Rainfall Intensity Duration Frequency Research Articles

Case Study of Applying Multifractal Models for Rainfall IDF Analysis in China

AbstractRainfall intensity-duration-frequency (IDF) curves are one of the most commonly used tools in water resources engineering. Two multifractal rainfall models with multifractal behavior are used to estimate IDF curves in this paper. The models are composed of exterior and interior processes with constant duration D and “bare” intensity ID′. Using high resolution data of rainfall, previous research concluded that the results of the IDF curves tend to be insensitive to the length of data record. In this paper, six years of rainfall data at a 5-min resolution at two stations (Nan Xiong and Ai Zi), Guangdong province, China, are analyzed with the multifractal models to estimate IDF curves. Compared with the traditional parametric models for determining IDF curves, the multifractal approach reduces the amount of parameters required to be calculated, and six years of high resolution rainfall data are sufficient to estimate the IDF curves. Forty-six years of annual maxima rainfall data for different duratio...

Simple generalization approach for intensity-duration-frequency relationships

Rainfall intensity–duration–frequency (IDF) relationships describe rainfall intensity as a function of duration and return period, and they are significant for water resources planning, as well as for the design of hydraulic constructions. In this study, the two-parameter lognormal (LN2) and Gumbel distributions are used as parent distribution functions. Derivation of the IDF relationship by this approach is quite simple, because it only requires an appropriate function of the mean of annual maximum rainfall intensity as a function of rainfall duration. It is shown that the monotonic temporal trend in the mean rainfall intensity can successfully be described by this parametric function which comprises a combination of the parameters of the quantile function a(T) and completely the duration function b(d) of the separable IDF relationship. In the case study of Aegean Region (Turkey), the IDF relationships derived through this simple generalization procedure (SGP) may produce IDF relationships as successfully as does the well-known robust estimation procedure (REP), which is based on minimization of the nonparametric Kruskal–Wallis test statistic with respect to the parameters θ and η of the duration function. Because the approach proposed herein is based on lower-order sample statistics, risks and uncertainties arising from sampling errors in higher-order sample statistics were significantly reduced. The authors recommend to establish the separable IDF relationships by the SGP for a statistically favorable two-parameter parent distribution, because it uses the same assumptions as the REP does, it maintains the observed temporal trend in the mean additionally, it is easy to handle analytically and requires considerably less computational effort. Copyright © 2012 John Wiley & Sons, Ltd.

Climate change impact and uncertainty analysis of extreme rainfall events in the Apalachicola River basin, Florida

Climate change impact on rainfall intensity–duration–frequency (IDF) curves at the Apalachicola River basin (Florida Panhandle coast) is assessed using an ensemble of regional climate models (RCMs) obtained from the North American Regional Climate Change Assessment Program. The suitability of seven RCMs on simulating temporal variation of rainfall at the fine-scale is assessed for the case study region. Two RCMs, HRM3–HADCM3 and RCM3–GFDL, are found to have good skill scores in generating high intensity events at the mid-afternoon (2:00–4:00 PM). These two RCMs are selected for assessing potential climate change impact on IDF curves. Two methods are used to conduct bias correction on future rainfall IDF curves, i.e., maximum intensity percentile-based method, and sequential bias correction and maximum intensity percentile-based method. Based on the projection by HRM3–HADCM3, there is no significant change in rainfall intensity at the upstream and middle stream stations but higher intensity at the downstream station. RCM3–GFDL projected increased rainfall intensity from upstream to downstream, particularly at the downstream. The potential temporal shift of extreme rainfall events coupled with overall increased intensities may exacerbate flood magnitudes and lead to increased sediment and nutrient loadings to the estuary, especially in light of sea level change.

Rainfall spatial organization and areal reduction factors in the metropolitan area of Barcelona (Spain)

The rainfall spatial organization in the metropolitan area of Barcelona (Spain) has been studied from records of an urban rain gauge network in the period 1994–2009. Using statistical and regional analysis techniques, correlation between data recorded by the different rain gauges has been calculated, and the effective number of independent stations (n eq) equivalent to the used network has been determined. It has been found out that for durations longer than 20 min, the areal rainfall return period observed for a storm registered by the network approximately decreases by a factor of 1/n eq in relation to the current point rainfall intensity–duration–frequency relationships for the metropolitan area of Barcelona. Using objective analysis techniques, continuous precipitation fields have been generated on a regular grid with a spatial resolution of 300 × 300 m for the storms registered by the rain gauges from 1994 to 2009, for durations from 10 min to 24 h. The precipitation fields obtained have been useful to estimate the characteristic areal reduction factors in the metropolitan area of Barcelona. A direct relationship has been found between the areal reduction factor for all the area corresponding to the urban rainfall network of Barcelona and the effective number of n eq for every duration considered.

The impact of climate change on rainfall Intensity–Duration–Frequency (IDF) curves in Alabama

Changes in the hydrologic cycle due to increase in greenhouse gases are projected to cause variations in intensity, duration, and frequency of precipitation events. Quantifying the potential effects of climate change and adapting to them is one way to reduce vulnerability. Since rainfall characteristics are often used to design water management infrastructures, reviewing and updating rainfall characteristics (i.e., Intensity–Duration–Frequency (IDF) curves) for future climate scenarios is necessary. This study was undertaken to assess expected changes in IDF curves from the current climate to the projected future climate. To provide future IDF curves, 3-hourly precipitation data simulated by six combinations of global and regional climate models were temporally downscaled using a stochastic method. Performance of the downscaling method was evaluated, and IDF curves were developed for the state of Alabama. The results of all six climate models suggest that the future precipitation patterns for Alabama are expected to veer toward less intense rainfalls for short duration events. However, for long duration events (i.e., >4 h), the results are not consistent across the models. Given a large uncertainty existed on projected rainfall intensity of these six climate models, developing an ensemble model as a result of incorporating all six climate models, performing an uncertainty analysis, and creating a probability based IDF curves could be proper solutions to diminish this uncertainty.

Determining rainfall-intensity-duration-frequency relationship using Particle Swarm Optimization

This study proposes a Particle Swarm Optimization (PSO) algorithm to model the Rainfall-Intensity-Duration-Frequency (RIDF) relationship. The study is carried out under two scenarios. In scenario I, a data set with a length of 50 years is used. In Scenario II, the data set is extended to 68 years by adding the values of the recent 18 years. Scenario I is used for testing the robustness of the proposed PSO-RIDF model. The PSO-RIDF algorithm gives the same objective function value for different runs and this shows that the proposed algorithm is robust. Scenario II is used to investigate the influence of data length on model performance. It has been observed that the proposed PSO-RIDF model gives the same performance results as that of the Genetic Algorithm (GA) according to various error evaluation criteria. The PSO-RIDF model shows better performance than GA formulas when the number of parameters increases. It has also been observed that the length of the data set and the chosen formulation are influential on model performance. The weighting parameters of the RIDF model may be determined with PSO algorithm in one-stage instead of any statistical computations and/or trial-error procedure.

Rainfall Intensity-Duration-Frequency Relationships for Andhra Pradesh, India: Changing Rainfall Patterns and Implications for Runoff and Groundwater Recharge

Accurate and current rainfall characterization is an important tool for water-related system design and management. Updated rainfall intensity-duration-frequency (IDF) relationships in peninsular India were developed; impacts on runoff and groundwater recharge attributable to changes in rainfall characteristics are discussed. Two data sets were used from gage in Hyderabad city, the capital of Andhra Pradesh: hourly rainfall data for the 19 years from 1993–2011 and daily rainfall data for the 30 years from 1982–2011. Hourly data were used to develop updated rainfall IDF relationships; daily data were used for trend analysis of threshold-based rainfall events. IDF curves were developed for return periods of 2, 5, 10, 15, 25, 50, 75, and 100 years for 1-, 2-, 4-, 8-, and 24-h durations. The updated IDF relationships showed a significant change in rainfall characteristics compared with older relationships for the region surrounding Hyderabad, India; they showed greater rainfall intensities across all durations and return periods. Greater intensity storms may reduce groundwater recharge and increase runoff, making the surface storage of runoff increasingly important to enhance recharge and reduce flooding risks.

Development of hydrological tools using extreme rainfall events for Dhaka, Bangladesh

Annual daily maximum rainfall data for 57 years (1953 to 2009) in Dhaka, Bangladesh are analysed statistically to prepare two hydrological tools: (1) probable return periods of extreme rainfall events, and (2) intensity-duration-frequency (IDF) curves. Limited availability of short-duration rainfall data leads to difficulties in performing the task through traditional approaches; hence, the Gumbel distribution function and scaling theory have been applied in preparing the probable return periods of extreme rainfall events and IDF curves, respectively. The outcomes of this paper can be used in better designing hydraulic structures in Bangladesh.

Rainfall Intensity Duration Frequency Curves Under Climate Change: City of London, Ontario, Canada

Potential shifts in extreme rainfall at the local level require revisions of existing water infrastructure management regulations as well as changes in design practices. This paper assesses the change in IDF curves for use by the City of London, Ontario under changing climatic conditions. A non-parametric K-Nearest Neighbour weather generator (WG) algorithm is used to synthetically create long time series of weather data. Nine daily maximum rainfall datasets (5, 10, 15, 30 minutes, 1, 2, 6, 12, and 24 hour) collected from the London Airport station for the period 19612002 are used as input into the WG. The WG uses sophisticated shuffling and perturbation mechanisms to generate synthetic rainfall records similar (but not identical) to the observed historic record. The shuffling mechanism generates synthetic rainfall values and the perturbation mechanism can generate extreme rainfall values outside the observed bounds to simulate plausible future rainfall amounts not yet observed. Two climate scenarios are selected for the analysis: climate change lower bound (CC_LB) and climate change upper bound (CC_UB). The CC_LB scenario uses observed rainfall record as WG input. The CC_UB scenario modifies the observed record using the results of a selected global climate model (change fields) and then uses the modified rainfall datasets as WG input. Outputs are used to generate IDF curves. Results of the study include numerical and graphical presentation of updated IDF curves for 2, 5, 10, 25, 50, and 100 years for the city of London, Ontario. The comparison between climate change scenario IDF curves and Environment Canada IDF curves indicates an increase in maximum rainfall intensities and magnitudes which has major implications on ways in which current (and future) municipal water management infrastructure is designed, operated, and maintained.

Regionalization of heavy rainfall to improve climatic design values for infrastructure: case study in Southern Ontario, Canada

Southern Ontario, Canada, has been impacted in recent years by many heavy rainfall and flooding events that have exceeded existing historical estimates of infrastructure design rainfall intensity–duration–frequency (IDF) values. These recent events and the limited number of short-duration recording raingauges have prompted the need to research the climatology of heavy rainfall events within the study area, review the existing design IDF methodologies, and evaluate alternative approaches to traditional point-based heavy rainfall IDF curves, such as regional IDF design values. The use of additional data and the regional frequency analysis methodology were explored for the study area, with the objective of validating identified clusters or homogeneous regions of extreme rainfall amounts through Ward's method. As the results illustrate, nine homogeneous regions were identified in Southern Ontario using the annual maximum series (AMS) for daily and 24-h rainfall data from climate and rate-of-rainfall or tipping bucket raingauge (TBRG) stations, respectively. In most cases, the generalized extreme value and logistic distributions were identified as the statistical distributions that provide the best fit for the 24-h and sub-daily rainfall data in the study area. A connection was observed between extreme rainfall variability, temporal scale of heavy rainfall events and location of each homogeneous region. Moreover, the analysis indicated that scaling factors cannot be used reliably to estimate sub-daily and sub-hourly values from 24- and 1-h data in Southern Ontario. Citation Paixao, E., Auld, H., Mirza, M.M.Q., Klaassen, J. & Shephard, M.W. (2011) Regionalization of heavy rainfall to improve climatic design values for infrastructure: case study in Southern Ontario, Canada. Hydrol. Sci. J. 56(7), 1067–1089.

Developing rainfall intensity–duration–frequency relationship for two regions in Saudi Arabia

Intensity–duration–frequency (IDF) relationship of rainfall amounts is one of the most commonly used tools in water resources engineering for planning, design and operation of water resources projects. The objective of this research is to derive IDF relationship of rainfall at Najran and Hafr Albatin regions in the kingdom of Saudi Arabia (KSA). These relationships are useful in the design of urban drainage works, e.g. storm sewers, culverts and other hydraulic structures. Two common frequency analysis techniques were used to develop the IDF relationship from rainfall data of these regions. These techniques are: Gumbel and the Log Pearson Type III distribution (LPT III).An equation for estimating rainfall intensity for each region was derived using both techniques. The results obtained using Gumbel distribution are slightly higher than the results obtained using the LPT III distribution. Rainfall intensities obtained from these two methods showed good agreement with results from previous studies on some parts of the study area. The chi-square goodness-of-fit test was used to determine the best fit probability distribution. The parameters of the IDF equations and coefficient of correlation for different return periods (2, 5, 10, 25, 50 and 100) are calculated by using non-linear multiple regression method. The results obtained showed that in all the cases the correlation coefficient is very high indicating the goodness of fit of the formulae to estimate IDF curves in the region of interest.

Developing an empirical formulae to estimate rainfall intensity in Riyadh region

The purpose of this paper is to develop an empirical formula to estimate design rainfall intensity based on intensity–duration–frequency (IDF) curves. These curves have been generated from a 32-year recorded rainfall data for Riyadh region. Rainfall intensity–duration–frequency curves describe rainfall intensity as a function of duration for a given return period which are important for the design of storm water drainage systems and hydraulic structures. The formula is derived using the analysis of results of three different frequency methods, namely: Gumbel, Log Pearson III, and Log normal. These methods are used to obtain the IDF curves for six different durations (10, 20, 30 min, and 1, 2, 24 h) and six frequency periods (2, 5, 10, 25, 50, 100 years) where the best method of IDF estimation is recommended for future analysis. The equation can predict rainfall intensity in Riyadh region for any return period with a given storm duration and calibrated parameters obtained from IDF curves. Good match was achieved between its results and other analytical methods results such as Gumbel method. Moreover, it allows incorporating data from non-recording stations, thus remedying the problem of establishing IDF curves in places with a sparse network of rain-recording stations.

The challenges of developing rainfall intensity-duration-frequency curves and national flood hazard maps for the Caribbean

In many Caribbean countries a lack of established good practice methods means that engineers and planners are often unable to plan for and mitigate floods effectively. In most Caribbean states rainfall intensity – duration – frequency (IDF) curves are not readily available. This is a result of the limited quantity of short duration rainfall data available and also because the few IDF curves that have been developed in the region are generally not in the public domain. The lack of readily available IDF curves in the region often results in engineers responsible for the design of key infrastructure inappropriately “transferring” IDF curves developed for islands, where rainfall is less intense, for use in their designs. There are no countries in the Caribbean with nationally consistent flood hazard maps. This often leaves spatial and emergency planners with insufficient information to make important strategic decisions. This paper details the challenges that were faced in producing rainfall IDF curves for return periods up to 1 in 50 years and nationally consistent extreme fluvial flood extent maps with limited data for selected countries within the Caribbean. Recommendations are made for the future development of rainfall IDF curves and national flood maps in the region both in terms of data and organisational requirements.

The impact of forest use and reforestation on soil hydraulic conductivity in the Western Ghats of India: Implications for surface and sub-surface hydrology

Summary There is comparatively limited information in the humid tropics on the surface and sub-surface permeability of: (i) forests which have been impacted by multi-decades of human occupancy and (ii) forestation of land in various states of degradation. Even less is known about the dominant stormflow pathways for these respective scenarios. We sampled field saturated hydraulic conductivity, K∗ at 23 sites at four depths (0 m, n = 166), (0.10 m, n = 139), 0.45–0.60 m, n = 117, (1.35–1.50 m, n = 117) under less disturbed forest (Forest), disturbed production forest of various local species (Degraded Forest) and tree-plantations (Acacia auriculiformes, 7–10 years old, Tectona grandis, ∼25–30 years old, Casuarina equisetifolia, 12 years old) in the Uttar Kannada district, Karnataka, India, in the Western Ghats. The sampling strategy was also undertaken across three physiographic blocks and under three main soil types. Subsequently the determined K∗ were then linked with rainfall intensity–duration–frequency (IDF) characteristics to infer the dominant stormflow pathways. The Degraded Forest shows an order of magnitude decline in K∗ at the surface as result of human impacts at decadal to century time scales. The lowest surface permeability is associated with the Degraded Forests over the Laterite (Eutric Nitosols and Acrisols) and Red soils (Eutric Nitosols) and infiltration-excess overland flow, IOF probably occurs. Further there is a progressive decline in K∗ with depth in these soils supporting Degraded Forests. The A. auriculiformes plantations over the Red and Lateritic soils are progressively restoring the near-surface K∗, but their K∗ still remain quite low when compared to the less disturbed forest permeability. Consequently these plantations still retain the ‘memory’ from the previous degraded state. In contrast the permeability of the Black soils (Vertisols) are relatively insensitive to T. grandis plantations and this soil group has a very low K∗, irrespective of land cover, so that IOF likely prevails. Overall, the Laterites are the most variable in K∗ when compared to the other soil groups. Thus when compared to other studies, IOF is probably more prevalent in this region. More especially so, when taking into account the marked reduction in surface K∗ during the wet season when compared to dry season measurements. In addition, we have demonstrated the potential for the ‘infiltration – trade-off’ hypothesis to be realized in this landscape under certain conditions of land degradation and restoration. It is most relevant to the combination of degraded sites and A. auriculiformes plantations on Red or Laterite soils using the less disturbed forests as the baseline. The intensity of forest use and effects of monoculture plantations on soil ecology (relative to native, mixed forests) is likely to be the critical factor in affecting surface K∗ over time. Predicted changes in the intensity of rain events in the future is likely to enhance overland flow on degraded sites on all soils and especially on Black soils, and restoration efforts by all stake-holders, preferably using native or non-invasive species, are needed to address this concern.

A generalized regional design storm rainfall model for Botswana

Design of drainage and dam structures involves a full understanding of the duration, magnitude and volume of peak flood flows anticipated. For gauged catchments a number of established flood frequency models and rainfall-runoff models are used widely. However, most planned developments for bridge or dam or any other water development structures in a catchment are located at a site in a stream where there are no discharge records. In a catchment, records of short duration rainfall data might not also be available in order to transform them to design flood. In this study, a generalized parametric model for rainfall intensity-duration-frequency (IDF) relations is developed for the estimation of rainfall extremes in Botswana. The model is calibrated on available records on rainfall IDF relationships that are in use by the Botswana Roads Department. The proposed formulation allows one to estimate the expected rainfall depth for a duration ranging from 5 minutes to 2 hours and beyond and for low and medium return periods (up to 50 years) in any location within Botswana. A simplified experiment is developed in order to assess the reliability of the proposed formulation, whose performances are tested also in comparison with other regionalization approaches recently proposed by the scientific literature. The proposed model reproduced the observed IDF both qualitatively and quantitatively with high values of R2 ranging between 92.9 to 99.9 % during model calibration and 92.3 to 99.8% during model verification. Given the lack of recorded continuous and short duration rainfall information, the model can be used to assist hydrologists in the design of drainage and other water control structures for ungauged sites in Botswana.Keywords: Design storms, IDF model, Calibration, verification, parameter sensitivity analysis, Botswana

Generating robust rainfall intensity–duration–frequency estimates with short-record satellite data

Summary In poorly instrumented areas, rainfall records are often absent or short, compounding the statistical challenge of estimating extreme rainfall characteristics and designing flood control structures. In this research two separate rainfall datasets in the country of Ghana were used with two different probability distribution frequency analysis methods to estimate intensity–duration–frequency (IDF) parameters. General extreme value type II (GEV-II) probability distributions were fit using two robust parameterization approaches, one called regional for combining regional and local data, the other called global for combining a global parameter and local data. Annual maximum rainfall data were from the Ghanaian Meteorological Service Department (GMSD) eight ground gages, containing N -min to 24 h durations at 5–24 years record lengths, and from 381 TRMM satellite precipitation bins covering the country, containing 3–24 h duration at 9 years record length in 2007. TRMM rainfall depths were statistically greater at 63% of the stations. Goodness of fit was computed for a maximum return interval of 43 years, and error analysis was computed for 24-h data at return intervals from 77 to 109 years, for all four separately parameterized GEV-II equations and corresponding IDF curves. The best fit and least error was obtained with the global method applied regionally, which used GMSD data to derive time-based parameters and TRMM to derive distribution parameters. The regional method could not incorporate GMSD data, and used only TRMM data, which led to substantial overestimation of rainfall intensity for short durations. This research shows it was essential to combine GMSD and TRMM data for IDF generation in Ghana. The short TRMM record sets with duplicate observed depths at increasing durations caused the regional method to generate internal consistency errors in the IDF plots, suggesting the global method with regional application is best for Ghana.

Approaches for defining thresholds and return periods for rainfall‐triggered shallow landslides

AbstractProbabilistic thresholds for triggering shallow landslides by rainfall are developed using two approaches: a logistic regression model and Iverson's physically based model. Both approaches are applied to a 180 km2 area in northern Italy. For the physically based model a Monte Carlo approach is used to obtain probabilities of slope failure associated with differing combinations of rainfall intensity and duration as well as differing topographic settings. For the logistic regression model hourly and daily rainfall data and split‐sample testing are used to explore the effect of antecedent rainfall on triggering thresholds. It is demonstrated that both the statistical and physically based models provide stochastic thresholds that express the probability of landslide triggering. The resulting thresholds are comparable, even though the two approaches are conceptually different. The physically based model also provides an estimate of the percentage of potentially unstable areas in which failure can be triggered with a certain probability. The return period of rainfall responsible for landslide triggering is studied by using a Gumbel scaling model of rainfall intensity–duration–frequency curves. It is demonstrated that antecedent rainfall must be taken into account in landslide forecasting, and a method is proposed to correct the rainfall return period by filtering the rainfall maxima with a fixed threshold of antecedent rainfall. This correction produces an increase of the return periods, especially for rainstorms of short duration. Copyright © 2009 John Wiley & Sons, Ltd.

Rainfall intensity–duration–frequency relationships derived from large partial duration series

A procedure is proposed for basing intensity–duration–frequency (IDF) curves on partial duration series (PDS) which are substantially larger than those commonly used for this purpose. The PDS are derived from event maxima series (EMS), composed of the maximum average intensities, over a given duration, determined for all rainfall events recorded at a station. The generalized Pareto distribution (GP) is fitted to many PDS nested within the EMS and the goodness-of-fit is determined by the Anderson–Darling test. The best fitted distribution is selected for predicting intensities associated with the given duration and with a number of recurrence intervals. This procedure was repeated for eleven rainfall durations, from 5 to 240 min, at four stations of the Israel Meteorological Service. For comparison, the GP and the generalized extreme value (GEV) distributions were fitted to annual maxima series (AMS) and the Gumbel and lognormal distributions were fitted to the PDS and to the AMS at these stations. In almost all cases, the GP distribution well fits to ranges of PDS within an EMS, while in a few cases the best fit is fair only. Another result is that the GP distribution does not fit to AMS and to EMS. The GEV distribution well fits to most AMS, and fairly fits to the others. The Gumbel and the lognormal distributions well fit to most of the AMS and to a very few PDS. In most cases of good fits of different distributions, the predicted values by the different distributions are not much different from one another. This indicates the importance of good fit of the distribution and of the power of the AD test used for determining it. In most cases the best fit of the GP distribution is to a PDS series substantially larger than its corresponding AMS. In most cases, the standard error of the estimated 100-year intensity, through the best fitted GP to PDS, is smaller than that estimated through the GEV fitted to the corresponding AMS. All these make the proposed procedure superior to the current ones. It also enables interpolated predictions down to recurrence intervals of N / n years ( N is number of years of complete records and n is PDS size). The use of large samples would reduce the sensitivity of predicted intensities to sampling variations.

Derivation and assessment of a bivariate IDF relationship using paired rainfall intensity–duration data

A procedure is presented for developing a rainfall intensity–duration–frequency (IDF) relationship that is consistent with bivariate normal distribution modeling. The Box–Cox transformation was used to derive the relation and two methods of determining the parameters of this transformation were evaluated. To assess the uncertainty of the parameters, a confidence interval was constructed and verified with the non-parametric bootstrap method. Additionally, the effect of sample size on the bivariate normality assumption was examined. Case studies, based on data from significant gauge stations in Korea, were performed. The result shows that the use of the bivariate normal model as an IDF relationship is particularly recommended when the available data size is small.

Updating Rainfall IDF Relationships to Maintain Urban Drainage Design Standards

The hydrologic design standards for urban drainage systems are commonly based on the frequency of occurrence of heavy rainfall events. Observations of recent climate history indicate that the frequency of occurrence of heavy rainfall events is increasing. This increasing trend will likely continue in the future due to global warming. In this study, extending from previous analysis results for Chicago, the rainfall intensity–duration–frequency (IDF) relationships were determined to represent the climate conditions of the first and second halves of the last century. Using these IDF relationships, the impact of the observed increase in heavy rainfall events on the design and performance of urban drainage systems were quantified. This quantification demonstrated the need for updating rainfall IDF relationships to reflect changing climate conditions. In the design of new and retrofitting or replacement of old urban drainage systems, up to date IDF relationships need to be used to maintain design standards.