Design Rainfall Research Articles

Towards new design rainfall profiles for the United Kingdom

AbstractThe Flood Studies Report (FSR) summer and winter design profiles are a key component of rainfall design guidance in the United Kingdom (UK). We have examined the rainfall profiles of over 70,000 extreme rainfall events with the original FSR profile methodology. This analysis reveals that rainfall profiles change with rainstorm duration but not season, contradicting one of the key assumptions in current UK rainfall design guidance. By using a method that does not artificially generate symmetrical and centred profiles we show that profile shapes are highly variable and strongly related to event duration and magnitude. Short events tend towards front‐loaded profiles, while heavy long‐duration events tend towards centred profile shapes. Finally, manual, automatic and mixed methods of deriving new design profiles for use in the UK were trialled, with consistent results. These could be used to derive new design profiles to supersede the FSR profiles. Notably, peak intensities in observed profiles and trialled summary profiles often exceeded those found in both FSR profiles. We conclude that current design profile guidance for the UK fails to account for the observed variability in event profile shapes and peak intensities and may lead to significant under‐ or over‐design of flood risk management solutions.

Derivation of long duration geographically-centred areal reduction factors for catchment design rainfall estimation in South Africa

Study regionSouth Africa. Study focusThe use of Areal Reduction Factors (ARFs) to convert average design point rainfall into areal catchment design rainfall is regarded as fundamental input to event-based deterministic design flood estimation methods. The ARF methods currently used in South Africa are outdated and were neither developed nor verified using local data. This paper presents the development and assessment of a regionalised approach to estimate long duration (≥ 1-day) geographically-centred ARFs using daily rainfall data representative of the 78 homogeneous long duration rainfall clusters associated with the Regional Linear Moment Algorithm and Scale Invariance (RLMA&SI) regionalisation scheme in South Africa. In order to meet the recommended World Meteorological Organisation rainfall station density criteria, the latter clusters were merged into 46 clusters. Subsequently, long duration geographically-centred sample ARFs were estimated using 2 053 circular catchments and 1 779 daily rainfall stations. New hydrological insights for the regionFive ARF regions were deduced from the 46 clusters and a single regional empirical ARF equation, with unique regional calibration coefficients, was derived. The ARF methodology developed and the subsequent findings are not only new to the South African flood hydrology community and practice, but are also probabilistically correct given that the ARF estimates decrease with an increasing catchment area and decrease with a decreasing storm duration and return period, unlike many other methods used internationally.

Research on rainfall prediction based on RBF neural network model and stormwater inundation risk in scenic areas: A case study of the Yesanpo Scenic Area, Baoding, China

Research on stormwater inundation risk and rainwater management in scenic areas has a lot to do with rainfall during the flood season. When the measured rainfall data is limited, an artificial network model with nonlinear mapping capability can be applied to predict rainfall data during the flood season, which increases the sample size of rainfall data and improves the accuracy of research results. Based on a radial basis function (RBF)neural network model, this paper takes the Yesanpo Scenic Area in Baoding City, Hebei Province as an example to estimate the monthly maximum rainfall data during the flood season (July–September) of 2022, 2023, and 2024 in the study area. On this basis, the Pearson III frequency curve is used to calculate the design rainfall corresponding to the rainfall frequency of 20%, 5%, and 2%. With the help of SCS-CN model and ArcGIS spatial analysis tools, the stormwater inundation areas are simulated in the study area, which are divided into three risk levels: high, medium, and low, providing a reference for the stormwater management in the Yesanpo Scenic Area.

Analysis of Annual Rainfall Distribution and Planned Rain Intensity at 11 (Eleven) Rain Post Stations in Serang District

This research aimed to find the best rainfall probability model and planned rain intensity using the Mononobe formula for 11 rain stations in Serang Regency. Annual rainfall data is processed and evaluated as secondary data using the rain data consistency test method, the Gumbel probability distribution, the Normal probability distribution, the Log Normal probability distribution, and the Pearson Type III Log probability distribution. The consistency test results reveal that the rainfall data is consistent. The Gumbel probability distribution is used to examine the design rain intensity based on the analysis. This study is intended to guide estimating the design rainfall intensity to develop the design flood discharge and run-off calculations. Suggestions for future research include improving the accuracy of rain data processing and making longer-term data available to provide a more accurate frequency analysis

Derivation of nonstationary rainfall intensity-duration-frequency curves considering the impacts of climate change and urbanization

Urban infrastructure traditionally relies on stationary rainfall intensity-duration-frequency (IDF) curves. However, this assumption is challenged by climate change and urbanization. Many studies tried to update IDF using time covariate which lacks physical significance. More importantly, the stationary (ST) design method is not applicable for nonstationary (NS) design where the distributions of extreme precipitation change over time. For the annual maximum precipitation (AMP) in Beijing, we utilized local factors (urbanization and temperature) and global factors (ENSO and EASM etc.) to develop NS models, with the average annual reliability method first employed to update the IDF curves. Short-duration (shorter than 6-h) AMP of most stations show upward trends, whereas the AMP with longer durations exhibits downward trends. The NS modeling reveals that the 18-h AMPs is mainly affected by global processes (ENSO and EASM). The predictive accuracy of the optimal NS model outperforms ST model by a remarkable 219% during the validation period. In addition, the ST design rainfall tends to overestimate rainfall for durations longer than 12-h. Interestingly, the gap between NS and ST design uncertainties diminishes as duration/return period expands. The above findings provide new insights about impacts of local and global physical processes on the variation of extreme rainfall.

Impact and analysis of urban water system connectivity project on regional water environment based on Storm Water Management Model (SWMM)

SWMM stands as a dynamic rainfall-runoff urban hydrological model, crafted by the U.S. Environmental Protection Agency. It adeptly replicates urban rainfall production and ground runoff, and the Pressure-State-Response (PSR) theory artfully reflects human-environment interactions. Urban Water System Connectivity (UWSC) fortifies connections among regional rivers, transforming them into an intricate, dense network. To study the improvement of the regional water environment by the UWSC project, this study takes the UWSC project in Runan County, Zhumadian, China as the research object, constructs a hydrodynamic and water quality model based on SWMM, and simulates it under different rainfall situations. At the same time, the ecological service value theory and PSR theory are used to establish an ecological effect index system to analyze the ecological effect before and after the UWSC project. This paper evaluates the urban water system connectivity project from three aspects: hydrodynamic, water quality, and ecological effects. Results underscore that the post-UWSC era witnesses decreased river flood flows in varied design rainfalls, accompanied by delayed flood peaks. Under P = 10a and P = 20a rainfalls, peak flow reductions of 6.6% and 4.96% respectively, manifest with peak time lags of 0.17h. Flow rate adjustments align with flow behavior, exhibiting decreased peak flow rates accompanied by temporal lags. Initial river flow increases by about 30%, amplifying river water body exchange capacity. Following the UWSC implementation, the study area's five primary rivers display TSS reductions ranging from 46% to 86.94%, COD from 36.98% to 92.43%, TN from 45.9% to 92.96%, TP from 35.71% to 84.78%, and NH3–N from 38.52% to 92.19%. Simulated point source pollution, under comparable initial conditions, indicates pollutant decay rates escalating from 3.2%–20%–35.71%–92.43%. Ecological impact ascends from 6.33 × 108 RMB to 9.65 × 108 RMB, reflecting a 52.5% escalation. The UWSC initiative enriches urban river flood resilience and water quality, emblematic of urban water ecological civilization progress.

The Development of Ungauged-Catchment Integrated-Similarity Unit Hydrograph to Estimate Inflow of Wonogiri Reservoir

The Wonogiri Reservoir is a multipurpose reservoir at the Upper Bengawan Solo Watershed, primarily designed to serve as a flood control system. However, there is no accurate estimation of the inflow into the reservoir due to the limited availability of hydrological stations. Observations showed only four out of ten unit hydrographs of the Wonogiri Reservoir watershed. Therefore, this study was conducted to apply an integrated similarity-based approach for designing unit hydrographs in ungauged catchments. The process involved evaluating the integrated similarity between pairs of gauged-ungauged catchments using hydrologic and physical property parameters. This led to the selection of the donor or gauged catchment with the highest similarity score to develop the unit hydrograph for the ungauged catchments. The developed UHs were further applied to estimate the reservoir inflow for the December 25, 2007, flood event. The results showed that the computed peak discharge was 10.9% lower than a previous study. Subsequently, the HEC-HMS simulation model was used to project the updated design flood hydrographs to the reservoir. The design rainfall was derived from automatic rainfall recorder (ARR) and PERSIANN satellite-based data. The ARR data showed that the extreme rainfall duration was 5 hours while satellite data indicated 6 hours. The application of the ARR 5-hour duration to the updated flood hydrographs led to a peak discharge of 5123 m3 s-1, 7041 m3 s-1, and 10,370 m3 s-1 for the 60-year, 500-year, and PMF floods respectively in line with the flood design criteria of Wonogiri Reservoir. These estimates were observed to be significantly higher than the 1982 design floods which were 4000 m3 s-1, 5100 m3 s-1, and 9600 m3 s-1 respectively. This updated flood control design was important to renew the operation rule of the Wonogiri reservoir during flood periods.

Coastal and River Embankment Performance at Cengkareng Drain Estuary Under Compound Hazards Conditions Using HEC-RAS 2D

Jakarta is prone to pluvial, fluvial, and coastal flooding due to its geographical location and topography. In response to this problem, the Indonesian government has implemented several master plans, including the National Capital Integrated Coastal Development (NCICD). This ongoing program encompasses the construction of coastal and river embankment that stretch all over the coast of Jakarta. Since many coastal areas in Jakarta are residential or industrial, evaluating this performance of embankment has become crucial for effective flood management. The findings of this research can also support the development of other locations where NCICD embankment plan and enhance coastal resilience. Therefore, this research assessed the effectiveness of coastal and river embankment at Cengkareng Drain, a vital floodway in Jakarta, during extreme events that occur simultaneously. To simulate flooding events, two-dimensional HEC-RAS features were used to numerically calculate the area and depth of inundation. The simulation required geometry, terrain, land cover, and unsteady flow data. For the flow boundary conditions, a 100-year design rainfall, HHWL (Highest High Water Level), and 100-year design wave were considered to represent estuary conditions accurately. The simulation result showed that the maximum water level influenced by these factors was +3.145 mMSL, while the planned embankment top elevation was +3.40 mMSL. Furthermore, without the NCICD embankment, the simulation showed an inundation area of 1212.37 ha, which was reduced to 1111.22 ha after their implementation, leading to a decrease of 101.15 ha. This reduction significantly decreases potential damage to property and infrastructure, particularly in densely populated areas. The simulation also showed a reduction of 86.49 hectares or 66.22% in the inundation area with a depth exceeding 1 meter. These findings demonstrate the effectiveness of embankment in reducing the inundation area without any overtopping incidents.

Implementation of a probability matching method in developing intensity–duration–frequency relationships for sub-daily durations using IMERG satellite-based data

ABSTRACT Reliable estimation of design rainfall in time and space can play a significant role in reducing flood-related losses. However, many parts of the world suffer from a lack of dense raingauge networks. Under this condition, the use of satellite-based data can be an alternative solution. In this research, using data from a dense ground-based raingauge network and Integrated Multi-satellitE Retrievals for GPM (IMERG) satellite-based precipitation product, the performance of a probability matching method for satellite-based extreme values has been investigated. The results indicate that the correction model, especially at shorter durations, is able to reduce the error of extreme values of raw satellite-based estimates, and its performance is not affected significantly by the density of the available raingauge network. In conclusion, implementation of the proposed method in poorly gauged regions can play an effective role in providing a reliable estimate of the design rainfall and eventually reducing the financial losses caused by floods.

Impact of Different Design Rainfall Pattern Peak Factors on Urban Flooding

In order to investigate the influence of different design rainfall peaks on urban flooding characteristics based on the MIKE hydrodynamic model, the inundation process scenarios were extrapolated for different recurrence periods and three single- and double-peak rainfall types in Zhoukou city as an example, and the equivalent values of total inundation and inundation area were compared and analysed. The results show that bimodal rainfall has a higher risk of inundation than unimodal rainfall for the same rainfall ephemeris and return period. For unimodal rainfall, when the return period is less than 20 years, the more advanced the rainfall peak, the more severe the design rainfall inundation. When the return period is greater than 20 years, the further back the rainfall peak, the more severe the inundation of the design rainfall. The difference between the risk of inundation due to single- and double-peaked rainfall decreases as the return period increases.

Exploring the relationship between urban flood risk and resilience at a high-resolution grid cell scale

The assessment of flood risk and resilience has become increasingly important in recent years for effective urban flood management. While flood resilience and risk are two distinct concepts with unique assessment metrics, there is lack of quantitative analysis and understanding of the relationship between them. This study aims to investigate this relationship at the grid cell level in urban areas. To assess flood resilience for high-resolution grid cells, this study proposes a performance-based flood resilience metric, which is calculated using the system performance curve based on flood duration and magnitude. Flood risk is calculated as the product of maximum flood depth and probability, considering multiple storm events. The case study of Waterloo in London, UK is analyzed using a two-dimensional cellular automata-based model CADDIES, which consists of 2.7 million grid cells (5 m × 5 m). The results indicate that over 2 % of grid cells have risk values exceeding 1. Furthermore, there is a 5 % difference in resilience values below 0.8 between the 200-year and 2000-year design rainfall events, specifically 4 % for the former and 9 % for the latter. Additionally, the results reveal a complex relationship between flood risk and resilience, though decreasing flood resilience generally leads to increasing flood risk. However, this relationship varies depending on the land cover type, with building, green land, and water body cells showing higher resilience for the same level of flood risk compared to other land uses such as roads and railways. Classifying urban areas into four categories, including high risk vs. low resilience, high risk vs. high resilience, low risk vs. low resilience, and low risk vs. high resilience, is crucial in identifying flood hotspots for intervention development. In conclusion, this study provides an in-depth understanding of the relationship between risk and resilience in urban flooding, which could help improve urban flood management. The proposed performance-based flood resilience metric and the findings from the case study of Waterloo in London could be valuable for decision-makers in developing effective flood management strategies in urban areas.

Investigating the Reliability of Stationary Design Rainfall in a Mediterranean Region under a Changing Climate

Extreme rainfall events have been more frequent in recent decades, potentially as a climate change effect. This has been leading to a higher risk of the failure of existing hydraulic infrastructures, and to a higher awareness regarding the unreliability of design rainfall calculated with reference to historical data recorded in the last century. With this in mind, the present study questions the stationary assumption of the rainfall Depth–Duration–Frequency curves commonly used in Sicily, the biggest island of the Mediterranean Sea. Quantiles derived from the most up-to-date regional method, regarding Sicily, based on observations in the period 1928–2010, have been compared with those extracted from a high-resolution dataset related to the period 2002–2022, provided by the SIAS agency. The results showed a remarkable underestimation of the rainfall quantiles calculated with the regional approach, especially at the shortest durations and low return periods. This means that new hydraulic works should be designed with reference to longer return periods than in the recent past, and those that currently exist may experience a higher risk of failure. Future investigation of this aspect is crucial for enhancing the effectiveness of water management and detecting hydrological risks under a changing climate.

Benchmarking Three Event-Based Rainfall-Runoff Routing Models on Australian Catchments

In the field of hydrology, event-based models are commonly used for flood-flow prediction in catchments, for use in flood forecasting, flood risk assessment, and infrastructure design. The models are simplistic, as they do not consider longer-term catchment processes such as evaporation and transpiration. This paper examines the relative performance of two widely used models, the American HEC-HMS model, the Australian RORB model, and a newer model, the RRR model. The evaluation is conducted on four case study catchments in Australia. The first two models, HEC-HMS and RORB, do not include baseflow, necessitating the estimation of baseflow through alternate means. By contrast, the RRR model includes baseflow, by extracting a separate loss from the rainfall, and then routing the resultant flow through the catchment, much like quickflow, but with a longer delay time. The models are calibrated and then verified with weighted mean parameter values on an independent set of events in each case study catchment. This gives an indication of the ability of the models to correctly predict flow, which is important when the models are used with design rainfalls to predict design flows. The results demonstrate that all models perform adequately on the four examined catchments, but the RRR model exhibits superior calibration, and, to a lesser extent, better validation compared to the other two models.

Hydrologic Design of Soil and Water Conservation Structures Using Probability Analysis and Machine Learning Techniques in Saurashtra Region of Gujarat, India

The soil and water conservation structures are constructed to overcome water scarcity as a result of interannual rainfall variability and paucity of the perennial source of water. The present study was aimed to estimate the design runoff for the efficient hydrologic design of various soils and water conservation structures using machine techniques for enabling efficient harvesting of available rainfall with economical design which can support in developing climate resilience for the Saurashtra region of Gujarat, India. The design rainfall at various return periods was predicted by Annual One Day Maximum Rainfall (ADMR) using three technics i.e. Probability Distribution Fitting, Artificial Neural Network (ANN) and Gaussian Process Regression (GPR) for 11 stations. Various goodness of fit tests revealed that ADMR was efficiently predicted by log-logistic (3P) distribution for six stations, generalized extreme value distribution for two stations and lognormal (3P), gamma (3P) and lognormal distribution for one station each. Among ANN and GPR, the performance indicators revealed that GPR has shown a higher capability to predict ADMR as compared to ANN with correlation coefficient ranging from 0.97 to 0.99, mean absolute error from 15 mm to 411 mm and root mean squared error from 40 mm to 494 mm for various stations. The design runoff estimation was demonstrated based on predicted ADMR for return periods suitable for various soil and water conservation structures like field bunding, terrace outlets and vegetative outlets, field diversion, permanent masonry gully control structures, earthen dam, etc. using SCS-Curve Number method for curve number 70 and 85. The study is useful for researchers, planners and engineers to implement the economical, efficient and safe design of various soil and water conservation structures.

Assessment of the drainage systems performance in response to future scenarios and flood mitigation measures using stormwater management model

Urban Flooding represents a significant problem in developing urban areas caused by inadequate stormwater drainage systems, increased impervious surface areas, and climate change. The performance of drainage systems can be evaluated using simulation models such as the stormwater management simulation model (SWMM). In this study, the potential impacts of future design rainfall on the performance of stormwater management systems were assessed by altering a hyetograph derived from rainfall intensity duration curves from three climate models. In addition, the effects of continued urbanization on the systems have been simulated by changing the percentage of imperviousness from current land use conditions. According to the findings, existing drainage systems cannot manage the expected flooding risks caused by a slight change in future rainfall intensity under each climate model. As a result of urban development, increasing the imperviousness ratio from 10% to 70% has increased peak runoff from 51.3 to 82.4 m3/s, flooding volume amplified from 24,320.5 x103 to 33,647.4 x103 m3 (representing 38.4% of the increase), and flooded nodes risen from 64 to 196 (representing 67.12% of raise). Overall, flooding locations and magnitude were identified, while drainage systems failed to safely convey surface runoff at baseline conditions, implying that future flooding will be more intense. As a result, selected mitigation strategies should be considered to alleviate the flooding risks that disrupt the socio-economic environment and the resulting significant property and life losses in Dodola, Ethiopia.

Mapping of Design Rainfall at Multiple Return Periods Using Spatial Interpolation in Abab Sub-Watershed, Blitar Regency

Mapping of Design Rainfall at Multiple Return Periods Using Spatial Interpolation in Abab Sub-Watershed, Blitar Regency

THE SEROK RIVER CATCHMENT FLOOD HYDROGRAPH

Global climate change is expected to cause an increase in the intensity and duration of extreme rainfall events that occur today. The leading cause of flooding in various world regions, including flat coastal areas such as the Serok River catchment in Kota Pontianak, influenced by tides, is excessive rainfall. This article presents the results of an analysis of the impact of extreme precipitation on the peak discharge of flood hydrographs in the Serok River catchment, Kota Pontianak.Maximum daily rainfall data for 2009-2020 recorded at PTK-11 Pontianak Station were selected using the Annual Maximum Series Method. Frequency analysis was conducted using the best distribution method selected from Normal, Log Normal, Log Pearson Type III, and Gumbel Type I to obtain the design rainfall. The design rainfall was transformed into flood hydrographs at the next stage using the Snyder Synthetic Unit Hydrograph based on several return periods.The results of the analysis show that there are changes in flood discharge in the Serok River catchment area for each return period. The location of land use and the value of rain intensity significantly affect the calculation of plan discharge; the more significant the land area and the higher the rain intensity, the greater the resulting release. The most considerable flood discharge (Qmax) in the 2, 5, and 10 years return occurs at STA 1 + 100, w.290 m3/s, 0.347 m3/s, and 0.377 m3/s, respectively. Thus, this causes periodic flooding/inundation conditions, especially in areas that have low elevations.

Derivation of short-term design rainfall intensity from daily rainfall data for urban drainage design using empirical equations in robe town, Ethiopia

Flooding is a significant impact that regularly affects the majority of cities/towns in developing countries due to inadequate drainage systems that were designed without considering hydrological-hydraulic efficiency caused by design rainfall intensity. Design rainfall intensity is essential to urban stormwater management systems; however, obtaining long-term, short-term design rainfall in developing countries such as Ethiopia is challenging. As a result, this study is conducted to derive short-term design rainfall intensity from daily rainfall data for Robe town using three empirical equations for urban drainage design: Indian Meteorological Method (IMD), Modified Indian Meteorological Method (MIMD), and Ethiopian Road Authority Method (ERAM). The results show that the estimated design rainfall by IMD is greater than other methods; the relationship between IMD, MIMD, ERAM, and existing ranges from 0.57 to 1.001, 1.015 to 1.218, and 0.890 to 1.027, respectively. According to the findings of this study, the design rainfall intensity of all empirical equations is not the same in all return periods and durations. Furthermore, the peak stormwater that caused flooding will vary due to variations in rainfall intensity. Thus, this study strongly suggested that the experts consider each empirical equation and select the accurate design rainfall to design adequate stormwater drainage systems for Robe Town. To manage unexpected urban inundation caused by urban development, short-duration design rainfall and other sub-catchment characteristics will need to be considered.

Impact of Urbanization on Regional Rainfall-Runoff Processes: Case Study in Jinan City, China

Rapid urbanization has altered the regional hydrological processes, posing a great challenge to the sustainable development of cities. The TVGM-USWM model, a new urban hydrological model considering the nonlinear rainfall-runoff relationship and the flow routing in an urban drainage system, was developed in this study. We employed this model in the Huangtaiqiao drainage basin of Jinan City, China, and examined the impact of land cover changes due to urbanization on rainfall-runoff processes. Two urbanization scenarios were set up in the TVGM-USWM model during the design rainfall events with different return periods. Results showed that (1) the TVGM-USWM model demonstrated good applicability in the study area, and the RNS values of the flood events are all greater than 0.75 in both calibration and validation periods; (2) the proportion of impervious areas increased from 44.65% in 1990 to 71.00% in 2020, and urbanization played a leading role in the process of land cover change and manifested itself as a circular extensional expansion; and (3) urbanization showed a significant amplifying effect on the design flood processes, particularly for relatively big floods with small frequency, and the impact of urbanization on the time-to-peak of the design flood gradually decreased as the frequency of the design rainfall decreased. The results of this study can provide technical support for flood mitigation and the construction of a sponge city in Jinan City.

Estimation of daily design rainfall in Argentina from satellite-derived data

Se presentan los resultados de la estimación de las precipitaciones diarias de diseño en Argentina para el 97 % del territorio nacional continental. Este análisis se basó en el procesamiento de los datos de precipitación derivados de satélite (DPDS) del producto CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data), con una resolución espacial de 5 km y una cobertura temporal de 37 años. La extracción de los mapas de precipitación diaria máxima anual (pdMa) se efectuó por medio de códigos ad hoc desarrollados a través de la plataforma Google Earth Engine. Se compararon las series de pdMa provenientes de CHIRPS con las obtenidas a partir de 64 estaciones pluviométricas provistas por el Servicio Meteorológico Nacional (SMN), determinando las pendientes de la regresión lineal. Estos parámetros de la regresión fueron interpolados al territorio bajo estudio para corregir los mapas de pdMa. Los mapas corregidos se procesaron a través de códigos desarrollados en Python para asociar probabilidades empíricas de no excedencia y ajustar la distribución teórica óptima de probabilidades a cada uno de los 106 778 pixeles considerados. A partir de estos resultados se generaron mapas de precipitaciones diarias de diseño para periodos de retorno comprendidos entre 2 y 100 años. Los resultados se validaron contra 30 estaciones provenientes del Sistema Nacional de Información Hídrica, obteniéndose un acuerdo aceptable. Se considera que los resultados obtenidos serán de utilidad en tareas de diseño hidrológico, en especial en las regiones que carecen de registros pluviométricos adecuados para un análisis estadístico tradicional.