مجله تحقیقات منابع آب ایران
سال هفدهم شماره 4 (پیاپی 59، زمستان 1400)

Droughts are the most important challenge in Iran's water supply. In this study, in order to identify the synoptic mechanism of occurrence of climatic droughts in Iran, daily and monthly precipitation data of meteorological stations of provincial centers (sample) and NCAR data analyzed for the period of 1960-2015 were used.  First, the dry periods of the stations were identified by the method of difference between the means and rate methods. Also, to determine the blocking systems, Tibaldi-Multeni index was used and to identify the blocking systems, three quantitative, limit and continuity triple filters were used. Reduction of rainfall or no precipitation in periods of 20 days or more in the cold season leads to severe and very severe droughts in Iran. Synoptic analysis of the study sample indicated that the Atlantic-European region (as a region affecting the synoptic operators affecting Iran's rainfall) and the Pacific have the highest frequency of the blocking system. With the establishment of blocking systems in the cold season of the year, the thickness of the atmosphere (500-1000 hpa) has increased by 10 to 30 geopotential meters and the east winds dominate the Iranian atmosphere instead of the west winds. This change in wind direction leads to the failure of systems such as polar wind and polar front to enter the synoptic area of ​​Iran.  Therefore, with the formation of blocking systems and the resulting blocking conditions of synoptic, drought in the coming wet year is determined and drought damage can be reduced by risk management and predication.

In most studies, the SWAT model is calibrated based on surface runoff in hydrometric stations, and the evapotranspiration component, which has a great impact on the estimation of balance components, is not considered or less considered in the calibration process. Therefore, the aim of this study was to estimate the yield and evapotranspiration values of major crops in Mahabad plain in West Azerbaijan province, through multivariate calibration of SWAT model. Calibration and validation of the model based on the data of a hydrometric station (Gerdyaghoub station located at the exit of the plain), and crop yield and evapotranspiration of the major crops of the region including wheat, barley, corn, sugar beet, alfalfa, apple, and grape. A six year calibration period followed by a four-year validation period was used. In the multi-purpose calibration process, the coefficients of 1, 0.9, and 0.8, respectively, for hydrometric data, yield, and evapotranspiration were considered in the objective function of SWAT-CUP software and SUFI2 method. In general, the sensitivity analysis of the model led to the selection of 43 of the most sensitive parameters according to their sensitivity to river discharge, crop yield and evapotranspiration. Also, the heat unit potential required for full plant growth and Leaf area index (LAI) were the most important parameters to simulate the yield and evapotranspiration crops in the model calibration process. The results showed that the SWAT model was able to simulate the surface flow in the periods of calibration (NSE = 0.85; R2 = 0.87), and validation (NSE = 0.92; R2 = 0.89), as well. The model has high uncertainty in surface flow simulation, especially over-estimation in low flow during calibration period (PBIAS = 4.5%). In evaluating the performance of the SWAT model in estimating actual evapotranspiration, these values ​​were compared with the output of the WaPOR remote sensing model. The results showed that the RMSE criteria varies between 13.8 to 66.4 mm in the calibration period, and between 23.9 to 53.2 mm in the validation period. At the same time, the estimated actual evapotranspiration values ​​of the SWAT model were compared with the estimated crop evapotranspiration of the CROPWAT model. In this study, RMSE criteria in the calibration period between 24.4 (3.6%) to 49.4 (6.5%) mm, and in the validation period between 21.7 (6.2%) to 4.4 53 (7.2%) mm were obtained for different crops. PBIAS values ​​showed that the estimate of SWAT model evapotranspiration in both calibration and validation periods was lower than the estimate of CROPWAT crop evapotranspiration. In general, for most crops, the evapotranspiration values ​​obtained from the SWAT and WAPOR models are far less than the evapotranspiration values ​​estimated by the CROPWAT model that can indicate deficit-irrigation. Crops yield performance estimates were compared by SWAT model with crop yield performance values ​​reported in the region. The results showed a relative estimate of the model for crop performance, while the SWAT model somewhat over-estimated crop performance. The present study showed that multifunctional calibration of large-scale hydrological model SWAT in an irrigated area in addition to using the usual river flow index, taking into account additional parameters such as evapotranspiration and crop yield can increase the accuracy of model results.

This study describes optimization of Support Vector Machine (SVM) using meta-optimization algorithms including the Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Ant Colony optimization for flood susceptibility mapping at Zahedan Basin. To determine the best factors among the 19 factors used in previous studies and the relative importance of input variables, two experiments of Information Acquisition Ratio (IGR) and multilinearity of parameters were used soil moisture content factor which is identified as a highly effective factor (IGR=0.767),  is used directly in this study for the first time. The flood inventory map was prepared from Sentinel-1 satellite data processing and validated. The generated data set was used to map the flood prone areas using SVM model optimized with the mentioned algorithms. For the first time, in this research, ACO algorithm was used to optimize SVM model. The prediction accuracy of the models was evaluated using statistical criterion. All three algorithms used in this study improved SVM performance by 4% in average, while the PSO-SVM model had the best performance among the others with AUC=0.953, MSE=0.025, RMSE=0.158 and StD=0.405.

Flood is one of the most important natural disaster that cause human and financial damages and its evaluation needs peak discharge. This study evaluates Beshar River runoff peak discharge due to precipitation with different return periods. The geological and land use maps were provided in ArcGIS and ENVI, based on which the CN map was prepared. Respectively, 53.46 % and 30.75 % of the study area are in A and D hydrologic groups. The best probability distribution for each station was determined using Chi-square test, thereafter, precipitation with different return periods was calculated. After dividing the area into 9 sub-basins and calculating the required parameters for each, the model was created. Three and two flood events were respectively used for calibration and validation and the average values of RMSE and NS indexes were obtained as 0.53 and 0.67 for calibration and 0.55 and 0.68 for validation. The low values of errors indicated the reliability of the simulated model. The peak discharge of each return period was calculated employing type IA of SCS model. Comparing the peak discharges obtained from HEC-HMS and statistical method at the basin outlet showed that the least difference between these two methods was related to the 50-year return period and for the return periods below and above 50 years, the HEC-HMS discharges were correspondingly less and greater than the statistically calculated peak discharges. Consequently, the HEC-HMS model can accurately calculate the flood peak discharge for Beshar basin.

Assessing the performance of water and wastewater companies is one of the duties of the Ministry of Energy. One of the most important tools for comparing performance is the use of quantitative data envelopment analysis techniques. In recent years, the subject of studying economic efficiency using stochastic data envelopment analysis has been considered by researchers. Data envelopment analysis typically uses past and definite inputs and outputs to measure the performance of decision-making units. For this reason, the problems are the impossibility of estimating efficiency, unrealistic distribution of weights to model inputs and outputs, and the use of definite inputs and outputs. While in the real world, we encounter more random parameters. Therefore, in this paper, the issue of super-efficiency in the analysis of stochastic data for the data of water and wastewater companies of Markazi province based on the statistics of 2016 has been investigated. The computational results of both definite and stochastic super-efficiency models show that Arak Co. is the best company in terms of technical efficiency. Ashtian Company is also the worst company among 17 companies in this research. Although the ranking results of both models are similar for the rating companies, the super-efficiency scores are different.

Water resources systems are constantly changing in all their natural and socio-economic dimensions. So, instead of managing based on predicting the probabilities of various events in the future, inevitably, arrangements must be made for facing the possibility of various phenomena occurring in the future. Therefore, the only option is to base the management of water resources systems on a mechanism for understanding the changes and adapting to them. This type of management, which is based on adaptation to change, is known as adaptive management. One of the main features of an adaptive structure is its institutional adaptive capacity. Therefore, in this article, the adaptive capacity of the Iranian water laws, as part of the formal water institution, will be examined. The evaluation framework used in this research was the adaptive capacity wheel. All water laws of Iran have been analyzed in five legal epochs, including the modern customary epoch, the epoch of private law, the epoch of public law, the epoch of governmentalization of water law, and the epoch of tolerance leading to crisis. For this purpose, the method of qualitative content analysis with quantitative scoring has been used. The results showed that the adaptive capacity of the water laws in each epoch has a relatively negative effect, that is, in the laws of those epochs to deal with the negative effects of the new conditions and adapt to them, there are many gaps that need to be fixed.

One of the most important challenges of hydrological studies is the projection of precipitation variability in a basin in future periods. Atmospheric Ocean General Circulation Models (AOGCMs) can project this variability but in large-scale regions. Various versions of these models have been released, one of which is the CMIP5 series with about 40 dynamic models. In this study, the CCSM4 climate model has been used. The data output of this model is in 1 × 1 (Latitude× longitude) degree. To downscale the precipitation data of this model, the hybrid of two dynamic (WRF1) and statistical methods has been proposed. The study area is the Poldokhtar subbasin in the ​​Karkheh basin and rainfall data between 1996-2005 have been used. First, the precipitation data were downscaled by the WRF model from the range of 1 × 1 degree to 9 × 9 km, and then these data were converted to the range of 3 × 3 km separately by two methods a) hybrid and b) WRF. The results showed that the dynamic downscaling by the WRF model in the range of 9 × 9 km quite shows the precipitation fluctuations during the statistical period. In the 3 × 3 km range, the hybrid method performed better than the WRF method. Finally the results showed that downscaling of precipitation in this basin using both methods is associated with underestimation and should be accompanied by an bias correction method. As a result, by reducing the time and cost of dynamical downscaling of climate models, the findings of this paper can be of great help in making decisions about water resources management in the wet and dry years of the coming decades of a basin.

During last century, anthropogenic forcing and climate change have influenced the stationarity of the many extremes. Therefore, using of stationary pre-assumption-based Frequency Analysis (FA) techniques for estimating the risk of extremes may not be reliable anymore. In present study we introduced a nonstationary FA method to estimate risk of 24-hour maximum precipitation variable, as one of the major factors for generating floods in West of Iran. Nonstationarity assessments showed that among 53 investigated stations, only 4 stations (i.e., Khorramabad and Poldokhtar stations with increasing linear trends and Izeh and Ramhormuz stations with decreasing linear trends) have significant nonstationarity. Three hydrological homogeneous regions were characterized based on statistical properties of 24-hour maximum precipitation variable at study stations. Results revealed that stations in the Region_II, mostly including the stations in Fars, Chaharmahal and Bakhtiari, Bushehr and Kohgiluyeh and Boyerahmad Provinces, have higher risks for more severe 24-hour maximum precipitation compared to stations in other regions. Also, results showed that if nonstationarity in Khorramabad and Poldokhtar stations is ignored, 100-year quantiles of 24-hour maximum precipitation will underestimate around 10.1% and 13.8% in those stations.

Excessive water extraction from aquifers in arid and semi-arid areas poses a serious threat to natural resources and the environment. Damghan's critical forbidden plain has faced a drop in groundwater level in recent years. In this study, the agent-based model has been used to simulate the behavior of effective stakeholders in the region. First, the agent-based model is considered based on the key stakeholders of the region (farmers are the most important consumers of groundwater in the region, Regional Water Company and Agriculture- Jahad), characteristics, behavior, characteristics of the environment, how the interaction between the agents and the environment (Damghan aquifer). Information about exploitation wells and characteristics of the dominant cultivation in the region is related to 1397. To identify the behavior and characteristics of the agents, a visit to the area and interviews with experts and farmers have been done. The characteristics, behaviors, and interactions of agents are expressed by if-then rules or logical operators or by formulated equations. Then, management scenarios in the study area have been studied for 10 years. The results show that the simultaneous implementation of four projects of installing smart meters, modifying well licenses, promoting new irrigation systems, and establishing production cooperatives while maintaining farmers' net incomes will reduce water withdrawal 44% compared to the base scenario. Also, as a result of the implementation of these four projects, the irrigation method of 4000 hectares of agricultural lands will be changed to pressurized irrigation.

Microwave remote sensing soil moisture data have a high ability to provide soil moisture information due to their spatial-temporal coherence. NASA SMAP satellite is one of the most important methods for preparing soil moisture data within the microwave spectrum (L-band) and spatial separation of about 40 km. The low spatial resolution of the soil moisture data of this satellite causes limitations in practical applications and at local scales. In the present study, to subscale daily surface soil moisture data from SMAP 4 level satellite products (with a resolution of 9 km) and increase its resolution to one kilometer, a downscaling algorithm using SMBDA downscaling method, satellite radar image Sentinel 1, and ground observations were developed. For this purpose, 1037 soil samples of soil moisture in 32 different days (autumn and winter of 1399) were measured simultaneously with the passage of time of Sentinel 1 satellite from SalehAbad plain (Ilam). The results showed that the square root of the error between the values ​​of down-scale soil moisture with ground observations is 0.085 (m3.m-3), which has good accuracy compared to similar studies. The effect of the challenges of vegetation change and rainfall on the accuracy of the algorithm results used was investigated. The temporal-spatial extension of field measurements due to the greater variability and dispersion of the measured values ​​as well as the implementation of the algorithm using non-classical methods (soft computing) can improve the results of downscaling.

Water supply networks are directly related to the economic and social development of urban communities. Due to the rapid increase in population and urbanization, these networks should be properly maintained and rehabilitated. In this paper, an unsupervised learning method with OPTICS density-based clustering algorithm is used to determine the priority areas for rehabilitation. 361 burst event data in one of the Mashhad water network zones were analyzed. The algorithm identified a total number of 16 clusters at 5 different levels of importance. These 16 clusters, which are considered sub-clusters for higher levels, were compared in terms of burst rate. Three clusters with failure rates of 79.1, 62.2, and 50.1 (failures/100 km/year) were introduced as the main priorities for rehabilitation and renovation, respectively. The average burst rate in the whole network was 14.8. The identified clusters were examined in terms of pipe material and diameter and their most affecting factors on the burst rate. The obtained results showed that the OPTICS clustering algorithm has a significant ability to determine priority zones for the rehabilitation plan, by identifying multiple clusters and their according levels. Therefore, the proposed method can be used as a practical and flexible tool to prioritize the rehabilitation process of water networks and identify the main causes of failure events, avoiding complex computational methods or the personal judgment of experts.

A properly monitoring well network can provide quantity and quality data needed to make informed decision making about the state of the environment. The selection of the optimum number of monitoring wells and their spatial distribution is a major challenge for the hydrogeologist. On the other hand, improper distribution of monitoring wells or an insufficient number of them does not properly represent the state of the environment. In this study, the current monitoring network in the study area was evaluated according to the simulation results of MODFLOW and MT3D models. Then, the monitoring network was designed based on the wells in the area with the optimization method developed in this study. The optimization model consists of two objective functions to maximize the Nash Sutcliffe coefficient and to minimize the costs simultaneously, which was defined as one target function by applying the weighting factor W. Genetic algorithm was used to solve the optimization model. The results showed that the finding of the optimal value depends on the value of the weight coefficient (W). Therefore, the best value of W is selected according to an acceptable trade-off between cost and spatial distribution of wells in the area. To choose the best solution, PBIAS, RMSE, and regression coefficients were used in which their values were acceptable in this study. Also, the higher the average optimal TDS values than the average observed TDS values indicated that the optimal network could provide groundwater quality data for more polluted areas. The method presented in this study for other pollutants should be evaluated and validated.

Establishing a local water market in the agricultural sector is a promising solution to increase the economic efficiency of water in the event of drought, water shortage, and reduced agricultural productions. With the opportunities created in the water market, farmers will rent and sell this scarce input by improving the methods of water supply management and will work to provide water that can be sold in the market. In addition to managing surface water resources, this reduces farmers' pressure to use groundwater resources. Due to the importance of this issue, in the present study, the economic effects of the formation of the local water market in the five regions of Tehran province under the conditions of drought, water shortage, and reduced crop production in Tehran province were evaluated. This work was done by using a combined economic model of Statewide Agricultural Production (SWAP), hydrological model of Water Evaluation and Planning (WEAP), and related statistical data to the years 2013-2019. The results showed that with the establishment of the local water market and balancing agricultural water trade between the study basins of Tehran province, the negative consequences of drought in the use of available water resources are reduced by about 12/7 percent compared to the base period. In addition, the establishment of the local water market as a customary and legal institution in Tehran province, despite the transfer of surplus water resources from the eastern and northern basins (M1 and M2) to the southwestern basins of Tehran province (M3, M4, and M5), caused increasing the reliability of farmers' access to irrigated water and preventing the reduction of profitable crops (tomatoes, corn, watermelon, and sunflower) in optimal cropping patterns. Also, this structural institution by realizing the policy of sharing agricultural water resources and increasing the “profit to water ratio index” from 5/89 to 11/06 percent, reflects optimally allocates the issue of allocation and optimal management of water resources between different agricultural activities in the five basins of Tehran province. Finally, according to the positive and effective results of the local water market in the management of water resources and agriculture, the implementation of the preparations for its formation is proposed to the relevant authorities and organizations in Tehran province.

Existence of various stakeholders with different values, interests, and goals, scarcity and unbalanced water distribution, as well as increasing demands have made conflict one of the main issues of water systems. Due to the interaction of water systems with other human systems, the correct water conflicts addressing is significant. The first step in dealing with a conflict is to recognize and analyze it. Water transfer is a solution that has been adopted to deal with the problem of scarcity of drinking water in Tehran, which has led to the potential for numerous conflicts in the origin catchments. Due to the direct impact of the water conflicts on Tehran's drinking water supply, this research was conducted to analyze the potential of conflicts in Tehran's drinking water supplier catchments. In this regard, identifying and analyzing the issues, causes, and stakeholders of water conflicts and the type of relationships among stakeholders were the main objectives of this research. Water conflicts in the target basins were analyzed using the conflict mapping tool based on the Conflict and Development Analysis framework developed by the UN. The results showed that in general, the existing conflicts are in the fields of water allocation, development, and environment. The main reason for the conflicts in these basins is the adoption of alternatives such as transferring water to Tehran. As the outputs, the actors in the water conflict were recognized and the relationship among them corresponding to their alliance and/or conflict were mapped.

The importance of adaptation to climate change in the agricultural sector due to its vulnerable nature to climate risks is more than other economic sectors. Adaptation strategies in the agricultural sector should be designed and applied in a way that reduce losses and also sustain the livelihoods of the vast majority of working households. Due to the existence of different criteria, it is necessary to use decision-making techniques in order to prioritize and ultimately select adaptation strategies. Therefore, the purpose of this study is to investigate the criteria and prioritization techniques to identify the most appropriate climate change adaptation strategies in the agricultural sector. This qualitative research was done by content analysis of literature using MAXQDA software to identify criteria, prioritization technique and finally selecting climate change adaptation strategies in the agriculture sector. Based on findings, indicators of climate change adaptation strategies are divided into two main costs and benefits categories. In the cost category, emphasis was on the criteria of the minimum cost of implementation, maintenance, and other costs. Also in the benefits category, the criteria are divided into five sub-categories: institutional-political, environmental, social, economic, and climatic. Based on the results, different methods and techniques have been proposed to prioritize and select appropriate strategies. However, it is not possible to recommend one of them in all situations, but this choice should be made in accordance with the situation, purpose, and level of available information resources. For this purpose, the strengths and weaknesses of the most common methods of prioritization and selection of adaptation mechanisms to climate change are presented. These methods including multi-criteria analysis, hierarchical analysis, economic analysis, and network analysis, have been discussed in this study to better identify and select the most suitable set of strategies.

Hydrological simulation models are valuable tools for examining challenging issues related to watershed management such as the impact of climate change on water resources, the impact of urban planning on floods and droughts. In this study, WetSpa-Python model was developed to simulate daily flow hydrographs at the Arazkouse basin. This is an object-oriented, process-based modular model which has been developed based on the principles of flexible modeling in python. Data inputs included DEM, soil type, land-use, precipitation time series, temperature, and evapotration, which were acquired from nine meteorological stations for a ten-year period (from 2006-07 to 2015-16). Model calibration was performed in a limited manner by assigning rational values to 8 global parameters based on the best fit between the simulated and observed hydrographs. Model performance was tested via the Kling-Gupta index, and obtained 0.6 and 0.52 for the calibration and validation periods, respectively. The results of the water-balance analysis with the model indicated that the outflow of the basin constitutes 13.2 and 18.1% of total precipitation in the calibration and validation periods.

In the original paper, Mohammadi Sedaran et al. (2021) (DOR: 20.1001.1.17352347.1400.17.2.11.4) assessed the water resources carrying capacity using a combined simulation-indicators system approach in the Zarrineh-Roud river basin. In the original paper, river basin modeling focuses on agriculture using the SWAT model, and system identification is made using the pressure-support-state framework. Then a set of indicators is used based on the pressure-support-state framework for system analysis. This research provides a valuable analysis of the system under study. However, according to the title used, the mentioned research has some drawbacks in carrying capacity assessment that will be addressed in this discussion. The present discussion criticizes different sections of the original article, including (1) literature review and research problem, (2) the implemented definition of the carrying capacity, (3) methodology, and (4) the results. In this discussion, first, the theoretical framework of the discussion is presented. Then, the different sections of the article will be examined. The objection to the content will be presented by reviewing each section, then appropriate references and methodological recommendations are provided during the review.

As other researchers have shown, one of the main problems in studies in carrying capacity is not paying attention to the evolution of this concept and its various aspects. Therefore, this paper has been compiled to investigate one of these cases, namely the article “Critique of the article on assessment of water resources carrying capacity of the river basins using the simulation approach and index-based evaluation method; case study: Zarrineh-Roud basin”. This article tries to explain and supplement the arguments and views of the critic(s) constructively and to eliminate the doubts and shortcomings of the statements made and increase the awareness of the audience of the article. This article first tries to provide a correct view of these concepts. It eliminates the essential ambiguities in the opinions expressed in this field by stating the concepts of carrying capacity and carrying capacity of water resources and introducing reputable authorities. Then all their ambiguities were answered with various, understandable and straightforward arguments based on the critic's point of view and extracted from the references they have studied. It should be noted that the innovation and scientific value of the article is in approach, the evaluation framework and methods. The approach and methodology recommended in the articles cited by the critics have been considered as the missing key to the other research. The issues raised by the critic are the principles of the carrying capacity studies, which have been considered in the published article. The concept of carrying capacity is complex with scattered literature, so ambiguities and disagreements about this concept are axiomatic. Therefore, introducing the concept of resources and environment carrying capacity into the scientific literature of the country depends on the special attention of domestic researchers to this concept and the synergy between them. Obviously, scientific and constructive critiques will be constructive in this direction.