Hydrodynamics in the Morganza Floodway and Atchafalaya Basin, report 3 : phase 3; a report for the US Army Corps of Engineers, MRG&P

The Morganza Floodway and the Atchafalaya Basin, located in Louisiana west of the Mississippi River, were evaluated using a two-dimensional Adaptive Hydraulics model. Prior to this study, Phase 1 and 2 model studies were performed that indicated that the existing floodway may not be able to pass the Project Design Flood discharge of 600,000 cubic feet per second due to levee overtopping. In this study, all elevations of exterior and interior levees were updated with current crest elevations. In addition, the Phase 3 effort evaluated the sensitivity of the floodway’s flow capacity to variations in tree/vegetation density conditions. These adjustments in roughness will improve the understanding of the role of land cover characteristics in the simulated water surfaces. This study also provides a number of inundation maps corresponding to certain flows through the Morganza Control Structure.

Nonstationary Bayesian Modeling of Extreme Flood Risk and Return Period Affected by Climate Variables for Xiangjiang River Basin, in South-Central China

The accurate design flood of hydraulic engineering is an important precondition to ensure the safety of residents, and the high precision estimation of flood frequency is a vital perquisite. The Xiangjiang River basin, which is the largest river in Hunan Province of China, is highly inclined to floods. This paper aims to investigate the annual maximum flood peak (AMFP) risk of Xiangjiang River basin under the climate context employing the Bayesian nonstationary time-varying moment models. Two climate covariates, i.e., the average June-July-August Artic Oscillation and sea level pressure in the Northwest Pacific Ocean, are selected and found to exhibit significant positive correlation with AMFP through a rigorous statistical analysis. The proposed models are tested with three cases, namely, stationary, linear-temporal and climate-based conditions. The results both indicate that the climate-informed model demonstrates the best performance as well as sufficiently explain the variability of extreme flood risk. The nonstationary return periods estimated by the expected number of exceedances method are larger than traditional ones built on the stationary assumption. In addition, the design flood could vary with the climate drivers which has great implication when applied in the context of climate change. This study suggests that nonstationary Bayesian modelling with climatic covariates could provide useful information for flood risk management.

Hydrological Analysis In Selecting Flood Discharge Method In Watershed Of Kelara River

For Engineers involved in planning and construction of water resources building, hydrology becomes very important data. In terms of planning stage in water resources especially waterworks, it is known that design flood discharge closed to field realistic conditions is often needed in order that a planned construction is able to control flood discharge. Several previous researches in choosing flood discharge selection method have diverse depending on observed watershed. One method in determining selected flood discharge by verification using Creager diagram, by comparing discharge calculation results of several Synthetic Unit Hydrograph (SUH) with infrastructure flood discharge (AWLR result) in observation point. This research aims to obtain the most suitable synthetic unit hydrograph and close to analysis result of measured discharge frequency, and Creager diagram in Kelara watershed (DAS). Based on the calculation of design flood discharge according to rainfall data using synthetic unit hydrograph of Nakayasu, ITB I, ITB II, and SCS (HEC-HMS) as well as the calculation of design flood discharge according to collected data, it is concluded that the synthetic unit hydrograph method closest to design flood discharge with measured discharge rate and Q1000 rate of Creager diagram is SCS. Flood discharge rate obtained according to HSS SCS method using HEC-HMS 4.8 application in period of 2 years is 658,40 m3/s, 25 years is 682,70 m3/s, 50 years is 787,00 m3/s, 100 years is 885,70 m3/det, and 1000 years is 1202,60 m3/s

Probable maximum precipitation for the catchment of Koyna dam

Estimates of Probable Maximum Precipitation (PMP) for different durations were made for the catchment above Koyna dam on the Koyna river. The catchment spans an area of 892 km2 and the PMP estimates were made for a range of durations of 1 to 3 days. The PMP estimates for Koyna dam were found to be 48, 87 and 117 cm by the physical method and 54, 89 and 124 cm by statistical method for 1, 2 and 3 day respectively. These estimates can be used to check the existing spillway design flood of Koyna dam.

Devastating rainstorm of June-2013 in Uttarakhand

The state of Uttarakhand is prone to floods and landslides due to its topographic location. The state of Uttarakhand and neighbouring states experienced heavy to very heavy rainfall during 15-18 June, 2013. The analysis of this rainstorm is important because it caused severe floods, landslides, loss of thousands of lives, property etc. During this period, many stations reported very heavy rainfall with a few extremely heavy rainfall (more than 24.5 cm in a day) in Uttarakhand and also in the neighbouring states of Himachal Pradesh, Haryana and Punjab. Most part of the state of Uttarakhand lies in the Greater Himalayan region. For safety from floods, one of the methods is to store water in hydraulic structures. For planning and designing of hydraulic structures, the estimation of design storm is the primary and the basic input for the computation of design flood. In the estimation of design storm, all the heavy rainstorms occurred over or near the area have to be analysed. In this paper, this rainstorm and other heavy rainstorms over a wide area has been analysed for the purpose of computation of Design storm estimates of hydraulic structures in that area. The rainstorm of June 2013 is compared with the earlier historical heaviest rainstorm of 28th to 30th September, 1924 at Lansdowne and it is observed that the rainstorm of June 2013 has contributed more rainfall than the rainstorm of September 1924 rainstorm for an area up to 5000 km2 for 1-day duration, while the DAD estimates for two day and three duration of rainstorm of September 1924 are higher than the rainstorm of June 2013 for area up to 20,000 km2.

Dam Break Analysis of Gembong Dam Using Zhong Xing HY21

Dams are a form of effort to conserve or protect water resources. The function of the Dam as a reservoir for water, irrigation, power generation, and flood control. However, in addition to its huge benefits, dam construction also can endanger the community’s safety, namely in the form of dam breaks. The main causes of dam break are overtopping and piping. So that analysis is needed related to dam break to minimize the impact. Based on the Zhong Xing HY21 software, the most severe impact of the break of the Gembong Dam was due to overtopping using the QInflow PMF design flood of 724.142 m3/s. It resulted in an inundation area of 54.682 km2 with a maximum inundation height of 5.129 m. As a result of the break of the Gembong Dam, 37 villages downstream of the Gembong Dam were flooded. There are 80.819 people affected by this risk. It is stated that all affected villages are at the 4th hazard classification level or very high hazard.

Integrated Engineering, Environmental, and Economical Modelling of Micro Hydro Plant (MHP) Production

The use of renewable energy has commonly concentrated on energy production through wind engines and solar panels. Nowadays, the micro-hydropower (MHP) plant has a great challenge as an important contributor to energy systems. Indonesia has the potential natural resources to develop that power plant, in the form of the river where is abundant throughout all provinces. The research aims to address solving issues regarding deficit energy by renewable energy production. The environmental and hydrological approaches were used to determine the location to obtain the optimal and proper utilization of MHP. The analysing from all modelling creates an economical assessment of MHP energy production. The result recommends MHP with the capacity of 2 x 4.0 MW and a total discharge of 14.30 m3/second whereas design flood discharge is 813.47 m3/second (Q100 year). The implementation of MHP is an effort to achieve independent energy in the region.

Design flood estimation for global river networks based on machine learning models

Design flood estimation is a fundamental task in hydrology. In this research, we propose a machine-learning-based approach to estimate design floods globally. This approach involves three stages: (i) estimating at-site flood frequency curves for global gauging stations using the Anderson–Darling test and a Bayesian Markov chain Monte Carlo (MCMC) method; (ii) clustering these stations into subgroups using a K-means model based on 12 globally available catchment descriptors; and (iii) developing a regression model in each subgroup for regional design flood estimation using the same descriptors. A total of 11 793 stations globally were selected for model development, and three widely used regression models were compared for design flood estimation. The results showed that (1) the proposed approach achieved the highest accuracy for design flood estimation when using all 12 descriptors for clustering; and the performance of the regression was improved by considering more descriptors during training and validation; (2) a support vector machine regression provided the highest prediction performance amongst all regression models tested, with a root mean square normalised error of 0.708 for 100-year return period flood estimation; (3) 100-year design floods in tropical, arid, temperate, cold and polar climate zones could be reliably estimated (i.e. <±25 % error), with relative mean bias (RBIAS) values of −0.199, −0.233, −0.169, 0.179 and −0.091 respectively; (4) the machine-learning-based approach developed in this paper showed considerable improvement over the index-flood-based method introduced by Smith et al. (2015, https://doi.org/10.1002/2014WR015814) for design flood estimation at global scales; and (5) the average RBIAS in estimation is less than 18 % for 10-, 20-, 50- and 100-year design floods. We conclude that the proposed approach is a valid method to estimate design floods anywhere on the global river network, improving our prediction of the flood hazard, especially in ungauged areas.