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Accurately estimating peak discharge and flood volume in small and data-deficient basins within larger watersheds is crucial for effective flood planning and management. This study focuses on the Kamalvand Central Site and the Faculty of Agriculture and Natural Resources (FANR) at Lorestan University to determine maximum flow and flood volume. This estimation is achieved by applying the SCS-CN method, utilizing rainfall patterns generated by the fractal method within the HydroCAD software environment. Flow measurements were taken during precipitation events on December 18, 2021 (39 mm of precipitation) and January 03, 2022 (29 mm of precipitation) for the FANR basin and Sub-basin 2 of the Kamalvand site to validate the rainfall-runoff model. The results from the SCS-CN model were compared with empirical methods, such as Fuller and Creager, to assess its performance. The results showed that the fractal method could accurately estimate precipitation duration and return periods. In addition, the IDF of this method, compared with Ghahraman, showed low RMSE in the period of low returns (from 2 to 100 years). The relationship between the scale exponent and weighted moment order for all stations was linear and statistically significant at the 1% level. The highest peak flow and runoff volume in the FANR Basin belong to Sub-basin 1, measuring 22.35 m3/s and 1,32,000 m3 for a 25-year return period, respectively. Furthermore, the highest values for these variables in the Kamalvand basin are associated with Sub-basin 2, which covers an area of 237 hectares and has a curve number of 80, with a concentration–time of 18.4 min. In this context, peak flow and flood volume for the 25-year return period were estimated at 23.49 m3/s and 54,540 m3, respectively. Flow measurement results from both basins indicated the accuracy of the SCS-CN model in simulating and estimating flow, with correlation coefficients of 0.88 and 0.94 and Nash–Sutcliffe coefficients of 0.74 and 0.52 for the Kamalvand and FANR basins, respectively. Moreover, the results demonstrated the high performance of the SCS-CN model in estimating peak flow based on designed rainfall patterns using the fractal method and utilizing the curve number obtained from Sentinel 2 imagery within the HydroCAD software environment, compared to empirical methods like Fuller and Creager, for return periods of 25, 50, and 100 years. Therefore, this rapid and practical approach is recommended for other ungauged basins. [ABSTRACT FROM AUTHOR]

Various empirical methods have evolved over the years in South Africa to estimate either design floods, design rainfall, catchment response time, and/or Areal Reduction Factors (ARFs). The verification of any empirical method requires the use of observed data not used during the calibration process, while observed data is also required for validation purposes. In the case of ARFs, which are used to convert average design point rainfall depths to an areal (catchment) design rainfall depth, all the calibration/verification data sets remain only estimated sample values of design rainfall. Subsequently, this paper presents an independent application and validation of the regional geographically-centred ARF method (Pietersen 2023) against the currently recommended geographically-centred ARF method (Alexander 2001) by incorporating the different ARF estimates into the Rational Method (RM) to highlight the impact thereof on the resulting flood estimates. In applying a ranking-based goodness-of-fit selection procedure, the RM in combination with the newly derived regional geographically-centred ARF method (Pietersen 2023) resulted in the best deterministic flood estimates when compared to the at-site statistical flood peaks. Apart from the ARFs, catchment response time, design rainfall, and weighted runoff coefficients are all regarded as key input parameters for design flood estimation in ungauged catchments. [ABSTRACT FROM AUTHOR]

Areal Reduction Factors (ARFs) are used to convert average design point rainfall depths to an areal (catchment) design rainfall depth to serve as primary input to estimate the design flood associated with a specific storm duration and return period. This paper presents the development and critical evaluation of a stand-alone software interface to estimate regional, geographicallycentred ARFs using the methodology developed by Pietersen (2023). By considering standard input variables in a range of catchment areas, the application of the ARF software demonstrated that it is an easy-to-use software tool for the rapid estimation of ARFs in both gauged and ungauged catchments, and with the aid of the default and combined algorithm, geographically-centred ARFs which vary with return period can be estimated. Given that the other geographically-centred ARF methods reviewed in this paper do not take return periods into account and have not been validated using local and up-to-date rainfall data applicable throughout South Africa (SA), it is recommended that the ARF software be incorporated as the standard estimation procedure for long duration (≥ 24-hour), geographically-centred ARFs in SA. In addition, the proposed methodology and ARF software should also be further validated for short (< 24-hour) and long (≥ 24-hour) durations by applying it to actual catchments distributed throughout SA and subjected to different rainfall-producing mechanisms. [ABSTRACT FROM AUTHOR]

The occurrence of rainfall is significantly affected by climate change around the world. While in some places this is likely to result in increases in rainfall, both winter and summer rainfall in most parts of New South Wales (NSW), Australia are projected to decrease considerably due to climate change. This has the potential to impact on a range of hydraulic and hydrologic design considerations for water engineers, such as the design and construction of stormwater management systems. These systems are currently planned based on past extreme rain event data, and changes in extreme rainfall amounts due to climate change could lead to systems being seriously undersized (if extreme precipitation events become more common and/or higher in magnitude) or oversized (if extreme rainfall events become less frequent or decrease in magnitude). Both outcomes would have potentially serious consequences. Consequently, safe, efficient, and cost-effective urban drainage system design requires the consideration of impacts arising from climate change on the approximation of design rainfall. This study examines the impacts of climate change on the probability of occurrence of daily extreme rainfall in New South Wales (NSW), Australia. The analysis was performed for 29 selected meteorological stations located across NSW. Future design rainfall in this research was determined from the projected rainfall for different time periods (2020 to 2039, 2040 to 2059, 2060 to 2079, and 2080 to 2099). The results of this study show that design rainfall for the standard return periods was, in most cases, lower than that derived employing the design rainfall obtained from the Australian Bureau of Meteorology (BoM). While most of the analysed meteorological stations showed significantly different outcomes using the climate change scenario data, this varied considerably between stations and different time periods. This suggests that more work needs to be performed at the local scale to incorporate climate change predicted rainfall data into future stormwater system designs to ensure the best outcomes. [ABSTRACT FROM AUTHOR]

Land use and climate change studies have emerged as a critical component of current natural resource management and environmental monitoring strategies. Remote sensing and geographic information systems (GIS) have proven to be instrumental in assessing and analysing changes in land use and land cover (LULC) and understanding the climate dynamics. In this study, a decadal analysis of annual maximum rainfall, LULC changes, and in turn, design runoff, is carried out to investigate the impact of the above factors on extreme events in the tropical basins of India. To this end, daily rainfall data from the year 1980 to 2019, LULC maps of 1985, 1995, 2005, and 2015 for four catchments of Mahanadi Basin and six catchments of Godavari Basin are utilized to estimate 50-year, 100-year and 200-year design rainfall, and in turn, design runoff, from four different decades, viz, 1980–89, 1990–99, 2000–09 and 2010–19. The design rainfall is estimated after fitting suitable distributions on the respective decadal rainfall series while the design runoff is estimated using the popular Natural Resources Conservation Service-Curve Number (NRCS-CN) method. Results showed that the decadal mean of annual maximum rainfall series increased from 1980–89 to 1990–99 and from 1990–99 to 2000–09 in seven out of ten catchments but declined in most catchments from the period 2000–09 to 2010–19, which indicates the dynamic nature of rainfall patterns over the tropical basins and highlights the importance of considering climate dynamics for hydrologic design purposes. Also, an increase in CN values from 1985 to 2015 in most of the catchments is mainly due to increased urbanization and reduced forest lands. This indicates intensification of runoff potential, which may lead to increased flood risk, soil erosion, and water quality degradation. The inferences from the study will aid policymakers in designing appropriate policies like sustainable land use practices, rainwater harvesting, and afforestation to ensure the well-being of communities in the face of changing climate and land use. [ABSTRACT FROM AUTHOR]

Climate change impacts have the potential to alter the design rainfall estimates around the world. Decreasing trends in the summer and winter rainfall in New South Wales (NSW), Australia have already been observed due to climate variability and change. The derivation of design rainfall from historical rainfall, which is required for the design of stormwater management infrastructure, may be ineffective and costly. It is essential to consider climate change impacts in estimating design rainfall for the successful design of stormwater management infrastructure. In this study, the probability of the occurrence of daily extreme rainfall has been assessed under climate change conditions. The assessment was performed using data from 29 meteorological stations in NSW, Australia. For the evaluation of future design rainfall, the probability of the occurrence of extreme rainfall for different recurrence intervals was developed from daily extreme rainfall for the periods of 2020 to 2099 and compared with the current Australian Bureau of Meteorology (BoM) design rainfall estimates. The historical mean extreme rainfall across NSW varied from 37.71 mm to 147.3 mm, indicating the topographic and climatic influences on extreme rainfall. The outcomes of the study suggested that the future design rainfall will be significantly different from the current BoM estimates for most of the studied stations. The comparison of the results showed that future rainfall in NSW will change from −4.7% to +60% for a 100-year recurrence interval. However, for a 2-year recurrence interval, the potential design rainfall change varies from an approximately 8% increase to a 40% decrease. This study revealed that the currently designed stormwater management infrastructure will be idle in the changing climate. [ABSTRACT FROM AUTHOR]

In this work, we formulate a regionalization framework for rainfall intensity–time scale–return period relationships which is applied over the Greek territory. The methodology for single-site estimation is based on a stochastic framework for multi-scale modelling of rainfall intensity which is outlined in the companion paper. Five parameters are first fitted independently for each site and the resulting parameter variability is assessed. Following a systematic investigation of uncertainty and variability patterns, two parameters, i.e. the tail-index and a time scale parameter, are identified as constant in space and estimated using data pooling techniques. The other three parameters are regionalized over Greece by means of spatial interpolation and smoothing techniques that are assessed through cross-validation in a multi-model framework. The regionalization scheme is implemented in a sequential order that allows exploiting rainfall information both from rainfall stations with sub-daily resolution and from the more reliable network of daily raingauges. [ABSTRACT FROM AUTHOR]

This work presents a stochastic framework for the construction of rainfall intensity–time scale–return period relationships, which was applied in the recent regionalization of design rainfall curves over the Greek territory, described in a companion paper. The methodology outlined herein builds upon a widely-used mathematical framework, which has been recently revisited and upgraded, and incorporates two different versions: (a) a theoretically consistent stochastic model applicable for rainfall intensity over any scale of interest; and (b) a simplified version valid over small scales, which makes parameter estimation easier. Special attention is given to the presentation of the simplified version, which suffices for most engineering tasks. Parameter estimation approaches are presented in detail, including the K-moments framework that allows for reliable high-order moment estimation and handling of bias due to spatiotemporal dependence. [ABSTRACT FROM AUTHOR]

Copyright of Jurnal Teknologi dan Rekayasa Sumber Daya Air is the property of Brawijaya University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The runoff volume capture ratio is the primary indicator of sponge city planning. The design rainfall corresponding to the runoff volume capture ratio is very important for the sponge city planning. Based on the 30-year hydrological rainfall data of 39 cities (include Shennongjia Forestry District) in Hubei Province, the relationship between the design rainfall and the runoff volume capture ratio in Hubei Province was analyzed, and the annual runoff volume capture target and the regional division for total rainfall runoff volume capture target of cities were formed, which filled the gap in the annual total runoff control index of cities in Hubei. The relevant value suggestions will contribute to the planning and construction of sponge cities in the Province. The results showed that the runoff volume capture ratio was divided into three zones, corresponding to Zone II (80%≤α≤85%), Zone III (75%≤α≤85%) and Zone IV (70%≤α≤85%) respectively, and the design rainfall ranges were Zone II (10 mm≤H≤28.3 mm), Zone III (12.7 mm≤H≤39.5 mm), Zone IV (14.3 mm≤H≤49.0 mm) respectively. Shennongjia, Danjiangkou, Shiyan etc. are in Zone II, and 17 areas such as Xiangyang, Lichuan, Xuan' en etc. are in Zone III, Suizhou, Tianmen, Xianning, Huangshi, Xiaogan, Xiantao, Huanggang, Ezhou, Wuhan and other regions are in Zone IV. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate how different methods of determining design rainfall levels and land usage affect flood hydrographs in an urban catchment; specifically, the catchment in southern Poland. The data included daily precipitation records from 1981 to 2020 and land cover information from Corine Land Cover and Urban Atlas databases for 2006 and 2018. The analysis involved examining precipitation data, determining design rainfall levels, analyzing land usage databases, exploring the influence of design rainfall levels on hydrograph characteristics, and investigating the database's impact on these characteristics. No discernible trend in precipitation was found. The highest design rainfall values followed the GEV distribution, while the lowest followed the Gumbel distribution. Both land usage databases indicated an increasing human influence from 2006 to 2018. This study conclusively showed that the method used for estimating design rainfall and the choice of the land usage database significantly affected hydrograph characteristics. Multivariate analyses are recommended for design rainfall assessments, while the Urban Atlas database is preferred for urban catchment land usage determinations due to its detailed information. [ABSTRACT FROM AUTHOR]

A reliable estimate of the areal reduction factor (ARF), useful for implementing the upscaling procedure of point rainfall information, is of crucial relevance in many hydrological applications aimed at hydraulic structures design. Despite the availability of different methodologies in the literature, the choice of the best formulation to be applied for ARF assessment in a specific region remains an open problem. In fact, the transposition of ARF formulations to areas different from those where they were developed, even with similar geographical features, could lead to incorrect ARF estimates and relevant errors in design rainfalls, especially for short durations. In this paper, a new deterministic fixed-area approach is proposed; it relies upon an averaging procedure of the ratios between areal and local annual maximum rainfalls. The proposed approach was applied to the study area of Umbria region in central Italy, where a parametric relation expressing ARF in a wide range of rainfall duration (5–2,880 min) and areas (up to about 6,100 km2) was derived. A comparison of the proposed approach with the most widely used empirical methodologies was also performed. The methodology can be adopted in any other region where a network characterized by a minimum length of rainfall time series of 7 years and a proper spatial density of stations is available. [ABSTRACT FROM AUTHOR]

ABSTRACT The Chicago Method is one of the most common methods to determine design rainfall hyetographs for urban drainage infrastructures. Among the advantages of the method is that it is easy to apply and is based on traditional IDF equations. Nevertheless, applications to other IDF equation models presents some limitations. The aim of the present study was to adapt and apply the Chicago hyetograph method with intense rainfall equations of the LnLn type. Equations to estimate rainfall intensity before and after peak duration were presented. In addition, equations to obtain accumulated rainfall before and after peak rainfall volumes were adapted. With this information, we were able to obtain rainfall blocks for each interval of the hyetograph. The method was applied to determine the hyetograph based on the intense rainfall equation for the town of Piracicaba, São Paulo, Brazil. The equations presented here can be implemented on electronic spreadsheets or in programming routines, hence allowing Engineering professionals to apply the most adequate methods to local data.

ABSTRACT Determining hydrographs for hydraulic works projects such as dams and reservoirs requires the definition of the design rainfall hyetograph. The Chicago method stands out as one of the most used methods, with the advantage of being easy to apply. However, the dependence on traditional and updated IDF equations can be pointed out as a limitation of the method. This study aimed to adapt and apply the Chicago hyetograph method with the intense rainfall equations of the alternative model, which stands out for its ease of obtaining and updating. The equations for estimating rainfall intensities for the duration before and after the peak of the hyetograph were presented. The equations were also adapted to obtain the accumulated depths or volumes of rainfall before and after the peak of the hyetograph. This information allows us to easily obtain the rainfall blocks for each interval of the hyetograph. The method was applied to determine the hyetograph based on the maximum daily rainfall, demonstrating each calculation step. The equations presented here can be implemented in electronic spreadsheets or programming routines, allowing Engineering professionals to apply methods that are more appropriate to local data.

Copyright of Jurnal Teknologi dan Rekayasa Sumber Daya Air is the property of Brawijaya University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Jurnal Teknologi dan Rekayasa Sumber Daya Air is the property of Brawijaya University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Jurnal Teknologi dan Rekayasa Sumber Daya Air is the property of Brawijaya University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Jurnal Teknologi dan Rekayasa Sumber Daya Air is the property of Brawijaya University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Jurnal Teknologi dan Rekayasa Sumber Daya Air is the property of Brawijaya University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Short-duration rainfall data are basic inputs to many rainfall-runoff models for generating the flood hydrographs. But these data are scarce in comparison to daily data, which is abundantly available, but cannot be directly used unless disaggregated to a shorter duration. This paper adopts a simple scaling approach for disaggregation of daily design precipitation into the desired duration and the time distribution of precipitation based on 3p Beta distribution herein referred to as the scaled 3p-Beta approach. The rainfall quantiles and their temporal distribution, when used as an input to the rainfall-runoff model, generate the design flood hydrograph at the ungauged location. The Upper Baitarani Basin under Mahanadi Sub-zone (3d) of India has been selected as the test catchment. The efficacy of the proposed scaled 3p-Beta approach, and also the rational approach coupled with CWC-2p Gamma UH was verified in the test catchment for design flood computation. The findings reveal that the methodology ensures encouraging results directly derivable from the abundantly available daily rainfall data and can be applied in any ungauged catchment in a region. [ABSTRACT FROM AUTHOR]

This study evaluates the effects of climate change (CC) on runoff properties over the case study of the Qaran Talar watershed located in Iran. To consider the two main sources of uncertainty, i.e., Greenhouse Gases emission (GHG) scenarios and outputs of Atmosphere-Ocean General Circulation Models (AOGCMs), a daily rainfall time series was generated for two future periods (2021-2050 and 2070-2099) at three risk levels of 0.1, 0.25 and 0.50. 22 AOGCMs outputs following two emission scenarios (RCP4.5 and RCP8.5) were used. The results showed that the uncertainty of climate change scenarios was primarily owing to the uncertainty of GCMs outputs. Regarding the 2021-2050 period, under both emission scenarios, the increases in peak discharge and flood volume (FV) were estimated to reach 70, 50, and 30% at three risk levels of 0.1, 0.25 and 0.50, respectively, compared to the recent past period. As the current century draws to a close, the difference between the results of the two emission scenarios becomes apparent so that in the far-future period (2070-2099), the RCP8.5 scenario estimates and FV more than the RCP4.5 scenario does. Additionally, it was found that the uncertainty caused by AOGCMs was more than that by GHG emission scenarios. HIGHLIGHTS The impacts of CC on flood hydrographs were discussed.; CC leads to an increasing trend in and FV.; RCP8.5 predicted a greater increase in and FV compared to RCP4.5.; The uncertainty caused by AOGCMs is more compared to GHG scenarios.;

Copyright of Journal of Kirkuk University for Agricultural Sciences is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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.

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. [ABSTRACT FROM AUTHOR]

Areal reduction factors (ARFs) are widely used to transform the point rainfall intensity to the areal rainfall intensity in engineering practice. Inappropriate ARFs may result in an overestimate or underestimate of the areal rainfall and consequently lead to the inappropriate design of infrastructure. This study aims to explore the differences in ARFs estimated by four empirical methods and quantitatively analyze the effect of rainfall duration, area, return period, local topography, and rain gauge density on ARFs in the coastal city Shenzhen, China. The results indicate that the original fixed-area method yields more conservative (higher) ARF estimates than the other three methods, which also consider the return period with the coefficient of variation ranging from 0.014 to 0.054. Bell's method and its modified versions produced modest discrepancies in ARFs, with coefficient of variation (COV) values ranging from 0.008 to 0.023. A declining trend of ARFs with increasing return period was observed for six durations (1, 2, 3, 6, 36, and 48 h), whereas ARFs tended to increase with increasing return period for 12- and 24-h durations. Meanwhile, ARFs in mountainous areas (the east part of Shenzhen) were lower than that in the flat terrain in the west part with a maximum reduction of 0.13, which might be associated with the higher spatial variability of rainfall caused by the terrain effect. In addition, ARFs derived from the sparse rain gauge network may be overestimated compared with that from the dense network (maximum overestimation of 0.041). This study provides new insights into the relationship between ARFs and return periods, and highlights that ARFs should be further studied based on the up-to-date rainfall data to tackle the changing climate. [ABSTRACT FROM AUTHOR]

Copyright of Tecnología y Ciencias del Agua is the property of Instituto Mexicano de Tecnologia del Agua (IMTA) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The main occupation of residents who live in Abab Sub-Watershed, Blitar Regency, is as farmers in agriculture and plantations. Agriculture and plantations need rain data that have been calculated to maximize the yields to be obtained. Hydrometeorological disasters, specifically floods, often occur at this location. Therefore, research is needed on calculating design rainfall, outlined in easy-to-understand isohyet maps. The research aims to assist the planning of water structures or other hydrological research without having to recalculate or retest data from the beginning. This study's utilized return periods were 2, 5, 10, and 25 years, plotted as isohyet maps. Before calculating the design rainfall, the rainfall data had to be tested first. Calculation of design rainfall used SMADA Distrib 2.13 application and was tested with the distribution suitability test. The results of the distribution suitability test showed that Log Normal is appropriate to be used. The results of plotting the design rainfall on an isohyet map using the IDW, Kriging, and Spline methods showed that the IDW and Spline maps are smoother and not as broken as Kriging. Next, a comparative analysis of RMSE and NSE was carried out. For return periods of 2, 5, 10, and 25 years, IDW has the smallest RMSE mean value of 0.016 and the highest NSE average value of 0.9999.

Extreme rainfall has changed in frequency and intensity as a result of climate change, and its impact on nature and society is far greater than that of rainfall change. Scientifically defining extreme rainfall events and obtaining the design rainfall is of great significance to analyze the impact of climate change on extreme precipitation events. Existing definitions of extreme precipitation events have usually focused on rainfall amounts at fixed durations rather than complete events with variable durations. Using sub-daily precipitation and runoff data covering 1971–2018 from 17 stations over the Jingle sub-basin, we constructed an appropriate copula function to define extreme persistent rainfall events under bivariate analysis and obtained the rainfall process of the designed rainfall under different return periods. The results showed that (1) the joint distribution based on Copula was more accurate than the traditional univariate probability methods for identifying extreme rainfall events with a threshold of 90%. (2) The Copula joint distribution established in the basin can well calculate the designed extreme rainfall under the return periods of 100 a, 50 a, 30 a, 25 a, 10 a and 5 a. (3) The rainfall intensity duration model had a good simulation effect on the rainfall intensity duration distribution of the basin. [ABSTRACT FROM AUTHOR]

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.

A climate model is essential for hydrological designs considering climate change, but there are still limitations in employing raw temporal and spatial resolutions for small urban areas. To solve the temporal scale gap, a temporal disaggregation method of rainfall data was developed based on the Neyman–Scott Rectangular Pulse Model, a stochastic rainfall model, and future design rainfall was projected. The developed method showed better performance than the benchmark models. It produced promising results in estimating the rainfall quantiles for recurrence intervals of less than 20 years. Overall, the analysis results imply that extreme rainfall events may increase. Structural/nonstructural measures are urgently needed for irrigation and the embankment of new water resources. [ABSTRACT FROM AUTHOR]

Ombrian curves, i.e., curves linking rainfall intensity to return period and time scale, are well-established engineering tools crucial to the design against stormwaters and floods. Though the at-site construction of such curves is considered a standard hydrological task, it is a rather challenging one when large regions are of interest. Regional modeling of ombrian curves is particularly complex due to the need to account for spatial dependence together with the increased variability of rainfall extremes in space. We develop a framework for the parsimonious modeling of the extreme rainfall properties at any point in a given area. This is achieved by assuming a common ombrian model structure, except for a spatially varying scale parameter which is itself modeled by a spatial smoothing model for the 24 h average annual rainfall maxima that employs elevation as an additional explanatory variable. The fitting is performed on the pooled all-stations data using an advanced estimation procedure (K-moments) that allows both for reliable high-order moment estimation and simultaneous handling of space-dependence bias. The methodology is applied in the Thessaly region, a 13,700 km2 water district of Greece characterized by varying topography and hydrometeorological properties. [ABSTRACT FROM AUTHOR]

This study aims to explore possible distributional changes in annual daily maximum rainfalls (ADMRs) over South Korea using a Bayesian multiple non-crossing quantile regression model. The distributional changes in the ADMRs are grouped into nine categories, focusing on changes in the location and scale parameters of the probability distribution. We identified seven categories for a distributional change in the selected stations. Most of the stations (28 of 50) are classified as Category III, which is characterized by an upward trend with an increase in variance in the distribution. Moreover, stations with a downward trend with a decrease in the variance pattern (Category VII) are mainly distributed on the southern Korean coast. On the other hand, Category I stations are mostly located in eastern Korea and primarily show a statistically significant upward trend with a decrease in variance. Moreover, this study explored changes in design rainfall estimates for different categories in terms of distributional changes. For Categories I, II, III, and VI, a noticeable increase in design rainfall was observed, while Categories IV, V, and VII showed no evidence of association with risk of increased extreme rainfall.

Study Region: ChinaStudy Focus: In sponge city construction in China, rainfall data is the key to determining the rainwater source control scale. However, changes in rainfall characteristics can reduce the representativeness of the data. To obtain stable volume capture ratios (VCRs) of the annual rainfall through as little rainfall data as possible, this paper compares daily rainfall data from 159 cities in China in recent decades and finds the minimum number of years required to maintain stable VCRs under different design rainfalls. Finally, it gives the recommended observation periods (OPs) for different regions. New Hydrological Insights for the Region: For the last 35 years, the variation of daily rainfall in 75% of cities in China has been less than 0.66 mm, and the variation of skewness is less than 0.62. In general, the longer the observation period, the smaller the calculated VCR anomaly value and variation gradient will be. About 10% of cities cannot achieve stable VCRs by increasing the number of years of data. The denser urban distributed area needs larger OPs to determine the stable VCR; with the increase in design rainfall, the required OPs will also be lowered; in most cities, the VCR calculation does not require 30 years of rainfall data.

The rainfall Intensity-Duration-Frequency (IDF) relationship is one of the most commonly used tools in establishing rain intensity formulas for urban stormwater drainage design. Currently, the rain formulas being applied in Vietnam according to the design standard TCVN 7957-2008 are mostly Soviet formulas with climate parameters dating back to the 80s of the twentieth century. Therefore, it is no longer suitable for the calculation of the current stormwater drainage system, especially in the context of climate change. In this paper, we used statistical methods to process rain gauge data from 1960 to 2021 to build the IDF curve for the inner city of Hanoi (Vietnam). The results show that the new IDF curves are more suitable for the current climate situation than the IDF curves according to TCVN 7957-2008.

Rooftops cover a large percentage of land area in urban areas, which can potentially be used for stormwater purposes. Seeking adaptation strategies, there is an increasing interest in utilising green roofs for stormwater management. However, the impact of extreme rainfall on the hydrological performance of green roofs and their design implications remain challenging to quantify. In this study, a method was developed to assess the detention performance of a detention-based green roof (underlaid with 100 mm of expanded clay) for current and future climate conditions under extreme precipitation using an artificial rainfall generator. The green roof runoff was found to be more sensitive to the initial water content than the hyetograph shape. The green roof outperformed the black roof for performance indicators (time of concentration, centroid delay, T50 or peak attenuation). While the time of concentration for the reference black roof was within 5 minutes independently of rainfall intensity, for the green roof was extrapolated between 30 and 90 minutes with intensity from 0.8 to 2.5 mm/min. Adding a layer of expanded clay under the green roof substrate provided a significant improvement to the detention performance under extreme precipitation in current and future climate conditions.

Green roofs are a proven measure to increase evapotranspiration at the expense of runoff, thus complementing contemporary stormwater management efforts to minimize pluvial flooding in cities. This effect has been quantified by numerous studies, ranging from experimental field campaigns to modeling experiments and even combinations of both. However, up until now, most green roof studies consider standard types of green roof dimensions, thus neglecting varying flow length in the substrate. For the first time, we present a comprehensive investigation of green roofs that involves artificial rainfall experiments under laboratory conditions (42 experiments in total). We consider varying flow length and slope. The novelty lies especially in the consideration of flow lengths beyond 5 m and non-declined roofs. This experimental part is complemented by numerical modeling, employing the open-source Catchment Modeling Framework (CMF). This is set-up for Darcy and Richards flow in the green roof and calibrated utilizing a multi-objective approach, considering both runoff and hydraulic head. The results demonstrate that through maximizing flow length and minimizing slope, the runoff coefficient (i.e., percentage of rainfall that becomes runoff) for a 100 years design rainfall is significantly decreased: from ~30% to values below 10%. These findings are confirmed through numerical modeling, which proves its value in terms of achieved model skill (Kling-Gupta Efficiency ranging from 0.5 to 0.95 with a median of 0.78). Both the experimental data and the numerical model are published as open data and open-source software, respectively. Thus, this study provides new insights into green roof design with high practical relevance, whilst being reproducible.

Abstract Internationally, the occurrence and frequency of floods, along with the uncertainty involved in the estimation thereof, contribute to the practitioners' dilemma to make a single, justifiable decision when various design flood estimation methods are used. This article presents the further development of a Design Flood Estimation Tool (DFET) using Microsoft Visual Basic for Applications to assess the performance of event‐based design flood estimation methods in 48 gauged catchments in South Africa. The improved DFET proved to be an easy‐to‐use software tool for the rapid estimation and assessment of at‐site design floods in both gauged and ungauged catchments. In using a ranking‐based selection procedure, the Soil Conservation Service, Alternative Rational and Catchment Parameter methods provided the best estimates of the at‐site probabilistic flood peaks, while the Standard Design Flood method proved to be the least appropriate. Since the accuracy and uncertainty associated with each design flood method's key input parameters are unknown when applied in ungauged catchments, the incorporation of an ensemble event approach as part of the DFET calculation routines, is recommended. This will ensure that the key input parameters from an expected range of values are used to achieve probability neutrality between input rainfall and estimated runoff.

Internationally, the occurrence and frequency of floods, along with the uncertainty involved in the estimation thereof, contribute to the practitioners' dilemma to make a single, justifiable decision when various design flood estimation methods are used. This article presents the further development of a Design Flood Estimation Tool (DFET) using Microsoft Visual Basic for Applications to assess the performance of event‐based design flood estimation methods in 48 gauged catchments in South Africa. The improved DFET proved to be an easy‐to‐use software tool for the rapid estimation and assessment of at‐site design floods in both gauged and ungauged catchments. In using a ranking‐based selection procedure, the Soil Conservation Service, Alternative Rational and Catchment Parameter methods provided the best estimates of the at‐site probabilistic flood peaks, while the Standard Design Flood method proved to be the least appropriate. Since the accuracy and uncertainty associated with each design flood method's key input parameters are unknown when applied in ungauged catchments, the incorporation of an ensemble event approach as part of the DFET calculation routines, is recommended. This will ensure that the key input parameters from an expected range of values are used to achieve probability neutrality between input rainfall and estimated runoff. [ABSTRACT FROM AUTHOR]

Many hydrologic and hydraulic (H&H) engineering applications require spatial rainfall distribution over a watershed, but point precipitation frequency estimates, such as those provided by NOAA Atlas 14, are only applicable for relatively small areas. For larger areas, areal reduction factors (ARFs) are commonly used to transform a point precipitation frequency estimate of a given duration and frequency to a corresponding areal estimate. The most common source of ARFs for the United States is Technical Paper 29 (TP-29), published in 1958, although there have been significant increases in record length and types of available data and several new methods for computing ARFs have been proposed over the last several decades. This study applied up-to-date precipitation data products and analysis methods with a watershed-based approach to investigate factors that affect ARF variabilities, and to compare ARFs across multiple US hydrologic regions. Our overall findings are in line with other recent studies showing that ARFs decrease with increasing area, increase with increasing duration, and decrease with increasing return period. In particular, we found a strong geographical variability across different US hydrologic regions, suggesting that ARF are specific to regional climate patterns and geographical characteristics and should not be applied arbitrarily to other locations. The results also reveal the importance of record length, especially for long return period ARFs. The study demonstrates the need to improve ARFs with new data and methods to support more reliable areal precipitation frequency estimates for H&H applications.

Abstract Data on intensity–duration–frequency or design rainfall are one of the most important information required for various hydrological and water resources studies. However, such crucial data are often unavailable in various parts of the world due to lack of enough rain gauging stations. It is not only tedious to determine design rainfall from the raw data but also occasionally impossible to calculate due to lack or absence of short-duration rainfall data. Generally, the manual rain gauges outnumber the automatic gauges, making it difficult to have adequate data on short-duration rainfall values, which is very important for urban hydrology. However, no graphical or mathematical relation could be found in the literature, which can be used for quick estimation of short-duration design rainfall from the daily rainfall data recorded by the manual stations. Annual maximum rainfall data from 143 rain gauging stations located at Klang Valley in Malaysia were used in this study. Statistical analyses and logarithmic graph fitting techniques were used to develop excellent correlation between short-duration rainfall and daily rainfall values for 96 automatic and 46 manual stations. Rainfall data analyze the design rainfall data of various duration and return periods. The 15, 30 and 45 min of short-duration rainfall, which is the most common rainfall duration in the study area, was observed to be 32.4%, 47.1% and 57.4% of the daily rainfall amount, respectively. The amount of rainfall during 1-, 2- and 3-h storm events contribute 64.9%, 76.5% and 80.9% of the daily rainfall. Such relations can be used for quick estimation of short-duration rainfall resulting in saving time, money and other resources.

Projection of extreme rainfall under climate change remains an area of considerable uncertainty. In the absence of geographically consistent simulations of extreme rainfall for the future, alternatives relying on physical relationships between a warmer atmosphere and its moisture carrying capacity are projected, scaling with a known atmospheric covariate. The most common atmospheric covariate adopted is surface air temperature, as it exhibits great consistency across climate model simulations into the future and, as per the Clausius‐Clapeyron relationship, has a well‐established link to atmospheric moisture capacity. However, empirical assessments of this relationship show that it varies with latitude, surface temperature, atmospheric temperature, and other factors, suggesting there may be more stable "global" atmospheric covariates that could be used instead. We argue that a better‐suited covariate would be one that captures the relationship between extreme rainfall and temperature but exhibits greater consistency in the relationship across regions as well as climatic zones. Our analysis identifies plausible atmospheric indicators of changes to future extreme rainfall, which now proliferate literature and compare their suitability based on the variability they exhibit across multiple geographical, topographic, and climatic zones within Australia. It is shown that surface air temperature exhibits a regionally inconsistent relationship with extreme rainfall and hence is not suitable for projecting to future conditions. The study identified integrated water vapor and surface dew point temperature as promising alternatives, with the former showing greater consistency in space but at the cost of reduced temporal coverage. Plain Language Summary: Studies of extreme rainfall sensitivity to temperature (termed scaling) improve our understanding of how extreme rainfall can be expected to change under global warming. The widespread and intuitive use of surface air temperature in rainfall scaling studies is likely the result of its observational availability and its apparent physical relationship with extreme rainfall. This study investigates the reliability of surface air temperature, integrated water vapor, surface dew point temperature, and 850 hPa atmospheric temperature as possible covariates for rainfall projection. Consistent with observed increases in extreme rainfall, a covariate that exhibits consistency across varying climatic conditions will result in more robust projections of future extreme rainfall. Here, we investigate the susceptibility of each covariate to varying conditions exhibited by the broad climates found across Australia. Integrated water vapor, retrieved from satellites, is found to be the most suitable scaling covariate for extreme rainfall projection. Key Points: Extreme rainfall does not scale consistently with surface air temperatureIntegrated water vapor is the most stable covariate when correlated to rainfallIt is suggested integrated water be used as a covariate for rainfall projection [ABSTRACT FROM AUTHOR]

This study aims to explore possible distributional changes in annual daily maximum rainfalls (ADMRs) over South Korea using a Bayesian multiple non-crossing quantile regression model. The distributional changes in the ADMRs are grouped into nine categories, focusing on changes in the location and scale parameters of the probability distribution. We identified seven categories for a distributional change in the selected stations. Most of the stations (28 of 50) are classified as Category III, which is characterized by an upward trend with an increase in variance in the distribution. Moreover, stations with a downward trend with a decrease in the variance pattern (Category VII) are mainly distributed on the southern Korean coast. On the other hand, Category I stations are mostly located in eastern Korea and primarily show a statistically significant upward trend with a decrease in variance. Moreover, this study explored changes in design rainfall estimates for different categories in terms of distributional changes. For Categories I, II, III, and VI, a noticeable increase in design rainfall was observed, while Categories IV, V, and VII showed no evidence of association with risk of increased extreme rainfall. [ABSTRACT FROM AUTHOR]

Design rainfall depth, which is a fundamental index used in river planning, was estimated by rainfall obtained from super-ensemble simulations with bias correction, and the future change under 4 degree warming was projected. The modifications of existing bias correction methods were proposed to resolve the issue of overfitting and gap in size between reference and super-ensemble simulation data. A bias correction approach considering the bias between the historical experiment, the reference data, and the change between the historical and future experiments separately was defined as two-pass bias correction. The two-pass bias correction was performed with a moving window method that calculated moving average for time period and rankorder statistics. The result indicated that the approach proposed in this study estimates the design rainfall depth with a small error compared to that calculated without the moving window. The moving window method effectively resolves the issue of overfitting. The projection indicated that the range of projection among sea-surface temperature (SST) patterns is equivalent to 25% of the design rainfall depth for most basins and 60% for certain specific basins. The results indicate the importance of the appropriate bias correction and the consideration of range among the SST patterns for super-ensemble simulation data. [ABSTRACT FROM AUTHOR]

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