Design Storm Research Articles

Evaluation of an urban drainage system using functional and structural resilience approach

ABSTRACT This study presents a resilience-based evaluation of an urban drainage system (UDS) under the impact of functional and structural failure modes. Resilience based analysis is carried out using SWMM for a part of Gurugram City of Haryana, India. For simulating the drainage system response, half-hourly rainfall data available from GPM-IMERG was utilized to estimate the design storm of suitable duration. Sensitivity analysis is carried out to overcome the problem of lack of in-depth data to perform model calibration and validation. Besides, a comparison of three different estimation approaches of subcatchment width, an important SWMM parameter, is also presented. Different rainfall and urban growth scenarios were considered to analyse the drainage system's functional and structural resilience. For the studied UDS, a total of 22 vulnerable nodes were identified through the structural resilience approach, and the functional resilience approach revealed that urbanization has more pronounced effects on UDS than climate change.

Pluvial flooding: High-resolution stochastic hazard mapping in urban areas by using fast-processing DEM-based algorithms

Climate change and rapid expansion of urban areas are expected to increase pluvial flood hazard and risk in the near future, and particularly so in large developed areas and cities. Therefore, large-scale and high-resolution pluvial flood hazard mapping is required to identify hotspots where mitigation measures may be applied to reduce flood risk. Depressions or low points in urban areas where runoff volumes can be stored are prone to pluvial flooding. The standard approach based on estimating synthetic design hyetographs assumes, in a given depression, that the T-year design storm generates the T-year pluvial flood. In addition, urban areas usually include several depressions even linked or nested that would require distinct design hyetographs instead of using a unique synthetic design storm. In this paper, a stochastic methodology is proposed to address the limitations of this standard approach, developing large-scale ∼ 2 m-resolution pluvial flood hazard maps in urban areas with multiple depressions. The authors present an application of the proposed approach to the city of Pamplona in Spain (68.26 km2). The Safer_RAIN fast-processing algorithm based on digital elevation models (DEMs) is compared with the IBER 2D hydrodynamic model in four real storms by using 10-min precipitation fields. Precipitation recorded at rainfall-gauging stations was merged with continuous fields obtained from a meteorological radar station. Given the hydrostatic limitations of Safer_RAIN, the benchmarking results are adequate in terms of water depths in depressions. A long set of 10 000 synthetic storms that maintain the statistical properties of observations in Pamplona is generated. Safer_RAIN is used to simulate runoff response, and filling and spilling processes, in depressions for the 10 000 synthetic storms, obtaining the probability distribution of water depths in each cell. Maps of pluvial flood hazards are developed in the Pamplona metropolitan area for 10 return periods in the range from two to 500 years from such pixel-based series of simulated water depths. Bivariate return-period curves are estimated in a set of cells, showing that several storms can generate a given T-year pluvial flood with an increasing precipitation with storm duration that depends on the draining catchment soil characteristics. The methodology proposed is useful to develop maps of pluvial flood hazards in large multi-depression urban areas in reasonable computation times, identifying the main pluvial flood hotspots.

Calibration of a continuous hydrologic simulation model in the urban Gowrie Creek catchment in Toowoomba, Australia

Study regionToowoomba, Queensland, Australia Study focusIn this study we derive loss model parameters suitable for use in the dynamic loss Australian Representative Basin Model (ARBM) through the calibration of a continuous simulation hydrologic model. We compare the derived parameters to those published in the literature, and our results highlight the need to develop a database of calibrated loss parameters for urban catchments. New hydrological insightsThe development of design storms for flood modelling commonly uses the initial loss/continuous loss model to estimate the conversion of rainfall to runoff. This loss model, when applied to pervious areas, uses parameters that have been calibrated for gauged rural catchments. These same parameters are often applied to the pervious component of ungauged urban catchments with minimal understanding of the resulting impact on runoff. This research uses a continuous simulation modelling approach to calibrate parameters suitable for use in the ARBM loss model built into the hydrological modelling software XPRAFTS. Through a two-stage calibration approach, the model offered a satisfactory fit (Nash Sutcliffe Efficiency > 0.5) for 9 of the 11 selected storm events, with seven events exceeding a Nash Sutcliffe Efficiency of 0.75. Events used in the calibration/validation included peak flows as low as 9 m3/s and as high as 600 m3/s. Developing these loss model parameters offers new insights into the suitability of a dynamic loss model approach in an urban catchment in regional Australia and provides an alternative to the parameters already available in the literature which were found to overestimate the peak flow in frequent events.

Development of Rainfall Design Storm Hyetographs for Al-Quassim Region – Kingdom of Saudi Arabia

Development of Rainfall Design Storm Hyetographs for Al-Quassim Region – Kingdom of Saudi Arabia

Effects of stormwater infrastructure data completeness and model resolution on urban flood modeling

The accuracy of hydrologic and hydrodynamic models, used to study urban hydrology and predict urban flooding, depends on the availability of high-resolution terrain and infrastructure data. Unfortunately, cities often do not have or cannot release complete infrastructure data, and high-resolution terrain data products are not available everywhere. In this study, we quantify how the accuracy and precision of urban hydrologic-hydrodynamic models vary as a function of data completeness and model resolution. For this aim, we apply the one-dimensional (1D) and coupled one- and two-dimensional (1D-2D) versions of the U.S. Environmental Protection Agency’s Storm Water Management Model (SWMM) in an urban catchment in the city of Phoenix, Arizona. Here, we have collected detailed infrastructure data, a high-resolution 0.3-m LiDAR-based digital elevation model, and catchment properties data. We tested several model configurations assuming different levels of (i) availability of stormwater infrastructure data (ranging from 5% to 75% of attribute-values missing) and (ii) terrain aggregation (i.e., 4.6 m and 9.7 m). These configurations were generated through random Monte Carlo sampling for SWMM 1D and selective sampling with four cases for SWMM 1D-2D. We ran simulations under the 50-year return period design storm and compared simulated flood metrics assuming the highest-resolution and complete data model configuration as a reference. The study found that the model may over or underestimate flood volume and duration with different levels of missing data depending on the parameters — roughness, diameter or depth, and that model performance is more sensitive to missing data that is downstream and closer to the outfall as opposed to missing data upstream. Errors in flood depth, area and volume estimation are functions of both the data completeness and model resolution. Missing feature data leads to overestimation of flood depth, while lower model resolution results in underestimating flood depth and overestimating flood extent and volume.

Role of Neighborhood Design in Reducing Impacts of Development and Climate Change, West Sherwood, OR

We used the EPA SWMM-5. 1 model to evaluate the relative impact of neighborhood design and constructed Low Impact Development (LID) features on infiltration, evaporation, and runoff for three future scenarios. In the Current Course (CC) future, current regulations and policies remain in place under lower rates of climate change and population growth. In the Stressed Resources (SR) future, rapid rates of population growth and climate change stress water systems, and conventional development patterns and management actions fail to keep pace with a changing environment. In the Integrated Water (IW) future, with the same rapid rates of climate change and population growth as the SR future, informed water management anticipates and adapts to expected changes. The IW scenario retains public open space, extensive use of constructed LID features, and has the lowest proportion of impervious surface. Neighborhood designs varied in the number of dwelling units, density of development, and spatial extent of nature-based solutions and constructed LID features used for stormwater management. We compared the scenarios using SWMM-5.1 for a set of NRCS Type 1a design storms (2-yr, 25-yr, 20% increase over 25-yr, 30% increase over 25-yr) with precipitation input at 6-min time steps as well as a set of 10-year continuous runs. Results illustrate the importance of neighborhood design in urban hydrology. The design with the highest proportion of impervious surface (SR future) produced runoff of up to 45–50% of precipitation for all variations of the 25-year storm, compared to 34–44 and 23–39% for the CC and IW futures, respectively. Evaporation accounted for only 2–3% of precipitation in the 25-year design storm simulations for any scenario. Results of continuous 10-year simulations were similar to the results of design storms. The proportion of precipitation that became runoff was highest in the SR future (33%), intermediate in the CC (16%), and lowest in the IW future (9%). Evaporation accounted for 6, 11, and 14 of precipitation in the SR, CC, and IW futures with LID, respectively. Infiltration was higher in scenarios with LID than for the same scenario without LID, and varied with the extent of LID employed, accounting for 59, 71, and 74% of precipitation in the SR, CC, and IW scenarios with LID. In addition to differences in performance for stormwater management, the alternative scenarios also provide different sets of co-benefits. The IW and SR future designs both provide more housing than the CC, and the IW future has the lowest cost of development per dwelling unit.

Application of the WRF model rainfall product for the localized flood hazard modeling in a data-scarce environment

Urban flood hazard model needs rainfall with high spatial and temporal resolutions for flood hazard analysis to better simulate flood dynamics in complex urban environments. However, in many developing countries, such high-quality data are scarce. Data that exist are also spatially biased toward airports and urban areas in general, where these locations may not represent flood-prone areas. One way to gain insight into the rainfall data and its spatial patterns is through numerical weather prediction models. As their performance improves, these might serve as alternative rainfall data sources for producing optimal design storms required for flood hazard modeling in data-scarce areas. To gain such insight, we developed Weather Research and Forecasting (WRF) design storms based on the spatial distribution of high-intensity rainfall events simulated at high spatial and temporal resolutions. Firstly, three known storm events (i.e., 25 June 2012, 13 April 2016, and 16 April 2016) that caused the flood hazard in the study area are simulated using the WRF model. Secondly, the potential gridcell events that are able to trigger the localized flood hazard in the catchment are selected and translated to the WRF design storm form using a quantile expression. Finally, three different WRF design storms per event are constructed: Lower, median, and upper quantiles. The results are compared with the design storms of 2- and 10-year return periods constructed based on the alternating-block method to evaluate differences from a flood hazard assessment point of view. The method is tested in the case of Kampala city, Uganda. The comparison of the design storms indicates that the WRF model design storms properties are in good agreement with the alternating-block design storms. Mainly, the differences between the produced flood characteristics (e.g., hydrographs and the number of flood gird cells) when using WRF lower quantiles (WRFLs) versus 2-year and WRF upper quantiles (WRFUs) versus 10-year alternating-block storms are very minimal. The calculated aggregated performance statistics (F scores) for the simulated flood extent of WRF design storms benchmarked with the alternating-block storms also produced a higher score of 0.9 for both WRF lower quantiles versus 2-year and WRF upper quantile versus 10-year alternating-block storm. The result suggested that the WRF design storms can be considered an added value for flood hazard assessment as they are closer to real systems causing rainfall. However, more research is needed on which area can be considered as a representative area in the catchment. The result has practical application for flood risk assessment, which is the core of integrated flood management.

AltBlock - Software para determinação de Chuvas de Projeto

A design storm can be defined as a precipitation pattern used to determine indirectly the design flood, which is an important data in many hydrologic design projects. Due to difficult to obtain historical data on precipitation, it has become common to construct design storms using general characteristics of precipitation in the surrounding region, represented by intensity-duration-frequency (IDF) relationships. In addition, it’s also necessary specify design return period, storm duration and the temporal distribution. For this purpose, is used the Alternating Block Method. In the view of software development applied to hydrology and to make more practical using this Alternating Block Method, this article intended to develop the AltBlock, a software able to calculate design storms automatically. Using Visual Studio .NET and the programming language Visual Studio .NET it was sought to build a graphical user-friendly interface. The AltBlock is applicable to any location and it’s useful for educational uses, engineering projects and hydrological studies.

Evaluating the Hydrologic and Water Quality Impacts of the Revised SCS CN Method and its Implications on Decision-Making

Highlights The revised CN equation uses decreased CN values, causing decreased initial abstraction values and increased runoff. SWAT’s water balance approach simulated increased runoff to decrease groundwater flow and associated baseflow with the revised SCS CN method. Landscape analysis showed minor changes in runoff and nutrient loadings, except in row cropping areas in high runoff potential soils. Reduced mitigation occurs if post-development runoff increases by a greater margin than the pre-development runoff. Abstract. The Soil Conservation Service (SCS) Curve Number (CN) method is a widely used model developed by the Natural Resources Conservation Service (NRCS) that estimates surface runoff generated from a land area using factors such as land cover, soil type, and precipitation depth. However, because this empirical model was developed over 60 years ago with limited data, the NRCS is considering revising it with the help of an ASCE-ASABE task group. The proposed revisions include updating the initial abstraction (Ia) ratio in the CN equation and modifying the curve number (CN) for all land use and soil hydrologic group combinations. The proposed revisions are expected to alter the hydrologic response estimation, especially for low flow events. Since surface runoff is driving sediment, nutrients, and the transport of chemicals in natural systems, this study aims to understand how predicted hydrologic and water quality variables vary between the original and the proposed revised versions of the SCS CN method using the Soil and Water Assessment Tool (SWAT). Additionally, a case study site was selected to understand how the revisions alter the design storm runoff analysis. Results from the simulation case study on a 36,900 ha mixed land-use watershed located in central Pennsylvania, USA indicate a 5% to 14% increase in annual runoff predictions with the revised equation compared to the original equation. Though most average monthly runoff depths increased by 1% to 25% using the revised equation, winter months generally simulated runoff depths that were 1% to 5% lower than the original equation. Average daily loadings at the watershed outlet increased by 11% to 19% and 4% to 11% for nitrate and mineral phosphorus, respectively. The SWAT simulation results suggest that current agricultural and urban best management practices (BMPs) will experience higher runoff volumes on a yearly time scale due to the decrease in the Ia term, while the design storm case study results suggest that urban BMPs can be smaller in size when rural lands are urbanized due to the reduction in runoff estimation from the initial land use with the revised equation. Additional detailed evaluations of the proposed SCS CN method are required for water quality simulations, stormwater management, and BMP designs. Keywords: Hydrology, Revised curve number method, SCS Curve Number Method, Soil and Water Assessment Tool, Water quality.

A Novel Statistical Modeling Approach to Developing IDF Relations in the Context of Climate Change

Extreme rainfall intensity–duration–frequency (IDF) relations have been commonly used for estimating the design storm for the design of various urban water infrastructures. In recent years, climate change has been recognized as having a profound impact on the hydrologic cycle. Hence, the derivation of IDF relations in the context of a changing climate has been recognized as one of the most challenging tasks in current engineering practice. The main challenge is how to establish the linkages between the climate projections given by climate models at the global or regional scales and the observed extreme rainfalls at a local site of interest. Therefore, our overall objective is to introduce a new statistical modeling approach to linking global or regional climate predictors to the observed daily and sub-daily rainfall extremes at a given location. Illustrative applications using climate simulations from 21 different global climate models and extreme rainfall data available from rain gauge networks located across Canada are presented to indicate the feasibility, accuracy, and robustness of the proposed modeling approach for assessing the climate change impact on IDF relations.

Assessing the role of SuDS in resilience enhancement of urban drainage system: A case study of Gurugram City, India

The increasing frequency of urban floods worldwide due to rapid urbanization, frequent climatic extremes, or poor drainage conditions necessitates evaluating the performance of the urban drainage systems (UDS) and enhancing their resilience. In this study, a comprehensive assessment of the UDS of Gurugram City, India, through the concepts of sustainable drainage systems (SuDS) is presented. A stormwater management model (SWMM) was set up to model the existing UDS response to a design storm of a 5-year return period. The increase in percentage imperviousness (due to urbanization) and rainfall intensity (due to climate change) are considered the governing factors for functional failures. The results revealed climate change to be a more severe threat to UDS than urbanization, while their combinations can further worsen the repercussions. The structural failure was modelled using the single link-failure scenarios, where 3 and 12 conduits possessed low resilience and no resilience (severe), respectively. The role of SuDS in enhancing the resilience of UDS was assessed by simulating all these functional and structural failure scenarios for three SuDS-implemented conditions, i.e., only infiltration trenches (SuDSIT), only retention ponds (SuDSRP), and both of them together (SuDSIT+RP). The SuDS abated the flood magnitudes, delayed the time to peak flow, and stored an additional volume of water within the catchment, thereby justifying their efficacy to mitigate the pluvial flood and enhance the resilience of UDS. The findings of this study encourage implementing SuDS over the developing countries to bring down the frequency of urban floods.

Influence of spatio-temporal distribution of design storm on Lake Taihu flood level

Influence of spatio-temporal distribution of design storm on Lake Taihu flood level

Climate change risk and adaptation costs for stormwater management in California coastal parklands

ABSTRACT Extreme precipitation from climate change may strain many existing stormwater systems. While studies have evaluated such effects on stormwater infrastructure, other sources of uncertainty not yet explored should also be considered. This paper presents an analysis of adaptation costs for new stormwater infrastructure to mitigate increases in design storm precipitation depth with climate change, including how economic and managerial uncertainty related to life cycle unit costs and knowledge of existing infrastructure affect costs. For case study areas in California, we quantify adaptation costs for new green infrastructure capacity by evaluating future design storms. Results indicate that design storm depths increase by an average of 28%, but lack of knowledge of the condition of existing infrastructure and life cycle unit costs result in wide cost ranges. The findings illustrate how climate change planning for stormwater should also consider economic and managerial uncertainty when estimating long-term adaptation costs.

Simulating sediment discharge at water treatment plants under different land use scenarios using cascade modelling with an expert-based erosion-runoff model and a deep neural network

Abstract. Excessive sediment discharge in karstic regions can be highly disruptive to water treatment plants. It is essential for catchment stakeholders and drinking water suppliers to limit the impact of high sediment loads on potable water supply, but their strategic choices must be based on simulations integrating surface and groundwater transfers and taking into account possible changes in land use. Karstic environments are particularly challenging as they face a lack of accurate physical descriptions for the modelling process, and they can be particularly complex to predict due to the non-linearity of the processes generating sediment discharge. The aim of the study was to assess the sediment discharge variability at a water treatment plant according to multiple realistic land use scenarios. To reach that goal, we developed a new cascade modelling approach with an erosion-runoff geographic information system (GIS) model (WaterSed) and a deep neural network. The model was used in the Radicatel hydrogeological catchment (106 km2 in Normandy, France), where karstic spring water is extracted to a water treatment plant. The sediment discharge was simulated for five design storms under current land use and compared to four land use scenarios (baseline, ploughing up of grassland, eco-engineering, best farming practices, and coupling of eco-engineering/best farming practices). Daily rainfall time series and WaterSed modelling outputs extracted at connected sinkholes (positive dye tracing) were used as input data for the deep neural network model. The model structure was found by a classical trial-and-error procedure, and the model was trained on 2 significant hydrologic years. Evaluation on a test set showed a good performance of the model (NSE = 0.82), and the application of a monthly backward-chaining nested cross-validation revealed that the model is able to generalize on new datasets. Simulations made for the four land use scenarios suggested that ploughing up 33 % of grasslands would increase sediment discharge at the water treatment plant by 5 % on average. By contrast, eco-engineering and best farming practices will significantly reduce sediment discharge at the water treatment plant (respectively in the ranges of 10 %–44 % and 24 %–61 %). The coupling of these two strategies is the most efficient since it affects the hydro-sedimentary production and transfer processes (decreasing sediment discharge from 40 % to 80 %). The cascade modelling approach developed in this study offers interesting opportunities for sediment discharge prediction at karstic springs or water treatment plants under multiple land use scenarios. It also provides robust decision-making tools for land use planning and drinking water suppliers.

Comparing methods to place adaptive local RTC actuators for spill volume reduction from multiple CSOs

Abstract The selection of flow control device (FCD) location is an essential step for designing real-time control (RTC) systems in sewer networks. In this paper, existing storage volume-based approaches for location selection are compared with hydraulic optimisation-based methods using genetic algorithm (GA). A new site pre-screening methodology is introduced, enabling the deployment of optimisation-based techniques in large systems using standard computational resources. Methods are evaluated for combined sewer overflow (CSO) volume reduction using the CENTAUR autonomous local RTC system in a case study catchment, considering overflows under both design and selected historic rainfall events as well as a continuous 3-year rainfall time series. The performance of the RTC system was sensitive to the placement methodology, with CSO volume reductions ranging between −6 and 100% for design and lower intensity storm events, and between 15 and 36% under continuous time series. The new methodology provides considerable improvement relative to storage-based design methods, with hydraulic optimisation proving essential in relatively flat systems. In the case study, deploying additional FCDs did not change the optimum locations of earlier FCDs, suggesting that FCDs can be added in stages. Thus, this new method may be useful for the design of adaptive solutions to mitigate consequences of climate change and/or urbanisation.

Retrofitting urban land through integrative, subsoils-based planning of green stormwater infrastructure: a research framework

Abstract We present a research framework that integrates native subsoil performance and surface retrofitting into coordinated green stormwater infrastructure (GSI) planning. This framework provides communities a strategy to move beyond opportunistic GSI, which can be limited to capturing marginal amounts of stormwater, toward more impactful, coordinated GSI planning that restores the lost hydrologic functioning of the pre-development landscape. We create this framework by establishing critical performance-based relationships among four variables: (1) saturated hydraulic conductivity of native subsoils (∼upper 2 m below urban compaction and fill); (2) GSI design depth for both rain gardens and permeable pavement (in increments of 6″ from 12–30″ for planted and paved GSI); (3) loading ratio, defined as the ratio of GSI retrofit area to upstream impervious surface runoff area (from 1:2 to 1:5 for planted GSI; and 1:1 and direct infiltration for paved GSI); and (4) design storms (rainfall quantity up to 5-inches over 2 h and 24 h durations). We model the four variables using GSI models (built in the US Environmental Protection Agency’s Storm Water Management Model) and reliability analysis, a risk-assessment method adapted to characterize the reliability of GSI in response to varying stormwater runoff loading. The outcome of the modeling is a set of fragility curves and design prototypes, adjustable to catchment and sub-catchment scales, to assist municipalities in early funding and investment decisions to retrofit urbanized land through GSI. We also share two piloted applications in which we use the research framework within the Chicago-Calumet region in Illinois, USA, to conduct site-specific subsoil sampling and determinations of saturated hydraulic conductivity and to develop urban-scale GSI retrofit scenarios. Our framework is transferable to other urban regions, and particularly useful where a lack of integrating native subsoil performance into GSI design hinders decision-making, coordinated GSI planning at scale, and achieving high runoff reduction targets.

Bamboo Fences as a Nature-Based Measure for Coastal Wetland Protection in Vietnam

Climate change has induced sea-level rise and a high intensity of storms, which create high nearshore waves. These caused severe mangrove degradation and erosion along the coastal wetland areas in the Mekong Delta in Vietnam. Mangroves in the coastal wetland foreshore can withstand only some certain design storm waves and grow under several certain submerged conditions. Therefore, reducing waves and shallowing wetland elevation for recovering mangroves and protecting them in an early birth state is important. Bamboo or melaleuca fences have been used as a nature-based solution to reduce waves and currents approaching the shore for these above purposes along Vietnamese Mekong deltaic coasts. This paper investigates wave transmission through the bamboo fence system and assesses its effectiveness in protecting the mangroves. Waves were simultaneously measured at two locations for comparison: in front of and behind the fences. The result shows that the wave reduction by the fences is considerable, and sedimentation occurs rapidly in the shelter areas behind the fences, which is highly favorable for the recovery and growth of mangroves. Next, the empirical formulae have been proposed for relationships between the wave transmission coefficient of the fence and the dimensionless wave-structures parameters, such as the relative water depth, the wave steepness, and the fence freeboard. The findings create a basic technical reference for designing a naturally friendly-based solution by using bamboo and/or wooden fences in coastal protection generally and protecting mangroves specifically. The outcome of the research contributes to narrowing an existing gap in Vietnamese design guidelines for coastal wetland protection and also facilitates the use of locally available eco-friendly materials for coastal management along the Vietnamese Mekong delta coasts.

Developing Green Infrastructure Strategies Based on the Analysis of Sewer System Critical Components

Flooding has presented a significant risk for urban areas around the world. Road inundation is one of the severe consequences leading to traffic issues and congestion. Green infrastructure (GI) offers further potential for stormwater management as an environmentally friendly and sustainable solution. However, sewer system behaviour has been overlooked in GI implementation. This study investigates sewer performance by measuring topological connectivity and hydraulic characteristics, and critical components are identified under different design storms. Three retrofit scenarios, including enlarged pipes (grey infrastructure, Grey I), rain gardens (GI), and the combination of enlarged pipes and increased rain gardens (GI + Grey I), are proposed according to the distribution of critical components. The results show that it is feasible to locate the vulnerable parts of the sewer system and GI site allocations based on the critical components that significantly impact the performance of the entire system. While all three scenarios can mitigate inundation, GI and GI + Grey I perform better than pipe enlargement, especially for runoff reduction during long-duration rainfall. Furthermore, the sewer behaviour and retrofit effect are dynamic under different rainfall patterns, leading to diverse combined effects. The discoveries reveal that the adaptation measures should combine with sewer behaviour and local rainfall characteristics to enhance stormwater management.

Investigating event-based temporal patterns of design rainfall in a tropical region

ABSTRACT This study investigated the temporal rainfall pattern in order to facilitate rainfall design, which normally requires a good understanding of the temporal patterns of rainstorm events. The analysis employed a storm-event-based approach using the concept of inter-event time definition (IETD) and rainfall depth/duration/intensity thresholds. The 5-min rainfall data at three raingauge stations were analysed to determine representative quartiles of a design storm in a tropical city. The temporal characteristics of the design storm could be determined from the rainfall depth ratios of consecutive peak rainfalls for each interval of storm duration, and time to the first peak rainfall depending on each quartile’s rainstorm events. The determination of the quantile distribution of tropical rainfall could help improve the representativeness of design rainfall and facilitate rainfall–runoff modelling for urban flood control in a tropical region.

Testing the impacts of wildfire on hydrological and sediment response using the OpenLISEM model. Part 2: Analyzing the effects of storm return period and extreme events

Wildfires can have strong negative effects on soil and water resources, especially in headwater areas. The spatially explicit OpenLISEM model was applied to a burned catchment in southern Portugal to quantify the individual and combined impacts of wildfire and rainfall on hydrological and erosion processes. The companion paper has calibrated and assessed model performance in this area before and after a fire. In this study, the model was applied with design storms of six different return periods (0.2, 0.5, 1, 2, 5, and 10 years) to simulate and evaluate pre- and post-wildfire hydrological and erosion responses at the catchment scale. Our results show that rainfall amount and intensity played a more important role than fire occurrence in the catchment discharge and sediment yields. Fire occurrence was found to be an important factor for peak discharge, indicating that high post-fire hydro-sedimentary responses are frequently related to extreme rainfall events. The results also suggest a partial shift from runoff to splash erosion after fire, especially for higher return periods. This can be explained by increased splash erosion in burned upstream areas saturating the sediment transport capacity of surface runoff, limiting runoff erosion in downstream areas. Therefore, the pre-fire erosion risk in the croplands of this catchment was partly shifted to a post-fire erosion risk in upper slope forest and natural areas, especially for storms with lower return periods, although erosion risks in croplands were important both before and after fires. These findings have significant implications to identify areas for post-wildfire stabilization and rehabilitation, which is particularly important given the predicted increase in the occurrence of fires and extreme rainfall events with climate change.