High-resolution rainfall forecasts are essential for forecasting urban pluvial floods and providing local decision support before an event when using rainfall or model-based approaches. Regional Numerical Weather Prediction (NWP) models increase the resolution and extend forecasts by several days when initialised with global models. These models produce forecasts at higher spatial and temporal resolutions but are computationally demanding and do not necessarily result in more accurate forecasts especially in data-scarce cities. This research evaluated how rainfall forecasting model scale dependencies satisfy high-resolution hazard forecasting requirements with two different flood forecasting approaches. Rainfall forecasts of different spatial resolutions, cumulus schemes and lead times from a high-resolution Weather Research and Forecasting (WRF) model were first evaluated and then used as input in a rainfall threshold and 1D MIKE urban drainage model for flood forecasting in the data-scarce city of Alexandria City, Egypt. Results indicate the flood forecast severity class and flood model simulation results vary with the neighbourhood size, forecast horizon, and chosen cumulus configuration but in general the smallest resolutions evaluated did not improve the hazard estimation for both flood forecasting approaches. Therefore, trade-offs must be made regarding model configurations, resolution, lead times and how the forecast output will be used. This study demonstrates the opportunities and limitations for better integrating high-resolution meteorological for the development of a rainfall threshold-based and model-based flood forecasting in cities with similar conditions. It also highlights the need to align the selected model configuration with the goals of the flood forecasting application which is critical for effective early warning systems and anticipatory flood management.@en

Urbanization is one of the important drivers of increasing local temperatures. As cities and urban areas evolve, extensive land use and land cover (LULC) changes alter the physical characteristics of surface materials. This modification results in reduced evapotranspiration rates, ultimately contributing to higher surface and air temperatures. This study investigated the impact of urbanization on urban temperature in Jakarta. Urban temperature was simulated for a 20-year time period (1995–2014) by the urban boundary layer climate model UrbClim, using LULC data for both 1995 and 2014. Temperature changes were analysed by assessing the temperature anomaly across different LULC change classes divided into four main classes namely no built-up changes (BB), no green spaces changes (GG), built-up to green spaces (BG), and green spaces to built-up (GB). The study revealed that the conversion of green spaces to built-up areas (GB) had the most significant impact on the increase in air temperature. This was indicated by the mean values of the temperature anomaly of GB of about 0.24°C followed by GG, BB, and BG with the mean values of the temperature anomaly of about 0.20°C, 0.19°C, 0.17°C, respectively. The different temperature anomalies of the LULC change classes indicate that green spaces have an important role in maintaining local climate. Hence, it is important for local government to effectively manage the composition, the quantity, as well as the distribution of green spaces within a city. By looking at temperature anomalies of LULC change classes, the present study provides an alternative approach to many existing methods that provide general information about temperature changes, without specifically analyzing the effects of LULC transformations.@en

Urban water management is confronted with more frequent, more extreme weather events. This paper introduces the Three-Points Approach (3PA) into Sponge City concept, to create a novel framework aimed at guiding water management interventions across local, urban, regional, and river basin scales. The 3PA integrates three domains—Day-to-day, Design, and Extreme —offering a nuanced strategy for flood and drought risk mitigation, also for extreme events. Notably, the 3PA emphasizes the fusion of blue-green infrastructure (BGI) with conventional gray approaches to enhance both multifunctionality and resilience in extreme weather conditions. The study identifies critical issues of implementing this Three-Points Sponge Policy (3PSP) approach, including spatial and temporal scales, transitioning from gray to blue-green infrastructure, asset management, data handling, and effective communication. Interventions spanning various spatial scales and addressing flood protection, drought resilience, and water quality are explored in a first and indicative application in Zhengzhou. The case study distills key design principles, highlighting the imperative of never shifting problems, embracing ecosystem-based adaptation, seeking synergy between interventions, and incorporating adaptability into designs. The 3PSP approach emerges as a holistic framework that considers both risks and benefits, contributing valuable insights to the discourse on integrating urban and river basin water management, improving our ways of dealing with extreme weather events while maximizing the day-to-day benefits of our interventions.@en

The increasing global population and in-country migration have a significant impact on global land use land cover (LULC) change, which reduces green spaces and increases built-up areas altering the near-surface radiation and energy budgets, as well as the hydrological cycle over an urban area. The LULC change can lead to a combination of hazards such as increasing urban temperatures and intensified rainfall, ultimately resulting in increased flooding. This present study aims to discuss the changing pattern in urban temperature, daily rainfall, and flooding in Jakarta. The daily urban temperature and daily rainfall were based on a 30-year dataset from three meteorological stations of Jakarta in the period between 1987 and 2013. The changing trend was analyzed by using the Mann–Kendall and the Pettitt’s tests. The relation between daily rainfall and flooding was analyzed using a 30-year flooding dataset collected from several sources including the international disaster database, research, and newspaper. The results show that there was an increasing trend in the daily temperature and the daily rainfall in Jakarta. The annual maximum daily temperature showed that an increasing trend started in 2001 at the KMY station, and in 1996 at the SHIA station. In general, the highest annual maximum daily temperature was about 37 °C, while the lowest was about 33 °C. Moreover, the maximum daily rainfall started increasing from 2001. An increase in the maximum daily rainfall was observed mainly in January and February, which coincided with the flood events recorded in these months in Jakarta. This indicates that Jakarta is not only vulnerable to high urban temperature but also to flooding. While these two hazards occur in distinct timeframes, there is potential for their convergence in the same geographical area. This study provides new and essential insights to enhance urban resilience and climate adaptation, advocating a holistic approach required to tackle these combined hazards.@en

Evaluation of the hydrological performance of grassed swales usually needs long-term monitoring data. At present, suitable techniques for simulating the hydrological performance using limited monitoring data are not available. Therefore, current study aims to investigate the relationship between saturated hydraulic conductivity (K_s) fitting results and rainfall characteristics of various events series length. Data from a full-scale grassed swale (Enschede, the Netherlands) were utilized as long-term rainfall event series length (95 rainfall events) on the fitting outcomes. Short-term rainfall event series were extracted from these long-term series and used as input in fitting into a multivariate nonlinear model between K_s and its influencing rainfall indicators (antecedent dry days, temperature, rainfall, rainfall duration, total rainfall, and seasonal factor (spring, summer, autumn, and winter, herein refer as 1, 2, 3, and 4). Comparison of short-term and long-term rainfall event series fitting results allowed to obtain a representative short-term series that leads to similar results with those using long-term series. A cluster analysis was conducted based on the fitting results of the representative rainfall event series with their rainfall event characteristics using average values of influencing rainfall indicators. The seasonal index (average value of seasonal factors) was found to be the most representative short rainfall event series indicator. Furthermore, a Bayesian network was proposed in the current study to predict if a given short-term rainfall event series is representative. It was validated by a data series (58 rainfall events) from another full-scale grassed swale located in Utrecht, the Netherlands. Results revealed that it is quite promising and useful to evaluate the representativeness of short-term rainfall event series used for long-term hydrological performance evaluation of grassed swales. Graphical Abstract: (Figure presented.).

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Urbanizing river deltas are highly susceptible to sea level rise and extreme weather events such as floods and droughts. Water-related disasters are already happening more often due to climate change, rapid urbanization, unsustainable land use and aging infrastructure threatening a large fraction of human and natural environments in these low lying and sinking areas around the globe. As stress levels of climate change are accelerating, societal and physical transformations are essential for adapting our deltas to climate change. In the Netherlands, imagination and evidence by design in the form of a long-term spatial vision, played a pivotal role in the past century to set, share and accomplish a new direction to overcome flood disasters by altering the coastlines and riverbeds of the Rhine–Meuse–Scheldt delta. The unprecedented rainfall in July 2021 and the storm in December 2021 which hit Western Europe revealed the effectiveness of this new direction. We therefore plea for a prominent role of design in climate science and delta management to imagine, analyse and communicate future perspectives for climate adaptation in urbanizing deltas.@en

The rapid growth of impervious areas in urban basins worldwide has increased the number of impermeable surfaces in cities, leading to severe flooding and significant economic losses for civilians. This trend highlights the urgent need for methodologies that assess flood hazards and specifically address the direct impact on pedestrians, which is often overlooked in traditional flood hazard analyses. This study aims to evaluate a methodology for assessing the risk to pedestrians from hydrodynamic forces during urban floods, with a specific focus on Cúcuta, Colombia. The methodology couples research outcomes from other studies on the impact of floodwaters on individuals of different ages and sizes with 1D/2D hydrological modeling. Advanced computational algorithms for image recognition were used to measure water levels at 5-s intervals on November 6, 2020, using drones for digital elevation model data collection. In Cúcuta, where flood risk is high and drainage infrastructure is limited, the PCSWMM (Computer-based Urban Stormwater Management Model) was calibrated and validated to simulate extreme flood events. The model incorporated urban infrastructure details and geomorphological parameters of Cúcuta's urban basin. Four return periods (5, 10, 50, 100), with extreme rainfall of 3 h, were used to estimate the variability of the risk map. The output of the model was analyzed, and an integrated and time-varying comparison of the results was done. Results show that the regions of high-water depth and high velocity could vary significantly along the duration of the different extreme events. Also, from 5 to 100 years return period, the percentage of area at risk increased from 9.6% to 16.6%. The pedestrian sensitivity appears much higher than the increase in velocities or water depth individually. This study identified medium to high-risk locations, which are dynamic in time. We can conclude dynamics are spatiotemporal, and the added information layer of pedestrians brings vulnerability information that is also dynamic. Areas of immediate concern in Cúcuta can enhance pedestrian safety during flash flood events. The spatiotemporal variation of patterns requires further studies to map trajectories and sequences that machine learning models could capture.

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In response to pressing global challenges like climate change, rapid population growth, and an urgent need for sustainable infrastructure, cities face an immediate and crucial necessity to transition swiftly toward an integrated approach to managing urban water resources. This shift is not merely an option but an imperative, driven by the rapidly evolving urban landscape. In addressing this imperative, a crucial decision support tool that has emerged as an asset in the domain of urban water planning and management is the Urban Water Use (UWU) tool. This tool offers an integrated approach for strategic planning, promoting urban water conservation and environmental health through the investigation of interventions in urban infrastructure under different scenarios. In this study, the latest version of this UWU tool was deployed in a case study conducted in Almirante Tamandaré, Brazil. The objective was to evaluate how an integrated decision-making approach concerning urban water systems influences the efficiency and effectiveness of interventions, ultimately contributing to achieve widespread adoption, accessibility, and relevance of urban water services. The refined UWU tool evaluates a spectrum of measures across diverse scenarios, incorporating various drivers, focusing on the stakeholders' visions for the locality. These visions are composed of sustainability indicators, specifying different sets of target values and importance weights for each indicator. The approach followed in this study demonstrates how the effectiveness indexes can vary based on stakeholders' perception. Measures under Water Sensitive Urban Design and Water Demand Management strategies were deployed to simulate the response of urban water systems under three distinct scenarios, embracing the complexities of social dynamics and of climate change. The findings of the study emphasize that realizing a desired vision through selected measures relies significantly on the adoption of an integrated approach within the decision-making process. The stakeholders' perception of how indicators should be weighted while defining the vision was found to significantly impact the effectiveness range of these measures.

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Agriculture-dependent developing Southeast Asian countries need to assess residual pesticides in receiving water from agricultural runoff as one of the basis for the establishment of baseline data. Monitoring residual pesticides in surface water is challenging due to pesticides’ irregular/intermittent emission and low solubility in water. To address the challenge of pesticide assessment, passive samplers composed of silicon rubber sheets (SR) and speedisk (SD) were used to capture hydrophobic and hydrophilic organic pesticides and other organic pollutants, respectively. Samplers were submerged uninterruptedly for at least 30 days in three selected sites in Can Tho River, Mekong Delta, Vietnam, and Cagayan de Oro River Basin, Philippines, for 2 years. Passive samplers (SR spiked with 232 pesticides) captured 83 and 69 residual pesticides at concentrations of ng/L levels in Vietnam and the Philippines, respectively, which is unattainable through conventional grab sampling methods. Trace concentrations of banned compounds such as OCPs, PCBs, and PAHs were also detected at pg./L levels. The success of this alternative methodology can be attributed to the combination of passive samplers tailored for nonpolar (water-insoluble) and polar (water-soluble) organic contaminants coupled with sensitive analytical instruments, including GCMSMS and LCMSMS.@en

With rapid urbanization, the types of land in China’s cities are continuously evolving, irreversibly impacting the habitat patches within urban areas. However, the development of park cities has reversed this trend to some extent, particularly in Chengdu, China. To investigate the influence of land use type changes on habitat quality in Chengdu Tianfu New District, the research team selected remote sensing imagery data from the Landsat satellite for three distinct periods: 2014, 2019, and 2024. By employing a comprehensive approach that includes land cover trajectory analysis, land transfer matrices, FRAG-STATS landscape pattern indices, and the habitat quality module within the In-VEST model, this study analyzes the spatial and temporal evolution of land use patterns and the dynamics of habitat quality categories. The findings reveal: (1) the coverage of trees and shrubs in the study area initially declined but later increased, primarily driven by anthropogenic construction activities. Specifically, the land use types in the built-up areas on the northern side of Tianfu New District underwent notable fluctuations, whereas those on the southern side, adjacent to the Longquan Mountain Range, remained relatively stable. (2) From 2014 to 2019, high-quality habitats were predominantly distributed in the southeast of Tianfu New District, characterized by a robust ecological foundation, high landscape integrity, and strong connectivity of ecological land. In contrast, the areas with the poorest habitat quality were situated in the northern built-up areas of Tianfu New District, exhibiting highly fragmented habitat patches, simple edge shapes, and low connectivity. However, between 2019 and 2024, the overall habitat quality within the study area improved, characterized by an increase in the number of high-quality habitats and continuous expansion of habitat areas. The research findings offer valuable insights into future urban planning, ecological restoration, and conservation efforts in Chengdu Tianfu New District, providing critical guidance for the implementation and strategic development of the park city policy.

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Microbial pathogens in urban floodwaters pose risks to human health, potentially causing diseases such as diarrhea. However, the disease burden related to urban traffic exposure from citizens passing through floodwaters is not easily quantified and therefore not included in many studies. Notably, this problem has received little attention in low-to-middle-income countries, with frequent flood events and the heavy diarrheal disease burden. This article calculates the infection risks and disease burden, considering traffic associated with exposure to floodwater contaminated with rotavirus for the first time in Ninh Kieu District, Can Tho city. Can Tho city in the Vietnamese Mekong Delta is well known to have many flood events every year, with many diarrheal cases during the flood season. The methodology comprises two steps. First, we applied quantitative microbial risk assessment that proposes the inclusion of exposure to traffic due to rotavirus in floodwater. Second, the disease burden was expressed in disability-adjusted life years (DALYs). The exposed groups are child pedestrians, adult pedestrians, motorcyclists, and cyclists. We used video footage to monitor the traffic. The results show that total DALYs per flood event were 1.35 × 10⁴ for 63,390 exposed people (i.e., 2129 DALYs per 10,000 cases). Motorcyclists are the strongest contributors to the DALYs (95%), followed by cyclists (2.8%), adult pedestrians (2%), and child pedestrians (0.2%). The population in Ninh Kieu District may suffer from waterborne diseases through traffic activities during flooding times. Our approach can be applied in other areas worldwide and helps identify main risk groups and focus areas for interventions.

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This chapter assesses ACM’s potential as a pathway to address the flooding problem of Greater Jakarta, significantly exacerbated by land subsidence and climate change. It is based on a thought experiment by the authors to envision application of this approach to the problem and is not the result of empirical work. A background of Jakarta’s flooding is first provided and subsequently its framing as a ‘wicked problem’. Results of the thought experiment are then discussed, focusing on three questions: (i) Can ACM be applied, given Jakarta’s flooding governance structure? (ii) Will ACM’s social learning work for the flooding problem? And (iii) if ACM were applicable to Jakarta’s case, what operational indicators would apply? The chapter concludes with recommending a two-step ACM pathway: (1) adjusting the current flooding governance structure, for which leadership is needed with a long-term vision and the application of adaptive governance at the river basin scale; (2) shaping the enabling conditions for learning that stimulate creativity in and discovery of new problem framings and solutions outside the policy system. While the authors recognise the considerable challenges when applying ACM to the flooding of Greater Jakarta, the crisis stage it has reached necessitates adaptation approaches that can break the cycle of narrow, longstanding paradigms, policy beliefs, and maladaptive pathways..

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Saturated hydraulic conductivity (K_s) of the filler layer in grassed swales are varying in the changing environment. In most of the hydrological models, K_s is assumed as constant or decrease with a clogging factor. However, the K_s measured on site cannot be the input of the hydrological model directly. Therefore, in this study, an Ensemble Kalman Filter (EnKF) based approach was carried out to estimate the K_s of the whole systems in two monitored grassed swales at Enschede and Utrecht, the Netherlands. The relationship between K_s and possible influencing factors (antecedent dry period, temperature, rainfall, rainfall duration, total rainfall and seasonal factors) were studied and a Multivariate nonlinear function was established to optimize the hydrological model. The results revealed that the EnKF method was satisfying in the K_s estimation, which showed a notable decrease after long-term operation, but revealed a recovery in summer and winter. After the addition of Multivariate nonlinear function of the K_s into hydrological model, 63.8% of the predicted results were optimized among the validation events, and compared with constant K_s. A sensitivity analysis revealed that the effect of each influencing factors on the K_s varies depending on the type of grassed swale. However, these findings require further investigation and data support.

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Risk-informed flood risk management requires a comprehensive and quantitative risk assessment, which often demands multiple (thousands of) river and flood model simulations. Performing such a large number of model simulations is a challenge, especially for large, complex river systems (e.g., Mekong) due to the associated computational and resource demands. This article presents an efficient probabilistic modeling approach that combines a simplified 1D hydrodynamic model for the entire Mekong Delta with a detailed 1D/2D coupled model and demonstrates its application at Can Tho city in the Mekong Delta. Probabilistic flood-hazard maps, ranging from 0.5 to 100 year return period events, are obtained for the urban center of Can Tho city under different future scenarios taking into account the impact of climate change forcing (river flow, sea-level rise, storm surge) and land subsidence. Results obtained under present conditions show that more than 12% of the study area is inundated by the present-day 100 year return period of water level. Future projections show that, if the present rate of land subsidence continues, by 2050 (under both RCP 4.5 and RCP 8.5 climate scenarios), the 0.5 and 100 year return period flood extents will increase by around 15- and 8-fold, respectively, relative to the present-day flood extent. However, without land subsidence, the projected increases in the 0.5 and 100 year return period flood extents by 2050 (under RCP 4.5 and RCP 8.5) are limited to between a doubling to tripling of the present-day flood extent. Therefore, adaptation measures that can reduce the rate of land subsidence (e.g., limiting groundwater extraction), would substantially mitigate future flood hazards in the study area. A combination of restricted groundwater extraction and the construction of a new and more efficient urban drainage network would facilitate even further reductions in the flood hazard. The projected 15-fold increase in flood extent projected by 2050 for the twice per year (0.5 year return period) flood event implies that the “do nothing” management approach is not a feasible option for Can Tho.

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Stormwater biofiltration systems (SBS) are a popular technology for mitigating the negative effects of urbanization on the hydrological processes and water quality in urban areas. However, little is known about SBS's long-term performance in actual field conditions. The findings of a review of the scientific literature on the long-term performance of SBS are presented in this paper. The findings show that only a few studies have investigated the performance of SBS and its change over time, and that the results of laboratory and field experiments differed due to the presence of plants, regular maintenance, and some uncertain environmental factors. Based on the existing knowledge gaps in this field, the main challenges observed was the lack of long-term field data series, and the existing mathematical models are not able to accurately forecast the long-term performance of SBS. This could be owing to the difficulties in monitoring activities, the high costs involved and the unpredictability around the operational timeframe. Future study should concentrate on the implementation of simulation and modeling-based research in pilot and full-scale SBS, and the inclusion of new performance indicators should be considered as a priority.

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Flash Flood Guidance (FFG) is a rainfall threshold which initiates flooding in streams. It merely provides a binary output (yes or no) which has large uncertainties in forecasting. In this paper, we propose a new method by combining FFG with the Frequentist method to present the probability of flash flood occurrence based on historical rainfall events. We first calculated deviation from the log transform rainfall data leading to flash floods. Kernel Density Estimation (KDE) was used to describe the deviation. Normal Distribution Function (NDF) was chosen to fit the KDE output and to calculate probabilities of flooding as per the Frequentist FFG. In order to aid decision making, three probability thresholds (10, 20 and 60%) were used for defining four flood risk classes, namely very low, low, significant and high, and were colour coded respectively as green, yellow, orange and red. The proposed Frequentist FFG method was then applied to the Posina River basin in Italy. Comparison of forecasts from the conventional FFG (with probability 0 or 1) and Frequentist FFG for 94 6-hourly rainfall events, including 23 flood events, shows that the Frequentist FFG presented a probability of flooding varying from 0 to 100% and the corresponding risk class can be used to reduce false alarms while still reducing the disaster risk. The application of the developed approach to the Posina basin shows that decision making regarding flash forecasting is easier with the presented approach compared to the traditional FFG approach.

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To prevent floods from becoming disasters, social vulnerability must be integrated into flood risk management. We advocate that the welfare of different societal groups should be included by adding recovery capacity, impacts of beyond-design events, and distributional impacts.@en

As a result of the fast growth of remote sensing and data assimilation technology, many global land use land cover (LULC) and climate reanalysis data sets have been used to advance our understanding of climate and environmental change. This paper investigates the precipitation variations of the Yangtze Delta Megalopolis by using precipitation reanalysis data under conditions of dynamic urban sprawl. Compared with current precipitation characteristic analyses, which are often based on a limited number of ground rainfall stations, the approach followed in this study comprises a grid-based statistical method using large sets of samples with a uniform distribution and a same representative grid area. This novel approach of dynamic sampling is applied in this study to overcome the temporal and spatial inconsistency of stationary sampling. This approach allows to examine the impact of urbanization on regional precipitation characteristics. The Yangtze Delta Megalopolis (YDM) region, one of the most developed regions in China, was selected as a case study to evaluate the impact of urbanization on subsequent precipitation features. The results reveal that the annual total precipitation (TP) and the maximum daily precipitation (MDP) in both urban and non-urban areas of the YDM region generally have increased during the past 30 years. Hence, the region has become increasingly humid. Extrema of annual MDP and TP show obvious spatial characteristics, in which most maxima are located in the southern part of YDM while minima are more concentrated in the northern part. This newly developed approach has potentials for application in studies where underlying surface features exhibit rapid alterations. The findings of this case study provide relevant information for planning and design of regional water resources management, flood risk management, and planning of the urban drainage system of the YDM region.

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Rapidly expanding cities in the Middle Eastern and North African (MENA) region are at risk of flooding due to heavy rainfall, insufficient drainage capacity, a lack of preparedness and insufficient data to conduct required studies. A low regret Early Warning Systems (EWS) using rainfall thresholds is proposed as a cost-effective short-term solution. This study aims to utilise a probabilistic approach to characterise and predict urban floods by assessing critical rainfall thresholds likely to cause flooding combined with ensemble precipitation forecast in Alexandria, Egypt. Rainfall thresholds were inferred by associating observed rainfall and historical flood information sourced from social media and newspapers. Floods were classified in a colour-coded hazard matrix as no flood (green), minor flood (yellow), significant flood (orange), and severe flood (red). Probability of occurrence of hazard classes was derived by incorporating ensemble rainfall into the hazard matrix to jointly evaluate likelihood and hazard severity. Results from this study showed that three of four severe events analysed could have been predicted with a high likelihood up to 24 hr before. The presented approach supports decision making to issue warnings and flood control actions with limited data and is a model for other data scare regions.

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Today we experience and acknowledge the nexus of ecology, culture and politics as a moving objective, defined by local realities placed within global developments. Large-scale change is no longer a distant probability but an approaching condition, which forces us to accept instability and envision sustainability transitions as the ground of future inhabitation. When looking closer into atmospheric, water (riverine, maritime, deltaic), and land systems and their inherent uncertainties we realize the agency that local sensitivities, culture and planning regimes have in defining the success or failure of sustainable development. This dialogue will question what the real ground of preMarsent and future urbanization is, imagining adaptive and transformative change as material and ecologically sensitive practices to site, context and culture.

This dialogue is the transcription of the round table talk on the International Forum on Urbanism held in Delft on 26 November 2021. Lars Marcus, Chris Zevenbergen and Carola Hein presented their work in the light of the environmental crisis, sectoral versus integral: the agency of change. With moderator Fransje Hooimeijer they elaborated and related their work in a discussion around the main questions of history, the longue durée, disciplinarity and agency of change.@en