Explore the vast range of titles available.

To advance proper planning, water accounting (WA) could provide the possibility of linking physical and operational data to their interdisciplinary attributes. In its new form, WA, combined with a dynamic model considering socio-economic aspects, is a valuable tool for rectifying today's water issues. The social water-accounting-based system dynamics (SWA-SD) model provides a feedback-based platform to better support flexible decision-making. Analyzing the indicators that correspond to water security in the context of DPSIR (driving force-pressure-state-impact-response) and SWA-SD combined with principal component analysis (PCA) for identifying data patterns is applied to a generic study area suffering from water stress to assess the environmental, economic, and social vulnerabilities. The water accounting has to be based on water balance data (called water accounting balance). As a practical solution to generate water balance data, a time series using basic climatic and hydrologic data is synthesized. According to the results, the water stress and urbanization index were increased by 43% and 64% in 2020 during a 20-year time horizon, respectively, which is alarming for the region. Moreover, the economic and social water resources vulnerability shows an upward trend. The environmental component shows many ups (as much as 2.24) and downs (as low as 0.73) due to different supply measures responding to the increasing demands. This study provides a basis that can be replicated for other developing regions to quantify this type of important planning information and for implementing different socially sensitive triggers and technically feasible to measure water vulnerabilities.

In a companion paper (Part 1), the basic concepts are discussed in details. In this paper, the application of the concepts and the proposed methodology in that paper are utilized to set the strategies in order to quantify reliability attributes. The case study is Hunts Point wastewater treatment plant and its sewershed in Bronx, New York City, so that it could function during flood. The strategies are selected and reliability of the Hunts Point plant is estimated before and after using best management practices (BMPs). Therefore, the copula based non-stationary 100–year flood frequency analysis of rainfall and storm surge analyzed in the companion paper (Part 1), are used to obtain the design values of surge and rainfall. A differential evaluation Markov Chain with Bayesian interface is used in that paper for parameter estimation. Because the co-occurrence of surge and rainfall is more critical in coastal areas, the design value resulted from bivariate analysis has been considered in this study. In this Part 2, a multi-criteria decision making (MCDM) approach, which characterized the uncertainty of sub-criteria in load-resistance concept, is applied. The Margin of Safety (MOS) concept is extended to numerically assess a rather non-probabilistic MCDM evaluation of load and resistance to estimate the reliability of the plant. Finally, Effective strategies are selected for flood hazard mitigation to improve the reliability and performance of the plant. The results present an increase of about 46% in reliability after using BMPs. The framework presented in this paper is applicable to other coastal watersheds and could be a platform for addressing some pressing issues in coastal preparedness with impacts on design criteria of coastal infrastructure.

Due to increasing flood severities and frequencies, studies on coastal vulnerability assessment are of increasing concern. Evaluation of flood inundation depth and extent is the first issue in flood vulnerability analysis. This study has proposed a practical framework for reliable coastal floodplain delineation considering both inland and coastal flooding. New York City (NYC) has been considered as the case study because of its vulnerability to storm surge-induced hazards. For floodplain delineation, a distributed hydrologic model is used. In the proposed method, the severities of combined inland and coastal floods for different recurrence intervals are determined. Through analyzing past storms in the study region, a referenced (base) configuration of rainfall and storm surge is selected to be used for defining flood scenarios with different return periods. The inundated areas are determined under different flooding scenarios. The inundation maps of 2012 superstorm Sandy in NYC is simulated and compared with the FEMA revised maps which shows a close agreement. This methodology could be of significant value to the planners and engineers working on the preparedness of coastal urban communities against storms by providing a platform for updating inundation maps as new events are observed and new information becomes available.

Low-lying coastal urban areas are vulnerable to frequent and chronic flooding due to population growth, urbanization, and accelerated sea level rise originating from climate change. This paper is part one of a 2 paper series, however a detailed literature review on the concept and the technical aspects of both papers is presented. In the 2nd paper, the application of the concepts and the proposed methodology are utilized to set the mitigation strategies for quantification of reliability attributes. The case study is the Hunts Point wastewater treatment plant and its sewershed in Bronx, New York City. The suitability of two major rainfall stations of Central Park and LaGuardia airport in the vicinity of the case study is tested. The copula-based non-stationary 100–year flood frequency analysis of rainfall and storm surge is analyzed to obtain the design values of surge and rainfall. A differential evaluation Markov Chain with Bayesian interface is used in this paper for parameter estimation. In this study, the likelihood of joint probability of co-occurring heavy rainfall and storm surge is determined to illustrate the risk of joint events. Therefore, the copula-based non-stationary 100–year flood frequency analysis of rainfall and storm surge are performed to obtain the design values of surge and rainfall. A multi-criteria decision-making (MCDM) approach that incorporates the load-resistance concept is presented in Part 2 paper to assess the Margin of Safety flood reliability of a wastewater treatment plant (WWTP). The framework presented in this paper is applicable to other coastal sewersheds.

Soil moisture represents many attributes of the geo-hydrological cycle and the climate system. Citizen science through social media as an emerging tool could be utilized to collect soil moisture data. A pilot study area was selected in Shahriar, Iran. A user interface and a sampling process (use of citizen science by subscribers) were designed to analyze the subjective and gravimetric soil moisture data. Furthermore, explanatory moisture condition (EMC), a new initiative to consider land use in soil moisture information from vegetation cover, was evaluated. A statistical artificial neural network was used for quantifying subjective data, and soil moisture layouts were produced by utilizing the ordinary kriging (OK) method. For cross-validating, the land surface temperature data from the MODIS satellite were retrieved. A platform for the region with 200 m grids resolution to collect daily soil moisture at eight ungauged stations is proposed to utilize subjective data from the subscribers and cross-validated with satellite data. A virtual station at the centroid of the pervious part of the study area was selected as a reference station for data collection daily or weekly to generate soil moisture time series. The results showed a high potential of utilizing satellite and citizen science data for real-time estimation of scarce soil moisture data in developing regions.

Rivers bring vitality to a city and its environment. However, today, due to the lack of water for essential purposes in many regions of the world, many urban rivers do not have instream flow. To rectify this, first, a minimum flow of water required to make the river visible is determined, and then the possibility of recirculating water is explored. Ecotourism in the context of eco-solidarity is defined as responsible travel to natural areas that preserve the environment, sustain the well-being of local people, and involve “interpretation and education.” Isfahan is a unique tourism hub in Iran, and the region has faced significant environmental and economic changes. Unlike before, there is no permanent flow in the Zayandeh-Rud River passing through the city. This study evaluates the two river alternatives without and with water recirculation with an uncertain multi-criteria decision-making method (MCDM) and measures an Eco-Index. A detailed uncertainty and cost-benefits analysis, including tourists’ income, capital cost, and some losses to the agricultural sector, are performed. Assuming 12% as an upper bound for the growth of tourists with the water recirculation scenario, the first-year net benefit will be at least $240 million. The net benefit is also estimated by examining the growth in tourism in the three countries of Chile, Greece, and the UAE before Covid 19. Under different scenarios over a 20-year time horizon, it could be as much as $3.64 billion that will significantly change the economic prosperity of the city and the region.

The continued development efforts around the world, growing population, and the increased probability of occurrence of extreme hydrologic events have adversely affected natural and built environments. Flood damages and loss of lives from the devastating storms, such as Irene and Sandy on the East Coast of the USA, are examples of the vulnerability to flooding that even developed countries have to face. The odds of coastal flooding disasters have been increased due to accelerated sea level rise, climate change impacts, and communities’ interest to live near the coastlines. Climate change, for instance, is becoming a major threat to sustainable development because of its adverse impacts on the hydrologic cycle. Effective management strategies are thus required for flood vulnerability reduction and disaster preparedness. This paper is an extension to the flood resilience studies in the New York City coastal watershed. Here, a framework is proposed to quantify coastal flood vulnerability while accounting for climate change impacts. To do so, a multi-criteria decision making (MCDM) approach that combines watershed characteristics (factors) and their weights is proposed to quantify flood vulnerability. Among the watershed characteristics, potential variation in the hydrologic factors under climate change impacts is modeled utilizing the general circulation models’ (GCMs) outputs. The considered factors include rainfall, extreme water level, and sea level rise that exacerbate flood vulnerability through increasing exposure and susceptibility to flooding. Uncertainty in the weights as well as values of factors is incorporated in the analysis using the Monte Carlo (MC) sampling method by selecting the best-fitted distributions to the parameters with random nature. A number of low impact development (LID) measures are then proposed to improve watershed adaptive capacity to deal with coastal flooding. Potential range of current and future vulnerability to flooding is estimated with and without consideration of climate change impacts and after implementation of LIDs. Results show that climate change has the potential to increase rainfall intensity, flood volume, floodplain extent, and flood depth in the watershed. The results also reveal that improving system resilience by reinforcing the adaptation capacity through implementing LIDs could mitigate flood vulnerability. Moreover, the results indicate the significant effect of uncertainties, arising from the factors’ weights as well as climate change, impacts modeling approach, on quantifying flood vulnerability. This study underlines the importance of developing applicable schemes to quantify coastal flood vulnerability for evolving future responses to adverse impacts of climate change.

Water Distribution Systems (WDSs) are indispensable infrastructures for urban societies. Due to vitality of continuous supply of drinking water in urban areas, it is necessary to have a performance evaluation and monitoring system to provide the expected level of security in water distribution systems. A main weakness point of these systems is the physical break of pipes which results in high level of water loss, pollution risk and public unsatisfactory. In this study, a framework is developed to increase physical water supply security in urban areas. For this purpose, a physical vulnerability index (PVI) is developed for evaluation of physical statues of water mains. In quantifying PVI, pipe characteristics and bedding soil specifications are considered. The importance of these factors on PVI is determined using Analytical Hierarchy Process (AHP). In system performance evaluation, the pipe role in system performance is incorporated regarding pipe location in WDS, distance of pipe from reservoir and average pressure of pipe. Then, System Physical Performance Index (SPVI) is evaluated. An optimization algorithm is employed to determine ways to improve the system performance through enhancing the physical condition of the pipe in the system at a minimum cost. The genetic algorithm is employed for solving the optimization model. A global sensitivity analysis method named FAST, is used for sensitivity analysis to incorporate the correlation between different parameters in analysis. The proposed framework is applied to a case study located in Tehran metropolitan area. The results of this study show the significant value of the proposed algorithm in supporting decision makers to better choose vulnerable pipes for rehabilitation practices in order to decrease system vulnerability against physical failures.