مجله مدیریت آب و آبیاری
سال چهاردهم شماره 3 (پاییز 1403)

The important share of agriculture in groundwater resources depletion as well as job creation for some of the most disadvantaged sections of the society has caused hiring any restrictions on this sector with the aim of restoring groundwater resources results in a wide range of socio-economic challenges. In such a situation, a potential solution to overcome the dire situation of groundwater resources without the emergence of socio-economic consequences is to achieve the growth of the agricultural economy along with the decrease of groundwater consumption, which is known as strong decoupling in the research literature. In this study, an attempt was made to evaluate the nature of the relationship between the growth of the agricultural economy and the withdrawal of groundwater resources in 31 provinces of Iran between 2012 and 2019 by applying an approach called the Tapio approach. Then, the effect of being placed in a state of strong decoupling on the depth of groundwater should be estimated by quantile regression model. According to the findings, almost all the main agricultural centers of Iran, such as Fars and Khorasan Razavi, have not only failed to achieve strong decoupling, but in many cases, they have also experienced negative growth in the agricultural economy along with the increase in the withdrawal of groundwater resources, and consequently, they are in unstable conditions in terms of economic and groundwater resources. Further, the results of the quantile model depicted that in the areas with medium and deep groundwater resources, achieving strong decoupling reduces the depth of these resources by about 8%, although the same thing does not affect the depth of these resources in areas with shallow groundwater.

The use of natural processes such as phytoremediation is a suitable solution to reduce water and soil pollution. In this study, two separate experiments were conducted in the form of a 2019-2020 factorial experimental design in a greenhouse to investigate the effects of sewage leachate and industrial effluents on the growth characteristics of vetiver plant species. The experimental factors included leachate and industrial effluents at concentrations of Zero Percent, 25 Percent, 50 Percent, 75 Percent, and 100 Percent in three replicates with two water use stress in five and 10 days. Characteristics evaluated included plant height, number of branches, fresh and dry weight of shoots, and fresh and dry weight of soil organs (roots). The results showed that irrigation with municipal wastewater leachate had a significant effect on the number of branches (P<0.01), fresh weight, and dry weight of roots at a five Percent level. The results of applying industrial wastewater had a significant effect on height, number of branches (P<0.01), dry weight of vetiver, and fresh and dry weight of roots (P<0.05), but no significant effect on fresh weight of vetiver (P>0.05). The highest additive effect of industrial effluent and irrigation stress on plant morphological characteristics was obtained at the interaction level, W2A1 treatment (25% industrial effluent and five days irrigation stress). The results of this study showed that the use of waste leachate and industrial wastewater mixed with irrigation water to irrigate compatible vetiver species can be considered as a solution for the use of unconventional water in production.

The primary objective of this research is to comprehensively investigate fluoride concentration in the Maku-Bazargan-Poldasht area, located in the north of West Azerbaijan province. In October 2021, 60 samples were collected from various water resources in the region. The fluoride concentration ranged from 0.39 to 9.89 mg/L, with more than 50% of the samples exceeding the World Health Organization's standard. This study investigated into the correlation between fluoride and other elements, assessed various processes influencing fluoride levels, investigated its effects on humans and plants, and utilized multivariate statistical techniques to determine contributing processes and factors. Moreover, it examined fluoride concentration fluctuations over the past 15 years across different water resources (Deep wells, Shalow well, Springs, Qanats, and Surface water) for the first time. The assessment of fluoride included multiple dimensions related to this element. Comparing fluoride levels across various water sources revealed that Deep wells exhibited the highest fluoride concentrations due to the long residence time of water within the aquifer matrix. This study also highlighted, for the first time, the correlation between high fluoride concentrations and plant diseases such as necrosis and chlorosis in specific parts of the study area. Bivariate plots indicated that processes involving carbonate dissolution and ion exchange contributed to increased fluoride and carbonate concentrations in the area. Furthermore, an analysis of changes in fluoride concentration in 12 sampling stations indicated an eightfold average increase in anomaly intensity over the past 15 years in these stations. Employing Principal Component Analysis (PCA) and Factor Analysis (FA), the research identified three groups and three factors, confirming that fluoride anomalies are natural, while nitrate anomalies originate from human activities within the study area.

In this study, the amount of flood risk reduction due to applying one of natural flood management measures, in alluvial fans, was investigated. Usually, flood management is done by common structural and non-structural methods, which are expensive and short-lived. Flood damage reduction and using more stable and flexible solutions for flood management, have been received more attention from researchers in recent years. Using natural flood management (NFM) is considered stable methods of flood management, and in this study by presenting a natural solution in the form of increasing the length of the river by creating a meander, to investigate its effect on the expected flood damage compared to the base mode is paid. The method of conducting this study is based on modeling, which uses three models: HEC-HMS, HEC-RAS 2D and ArcMap. The study area is Abbakhsha River catchment located in Bardsir city, Kerman province, with an area of 1136 square kilometers, has the state of an alluvial fan that numerous floods have occurred. Topography, precipitation and discharge are the most important data required for this study. According to the results of this research, creating a meander in the river reduces the expected annual damage (EAD) by 15.5%. The results of this research can be effective in the planning and policy making of optimal flood management solutions in the region.

Appropriate precipitation can play a crucial role in providing soil water content in rainfed fig orchards. Meanwhile, one of the main problems in most rainfed agriculture areas is the unavailability of rainfall data, which satellite rainfall datasets can help to solve this problem. The area investigated in this research is rainfed fig orchards of Estahban and the rainfall data of the meteorological station located in the area was applied for different periods of time. In this research, first, the relationship between yield and distribution of precipitation values in different time scales (monthly, seasonal and annual) was determined. Then the amount of satellite-derived rainfall was found using the rainfall datasets (i.e. CHIRPS, ERA5, ERA5-Land, GPM, PERSIANN and GSMaP) and based on these values, the amount of effective rainfall was calculated using different methods including USDA, ET-Rainfall, and Dependable Rain for the time period range between 2005 and 2021. Results showed, the rainfall in the months of April and then in May and November has had the greatest effect on improving the yield of the crop. Additionally, it is recommended supplemental irrigation events at the beginning of spring to provide higher soil water content for fig orchards in drought conditions. Based on the analyzed statistical criteria, it can be said that GPM was the most suitable dataset and USDA was the best effective rainfall method among the investigated methods in the area.

Spatial quantification of actual evapotranspiration (ET) is crucial for water resource management and planning in arid regions. This research focuses on the investigation and estimation of evapotranspiration using Py_SEBAL and METRIC algorithms, as well as the WaPOR model and MOD16 product, during the years 2021 and 2022 in the Moghan Plain located in Ardabil Province. The results of each model are compared with the FAO-56 method, which is a standard approach for estimating evapotranspiration in different areas. The results indicate that the Py_SEBAL algorithm shows the highest correlation with the FAO-56 method, with an R value of 0.97 and an RMSE (mm/month) of 1.88. Next, the METRIC algorithm demonstrates the highest correlation with an R value of 0.89 and an RMSE (mm/month) of 1.5. To further validate the performance of the estimation models in different areas, the WaPOR database is also utilized. The obtained outputs indicate that among the irrigated lands covered by the water network, the Py_SEBAL algorithm exhibits the highest correlation with the values derived from WaPOR, with an R2 value of 0.77. After Py_SEBAL, METRIC demonstrates a relatively suitable correlation with an R2 value of 0.55. Considering the land use map of the region, more than 60% of the area is covered by the irrigation network. Since Py_SEBAL yields the best results in the conducted investigations for these lands, the estimation of evapotranspiration volume is focused on the entire region. The results indicate that the volume of evapotranspiration is approximately 4/5 times higher per hectare in irrigated lands compared to drylands.

The occurrence of droughts that are affected by the change of climatic factors and the development of human activities have faced more serious problems in the management of limited water resources. In this research, SPI and SSI indices were used in different time scales in order to investigate meteorological and hydrological drought characteristics and extract the propagation relationship between them in the basin overlooking Samian station in Ardabil plain. To conduct the research, first, the average monthly rainfall of the study area was extracted using the IDW method. Then, by identifying the change point, the flow time series was divided into two periods before (natural) and after (disturbed) construction of Yamchi reservoir dam, and SPI and SSI indices were calculated for each period. In the natural period, hydrological drought prevailed about 30% of the time, but the share of hydrological and meteorological droughts was the same in this period. However, in the distributed period, the frequency of meteorological drought was less than 30%, but the frequency of hydrological drought was about 80%. This issue shows the effect of the construction and operation of Yamchi Dam so that in the years after the construction of the dam, the hydrological regime of the river was affected and experienced more drought. According to the correlation between SPI and SSI indices in two natural and disturbed periods, the propagation of meteorological drought to hydrological has been a third-order relationship.

Groundwater resources are an important factor in managing and maintaining water that is used for drinking water, irrigation and other purposes. Groundwater level forecasting is very important for assessing total water resources and their allocation, contributing to water sustainability and drought mitigation. Sometimes, due to the presence of obstacles such as unfavorable weather conditions, blocked roads, or lack of equipment and people, measurements are not carried out for months. On the other hand, accurate and abundant groundwater level data helps to predict various consequences related to groundwater management and ecosystem health. Nevertheless, completing the missing data and improving them by interpolation method helps effectively in predicting the stability level by deep learning method. . In this study, the Azarshahr aquifer, which has recently faced a significant drop in the underground water level, was examined monthly from 1397 to 1400. Also, in order to complete the data that was not measured for any reason, kriging interpolation methods and M5P algorithm were used. By analyzing each method, the M5P method with the minimum root mean square error of 1.83 meters and correlation coefficient of 0.975 was the best. It had the function. On the other hand, in order to predict the underground water level, the data was divided into 70 and 30 calibration and accuracy measurements, and the deep learning (DL) method was used, which was acceptable with an error of 1.408 meters and an accuracy of 88%. And it can be used in future research for better management of water resources.

One of the most important sources of water loss in reservoirs is controlling reservoir efficiency indicators, water deficit, and losses through evaporation and seepage. In this study, in the first step towards formulating operational policies, the SOP model of Pishin dam located in Sistan and Baluchestan Province during the years 1390 to 1397 was developed. Subsequently, to identify optimal release values in operational policies, the Generalized Reduced Gradient (GRG) extended to standard operational policy (SOP) and averaging method. Thus, hybrid optimization-simulation models of Generalized Reduced Gradient-Standard Operational Policy (GRG-SOP) and Generalized Reduced Gradient-Standard Operational Policy-Averaging (GRG-SOP-AVE) were developed. In this study, indicators of water losses (evaporation and seepage), deficit, and reservoir efficiency indices for the GRG-SOP, GRG-SOP-AVE policies, and current operation were estimated to identify the best operating policy. The results reveal that the operating policy derived from the GRG-SOP-AVE model leads to a reduction in the values of deficit, evaporation and seepage indicators by 35.32 MCM/yr, 10.74 MCM/yr, 0.002 MCM/yr, respectively. Additionally, the indicators of reliability, resilience, vulnerability, and flexibility have improved by 67.58%, 24.59%, 31.69%, and 11.35% respectively compared to other policies. Therefore, it is suggested to utilize the policy derived from the GRG-SOP-AVE model in other dams to reduce seepage, evaporation, and deficit indicators.

The examination of water quality in terms of pollution is a crucial aspect in managing the quality of surface water, such as rivers. This study focused on analyzing the trend of nitrate (NO3) pollution in the 7.02 km long of the Abbas-Abad River in 2022. The HEC-RAS model was used to determine the river pooling, and then, the geometry was entered into the QUAL2Kw model. Calibration and validation were conducted using the data from May and July 2022, respectively, demonstrating the model's accuracy. The findings revealed an increasing trend in nitrate concentration of 7.6% during the non-agricultural season and an 8.0% increase during the agricultural season due to the use of fertilizers and chemical pesticides. To mitigate this, it is recommended to prevent pollutant entry into the riverbed.

Aquaculture activity and discharge of pollutants in the upstream of the rivers bring various environmental impacts such as ecosystem toxicity and eutrophication. Thus, it requires an integrated method for evaluating the cumulative environmental impacts. This research presented a developed method for analyzing the environmental impacts based on the analysis of the inlet and outlet water quality of fish farms and used the coefficients of the ReCiPe as a life cycle impact assessment (LCIA). In this framework, water consumption was also included based on grey water footprint, along with eutrophication and toxicity for 5 trout farming in various regions of Iran. The results showed that total suspended solids was the leading water quality parameter, water consumption had the highest impact in LCIA, human health was relatively more vulnerable than the ecosystem, and total damages increased 95 percent on average from inlet to outlet. Nevertheless, factors like the inflow, ReCiPe background, and the weighting coefficients were effective on results uncertainties. The sensitivity analysis showed that changing ReCiPe background from hierarchic to egalitarian had the greatest impact on the results of LCIA with 35 percent damage reduction, while the increase in the pollution load caused by the increase in flow or concentration of the dominant pollutant in the grey water footprint can linearly increase the equivalent damages. Therefore, it was suggested to use wastewater pretreatment systems to control the spread of pollution beside managing and optimally using feed in farms.

Maintaining water security along with food security, as two civilization-building areas, requires water governance and agriculture governance assessment. The research was a mixed type and was done under action research approach, apply literature review, semi-structured interviews, workshops with agriculture and water experts. While introducing the governance features, the relevant indicators in the form of researcher-made questionnaire has been measured in two chains of water supply and agricultural water consumption. The validity of the questionnaire was confirmed by experts and its reliability with Cronbach's alpha of 0.933. The results of the evaluation of nine governance indexes in the water supply chain was (Min=1.72, Max=2.11) and the evaluation of 9 governance indexes results in the agricultural production chain was (Min=2.09, Max=2.49). The results indicate, the average score of the water supply organization in the direction of balancing water resources in recent decades is 1.9 (out of 5) and the average score of the agricultural production organization in the direction of improving agricultural water productivity is 2.3 (out of 5). So it is suggested to improve the capacity of the National Supreme Water Council in such a way that the effective participation of other government and NGOs be reviewed for designing a road map for improving agricultural water productivity and balancing underground water resources.

The phenomenon of climate change has caused a change in the intensity and frequency of extreme phenomena, especially extreme rainfall. Spatiotemporal analysis of extreme precipitation is very important in order to increase the flexibility of socio-ecological systems and their infrastructures under climate change. This study examines the spatiotemporal changes of precipitation characteristics with temperature changes. For this purpose, Spearman's non-parametric test has been used to evaluate trends in three precipitation indices (maximum 3 and 6-hour precipitation and total annual precipitation) and two temperature indices (maximum and minimum annual temperature) in 26 synoptic stations located in Iran. In this research, statistics and information from 34 to 70 years old (from 1951 to 2020) were used. The trend of the data was checked at a significance level of 95%. The results showed that the maximum rainfall of 3 and 24 hours in Gorgan station has a positive trend, but the index of total annual rainfall in this region has a negative trend, also the maximum rainfall of 3 and 24 hours in Ahvaz, Isfahan and Semnan stations also has a significant increasing trend, and these areas are prone to flash floods. Also, the results showed that the increase in maximum 3-hour and 24-hour precipitation at higher temperatures in a limited number of stations leads to an increase in annual precipitation, and most stations show a decrease in precipitation with increasing temperature. Also, the maximum temperature in all stations (except Shahrekord and Birjand) has increasing changes, which indicates the warming of the air in summer.

Although technology development in villages can have undeniable benefits; In some cases, we see the reduction of the effectiveness and efficiency of technology, the waste of villagers' material resources and the villagers' pessimism towards technology used in irrigation systems. The incompatibility of technology with the time and place conditions of the villages has a prominent role in the occurrence of these damages. This research aims to explain the concept and identify indicators of appropriate technology to rural environments, with special emphasis on irrigation systems in rural areas of Taft city, using the qualitative approach of Grounded Theory technique. According to the results, the appropriateness of a technology with the village environment and its effectiveness for the agricultural sector requires the inclusion of all socio-cultural, technical-economic, physical-infrastructural and environmental aspects. The results show that technology in terms of socio-cultural aspect, should be needs-oriented while being compatible with the epistemic environment of the village and based on local knowledge. It is also in terms of technical-economic aspect necessary to be scalable, cheap, simple, controllable, durable and standard. In addition, the technology should be compatible with each plant in terms of physical infrastructure and the necessary infrastructure should be provided in the village. The results also show that the technology must be environmentally friendly, consistent with the principles of sustainability and bring the least shock and stress to the agricultural unit. In the paradigm model presented in this research, "Not considering the special conditions of villages", "Not considering the real needs of villagers" and "weakness of facilities and infrastructures" are mentioned as the causal conditions for the introduction of inappropriate technology in the villages. Also, cases such as "small ownership", "monopoly and incorrect relationships", "short life of planning in the rural system", and "weakness of the extension system in introducing appropriate technology" have played an interfering role in intensifying the current situation. This model points to the fact that if strategies such as "shaping the rural technological innovation system" are used, the cycle of generation, diffusion and utilization of appropriate technology in villages can be accelerated.

Biochar as a soil amendment improves soil physical and chemical properties. Drought stress is one of the most important factors that limit plants growth. In order to study the effect of biochar on growth and morphological characteristics of coriander in a fine-grained soil under water stress, one factorial experiment in Randomized Complete was carried out in the research greenhouse of Urmia University, Iran. Experimental treatments included three levels of deficit-irrigation 100, 75 and 50 percent of water requirement of coriander (a1, a2 and a3) and three levels of application of biochar 0, 2.5 and 5 percent by weight percentage of each pot (b1, b2 and b3). The results of analysis of variance and comparison of the mean of measured traits (fresh and dry weight of plant, leaves, stems and roots) showed that these traits were significantly different under the influence of different levels of irrigation and biochar application. So that the highest value of each of these traits was observed in the treatment of complete irrigation and application of 2.5 percent by weight of biochar (a1b2) and the lowest value was observed in the irrigation treatment of 50 percent of water requirement and without biochar (a3b1). The highest water productivity based on fresh (3.26 kg/m3) and dry (0.49 kg/m3) of the coriander was obtained from a2b2 treatment. So, it can be concluded that the application of the appropriate amount of biochar reduces the negative effects of moisture stress and improves plant growth and development indicators compared to the control treatment. Therefore, it is recommended to use it for the plant in conditions where the plant is under drought stress or in greenhouses in order to reduce the amount of water consumed and improve the growth and performance of the plant.