مجله تحقیقات منابع آب ایران
سال هجدهم شماره 1 (پیاپی 60، بهار 1401)

Sewage produced in homes can be divided into two groups. The sewage produced from domestic uses such as bathing and laundry and dishwashing water is called gray water and the sewage produced from toilets is called black water. In many systems used in the world, gray water is combined with black water and discharged by the municipal sewage system. However, gray water has a higher quality due to its lower pollution content and has a higher potential for reuse. In this study, using the combined model of SWOT analysis and QSPM matrix, the do's and don'ts of using the effluent from the Sabzevar city treatment plant were investigated. Based on the results of experiments on the effluent, the use of this effluent for agriculture demands further disinfections due to the Coliform density outside the permitted range which is recommended in national and international standards. However, in general and in most of the years, the quality of the effluent of Sabzevar municipal wastewater Treatment Plant is within the permissible limits and it can be used for irrigation of industrial and fodder plants which is not used directly by humans or for urban landscape according to the results obtained from the study of chemical and microbial quality of effluent (TDS, Nitrate, Nitrite, EC, parasite eggs). Considering that public opinion on the use of wastewater is somewhat negative, we should seek to create a positive culture by holding events at the level of councils, villages and rural people. In addition, due to the desert nature of the area, the effluent can be used for biological regeneration and planting plants such as Nitraria and Haloxylon, and species such as Atriplex. Also, due to the existence of factories such as washing plants and cement factories in the region and the reasonable price of effluents and water saving, the conditions of using effluents in such factories can be studied and researched.

Estimation of basin outflow under the influence of various parameters is a complex process and in case of basin information lack, the analytical models are not applicable. On the other hand, Artificial Intelligence models do not require basin information, and some, such as the convolutional neural network (CNN), have recently been widely used in hydrology. The purpose of this study was to investigate the performance of CNN in estimating the outflow in terms of temperature, precipitation and inflow to the basin. In this study, CNN, combination of CNN with wavelet analysis (WCNN), and perceptron neural network (MLP) were used to evaluate the effect of temperature on the outflow within the Ghaleh Shahrokh Chelgard basin from 1992 to 2015. Each model was run 20 times and the mean values ​​of correlation coefficient(R), root mean square error (RMSE) and Nash Sutcliffe coefficient (NS) were calculated. Lags of one, two and three-month of temperature and rainfall data are also included as input data. Wavelet analysis was used for noise reduction and the results showed that CNN with a lag of three months had ,  and  equal to 14.20 (m3/s), 0.922 and 0.772, respectively. In contrast, the WCNNT3 method with Daubechies wavelet, which is a combination of CNN and wavelet analysis, ​​with level four performance and resolution two (WCNNT3-db42) had indices respectively equal to 9.45 (m3/s), 0.945 and 0.863. Accordingly, CNN performed better than MLP, and the WCNN method with wavelet analysis showed better performance than CNN.

In management and planning of water resources, hydrological models are suitable tool that can be very effective in simulating hydrological processes such as water balance. Distributed hydrological models simulate each of the water balance parameters by discretization and solving equations in each cell. In the present study, the WetSpass-M distributed model is used to estimate and evaluate the components of the water balance in Hashtgerd study area in Alborz province. The model was implemented in monthly basis and for a 20 year period. In order to calibrate and validate the model, first the monthly flow data of the hydrometric station were used as observational data. The remote sensing approach (SEBAL algorithm) was applied to re-estimate evapotranspiration. Then, the results of the two approaches were evaluated and compared. According to the model results in the Hashtgerd study area, the mean annual values of evapotranspiration and groundwater recharge were estimated to be 347.3 and 272.6 MCM, respectively. Furthermore, the mean annual values of evapotranspiration for plains and mountains were respectively 241 and 106.3 MCM. The mean annual recharge rate in the plains was equal to 197 MCM, while it was estimated to be 75.6 MCM for mountains. The variations analysis of model outputs was performed based on the standard deviation for the water balance parameters in plains and mountains. The results showed that the most variations during the simulation period were observed respectively in the irrigation component, evapotranspiration, recharge, and rainfall.

Macro-level documents, laws, programs, and documents are of utmost importance in any country since they are the basis of planning in the executive areas at different levels of management. Amongst these executive areas, water resources management is one of the most important. The aim of this study is to analyze the discourse of macro-level documents on water management after the 1978 revolution. The statistical population of the research includes the Sixth Development Plan before the revolution (1978-1988), the Law of Equitable Distribution of Water (since 1982), and the Law of Preservation and Stabilization of the Border Rivers Banks and Beds (1983). The method of the present study is the analysis of discourse by Laclau and Mouffe method and we tried to answer these two questions; What has been the dominant discourse of the macro-level documents in the field of water resources management and What are the consequences of this discource for water resources? The analysis of these documents showed that in the period under consideration the main governing discourse is the exploitative discourse which is the main signifier and center of gravity of these documents. This indicates the full use of the country's water resources using technology and mechanization in methods of production. This discourse manifests itself in the othering the discourse of protection in these documents. The discourse of modernization versus development, and governmental versus participatory management confirms this conclusion which is approved through equivalence signs such as the use of surface and groundwater resources, attention to agriculture, employment and income generation, diging deep and semi-deep wells to supply drinking water, industry and Agriculture, increase the capacity of the country's hydropower plants, and the policy of self-sufficiency in agricultural products.

The use of temperature and precipitation data from the NASA Earth Exchange Global Daily Downscaled Projections dataset (NEX-GDDP) is increasingly expanding as one of the products derived from the global climate models. Investigating the quality of this product’s precipitation data in Iran can help the researchers to consciously use them in hydrological and water resources practices. In this study, first, the degree of improvement of the monthly precipitation data of ACCESS1-0 model from the NEX-GDDP product was investigated against the corresponding GCM model as well as the observational data measured at stations located in eight homogeneous precipitation regions of Iran. Then the NEX-GDDP data was bias-corrected using the Quantile Mapping (QM) method through using the SSPLINE, QUANT, PTF, RQUANT and DIST functions. Comparison of monthly precipitation data of the selected models of the NEX-GDDP product with its raw GCM data showed that R, PBIAS, NSE, and KGE statistics have significantly improved respectively in 75%, 100%, 100%, and 88% of the studied stations. The correlation between the bias-corrected data and the observational data was also improved in 50% of the stations, the NSE and KGE were improved respectively in 75% and 62.5% of the stations, and PBIAS was improved in all stations. This study also showed that among the used bias correction functions, the RQUANT had the best performance.

Over recent decades Iran and especially its western regions have suffered from devastating floods. Planning and designing hydraulic structures require information from flood magnitude corresponding to a given occurrence probability. Hence, in this study, we aimed to determine flood homogeneous regions and regional growth curves using L-moments and flood index method for annual maximum flow of 62 sub-basins in Great-Karoon and Karkhe basins. Moreover, the impacts of droughts and hydraulic structures on the stationary and stochastic nature of floods were investigated using Mann-Kendall trend test, Pettitt’s change point detection test (CPD) and graphical interpretations. It was found that there are five hydrological homogeneous regions in the study area. The goodness of fit tests results showed that the Generalized Pareto (GPA) distribution for the first and second regions, the Generalized Normal (GNO) distribution for the third region and the Generalized Logistic (GPA) distribution for the fourth and fifth regions are the most appropriate regional statistical distributions. Also, maximum daily flows corresponding to 2, 5, 10, 25, 50, 100, 500 and 1000-year return periods were estimated for all study sub-basins.  Regional flood frequency analysis revealed that for 100-year return period the fifth region’s sub-basins, with 4060 m3/s discharge on average, have the highest maximum daily flow. The average 100-year maximum daily flows in the regions I, II, III and IV were estimated around 632, 682, 460 and 429 (m3/s), respectively.

The regional climate models play an important role in simulating the atmospheric and land surface processes and are considered as an important tool in climatic studies. Aimed at comparing the performance of the different convection parameterization schemes (Emanuel, Tiedtke, Kain-Fritsch, Grell-AS and Grell-FC) in simulating precipitation, temperature and actual evapotranspiration over the Lake Urmia Basin, this study employed the RegCM4.5 model for downscaling the outputs of NNRP1 model for a 5-year period. Moreover, the effect of application of two different spatial resolutions was investigated. The results showed that for the 48 km resolution, the Kain-Fritsch scheme, with a slight difference from the Grell-AS and the Grell-FC, had the highest performance in simulating precipitation and actual evapotranspiration and the Grell-AS scheme had the highest performance in simulating temperature. In the case of 12 km resolution, the difference among stations in terms of the most appropriate convection scheme for simulating precipitation was high; but in the case of temperature, the Kain-Fritsch showed the superiority. Also, the comparison of the results for two spatial resolutions showed that, in most cases, application of the 12 km resolution resulted in no improvement in the simulation performance. Thus, the application of the Kain-Fritsch scheme and the 48 km resolution are recommended for the Lake Urmia Basin.

This study aims to investigate the changes in the spatial patterns of residential water consumption before and after the outbreak of the Coronavirus (from April 2016 to February 2016) in city of Shabestar in East Azerbaijan province using water consumption data obtained from 594 subscribers. To this end, the average water consumption level for every two months of the year before the outbreak of coronavirus (until February 2017) has been compared to the water consumption level of the same period after the outbreak. To study the spatial patterns of the difference, the study area was divided into several regions using a 400-meter grid, and the statistical significance of the difference in water consumption of each grid cell has been evaluated using the T-test. Then, using the Moran index, the distribution of areas with a significant difference in their water consumption has been investigated. The obtained results of this study showed that the number and location of the regions with increased water consumption levels were different during this period. The results also showed no spatial correlation between grids with significant consumption change and the random distribution of these areas.

Due to the scarcity of fresh water resources in Iran like many other parts of the world, the demand for providing drinking water resources using desalination processes is increasing. The desalination processes though require a significant amount of energy and financial resources. Therefore, the economic study of water desalination processes is very important in order to choose the optimal desalination method. Identifying and evaluating the risks associated with each process is a great help for the economic evaluation of such projects.In this research, with the help of Delphi method, significant risks in the construction and operation of humidifiers-dehumidifiers have been identified among 35 risks. Then, using the DEMATEL method, which is one of the decision-making methods based on pairwise comparisons, risks were prioritized based on the degree of impact and effectiveness. A total of 13 risks have been identified in the five fields of technical, economic and support, executive, political, and environmental. It can be argued that the factors of choosing inappropriate manufacturing technology, price changes and inflation, energy supply, improper design of wastewater and waste disposal systems and large-scale technology maturity are the main risk factors in this type of desalination plants. The results showed that locating this group of desalination plants requires careful study of the temperature difference and the intensity of cold and hot conditions. It can also be concluded that to apply this desalinization process in a large and industrial scale requires further studies.

Each year, Golestan Province faces damaging floods. Particularly, the province was severely impacted by the 2019 flood events. Therefore, within the context of flood governance, this paper seeks answer to the question of what measures and programs can be adopted to reduce casualties and financial losses caused by floods in Golestan province. The method used is based on the qualitative content analysis considering four components including resilience, efficiency, effectiveness, and legitimacy and the criteria related to each of the components. Through assessing the four components, the overall status of the flood risk governance in the 2019 flood events is categorized as medium (2.4 from 5). The three components of resilience, effectiveness, and legitimacy were assessed as medium, while the component of efficiency was categorized as relatively inappropriate. The criteria of accountability and procedural justice, access to information and transparency, as well as the rate of casualties showed relatively good performance (4 of 5). While the criteria of technology, financial efficiency, and damages had relatively poor status (1 of 5). Based on the findings of this research, to improve the flood risk governance in Golestan Province the components of efficiency, effectiveness, resilience, and legitimacy need more attention, respectively.

The aim of this article was to explain and describe the meteorological and geohydrological droughts, to quantify the lack of rainfall at different time scales and the effect of which on groundwater resources, and to detect the relationship between the occurrence and time delay of meteorological and geohydrological droughts in Kuhdasht aquifer. Groundwater Resource Index and Standardized Precipitation Index indices were used in this research. The SPI index at monthly, quarterly, and annual time scales and the GRI index during the statistical period of 1985-2021 were used to investigate the drought condition and its impact on groundwater resources. In addition to the seasonal and annual scales, the mentioned indices were also calculated on 3, 6, 9, 12, 18, 24, and 48-month basis. The most extended drought period and frequency were obtained using the total Drought Magnitudes criterion. Moisture status for each period was determined with the values obtained from SPI and GRI indices, and thus the trend of drought was investigated. The correlation between different time scales of the SPI index, with average groundwater level and the GRI, was evaluated. The results showed that with increasing time scale, the correlation coefficient of SPI rises with the average groundwater level and GRI and meteorological droughts rate with time delay of 48-months affects the groundwater resources (1% level of significance). The coefficient of (R2) showed that less than 33.1% of the variance of the groundwater level was affected by SPI_48, more than 66.9% of which was due to drinking water and industrial water use.

In recent years, methods for evaluating the resilience of water resources management projects, especially during extreme conditions, have attracted much attention from researchers. Resilience is the ability of a system to withstand crises or successive difficulties so that it can recover or reach an acceptable level of performance. In previous works, the assessment of resilience of water supply and demand scenarios throughout a river basin has not been adequately researched. In addition, to decide on determining appropriate management scenarios, it is necessary to consider the powers, organizational positions and limitations of different stakeholders. In this paper, first, the resilience of a water supply-demand system under events with known and unknown probabilities is evaluated. In the next step, scenarios of water supply and demand resilience in Zarrinehrud river basin, which is the most important sub-basin of the Lake Urmia basin, are analyzed using a multi-agent-multi-criteria decision-making method. Then, the results are compared with those of a decision-making method without considering the role of stakeholders. Finally, to consider stakeholders utilities and powers, a combination of a leader-follower game and evidential reasoning (ER) approach is used to determine appropriate scenarios. The results showed that in the decision-making method with one level (without leader-follower game), the implementation cost of the selected scenario is 21% higher than that of the scenario selected using the multi-agent-multi-criteria decision-making method. Also, the difference between supply-demand resilience of the selected scenarios using the two methods is low and the resilience of the selected scenarios in both methods are appropriate. Finally, the payoff of the selected scenario in the multi-agent-multi-criteria decision-making method is estimated to be 0.72. Therefore, in using the leader-follower game, a more logical scenario is selected, so that the selected scenario has a reasonable resilience and cost.

Iran is a very rugged country with a fairly high variation of climate. These different climates can affect the heteroscedasticity of precipitation data. Because, precipitation is a missing variable in heteroscedastic. To investigate the spatial and seasonal variation of heteroscedasticity in this study, building on the catchment scale and investigating the precipitation data from 146 synoptic stations -the effect of heteroscedasticity on mean precipitation was investigated by the Levene test. The results show that precipitation data on the catchment scale are also heteroscedastic. Also, the current network of synoptic stations cannot help decrease heteroscedasticity in precipitation data on the catchment scale. The most heteroscedasticity and homoscedasticity are located in the Mazandaran Sea and the Central Plateau catchments. Hence, heteroscedasticity of precipitation data challenges the efficiency of mean precipitation on the catchment scale, like the climatic zoning scale. Therefore, to achieve an efficient mean of annual precipitation in the country, it is necessary to do practice to enhance the calculated mean precipitation, by avoiding calculating the mean precipitation in the 2nd grade catchment and climatic regions.   Also, heteroscedasticity is reduced by determining the cause of heteroscedasticity of precipitation data errors and the selection of the best model that can consider the heteroscedasticity on the small catchment scale (3, 4, 5, 6 and 7 grades).

Awareness of the spatial and temporal distribution of precipitation around the world is useful for improving climate awareness and modifying climate forecasting models. However, determining the precipitation distribution is a complex task due to the lack of a single estimator with sufficient coverage and accuracy. In this study, the performance of TRMM-3B43-V7 and PERSIANN-CDR satellite precipitation products on a monthly scale and in different climatic regions in Iran were evaluated. For this purpose, measured rainfall data were used in 81 synoptic stations located in the whole country of Iran in the period from 2008 to 2019. To more accurately evaluate the efficiency of the two products, the values ​​of the statistical indices of correlation coefficient, root mean square error, efficiency factor and false alarm ratio in the position of all synoptic stations were calculated and analyzed. The results showed that in general, TRMM has a significant advantage over PERSIANN-CDR in all statistical indicators. However, the performance of both products in rainy areas was associated with more errors. With the exception of moderate and humid regions, both products estimated more rainfall in the rest of the climatic Regions. This difference in rainfall estimates is greater in arid and semi-arid areas than in other areas.