Iranian Journal of Soil and Water Research
Year:2020 | Volume:51 | Issue:5|Papers Count:20

Identification of areas vulnerable to land degradation is essential for sustainable management of natural resources as one of the steps in the conservation framework. Identification of areas susceptible to degradation as well as determination of vulnerability to this phenomenon is one of the most important issues to an assessment of land degradation. This study tries to assess the land degradation vulnerability in Maharloo-Bakhtegan watershed using nine criteria including land use, vegetation, soil salinity, quantity and quality of groundwater, livestock density, literacy level, and population. In the first step, the relationships between the criteria were determined using the eDPSIR framework, then the weight of each criterion was determined using the ANP method. Fuzzing the layers, the map of land degradation vulnerability was provided by combining the layers using ArcGIS10. 3 software. The results showed that the high class of vulnerability covers the highest area in all elevations class except for the first 200 m. the most vulnerable class was in the high class covering about 64. 31% of the area. The high and medium classes of vulnerability include rangeland and agricultural land uses, respectively, indicating a high level of vulnerability and impact of human activities. This percentage of vulnerability in rangeland and agricultural land uses is due to the importance of land use and vegetation criteria having the highest weight among the criteria affecting the vulnerability to land degradation.

The particle sizes distribution (PSD) has a major impact on the pore arrangement in the soil, which is the basis for many soil water retention curve (SWRC) models. Lack of some particles in PSD lead to bimodal distribution of soils. In this situation, the performance of developed SWRC models for normal soils were decreased. In this study, the accuracy of three models that estimate SWRC from PSD including Aria et al. (1999), Mohammadi and Vanclooster (MV) (2011), and modified MV, that combined with VanGenuchten (1980) model, (MV-VG) (2013) were investigated in unimodal and bimodal zone of soil textural triangle. For this purpose, 94 soil samples, with a wide range of physical properties including PSD and SWRC data, were selected from the UNSODA hydraulic properties database and their SWRC were estimated by the proposed models. Estimation accuracy was evaluated using RMSE, NSE and R2 statistics. Results showed that in unimodal soil textures including loam, silt loam and silty clay, the models have good accuracy. As well as in sand, sandy loam and loamy sand soils, because of high sand content, models accuracy not affected by bimodality. In soils associated with bimodal zone of soil textural triangle including sandy clay loam, clay loam, sandy clay and clay, SWRC prediction depended on bimodality index that proposed in this paper. The mean RMSE, NSE and R2 statistics for the three models in unimodal zone of soil textural triangle were obtained 0. 044, 0. 378 and 0. 921 and in bimodal zone they were 0. 062,-2. 501 and 0. 859 respectively. Also, it was found that the accuracy of the three models was different and the MV-VG model had insignificant correlation with the bimodality index and could estimate more accurately SWRC from PSD.

Water management in agricultural sector is essential as the most important consumer of water. Assessing the actual amount of water used by different crops could be very effective in identifying and providing appropriate solutions to reduce agricultural water consumption. In this study, water footprint and partial irrigation water supply index were used to investigate the amount of water consumed by crops in Sistan and Baluchistan Province. The water footprint is a complete index, representing the actual amount of water consumed based on climatic condition in each area. Water footprint was evaluated on the basis of four components; green, blue, gray and white water footprints. Water productivity of different crops was also studied from an economic point of view. The results showed among the crop and orchard products, the wheat and pistachio showed the highest green water footprints, respectively. In terms of blue water footprint, maize, pomegranate and grape had the lowest amount. In terms of gray water footprint, wheat and pistachio had the highest values. In terms of white water footprint, wheat and pistachio had the highest values. In terms of overall water footprint, wheat and pistachio had the highest values. Among the crop products, barley and wheat had the lowest economic productivity and maize had the highest value. Among the orchard products, bananas had the highest economic productivity (2562. 64x1000 riyals per cubic meter) and pistachio had the lowest one (29. 4x1000 riyals per cubic meter). The values of relative irrigation water supply index were higher than one, indicating all crops are over-irrigated. Therefore, considering the high water footprint in the products produced in the province, the priority should be given to plant crops in each area based on the water footprint. Also, deficit irrigation methods should be used to increase irrigation water productivity.

Nitrate is one of the most important pollutants in drainage water in agricultural lands. Biological removal or reduction of nitrate has recently been considered in different parts of the world. The bioreactor with the denitrification process is one of the newest solutions for this purpose. Scientific and local experience is needed to optimally use the bioreactor. Due to the existence of Moghan irrigation and drainage network and a high volume of effluent, this study was conducted to evaluate the efficiency of bioreactor for removal of nitrate at Moghan plain conditions. The cross-section of bioreactor was triangular and water retention times were 12, 16 and 24 hours. The bioreactor core was selected from wood chip, wheat straw and corn chips as carbon-based and treated substrates, and each treatment had three replicates. Results of 12 hours retention time showed that, on average, the wood chip reduced the initial nitrate by 29. 84%, which had the highest nitrate depletion among the organic matters. The performance of the two other organic matters was not significantly different according to Duncan test. In 16 hours retention time, the performance of bioreactors with different organic matters was statistically different for nitrate removal and the wood chip, wheat straw and corn stalk treatments were prioritized with 40. 1, 35. 23 and 28% nitrate removal, respectively. In 24 hours retention time, although all three treatments had the same performance for nitrate removal from agricultural wastewater, the wood chip treatment with 46. 75% removal efficiency was the best. The results also showed that the percentage of nitrate removal increased with increasing the retention time for all three treatments.

Labyrinth weirs are structures for transferring large flows at low heads, in which the effective length of crest for a given channel width is increased. In this study trapezoidal arced labyrinth weirs with different arc radius and cycle length were investigated. Several experiments were conducted using physical models to evaluate the effect of R/w1 (ratio of arc radius to middle cycle width) and B/w1 (ratio of weir length in flow direction to middle cycle width) on weir discharge coefficient. The experiments were carried out using a 6 m long test flume with cross section of 0. 6 m width and 0. 6 m height. Using Buckingham method of dimensional analysis, it was found that the discharge coefficient is a function of three variables; hydraulic head, arc radius of weir and weir length ratio. In general, the results of this study showed by increasing arc radius ratio, discharge coefficient of trapezoidal arced labyrinth weir increases up to 27. 3%. Besides, by decreasing the weir length ratio from 1. 5 to 1, discharge coefficient increased up to 29. 7%.

Due to poor seasonal distribution of rainfall in Mazandaran province and shortage of water resources for citrus irrigation in recent years, these trees are generally subject to water stress in the warm seasons. In order to study water deficite stress on quantitative and qualitative yield of oranges, a completely randomized block design with four treatments and four replications was conducted at Ramsar citrus and subtropical fruits research center in 2018-2019. Experimental treatments included full irrigation (FI), deficite irigation (DI), partial rootzone drying irrigation (PRD) and fixed partial rootzone drying irrigation (FPRD) at 50% level of full irrigation. At the end of study, quantitative and qualitative characteristics of tree and fruit, including leaf relative swelling, leaf water potential, length and branch diameters, fruit diameter, relative growth rate of the fruit, leaf elements, weight of the shed fruits and width and thickness of skin and fruit volume, yield, vitamin C, soluble solids (TSS), titrable acidity (TA), color index (Chroma, CI, h, L) were measured and the comparisons between treatments were performed by SNK test at 5% level. The results showed that there was no significant differences between treatments in terms of shoot length and diameter, amount of leaf elements, relative water content of leaves, and fruit weight. Although, there was no significant difference among treatments in terms of fruit quality, but PRD, FPRD and DI treatments had good quality compared to FI treatment. Comparison of leaf water potential of relative growth rate and fruit diameter showed significant differences among treatments. FPRD, PRD and DI methods reduced water consumption and increased water use efficiency. Regarding to the fruit color index, the highest fruit market value was observed in DI method. The PRD method slightly reduced fruit weight but increased TSS and TA, which are important in fruit juice production.

Some parts of the free surface flow including river networks in which the velocities is low, can act as dead or hyporheic zones. These areas can help to the temporary storage of the tracers and consequently increasing the residence time parameter. In this study, the effects of consecutive reservoirs caused by construction of gabion flood control structures have been investigated in terms of dead zones creation and residence time expansion. For this purpose, 36 experiments were performed in the laboratory flume, including two gabion dams. The experimental variables included three rock median diameters, four entrance discharges and three entrance concentrations. The HCIS model, which includes temporal parameters of the λ , T1, and T2, has been used to obtain the residence time, the reservoirs volume behind the gabion dams and flow hydraulic parameters. The results showed that the transport time parameters were increased linearly with reservoir volume (V) and number (N). Also, linear regressions were established between the number of dams and the other temporal parameters obtained from experimental breakthrough curves (BC). It was found that the slopes of N-𝑡 𝑡 and V-𝑡 𝑡 (𝑡 𝑡 is total duration time of the BC) linear regressions were bigger than the similar values for 𝑡 1 (time from the injection time origin to the rising point of BC curve), indicating a higher residence time due to transient storage of the pollution. Also, it was found that the time parameters obtained from HCIS model are increased linearly with N and distance from the injection point.

Hyporheic zone is an active area that groundwater and surface water are mixed together in that zone. Any existing contamination in the surface water can be transferred to groundwater through this zone. In this research, the hyporheic zone beneath Zarjoob River and above Foomanat Aquifer was investigated by modeling to understand the impact of river on groundwater quality. For this purpose, three stations and three nearby groundwater wells were selected and water samples were collected in Year 2006-2007. The hyporheic zone was modeled for TDS as conservative parameter and NO3 as non-conservative parameter. MODFLOW and MT3D were used to simulate TDS in the hyporheic zone in two seasons; the agricultural season and nonagricultural season. The results showed that the hyporheic zone in non-agricultural season is 20 m far from the river, while in the agricultural season it was significantly less than 20 m. The results also showed that the reduction rate of TDS in agricultural season was more than that in non-agricultural season. This could be due to more groundwater use and increase in groundwater flow velocity. In the next step, NO3 was simulated using MODFLOW and RT3D. The simulation was carried out for two scenarios; with and without biodegradation. The results showed that without considering biodegradation, the hyporheic zone would extend to 25 m far from the river while with biodegradation it would be reduced to 20 m.

One of the most significant environmental consequences of municipal solid waste is the generation of leachate at landfills. Leachate is a very hazardous liquid leading many difficulties including contamination of surface, groundwater, and soil. The mechanical parameters of the soil can be affected in contact with leachate and its changes depend upon the type of leachate and soil. The reactions between the soil system and the leachate cause changes in landfill soil mechanical properties that may affect the structural stability of the landfill structures. So that, the present study investigate the effects of natural leachate of Aq Qala landfill on silty-clay soil. For this purpose, the natural leachate samples and the untoched soil samples with leachate were collected from the Aq Qala landfill. Unconsolidated no drained (UU) triaxial test was performed on soil specimens containing 0, 5 and 15% leachate at three curing times; 7, 14, 28 days. In order to analyze the obtained results, the stressstrain curve was investigated in terms of leachate amount, curing period and cell pressure as the variables applied to the samples. The results indicate that the contamination of soil by leachate reduces the maximum deviator stress and the friction angle, while it increases the soil adhesion. In addition, the influence of leachate increases by leachate concentration in the soil and curing period.

Evapotranspiration is an important component of water balance and a key element in water resources management, especially in arid and semi-arid regions such as Iran. The purpose of this study is to investigate the uncertainty of actual evapotranspiration (ETa) estimates derived from a remote sensing-based model, i. e. Priestley– Taylor Model (PT-JPT), and two global climate datasets namely GLEAM and ERA-Interim in Karkheh basin southwest of Iran during the 2013-2017 period. The three cornered hat (TCH) method was used to analyze the uncertainty for each spatial cell (0. 25× 0. 25) in the basin. The results of uncertainty analysis showed that ETERA-Interim, ETGLEAM, and ETPT-JPT data have the lowest relative uncertainty in 38%, 12. 6% and 49. 4% of cells, respectively. The highest percentage of cells with lowest uncertainty in Seimare, South Karkhe and Gamasiab sub-basins was correspond to ETPT-JPT model (54. 4%, 72. 3%, and 50%, respectively). In Gharehsoo and Kashkan sub-basins the ETERA-Interim estimations were found as the method with least uncertainty, (55. 5% and 53. 4%, respectively). The highest number of cells with lowest relative uncertainty belongs to ETERA-Interim. Considering the lowest uncertainty, variation of actual evapotranspiration with elevation in Karkhe basin showed that the two databases and PT-JPT model perform well at 1400 to 1800 m above sea level. ETPT-JPT model did a better job in warm dry climates. ETERA-Interim and ETGLEAM data estimations were selected as the best methods in semi-humid temperate and hyper-humid-cold climates, respectively. In cells with farm-garden and forest land use, ETGLEAM have the lowest uncertainty. Similarly, in rangelands, both ETPT-JPT and ETERA-Interim databases, and for drylands, ETERA-Interim data can be recommended. Further feasibility studies in other climates are required for more scrutiny.

The lack of required datasets over the catchments impose basic problems for applying hydrologic models. By increasing the satellite-based technologies over the past decades, several water balance components have been developed by using remote sensing and data assimilation techniques. This research addresses the efficiency of evapotranspiration values which are obtained from the reanalysis models (GLEAM, W3RA and HBV) for calibration of VIC-3L hydrologic model over the SefidRood basin (SRB). Results showed that using the evapotranspiration dataset, which is estimated by GLEAM, is the best for calibration of VIC-3L (NS=0. 56 and CC=0. 80) and simulating the streamflow at the outlet of SRB. Also, using the HBV reanalysis model’ s results, in both daily and monthly time scales, with the KGE=0. 64 leads to the better performance in simulating streamflow when comparing to the base scenario (calibration of VIC-3L model with the observed streamflow data). Finally, results indicated that using W3RA and GLEAM datasets improved the VIC-3L performance in estimation of runoff volume and the maximum relative error restricted to only 4. 0 %.

The rapid growth in world population and its consequent increasing food demand require a scientific approach to paddy field productivity. To further increase rice production, the best solution is enhancing the rice yields per unit area. There are numerous integrated indices that can clarify the soil conditions and fertility characteristics, in which the integrated fertility index (IFI) is more practical. Therefore, the current study will explore soil fertility status of paddy field using IFI equation, and more broadly to issue suitable solutions for paddy soil management. This study was undertaken at Goldasht research station of the rice research institute of Iran-Amol. One hundred and twenty-eight paddy soil composite samples of plowing layer (depths of 0 to 30 cm) with a constant interval were collected to analyze for some physical and chemical properties based on rice soil requirements. Fuzzy logic theory, Principal component analysis (PCA) and IFI concepts were used for quantitative ranking of qualitative soil characters, weighing of soil properties and integration of studied soil characters, respectively. The results indicated that IFI values varied from 0. 03 to 0. 20. The studied paddy fields were divided into 4 individual parts through IFI values mapping method. At lower values of IFI (low soil fertility), pH, available P, OC and less broadly total N were lower than their critical levels for proper rice growth and development. Interestingly at higher values of IFI, OC and total N limitation still existed. It can be concluded that organic carbon limitation in all studied plots had negative and unavoidable effects on not only paddy soil fertility status (a vital role for sorption and desorption of soil nutrients), but also soil physical characters (enhancing soil structure, porosity, and water retention). The findings of current study also showed that the integrated fertility indices not only can show the most important limitations for rice production but also can issue the effective solutions to remediate these limitations. Key words: Rice, soil fertility, integrated fertility index, fuzzy logic, geostatistics

The yield of Wheat is influenced by various factors including climate, land management practices and soil properties. It is important to investigate the relations between soil physical and chemical properties and the yield of wheat. In this study, the physical and chemical properties of the soil top layer (0-30 cm) and the yield of Wheat were determined in 34 wheat fields of Nazarabad region in Alborz province, during wheat crop year of 2018. Principal Component Analysis (PCA) was used to select the effective parameters on wheat yield and multivariate linear regression was applied to analyze the relationship between wheat yield and soil properties. Finally four regression equations were presented. Principal Component Analysis (PCA), stepwise linear regression, the highest correlation method and all the measured properties were used respectively to prepare four equations to estimate the Wheat yield. The evaluation of each equation was performed by Geometric Mean Error Ratio (GMER), Geometric Standard Deviation of the Error Ratio (GSDER), Normalized Root Mean Squared Error (NRMSE), and determination coefficient (R2). The results showed that wheat yield varies from 2750 to 10500 kg/ha in the region and the proposed equation using clay, Pava, Cu, porosity, calcium carbonate equivalent and pH with GMER, GSDER, NRMSE and R2 values of 0. 99, 1. 19, 0. 17, and 0. 64 respectively, is the most appropriate equation for determining of wheat yield. Therefore, in regions with climatic conditions and soil physical and chemical properties similar to the study area, the yield of wheat can be estimated with an acceptable level, based on the proposed equation.

The aim of this study was to assess the crop water stress index (CWSI), derived from leaf temperature using infrared thermometer measurements, to investigate the water stress status and irrigation timing of olive trees. Fpr this purpose a regression function was determined between crop water stress index and relative water content of leaf (RWC) and soil water content (SWC). The experimental treatments involved two olive cultivars (Koroneiki and T2) and four water regimes (irrigation of 100, 85, 70 and 55% of crop water requirement). The results showed that the non-water stressed baseline is varied throughout the study period as well as during the day. The daily variations of non-water stressed baseline were mainly due to variations in the intercept of the non-water stressed baseline that can be explained by variations in zenith solar angle. After investigating the relationship between vapor pressure deficit (VPD) and the difference between crop and air temperature (𝑇 𝑐 − 𝑇 𝑎 ), the equation of Tc-Ta =-0. 45 VPD+1. 06, r2 = 0. 99 was determined for the non-water stressed baseline of the olive trees at 12: 30 pm. Crop water stress index of olive trees increased significantly in deficit irrigation regims compared with control trees. crop water stress index was significantly correlated with relative water content (Kroneiki: r2=0. 82**, T2: r2=0. 80**) and soil water content (Kroneiki: r2=0. 66**, 𝑇 2: r2=0. 69**). Therefore, the crop water stress index is a good indicator of the water stress status of the Koroneiki and T2 olive trees.

Biocrusts affect several soil hydrological properties such as soil water dynamic and evaporation. The aim of this study was to explore the effects of biocrusts on soil water dynamic and evaporation as a function of time. Soil sampling carried out from saline soil mass and biocrusts (undisturbed along with 5 cm underneath soil) from Qara Qir rangeland. To conduct experiment in a controlled condition, four plastic columns (20 cm d × 50 cm h) were prepared and filled up to 48 cm and 6 columns up to 43 cm with uniform saline soil mass collected separately from bare soils of study area, then a layer of intact BSCs (with 5 cm thickness) was put on the top of soil columns. Daily evaporation rates were measured with electronic balance weightings during 142 days. soil water content was determined three times in days of 17, 50 and 103 after experiment onset in any columns, at depths of 10 (D1), 20 (D2), 30 (D3) and 40 (D4) cm. The results showed that BSCs prevent water evaporation from soil surface, particularly at high evaporation demand (up to 77 days). The effect of BSCs on the evaporation rate at low atmosphere demand (77 to 142 days) was insignificant. Soil water content followed evaporation trend. According to these findings, it can be concluded that the BSCs as soil surface coverage is a key factor for reducing evaporation and conserving water in the soil.

Accurate and reliable forecasts of river flow are required for proper management of watershed systems. In recent years, data-driven models and especially artificial intelligent based models have been successfully used in various areas related to water resources. However, uncertainty analysis of these models has been less appreciated in prior studies. In the present study, the output uncertainty of five data-driven models including modular, PCA (Principle Component Analysis), TLRN (Time-Lagged Recurrent Network), ANFIS (Adaptive-Network-based Fuzzy Inference System) and SVM (Support Vector Machine) type models in forecasting river flow has been investigated using 95PPU, p-factor and d-factor quantities. Using the observed meteorological and flow data during 1998-2012 in Hablehroud Basin, different structures of the proposed models were trained and tested. The final values of p-factor and d-factor for each model type were obtained. The results showed that SVM with a p-factor of 82% produces the most reliable forecasts in the present study.

Accurate prediction of water infiltration rate is very important for programming the soil and water conservation practices in catchments. In this study, the efficiency of infiltration rate models was investigated in three land uses consist of dry-farming, irrigated farming and pasture lands in Tahamchai catchment (20 locations with three replications) in North West of Zanjan province, Iran. The efficiency of models was assessed using the measured data based on the determination coefficient (R2), root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE). Results indicated that there is obvious variation in water infiltration rate in different land uses, so that the highest value was in dry-farming lands (16. 6 cm h-1) and the lowest value was in pastures (5. 4 cm h-1). Among the proposed models, the Kostiakove’ s equation showed the highest R2 (0. 99), the lowest error (RMSE= 0. 01 cm h-1) and the highest NSE (0. 99) in pasture. Philip’ s equation appeared to be more efficient in the rainfed-farming and irrigated farming lands with R2=0. 99, RMSE ranging from 0. 14 to 0. 22 and NSE=0. 99. Although, the Green-Ampt’ s equation was fitted relatively well to the measured data (R2= 0. 94), its error index (RMSE= 2. 32 cm h-1) was relatively high, indicating the least efficiency among the models. The GA model showed higher estimation error for higher infiltration rate values which occur mostly at initial times of water infiltration process. Therefore, regarding the higher correlations of the Kostiakove’ s and Philip’ s equations with the measured data, these two models are recommended for predicting water infiltration rate in different land uses of Tahamchai catchment.

The study of turbulent flow field passing over the rough beds is still one of the important and controversial issues after a few years. In the past, most researchers have focused on flow with a high and medium relative submergence (the ratio of water depth to aggregate size), but only a few studies have been done on the low relative submergence flows. In this study, the gravel bed open-channel flow in a straight channel has been numerically modeled and studied using the Flow-3D package. The numerical model has been calibrated and verified using available data in the literature. During simulation, six different relative submergences were analyzed and the coefficients of Von Karman, integral constant and zero displacement planes determined. Results showed that in flat-bed conditions, the Von Karman coefficient is 0. 41, but in the case of rough bed and relatively low submergence conditions, this value changes with relative submergence. These changes ranged from 0. 29 to 0. 43. It was also observed that with increasing depth, the Von Karman coefficient initially decreased and increased consecutively. Also, the zero displacement plane has no coherent relationship with relative submergence at all and it cannot be commented definitively. At the end, a new experimental formulation for the Von-Karman coefficient has been presented as a two-function equation with relative submergence boundary.

Despite the abundance of iron in the earth's crust and soil, this nutrient is not usually available for plants in calcareous soil with high pH. In the present study four superior isolates with alternative physiological traits (No. 3, 8, 20 and 23) isolated from 10 soil samples for producing siderophore and their contribution in solubilizing insoluble iron-containing compounds in calcareous soil were evaluated. Results showed that in spite of higher halo diameter to colony diameter of isolate No. 23 in CAS agar medium (3. 46mm) at soil incubation test, DTPA-extractable iron using isolates No. 3 and 20 was greater than the ones in isolate No. 23 as 10. 7 and 14. 67 percent, respectively. Greatest amount of DTPA-extractable iron in the soil sample was obtained during 40-days incubation. Molecular test showed that isolate 20 was 99 percent similar to the strain Bacillus Sporothernodurans. Biochemical tests also revealed that isolate 8 probably belong to Entrobacteriaceae family and isolates 3 and 23 belong to Pseudomonas Genus.

Soil moisture is a key variable in determinant terrestrial systems for water and energy exchanges between the earth's surface and the atmosphere. In this study, the soil moisture data of SMAP satellite at different times and land uses were validated through four indices of correlation coefficient, root mean square error, unbiased root mean square error, and mean difference in 2017. For this purpose, Simineh-Zarineh basin located in the south and southeast of Urmia Lake, which is the largest sub-basin of the Urmia Lake basin, was investigated. The total study area is about 1762500 hectares. The spatial and temporal resolution of the SMAP satellite is 9 square kilometers and three days. Therefore, 287 ground points on a grid were selected for sampling in the study area. The results showed that the SMAP satellite data with ground observation data on December 3 and April 3 had a maximum RMSD value of 0. 25 to 0. 35 cm3 cm-3. The results revealed that the soil moisture data of SMAP satellite with RMSD values between 0. 18 to 0. 33 cm3 cm-3 and ubRMSE between 0. 17 to 0. 33 cm3 cm-3 show better performances correspond to ground data. The highest correlations and the lowest RMSD value were observed in July 3rd and September 13th, respectively. The lowest RMSD and the highest correlation for dryland was observed on April 3rd. In July 3rd the highest correlation was observed in all land uses, and among them the highest correlation was observed in dryland.