IRAN-WATER RESOURCES RESEARCH
Year:2021 | Volume:17 | Issue:1|Papers Count:15

As the ratio of evapotranspiration to precipitation, Aridity Index (AI) is used to quantify the value of aridity. In this study, sensitivity analysis was performed on AI using the partial derivative method based on 7 meteorological variables including Pre, TMax, TMin, ea, U2 and RS in 5 different climates based on De Martonne’ s classification method during the period 1990-2019 on annual time scale. Mann-Kendall test and Sen’ s slope estimation method were employed for the purpose of trend detection of AI variations. CanESM2 atmospheric circulation method under two scenarios including RCP4. 5 and RCP8. 5 and Statistical Downscaling Model (SDSM) were used to predict AI variations in the future period of 2020-2050. The Results of AI trend analysis indicated increased aridity in all stations excluding Mashhad. The Results of sensitivity coefficient showed that precipitation, among all other climate variables, contributed the most to AI variations, as 10% increase in precipitation resulted in a decrease in AI in Rasht, Ilam, Yasouj, Mashhad and Kerman by 10. 72%, 11. 81%, 12. 48%, 11. 14% and 12. 82%, respectively. AI had then the highest sensitivity to TMax and TMin in Ilam and Rasht stations, to ea in Kerman and Mashhad stations, and to Rs in Yasouj station. Throughout the next 30-year period, it is expected that AI values increase in all observed stations except Yasouj. The highest and lowest annual AI increase rates throughout this period would take place in Rasht station under scenario RCP8. 5, and in Mashhad station under scenario RCP4. 5.

Understanding the frequency of dust storms in each area and being mindful of temporal-spatial variation of this event can help to monitor and reduce the damages induced by dust events. Due to the increasing development of metamodels and their combination with optimization algorithms used to model and predict hydrological variables, machine learning models due to high accuracy in forecasting, in the form of a black box, have received a lot of attention. Therefore, in the present study, a hybrid approach is proposed to predict the Frequency of Dust Storm Days (FDSD) on a seasonal scale, which uses a combination of Lang Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) neural networks. In this study, the performance of the proposed hybrid model was compared with a neural network based on Radial Basis Functions (RBF) and Support Vector Machine (SVM). For this purpose, hourly dust data and codes of the World Meteorological Organization were used on a seasonal scale with a statistical period of 30 years (1990-2019) for seven synoptic stations in Khuzestan province. The results of the evaluation criteria in the training and testing Stages showed that the GRU-LSTM hybrid model offered better performance than other models used to predict the frequency of days with dust storms; The proposed hybrid model with correlation coefficient (R) of 0. 905-0. 988, Root Mean Square Error (RMSE) of 0. 313-0. 402 day, Mean Absolute Error (MAE) of 0. 144-0. 236 day, and Nash-Sutcliffe (NS) of 0. 819-0. 903 had better performance compared to the other models used in predicting the FDSD index. In general, comparing the models used in this study, the GRU-LSTM hybrid method and the SVM model, respectively, provided the best prediction skills. As a result, application of the proposed hybrid model can be used as a suitable tool to predict the FDSD index and adopting management decisions to reduce the dust storms damages in the study area.

Limitated fresh water resources in Iran and increasing need for sustainable water resources have attracted great attention to groundwater. However, the renewability of aquifers has worsened owing to drought and climate changes. Groundwater supplies in Abhar plain which provide water for Abhar and Khorramdareh cities have been dramatically affected by overdrilling, which resulted in a sharp drop in the water level. Consequently, deepening of wells has been applied in this area. In this study, the groundwater resources of Abhar plain were investigated to determine the optimum depth in well deepening. To this end, Abhar plain aquifer volume was determined using ArcGIS software. Considering the current conditions of the plain and water resources management policies, three different scenarios were used to predict and evaluate the future conditions of the plain aquifer. The results of these scenarios demonstrated that in the case of current exploitation method, a large area of the western part of the plain would thoroughly dry over the next 25 years, and the saturated aquifer extent will diminish to 65% of the current level. The study findings illustrated the critical role of limiting the agricultural well depth as a management strategy in retarding the aquifer drying trend and slowing down the decreasing rate of the saturated aquifer level.

Estimation of suspended and bed sediment load transferred by streamflow is important for planning and storing water in dam reservoirs, watershed management, coastal and environment protection. In this study, multivariate frequency analysis was performed between the maximum annual values of flood discharge, suspended sediment load and bed sediment load in Sierra Karaj hydrometric station with different copula functions. The common time period between the variables of suspended sediment load and bed sediment load was determined from the water year of 2009-2010 to 2019-2020. The results showed that the best copula functions in the analysis of dependency between the variables of flood discharge-suspended sediment load, flood discharge-bed sediment load and suspended sediment load-bed sediment load are Tawn, Shih-Louis and Gaussian, respectively. The results showed that for the joint return period equal to 10 years for the “ OR” scenario, the values of flood discharge, suspended sediment load and bed sediment load are respectively equal to 125 cubic meters per second, 100 thousand tons per day and 2500 tons per day. Maximum probability of occurrence of suspended sediment load and bed sediment load for joint return period equal to 10 years for “ AND” scenario are equal to 45000 tons per day and 1500 tons per day, respectively. According to the "AND" scenario for the joint return period, the multivariate design quantiles of the suspended and bed sediment loads are smaller than the univariate quantiles. Therefore, ignoring the correlation between suspended and bed sediment load and flood discharge may significantly overestimate the actual sediment value and, consequently, overestimate the corresponding occurrence probability.

As the main component of real water losses, leakage afflicts most water networks worldwide; even the best Water Distribution Networks (WDNs) have leakage in their network infrastructure. Several methods and strategies have been developed for leakage reduction and performance improvement in WDNs. In practice, leakage control strategies, including active leakage control, passive leakage control, pressure management, and infrastructure asset management, are performed by water utilities to reduce leakage. The main question is, which of these leakage management strategies are the most appropriate for a specific WDN? The answer to this question is obtained by analyzing the economic level of leakage (ELL). In fact, the essential component of a leakage control strategy is that its target is set in terms of the economic level of leakage (ELL). This paper provides a comprehensive review of the estimation of the ELL at different time frames, including short-run, long-run, and sustainable in WDNs. In addition, a procedure to estimate the ELL is proposed according to the conditions in each network or the relevant water utilities. Results of this review could be a valuable reference resource for practitioners and researchers dealing with non-revenue water in WDNs.

This study is performed to retrieve precipitation amount using Spinning Enhanced Visible and InfraRed Imager (SEVIRI) from Meteosat Second Generation (MSG). According to the relationship between the infrared channels brightness temperature and the microphysical and optical properties of the clouds (such as cloud top temperature, cloud top height, optical thickness, particle size, and particle phase), and the influence of changes in these properties on the determination of precipitation amount and intensity, the relationship between brightness temperature and precipitation have been studied for two stations in Hormozgan province. The performance of an artificial neural network and also several regression models to estimate precipitation has been evaluated. The results showed that the exponential Gaussian process regression model with performing principal component analysis by RMSE of 0. 44, POD of 0. 96 and the HSS of 0. 67 for precipitation threshold 0. 1 mm for the less than 10 mm precipitation data set have the best performance. The artificial neural network also presented a RMSE of 1. 27 which indicates weaker performance in comparison with the regression model but showed good performance in distinguishing precipitation conditions from non-precipitation conditions (POD of 0. 85 and HSS of 0. 48). By comparing the correlation between precipitation and brightness temperature of infrared channels (average 0. 36), and the correlation between observed and retreived precipitation (0. 91 in the regression model and 0. 43 in the neural network), it can be concluded that the precipitation products which extracted in this study, show a good correlation between observed and retrieved precipitation.

Population growth and population needs, including the need for food, necessitates the development and implementation of policy solutions based on reducing the pressure on water resources. Especially when the notion of food security and selfsufficiency policies for strategic commodities have been the focus of attention in higher policies of the country. One of the most effective solutions is to use a diet that has low water demand. On the other hand, considering some deficiencies in the current diet of the country; it is necessary to change it and design a healthy and sustainable diet that simultaneously promotes the health of the community and reduces its environmental effects (such as water footprint). In this study, the current dietary pattern and three alternative food baskets are evaluated by the multi-criteria group decisionmaking taking into account criteria including health (energy and protein intake from the diet), environment (water footprint), the economic cost of the diet, and social acceptance of the diet. Finally, the desired dietary pattern and its effects are introduced. Also, to analyze the uncertainty of some data, such as the price of products, and to create random numbers, tools such as Central Limit Theorem have been used. One of the most important outcomes of this study is the weakness of the current diet compared to other diets from environmental, health, and economic perspectives. The results also showed that designing diets, while improving health, can lead to an annual reduction in water consumption, which can lead to food security in the country.

In arid regions, excessive use without proper management put water resources under immense pressure and multiple stresses. Finding a good strategy for water resources management is essential to preserve sustainability in such regions. This study aimed at optimizing the water use for the agricultural crops in the Eshtehard watershed in Iran, where the aquifer is a strategic resource for irrigated agriculture and is facing intensive drawdown due to over extraction. A hydro-agronomic simulation-optimization approach is used for surface and groundwater modeling in which the agricultural production and water level variation are simulated by linking SWAT and MODFLOW and the optimal crops pattern is searched for by the PSO algorithm. The crops’ area and their irrigation water consumption are the decision variables with the objective of maximizing the net benefit gained from the crops’ yield while the groundwater drawdown is limited to a pre-defined stability level. Results showed that in the optimum state, irreparable damage to groundwater depletion is reduced. To this result, a part of area cultivated by winter wheat and cotton must be replaced by winter barley which results in reduction of the groundwater extraction for winter wheat, winter barley and cotton by 45%, 7%, and 10%, respectively. Also, after the application of these changes, the profit from winter wheat and cotton crops decreased by 35% and 13%, respectively, and that for barley increased by 49%, which generally increased the production profit of irrigation products by 4%.

Recurring droughts at various intensity leads to decline in streamflow and wetland area. In this study, using Landsat satellite images, temporal changes in the area of the Bakhtegan and Tashk lake from 1986 to 2019 were investigated. Also, based on the Standard Precipitation Index (SPI), the effect of precipitation falling on the lake area as well as the total inflow to the lake were studied. Then, by generating land-use maps, land-use changes in Bakhtegan and Tashk basin area were analyzed. In addition, a model for forecasting lake area (of next year) on the basis of lake area, total inflow, and annual precipitation falling on the lake basin area associated with the previous year was presented. The results showed that in the study period, the minimum lake area occurred in 2011 and was equal to 17. 038 square kilometers, which shows a decrease of 98% compared to the maximum area corresponding to the year 1993. Furthermore, 12-month SPI in Bakhtegan and Tashk Lake basin indicated that the meteorological drought index directly affects the changes of the lake area. However, from 2006 to 2012, the inflow to the lake has severely decreased due to the increasing human interventions within the basin such that, during this period, lake surface area does not strongly respond to SPI variations. The results of the forecast model showed that the coefficient of determination between neural network model output (lake area) with observed lake area corresponding to satellite images was equal to 0. 72. As a result, the forecast model could acceptably predict the lake area.

Deteriorated quality and scarcity of water are two serious problems and the water resources management corresponding to these problems is often accompanied by conflict between consumers. The purpose of this study is to analyze the behaviors and interactions of stakeholders in the Karaj basin in order to provide optimal strategy in sustainable policy-making of water resources in this basin with respect to environmental protection. In this study, definitions of stability were used to analyze the results of the Graph model in non-cooperative game theory. Players include the Ministry of Agriculture, the Regional Water Company, the Farmers and the Department of Environment. The results of the Graph model showed that among the definitions of stability used in this study, Non-Myopic stability analysis is reliable for the analysis of this game and the output of this stability is more likely to occur in the behavior of players. One of the most desirable equilibrium states is the basic situation and the other equilibrium state is the situation in which farmers perform unauthorized withdrawals of irrigation canals, in which case an undesirable situation will occur in the future. Therefore, the water resources management in the basin can be improved by determining incentives from the regional water company for the cooperation of farmers and their training, as well as identifying and punishing violators. Finally, the results showed that using appropriate stability definitions can provide valuable insights for policy-making to analyze specific conflict, when there is uncertainty about player behavior.

Today, with population growth, urbanization and expanding demands of societies, water resources management has received more attention than the past decades. Urban water management is mostly conducted by controlling and directing surface runoff through reducing the peak discharge and flood volume. The construction of storm detention ponds in urban drainage systems delays the time of peak flow and reduces the peak discharge. The performance of these ponds depends on not only their dimensions and their inlet/outlet structures, but also the procedure of operating these structures. In this study, coordinated operation of detention ponds is taken into consideration at Tehran’ s East stormwater urban drainage system, through the gates optimal maneuver. To achieve this, harmony search algorithm (HS) was linked to the SWMM hydrological-hydraulic model to find optimal gate openings of inlet/outlet structures of ponds in order to minimize the volume of stormwater exceeding the hydraulic capacity of drainage network. The results for five extreme rainfall events at the studied catchment showed that the optimal coordinated operation of these ponds has improved the level of ponds performance in terms of network flooding compared to the current method of operation and flooding in the drainage network was reduced by 62% in average for the considered extreme rainfall events.

Preparation of the conceptual model of groundwater flow, as an essential step in groundwater flow modeling, is one of the primary measures in properly managing groundwater resources, especially in arid areas where most consumption is directed to groundwater resources. Preparation of groundwater balance as an essential component of the conceptual model of groundwater flow is associated with problems such as lack and heterogeneity of information due to lack of proper spatialtemporal monitoring network. In the present study, we tried to provide methods for estimating the groundwater balance equation's components as accurately as possible by using auxiliary data, mathematical-statistical tools, and new capabilities of GIS, such as a geostatistical analyst. These methods were implemented in the Mahvelat aquifer, one of Iran's critical aquifers, for 2001-2012 (12 Years). The balance equation's mean error was calculated to be 26. 9% of the total components of the balanced input using the proposed methods of the present study. Then, due to the significant amount of error in the available information, by considering the correction coefficients for the balance equation's components on an annual scale, the absolute value of the errors was minimized using the Taguchi method. The output of these calculations was the optimal values of the corrective coefficients. The result showed that the error was reduced by 97%; from 227 to 115 million cubic meters.

Declining pervious areas is one of the most important effects of land use changes and replacing natural watersheds with urban zones. This phenomenon increases the surface runoff and the possibility of urban floods. In recent years, the unprecedented expansion of urbanized areas of Mashhad City has caused an increase in runoff potential. Since, on the other hand, there is a serious lack of water resources for the city, a comprehensive study on urban surface runoff and methods of managing the runoff has become a serious necessity in Mashhad. In this study, after sub-basin delineation, based on the available data, first the rainfall-runoff process for a number of urban and natural sun-basins was calibrated using HECHMS rainfall-runoff model. Then, the volume of surface runoff was computed for the whole city of Mashhad. Finally, management methods of surface runoff especially in terms of runoff storage were considered both technically and economically. The results showed that despite the high volume of produced runoff, runoff management merely based on storage is not reasonable due to spatial restrictions. In other words, the cost ratio for storing and using each cubic meter of runoff is very high and economically not feasible. Consequently, the main approach in runoff storage in Mashhad needs to focus on utilizing the potential of existing lakes and reservoirs. In addition, the other important approach should be based on storing the water released from Golestan Dam located 5 km of the southwest of Mashhad.

Gotvand Aquifer is one of the aquifers, water resources of which are mainly used for agricultural purposes. To evaluate the water quality of this aquifer with emphasis on nitrate pollution, samples were taken from eleven wells in June 2020. Field parameters (temperature, pH and EC) were recorded and the concentrations of major elements (Ca2+, Mg2+, Na+, K+-, Cl-, SO4 2-, CO3 2-, and HCO3-) and nitrate were measured. The results showed that the spatial distribution of nitrate ion almost follows the direction of groundwater flow in Gotvand aquifer and shows a decreasing trend as moving from the upstream in the northern and western parts to the end of the flow lines in the east and southeast. Ion ratios, NO3− Cl− , K+ Cl− , and SO42− Cl− , showed that the increase in chloride and sulfate ions, beside the natural tectonic factors, is caused by human activities. In the statistical analysis of the main components, the first and second factors respectively contributed to 47. 7% and 32. 2% of the total changes. The predominant type of groundwater is sulfatecalcium. In general, changes in nitrate ion concentration in groundwater of Gotvand aquifer have been affected by the size of soil texture in the area, groundwater depth, irrigation and drainage network, domestic sewage leakage and the use of chemical fertilizers.

The importance of policy making in achieving "water security" on the one hand and complexity of human and water security, on the other hand, have raised the necessity of a comprehensive understanding of the "water security" concept as the first and one of the most significant steps of water policy making process. So far, most of the analyzes related to water security and water policy making have been limited to the development of objective dimensions. To address this limitation, this article tries to redefine the concept of water security with fundamental-theoretical research, using the descriptiveanalytical method. Results showed that in addition to the objective dimensions, it is necessary to pay attention to social, political, and cross-sectoral dimensions. Accordingly, this paper reframes the components of water security with consideration, 1) constructed identities in water relations, 2) the importance of the ideology of stakeholders, 3) identifying securitization and desecuritization of water projects and taking actions against associated politicizing, and 4) the importance of water-food-energy nexus.