM models to simulate and analyze interactions between rainfall, runoff, and the extent of the flood zone. Furthermore, LID can be applied to reduce flooding in urban watersheds. Overall, the framework can be helpful for policymakers and system managers to build the watershed's resilience during catastrophic flooding events caused by climate change and urbanization.
Download or read book Risk Reliability Uncertainty and Robustness of Water Resource Systems written by Janos J. Bogardi and published by Cambridge University Press. This book was released on 2002-01-28 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: 35 leading multi-disciplinary scientists with international reputations provide reviews of topical areas of research on uncertainty and reliability related aspects of water resource systems. The volume will be valuable for graduate students, scientists, consultants, administrators, and practising hydrologists and water managers.
