مجله تحقیقات آب و خاک ایران
سال پنجاه و سوم شماره 7 (پیاپی 79، مهر 1401)

The objective of this study was to eliminate chromium(VI) from a contaminated soil through reducing it to chromium(III) by immobilized Shewanella sp. bacteria on algae biochar and to investigate its accumulation in barley. A sandy loam soil was contaminated with 50 mg kg-1 Cr(VI) and incubated for two weeks. Then, the barley pot experiment in the contaminated soil was performed in the autumn of 1400 in the research greenhouse of University of Guilan in a completely randomized design with three replications. Treatments included Shewanella sp. (S), algae biochar (B), algae biochar + Shewanella sp. (BS), and immobilized Shewanella sp. bacteria on algae biochar (IB). Soil contaminated with Cr(VI) and non-contaminated soils were also included as positive (C+) and negative (C-) controls, respectively. After 30 days, the plant was harvested and dry weight of root and shoot were measured. Total chromium and Cr(VI) contents in the root and shoot of plant and also in the soil were measured. The Cr(III) content was calculated from the difference between the total chromium and the Cr(VI) contents. Growth ratio, Cr(VI) accumulation factor in roots and shoots and the transfer factor in plants were calculated. The highest and lowest amounts of Cr(III) in roots, shoots and soil were obtained in IB and C+ treatments, respectively. In Cr(VI) contaminated treatments, the highest and the lowest values of root and shoot dry weight were obtained in IB and C+ treatments, respectively. Cr(VI) reduction in soil in BS treatment was more than S and B treatments. The lowest and the highest plant growth ratios were obtained in C+ (23.8%) and IB (60%) treatments, respectively. The BS and IB treatments further reduced the transfer factor. Therefore, immobilized bacteria on biochar can be effective in remediation of chromium contaminated soils.

Potassium, as an essential element, which its role in plant metabolism and resistance to biological and environmental stresses has been proven many times, requires accurate extraction and measurement for optimal management. The present study was conducted to investigate the effect of soil/extractant ratio on measuring the amount of available potassium in the soil. For this purpose, in October 2021, 62 soil samples were taken from agricultural fields all over the country, and their potassium content was measured by three extractants: 1 M ammonium acetate (three ratios of 5:1, 10:1, and 20:1), ammonium bicarbonate-DTPA (2:1, 5:1, and 10:1), and Mahlic-3 (5:1, 10:1, and 20:1) in the Karaj soil and water research institute (SWRI). The results showed that the amount of available potassium measured by ammonium acetate and Mehlich-3 extractants had no significant difference, but these two extractants had a significant difference with ammonium bicarbonate-DTPA. Probably, this difference is due to replacing the 2:1 ratio with a 20:1 ratio in the extraction method by ammonium bicarbonate-DTPA. In all three extractants, the estimated soil available potassium increased by increasing the soil to extractant ratio. On average, the amount of extracted potassium in 20:1 ratio was 11.5% and 5.01% more than the ratio of 5:1 and 10:1 for ammonium acetate, and 8.79% and 6.84% more than the ratios of 10:1 and 5:1 for Mehlich-3, respectively. By using a 10:1 ratio, all three extractants measured the amount of soil-available potassium without any significant differences. Therefore, it is suggested that all three extractants be used to determine the amount of available potassium. In addition, it seems a 10:1 ratio is a suitable ratio for measuring the amount of available potassium with minimal difference between different extractants.

The Urmia Lake basin is one of the most vulnerable areas to frequent high-intensity droughts in Iran. The aim of this study is to project meteorological drought in the Urmia Lake basin through the 21st century. For this purpose, the standardized precipitation-evapotranspiration index (SPEI-1) was investigated using the bias-corrected CMIP6 models under SSP1-2.6 and SSP5-8.5 scenarios during the period 2026-2100. The performance of individual CMIP6 models and multi-model ensemble (MME) generated by the independent weighted mean (IWM) method with three metrics including NRMSE, MBE, and PCC were evaluated. Overall, all individual CMIP6 models showed a good performance in the Lake Urmia basin, despite some overestimations of precipitation. However, the generated CMIP6-MME has increased the PCC values in all stations to 0.99. The CMIP6 MME showed a good performance of the SPEI-1 index in autumn, winter, and spring against observation from ground stations in the historical period. The result indicates a significant increase in drought events mainly in the west and north of the Urmia Lake basin in the warm period of the year during the 21st century. The severity and the percentage of below-normal years for the basin-averaged drought in the middle 21st century (2051-2075) is more than the ones in the far future (2076-2100), especially for the SSP5-8.5 scenario. These results can provide a basis for the development of drought adaptation plans in the Urmia Lake basin.

High concentrations of ammonium and phosphate in leachate allow producing the struvite mineral (MgNH4PO4·6H2O), which is a valuable slow-release fertilizer in agriculture. In this study, the possibility of struvite precipitation from the Saravan landfill leachate was considered. The research was conducted in the Soil Sciences Department of the University of Guilan in 1400. Leachate was sampled and the concentration of ammonium, phosphate and magnesium ions in the leachate was measured. Struvite precipitation was evaluated in three molar ratios 1:1:1, 1:1.2:1.2, and 2.5:2:1 of [NH4+]:[Mg2+]:[PO43−] and at two different pHs; 9 And 9.5. Since, the amount of ammonium in the leachate was much higher than magnesium and phosphate, the tested molar ratios were established based on the ammonium concentration and the magnesium and phosphate concentrations were adjusted by magnesium chloride (MgCl2.6H2O) and phosphoric acid (H3PO4), respectively. XRD and FTIR analysis were used to assess the precipitated struvite mineralogy. The position and intensity of the peaks in the precipitate formed in all treatments were in good agreement with the standard struvite peak, which confirmed the precipitation of this mineral. FT-IR analysis showed the spectrum of struvite mineral in all tested molar ratios. Comparison of the formed precipitate showed that at pH= 9.5 the amount of struvite formed in molar ratios of 1:1:1, and 1:1.2:1.2 of [NH4+]:[Mg2+]:[PO43−] was more than that at pH=9. Removal of ammonium from the leachate at pH=9.5 and in molar ratios of 2.5:2:1, 1:1.2:1.2, and 1: 1: 1 was 45.5, 39.7 and 32.7%, respectively. Therefore, the use of resources such as landfill leachate in the struvite production, while removing ammonium, can reduce the production cost of this fertilizer.

Surface soil moisture is a key variable in hydrological, meteorological and environmental studies and one of the important and effective parameters in the occurrence of dust. The purpose of this paper is in two folds, the first to validate the soil moisture of ECV database and the second investigate the effect of soil moisture on occurrence dust. The first purpose of this study was to evaluate the relationship between estimated surface soil moisture of remote sensing ECV databases and observed surface soil moisture of agricultural meteorological stations located in the south and west of Iran in Khuzestan, Ilam, Kohgiluyeh and Boyer-Ahmad, Lorestan and Chaharmahal-Bakhtiari provinces.  For this purpose, statistical indicators such as Pearson correlation coefficient, mean absolute error, mean oblique error and root mean difference of squares were used to validate the data of this database with data measured in meteorological stations of Farkashhar, Sarablah and Silkhor in the south of the country.The results of soil moisture validation at selected stations showed that these data are able to measure the behavior and amount of soil moisture with relatively good accuracy.  The best result is obtained at Sarablah station, which shows a very good correlation coefficient (0.82), therefore ECV database data can be used to determine the behavior and amount of soil surface moisture on a large scale to compensate for the lack of terrestrial measurements inside and outside the country. The second purpose of this study is to find the effect and relationship between surface soil moisture in countries located in western Iran on the occurrence of dust in the southern and western provinces.  Regarding the relationship between the effect and the amount of surface soil moisture with the occurrence of dust, the results show that the when surface soil moisture decrease, the occurrence of dust in the interior of the same province has increased, but the decrease in soil moisture in foreign countries (western Iran), cause increasing the occurrence of dust in the entire southwestern region and even central of Iran. It was also found that the number of dust events during the cold periods of the year has increased in recent years.

Solar radiation is one of the key factors in the fields of agriculture, hydrology and meteorology and plays an essential role in various physical, biological and chemical processes such as snowmelt, evaporation, photosynthesis and crop production. Thus, accurate estimation of this parameter is very important. Accordingly, in this study, the amounts of daily solar radiation were estimated using artificial neural network and artificial neural network-genetic algorithm in six stations of Ardabil province including Ardabil, Bilehsavar, Sareyn, Germi, Meshgin Shahr and Nir. The data used in this research include maximum, minimum and average temperature, relative humidity and wind speed of the mentioned stations in a time period of two years (2017-2018) which are used in eight different combinations as input data of the models. Also, statistical indices of correlation coefficient, root mean square error, Wilmot index, Kling-Gupta efficiency and Taylor diagrams have been used to compare the obtained results. Generally, the obtained results indicated that among the artificial neural networks, the model of Bilehsavar station and among the artificial neural network-genetic algorithms, the model of Ardabil station recorded the most accurate results. Also, MLP-VIII model in Bilehsavar station with a correlation coefficient of 0.856, root mean square error of 0.319 (MJ/m2d), Kling-Gupta efficiency of 0.659 and Wilmot index of 0.893 have the best performance in the utilized models. Therefore, it is recommended to use artificial neural network-genetic algorithm method for estimation of solar radiation.

From environmental aspects, the exchange of surface and subsurface flows in riverbeds due to river morphology and in stream structures is very important. The flow path structures especially control structures have a more effective role than the river morphology in the formation of these exchanges. In this study, the effect of penetration depth of such structures in the porous bed on the characteristics of exchange flows was investigated both experimentally and numerically. The experiments were performed in a flume with a length of 10 m, width of 20 cm, depth of 30 cm and a slope of 0.01, at three penetration depths of 9, 11 and 13 cm respectively. Potassium permanganate tracer was used for tracking the flow. In addition, to obtain the characteristics of the exchange flow; the mainstream and the exchange pattern were simulated by particle tracking method using Flow 3D software. The results showed that in the Reynolds range of 1020 to 3450, increasing the penetration depth of the structure from 9 to 13 cm, would increase the residence time but decreases the exchange rate. However, increasing the flow rate would decrease the exchange rate and increase the retention time. Accordingly, the use of a step with a higher penetration depth is recommended to create a longer residence time. However, a step with a smaller penetration depth may be used to produce a higher exchange rate.

Soil moisture content (SM) is a critical state variable that significantly affects both the hydrological cycle and agricultural production. Therefore, accurate estimation of soil moisture is important for agricultural water resources management. Remote sensing observations in the near- and shortwave infrared have large potential for estimating soil moisture. In addition, soil physical and hydraulic properties affect spatial and temporal variability of soil moisture. The objective of this research was to derive different models for soil moisture estimation in Amir Kabir sugarcane agro-industry fields, Kuzestan province using a combination of soil physical/hydraulic properties and remote sensing observations with machine learning algorithms. Consequently, 166 ground control points and 16 Sentinel-2 satellite images were investigated during the growth period of sugarcane in the year 2021. Six machine learning algorithms including decision tree (DT), support vector machine (SVM), Linear regression, Boosted and Bagged trees, and nural network were used for modeling. Seven models were derived from the combination of soil physical/hydrological properties and remote sensing indices in a hierarchical manner to predict soil moisture content at the field scale. The results indicated that the combination of soil physical/hydraulic properties with remote sensing indices enhances the accuracy of soil moisture estimation. It is observed that almost all developed models performed well for estimating soil moisture, with an RMSE of 0.04-0.06 cm-3cm-3 and an R2 of approximately 0.80. The STR parameter was found to be more sensitive to changes in soil water content than NIR reflectance. Therefore, STR was identified as the most important feature in estimating soil moisture content. Moreover, stepwise linear regression with RMSE value of 0.042 cm3 cm-3 performed the best in soil moisture estimation. According to the results, the models successfully capture the spatiotemporal dynamics of soil moisture and can be used for irrigation scheduling and precision irrigation management at the field scale.

Awareness of erosion and its spatial changes is a guide for managers and planners in the important matter of water and soil protection in watersheds. In the present study water flow and sediment data of 40 hydrometric stations in the Middle Alborz region and in the statistical period between the wateAwareness of erosion and its spatial changes is a guide for managers and planners in the important matter of water and soil protection in watersheds. In the present study, with the aim of presenting a map of soil water erosion, water flow and sediment data of 40 hydrometric stations in the Middle Alborz region and in the statistical period between the water years of 1980-1981 to 2020-2021 were used. First, the most important factors affecting erosion and sedimentation in the studied sub-basins including 30 hydrological, physiographic, geomorphological, geological and soil characteristics, climate, land use and vegetation as independent variables and two sediment characteristics; including total yield and specific deposition as dependent variables were identified. Using factor analysis and principal component analysis methods, the most important characteristics of effective basins in sedimentation were identified. In the next stage, the study area basins are divided into six homogeneous groups based on selected characteristics and cluster analysis and multivariate regression stepwise method was used to model between specific sedimentation and basin characteristics. According to the selected regression models, it is determined that the amount of special sediment in the Middle Alborz region to five factors of agricultural land area (rainfed, irrigated and orchards), the area of sub-basins, the total area of erosion-sensitive and Quaternary structures, the average annual discharge and the form factor of the basin depend on the fact that these five factors control 92% of the sediment production changes in the selected sub-basins. Then, considering the sediment transfer coefficient of the sub-basins, the amount of soil erosion was determined and the soil erosion map was drawn for the Middle Alborz region. The results showed that the average sedimentation rate and the average weight of soil erosion in the study area were 3.84 and 13.56 tons per hectare per year, respectively. In general, the factors affecting erosion and sedimentation of the Middle Alborz region can be divided into three groups: land use change due to human activities, geology and physiography.r years 1980-1981 to 2020-2021 were used. First, the most important factors include 30 hydrological, physiographic, geomorphological, geological and soil characteristics climate land use and vegetation as independent variables and two sediment characteristics. The most important characteristics of effective basins in sedimentation were identified. In the next stage, the study area basins are divided into six homogeneous groups based on selected characteristics and cluster analysis and using multivariate regression by stepwise method to model between specific sedimentation and basin characteristics. According to the selected regression models, it is determined that the amount of special sediment in the Middle Alborz region to five factors of agricultural land area (rainfed, irrigated and orchards), the area of sub-basins, the total area of erosion-sensitive and Quaternary structures, The average annual discharge and the form factor of the basin depend on the fact that these five factors control 92% of the sediment production changes in the selected sub-basins. Then, considering the sediment transfer coefficient of the sub-basins, the amount of soil erosion was determined and the soil erosion map was drawn for the Middle Alborz region. The results showed that the average sedimentation rate and the average weight of soil erosion in the study area were 3.84 and 13.56 tons per hectare per year, respectively. In general, the factors affecting erosion and sedimentation of the Middle Alborz region can be divided into three groups: land use change due to human activities, geology and physiography.

Global warming has changed rainfall patterns and reduced snow sources. The main objective of this research was to investigate the impact of temperature increase on snowmelt and river runoff in hot months of the year along with analysis of climate variables in Tamar basin, Iran. For this purpose, the snow cover area was extracted from the daily images of Modis Satellite, based on elevation. Then, the study area was divided into four districts. Discharge flow measured data of Tamar hydrometric station, precipitation of Qarnaq and average temperature of Gidagh stations were used from 2013 to 2016 for calibration and from 2017 to 2019 for verification, to simulate snowmelt runoff. Snow cover extent, in calibration stage and january, reached the highest values of 28% and 28.8% in the third and fourth districts, respectively. Furthermore, in the verification stage, the third and fourth districts in February had the highest percentages of 45.8 and 30.2, respectively. Comparison of simulated and measured runoff data revealed that the portion of runoff due to snowmelt is significant by passing from February to April. So that the highest increase (from 1.8% to 39.1%) in runoff amount was corresponded to the water year of 2018-2019. The highest and the lowest percentages of snowmelt in water years of 2014-2015 and 2017-2018 were 19 and 3.3 percent, respectively. The results of sensitivity analysis of model parameters including temperature decrease rate, critical temperature, delay time, degree-day factor, X and Y coefficients, precipitation runoff coefficient and snow runoff coefficient showed that the rainfall coefficient and X parameters are the most effective parameters. The effect of temperature and rainfall on runoff process was varied in different months.

Nowadays, vast areas of forests have been changed to farmlands, and the change in land use is one of the important factors reducing soil quality. The purpose of this research is to investigate the effect of land use change from forest and pasture to agriculture on some soil characteristics in Sarab Badia area (Kermanshah province). Sampling was done in 2018 from points with the same slope in the form of a nesting site. For this purpose, four areas near each other that have the same landscape and include 3 uses of forest, pasture, and agriculture and also two depths of 0-20 and 20-40 cm were considered. Composite samples were prepared from each depth. After transferring the samples to the laboratory, the important characteristics of the soil were measured based on standard methods. The results showed that among the physical characteristics of the soil, MWD was affected more than the other physical characteristics due to the change in land use, so that by changing the land use from forest to agriculture in the subsoil layer (20-40 cm), MWD decreased by 51.04%. Among the soil chemical properties, organic carbon and total nitrogen with 52.95% decrease in top layer of the soil (0-20 cm), had the most variability due to the change of land use from forest to pasture. The metabolic coefficient was sensitive to the change in land use from forest to agriculture, as its value decreased by 92.92% in the sub layer (20-40 cm). Characteristics such as; MWD, organic carbon, total nitrogen, and metabolic coefficient are highly sensitive to changes of management conditions at the field level, so these characteristics can be used to monitor soil quality.

Declining water table and its consequences due to overexploitation of groundwater resources will be one of the challenges in the coming years in arid and semi-arid areas. Therefore, in this study, the groundwater level and its salinity in Shiraz basin for 27 years (1993-2020) was investigated. The trend of the water table time series was analyzed using Mann-Kendall test. Result shows a significantly decreasing trend; So that the negative trend of water table after the change point in June 2002 has increased to 2.8 times of the previous period. The possibility of using Gravity Recovery and Climate Experiment (GRACE) satellite data to monitor the groundwater level was also investigated. The results show very good accuracy (NRMSE <10%) of different versions of data. Examination of groundwater salinity using electrical conductivity (EC) data showed an increasing salinity trend in the basin. Factors affecting decreasing trend of quantity and quality in the basin were also analyzed. Results showed no significant trend in rainfall time-series. However, the increasing trend of the population and vegetation in the basin and the lack of surface water resources have led to a significant increase in groundwater abstraction. Thus, when planning, the land sustainability should be seriously considered by managers.

Drought is one of the most harmful natural disasters that affects the plants yield and terrestrial ecosystems and causes significant damage. The severity of drought and duration of drought recovery (the time required for plant to return to normal conditions, after the end of drought) are vital parameters for better drought management. This article assesses and investigates the length of drought recovery period in different land uses and climates of Iran. For this purpose, climate classification was done using the De Martonne method, and agricultural drought was monitored using the Vegetation Health Index (VHI) from 2000 to 2020 for cropland, forest, grassland, and shrubland uses. Years of 2000, 2001, and 2008 were selected as drought periods. Furthermore, using gross primary productivity (GPP), the length of drought recovery period was acquired. The results showed that the average duration of  drought recovery period varies from about 34 days in the forest to 81 days in the shrubland. The rapid recovery of forests after the drought is due to their deep roots. In general, the shrubland and cropland classes had a more prolonged recovery period than the other classes, and the forest class had the shortest recovery period, which indicates the high resilience of the forest and the low resilience of the cropland and shrubland classes. Also, the results revealed that the average length of the recovery period varies from about 20 days in humid climates to 80 days in arid climates, which indicates that the conditions for drought recovery in humid climate are better than that in arid climates. In general, the drought recovery period becomes longer as one moves from a very humid climate to a dry climate.

Zayandeh-rud basin can be considered as one of the most challenging basin in terms of water security in Iran, followed by political, social and economic security affected by the water governance crisis in the country. The failures of the hierarchical governance structure in this basin lead us to formulate an appropriate mechanism based on participation in the framework of "Social Water Banking". For this purpose, a qualitative research method based on the analysis of interviews, articles and documents using philosophical theory of “Practice” and “Normative Practice” model was used. The results of in-depth analysis and review of information sources using the tools of normative practice model visualized the structure and objectives of social water banking in Zayandeh-rud basin, including the rules of qualifing, fundational, conditional and regulation. The formation of the Zayandeh-rud River Basin Parleman, the strengthening of multilateral and multi-level committees, information transparency and the formation of information working group including farmers are structural changes that in the form of social banking and by reforming governance structure, water sustainable security can be reached in the basin.