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19 pages, 4916 KiB  
Article
Using Data-Driven Prediction of Downstream 1D River Flow to Overcome the Challenges of Hydrologic River Modeling
by Jeremy Feinstein, Quentin Ploussard, Thomas Veselka and Eugene Yan
Water 2023, 15(21), 3843; https://doi.org/10.3390/w15213843 - 3 Nov 2023
Cited by 5 | Viewed by 2246
Abstract
Methods for downstream river flow prediction can be categorized into physics-based and empirical approaches. Although based on well-studied physical relationships, physics-based models rely on numerous hydrologic variables characteristic of the specific river system that can be costly to acquire. Moreover, simulation is often [...] Read more.
Methods for downstream river flow prediction can be categorized into physics-based and empirical approaches. Although based on well-studied physical relationships, physics-based models rely on numerous hydrologic variables characteristic of the specific river system that can be costly to acquire. Moreover, simulation is often computationally intensive. Conversely, empirical models require less information about the system being modeled and can capture a system’s interactions based on a smaller set of observed data. This article introduces two empirical methods to predict downstream hydraulic variables based on observed stream data: a linear programming (LP) model, and a convolutional neural network (CNN). We apply both empirical models within the Colorado River system to a site located on the Green River, downstream of the Yampa River confluence and Flaming Gorge Dam, and compare it to the physics-based model Streamflow Synthesis and Reservoir Regulation (SSARR) currently used by federal agencies. Results show that both proposed models significantly outperform the SSARR model. Moreover, the CNN model outperforms the LP model for hourly predictions whereas both perform similarly for daily predictions. Although less accurate than the CNN model at finer temporal resolution, the LP model is ideal for linear water scheduling tools. Full article
(This article belongs to the Section Hydrology)
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20 pages, 7251 KiB  
Article
Mega Flood Inundation Analysis and the Selection of Optimal Shelters
by Daegun Han, Deokhwan Kim, Kyunghun Kim, Won-Joon Wang, Jaewon Jung and Hung Soo Kim
Water 2022, 14(7), 1031; https://doi.org/10.3390/w14071031 - 24 Mar 2022
Cited by 5 | Viewed by 2899
Abstract
In recent decades, extreme storm events due to climate change have frequently occurred worldwide, a few of which have even occurred consecutively; we class such rainfall events as mega events. That is to say, if the inter-arrival time between rainfall events with a [...] Read more.
In recent decades, extreme storm events due to climate change have frequently occurred worldwide, a few of which have even occurred consecutively; we class such rainfall events as mega events. That is to say, if the inter-arrival time between rainfall events with a 100-year frequency is less than the IETD (Inter-Event Time Definition), the event can be considered a mega event. Therefore, the aim of this study was to implement flood inundation analysis using the hypothetical mega event from two consecutively occurring events of 100-year frequency, and select the optimal shelters using a developed method for minimizing casualties from floods. The Gyeongan stream basin, which is a tributary of the Namhan River in Korea, was selected as the study area. This study calculates mega flood discharge using the SSARR (Stream Synthesis and Reservoir Regulation) model, and conducts a flood inundation analysis of mega floods via the level pool method and the HEC-GeoRAS model. An inundation map was constructed, and the inundated area was classified into three zones and five administrative districts. Sixteen shelters were selected as candidates based on the criteria of the local government safety management plans and the Guidelines for Establishing the Disaster Relief Plan of 2013. To evaluate the candidates for evacuation in each district, we selected seven evaluation indicators from the shelter criteria of several countries, and calculated the weights of the indicators using the Analytic Hierarchy Process (AHP) method. As a result, four optimal shelters were selected in the study area. The results of the study can be used as the basic information for analyzing mega natural disaster events and inundation, and for establishing evacuation shelters, which are one of the non-structural flood protection measures. Full article
(This article belongs to the Special Issue The Impacts of Climate Change on Hydrologic Extremes)
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20 pages, 7058 KiB  
Article
Case Study: On Objective Functions for the Peak Flow Calibration and for the Representative Parameter Estimation of the Basin
by Jungwook Kim, Deokhwan Kim, Hongjun Joo, Huiseong Noh, Jongso Lee and Hung Soo Kim
Water 2018, 10(5), 614; https://doi.org/10.3390/w10050614 - 9 May 2018
Cited by 5 | Viewed by 4175
Abstract
The objective function is usually used for verification of the optimization process between observed and simulated flows for the parameter estimation of rainfall–runoff model. However, it does not focus on peak flow and on representative parameter for various rain storm events of the [...] Read more.
The objective function is usually used for verification of the optimization process between observed and simulated flows for the parameter estimation of rainfall–runoff model. However, it does not focus on peak flow and on representative parameter for various rain storm events of the basin, but it can estimate the optimal parameters by minimizing the overall error of observed and simulated flows. Therefore, the aim of this study is to suggest the objective functions that can fit peak flow in hydrograph and estimate the representative parameter of the basin for the events. The Streamflow Synthesis And Reservoir Regulation (SSARR) model was employed to perform flood runoff simulation for the Mihocheon stream basin in Geum River, Korea. Optimization was conducted using three calibration methods: genetic algorithm, pattern search, and the Shuffled Complex Evolution method developed at the University of Arizona (SCE-UA). Two objective functions of the Sum of Squared of Residual (SSR) and the Weighted Sum of Squared of Residual (WSSR) suggested in this study for peak flow optimization were applied. Since the parameters estimated using a single rain storm event do not represent the parameters for various rain storms in the basin, we used the representative objective function that can minimize the sum of objective functions of the events. Six rain storm events were used for the parameter estimation. Four events were used for the calibration and the other two for validation; then, the results by SSR and WSSR were compared. Flow runoff simulation was carried out based on the proposed objective functions, and the objective function of WSSR was found to be more useful than that of SSR in the simulation of peak flow runoff. Representative parameters that minimize the objective function for each of the four rain storm events were estimated. The calibrated observed and simulated flow runoff hydrographs obtained from applying the estimated representative parameters to two different rain storm events were better than those retrieved from parameters estimated using a single rain storm event. The results of this study demonstrated that WSSR is adequate in peak flow simulation, that is, the estimation of peak flood runoff. In addition, representative parameters can be applied to a flow runoff simulation for rain storm events that were not involved in parameter estimation. Full article
(This article belongs to the Section Hydrology)
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22 pages, 5096 KiB  
Article
Assessing the Coordinated Operation of Reservoirs and Weirs for Sustainable Water Management in the Geum River Basin under Climate Change
by Jung Min Ahn, Deuk Seok Yang, Kang Young Jung and Dong Seok Shin
Water 2018, 10(1), 30; https://doi.org/10.3390/w10010030 - 2 Jan 2018
Cited by 5 | Viewed by 4565
Abstract
In this study, an integrated system for the comprehensive analysis of climate change, runoff, reservoir operation, and power generation was developed. In order to apply reliable climate change scenarios to the Geum River Basin, we applied representative concentration pathway (RCP) scenarios adopted by [...] Read more.
In this study, an integrated system for the comprehensive analysis of climate change, runoff, reservoir operation, and power generation was developed. In order to apply reliable climate change scenarios to the Geum River Basin, we applied representative concentration pathway (RCP) scenarios adopted by the Intergovernmental Panel on Climate Change for its fifth assessment report in 2014 to the streamflow synthesis and reservoir regulation model at a regional scale with 1-km spatial resolution to analyze future runoff. This analyzed future runoff was applied to the Hydrologic Engineering Center—Reservoir System Simulation to analyze the hydrological behavior caused by reservoir operation through flow duration analysis at each of several important points. The objective was to provide initial data suitable for future basin management through an examination of power generation. Applying the RCP 4.5 and 8.5 scenarios showed that runoff would increase continuously compared with the past. However, in the RCP 8.5 scenario (where carbon reductions have not been achieved), runoff from flooding would be reduced considerably. It was found that power generation would be reduced compared with the past under the climate change scenarios, but additional power generation could be realized with the coordinated operation of reservoirs and weirs. These results suggest that, despite climate change, the risk to power generation could be reduced with the coordinated operation of reservoirs and weirs. Full article
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