Spatiotemporal Variability of Intensity–Duration–Frequency (IDF) Curves in Arid Areas: Wadi AL-Lith, Saudi Arabia as a Case Study

In arid areas, flashflood water management is a major concern due to arid climate ambiguity. The examining and derivation of intensity–duration–frequency (IDF) curves in an urban arid area under a variety of terrain patterns and climatic changes is anticipated. Several flood events have been reported in the Al-Lith region of western Saudi Arabia that took away many lives and caused disruption in services and trade. To find and examine the extremities and IDF curves, daily rainfall data from 1966 to 2018 is used. The IDF curves are created for a variety of return periods and climate scenarios in three terrain variabilities. This research examines various distributions to estimate the maximum rainfall for several metrological stations with varying return periods and terrain conditions. Three main zones are identified based on ground elevation variability and IDF distributions from upstream in the eastern mountainous area to downstream in the western coastal area. These IDF curves can be used to identify vulnerable hotspot areas in arid areas such as the Wadi AL-Lith, and flood mitigation steps can be suggested to minimize flood risk.

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.

Modeling seasonal variations of extreme rainfall on different timescales in Germany

We model monthly precipitation maxima at 132 stations in Germany for a wide range of durations from 1 min to about 6 d using a duration-dependent generalized extreme value (d-GEV) distribution with monthly varying parameters. This allows for the estimation of both monthly and annual intensity–duration–frequency (IDF) curves: (1) the monthly IDF curves of the summer months exhibit a more rapid decrease of intensity with duration, as well as higher intensities for short durations than the IDF curves for the remaining months of the year. Thus, when short convective extreme events occur, they are very likely to occur in summer everywhere in Germany. In contrast, extreme events with a duration of several hours up to about 1 d are conditionally more likely to occur within a longer period or even spread throughout the whole year, depending on the station. There are major differences within Germany with respect to the months in which long-lasting stratiform extreme events are more likely to occur. At some stations the IDF curves (for a given quantile) for different months intersect. The meteorological interpretation of this intersection is that the season in which a certain extreme event is most likely to occur shifts from summer towards autumn or winter for longer durations. (2) We compare the annual IDF curves resulting from the monthly model with those estimated conventionally, that is, based on modeling annual maxima. We find that adding information in the form of smooth variations during the year leads to a considerable reduction of uncertainties. We additionally observe that at some stations, the annual IDF curves obtained by modeling monthly maxima deviate from the assumption of scale invariance, resulting in a flattening in the slope of the IDF curves for long durations.

Study of Impact of Cloud-Seeding on Intensity-Duration-Frequency (IDF) Curves of Sharjah City, the United Arab Emirates

Despite the availability of some studies related to rainfall characteristics in Sharjah city and the UAE, very few of these studies have investigated any causal link between recent cloud-seeding missions and the increasing rainfall intensities and urban floods being experienced. This study has assessed the impact of cloud-seeding operations that started in 2010 on the IDF curves of Sharjah city, The UAE. Hourly rainfall data spanning between 2010 and 2020 available at three stations, namely Sharjah Airport, Al Dhaid, and Mleiha, and provided by the National Center of Meteorology were used. To allow comparison with the pre-cloudseeding (2010) era, these records were extended back to 1992 using the much longer data available at Dubai Airport with the aid of the Self-organizing map approach. The developed IDF curves showed an apparent increase in rainfall intensities after implementing the cloud-seeding missions. In addition, the estimated mean rainfall intensities for three regions of the city were also much higher for the cloudseeded years compared to the pre-cloudseeding period. The study suggests that, while cloud-seeding provides water security benefits, its impact on urban flooding should also be carefully considered in the context of urban development plans.

Stochastic simulation of reference rainfall scenarios for hydrological applications using a universal multifractal approach

Hydrological applications such as storm-water management or flood design usually deal with and are driven by region-specific reference rainfall regulations or guidelines based on Intensity-Duration-Frequency (IDF) curves. IDF curves are usually obtained via frequency analysis of rainfall data using which the exceedance probability of rain intensity for different durations are determined. It is also rather common for reference rainfall to be expressed in terms of precipitation P, accumulated in a duration D (related to rainfall intensity ), with a return period T (inverse of exceedance probability). Meteorological modules of hydro-meteorological models used for the aforementioned applications therefore need to be capable of simulating such reference rainfall scenarios. The multifractal cascade framework, since it incorporates physically realistic properties of rainfall processes (non-homogeneity or intermittency, scale invariance and extremal statistics) seems to suit this purpose. Here we propose a discrete-in-scale universal multifractal (UM) cascade based approach. Daily, Hourly and six-minute rainfall time series datasets (with lengths ranging from 100 to 15 years) over three regions (Paris, Nantes, and Aix-en-Provence) in France that are characterized by different climates are analyzed to identify scaling regimes and estimate corresponding UM parameters (α, C1) required by the UM cascade model. Suitable renormalization constants that correspond to the P, D, T values of reference rainfall are used to simulate an ensemble of reference rainfall scenarios, and the simulations are finally compared with datasets. Although only purely temporal simulations are considered here, this approach could possibly be generalized to higher spatial dimensions as well.

Climate change impacts on intensity duration frequency curves of precipitation: A case study of Shiraz synoptic station, Iran

Intensity-duration-frequency (IDF) curves are among the standard design tools for many engineering applications such as urban drainage management. Since climate change may considerably affect precipitation, updating of IDF curves is highly necessary. The present study aims to examine the impacts of climate change on IDF curves of Shiraz synoptic station using downscaled outputs of Hadcm3 AOGCM under various emission scenarios (A1B, A2,B1) applying larswg-5 model for the period of 2046 to 2065. The fitted Gumbel distribution was used to estimate the maximum short-term precipitation quantiles in the base period (1968-2000) and the verified empirical Bell type equation was used for the future period. The results show that the mean of maximum daily precipitation and annual precipitation will decrease in the future. Also, the maximum precipitation intensities up to 60 min duration will reducefrom 0.15 mm hr-1 to about 10.79 mm hr-1 compared to the observed period in all returns periods and various scenarios. Overall, there were no tangible changes in intensities for durations higher than 60 min. The highest reduction in precipitation intensity would be at the 20 min duration with 100-year return period in the A2 scenario.

Disaggregation of future GCMs to generate IDF curves for the assessment of urban floods

Urbanization and industrialization cause an increase in greenhouse gas emissions, which in turn causes changes in the atmosphere. Climate change is causing extreme rainfalls and these rainfalls are getting stronger day after day. Floods are threatening urban areas, and short-duration rainfall and outdated drainages are responsible for urban floods. Intensity–Duration–Frequency (IDF) curves are crucial for both drainage system design and assessment of flood risk. Once IDF curves are determined from historical data, they are assumed to be stationary. However, IDF curves must be non-stationary and time varying based on preparation for extreme events. This study generates future IDF curves with short-duration rainfalls under climate change. To represent future rainfall, an ensemble of four Global Climate Models generated under Representative Concentration Pathways (RCP) 4.5 and 8.5 were used in this study. A new approach to the HYETOS disaggregation model was applied to disaggregate daily future rainfall into sub-hourly using disaggregation parameters of hourly measured rainfalls. Hence, sub-hourly future rainfalls will be obtained capturing historical rainfall patterns instead of random rainfall characteristics. Finally, historical and future IDF curves were compared. The study concludes that increases in short-duration rainfalls will be highly intensified in both the near and distant futures with a high probability.