Intensity-duration-frequency Curves Research Articles

Developing Non-Stationary Frequency Relationships for Greater Pamba River basin, Kerala India incorporating dominant climatic precursors

Abstract. Global climate changes significantly contribute to increased frequency of hydrologic extremes. This significantly underestimates the hydrologic design parameters, bringing of hydro systems to increased failure risk. In order to address this concern, the current practice of development of hydrologic frequency tools need to be updated accounting for non-stationarity. This study first considered a diverse set of statistical tests to examine the trend, change points, non-stationarity and randomness of streamflow, rainfall and temperature time series of scales ranging from daily to annual. The annual maxima time series indicated non stationarity against the stationary behaviour of daily series of hydro-meteorological datasets of the basin. Subsequently, this study developed the Temperature Duration Frequency (TDF), Rainfall Intensity Duration Frequency (IDF) and Flood Frequency (FF) curves of Greater Pamba river basin in Kerala India, the part of which was most severely affected by the near century return period flood event of 2018. The analysis was performed for a multitude of combinations of variations in distribution parameters with time and climatic drivers as physical covariates in the extreme value formulations. The study proposed a novel wavelet coherence (WC) based driver selection of most dominant combination of climatic precursors in developing FF and IDF relations of three locations of Kalloopara, Malakkara and Thumpamon and TDF curve of Kuttanad region in the basin, considering data of 1985–2015 period. The proposed WC framework considers bi-multi-and partial effects of climatic oscillations (COs) like El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO) in identifying potential drivers. The different WC formulations captured in-phase relationships of streamflows and rainfall with COs at intra-annual, annual and inter annual scales up to 4 years. The methods showed that addition of climatic precursors improved the NS estimates of flood and rainfall quantiles by more accurately capturing the magnitudes of extreme streamflows and rainfalls of 2018, 2021 than the time covariate formulations. However, the role of COs on extreme temperature is not found to be influential in developing TDF relationships, which needs further investigation.

Design of drainage channel for effective use of land on fully mechanized sugarcane plantations: A case study at Bone Sugarcane Plantation

Abstract Drainage in sugarcane cultivation in high-rainfall areas is of paramount importance because it affects sugarcane plants from planting, maintenance, and production. Poor drainage can damage plants and reduce productivity. This study was conducted at Bone Sugarcane Plantation, which typically has high annual rainfall; thus, drainage is necessary. The existing drainage channel cannot drain all surface runoff quickly and causes problems to sugarcane plants. Therefore, a study was conducted with the aim of designing the shape and size of drainage channels that can drain surface runoff quickly, have a strong structure, allows for an effective use of cultivated land by reducing headland for tractor turning, and maintains appropriate soil moisture. The research began by determining the saturated hydraulic conductivity of the soil using the Falling Head method. Surface runoff discharge was calculated using rational equations to determine the dimensions of the drainage channel. Rainfall intensity was determined from Intensity Duration Frequency curve which was constructed using Manonobe method. The results showed that the saturated hydraulic conductivity of the soil was 3.54 × 10−3 cm/s which is suitable with surface drainage. Rainfall intensity is estimated to be 201.33 mm/hour. The shape and dimensions of the drainage channel are parabolic with the largest width and depth of 1.70 m and 0.90, respectively. This study provides a practical method to solve drainage problems in sugarcane fields that apply full mechanization. In addition, the practical analysis used in this study can be adapted to analyze the design of drainage channel for other plantations or regions with similar constrains.

Influence of vegetation index to the rainfall intensity in Pasuruan Area, East Java Province, Indonesia

An increase in population increases the rate of urbanization. This results in changes in land cover from vegetation to artificial material. As a result, much of the land surface reflects the sun's energy. Consequently, this increases the surface temperature of the land. An increase in land surface temperature (LST) will increase the intensity of rainfall. Therefore, the present study aimed to investigate the relationship between the increase in LST and rainfall intensity. Changes in land cover can be detected by normalized difference vegetation index (NDVI) and normalized difference built-up index (NDBI) parameters. Landsat satellite imagery was used to detect NDVI, NDBI, and LST. Image processing was done for imageries scanned in 1995, 2015, 2017, and 2021. Two areas in the East Java Province of Indonesia, namely Malang City and Pasuruan Area, were selected. The daily rainfall intensity data were collected from related rainfall stations in the same year. The Mononobe method was applied to analyze hourly and minute rainfall intensity. IDF curves were drawn from the analyzed results. The relationship between both parameters was analyzed by comparing the LST and hourly rainfall intensity from the IDF curve. The studied results showed that the maximum temperature increase from 1995 to 2021 for the Malang City and Pasuruan Area was 2.60 C and 7.60 C, respectively. For rain, the maximum rainfall intensity increased by 58 mm for Malang City and 18 mm for the Pasuruan Area. LST and rainfall intensity change trends of the two areas had a positive coefficient of regression. The findings can be used to predict the rainfall intensity and floods based on the LST data.  

Climate change impacts on rainfall intensity–duration–frequency curves in local scale catchments

The increasing intensity and frequency of rainfall events, a critical aspect of climate change, pose significant challenges in the construction of intensity–duration–frequency (IDF) curves for climate projection. These curves are crucial for infrastructure development, but the non-stationarity of extreme rainfall raises concerns about their adequacy under future climate conditions. This research addresses these challenges by investigating the reasons behind the IPCC climate report’s evidence about the validity that rainfall follows the Clausius-Clapeyron (CC) relationship, which suggests a 7% increase in precipitation per 1 °C increase in temperature. Our study provides guidelines for adjusting IDF curves in the future, considering both current and future climates. We calculate extreme precipitation changes and scaling factors for small urban catchments in Barranquilla, Colombia, a tropical region, using the bootstrapping method. This reveals the occurrence of a sub-CC relationship, suggesting that the generalized 7% figure may not be universally applicable. In contrast, our comparative analysis with Illinois, USA, an inland city in the north temperate zone, shows adherence to the CC relationship. This emphasizes the need for local parameter calculations rather than relying solely on the generalized 7% figure.

Flash flood detection via copula-based intensity–duration–frequency curves: evidence from Jamaica

Abstract. Extreme rainfall events frequently cause hazardous floods in many parts of the world. With growing human exposure to floods, studying conditions that trigger floods is imperative. Flash floods, in particular, require well-defined models for the timely warning of the population at risk. Intensity–duration–frequency (IDF) curves are a common way to characterize rainfall and flood events. Here, the copula method is employed to model the dependence between the intensity and duration of rainfall events flexibly and separately from their respective marginal distribution. Information about the localization of 93 flash floods in Jamaica was gathered and linked to remote-sensing rainfall data, and additional data on location-specific yearly maximum rainfall events were constructed. The estimated normal copula has Weibull and generalized extreme value (GEV) marginals for duration and intensity, respectively. Due to the two samples, it is possible to pin down above which line in the intensity duration space a rainfall event likely triggers a flash flood. The parametric IDF curve with an associated return period of 216 years is determined as the optimal threshold for flash flood event classification. This methodology delivers a flexible approach to generating rainfall IDF curves that can directly be used to assess flash flood risk.

Development of intensity–duration–frequency relationships in Khon Kaen City, Thailand under changing climate using GCMs and a simple scaling method

Abstract This study analyses the annual maximum (AM) rainfall series (1991–2022) in Khon Kaen City, Thailand. The AM rainfall series ranging from 3 to 24 h was best fitted to the Log-Pearson Type-III distribution. Notably, our findings reveal linear relationships between the moments of rainfall intensities and durations establishing the practicality of the simple scaling method for disaggregating 24-h AM rainfall data. Additionally, the results of this method are influenced by factors such as sample size, rainfall durations and the chosen probability distribution. Comparisons between intensity–duration–frequency (IDF) curves obtained through the simple scaling method and those derived from traditional frequency analysis provide valuable insights. Furthermore, this method was applied to bias-corrected rainfall data of 15 global climate models facilitating the generation of future IDF curves under SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5 scenarios. Our results highlight that rainfall events in the SSP5-8.5 scenario are projected to exhibit higher intensities emphasizing the need to understand and prepare for increased rainfall extremes in the context of climate change. This research contributes valuable insights into rainfall analysis and prediction techniques, which are crucial for effective water resource management and climate adaptation strategies in the Khon Kaen region.

Flood Modeling: A Comprehensive Review on IDF Curves, HEC-HMS, HEC-RAS, and GIS Integration

Flood Modeling: A Comprehensive Review on IDF Curves, HEC-HMS, HEC-RAS, and GIS Integration

Review: Fractal Geometry in Precipitation

Rainfall, or more generally the precipitation process (flux), is a clear example of chaotic variables resulting from a highly nonlinear dynamical system, the atmosphere, which is represented by a set of physical equations such as the Navier–Stokes equations, energy balances, and the hydrological cycle, among others. As a generalization of the Euclidean (ordinary) measurements, chaotic solutions of these equations are characterized by fractal indices, that is, non-integer values that represent the complexity of variables like the rainfall. However, observed precipitation is measured as an aggregate variable over time; thus, a physical analysis of observed fluxes is very limited. Consequently, this review aims to go through the different approaches used to identify and analyze the complexity of observed precipitation, taking advantage of its geometry footprint. To address the review, it ranges from classical perspectives of fractal-based techniques to new perspectives at temporal and spatial scales as well as for the classification of climatic features, including the monofractal dimension, multifractal approaches, Hurst exponent, Shannon entropy, and time-scaling in intensity–duration–frequency curves.

Possibility of using the STORAGE rainfall generator model in the flood analyses in urban areas

In this investigation, we evaluated the applicability of the Stochastic Rainfall Generator (STORAGE) as a data source for deriving design hydrographs in urban catchments. This assessment involved a comparison with design rainfall calculated using Intensity-Duration-Frequency (IDF) curves derived from observed time-series data. The resulting design rainfall values from both methods were incorporated into a hydrodynamic model of the storm sewer network. To simulate peak discharge and flood areas, the Storm Water Management Model (SWMM) program was employed in conjunction with SCALGO. Our findings indicate that design rainfall values obtained from the STORAGE model exceeded those derived from the observed time-series, with a more pronounced difference for shorter rainfall durations. Simulations further revealed that peak runoff disparities between the two approaches were most evident at a 0.10 probability of exceedance compared to a 0.01 probability. Hydrodynamic simulations demonstrated that the flooding volume induced by design rainfall based on the STORAGE model surpassed that resulting from observed rainfall. Across all events, both the flooding volume and area from STORAGE were consistently greater than those derived from IDF curves. The integration of the SWMM model with the SCALGO application introduced a novel functionality for dynamic visualization of flooding, offering valuable insights for effective flood management in urban areas.

Territorial Decision Support System Based on IDF Curves’ Parameters Regionalization

Territorial Decision Support System Based on IDF Curves’ Parameters Regionalization

Development of intensity – duration – frequency (IDF) curves using combined rain gauge (RG) and remote sense (TRMM) datasets for Weta Traditional Area in Ghana

This research developed IDF curves and derived empirical equations for the Weta Area to estimate design rainfall. Daily rainfall data of Rain Gauge and Tropical Rainfall Measuring Mission (TRMM) 3B42 over 22 years for Weta were obtained from the Ghana Meteorological Services and National Aeronautics and Space Administration, respectively. The Indian Meteorological Department formula was used to disaggregate the daily data into hourly synthetic series to develop the IDF curves. The combined dataset was subjected to frequency analysis to determine the distribution which best characterize the dataset. The results demonstrated that the IDF curves provided higher intensities for shorter durations (0.08-h, 0.17-h, 0.25 h, and 0.5 h) while lower intensities for longer durations (1 h, 2-h, 6-h, 12 h and 24 h). The rainfall intensities and return periods are parallel and high intensities correlated with brief durations for the same return period. TRMM overestimated rainfall compared to Rain Gauge data. The IDF curves and derived empirical equations are useful scientific tools for hydraulic infrastructure design and water resources planning and management.

Applicability of Utilizing Remote Sensing Rainfall Products Data in Arid and Semi-Arid Poorly Gauged Catchments: Study of Wadi Ghoweiba Watershed, Egypt

AbstractDue to the scarcity of established rain gauge stations, obtaining continuous time series daily rainfall observation data is a major challenge. The availability of these data is very essential to conduct hydrological studies and predicting flood events. Nowadays, several satellites could be used to provide such data. This study aims to investigate the appropriate remote sensing (RS) rainfall product and use its data to develop frequency analysis and intensity–duration–frequency curve (IDF curve) at 5-, 10-, 25-, 50-, 100-, and 200-year return periods in the study area. The evaluation of the PERSIANN family products (PERSIANN, PERSIANN-CCS, PERSIANN-CDR, and PDIR-Now) with NASA-POWER datasets compared to the available annual maximum of daily observation rainfall in Suez Rain Gauge (SRG) station as a reference was conducted. The results show that the PERSIANN-CDR product is the appropriate satellite-based rainfall dataset product based on the outcomes of the comparison criteria (RMSE, Bias, CC, and R2 error measures) of rainfall characteristics analysis and Chi-squared test of distributions. The frequency analysis results confirmed that the values of about 30.3–38.6 and 40–53.3 mm/day corresponding to the biggest flood reported in 1965 and 2020 in SRG station and PERSIANN-CDR product have a return period of 50–100 years, classifying it as an extreme event in Wadi Ghoweiba. These findings would considerably benefit decision-makers in estimating flood risks and planning the appropriate structure protections in the Wadi Ghoweiba Watershed.

Precipitation Study in Flood Zones: San Mateo Atenco, State of Mexico, Mexico Case Study

This work is focused on analyzing the causes of flooding in the sub-basin belonging to the municipality of San Mateo Atenco: Almoloya-Otzolotepec, because the municipal territory is constantly threatened by hydrometeorological phenomena, such as hailstorms, frost and torrential rains. The maximum precipitation was analyzed in neighboring climatological stations and the precipitation at different return periods (2 to 1000) was determined through the Gumbel distribution, and its impact according to the Thiessen polygon method. With the information of the 24-hour intensities, the Intensity Duration Frequency (IDF) curves and the hietogram of the study area were plotted using the alternating block method. The above procedure was applied to the precipitation data from the 9 stations that affect the basin. The approach proposed in this work considers all the precipitation variables for the best approximation of the phenomena that may occur in the basin; it is an innovative model because it considers the weighted averages of precipitation for each area of influence and its surroundings; this information is useful for the implementation of flood protection projects, adequate design of drainage and sewage systems, and a rational use of the resource to guarantee better living conditions for the inhabitants. According to the results obtained, there is a slow hydrological response and the areas with the greatest runoff potential (8383<CN<100) are located towards the central part of the basin where there is a significant concentration of bare soil.

Development of Synthetic Unit Hydrographs Using Spatial Proximity Regionalization for the Makiling Forest Reserve, Philippines

There is a dearth of streamflow data in the Philippines to generate hydrographs needed for flood forecasting and water resources assessment. A method of generating and calibrating synthetic hydrographs using model simulations and spatial proximity regionalization is presented. Synthetic unit hydrographs of four storm events in the gauged watershed of Makiling Forest Reserve were generated using Soil Conservation Service Unit Hydrograph, Clark Unit Hydrograph, and Snyder’s Unit Hydrograph methods. The generated synthetic hydrographs for each runoff modeling technique were calibrated with the actual hydrographs of the watershed. Snyder’s Unit Hydrograph model results were the most acceptable based on the Nash-Sutcliffe Efficiency, Index of Volumetric Fit, and Relative Error of Peak Flow. The weighted values of the calibrated watershed parameters computed using spatial proximity regionalization technique and the hyetographs derived from the Rainfall Intensity Duration Frequency Curve of the University of the Philippines Los Baños-National Agrometeorological Station were used to generate the synthetic unit hydrographs for three neighboring ungauged watersheds at 2-, 5-, 10-, 15-, 20-, 25-, 50, 100-year return periods. Total runoff volume, the magnitude of peak flows, and time to peak derived from the generated hydrographs can be used in watershed planning, water resources management, flood forecasting and the design of various water control structures.

Simple scaling of extreme precipitation regime in Senegal

Extreme precipitation exhibits high temporal and spatial variability, and understanding this variability is crucial for designing hydraulic infrastructures and assessing the impacts of natural risks such as floods and droughts. The Simple Scaling (SS) model, which describes the dependence of extreme rainfall statistics on timescales, is used to estimate Intensity Duration Frequency (IDF) curves. This study aims to evaluate the validity of the Simple Scaling (SS) hypothesis for 14 rain gauges in Senegal and explore the existence of breaks in temporal scaling regimes (transition regimes). For the analysis of extreme characteristics, we considered the Annual Maximum Series (AMS) of precipitation in sub-hourly and supra-daily durations ranging from 10 min to 7 days. The empirical validation of the SS models was confirmed for the majority of the scaling intervals. We identified two scaling breaks, indicating the presence of three scaling regimes: short durations (SD), intermediate durations (ID), and long durations (LD). The spatial variation of scaling exponents reveals the existence of different scaling regimes across Senegal. The results are valuable for modeling the spatial distribution of scaling exponents, which can aid in characterizing IDF curves at ungauged locations.

Development of Intensity–Duration–Frequency (IDF) Curves over the United Arab Emirates (UAE) Using CHIRPS Satellite-Based Precipitation Products

The recent flooding events in the UAE have emphasized the need for a reassessment of flood frequencies to mitigate risks. The exponential urbanization and climatic changes in the UAE require a reform for developing and updating intensity–duration–frequency (IDF) curves. This study introduces a methodology to develop and update IDF curves for the UAE at a high spatial resolution using CHIRPS (Climate Hazards Group InfraRed Precipitation with Station) data. A bias correction was applied to the CHIRPS data, resulting in an improved capture of extreme events across the country. The Gumbel distribution was the most suitable theoretical distribution for the UAE, exhibiting a strong fit to the observed data. The study also revealed that the CHIRPS-derived IDF curves matched the shape of IDF curves generated using rain gauges. Due to orographic rainfall in the northeastern region, the IDF intensities were at their highest there, while the aridity of inland regions resulted in the lowest intensities. These findings enhance our understanding of rainfall patterns in the UAE and support effective water resource management and infrastructure planning. This study demonstrates the potential of the CHIRPS dataset for IDF curve development, emphasizes the importance of performing bias corrections, and recommends tailoring adjustments to the intended application.

Flood Estimation and Control in a Micro-Watershed Using GIS-Based Integrated Approach

Flood analyses when using a GIS-based integrated approach have been successfully applied around the world in large-sized watersheds. This study employed hydrological-hydraulic modeling to analyze flash floods by integrating HEC-HMS, HEC-RAS, and ArcGIS software for flood evaluation and control in a micro-watershed in the Samaru River, Nigeria. The watershed boundaries, its characteristics (soil and land use), the topographical survey, and the intensity duration frequency curve (IDF) of the study area were produced using data-driven techniques. The HEC-HMS model was used to derive the peak discharges for 2-, 5-, 10-, 25-, 50-, 100-, and 200-year return periods with the frequency storm method. Afterward, the water surface profiles for the respective return periods were estimated using the HEC-RAS hydrodynamic model. The simulated design flood for the 2-, 5-, 10-, 25-, 50-, 100-, and 200-year return periods at the reference location (the NUGA gate culvert) were 3.5, 6.8, 9.1, 12.1, 14.3, 16.6, and 19.0 m3/s, respectively, while those at the watershed outlet for the respective return periods were 7.5, 14.9, 20.3, 27.3, 32.6, 38.0, and 43.5 m3/s, respectively (with a water height of 0.9 m, 1.1 m, 1.3 m, 1.33 m, 1.38 m, 1.5 3m, and 1.8 m, respectively), at the NUGA gate culvert cross-section. The maximum water depths of about 0.9 m and 1.0 m were recorded in the right and left overbanks, which were similar to the simulated water depth for the 2- and 5-year return periods. Hence, for the smart control of floods passing through the river and major hydraulic structures, a minimum design height of 1.50 m is recommended. For the most economic trapezoidal channel section, a normal depth of 1.50 m, a bottom width of 1.73 m, a top width of 3.50 m, and a free board of 0.30 m is proposed to curb the overtopping of floods along the channel sub-sections. The findings of this study could help hydraulic engineers minimize flooding in streams and rivers overbanks in a micro-watershed.

Quantification of climate change impact on rainfall-induced shallow landslide susceptibility: a case study in central Norway

ABSTRACT Climate change impact on rainfall-induced landslide susceptibility of a certain region is often implied based on expected changes in rainfall patterns and rarely explicitly quantified. This study aims to address this gap by implementing coupled landslide and climate modelling chains to explicitly assess the effects of changing rainfall patterns on rainfall-induced landslide susceptibility. The effects of climate change are integrated into the landslide modelling chain via Intensity-Duration-Frequency (IDF) curves for the present and future climate conditions for a landslide-prone study area located in central Norway. The effects of climate change on landslide susceptibility are examined by using a physical-based landslide prediction model with rainfall events of varying duration and intensity that are simulated based on the climate-dependent IDF curves. The novelty of this study is the proposition of a novel probabilistic framework to assess the climate change impact on landslide susceptibility for rainfall events with a given duration. The proposed framework accounts for both the uncertainties of rainfall events through probabilistic interpretation of IDF curves and the uncertainties in the landslide model with the Monte Carlo method. Compared to results based on only intense rainfall events, the proposed framework leads to a lower increase in the probability of landslide initiation and landslide-susceptible extents due to climate change.

Evaluating Non-Stationarity in Precipitation Intensity-Duration-Frequency Curves for the Dallas–Fort Worth Metroplex, Texas, USA

Extreme precipitation has become more frequent and intense with time and space. Infrastructure design tools such as Intensity-Duration-Frequency (IDF) curves still rely on historical precipitation and stationary assumptions, risking current and future urban infrastructure. This study developed IDF curves by incorporating non-stationarity trends in precipitation annual maximum series (AMS) for Dallas–Fort Worth, the fourth-largest metropolitan region in the United States. A Pro-NEVA tool was used to develop non-stationary IDF curves, taking historical precipitation AMS for seven stations that showed a non-stationary trend with time as a covariate. Four statistical indices—the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Root Mean Square Error (RMSE), and Nash–Sutcliffe Efficiency (NSE)—were used as the model goodness of fit evaluation. The lower AIC, BIC, and RMSE values and higher NSE values for non-stationary models indicated a better performance compared to the stationary models. Compared to the traditional stationary assumption, the non-stationary IDF curves showed an increase (up to 75%) in the 24 h precipitation intensity for the 100-year return period. Using the climate change adaptive non-stationary IDF tool for the DFW metroplex and similar urban regions could enable decision makers to make climate-informed choices about infrastructure investments, emergency preparedness measures, and long-term urban development and water resource management planning.

RAINFALL ANALYSIS FOR CREATING INTENSITY-DURATION-FREQUENCY (IDF) CURVE OF PONTIANAK CITY

Pontianak is a lowland area prone to flooding if it rains with high rainfall intensity. Analysis of the planned flood discharge is needed to overcome the flood problem. The design flood discharge analysis can be calculated using the rational method, which requires rain intensity data in terms of duration and frequency, which can be described as an IDF curve.This research was conducted by calculating the average daily maximum rainfall after conducting consistency and homogeneity tests on the rainfall data used and determining the selected distribution based on the results of statistical parameters. The rain design with various return periods is calculated with the desired distribution that matches Pontianak City. The rainfall intensity calculation uses the Mononobe method because the rainfall data owned is daily rainfall data.The analysis results show that the Log Pearson Type III distribution corresponds to the data distribution in Pontianak. From the IDF curve, it can be seen that high rainfall intensity lasts for a short duration; this can prove the general nature of rain that the faster the rain stays, the higher the rainfall intensity and vice versa. The IDF curve can assist in calculating the design flood discharge.