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The effective management of flood risk and urban drainage design hinges on a comprehensive understanding and accurate modeling of extreme rainfall variations, particularly in vulnerable areas. The study proposes to model spatial extreme rainfall across various durations in the Ganga River basin of India using max-stable processes (MSP). Incorporating geographical covariates like longitude, latitude, and elevation, 28 surface response models were constructed for location and scale parameters, with linear variations in marginal parameters while keeping the shape parameter constant across space. Various max-stable characterizations were evaluated using the Takeuchi information criterion (TIC) value and likelihood ratio test statistics, including Brown-Resnick, Smith, Extremal-t, Schlatter, and Geometric-Gaussian models with different correlation functions. The findings showed that the Brown-Resnick model consistently simulated well for shorter extreme rainfall for 3, 4, and 6-h and 36-h durations. The extremal coefficients revealed higher dependency between closer locations for most durations. In comparison with classical univariate extreme value theory (UEVT), the MSP exhibits a minimal overestimation in extreme rainfall intensity at New Delhi (by 13.6 mm/h) and Diamond Harbor (by 10.2 mm/h) stations for shorter durations, i.e., 2-h to 6-h range. Its estimations align within the uncertainty bounds of the identical and independent distribution (I.I.D) for longer durations. This suggests the importance of considering the strengths and limitations of M.S.P. and UEVT approaches for accurate rainfall intensity estimation, especially in flood risk management and urban drainage design. In data-sparse region/ungauged basins, where traditional methods like univariate UEVT may be limited due to the absence of observed rainfall data. The fitted max-stable processes MSP can serve as a valuable tool when relevant geographical covariates are known. [ABSTRACT FROM AUTHOR]

The rainfall-intensity duration frequency (IDF) relationship is mostly used in water resource engineering to plan, design, and operate water source projects and projects to manage flood dangers. Engineers must accurately calculate rainfall to design structures that effectively manage runoff collection, conveyance, and storage, as the hydrologic cycle relies on precipitation. An analysis is conducted on the annual rainfall measurements (mm) from five atmospheric observatories in Iraq (Najaf, Hilla, Kerbala, Diwaniya, and Baghdad) spanning 1989 to 2023. The objective is to determine the characteristics of the observed frequency distributions. The Gamma, Log Normal, and Normal distributions compare the data. Kolmogorov-Smirnov, Anderson-Darling, and Chi-Square are study tests. The IDF depict extreme rainfall values over 15, 30, and 60 minutes, with 5, 10, 15, and 50-year return periods. The results indicate that the Chi-Square test has the most optimal distribution among all the stations. The normal distribution was found to be the best for the years (5, 10, 15, and 50) through the IDF curves drawing of stations where the distributions were compared. Equations of Hilla station were found through an IDF equations curve to Hilla from its surrounding stations; and get the error. The result was good agreement, with a ratio Coefficient of Determination ranging from 83.2 to 94.7. [ABSTRACT FROM AUTHOR]

Objective: In this research, triangular (Yen and Chao) and periodic block methods were used to calculate and draw precipitation hyetograph in Kashan synoptic station as an indicator station of dry areas. Method: In order to investigate the effect of climate change on precipitation in the study area, the general circulation model of the atmosphere and different climate scenarios were used. Then the frequency intensity curves for the base period (1993-2017) and the Znear future (2030-2011) and distant future (2050-2031) periods were drawn by using Kahraman-Abkhader relationship. In the following, the curves of intensity, duration, frequency of extraction and corresponding rainfall hyetograph were drawn based on triangular (Yen and Chau) and periodic block methods, and the results were compared with the rainfall patterns measured at the Kashan synoptic station. Results: The results showed that in the study area, the maximum amount of precipitation occurred within 30 minutes after the beginning of the precipitation. The results showed that the precipitation hyetograph of the measured and predicted precipitation data is similar to the hyetograph drawn by the triangulation method (Yen and Chau). Conclusions: According to the results, the triangular method (Yen and Chau) can be introduced as a suitable method for investigating the distribution of precipitation in dry areas. [ABSTRACT FROM AUTHOR]

In the arid Arabian Peninsula, particularly within the United Arab Emirates (UAE), the perception of rainfall has shifted from a natural blessing to a significant challenge for infrastructure and community resilience. The unprecedented storm on 17 April 2024, exposed critical vulnerabilities in the UAE's urban infrastructure and flood management practices, revealing substantial gaps in handling accumulated precipitation. This study addresses the necessity of updating the Intensity–Duration–Frequency (IDF) curves for the Sharjah Emirate by utilizing recent precipitation data from 2021 to April 2024, alongside previously published 2020 data. By recalibrating the IDF curves based on data from three meteorological stations, this study reveals a substantial increase in rainfall intensities across all durations and return periods. Rainfall intensities increased by an average of 36.76% in Sharjah, 26.52% in Al Dhaid, and 17.55% in Mleiha. These increases indicate a trend towards more severe and frequent rainfall events, emphasizing the urgent need to revise hydrological models and infrastructure designs to enhance flood resilience. This study contributes valuable insights for policymakers, urban planners, and disaster management authorities in the UAE and similar regions worldwide. [ABSTRACT FROM AUTHOR]

ABSTRACT Intensity‐duration‐frequency (IDF) models are considered one of the most important tools used in water resources projects, as well as the design and planning of hydraulic structures such as sewerage channels, bridges, culverts, and road networks. This study aims to generate IDF curves for the Iraqi city of Babylon based on the Indian Meteorological Department (IMD) empirical reduction formula and to choose the optimal distribution that gives the greatest rainfall intensity among the three distributions used in this research (generalized extreme value, Log‐Pearson type III, and Gumbel). This study examined daily rainfall data collected from the Iraqi Authority of Meteorology and Seismic Monitoring for a period of 32 years, from 1991 to 2022. The IMD reduction formula was used to calculate rainfall intensity for shorter durations (5, 10, 20, 30, 60, 120, 360, 720, and 1440 min) and custom return periods (2, 5, 10, 25, 50, and 100 years). To determine the goodness of fit for the data distributions, the Easy Fit 5.6 program was applied with three tests (the χ2 test, the Anderson–Darling test, and the Kolmogorov–Smirnov test). The results showed that all distributions were acceptable for both tests and all storm durations and that the rainfall intensity decreased with increasing duration of the rainstorm. It also showed that rainfall increases rainfall intensity during large return periods. Based on the criteria of AIC and BIC, the LP‐3 distribution was chosen as the best distribution to simulate rainfall in Babylon City using the IDM reduction formula.

ABSTRACTThis paper explores the utilisation of gauge rainfall and satellite-based precipitation product (SPP)-TRMM3B42, to develop IDF curves for the Fiji Islands. The study compares the application of remote sensing data against rain gauge (RG) data for two main stations, Nadi and Nausori (1991 to 2020). The accuracy of SPPs is evaluated through statistical analysis, employing continuous and categorical evaluation indices. The results indicate that TRMM3B42 tends to overestimate light precipitation and underestimate heavy rainfall in low elevations when compared to rain gauge data. Rainfall intensities derived from satellite data exhibit relative changes within ± 10%. This study also performs future projections. Two greenhouse emission scenarios, Shared Socioeconomic Pathways (SSP) 2–4.5 and 5–8.5, are employed for IDF curve projection. The analysis reveals that changes in IDF curves are more pronounced for short-duration rainfall as compared to high-duration rainfall. Additionally, higher emission scenarios demonstrate greater changes compared to lower scenarios. These findings emphasise the importance of accounting for climate change and future projections in designing urban infrastructure, particularly considering potential urban expansion and human settlements. This study helps in solving design problems associated with urban runoff control and disposal where knowing the rainfall intensities of different return periods with different durations is vital.

The main aims of the present work were to: develop sub-hourly Intensity–Duration–Frequency (IDF) curves considering future climate projections and predict the impact of climate change on rainfall induced runoff in an urban drainage network. The application was undertaken using hourly measured rainfall data from one station. Because data for sub-hourly rainfall durations were not available for the examined station, a relationship between hourly and sub-hourly rainfall depths was established by employing the scale-invariance theory and using 5-min and 10-min measured rainfall data from two nearby stations. IDF curves were developed based on 1-h annual maxima series, using both the Generalized Extreme Value (GEV) and the Gumbel distributions. Prior to the development of the IDF curves, a trend analysis was conducted. Climate change impact on the urban drainage network was assessed based on future IDF curves by employing the Storm Water Management Model (SWMM) for all hydrologic-hydraulic simulations. It was shown that the statistical properties of annual maxima series present a simple scaling property over time scales ranging from 5 min to 1 h. This allowed the development of IDF curves based on 5-min (scaled) annual maxima series using GEV distribution. The results revealed that by year 2100, rainfall intensities of 1-h duration are projected to increase under the mean climate scenario for all return periods examined. Finally, the predicted urban runoff presented significant variability depending on the studied future climate scenario. Peak discharge at the outlet of the urban drainage network ranged from 4.9 m3/s to 8.3 m3/s. With respect to the current situation, the percent change for peak discharge was estimated at -9%, 47% and 69% for the lower, mean and upper climate change scenarios, respectively. In addition, the surface runoff ranged from 22.2 mm to 73.8 mm, according to the examined scenario, with percent difference estimated at 0.02%, 86% and 232% for lower, mean and upper climate change scenarios, respectively. [ABSTRACT FROM AUTHOR]

This paper explores the utilisation of gauge rainfall and satellite-based precipitation product (SPP)-TRMM3B42, to develop IDF curves for the Fiji Islands. The study compares the application of remote sensing data against rain gauge (RG) data for two main stations, Nadi and Nausori (1991 to 2020). The accuracy of SPPs is evaluated through statistical analysis, employing continuous and categorical evaluation indices. The results indicate that TRMM3B42 tends to overestimate light precipitation and underestimate heavy rainfall in low elevations when compared to rain gauge data. Rainfall intensities derived from satellite data exhibit relative changes within ± 10%. This study also performs future projections. Two greenhouse emission scenarios, Shared Socioeconomic Pathways (SSP) 2-4.5 and 5-8.5, are employed for IDF curve projection. The analysis reveals that changes in IDF curves are more pronounced for short-duration rainfall as compared to high-duration rainfall. Additionally, higher emission scenarios demonstrate greater changes compared to lower scenarios. These findings emphasise the importance of accounting for climate change and future projections in designing urban infrastructure, particularly considering potential urban expansion and human settlements. This study helps in solving design problems associated with urban runoff control and disposal where knowing the rainfall intensities of different return periods with different durations is vital. [ABSTRACT FROM AUTHOR]

In order to examine the relationship between rainfall return periods and flood return periods, the design storm approach is compared to the rainfall–runoff continuous simulation and flood frequency analysis approach. The former was based on rainfall frequency analysis and event-based hydrological simulations, while the latter was based on continuous hydrological simulations and flood frequency analysis. All hydrological simulations were undertaken employing the HEC-HMS software. For the rainfall frequency analysis, the Generalized Extreme Value (GEV) probability distribution was used. For the flood frequency analysis, both the Extreme Value Type I (Gumbel) and GEV theoretical distributions were used and compared to each other. Flood hazard (inundation depth, flow velocities and flood extent) was estimated based on hydrodynamic simulations employing the HEC-RAS software. The study area was the Pineios catchment, upstream of Larissa city, Greece. The results revealed that the assumption of equivalent return periods of rainfall and discharge is not valid for the study area. For instance, a 50-year return period flood corresponds to a rainfall return period of about 110 years. Even if flow measurements are not available, continuous simulation based on re-analysis datasets and flood frequency analysis may be alternatively used. [ABSTRACT FROM AUTHOR]

In the hydrologic design of water management infrastructures, rainfall characteristics are often used and the available historical rainfall events in the form of intensity–duration–frequency (IDF) curves are essential. However, due to the rise in the emission of greenhouse gases, the magnitude and frequency of future extreme rainfalls will be changed. Therefore, the current study aims to develop the IDF curves models in the region of Makkah Al Mukarramah, Saudi Arabia. In this study, five models were developed to estimate the rainfall intensity for the different durations and return periods, using three statistical parameters e, m, and C, calculated from the rainfall intensity data for the time series in each station. The results showed that the rainfall intensity average is ranged between 15.4 mm/10 min and 25.9 mm/60 min for Al Karr Sufli station from 1966 to 2005, and 29.8 mm/120 min and 49.6 mm/720 min for Baqrane station during the period of 1971–2005. Besides, the KGE, R2, and Theil's U performance tests of the probability distribution models revealed that the exponential model is the best for the Al-Barzah, Ain Al Azizia and Al Karr Sufli, and Humma Syssed stations, and the log Pearson III model is the best model for Baqrane station. The outcomes of this research reveal the potential of this approach in projecting upcoming climate situations for urban catchment where long-term hourly rainfall data are not easily available. [ABSTRACT FROM AUTHOR]

The ideal framework for water infrastructure design in any region relies on rainfall characteristics of that region, which is defined through rainfall intensity-duration-frequency (IDF) curves. The current IDF curves are based on historical observations of precipitation. However, with the help of numerical models, more up-to-date IDF curves can be developed to reflect the current precipitation regime. Here, a weather research and forecasting (WRF) model was applied to produce the precipitation data for Arizona from 1950 to 2017. A total of 20 weather forecasting scenarios were simulated by changing the microphysics schemes to improve precipitation forecasting accuracy. The National Severe Storm Laboratory (NSSL) scheme with cloud condensation nuclei (CCN) improved the coefficient of determination by 10% and was selected as the optimum forecasting scenario. The IDF curves were then constructed based on the modeled data and annual maximum series analysis for each climate division in Arizona. The comparison between updated IDF curves and historical IDF curves showed that incorporating up-to-date precipitation data resulted in lower rainfall intensities for short durations. [ABSTRACT FROM AUTHOR]

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.

This paper presents the derivation of the intensity–duration–frequency (IDF) curves for the Kingdom of Saudi Arabia. Such curves were obtained based on rainfall events measured in 28 meteorological stations distributed throughout the Kingdom. For 20–28 years period, 2027 rainfall storms of durations ranging from 10 min to 24 hours were collected and analyzed. Both Institute of Hydrology model (IH-Flood) and Excel-sheet program are used for developing IDF equations for every station. The method of least squares was used to get relationships for the parameters of the IDF formulas. The calculated goodness of fit shows strong correlations range between 0.99 and 0.98 for one of the parameters, and between 0.92 and 0.74 for the other parameters and thence indicating robust IDF formulas for practical use. Regionalization of the IDF parameters for the 13 distinct regions of the Kingdom has been developed. In addition, an average of IDF parameters is made over the Kingdom as a whole to be used in regions of no rainfall records. The resulting IDF curves are usually used for flood estimation in urban/rural watersheds. Using the resulting IDF curves is highly recommended for rigorous, efficient and safe design of hydraulic structures and flood protection works.

Considerable efforts are underway to restore watersheds and estuaries downstream impacted by urban development; however, climate change (CC) may be undermining them. Current methods are limited in their ability to predict hydrology and water quality with CC and assess its effect on the efficiency of stormwater control measures (SCMs). We developed a method using downscaled global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to project precipitation and temperatures; these were used to force a Storm Water Management Model (SWMM). Three scenarios, a historical and two Representative Concentration Pathways (RCP 4.5 and 8.5) with five GCMs, were used to produce ensemble results. All GCMs in both RCP scenarios projected increases in precipitation and temperature compared to historical conditions. Both RCPs exhibited their largest increases in precipitation, streamflow, total suspended solids (TSS), total nitrogen (TN), and total phosphorous (TP) loads in the winter, summer exhibited the largest increase in temperature. Median loads of TSS, TN, and TP increased 3.1%, 2.5%, and 9.9%, respectively, for RCP 4.5, and increased 3.8%, 3.1%, and 10.4%, respectively, for RCP 8.5. Median reductions in TSS, TN, and TP SCM efficiency for RCP 4.5 were projected to be 6%, 7%, and 11%, respectively; and 11%, 12%, and 17% for RCP 8.5, respectively. Thus, it is likely that additional efforts will be needed to meet water quality goals in the future. Methods such as these can help create climate resilient watershed improvement strategies and guide urban stormwater planning against likely future changes as a result of CC. [ABSTRACT FROM AUTHOR]

Abstract: In recent decades, according to Intergovernmental Panel on Climate Change reports, the impact of climate change on hydro‐meteorological events has increased substantially. This point is obvious in many rainfall–runoff time series as a negative or positive trend. In this paper, first of all such trend possibilities are searched graphically according to Şen's 1:1 (45°) straight‐line method, which has been proposed instead of the classical methods including Mann–Kendall, Spearman's rho and linear regression approaches. Additionally, these trends are quantified by using frequency–intensity–duration (FID) curves, instead of intensity–duration–frequency (IDF) curves obtained from a set of single storm rainfall records. The FID curves provide practical, easy and clear representation of rainfall intensity variation through fitted exponential curves with coefficient of determination that is almost equal to 1 (R2 ≈ 1). FID curves are drawn on semilogarithmic paper with rainfall intensity estimations from the convenient Gamma probability distribution functions (PDFs) or cumulative distribution functions (CDFs). In this study 46‐year rainfall records are used from Florya station, which is located in Istanbul, Turkey. The comparisons generally indicated that a negative trend is valid at this station, and accordingly, representative FID curves are obtained on ordinary and semilogarithmic papers for this station. [ABSTRACT FROM AUTHOR]

This paper presents the derivation of the intensity–duration–frequency (IDF) curves for the Kingdom of Saudi Arabia. Such curves were obtained based on rainfall events measured in 28 meteorological stations distributed throughout the Kingdom. For 20–28 years period, 2027 rainfall storms of durations ranging from 10 min to 24 hours were collected and analyzed. Both Institute of Hydrology model (IH-Flood) and Excel-sheet program are used for developing IDF equations for every station. The method of least squares was used to get relationships for the parameters of the IDF formulas. The calculated goodness of fit shows strong correlations range between 0.99 and 0.98 for one of the parameters, and between 0.92 and 0.74 for the other parameters and thence indicating robust IDF formulas for practical use. Regionalization of the IDF parameters for the 13 distinct regions of the Kingdom has been developed. In addition, an average of IDF parameters is made over the Kingdom as a whole to be used in regions of no rainfall records. The resulting IDF curves are usually used for flood estimation in urban/rural watersheds. Using the resulting IDF curves is highly recommended for rigorous, efficient and safe design of hydraulic structures and flood protection works. [ABSTRACT FROM AUTHOR]

The impact of climate change on the behaviour of intensity-duration-frequency curves is critical to the estimation of design storms, and thus to the safe design of drainage infrastructure. The present study develops a regional time trend methodology that detects the impact of climate change on extreme precipitation from 1960 to 2010. The regional time trend linear regression method is fitted to different durations of annual maximum precipitation intensities derived from multiple sites in Ontario, Canada. The results show the relationship between climate change and increased extreme precipitation in this province. The regional trend analysis demonstrates, under nonstationary conditions arising from climate change, that the intensity of extreme precipitation increased decennially between 1.25% for the 30-min storm and 1.82% for the 24-h storm. A comparison of the results with a regional Mann-Kendall test validates the found regional time-trend results. The results are employed to extrapolate the intensity-duration-frequency curves temporally and spatially for future decades across the province. The results of the regional time trend assessment help with the establishment of new safety margins for infrastructure design in Ontario. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

ABSTRACT Capturing the intensity and return period of extreme rainfall events in the historic record and projecting them into the future are essential to managing, planning, and designing infrastructure. In this study, we assess the performance of the combination of four General Circulation Models ( GCMs) and six Regional Climate Models ( RCMs) that comprise the North American Regional Climate Change Assessment Program ( NARCCAP) and evaluate their performance in simulating rainfall extremes in the continental United States. We adopt a regionalization method to objectively delineate 12 regions in the continental United States with relatively homogenous annual maximum 24-h rainfall patterns from the North American Regional Reanalysis ( NARR) data set. We then compare the Intensity-Duration-Frequency ( IDF) curves generated from control simulations of NARCCAP models with those from NARR in each of these regions. We find significant spatial variability of model performance. The models perform reasonably well in many parts of the country, but poorly in the southeastern United States. The GCM providing boundary conditions strongly influences results - output from those RCMs driven by the Community Climate System Model ( CCSM) and Canadian Global Climate Model version 3 ( CGCM3) matched the NARR data best. Performance of individual RCMs also varied, often in response to nudging, wherein the regional model is constrained by the GCM fields. We also measure changes in bias-corrected IDF curves generated from NARCCAP projections of the future. In most regions, most models project intensified 24-h rainfall events in the future (exceptions include some model-projected decreases in southern California, the extreme north-central US, Florida, and the Texas Plains). This study provides a valuable means of assessing NARCCAP models' performance in simulating rainfall extremes at the regional scale and understanding how the GCMs, RCMs, and spatial variability affect model performance. [ABSTRACT FROM AUTHOR]

Summary Intensity–Duration–Frequency (IDF) curves are typically used as a standard design tool for various engineering applications, such as storm water management systems. Warming climate, however, changes the extreme precipitation quantiles represented by the IDF curves. This study attempts to construct the future IDF curves in Saskatoon, Canada, under possible climate change scenarios. For this purpose, a stochastic weather generator was used to spatially downscale the daily projections of Global Climate Models (GCMs) from coarse grid resolution to the local point scale. The stochastically downscaled daily precipitation realizations were further disaggregated to ensembles of hourly and sub-hourly (as fine as 5-min) series using a disaggregation scheme developed based on the K-nearest neighbor (K-NN) technique. This framework was applied to construct the future IDF curves in the city of Saskatoon. The sensitivity of the K-NN disaggregation model to the number of nearest neighbors (i.e. window size) was evaluated during the baseline period (1961–1990). The optimum window size was assigned based on the performance in reproducing the historical IDF curves. By using the simulated hourly and sub-hourly precipitation series and the Generalized Extreme Value (GEV) distribution, future changes in IDF curves and associated uncertainties were quantified using a large ensemble of projections obtained from eight GCMs and three representative concentration pathways – RCP2.6, RCP4.5, and RCP8.5. The constructed IDF curves were then compared with the corresponding historical ones and the IDF curves constructed using another genetic programming-based published method. The results show that the sign and the magnitude of future variations in extreme precipitation quantiles are sensitive to the selection of GCMs and/or RCPs, which seem to get intensified toward the end of the 21st century. The quantification of uncertainties suggests that GCMs are the main contributor to the uncertainty, followed by RCPs and the downscaling method. [ABSTRACT FROM AUTHOR]

Highlights: [•] Long-term sub-hourly extreme precipitation intensities are obtained by MM5. [•] Precipitable water and 2-m air temperature are well simulated by MM5. [•] High resolution (3km) grid-based IDF curves are developed. [•] The positive bias of MM5 IDF curves decreases with increase of return period. [•] The bias of MM5 IDF curves is removed by quantile-based bias correction method. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

• A methodology to estimate relative changes based on a pooled approach is proposed. • Gridded relative changes for 24-h rainfall intensity update are obtained. • Adjustments on relative changes are proposed for facilitating their application. • The approach is applied to Canada. The potential effect of climate change needs to be considered in urban infrastructure design and risk assessment to improve reliability. The present study proposes a methodology for obtaining grid-scale relative changes for updating 24-h extreme rainfall intensity, through the estimation of rainfall intensity quantiles from baseline and future simulations using a pooled frequency analysis approach. Coherence of relative changes over return periods and time horizons is analysed, and adjustments are proposed to facilitate the application of relative changes in practice. The approach is applied to Canada, using gridded daily precipitation series from model combinations belonging to the North American Coordinated Regional Climate Downscaling Experiment. Multi-model 10th, 50th and 90th percentile relative changes are provided for six return periods, considering two future scenarios (RCP 4.5 and RCP 8.5), and two horizons (2050 and 2080). Overall, estimated relative changes varied smoothly and formed a number of clusters of similar values across the country. Relative changes for RCP 8.5 are recommended for 2050, whereas either those for RCP 4.5 or RCP 8.5 could be used for 2080. As an example, median multi-model 50th percentile relative change over Canada is found to be 14%, 16% and 27% for RCP 4.5 – 2080, RCP 8.5 – 2050, and RCP 8.5 – 2080, respectively. [ABSTRACT FROM AUTHOR]

• Three quantile-based downscaling methods are systematically intercompared. • Performance of downscaling methods in producing observed quantiles can be divergent. • Downscaling methods with divergent functionality generate dissimilar future extremes. • Climate change can alter the current design storms under certain risk levels. • A risk-based approach is suggested to choose future design storms under uncertainty. Local characteristics of extreme rainfall quantiles, manifested through Intensity-Duration-Frequency (IDF) curves, are key to infrastructure design. Due to climate change, rainfall extremes are subject to changes, it is, therefore, crucial to explore the potential impacts these changes will have on design storms. A new strain of methodologies, quantile-based downscaling approaches, have recently been proposed to exclusively downscale extreme rainfall quantiles obtained from Global Climate Models (GCMs). These approaches, however, have not been systematically intercompared and the uncertainties related to assigning future design storms are poorly understood. This study evaluates the functionality of three quantile-based downscaling methods during the historical and future periods in Montreal, Canada. Results show that the performance of quantile-based downscaling approaches in reproducing observed extreme quantiles can be divergent. At lower return periods, however, differences between the three schemes are not significant. Similar performances for reproducing historical rainfall extremes, however, does not necessarily imply similar future projections due to the different functionalities of the three approaches in mapping GCM projections into finer scales. Despite these uncertainties, the total projection range of future rainfall extremes are, in many cases, comparable to the confidence interval of the parametric probability distribution when fitted to the observed annual maximum rainfall series. A risk-based approach to accommodate this uncertainty in vulnerability assessments through evaluating potential alterations in historical rainfall extremes using an ensemble projection coming from multiple downscaling approaches is suggested. This allows for the selection of design storms based on the acceptable level of risk and given budgetary and operational restrictions. [ABSTRACT FROM AUTHOR]

This paper aims to assess the necessity of updating the intensity-duration-frequency (IDF) curves used in Portugal to design building storm-water drainage systems. A comparative analysis of the design was performed for the three predefined rainfall regions in Portugal using the IDF curves currently in use and estimated for future decades. Data for recent and future climate conditions simulated by a global and regional climate model chain are used to estimate possible changes of rainfall extremes and its implications for the drainage systems. The methodology includes the disaggregation of precipitation up to subhourly scales, the robust development of IDF curves, and the correction of model bias. Obtained results indicate that projected changes are largest for the plains in southern Portugal (5-33%) than for mountainous regions (3-9%) and that these trends are consistent with projected changes in the long-term 95th percentile of the daily precipitation throughout the 21st century. The authors conclude there is a need to review the current precipitation regime classification and change the new drainage systems towards larger dimensions to mitigate the projected changes in extreme precipitation. [ABSTRACT FROM AUTHOR]