مجله تحقیقات منابع آب ایران
سال نوزدهم شماره 1 (پیاپی 64، بهار 1402)

Floods have many negative economic, social, and environmental impacts. The occurrence of this phenomenon in the West and South West of Iran has caused many challenges for the region and its communities. Investigating the flood monitoring parameters plays a key role in reducing the problems in the area. One of the most important hydrological parameters affecting this phenomenon is the the Total Water Storage (TWS). The purpose of this study is to use the GRACE and GRACE FO TWS time series data, as well as TRMM (The Tropical Rainfall Measuring Mission) rainfall time series, to extract the flood potential index (FPI). FPI is used to check the occurrence of floods in the study area. The geographical area investigated in this research was between 45-49N and 30-35E, which includes most of the West and South West parts of Iran. The studied time period was from 2002 to the end of 2019. The TWS anomaly extracted from the data of the GRACE satellites was validated using the water balance equation and TRMM satellite precipitation data, MODIS evapotranspiration data, and GLDAS hydrological model runoff data. The results obtained for GRACE and FO GRACE satellites yielded RMSE values of 0.034 and 0.051 meters, respectively. Then, in order to predict the possibility of floods, the process of determining the Flood Potential Amount (FPA) was run using the the GRACE/GRACE FO TWS data and the TRMM rainfall data between 2002 and the end of 2019. Finally, the obtained FPA was used to determine the FPI. The results showed that the FPI index is able to detect many floods that occurred in the studied area.

Issues related to water resources are complex due to two main reasons. First is the inherent nature of these resources in that they are exhaustible while it is difficult to limit the use of them. The second reason is the multiplicity and variety of dimensions related to water issues. In this study, in order to analyze the water resources governance model, the archetypes in the model were identified and intervention policies were presented. In this study 13 Archetypes are identified and analyzed in the form of five types introduced in the research literature, including limits to growth, fixes that fail, shifting the burden, escalation, and success to the successful. Then the leverage points identified using the twelve intervention levels provided by Meadows (1999) and the hour chart provided by Abson et al. (2017) were analyzed in terms of the level of influence. In this study, in addition to the proposed intervention measures, it was suggested to design and implement intervention measures at two levels in order to avoid falling into the trap of partial measures. At the first level comprehensive and long-term measures and at the second level short measures should be designed and implemented to facilitate the implementation of the long-term program.

The Caspian Sea level (CSL) fluctuations are driven by reciprocal hydro-meteorological processes which extend not only over the entire catchment area but also far beyond. According to the research literature, CSL has dropped approximately 3 m in the short-term period of 1929-1977. The origin of CSL changes and the future of these changes are still being debated. In this study, changes in precipitation, runoff, and evaporation in the catchment area, river discharge, sea surface temperature (SST), and also CSL change were investigated over 40-year. Study results revealed two major changes in the increasing trend of SST anomalies. With an increasing trend in the CS level with 0.03 slope, the results indicated an increase in SST by more than 1.5°C during the study period, which can be a response to the increase in air and land surface temperature on a regional and global scale. The decline in river discharge levels has also been significant in recent decades. These changes were more obvious in the volga river, which provides more than 80% of the CS balance. Reconstruction of long-term CSL change with daily water level data between 1981 and 2020 through fluxes also showed that the average sea level rise was about 20 cm/yr in the 1981-1995 period while a decrease of 6 cm/yr during the 1996-2020 period was clearly visible in the results of the water balance equation. Moreover, according to the observed peak values of the four parameters of precipitation, evaporation, runoff, and SST, the trend of increasing sea surface temperature and decreasing precipitation (with a slope of -1.8 mm/40yr) is more consistent with CSL change.

Nowadays, drought as the most destructive and damaging consequence of climate change has increasingly affected the earth. One of the most important strategies for dealing with devastating droughts is understanding and adapting to them, which can greatly reduce their negative effects. The aim of this quantitative and applied research is to examine and analyze the adaptation status of farmers to drought and identify solutions to deal with it through a case study among farmers in the Zayandehrud river basin  in Isfahan province. The statistical population of the research consists of all farmers in the east of Zayandehrud basin (villages of Nokhodabad, Hasanabad, Haratmeh, Joshan, and Mazrae Cheh) of whom 200 were selected as a completely random sample to achieve the research objectives. The main tool for collecting data in this study was a researcher-made questionnaire. For analyzing the collected data, the mean comparison test, frequency distribution table, and exploratory factor analysis method were used in SPSS software. The results of the research showed that the calculated mean for the adaptation of farmers to drought was 2.165, statistically significantly lower than the average level at a confidence level of 95 percent. Exploratory factor analysis revealed that six main factors are identified as the most important key solutions for improving how farmers are adapting to and coping with drought in Zayandehrud basin, explaining 71.88 percent of the dependent variable variance. These factors, in order of importance, are financial-organizational policies (17.533 percent), educational-promotional policies (12.946 percent), technical-agricultural policies (12.421 percent), infrastructure (10.697 percent), strengthening social institutions (9.188 percent), and enhancing local participation (9.096 percent).

The purpose of the research is to calculate the performance indexes of water supply system based on perspective of classical and fuzzy probabilities using three-different fuzzy membership function under climate scenarios in baseline period (1977-2001) and future (2015-2040) in the Marun Basin. First, the effects of climate change on temperature and precipitation were estimated for the period of 2015-2040 using climate models of the fifth report of the International Panel on Climate Change (IPCC) under RCP 2.6, RCP 4.5 and RCP 8.5 scenarios. For the same period, ANN were used to determine the changes in inflow to reservoir and the irrigation water requirements were determined using Cropwat. Then, the water supply system was modeled with WEAP, the goal of which was to maximize the water delivered to the points of need based on the defined conditions. The crisp and fuzzy water supply system performance indexes were then calculated. Results showed that under RCP 2.6, RCP 4.5 and RCP 8.5 scenarios, temperature will increase by 19, 20, 21%, and precipitation will decrease by 5% and increase by 14 and 15%, respectively. Future irrigation water requirements will increase relative to baseline, while inflow to the reservoir will decrease under RCP 2.6 and RCP 4.5 and increase under RCP 8.5. Also, the results showed that (1) the resiliency and vulnerability in the fuzzy environment with Gaussian and exponential fuzzy membership functions increases compared to the crisp environment, and (2) the choice of the type of fuzzy membership function is very important in extracting the results and so the fuzzy membership functions with fuzzy core perform very well in water resource management problems.

Conflict, an inevitable part of human interactions, is a complex, dynamic, and multidisciplinary process with interactions with a variety of social systems. The differences in theoretical frameworks and distinct understanding of human relations led to the formation of different theories to deal with the conflict. Neoliberal institutionalism is one of the novel theories in the field of political, economic, and social studies, emphasizing the importance of institutions in shaping behavior. According to this theory international institutions are effective tools for creating convergence and international cooperation. Liberal institutionalist perspectives are widely accepted and used by researchers in the fields of environment and water management. Water institutionalists believe that international water institutions can significantly reduce international water conflicts and promote water cooperation. However since water institutions have not always succeeded in that aim, serious criticisms have been made on institutionalism theory. Despite the importance of studying and analyzing the theoretical background of the neoliberal institutionalism and transboundary water conflicts, no specific scientific research has been conducted in this regard.  This study critically examines the capacity of neoliberal institutionalism to deal with water conflicts and to facilitate effective cooperation in transboundary river basins.

Flood risk analysis is a basic tool for flood planning and management. Usually, risk analysis is done based on the expected annual damage (EAD), which in this research is estimated based on hydrologic-hydraulic modeling. The annual expected damage is estimated based on instantaneous maximum discharge and daily maximum discharge. Flood frequency analysis, geometry estimation in GIS platform, and HEC-RAS hydraulic modeling have been done to estimate the annual expected damage. The results indicated that as the return period of the flood in the studied river increases, the area affected by the flood increases significantly up to the return period of 100 years and after that it is not much dependent on the return period. For example, the flood extent for a return period of 100 years compared to 500 years is only 7.5% less based on daily maximum discharge and 15% less based on instantaneous maximum discharge. The amount of expected annual damage based on the analysis of daily maximum discharge and instantaneous maximum discharge is 10.25% and 11.6%, respectively. These results show that the annual flood damage in this area is low and the implementation of hard engineering measures for flood control is not justified.

Artificial intelligence can learn, infer, and make intelligent decisions. One of the main advantages of artificial intelligence is that by extracting patterns and learning from data, it can correctly diagnose and predict problems. Artificial intelligence has been noticed as a tool to better solve problems due to its many applications in various fields. In recent years, this algorithm has been used in the area of water and wastewater treatment processes to model, optimize, and provide solutions for strategic management to prevent and reduce water pollution, reduce operating costs, and optimize the use of chemical substances. Various artificial intelligence algorithms in water and wastewater treatment processes focus on pollutant absorption and, in most cases, on the performance of adsorbents to remove organic and metal pollutants. This study presents various artificial intelligence models, their advantages, limitations, challenges, and research problems of models in water purification processes. Considering the many advantages of artificial intelligence, this algorithm with limitations can prevent its expansion in water purification processes. Regardless of these limitations, current research progress shows that artificial intelligence tools have great potential to revolutionize wastewater treatment processes and programs. According to the models reviewed in this research, the use of DNN, ANN models, and combined artificial intelligence techniques are good options to achieve more accurate predictions.

In this study, the Urban Water Scarcity Index (UWSI), a hydrology-demography based-index, was developed to assess the intensity of water scarcity in urban areas. The UWSI index is presented to show the difference between hydrological drought (in terms of standardized streamflow index) and the water-crowding index. For the application of the developed index, the city of Tehran was considered as a case study in which about 72% of the domestic water demands are supplied from the surface water sources in the surrounding catchments. The time series of the monthly data of surface water flow entering five reservoirs around Tehran during a period of 21 years (1998-2018) and the annual changes in Tehran's population were the input data to this study. The results showed that the annual value of the UWSI index in the three time periods of 1998-2007, 2007-2009, and 2009-2018 has negative, nearly zero, and positive values, respectively. During the first period, hydrological drought dominated the water stress in Tehran. But in the third period, the water stress is much higher than hydrological drought. The positive trend of UWSI during the recent decade reveals that water stress threatens the sustainability in providing the city's water needs. Therefore, strict strategies are needed to manage and overcome the water shortage. The UWSI index developed in this study incorporates both blue water resources (i.e., the river flows) and population size for Tehran city and can be served as an initial water scarcity assessment tool in other urban areas.