Extended water retention in a distribution network increases water age, heightening vulnerability to microbial growth and quality issues. Designers must ensure the system allows for frequent water flow without complete stagnation. Private tanks play a crucial role in regulating system flow and influencing water age. This investigation aimed to assess how private tank retention time and orifice sizes affect water age within a schematic of an existing network in Dubai, UAE. The results indicated that longer retention times facilitated greater flow, thereby reducing water age due to increased filling times. Similarly, smaller orifice diameters contributed to this effect. Additionally, the presence of float valves was found to hinder water flow, leading to higher water age. Ultimately, the study identified a more effective approach than float valves for minimizing water age, demonstrating the importance of optimizing tank design and flow regulation in water distribution systems to enhance water quality.

The use of pumps in water distribution networks is very useful when there is a need for additional pressure head. However, the functioning of pumps can be influenced by the presence of private storage tanks in the network, which alters the way the users draw water due to their compensation ability. This condition is very common in areas affected by the historical scarcity of water resources or intermittent supply (Mediterranean Area, Arabian Peninsula, etc.). This paper studies the effects of private tanks on the performance of pumps in a network model, considering different retention times and evaluating possible effects on background leakages. A sample network and two real water distribution networks in the UAE will be analyzed. The results show that low retention time (i.e., 12 h) leads to a decrease in pump running time, thus lowering the energy consumption and carbon footprint, which gives a sustainable solution. These results, therefore, suggest that considering the presence of private storage tanks for the pump design in network models is of crucial economic importance, as well as for efficient designs and sustainable water distribution systems.

In the arid Arabian Peninsula, particularly within the United Arab Emirates (UAE), the perception of rainfall has shifted from a natural blessing to a significant challenge for infrastructure and community resilience. The unprecedented storm on 17 April 2024, exposed critical vulnerabilities in the UAE’s urban infrastructure and flood management practices, revealing substantial gaps in handling accumulated precipitation. This study addresses the necessity of updating the Intensity–Duration–Frequency (IDF) curves for the Sharjah Emirate by utilizing recent precipitation data from 2021 to April 2024, alongside previously published 2020 data. By recalibrating the IDF curves based on data from three meteorological stations, this study reveals a substantial increase in rainfall intensities across all durations and return periods. Rainfall intensities increased by an average of 36.76% in Sharjah, 26.52% in Al Dhaid, and 17.55% in Mleiha. These increases indicate a trend towards more severe and frequent rainfall events, emphasizing the urgent need to revise hydrological models and infrastructure designs to enhance flood resilience. This study contributes valuable insights for policymakers, urban planners, and disaster management authorities in the UAE and similar regions worldwide.

The increasing interest in hydrological studies in the United Arab Emirates (UAE) has resulted in the publication of several papers on hydrology and its broad use for addressing contemporaneous challenges confronting humans and the environment in the region. However, for several reasons, these efforts have remained invisible and unrecognized. This paper has reviewed the literature on hydrological research in the UAE to provide a comprehensive source of information for researchers, practitioners, policymakers, and other stakeholders. The documented studies were carefully selected, relying on a bibliometric analysis methodology of five phases to specify the boundary of the study area, adopt the primary keywords for the search, evaluate the obtained papers, exclude the non-conforming ones, and classify the final results into four distinguished topics—namely, rainfall analysis, urban growth and flood hazards, cloud seeding and changing climate, and groundwater situation and utilization. The evaluation process considered assessing the papers’ relevancy, authenticity, and coverage of the main issues of interest. In all, a total of 50 published papers were identified based on the specified criteria and reviewed. The main findings were first that the amount of rainfall over the UAE has been declining in the last decade, and this trend is expected to continue, although intensities are rising, suggesting shorter duration events. Secondly, the extensive urban growth in the country has resulted in increasing incidences of urban floods and declining groundwater recharge. Both of these are to be expected as consequences of the increased imperviousness from urbanization and the higher intensities from shorter-duration rainfall events. Thirdly, although the cloud-seeding program has proved to be successful in increasing precipitation amounts, the impact of this on flooding due to more extreme rainfall intensities and on air quality remains worrisome. Finally, groundwater analyses have shown that it is still the main freshwater resource in the country, but its long-term sustainability and quality are being threatened by the declining recharge. This calls for a national policy for groundwater management in the UAE to tackle the challenges associated with the increasing demand for water in all sectors of the economy. The study recommended addressing the gap in the hydrological literature of the UAE, specifically in the field of big meteorological data analysis, the socioeconomic impacts of urban floods, the impacts of climate change in urbanized regions, and the possibility of using alternative resources to recharge groundwater as part of sustainable water management.

Reliable flood forecasting systems are essential for predicting and mitigating the impact of flooding worldwide. However, minimising flood forecast uncertainties remains a challenging task due to many sources of uncertainty in underlying flood simulation modelling. Such uncertainties can be reduced by employing data assimilation techniques to dynamically incorporate the most recent available observations into the system while accounting for existing uncertainties in both models and observations. However, traditional observations often lack the necessary temporal or spatial resolution, limiting the adoption of data assimilation methods for real-time applications. In contrast, data collection through crowdsourcing has grown in popularity with the potential to provide high spatiotemporal resolution data, especially in urban areas. Nevertheless, the use of crowdsourcing is still impacted by validation uncertainties and data quality, which makes it a complementing data to traditional observations rather than an alternative data source. This paper presents a novel methodology for assimilating crowdsourced social media data to improve a 2D flood forecasting model through various update strategies. The methodology was tested against a real case flood event of the 2017 Phetchaburi flood (Thailand), and the performance of different update strategies was evaluated with reference to the calibrated model output obtained from a particle swarm optimisation algorithm. Empirical results demonstrate that global state updates suffer from inconsistencies in predicted water levels, whereas topographically based local state updates provide encouraging results. Specifically, the improvement due to the local state update alone is short-lived, and findings indicate that a longer lasting improvement in flood forecasting performance can be achieved through a combination of both state and boundary updates. Overall, the results indicate the feasibility of utilising crowdsourced social media data to improve the performance of flood forecasting systems for urban environments.

It is often taken as given that community-based disaster risk reduction (CBDRR) serves as a mechanism for the inclusion of local knowledge (LK) in disaster risk reduction (DRR). In this paper, through in-depth qualitative analysis of empirical data from Malawi, we investigate the extent to which CBDRR in practice really takes into account LK. This research argues that LK is underutilised in CBDRR and finds that current practice provides a limited opportunity for the inclusion of LK, due to five prime obstacles: i) current approach to community participation, ii) financial constraints and capacity of external stakeholders, iii) the donor landscape, iv) infor-mation consolidation and sharing, and v) external stakeholders attitudes towards LK. In CBDRR, a strong dichotomy between local and scientific knowledge is maintained, and further re-examination of community-based approaches in practice is needed to make them truly transformative.

Index-based approaches are a popular method for assessing societal vulnerability to flooding, many of which differ in terms of indicator selection, underlying social data, spatial scale and aggregation methods. They are typically assessed at geographically broad spatial scales to provide a spatial picture of vulnerability for policy and decision-makers. However, aggregation of vulnerability at broad scales also potentially masks the true vulnerability of an area as the underlying data is not spatially refined. This research expands on a previous indicator approach, the Social Flood Vulnerability Index by using geodemographics to facilitate household and postcode level vulnerability assessment to explore the impact of spatial aggregation on vulnerability at national and local levels in Scotland. The results suggest that applying geodemographics to an existing approach increases spatial heterogeneity and has the potential to be adopted as a new dataset to guide indicator selection in future.

Geobag (sand-filled geotextile bags) revetments have recently emerged as long-term riverbank protection measures in developing countries; however, their performance is still not well understood. The hydraulic stability of geobag revetments used for riverbank protection has been studied within an extensive laboratory programme to improve our understanding of the complete failure processes of geobag revetments. A 1:10 scale distorted physical model was tested in a laboratory flume, comparing a range of different construction methods and revetment side slopes, subjected to different flow loading. The results indicate that whilst failure mechanisms are highly dependent on water depth and revetment slope, the construction method had no noticeable impact. It was thus concluded that the dominating factor is the friction between individual geobags, which itself is dependent on bag longitudinal overlap rather than a specific construction method.

The development of technology has made it easier for engineers to design and test models that allow simulation of real-time water distribution networks with greater accuracy. However, with so many nodes and links in a network, building a model still requires some simplification. One such simplification is the ‘conservative approach’, which applies the principle of ‘lumped demand’, taking the demand only from nodes at the ends of pipes. Herein, the full effect of lumped demand on key water parameters is analysed, on a large-scale network based on as-built networks of Al Furjan and Dubai Silicon Oasis, Dubai, UAE for different conditions. Epanet and WDNetXL software are used for the analysis, and results show the impact of different levels of skeletonisation on the head and velocity values for the two models. The analysis indicates that the head changes are high for a branched network under the extreme condition of firefighting. It includes the effect of skeletonising local tanks, with changes being higher when all tanks are empty. These findings provide a critical evaluation of the performance of this method for the Middle East region and it is concluded that the considerable velocity changes observed in the models could lead to overdesign.

Consumption of water varies throughout the day due to the daily routines of the consumer. This pattern of daily water consumption is called the water demand profile. The initiatives to create these profiles are to improve hydraulic performance and to build energy conservation strategies for designed networks in Dubai. Therefore, the aim of the work presented here was to develop and analyze a domestic consumption profile for selected developments with socio-demographic factors including weekday/weekend variation, population, income, fasting during the month of Ramadan, and the outbreak of COVID-19. Data from more than 7000 smart meters were collected while water meters of more than 350 residential flats were examined manually. Water demand profiles generated from the data showed weekdays have more predictable peaks (morning 6–8 am and evening 5–7 pm) than weekends. During Ramadan, peak hours shifted to 7–10 am followed by 3–4 pm during workdays while peaks for low-income areas were higher due to a stricter working routine. The COVID-19 crisis has led to significant rise in observed consumption, with over a 30% increase during the month of Ramadan. The observed results, if compared with further end-use studies on more factors affecting demand profiles, can help in generating both cost and energy efficient networks.

The role of private tanks is to provide excess storage to the consumer to satisfy the water demand. However, they are disregarded during the design stage, in favor of simplified network analysis. This affects the accuracy of the simulation because vital components, such as tank inlets and volume sizes, are completely ignored. Hence, the purpose of this study is to demonstrate the effectiveness of advanced modeling of water distribution networks (WDNs), encompassing the presence of local private tanks, to determine the optimum values of different parameters of private tanks by conducting time- and volume-based reliability analyses. Two network models are used to perform the analysis: a small sample network and a real network that resembles the area of Dubai Silicon Oasis, Dubai, United Arab Emirates. The results obtained from the simulation of networks indicated that the lowest orifice and volume sizes to achieve the required reliability of unity is the optimum values. Furthermore, it implied that any change in their optimum values would either result in tank failure or increase in the head loss and carbon footprint of the network.

Despite the availability of some studies related to rainfall characteristics in Sharjah city and the UAE, very few of these studies have investigated any causal link between recent cloud-seeding missions and the increasing rainfall intensities and urban floods being experienced. This study has assessed the impact of cloud-seeding operations that started in 2010 on the IDF curves of Sharjah city, The UAE. Hourly rainfall data spanning between 2010 and 2020 available at three stations, namely Sharjah Airport, Al Dhaid, and Mleiha, and provided by the National Center of Meteorology were used. To allow comparison with the pre-cloudseeding (2010) era, these records were extended back to 1992 using the much longer data available at Dubai Airport with the aid of the Self-organizing map approach. The developed IDF curves showed an apparent increase in rainfall intensities after implementing the cloud-seeding missions. In addition, the estimated mean rainfall intensities for three regions of the city were also much higher for the cloudseeded years compared to the pre-cloudseeding period. The study suggests that, while cloud-seeding provides water security benefits, its impact on urban flooding should also be carefully considered in the context of urban development plans.

Urban flooding can cause widespread devastation in terms of loss of life and damage to property. As such, monitoring urban flood evolution is crucial in identifying the most affected areas, where emergency response resources should be directed. Flood monitoring through airborne or satellite remote sensing is often limited due to weather conditions and urban topography. In contrast, crowdsourced data is not affected by weather or topography, and they hence offer great potential for urban flood monitoring through real-time information shared by individuals. Despite the benefits, there is no guarantee of quality associated with crowdsourced data, which hampers its usability. In this paper, we present and evaluate two different approaches (binary logistic regression and fuzzy logic) to assess the quality of crowdsourced social media data retrieved from the public Twitter archive. Input variables were constructed based on Twitter metadata and spatiotemporal analysis. Both models were trained and tested using actual flood-related information Tweeted during three consecutive years of flooding in Phetchaburi City, Thailand (2016 to 2018), and produced good results. The fuzzy logic approach is shown to perform better, however its implementation involves significantly more subjectivity. The ability to assess data quality enables the uncertainty associated with crowdsourced social media data to be estimated, which allows this type of data to supplement conventional observations, and hence improve flood management activities.

In the research and policy environment, local knowledge (LK) is increasingly seen as an important component of building the resilience of communities and delivering sustainable disaster risk reduction (DRR) approaches tailored to local contexts. Many studies focus on documenting LK in different contexts; however, far less emphasis has been given to understanding how external stakeholders (i.e. government, NGOs, consultants) engage with and perceive the value of LK for DRR. Through an intepretivist epistemology and a case study research design, this paper sets out to fill in this gap by engaging with external stakeholders involved with community-based flood risk management in Malawi. It bases its findings on a thematic analysis of qualitative data collected through focus group discussions (n = 7) and key informant interviews (n = 69) conducted in 2016 and 2017. The findings show that although there is an appreciation of the importance of LK in rhetoric, its inclusion in DRR practice remains limited. The strong dichotomy between local and scientific knowledge persists and it has led to the further marginalisation of LK. The international policy and research push for LK in DRR is therefore not translated to realities on the ground. To the best of our knowledge, this presents one of the first studies of external stakeholders' attitudes of LK and how these influence its overall position in DRR. The paper calls for further development of knowledge co-production processes that will be based on giving equal weight, recognition and importance to LK.

People possess a creative set of strategies based on their local knowledge (LK) that allow them to stay in flood-prone areas. Stakeholders involved with local level flood risk management (FRM) often overlook and underutilise this LK. There is thus an increasing need for its identification, documentation and assessment. Based on qualitative research, this paper critically explores the notion of LK in Malawi. Data was collected through 15 focus group discussions, 36 interviews and field observation, and analysed using thematic analysis. Findings indicate that local communities have a complex knowledge system that cuts across different stages of the FRM cycle and forms a component of community resilience. LK is not homogenous within a community, and is highly dependent on the social and political contexts. Access to LK is not equally available to everyone, conditioned by the access to resources and underlying causes of vulnerability that are outside communities' influence. There are also limits to LK; it is impacted by exogenous processes (e.g., environmental degradation, climate change) that are changing the nature of flooding at local levels, rendering LK, which is based on historical observations, less relevant. It is dynamic and informally triangulated with scientific knowledge brought about by development partners. This paper offers valuable insights for FRM stakeholders as to how to consider LK in their approaches.

Permeable pavements play an essential role in urban drainage systems, making them a subject of great interest to both researchers and practitioners. The majority of studies, however, have demonstrated a significant degree of uncertainty regarding both the operational performance and maintenance requirements of this type of pavement. This paper describes a laboratory-based experimental study investigating the influence of sediment on the hydrological performance of a permeable pavement. The experimental results show that, under sediment and rainfall loading typical for a 10 year period within the UK, partial clogging of the pavement voids with sediment led to a 6·4% decrease in total outflow, a 6·41% decrease in outflow rate, a 9·5% increase in outflow start time, a 20·7% increase in total outflow duration and no significant change in the concentration of suspended solids. However, no surface ponding was observed and it was therefore concluded that an appropriately designed permeable pavement system, exposed to typical UK rainfall and sediment loadings, should be able to operate efficiently for at least 10 years without the need for any post-construction maintenance. Hence, permeable pavements continue to represent an excellent form of source control for both surface runoff and pollutants.

Current flood risk strategies in Malawi are characterized by community-based flood risk management (CB-FRM), even though studies explicitly documenting evidence of successful CB-FRM remain limited. This paper investigates the realities and challenges of CB-FRM as seen through a lens of different stakeholders. In order to capture the experiences of CB-FRM, a predominantly qualitative research framework was developed. In 2016, 11 focus group discussions with stakeholder groups (local communities, local government and non-governmental organisations) were held. Additionally, informal discussions, field visits, a short survey and an extensive desk study were undertaken. The findings were analysed according to the major themes that emerged related to the realities and challenges of specific stakeholder groups. Although response and relief still remain prominent components of CB-FRM in Malawi, a number of mitigation and preparedness activities is observed. However, a lack of in-country resources, relief-oriented aid approaches and an ‘aid dependency’ syndrome represent obstacles. Different stakeholder groups share similar challenges in terms of financing, participation, decentralised governance and project management. Lack of project sustainability and localised ownership also emerged as major challenges. The identified challenges shed light on the frontiers and directions in which improvements are needed, thus offering a valuable contribution to the existing knowledgebase.