Simultaneous flood risk analysis and its future change among all the 109 class-A river basins in Japan using a large ensemble climate simulation database d4PDF

This study investigated simultaneous flood risk among all the 109 class-A river basins over Japan using the big data of (over 1000 years) annual maximum hourly flow simulated from a large ensemble climate simulation database for policy decision making for future climate change, and proposed a novel approach in its geospatial analysis by applying two informatics techniques: the association rule analysis and graph theory. Frequency analysis of the number of rivers with the annual maximum flow over the flow capacity in the same year (defined as simultaneous flooding here) indicated that simultaneous flood risk will increase in the future climate under 4-degree rise scenarios in Japan, whose increment is larger than the variation of sea surface temperature projections. As the result, the return period of simultaneous flooding in eight river basins (the same number as in a severe storm in western Japan, 2018, causing the second worst economic damage since 1962) is estimated at 400 years in the historical experiment, 25 years in the 4-degree rise experiment. The association rule and graph theory analyses for the big data of annual maximum flows in the future climate scenarios indicated that simultaneous flood occurrence is dominated by spatial distance at a national scale as well as by the spatial relation between mountainous ridges and typhoon courses at a regional scale. Large ensemble climate simulation data combined with the informatics technology is a powerful approach to simultaneous flood risk analysis

NRCS Curve Number Employed Hydrologic Homogeneous Regionalization in Regional Flood Frequency Analysis

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Catchment Scale Comparison on Lumped Representation for a Distributed Sediment Runoff Model

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Vulnerability Analysis of Regional Flood Hazard Based on MODIS Imagery and Demographic Data in the Huaihe River Basin, China

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Uncertainty assessment of water resources and long-term hydropower generation using a large ensemble of future climate projections for the Nam Ngum River in the Mekong Basin

[Study region] The Nam Ngum River Basin, the major tributary of the Mekong River, is located in the Laos PDR. [Study focus] This study aims to assess the sensitivity of Nam Ngum 1 reservoir operation to water resource uncertainty driven by a combination of climate change and upstream cascade dam development. [New hydrological insights for the region] Precipitation projections of the basin under a 4° increase scenario vary in the range of −9.6 % to +6.9 %, compared to the historical observed precipitation (present climate). The impact of climate change on hydropower resources was investigated. Based on the combined effect of climate change and upstream cascade dam development, the projected inflow of the Nam Ngum 1 reservoir at the full development stage will change from −16.0 % to +6.5 %, which results in a large range of annual energy production changes from −18.8 % to +2.8 % compared to the current condition (present climate and existing dam stage). Furthermore, water losses from the reservoir due to water discharge from the spillway for extreme floods and evaporation are expected to increase with increasing temperature, which will lead to a loss in energy production. Our study indicates that the operation of hydropower should be adapted to the effects of climate change. This information can be used by stakeholders to propose water resource management strategies

Complementary Information for Reducing Parameter Uncertainty in Distributed Rainfall-Runoff Modeling

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Hydrologic Precidtion of Climate Chante Impacts on Tone and Yodo River Basins

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Real-time optimization of a large-scale reservoir operation in Thailand using adaptive inflow prediction with medium-range ensemble precipitation forecasts

Study region: The Sirikit Dam in the Nan River Basin is located on a main tributary of the Chao Phraya River in Thailand. Study focus: This study investigates forecasting river flows and real-time optimization of dam release using a distributed hydrological model with ensemble weather forecasting for reservoir operations which provide hydropower and irrigation facilities in Thailand during a case study of the 2019 drought event. Medium-range ensemble precipitation forecasts were employed using a hydrological model to predict the real-time reservoir inflow. Real-time optimization of the water release strategy determined a week in advance with an effective initial condition for hydropower generation and irrigation was conducted with different scenarios using dynamic programming considering inflow predictions. New hydrological insights for the region: The medium-range ensemble precipitation forecast conducted by the European Centre for Medium Range Weather Forecasts was used to quantify precipitation for the study basin. The ensemble precipitation forecast with the hydrological model was employed for inflow prediction of the study basin which was located in a tropical climate with a distinct wet and dry season. The initial conditions of the hydrological model largely influenced the real-time inflow forecast. To determine the initial conditions of the model, the empirical data assimilation considering a drainage area factor was utilized and observed precipitation data were used for model input forcing data during the initial analysis period. This method improved the reservoir inflow prediction and real-time reservoir optimization using dynamic programming with considering ensemble forecasts provided more efficient operating decisions than employing historical data. The resulting information will be useful for water resource management, which may be adapted to other basins in the study region

A Numerical Method Combining the IADI Method with the Modified Picard Iteration Method for Solving Multi-Dimensional Saturated-Unsaturated Flow Equation

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Estimation of Intensity-Duration-Area-Frequency Curves Using Scaling Properties of Hourly Rainfall Data

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv