Intensity-duration-frequency Curves Research Articles

A Vine Copula‐Based Ensemble Projection of Precipitation Intensity–Duration–Frequency Curves at Sub‐Daily to Multi‐Day Time Scales

AbstractPrecipitation intensity–duration–frequency (IDF) curves play a crucial role in the design and planning of urban infrastructure to reduce the risk of urban flooding and rainfall‐triggered landslides. However, changing rainfall characteristics in a warming climate render conventional IDF curves inappropriate due to the statistical assumption of stationarity. In this study, we develop vine copula‐based projections of future IDF curves at sub‐daily to multi‐day time scales with a multi‐model ensemble of five regional climate simulations over China. Stochastic spatiotemporal downscaling of precipitation is achieved to generate extreme precipitation simulations at a high spatial (0.1°) and temporal (3 hourly) resolution. These downscaled simulations are combined by the vine copula to improve the reliability and accuracy of climate‐model‐based IDF curves relative to historical observations. Our findings reveal that climate‐model‐based stochastic downscaling of precipitation reproduces the IDF curves well based on historical observations in China. The vine copula multi‐model ensemble approach outperforms Bayesian model averaging by generating more accurate and reliable IDF curves. The urban areas of 196 Chinese cities are projected to experience an increase in extreme precipitation of up to 30% in intensity and nearly two times the frequency of historical events under a high emission scenario (RCP8.5). The current urban infrastructure of more than half of the 196 cities would thus be inadequate to prevent losses caused by rainfall‐triggered hazards if designed solely based on historical precipitation observations. Compared to the climate‐model‐based IDF curves, we find that statistical IDF curves based on a nonstationary time covariate (i.e., extrapolating historical trends) are likely to underestimate the risk of urban infrastructure failures under a warming climate. This work highlights that urban infrastructure design guidelines in China should be upgraded to adapt existing IDF curves to the changing climate.

Projected Rainfall Intensity Duration Frequency Relationships under Climate Change: A Case Study of Thane City

Climate change is the most important factor to increase in short-duration high-intensity rainfall and consequent flooding. Intensity-Duration Frequency (IDF) curves are commonly used tools in Stormwater design, so a method to derive future IDF curves including climate change effects could be necessary for mainstreaming climate change information into storm water planning. The objective of the present study is to define a mechanism to reflect the effect of climate change on the projected rainfall IDF relationships. For this, the continuously observed hourly rainfall data from 1969 to 2018 were divided into five subgroups. Then the IDF curve of each subgroup is defined. The rainfall intensity for the next 30 years was then estimated using a linear regression model. The obtained result indicates that for the same duration and for the same return period, the rainfall intensity is likely to increase over time: 17% (2019-2028), 25% (2029-2038) and 32% (2039-2048). However, the findings presented in this paper will be useful for local authorities and decision makers in terms of improving stormwater design and future flood damage will be avoided.

Ramifications due to urbanization and climate change on stormwater runoff and conduit efficiency: an integrated water management approach

Abstract Urbanization and climate change increase the frequency of urban floods worldwide which in turn poses a great challenge in the management of the urban stormwater drain system. This study investigated the impact of climate change and surface imperviousness in the urban stormwater runoff and the impact of washed off pollutants load in the conduit efficiency for two census wards Triplicane (ward 116) and Valasaravakkam (ward 152) in Chennai City. The climate change data for the study area wards were taken from the regional climate model (RCM) of Representative Concentration Pathway (RCP) 4.5. Storm Water Management Model (SWMM) with quality and quantity scenarios were developed and the results of the present year scenario were validated using a questionnaire survey. Intensity Duration Frequency (IDF) curves were generated to forecast the observed rainfall and climate model data for various return periods, i.e., 2, 5, 10, 50, and 100 years for future climatic scenarios (2030s and 2050s). The model results show that infiltration is only 3–7% of the total rainfall in the study areas and the maximum blockage and reduction in conduit capacity were estimated to be 65 and 40%, respectively. This paper presents the observations and suggestions for improving the conduit efficiency from an Integrated Water Management Approach (IWMA).

Understanding Intensity–Duration–Frequency (IDF) Curves Using IMERG Sub-Hourly Precipitation against Dense Gauge Networks

The design storm derived from intensity–duration–frequency (IDF) curves is the main input for hydrologic analysis or hydraulic design for flood control. The regions with higher flood risks due to extreme precipitation are often deficient in precipitation gauges. This study presents a detailed evaluation of IDF curves derived using IMERG Final half-hourly precipitation (V06), fitted with the widely used CDFs: Gumbel and MLE, Gumbel and MM, Pearson 3, and GEV. As benchmarks and following the same method, we also derived IDF curves using areal average gridded precipitation constructed from two dense gauges networks over (1) the WegenerNET Feldbach region in the Alpine forelands of Austria and (2) the gauge network of the Walnut Gulch Experimental Watershed, in a semiarid region of the United States. In both regions, the frequency analysis for return periods between 2 and 100 years was based on half-hourly rainfall and compared at a grid-scale with a spatial resolution of IMERG, 0.1° × 0.1° lat/lon. The impact of order in which the gridded gauge-based precipitation average is performed within an IMERG grid was evaluated by computing two different Annual Maximum Series (AMS). In one, the average was computed before obtaining the AMS (AB-AMS), and in the other, the average was computed after obtaining the AMS for each gauge grid (AA-AMS) within the IMERG grid. The evaluation revealed that IMERG AMS agrees better with AB-AMS than AA-AMS for the two study regions. Lastly, it was found that the use of Gumbel distribution in calculating IMERG IDF curves results in better agreement with the ground truth than the use of the other three distributions studied here. The outcomes should provide valuable knowledge for the application of IMERG precipitation over regions with sparse gauges.

Isopluvial Analysis and Intensity Duration Frequency (IDF) Curves for different cities in India

Globally water resource management is becoming a priority for every Government. This is due to tremendous increase in population growth,urbanization, modern life style, increase in agricultural activities, industrialization etc. which is increasing the water demand day by day. This paper focuses on design storms studiesusing return period analysis technique (Isopluvial analysis) based on 129 well distributedSelf Recording Raingauge (SRRG) stations in the various climatic zones of India. The extreme rainfall values are taken for preparation of Isopluvial maps for return period of 2-year, 5- year, 10-year, 25-year, 50-year and 100-year at1-hour, 3-hour, 6-hour, 12-hour and 24-hour duration. Further, station wise Intensity Duration Frequency (IDF) curves are also prepared for 27 stations of the country. The Gumble distribution technique for extreme rainfall series is used for this study. Isopluvial maps & IDF curves are found very useful for Design engineers, hydrologists and hydraulic-consultants for the purpose of planning & designing of water resources related projects in the country forthe construction of any drainage network system, metro, road ways etc.and also, to some extend for the estimation of availability of water.
 

Bias-Corrected IDF Curves From Satellite-Based Rainfall for HoaBinh Province, Vietnam

Satellite-based rainfall is extremely valuable data to quantify the probability of occurrence of rainfall events but is still uncertain to a certain extent. Therefore, this study firstly evaluates the performance of the satellite-based rainfall, PERSIANN-CCS, with rain gauge rainfall. The power transformation method is then applied to correct the satellite-based rainfall. Importantly, the Intensity-Duration-Frequency (IDF) curves are then constructed with the return periods of 5, 10, 25, 50, 100 and 200 years using the Gumbel probability distribution. The results show an efficiency of power transformation on satellite-based rainfall for both rainfall amount and events. It is especially noticed that it is well matched between bias-corrected satellite-based and rain gauge IDF curves duration 12-, 24-, 48- and 72-hour as a particular. For the duration of less than 12-hour, satellite-based IDF curves without bias correction significantly fit the rain-gauge IDF curves within the considered periods.

Developing numerical equality to regional intensity–duration–frequency curves using evolutionary algorithms and multi-gene genetic programming

Developing numerical equality to regional intensity–duration–frequency curves using evolutionary algorithms and multi-gene genetic programming

An overall optimization and solution framework for urban historical and future DRIF under climate change

Abstract The estimation and application of Intensity-Duration-Frequency (IDF) curves depend on the assumption of stationarity of the rainfall series, which is that the intensity and frequency of extreme hydrological events remain unchanged in the future. Climate change will have a significant impact on the collection and utilization of rainwater and its spatial characteristics. When the Gray-Green infrastructure is designed, if only historical precipitation is adopted to calculate the urban design rainstorm intensity formula (DRIF) and the total annual runoff control rate, it may be difficult to meet the demand of future precipitation changes on the city's ability to accommodate rainfall. Therefore, it is very important to study the impact of climate change on the IDF curve. This study proposes an overall optimization solution framework for historical and future DRIF. The impact of the extreme value on the IDF curve during the historical period is analyzed. The calculation method of the IDF curve in the future period is established. The changes of the rainstorm intensity in the historical and future period (SSP1-2.6,SSP2-4.5,SSP3-7.0,SSP5-8.5) were analyzed for the 15 durations and eight return periods in Beijing, China. The results of this study show that the nondominated sorting and local search (NSLS) has the best accuracy in fitting the statistical samples of precipitation for different durations. The best methods to judge and process the extreme value of the statistical sample are Z-score and average value of series greater than critical value (AVG). Under the four SSP scenarios, the estimated IDF value is larger than the observed value in the historical period. The results of the equivalent return period calculated using the DRIF show that the the four SSP scenarios are smaller than the historical period for the return period greater than five years. Taking 120 min of short-duration precipitation as an example, the 100-year equivalent return periods of the observation under the four SSP scenarios are 35-, 20-, 54-, and 17-years, respectively. The research can provide valuable reference for the design and planning of the drainage facility under climate change.

Regionalization of rainfall intensity–duration–frequency (IDF) curves with L-moments method using neural gas networks

Floods are one of the most frequent and destructive natural events which lead to lots of human and financial losses with damage to the houses, farms, roads, and other buildings. Intensity–duration–frequency (IDF) curves are the main and practical tools that have been used for flood control studies, including the design of the water structures. In many cases, there is no measuring device at the desired place, or their information is not helpful if there is any available. In this case, it is not possible to extract these curves through conventional methods. Regionalizing the IDF curves is a method that has solved the issues mentioned in the common methods. In this research, the regionalized IDF curves are extracted in Khuzestan province, Iran using 21 rain gauge stations through L-moments and neural gas networks. Clustering is one of the most effective steps and a prerequisite for regional frequency analysis (RFA) that divides the region and existing stations into hydrologically homogenous regions. In this study, clustering is done using two new models named neural gas (NG) and growing neural gas (GNG) network. Comparing the regional IDF curves with at-site curves, it was found that neural gas network models had a more accurate performance and higher efficiency, so they had the lowest estimate error amount among other models. Also, due to the acceptable difference between regional and at-site curves, the efficiency of L-moments in RFA was evaluated as appropriate.

Disaggregation coefficients for obtaining rainfall intensity-duration-frequency curves: concepts, models, errors and trends in Minas Gerais, Brazil

ABSTRACT Sub-daily rainfall datasets are not commonly available in developing countries, but the annual maximum daily rainfall (Pma ) often is. This article evaluates the ratio between 1440 min of rainfall and the Pma , as well as the sub-daily rainfall ratio from different origins as disaggregation coefficients for modeling the intensity-duration-frequency (IDF) curves in the metropolitan area of Belo Horizonte, Brazil. Non-parametric tests were previously applied to the series to verify stationarity, homogeneity, randomness, and independence. It was verified via Student’s t-test and identity test models that there is a significant difference between the IDF curves from the sub-daily rainfall dataset and disaggregation rainfall dataset. Nevertheless, the model performance indexes between the results of IDF curves indicate the errors are acceptable, thus guaranteeing an alternative tool in places where there are no sub-daily rainfall datasets available. Sub-daily rainfall ratios can be used as disaggregation coefficients on a local and regional scale.

Updating IDF Curves Under Climate Change: Impact on Rainfall-Induced Runoff in Urban Basins

Updating IDF Curves Under Climate Change: Impact on Rainfall-Induced Runoff in Urban Basins

Projection of rainfall intensity-duration-frequency curves at ungauged location under climate change scenarios

It is vital to quantify the changes in the IDF relationship due to climate change for designing climate-resilient urban hydraulic structures. Such projections are also important for ungauged locations due to the possible urban expansion or human settlements. This work proposed a method for IDF curve construction with associated uncertainty at ungauged locations under climate change scenarios, considering peninsular Malaysia as a case study. The bias in Global Satellite Mapping of Precipitation Gauge Calibrated (GSMaP_GC) data was estimated by comparing its IDF curve with the observed IDF curve. Daily rainfall simulations of four global climate models (GCMs), most suitable for the study area, were employed to approximate the possible alterations in future rainfall distribution for four radiative concentration pathways (RCPs). The results revealed changes in rainfall intensity by -3.4 − 26.7% during 2010−2039, -0.1 − 34.5% in 2040−2069 and -4.3 − 96.8% during 2070−2099 compared to base period 1971−2000 for different RCPs. Overall, the changes were pronounced for short-duration compared to high-duration rainfall. Also, higher emission scenarios showed a greater change than the lower scenarios. The climate change uncertainty range was wider for high-duration and smaller for short-duration. The uncertainty was also higher in the far future.

Developing Intensity-Duration-Frequency (IDF) Curves Based on Rainfall Cumulative Distribution Frequency (CDF) for Can Tho City, Vietnam

Information on the relationship between rainfall intensity, duration and accumulation frequency or return period (IDF) is commonly utilized in the design and management of urban drainage systems. Can Tho City, located in the Vietnamese Mekong Delta, is a city which has recently invested heavily in upgrading its stormwater drainage systems in the hope of preventing reoccurring flood events. Yet, much of these works were designed based on obsolete and outdated IDF rainfall curves. This paper presents an updated IDF curve for design rainfall for Can Tho City. For each duration and designated return period, a cumulative distribution function (CDF) was developed using the Pearson III, Log-Pearson III, and Log-Normal distribution functions. In order to choose the best IDF rainfall curve for Can Tho City, the CDF rainfall curve and empirical formulas used in Vietnam and Asia (Vietnamese standard 7957:2008, Department of Hydrology, Ministry of Transportation, Talbot, Kimijima, and Bermard) were compared. The goodness of fit between the IDF relationship generated by the frequency analysis (CDF curve), and that predicted by the IDF empirical formulas was assessed using the efficiency index (EI), and the root mean squared error (RMSE). The IDF built from Vietnam’s standard TCVN 7957:2008 with new parameters (A = 9594, C = 0.5, b = 26, n = 0.96) showed the best performance, with the highest values of EI (0.84 ≤EI≤ 0.93) and the lowest values of RMSE (2.5 ≤RMSE≤ 3.2), when compared to the other remnants.

The influence of climate change and variability on the IFD Curves in NSW, Australia

In this study, the possible impacts of climate change and multi-decadal climate variability on intensity-frequency-duration (IFD) curves were investigated using both stationary and non-stationary generalized extreme value (GEV) distributions. The current study covers rainfall data recorded over 41 years for two rainfall stations, namely, Gowrie-055194 and Sydney Airport-066037, located within New South Wales state in Australia. Three future times (2030, 2060, and 2100), as well as 15 rainfall durations ranging from 6 min to 3-days, are considered. Consideration of the location parameter of the GEV distribution is influenced by climatic change and/or climate variability, providing a more consistent set of IFD curves. It is found that when the future period increases, the relative differences between the stationary and non-stationary IFD curves generally increase. When the new IFD curves (i.e., derived from the stationary and non-stationary approaches) are compared to the Australian Rainfall and Runoff (ARR) IFD curves, it is clear that the ARR IFD curves and the new stationary IFD curves are more closely aligned compared to the non-stationary IFD curves. The findings of this research are useful and provide valuable information for future planning of water resources, environmental and urbanization plans. It is essential to understand the expected behavior of hydro-meteorological processes regarding the possible changes in the rainfall design.

Flow-Type Landslides Analysis in Arid Zones: Application in La Chimba Basin in Antofagasta, Atacama Desert (Chile)

In the world, the hazards of intense rainfall are recurrent and increasing. In addition, they are one of the natural hazards that cause the most severe damage to infrastructure and even cause deaths every year. Flow-type landslides are capable of develop in areas with different geomorphological, geological and climatic characteristics. In hyper-arid zones such as the Atacama Desert, these hazards are capable of develop in a timely manner, causing catastrophes. This study analyzes the flow-type landslide in a hyper-arid mountainous area in La Chimba basin of Antofagasta city (Chile). For this, a hydrometeorological analysis is carried out through a pluviometric analysis, statistical analysis of frequencies through the Gumbel probabilistic method of extreme values and determination of maximum flows by obtaining IDF (intensity-duration-frequency) curves and design rainfall intensity as a function of concentration time. To obtain the maximum flows of liquid runoff and debris, for different return periods, the rational method was used with the method proposed by O’Brien. For the determination in the impact zone, the modeling software HEC-RAS (Hydrologic Engineering Center’s River Analysis System) and RAMMS (Rapid Mass Movements). Hydrographs are used for a return period of about 200 years, considered the most unfavorable scenario with the Voellmy–Salm model. To validate the modeling, a morphometric, sedimentological and comparative analysis is carried out between real impact zones of 1991 event and those generated in this study. It is concluded that the sedimentological and morphometric characteristics indicate that the type of flow that it can originate would have a rapid response to rainfall events of great intensity or duration. The modeling provided by HEC-RAS represents a fluvial-type flow, while the RAMMS modeling is closer to the consistency of a flow-type landslide, which is estimated to be closer to reality. The results show that despite being in a hyper-arid zone, the rainfall factor is capable of landslides triggering in mountainous areas.

Desenvolvimento de Curvas de Intensidade-Duração-Frequência de Chuvas Intensas com ênfase no Comportamento da Cauda Superior da Distribuição

Abstract The design and management of various hydraulic structures (such as stormwater drains, bridges and dams) require the estimation of rainfall with duration of a few minutes up to 24 h or more. Intensity-duration-frequency (IDF) curves links probability of occurrence to a given rainfall intensity. The procedure for obtaining IDF curves basically involves two steps: (i) frequency analysis for different durations and (ii) modeling of IDF curves. In the first step, this study aimed to adequately select the upper tail weight of the following distributions: generalized extreme value (GEV), generalized logistic (GLO) and generalized Pareto (GPA). In the second step, this study aimed to evaluate the performance of three models of IDF curves. The traditional model (M1) was compared with empirical model (M2) and a second-order polynomial model (M3). To perform this study, rainfall data from the city of Caraguatatuba (São Paulo state, Brazil) for the period between 1971 and 2001 were used, for time intervals between 10 and 1440 min. The main conclusions were: (i) GLO and GEV had heavy upper tail while GPA had light upper tail, impacting quantiles with T > 100 years; (ii) M3 presents errors lower than M1 for return periods greater than 100 years.

Remote Sensing for Development of Rainfall Intensity–Duration–Frequency Curves at Ungauged Locations of Yangon, Myanmar

This study aims to develop the intensity–duration–frequency (IDF) curves for Yangon, the economic center of Myanmar, using four satellite precipitation datasets, namely GPM IMERG, TRMM, GSMaP_NRT, and GSMaP_GC. Different probability distribution functions were used to fit the annual rainfall maximum series to determine the best-fit distribution. The estimated parameters of the best-fit distribution were used to fit the rainfall intensities of 2, 5, 10, 25, 50, and 100-year return periods for generating IDF curves using the Sherman equation. The IDF curves were bias-corrected based on the daily rainfall data available only at a location in Yangon. The bias correction factors were then used to estimate IDF curves from satellite rainfall at ungauged locations of Yangon. The results showed that the Generalized Extreme Value Distribution best fit the hourly rainfall distribution of satellite data. Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) is the most suitable for constructing Yangon’s IDF curves. The bias-corrected IDF curve generated at four locations of greater Yangon indicates higher rainfall intensity at the coastal stations than the inland stations. The methodology presented in this study can be used to derive IDF curves for any location in Myanmar.

Linking Urban Floods to Citizen Science and Low Impact Development in Poorly Gauged Basins under Climate Changes for Dynamic Resilience Evaluation

Cities must develop actions that reduce flood risk in the face of extreme rainfall events. In this study, the dynamic resilience of the Gregorio catchment (São Carlos, Brazil) was assessed. The catchment lacks environmental monitoring and suffers from recurrent floods. The resilience curves were made considering the water depth in the drainage system as the performance index, obtained by simulations with SWMM and HEC-RAS. The calibration of the flood extension was performed using citizen science data. The contribution to increasing the dynamic resilience by implementing decentralized low impact development (LID) practices was also evaluated. For this purpose, bioretention cells were added to the SWMM simulations. The resilience curves were then calculated for the current and future climate scenario, with and without LID, for return periods of 5, 10, 50, and 100 years and duration of 30, 60, and 120 min. Intensity–duration–frequency curves (IDFs) updated by the regional climate model MIROC5 for 2050 and 2100 were used. The results showed a significant improvement in the system’s resilience for light storms and the current period due to LID practice interventions. Efficiencies were reduced for moderate and heavy storms with no significant drops in floodwater depth and resilience regardless of the scenario.

Development of Intensity-Duration-Frequency (IDF) Models for Manually Operated Rain Gauge Catchment: A Case Study of Port Harcourt Metropolis Using 50years Rainfall Data

Hydraulic structures such as surface drainages and culverts are usually constructed in urban areas with the intention of draining runoff into nearby streams and rivers in order to avoid flooding. However, most of these structures frequently fail to serve the intended use due to the occurrence of high intensity rainfall accompanied with long duration, which produce runoff discharge higher than their designed capacities. This is common in many developing countries as drainages and culverts are most times constructed without considering hydrological analysis of the catchment. Hence, this research considered Port Harcourt city as a case study by utilizing 50years rainfall data to develop rainfall Intensity-Duration-Frequency (IDF) curves that will be used for subsequent design of drainages and culverts within the city and its environs. The IDF curves were developed using Gumbel, Pearson type III and Log-Pearson type III distributions at return periods of 2, 5, 10, 25 and 50years. However, the durations considered were 5, 10, 20, 30, 45, 60, 90, 120, 150, 180, 210, 240, 300, 360 and 420minutes. Results showed that the IDF equations developed for the three frequency distributions highly correlate with the observed intensities since there goodness of fit (R2) ranges from 0.9766 – 0.9865. Also, it was noted that there was no significant difference (p < 0.01) between the predicted rainfall intensities from all the IDF equations and the observed intensities. Notwithstanding, the IDF equation developed for Gumbel distribution was recommended to be given higher priority since it has the highest R2 value.

Theoretical analysis of urban runoff pollutographs: identification of characterization variables and impact

ABSTRACT This research presents a novel methodology to determine runoff water retention volumes that allow the design of storage tanks for storm sewer overflows. It is based on the use of the Stormwater Management Model (SWMM) to generate hydrographs and runoff pollutographs of a fictional urban basin. Three pollutants (TS, BOD5 and TN) are simulated for a given set of rains and the values taken by a proposed set of characterization variables for the pollutographs obtained are analysed. Correlation and determination coefficients that exist between the different variables are analysed while also performing a multivariate characterization using PCA and cluster analysis. In the case study presented, using IDF curves of the studied city, a probability of occurrence (Tr) is assigned to the values taken by the proposed characterization variables. To assess the impact and identify the most unfavourable pollutographs within the set of selected rains, impact evaluation variables (IEV’s) are established, based on the proposed characterization variables and by simulating the discharge to a receiving water body (river with initial concentration and constant flow). Finally, a storm sewer overflow is simulated, deriving a maximum flow for purification, and dimensioning retention tanks for different fractions of the total volume of runoff to control the maximum values of a specific IEV impact evaluation variable. Taking a design return period Trssd ≥ 10 years, the results obtained in the study case were 146.50 m3/ha imp for a 100% retention of the total runoff volume and 117.20 m3/ha imp for an 80% retention.