Quantitative assessment of the variations in monthly precipitation trends induced by the impact of three gorges dam.

There are many studies that have examined the impact of the Three Gorges Dam (TGD) on changes in meteorological data, and most of them concluded that the TGD significantly reduced precipitation without taking into account the negative trends that had already existed before the impoundment. In this study, the investigation focused on the monthly precipitation data, and the Mann-Kendall (MK) trend analysis was conducted to show that the TGD had little effect on the trends of the precipitation data. Monthly data (1980-2018) from 19 stations upstream and downstream of the TGD and 5 stations located far from the main river were extracted. The analysis and results showed that although the linear long-term (1980-2018) precipitation trend upstream of the TGD was downward, the MK trend analysis showed that the precipitation trends became upward after impoundment. This situation existed even for station data located outside the region. Also, the analysis of monthly trends in different seasons showed that in spring and winter, there was only a very weak downward trend in monthly precipitation, while in summer and autumn, the trends were upward with steeper slopes. Following the upward trends of the monthly precipitation, the TGD generally positively intensified the monthly precipitation trends upstream and downstream of the dam, with the exception of a few months when total precipitation amounts were consistently low. In contrast to the trend analysis, which showed small and insignificant variations in precipitation data, the 12-month SPEI analysis showed a significant deterioration (about 20%) in the wetness index after impoundment both upstream and downstream of the TGD, while this situation did not occur outside the region. Thus, the TGD has extended dry periods both upstream and downstream of the dam over the past two decades.

A novel objective for improving the sustainability of water supply system regarding hydrological response.

In general, the sustainability of the water supply system is indicative of an adaptive operational approach, wherein the decision-maker adjusts the system's performance based on the availability of water resources in a given time frame. In light of this, a novel framework is proposed in this study to evaluate sustainability, including three key indicators: resilience, reliability, and vulnerability. To address stressors that may lead to system failure, a multisectoral water allocation optimization is undertaken. In order to account for the future implications of climate change on the hydrological cycle, a simulation step, is incorporated, utilizing the Soil and Water Assessment Tool (SWAT) under various emission scenarios (RCP4.5 and RCP8.5), prior to integrating the streamflow data into our proposed optimal framework. To calibrate and validate historical data (2014-2019) and simulate future streamflow patterns (2025-2085), the Sistan Basin, located in an arid region of Iran, is analyzed as a case study. In light of the anticipated adverse impacts on the water supply system, certain adaptation measures, such as demand shrinkage scenarios, are considered to further appraise the proposed framework. Based on the final output, it is evident that the agricultural and industrial sectors, being the primary water consumers, are more susceptible to negative impacts resulting from the reduction in system sustainability. This susceptibility is primarily attributed to their highest vulnerability and comparatively lower reliability.

Prediction of water quality under the impacts of fine dust and sand storm events using an experimental model and multivariate regression analysis.

Many regions of the world, especially arid and semiarid areas, occasionally experience fine dust and sandstorms, known environmental problems that make normal life difficult. Since the intrusion of large amounts of dust into treatment plants may significantly change the water quality indices, the main goal of this study was to estimate these indices during the events, which can help decision-makers to improve water quality. To achieve relationships using nonlinear multivariate regression analysis, a long-term (three years: April 2017-February 2020) experimental study of water quality parameters including total dissolved solids (TDS), hydrogen content (pH), electrical conductivity (EC), chlorine (Cl), total hardness, sodium (Na), and magnesium (Mg) for water samples from wastewater treatment plants in Sistan region (Iran) was conducted where is one of the most popular regions in the world with high amount of annual fine dust level. Analysis of ANOVA showed that of all the independent parameters considered in this study, water quality parameters strongly correlated with monthly mean sand and dust storm index (SDSI), wind speed, temperature, and the number of monthly windy days. For the regression analysis, 25 months of data were used for the simulation process and 10 months for validation. The final results showed that the relationships obtained from the nonlinear multivariate regression analysis could predict the water quality indices very well (with R2 more than 0.75) except for Mg with R2 equal to 0.55. In addition, the maximum mean relative error belongs to Mg (10.8%) and then Na (9.9%) whereas the minimum mean relative error belongs to pH (2.6%) and then EC (2.9%).

Dynamic multi-objective programming model for improving consumer satisfaction within water supply system under uncertain environment.

Water scarcity poses a real crisis for decision makers of water supply system because satisfying growing demand and, as a result, achieving full consumer satisfaction in different sectors of the system remains a major problem. Therefore, this study develops a dynamic multi-objective model of water supply optimization under different scenarios to improve multisectoral consumer satisfaction. To diminish the negative effects of the water crisis on long-term consumer satisfaction, the performance of the dynamic water supply system is evaluated and optimized, which can change the situation from a state of dissatisfaction to satisfaction. In this regard, to analyze the developed model, a real case study of the Hamoun wetland in southeastern Iran is considered. According to the proposed model, various strategies are performed along with the analysis of two scenarios related to runoff uncertainty in order to investigate the consumer satisfaction status in detail. However, given to the final results, which show the greater impact of the two sensitive factors of reliability and vulnerability on consumer satisfaction, the highest level of dissatisfaction is related to the agricultural sector because it has less reliability and higher vulnerability compared to other sectors. In this regard, by proposing policies such as weight scenarios and demand reduction scheme, the situation of consumer satisfaction has improved much more desirable.

How to improve public participation in disaster risk management: A case study of Buein Zahra, a small city in Iran.

Identifying and providing basic solutions using a collaborative approach in earthquake-stricken cities of Iran has not yet been addressed. This article focuses on an area of practice and views disaster risk management from the point of view of volunteer groups to illustrate how the main components of disaster risk management affect the strengthening of public participation. In this article, Buein Zahra, a small city in Iran, is considered as a high-risk earthquake zone. The basic components of risk management are identified, namely public awareness, knowledge, skills, enabling environment, organisational development and social participation. An assessment of these indicators was done, and multidimensional relationships were established between them to enable an increase in the capacity for public participation. Accordingly, the results indicate that a mere increase in public awareness and knowledge, as seen today, and an improvement in enabling environment, although affecting disaster risk reduction, cannot by themselves lead to real public participation. Organisational development and strengthening of crisis coping skills are two key components to improving participation during crises in the small cities of Iran. According to the results of this study, institutional capacity and unreal political commitment have caused inefficiency of public participation in earthquake preparedness.