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An appropriate distribution of flood losses over time span may dampen the degree of disruption. Flood insurance is one of the effective ways in order to cope with the aftermaths of flood events. In the absence of an acceptable risk-based assessment framework, flood insurance and its extensive benefits are not fully achieved yet. Consequently, flood insurance is trivially practiced worldwide. To ensure the integration of flood insurance into regular flood management practices, its acceptability by floodplain inhabitants is a prerequisite. Therefore, an admissible insurance rate is a vital factor for the acceptability of insurance policy. This article introduces a risk-based methodology to calculate insurance rate. Normally, insurance rates are based on historic flood events or on a specific design flood. Expected annual damages distribution map (EADDM) is developed to assess spatial distribution of risk. Distribution of flood losses against a specific flood is compared with EADDM. The impacts of both approaches on insurance provider and insured are studied. Single flood approach ignores the impacts because of other floods. Therefore, insurance rates based on single flood are not justifiable. The proposed framework not only facilitates risk-based insurance rate calculation but also endorse flood insurance acceptability. Collins and Simpson, 2007). The implementation of flood insurance is mostly supported by legal provisions, public incentives, and enforcement practices. For example, in the United States, no mortgage lenders that are federally bs_bs_banner J Flood Risk Management 7 (2014) 291-307

Water sharing within the states/provinces of a country and cross-border is unavoidable. Conflicts between the sharing entities might turn more severe due to additional dependency on water, growing population, and reduced availability as a result of climate change at many locations. Pakistan, being an agricultural country, is severely water stressed and heading toward a worsening situation in the near future. Pakistan is heading toward water scarcity as water availability in the Indus basin is becoming critical. Being a downstream riparian of India and Afghanistan in the Indus basin, water availability depends on the releases of water from both countries. The Indus Water Treaty is governing the water distribution rights between India and Pakistan. However, there exists no proper agreement between Pakistan and Afghanistan and the construction of new dams on the Kabul River is another threat to water availability to Pakistan. Correct implementation of the Indus Water Treaty with India is required, together with an effective agreement with Afghanistan about the water sharing. In addition to water shortage, poor management of water resources, inequitable sharing of water, lack of a systematic approach, old-fashioned irrigation practices, and growing agricultural products with large water footprints are all exacerbating the problem. The water shortage is now increasingly countered by the use of groundwater. This sudden high extraction of groundwater is causing depletion of the groundwater table and groundwater quality issues. This water shortage is exacerbating the provincial conflicts over water, such as those between Punjab and Sindh provinces. At one end, a uniform nationwide water allocation policy is required. At the same time, modern irrigation techniques and low-water-footprint agricultural products should be promoted. A fair water-pricing mechanism of surface water and groundwater could be an effective measure, whereas a strict policy on groundwater usage is equally important. Political will and determination to address the water issues are required. The solutions must be based on transparency and equity, by using engineering approaches, combined with comprehensive social support. To develop a comprehensive water strategy, a dedicated technopolitical institute to strengthen the capabilities of nationwide expertise and address the issues on a regular basis is required to overcome the complex and multidimensional water-related problems of the country.

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Modern-day flood management has evolved into a variety of flood management alternatives. The selection of appropriate flood measures is crucial under a variety of flood management practices, approaches, and assessment criteria. Many leading countries appraise the significance of risk-based flood management, but the fixed return period is still the de facto standard of flood management practices. Several measures, approaches, and design criteria have been developed over time. Understanding their role, significance, and correlation toward risk-based flood management is crucial for integrating them into a plan for a floodplain. The direct impacts of a flood are caused by direct contact with the flood, while indirect impacts occur as a result of the interruptions and disruptions of the socio-economical aspects. To proceed with a risk-based flood management approach, the fundamental requirement is to understand the risk dynamics of a floodplain and to identify the principal parameter that should primarily be addressed so as to reduce the risk. Risk is a potential loss that may arise from a hazard. On the one hand, exposure and susceptibility of the vulnerable system, and on the other, the intensity and probability of the hazard, are the parameters that can be used to quantitatively determine risk. The selection of suitable measures for a flood management scheme requires a firm apprehension of the risk mechanism. Under socio-economic and environmental constraints, several measures can be employed at the catchments, channels, and floodplains. The effectiveness of flood measures depends on the floodplain characteristics and supporting measures.

Modeling surface water quality using soft computing techniques is essential for the effective management of scarce water resources and environmental protection. The development of accurate predictive models with significant input parameters and inconsistent datasets is still a challenge. Therefore, further research is needed to improve the performance of the predictive models. This study presents a methodology for dataset pre-processing and input optimization for reducing the modeling complexity. The objective of this study was achieved by employing a two-sided detection approach for outlier removal and an exhaustive search method for selecting essential modeling inputs. Thereafter, the adaptive neuro-fuzzy inference system (ANFIS) was applied for modeling electrical conductivity (EC) and total dissolved solids (TDS) in the upper Indus River. A larger dataset of a 30-year historical period, measured monthly, was utilized in the modeling process. The prediction capacity of the developed models was estimated by statistical assessment indicators. Moreover, the 10-fold cross-validation method was carried out to address the modeling overfitting issue. The results of the input optimization indicate that Ca2+, Na+, and Cl− are the most relevant inputs to be used for EC. Meanwhile, Mg2+, HCO3−, and SO42− were selected to model TDS levels. The optimum ANFIS models for the EC and TDS data showed R values of 0.91 and 0.92, and the root mean squared error (RMSE) results of 30.6 µS/cm and 16.7 ppm, respectively. The optimum ANFIS structure comprises a hybrid training algorithm with 27 fuzzy rules of triangular fuzzy membership functions for EC and a Gaussian curve for TDS modeling, respectively. Evidently, the outcome of the present study reveals that the ANFIS modeling, aided with data pre-processing and input optimization, is a suitable technique for simulating the quality of surface water. It could be an effective approach in minimizing modeling complexity and elaborating proper management and mitigation measures.

A Smart City is a solution to the problems caused by increasing urbanization. Australia has demonstrated a strong determination for the development of Smart Cities. However, the country has experienced uneven growth in its urban development. The purpose of this study is to compare and identify the smartness of major Australian cities to the level of development in multi-dimensions. Eventually, the research introduces the openings to make cities smarter by identifying the focused priority areas. To ensure comprehensive coverage of all aspects of the smart city’s performance, 90 indicators were selected to represent 26 factors and six components. The results of the assessment endorse the impacts of recent government actions taken in different urban areas towards building smarter cities. The research has pointed out the areas of deficiencies for underperforming major cities in Australia. Following the results, appropriate recommendations for Australian cities are provided to improve the city’s smartness.

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