A review of methods to account for impacts of non-stationary climate data on extreme rainfalls for design rainfall estimation in South Africa

Frequency analysis of extreme rainfall and flood events are used to determine design rainfalls and design floods which are needed to design hydraulic structures such as dams, spillways and culverts. Standard methods for frequency analysis of extreme events are based on the assumption of a stationary climate. However, this assumption in rainfall and flood frequency analysis is being challenged with growing evidence of climate change. As a consequence of a changing climate, the frequency and magnitude of extreme rainfall events are reported to have increased in parts of South Africa, and these and other changes in extreme rainfall occurrences are expected to continue into the future. The possible non-stationarity in climate resulting in changes in rainfall may impact on the accuracy of the estimation of extreme rainfall quantities and design rainfall estimations. This may have significant consequences for the design of new hydraulic infrastructure, as well as for the rehabilitation of existing infrastructure. Hence, methods that account for non-stationary data, such as caused by climate change, need to be developed. This may be achieved by using data from downscaled global circulation models in order to identify non-stationary climate variables which affect rainfall, and which can then be incorporated into extreme value analysis of a non-stationary data series.

Impact of Extreme Rainfall on Flood Hydrographs

Extreme rainfall is the main factor triggering flooding in various regions of the world including Indonesia. The increase in intensity and duration of current extreme rainfall is predicted as a result of global climate change. This paper aims to analyze the impact of extreme rainfall to the peak discharge of flood hydrographs at a watershed outlet in Palu, Sulawesi, Indonesia. Maximum daily rainfall data for the period 1990-1999 recorded at the Palu Meteorological Station, Central Sulawesi were selected using the Annual Maximum Series Method, and grouped into two types. Type I is the maximum daily rainfall data with extreme events and Type II is the maximum daily rainfall data without extreme events. Frequency analysis was applied to the two data groups using the best distribution method of: Normal, Normal Log, Pearson III Log, and Gumbel to obtain the design rainfall of each data group. In the next stage, the design rainfall transformation into a flood hydrograph is performed using the Nakayasu Synthetic Unit Hydrograph based on a number of return periods in one of the rivers flowing into Palu Bay, namely the Poboya River. The analysis results show that the design rainfall graphs with both extreme rainfall and without extreme rainfall are identical at the low return period and divergent at the high return period with a difference of up to 21.6% at the 1000-year return period. Correspondingly, extreme rainfall has a greater impact at the peak of the flood hydrograph with increasing return periods ranging from -1.28% to 26.81% over the entire return period.

Flood Hazard Assessment Under Climate Change Scenarios in Kelantan River Basin, Malaysia

Climate change can significantly alter the hydrological cycle and lead to severe hydrological disasters. This study aims to determine the impact of climate change on flood hazards in the Kelantan River Basin of Malaysia. The Climate Change Factor (CCF) is used to calculate 24-hour design rainfall with 50, 100 and 200-year return periods. A distributed hydrological model, Rainfall-Runoff-Inundation (RRI), is used to simulate flood inundation under current and future climate scenarios. The results indicate an increase in 50, 100, and 200 years, design rainfall, streamflow and flood hazard. The expected design rainfall and streamflow for 50, 100, and 200 years would increase by 36.6%, 37.9%, 42.7%, and 43.2%, 32.7%, 36.5%, respectively. Flood hazard is spatially variable in the Kelantan River Basin. Tanah Merah is the town that would face a significant increase in future flooding. The findings of this study can aid relevant agencies and government departments to comprehend the current and future flood hazard situation in the Kelantan River Basin. It would also assist them in formulating appropriate flood management strategies to mitigate future severe flood hazards.

Urban Flood Analysis in Ungauged Drainage Basin Using Short-Term and High-Resolution Remotely Sensed Rainfall Records

Analyzing flooding in urban areas is a great challenge due to the lack of long-term rainfall records. This study hereby seeks to propose a modeling framework for urban flood analysis in ungauged drainage basins. A platform called “RainyDay” combined with a nine-year record of hourly, 0.1° remotely sensed rainfall data are used to generate extreme rainfall events. These events are used as inputs to a hydrological model. The comprehensive characteristics of urban flooding are reflected through the projection pursuit method. We simulate runoff for different return periods for a typical urban drainage basin. The combination of RainyDay and short-record remotely sensed rainfall can reproduce recent observed rainfall frequencies, which are relatively close to the design rainfall calculated by the intensity-duration-frequency formula. More specifically, the design rainfall is closer at high (higher than 20-yr) return period or long duration (longer than 6 h). Contrasting with the flood-simulated results under different return periods, RainyDay-based estimates may underestimate the flood characteristics under low return period or short duration scenarios, but they can reflect the characteristics with increasing duration or return period. The proposed modeling framework provides an alternative way to estimate the ensemble spread of rainfall and flood estimates rather than a single estimate value.

ECODRAINAGE SYSTEM EVALUATION AND CONTROL OF FLOODS IN JOMBANG DISTRICT, EAST JAVA

Jombang sub-district is the most densely populated sub-district because it is located in the middle of Jombang district and is also the center of government. Because it is a densely populated area, resulting in many changes in land use, green land for absorption has turned into a watertight area. The results of the analysis from this aspect indicate that several channels in Jombang District are not able to accommodate the design flood discharge. The calculation of the height of rain design in this study used the Log Person type III method with a return period of 5 years, which resulted in the design rainfall of 157 mm. The results of the analysis show that there are 8 channels out of 74 that are unable to accommodate the design flood discharge. After planning the infiltration wells, a different number was obtained for each road. For Jalan Sentot Prawirodirjo, there are 8 infiltration wells with a reduction power of 51.62%.

Impact of climate change on floods in Pamplona (Spain) by using climate change projections and a distributed hydrological model

<p>Understanding how floods are expected to change is essential for decision making and flood risk management, as flood risks are expected to increase in the future. Several studies have analysed the impact of climate change on flood risks with rainfall-runoff models and climate projections as input data. Nevertheless, most of these studies involve large-scale river basins instead of focusing on smaller river basins or points of interest like urban areas. This study quantifies the expected changes in flood quantiles at the River Arga in the city of Pamplona (Spain) within the SAFERDAMS project (PID2019-107027RB-I00) funded by the Spanish Ministry of Science and Innovation. It uses climate change projections from 12 climate models of the EURO-CORDEX programme for two Representative Concentration Pathways - RCPs as input data of the RIBS distributed hydrological model (Garrote and Bras 1995 ab, JoH). The analysis considers seven return periods (2, 5, 10, 50, 100, 500 and 1000 years), two greenhouse gas emission scenarios (RCP4.5 and RCP8.5) and three time windows (2011-2040, 2041-2070 and 2070-2100).</p><p>First, the RIBS model has been calibrated with a set of objective functions to minimise the bias between simulations and observations recorded at a streamflow-gauging station located in the Arga River in Pamplona. The seven greatest flood events occurred in Pamplona in the last decade are considered. A long set of random combinations of model parameter values are used. The combination of parameter values that led to the smallest errors were selected.</p><p>Second, 24-h design rainfall storms with a time step of 1 h in the current scenario at a set of rainfall gauge stations in the Arga River catchment are obtained by using an extreme frequency analysis. Expected changes in daily rainfall quantiles in the Arga River catchment obtained by processing climate change projections are used (Garijo and Mediero 2019, Water). Current and future design rainfall storms were obtained for the seven return periods, two RCPs and three time windows. The input data in the RIBS model are provided in a raster format. Hence, design rainfall storms were transformed into spatial distributions of precipitation with the Thiessen polygons technique.</p><p>The findings show a decrease in design peak discharges for return periods smaller than 10 years and an increase for the 500- and 1000-year floods for both RCPs in the three time windows. However, 50- and 100-year return period flood quantiles are expected to increase especially in the 2041-2070 and 2071-2100 time windows only in the emission scenario RCP8.5. The emission scenario RCP8.5 always provides greater increases in flood quantiles than RCP4.5, except for the more frequent floods (2, 5 and 10 years) in the time window 2011-2040. The increases of design discharges are 10-30% higher in RCP8.5 than in RCP4.5 for the greatest return periods. Therefore, flood magnitude changes for the most extreme events seem to be related to the evolution of greenhouse gasses emissions, following the same behaviour of the RCPs: the greatest expected changes are in the 2040 for the RCP4.5 and in the 2100 for the RCP8.5.</p>