Evaluation of Generalized Extreme (GEV), Log-Pearson Type 3 (LP3), Pearson Type 3(P3) and Gumbel (EV1) Distributions for Development of IDF Equations for Warri, Nigeria

The application of Gumbel (EVI) to the development of rainfall intensity– duration – frequency (IDF) curves has often been criticized on theoretical and empirical grounds as it may underestimate the largest extreme rainfall amounts. The consequences of underestimation are economic losses, property damages, and loss of life. Therefore, it is important that water resources engineering infrastructure be accurately design to avoid these consequences. This paper evaluates the performances of four probability distributions; GEV, EV1, LP3 and P3 using the annual maxima precipitation series of 26 years for Warri Metropolis obtained from Nigerian Meteorological Agency (NiMet). The strength and weakness of the four probability distributions were examined with the goodness of fit (GOF) module of Easyfit software which implemented Kolmogorov - Smirnov (KS) and Anderson - Darling (AD) tests at 5% significance level. The Easyfit software fitted the precipitation series data to the four probability distributions and ranked the four probability distributions across the fifteen rainfall durations. Results show that for both KS and AD tests, GEV distribution was found to be best-fit distribution and it was applied to the development of IDF curves in Warri Metropolis, Nigeria. Furthermore, the IDF values obtained were applied in the development of three-parameter IDF models for return periods of 10 - , 15 -, 20 -, 25 - , 50 -, and 100-years. The mean absolute error, Nash – Sutcliffe Efficiency (NSE) and Root Mean Square Error (RMSE) indices computed for the IDF models increase with increasing return periods. The IDF curves and models depicted the general attributes of IDF curves and models. This study could be of significant academic value and improvement to professional practice in the design of storm water drainage systems. Therefore, the developed IDF curves and models are recommended to the Warri Urban Authority for inclusion in her stormwater handbooks and manuals.

The Low Flow Assessment of Padma River in Bangladesh

Low flow or Environmental Flow (EF) assessment is vital to ensure the river and ecosystem remain healthy. Both natural and human interventions might alter a river. Therefore, this study presents EF requirements of the famous Hilsa breeding center in the Padma River, Bangladesh, by applying the Hydrologic Engineering Centers River Analysis System (HEC-RAS) for discharge and water surface levels simulations at different stations. The frequency analysis of 20 years of historical data, spanning 2000-2019, used the Log-Pearson Type III (LP-III) distribution method, while the one-dimensional unsteady flow simulation was performed for the last 10 years (i.e., 2012-2019). Subsequently, the HEC-RAS simulated water level values reasonably correlated with the field observations at four stations, namely Baruria Transit, Mawa, Tarpasha, Sureswar, with Coefficient of determination R2=0.86, 0.83, 0.92, and 0.74, alongside simulated minimum water surface levels of 1.57 m, 0.37 m, 0.30 m, and 0.27 m, respectively. Also, the Baruria Transit and Mawa had simulated flows that reasonably correlated with the field observations at R2=0.70 and 0.61, with a simulated minimum flow of 3849.51 m3/s and 3789.14 m3/s, respectively. The minimum flow according to the frequency analysis was 4017 m3/s, 3685 m3/s, 3449 m3/s, 3229 m3/s, and 3113 m3/s at Baruria Transit and 3304 m3/s, 2781 m3/s, 2438 m3/s, 2141 m3/s, 1992 m3/s at Mawa station in 5, 10, 20, 50 and 100 years return periods, respectively. This study overlooked to report the ongoing investigations into the water quality issues. Thus, this study is expected to guide the required EF quantity towards a healthy Hilsha fish habitat and surface water source for drinking purposes in this studied river. The stated method is also applicable to other similar rivers around the world.

Comparative study of flood coincidence risk estimation methods in the mainstream and its tributaries

The coincidence of floods in the mainstream and its tributaries may lead to a large flooding in the downstream confluence area, and the flood coincidence risk analysis is very important for flood prevention and disaster reduction. In this study, the multiple regression model was used to establish the functional relationship among flood magnitudes in the mainstream and its tributaries. The mixed von Mises distribution and Pearson Type III distribution were selected to fit the probability distribution of the annual maximum flood occurrence dates and magnitudes, respectively. The joint distributions of the annual maximum flood occurrence dates and magnitudes were established using copula function, respectively. Fuhe River in the Poyang Lake region was selected as a study case. The joint probability, co-occurrence probability and conditional probability of flood magnitudes were quantitatively estimated and compared with the predicted flood coincidence risks. The results show that the selected marginal and joint distributions can fit observed flood dataset very well. The coincidence probabilities of flood occurrence dates in the upper mainstream and its tributaries mainly occur from May to early July. It is found that the conditional probability is the most consistent with the predicted flood coincidence risks in the mainstream and its tributaries, and is more reliable and rational in practice.

Intercomparison of evaluation of low-flow characteristics of streams using statistical modelling approach

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Heavy rainfall frequency analysis in the Benin section of the Niger and Volta Rivers basins: is the Gumbel's distribution a one-size-fits-all model?

West African populations are increasingly exposed to heavy rainfall events which cause devastating floods. For the design of rainwater drainage facilities (to protect populations), practitioners systematically use the Gumbel distribution regardless of rainfall statistical behaviour. The objective of this study is twofold. The first is to update existing knowledge on heavy rainfall frequency analysis in West Africa to check whether the systematic preference for Gumbel's distribution is not misleading, and subsequently to quantify biases induced by the use of the Gumbel distribution on stations fitting other distributions. Annual maximum daily rainfall of 12 stations located in the Benin sections of the Niger and Volta Rivers' basins covering a period of 96 years (1921–2016) were used. Five statistical distributions (Gumbel, GEV, Lognormal, Pearson type III, and Log-Pearson type III) were used for the frequency analysis and the most appropriate distribution was selected based on the Akaike (AIC) and Bayesian (BIC) criteria. The study shows that the Gumbel's distribution best represents the data of 2/3 of the stations studied, while the remaining 1/3 of the stations fit better GEV, Lognormal, and Pearson type III distributions. The systematic application of Gumbel's distribution for the frequency analysis of extreme rainfall is therefore misleading. For stations whose data best fit the other distributions, annual daily rainfall maxima were estimated both using these distributions and the Gumbel's distribution for different return periods. Depending on the return period, results demonstrate that the use of the Gumbel distribution instead of these distributions leads to an overestimation (of up to +6.1 %) and an underestimation (of up to −45.9 %) of the annual daily rainfall maxima and therefore to an uncertain design of flood protection facilities. For better validity, the findings presented here should be tested on larger datasets.

Evaluation of Plotting Position Formulae for Pearson Type 3 Distribution in Three Hydrological Stations on the Niger River

In this study, eight unbiased plotting position formulae recommended for Pearson Type 3 distribution were evaluated by comparing the simulated series of each formula with the annual maximum series (AMS) of River Niger at Baro, Koroussa and Shintaku hydrological stations, each having data length of 51years, 53 years and 58 years respectively. The parameters of Pearson Type 3 distribution were computed by the method of moments with corrections for skewness. While the fitting of Pearson Type 3 distribution proceeds with the development of flood – return period (Q-T) relationship, followed by application of the derived Q- T relation to compute simulated discharges for comparison with AMS of the study stations. The plotting position formulae were evaluated on the basis of optimum values of the statistically goodness-of-fit of probability plot correlation coefficient (PPCC), relative root mean square error (RRMSE), percent bias (PBIAS), mean absolute error (MAE) and Nash-sutcliffe efficiency (NSE), across the stations. The plotting position formulae were ranked on scale of 1 to 8. Thus a plotting formula that best simulates the empirical observations using the goodness-of-measures was scored “1” and so on. The individual scores per plotting position were summed across the gof tests to obtain the total score. The study show that Chegodayev is the best plotting position formula for Baro, Weibull is the best plotting position Formula for Kourassou and Shintaku hydrological stations. The overall performances of the eight plotting position formulae across the hydrological stations show that weibull distribution is the overall best having scored 27, seconded by Chegodayev with 30 and thirdly, Beard with 38. The Pearson Type 3 distribution had been found one of the best probability distribution model of flood flow in Nigeria and this study was conducted to gain in-depth knowledge of the distribution. Finally, this study recommends extension of the studies to Log-Pearson Type 3 distribution.

Analysis of Cross-Sectional Capacity of the Jambi River in the Muaro Jambi Temple About Various Times of Flooding Using HEC-RAS Software

Jambi River is one of the rivers located in the Muaro Jambi Temple Complex Area, Muaro Jambi Regency, Jambi Province. Muaro Jambi Temple is one of the tourist attractions in Jambi Province. This study aims to find the capacity of Jambi River tested by planned flood discharge utilizing (synthetic unit hydrograph) HSS Nakayasu method for a return period of two, five, ten, twenty-five, fifty and hundred years. HEC-RAS software used to analyse the water level in the Jambi River towards the flood potential that causes the submerging of the Kedaton Temple building. This research used the log Pearson type III method to calculate the planned rain return period and used the Nakayasu synthetic unit method to calculate the planned flood discharge. The analysis showed that the Jambi River could not load the flood discharge in the five, ten, twenty-five, fifty, and one hundred years return period at several measurement points: river sta-1, river sta-2 and river sta-5. The floodwater level did not cause the Kedaton Temple building to be flooded from the simulation result

ANALISIS STABILITAS BANGUNAN PENGENDALI SEDIMEN PADA KONDISI BANJIR RANCANGAN DAN TAMPUNGAN SEDIMEN PENUH : SUATU KASUS DI ARBORETUM SUMBER BRANTAS, KOTA BATU

The level of land-use change in the Brantas watershed includes encroachment in the upstream area of the spring which has been increasingly massive since the 1960s, and reached the highest level in the late 1990s which driving the watershed damage. The damage in the upstream area encourages the need to increase resilience by building The Sumber Brantas Arboretum Area. This area is equipped with sedimentary control structures to ensure the long-term sustainability of the arboretum. A recent study of the rainfall plan and the security level of the sedimentary control building to the arboretum became an interesting thing to be reviewed. The analytical approach used in this study is quantitative. The method used for flood design analysis uses three methods including Log Pearson Type III Method, Gumbel Method, and Iwai Method. The selected hydrograph is the Nakayasu Hydrograph. Hydraulics analysis of sediment control buildings using HEC-RAS tools with several other hydrological calculations. The results of the analysis in the Sumber Brantas Arboretum Area showed that the design flood discharge (Q) was 59.35 m3 / sec. In flood design conditions with its own weight, the åf of the sediment control building is 42.2 (higher than the minimum safety level) and it is relatively safe, either in normal or in an earthquake condition. In the design flood conditions with full sediment storage, the Sf of sediment control buildings is 1.6 (higher than the minimum safety level) so that it is relatively safe, either in normal or in an earthquake condition.

Severity, Duration, and Magnitude Regionalization of Standardized Precipitation Index Over Iran During 1993-2016

Drought is a natural phenomenon that has environmental and socio-economical drawbacks. Especially in arid and semi-arid regions, human activities are closely linked to the water supply and agricultural water use. Although the consequences of drought are prolonged, immediate actions are needed in practice which urges the continuous need for drought monitoring. The present study addresses a regional frequency analysis (RFA) for extreme drought events including severity, duration, and magnitude over Iran. Standardized precipitation index (SPI) time series with 1, 3, 6, 9, and 12 moving averages are determined from 106 meteorological stations for the period 1993-2016. Using Ward’s clustering analysis, the drought characteristics are grouped into different clusters and their homogeneity is confirmed by the heterogeneity measure test based on the L-moment approach. The results of RFA indicate that both generalized Pareto (GP) and Pearson type 3 (PE3) distribution functions are the best-fitted regional models to the most identified homogenous clusters of all three drought characteristics, by which the quantiles of each drought characteristic related to different return periods, T = 2, 5, 10, 25, 50, 75, and 100 years, are estimated. The spatial pattern of the drought characteristics for all SPI time scales shows that extreme droughts in terms of severity, duration, and magnitude may occur everywhere in the country regardless of local climate conditions. As such, even humid and rainy regions including northern, northwestern, and western parts of Iran that receive high annual precipitation would encounter extreme and severe drought characteristics. It is concluded that the drought risks in the region are mostly the outcome of mismanagement, water resource allocation, and agricultural water use but could be exacerbated due to climatic events.