In this study, multi-temporal satellite images combined with rainfall data and field observations were used to assess the spatial and temporal changes in urban flooding and urban water harvesting potential in the coastal city of Sharjah, United Arab Emirates (UAE) during the period from 1976 to 2016. During the study period, the population increased by approximately 14-fold with about a 4-fold increase in built areas. Being in a hot, dry region with average rainfall of about 100 mm/year, the city did not invest in a comprehensive drainage infrastructure. As a result, the frequency, extent and risk associated with urban floods increased significantly. The expansion of built areas progressively increased the impervious land cover in the city, decreasing the minimum precipitation required to generate runoff by approximately 32% and significantly increasing the runoff coefficient. In parallel to rapid urbanization, the urban rainwater harvesting potential significantly increased over 1976-2016. Urban flood maps were generated using three thematic factors: excess rain, land elevation and land slope. The flood maps were confirmed by locating urban flood locations in the field using GPS. This study demonstrates the impact of urbanization through assessing the relationship between urbanization, runoff, local floods and rainwater harvesting potential in Sharjah and provides a basis for developing sustainable urban storm water management practices for the city and similar cities.
Abstract:A decision support system (DSS) is developed and applied to assess the susceptibility of water supply systems to droughts, and to aid decision-makers in determining optimal supply strategies. The DSS integrates three fundamental modules for water resources management: (1) a real time rainfall-runoff forecasting model enhanced by Kalman filtering; (2) a water demand forecast model; and (3) a reservoir operation model. Simulation and optimization procedures for the reservoir operation model are based on risk analysis to evaluate the system performance and to derive the most appropriate supply strategy of minimum risk, for the designed operating conditions. The optimization technique, based on genetic algorithms, introduces two new and distinct features, with the aim of minimizing the risks of drought damage and improving the convergence of the model toward practical solutions. Firstly, risk-based measures of system performance, termed reliability, resiliency and vulnerability, are combined into a global risk index, referred to as the drought risk index (DRI). The DRI, formulated as a weighted function of the risk measures, serves as the objective function to be minimized during the search for the optimal operation. Secondly, in the genetic algorithm search, each new generation of water supply solutions is created from solutions with risk levels clustered inside a defined 'acceptable risk space'. In other words, the convergence of the algorithm is improved by retaining only those solutions with DRI values smaller than the maximum acceptable risk. As a case study, the DSS is applied to the water resources system in Fukuoka City, western Japan. The DSS is believed to be an efficient tool for the assessment of a sequence of water supply scenarios, leading to the improved utilization of existing water resources during drought.
Although a few studies on rainfall spatial and temporal variability in the UAE have been carried out, evidence of the impact of climate change on rainfall trends has not been reported. This study aims at assessing the significance of long-term rainfall trends and temporal variability at Sharjah City, UAE. Annual rainfall and seasonal rainfall extending over a period of 81 years recorded at Sharjah International Airport have been analyzed. To this end, several parametric and nonparametric statistical measures have been applied following systematic data quality assessment. The analyses revealed that the annual rainfall trend decreased from −3 mm to −9.4 mm per decade over the study periods. The decreasing annual rainfall trend is mainly driven by the significant drop in winter rainfall, particularly during the period from 1977 to 2014. The results also indicate that high probability extreme events have shifted toward low frequency (12.7 years) with significant variations in monthly rainfall patterns and periodicity. The findings of the present study suggest reevaluating the derivation of design rainfall for infrastructure of Sharjah City and urge developing an integrated framework for its water resources planning and risk under climate change impacts scenarios.
River embankments failure due to severe flooding is an extremely complex phenomena triggering permanent or temporary modification to the river morphology, river flow and sediment movement. Reliable and automatic prediction of these movements is crucial to properly identify the protective measures for residents living within the inundation flood zones. In this regard, BISHOP, a decision tool to automatically predict, at multiple river cross-sections, the slope failure circle with the minimum safety factor has been developed. In this paper, the computer tool BISHOP, named after the simplified Bishop method, is presented. Its applications have proven to be highly efficient in real case studies, where the stability of multiple slope profiles, at different river cross-sections, must be analyzed to establish spatial and temporal evolution of the river banks failures. The integration of the proposed methodology within a comprehensive flow hydrodynamic, sediment transport and landslide calculation has particularly enhanced the evaluation of the flood-risk zone during major flooding. Typical results demonstrating the effectiveness of the developed methodology are demonstrated during the analysis of the evolution of a river reach downstream of a dam a dam break scenario.
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