JWSS - Journal of Water and Soil Science

In this study, the temporal and spatial variation of snow depth over the mountainous region of Zagros, in the western Iran, for the period 1979–2010 was investigated for the cold season when the probability of snow occurrences was high. For this purpose, daily gridded snow depth data relative to Era-Interim/land were retrieved from the European Centre for Medium-Range Weather Forecasts (ECMWF) and used for spatiotemporal analysis of snow in the region. Furthermore, monthly maximum, minimum and mean air temperature relative to the weather stations distributed over the region were also used to investigate the relationship between snow depth and air temperature variability in the region. In each grid point, the rate of temporal changes in the snow depth was estimated using the Sen’s slope estimator, while the modified Mann-Kendall Test was applied to assess if the change identified was statistically significant. The results showed that in almost all of the studied months, especially February and March, the snow depth was significantly reduced in the region, which was statistically significant at 5% significant level. Unlike the observed statistically significant decreasing trend in the depth snow in the region, a significant increase in the maximum, minimum and average temperature was observed for all the studied months and the stations. The result suggested that the observed decrease in the snow depth in the region was related to the increasing trend in the temperature during the study period, which could be attributed to the global warming and climate change.

Soil is one of the most important natural resources of countries in which erosion occurs. In this research, the effect of soil characteristics on the amount of erosion at the suborder level was studied. For this purpose, 77 soil samples (0-30 cm) were prepared and the parameters were determined in the laboratory. The semi-variograms of soil parameters and their spatial distribution maps were prepared with GS⁺ and GIS, respectively. The study area was divided into work units by combining land use and geology maps and water erosion was estimated at each unit by the EPM method. By drilling profiles in different parts of study area, soil suborders were determined by Soil Taxonomy and the average values of parameters in each suborder was estimated. The principle components analysis (PCA) was then used for data analysis. The results showed that three parameters of silt, organic carbon and electrical conductivity could account for 30.384% as the first main component; clay, sand and vegetation could explain 11.189% as the second main component; and slope and height covered 15.330% as the third main component; in total, 63.805% percent of erosion variation could be justified by three main components. The lowest and highest amounts of erosion (69.12 and 343.57 m³/km², respectively) were estimated in Xeralfs and Fluvents suborders. The erosion class of suborders at the study area was determined to be “few” and “medium”.

Benthos play an important role in the transmission of primary production and organic material (detritus) accumulation of the substrate in the water ecosystems to the higher levels of food chain. Also, they are used as biological indicators to evaluate the effect of pollutants caused by human activities on water ecosystems. To evaluate the benthic communities of Zayanderood Dam Lake, 4 sampling stations were selected on the lake; then, during the year 2014, seasonal sampling at each station was performed. The sampling was carried out by using the sediment sampler instrument with the dimensions of (20 cm × 20 cm). The average temperature of surface and deep water in the Zayanderood Dam Lake during the study was estimated to be 15.6 ± 2.4 and 8.9 ± 1.8°C, respectively. The average concentration of dissolved oxygen in the surface and deep water was varied from 10.3 ± 0.6 to 8.1 ± 0.7 mg/L, respectively. Totally, 2165 samples of benthos were collected and identified in the Zayanderood Dam Lake, belonging to 3 classes, 6 orders and 5 families. The maximum number of samples belonged to Tubifex, Naididae and Chironomidae genera. The dominant genus was Tubifex in all stages. According to this study, therefore, it seems that the structure of substrate, the amount of nutrients, grazing pressure and hydrostatic pressure are the most important environmental factors that can affect benthic community in the Zayanderood Dam Lake.

Water resources management depends on the precise assessment of water storage and access in each region, as well as environmental interactions of these resources. The man objective of this study was to delineate the potential zones of groundwater storage using FAHP. Mapping and assessment of it required maps of geomorphology, drainage, density, lineament density, slope and vegetation, which were initially prepared as the input layers in FAHP; the appropriate weights were attributed to them based on FAHP. Potential zones of ground water were classified into five classes of poor, average, good, very good and excellent. The number and density of available wells and springs in the study area dealt with the potential of the region for groundwater storage. So, ROC was used to assess the validation of results, considering spring points as signs of water resources. According to the results, classes of very good, good, average, weak, and very weak were ranked as the first to the last in terms of privilege order with an area of 37.7, 55, 40, 107, and 98.4 square kilometers, respectively.

Nowadays, with the increasing population in Iran, especially in arid and semi-arid areas, as a result of the growing importance of the quality of water resources, including groundwater, field experiments and many simulations have been conducted for the development of groundwater contamination through powerful and up- to- date software. However, in most cases, there is a tangible difference between the measured data in laboratories and the data produced with software; this is why the scientific validation and verification of the research results could be declined. In this study, in order to justify and correct these data, the calibration principle was used to minimize the error of testing and modeling. The purpose of this study was to validate and verify the SUTRA model for different scenarios of the solute transport in a sand tank with heterogeneous hydraulic conductivity to evaluate transverse dispersivity. In this study, coding was initially performed for the configuration and calibration of the SUTRA numerical model to simulate different scenarios of the solute transport in a heterogeneous sand Tank in the Hydraulic Laboratory of the University of Kassel, Germany, until acceptable values were obtained. Then the results were compared with the experimental model. In order to validate and verify the data obtained from the simulation with the SUTRA model, the relevant concentration profiles were compared with the results of the experimental model. The results of the numerical and laboratory models revealed the density effects by sinking the geometric center of the mixing zone for the low concentrations of salt, C₀ = 250 ppm. The results also showed that the width of the mixing zone between salt and fresh water depended on the amount of longitudinal dispersivity, especially the transverse dispersivity. By analyzing the results of simulation and experiment, it was observed that with increasing the velocity, reducing the amount of sinking and raising the input concentration, the time needed to achieve the steady dispersion was decreased.

One of the reasons for soil salinization is the accumulation of salts in it by transmission through water and wind. In order to investigate the phenomenon of transfer of salts with dust in the arid regions of the north of Yazd- Ardakan plain, field samples were taken using 32 MDCO sediments traps with uniform dispersion in an area of 20,000 hectares at some stage in 4 seasons of 2017. After washing the sediment collector with a liter of distilled water in the field and transferring the samples to the laboratory, for the quantitative analysis of saline dust, similar to measuring the Water Electrical Conductivity (EC_w), the Total Soluble Solids (TDS) were additionally measured through evaporation technique. The form and distribution of the dust particle size were additionally investigated using a Scanning Electron Microscope (SEM) tool. Within the qualitative examine of salts, effective cations and anions in salinity including Na⁺, K⁺, Ca⁺⁺, Mg⁺⁺, C1^-, HCO^-₃ and SO^-₄ were measured The results confirmed that, in general, the fallout was 11.1 g.m^-2 of soluble material with dust particles (13.28%) in the course of only 12 months. Particles with a diameter of 5 to 10 microns were the most frequent. Considering the high correlation between C1^- and Na⁺ in the spring, autumn and winter, due to the high correlation between Ca⁺⁺ and SO^-₄ in summer dust, sodium chloride (NaCl) and gypsum (CaSO₄) 2H₂O)), the most abundant composition of dust- containing salts could be expected in these seasons. By determining the percentage of solutes in the fallout dust, it was observed that the impact of the amount of the deposited salt from dust was slight and insignificant in the short time period; with the assumption of no change in the rate of subsidence, it was anticipated that it would explain the poor salinity in non- saline mass soils for up to 10 cm in 72 years. In general, the capability of airborne salt in increasing the soil salinity in the study area can be in long- term periods. Therefore, it is recommended to investigate other environmental effects of this phenomenon in order to identify its hazards.

In this study, the groundwater level (GWL) of the Sarab Qanbar region located in the south of Kermanshah, Iran, was estimated using the Wavelet- Self- Adaptive Extreme Learning Machine (WA- SAELM) model. An artificial intelligence method called “Self- Adaptive Extreme Learning Machine” and the “Wavelet transform” method were implemented for developing the numerical model. First, by using the autocorrelation function (ACF), the partial autocorrelation function (PACF) and the effective lags in estimating GWL, eight distinctive SAELM and WA- SAELM models were developed. Later, the values of the observational well were normalized for estimating GWL. Next, the most optimized mother wavelet was chosen for the modeling. By evaluating the results of SAELM and WA- SAELM, it was concluded that the WA- SAELM models could estimate the values of the objective function with higher accuracy. Then, the superior model was introduced, showing that it could be very accurate in forecasting the GWL. In the test mode, for example, the values of R (correlation coefficient), Main absolute error (MAE) and the NSC- Sutcliffe efficiency coefficient (NSC) for the superior model were calculated to be 0.995, 0.988 and 0.990, respectively. Furthermore, an uncertainty analysis was conducted for the numerical models, proving that the superior model had an underestimated performance.

Erosion under the conveying pipeline affected by river flow at the cross to rivers is one the important reasons for breaking the pipelines that can lead to leakage. While the mechanism of erosion under the conveying pipeline in steady flow has been studied by many researchers, studies have shown the importance of scouring research in flood times under unsteady conditions. So, this study has been concerned with the investigation of bed river erosion under the conveying pipeline at the conflict of river in unsteady condition. To achieve this aim, some effective hydrograph’s parameters were changed in different scenarios and the results were compared to the steady condition. The result showed the erosion’s ratio of unsteady condition to steady one was 34 to 69 percent. Also, the rise of flood hydrograph’s peak led to increasing depth erosion from 7% to 22%.

Synergistic relationships between mycorrhizal fungi (AMF) and organic compounds affect the mobility of the micronutrient elements in the rhizosphere and improve their bioavailability. In order to evaluate the effect of biochar and pruning waste compost of apple and grape trees, as well as AMF, on micronutrient bioavailability in calcareous soil at the wheat rhizosphere, an experiment was carried out in a completely randomized design under greenhouse conditions in a rhizobox study. Some factors including the organic sourses (pruning waste biochar, pruning waste compost and control), microbial inoculation (AMF and no inoculation) were considered. At the end of the growth period, Organic matter (OM) content and bioavailability of micronutrients including iron (Fe), Zinc (Zn), Copper (Cu) and Manganese (Mn) in the rhizosphere and their uptake by wheat plant were determined. The results indicated that OM, Fe, Zn, Mn and Cu were significantly increased in the rhizosphere soil under the influence of organic sources and mycorrhizal inoculation. Furthermore, biochar application in the mycorrhizal tratment resulted in 74.73% and 19.28% increase in Fe and Mn, as compared to non-inoculated conditions, in rhizosphere. The presence of mycorrhizal fungi increased the bioavailability of 94.66% and 29.54% Zn and Cu in the compost treatment, as compared to non-inoculated ones. Application of organic sources and mycorrhizal inoculation increased the micronutrient uptake and plant dry weight.

The estimation of reference crop evapotranspiration (ETo) is one the important factors in hydrological studies, irrigation planning, and water resources management. This study attempts to explore the possibility of predicting this key component using three different methods in the Sistan plain: Generalized Linear Models (GLM), Random Forest (RF) and Gradient Boosting Trees (GBT). The maximum and minimum temperature, mean temperature, maximum and minimum humidity, mean humidity, rainfall, sunshine hours, wind speed, and pan evaporation data were applied for years between 2009 to 2018. Using various networks, the ETo as output parameter was estimated for different scenarios including the combination of daily scale meteorological parameters. In order to evaluate the capabilities of different models, results were compared with the ETo calculated by FAO Penman-Monteith as the standard method. Among studied scenarios, M1 covering the maximum number of input parameters (10 parameters) showed the highest accuracy for GBT model, with the lowest RMSE (0.633) and MAE (0.451) and the maximum coefficient of regression (R = 0.993). Air temperature was found as the most sensitive parameters during sensitivity analysis of studied models. It indicated that accuracy and precision of temperature data can improve the results. Application of the GBT model could decrease the time consumed to run the model by 70%. Therefore, the GBT model is recommended for estimation of ETo in the Sistan plain.

One of the ways to increase water productivity in agriculture is the use of new irrigation systems; for the precise design of these systems, water quality assessment is needed. The purpose of this study was to study the groundwater quality of Khorramabad plain for the implementation of drip irrigation systems. The qualitative indices of EC, SAR, TDS, TH, Na and pH were related to the statistical years 2006-2012. In this research, the data were normalized first and it was determined that the data were abnormal; so, the logarithmic method was used for normalization. To evaluate the groundwater quality of the area, land use methods were used. Among different methods, the ordinary kriging interpolation method with the least root mean square error for all parameters was used. Quality zoning maps showed that in the north and southwest, EC and SAR concentrations were in poor condition in terms of qualitative classification. TDS had a concentration of more than 4000 milligramrels, and Na had a concentration of more than 15 milligrams / ltr. In these areas, TH with the concentration of more than 730 mg / l had the highest contamination; in the central area of the plain, there was a higher risk of carbonate sediments. LSI rates in the western regions were more than one, which included about 12% of the plain; there were restrictions on the implementation of droplet systems in these areas. The best quality for implementing these systems was located in the south-east of the plain, covering 19% of the plain. Finally, the integrated map of qualitative characteristics showed that the maximum concentration of qualitative characteristics was located in the northern, central and southern regions, which included 62.29% of the plain area.

Groundwater supplies a major portion of two basic human needs: drinking and agricultural water. Forecasting, monitoring, evaluating the performance and planning of this vital resource require modelling. The lag time of the groundwater level fluctuations against the rainfall is one of the essential data of the models. The purpose of the present study was to evaluate the piezometers behaviour by using the Pearson cross-correlation method between SPI and GRI indices in the Shiraz alluvial plain in order to determine the mentioned lag time. The results showed a similar behaviour for 86.2% of the piezometers. In 79.3% of the piezometers, groundwater level was declined one month after the rainfall event. The best correlation coefficient between the aforementioned indices was observed along the southwestern to the northeastern axis of the plain. The northern alluvial plain has a better correlation, as compared to the southern section because of the northern-southern slope of the plain. The central area of the plain had the highest correlation coefficient. The maximum correlation coefficients occurred at a time scale of 48 months. Also, since 2004, due to the decline in the atmospheric precipitation in the Shiraz plain, the SPI index has surpassed the drought level, although the trend has not been significant. However, the GRI does not follow this trend, showing a significant hydrological drought. The reason can be the disproportionate water extraction to recharge ratio in the alluvial aquifer of the plain.

Drought as a natural hazard is a gradual phenomenon, slowly affecting an area; it may last for many years and can have devastating effects on the natural environment and in human lives. Although drought forecasting plays an important role in the planning and management of water resource systems, the random nature of contributing factors contributing to the occurrence of and severity of droughts causes some difficulties in determination of the time when a drought begins or ends. The present research was planned to evaluate the capability of linear stochastic models, known as multiplicative Seasonal Autoregressive Integrated Moving Average (SARIMA) model, in the quantitative forecasting of drought in Isfahan province based on the Standardized Precipitation Index (SPI). To this end, the best SARIMA models were chosen for modelling the monthly rainfall data from 1990 to 2017 for every 10 synoptic stations in Isfahan province to forecast their monthly rainfall up to five years. The monthly time scale SPI values based on these predictions were used to assess the drought severity of different stations for the 2018- 2022 time period. The station results indicated a weak drought at the 2019- 2022 period for Isfahan, Kashan and Naeen, a severe drought in 2019 for Ardestan and Golpaygan, and a weak one in 2019 for the East of Isfahan, KabootarAbad and Shahreza stations. All other stations, except Golpayegan, Isfahan, Kashan and Naeen, faced a severe drought in 2018.

In order to investigate the effect of new deficit irrigation strategies on the quantitative characteristics and water productivity of two field grown corn cultivars, a split plot experiment was conducted as a randomized design in three replications. The irrigation treatments included full irrigation treatment (FI), static deficit irrigation (SDI), dynamic deficit irrigation (DDI), static partial root zone drying irrigation (SPRD), which received 75% of ET during the growth period, dynamic partial root zone drying irrigation (DPRD), which received 90% of ET in the first one- third of the growth period, 75% of ET in the second one- third of growth period, and 50% of ET in the last one- third of the growth period. The results showed that there were significant differences between irrigation strategies. The SDI, DDI, SPRD and DPRD irrigation treatments decreased the corn yield by 18%, 27%, 49% and 53%, as compared to FI, respectively. The results also showed that there were no significant differences between cultivars. Compared to FI, the SDI increased WP by 14%, but DDI, SPRD and DPRD decreased WP by 3%, 19% and 44%, respectively. According to economic analysis, irrigation optimum depth for the maximum net profit was obtained to be 858.5 mm. In general, the SDI strategy is recommended in the study area.

This study was conducted to evaluate AquaCrop for the simulation of potato yield and water use efficiency (WUE) under different water stress values at five levels (E0, E1, E2, E3 and E4, indicating 100, 85, 70, 50 and 30 percent of crop water needed, respectively) in three times during growth cycles (T1, T2, and T3, indicating 50, 100, and 150 days after sowing, respectively). The results showed that AquaCrop had overestimated and underestimated error for the simulation of yield and WUE, respectively. Based on RMSE and NRMSE values, the errors for yield and WUE were acceptable. The maximum and minimum error were also 0.3 (E1T3) and 3.15 (E1T2), respectively. The results obtained for WUE showed that the maximum and minimum were 0.53 (E3T2) and 0.03 (E4T2), respectively. The average differences between simulated and observed results (ADSO) of WUE for E1, E2, E3 and E4 were 0.24, 0.25, 0.19, and 0.44 ton.ha^-1, respectively; the ADSO of yield for T1, T2, and T3 was 0.19, 0.36, and 0.22 ton.ha^-1, respectively. Therefore, AquaCrop showed a high error for WUE when water stress was increased and crop was in its initial crop growth.

Water scarcity is the most important factor constraining agricultural production all over the world and water shortage in agriculture must be established to use the deficit irrigation. In order to study the effects of the regulated deficit irrigation and partial root zone drying on the growth traits of Rosmarinus Officinalis L., an experiment was conducted in the center of seed and plant production of IranShahr municipality in 2017. The experiment treatments were arranged as a randomized complete block design with three replications. The irrigation regimes consisted of full irrigation, regulated deficit (RDI₇₅ and RDI₅₅) and partial root zone drying irrigation (PRD₇₅ and PRD₅₅). The results showed that deficit irrigation at 75 and 55 percent of full irrigation resulted in saving 18.6 and 34.3 percent of water consumption, respectively. Comparison of full irrigation and PRD₇₅ showed that dry weight, height of plants and number of shoots per plant were decreased by 6.7, 14.3 and 12.1 percent, respectively. However, proper development of root in PRD₇₅ increased 12.9 percent of water productivity. Therefore, by considering the problems of water scarcity, it is possible to provide PRD₇₅ as a superior treatment and a suitable strategy to cope with the water crisis in order to move towards a sustainable agricultural system.

The soil engineering evaluation can be useful for construction and soil use. Aljarafe model has been used to evaluate the soil engineering properties by multiple regression techniques. In this research, Aljarafe model was used to predict the optimum moisture and plasticity index based on 184 series soils data of the Miandoab region. Based on all correlations between clay percentage and plasticity index, the optimum moisture proved to be highly significant (0.88 & 0.72). Also, Cation Exchange Capacity was significantly correlated (0.84 & 0.70) with the engineering properties. However, the correlation coefficients for the organic matter with optimum moisture and plasticity index were very low in the absolute amount. Application of the aljarafe model revealed that 50.3, 5.7, 0 and 44 % of the total extension could be classified as low, moderate and very high, respectively; on the other hand, based on the experiment data, 46, 13, 6 and 35 % could be classified as low, moderate, high and very high plasticity index classes, respectively. So, there was an overall agreement between the aljarafe model and Analytical Plasticity index maps, which was 80.4. Also, the coefficient of Determination, Root Mean Square Error (RMSE), Nash-Sutcliffe index (NES) and Geometric Mean Error Ratio (GMER) between calculated and experiment engendering properties was calculated to be 0.767, 9.3, 0.671 and 0.86 for the plasticity index and 0.739, 14.5, 0.543 and 0.73 for optimum moisture, respectively, were significant (P>5%). Finally, the aljarafe model provided a reliable estimate of engineering properties. 

 

Biocementation through microbial induced carbonate precipitation (MICP) is a recently developed new branch in geotechnical engineering that improves the mechanical properties of bio-treated soils. The potential application of MICP to handle problems such as liquefaction and erosion has been established; this technique offers an environmentally friendly, cost-effective and convenient alternative to traditional soil improvement approaches. Nevertheless, in spite of the widespread demonstration of the process at laboratory scale, few field and practical applications have been implemented to assess the efficiency of the biochemical process. Therefore, this paper presents a review of the utilization of MICP for soil improvement and discusses the treatment process including the key constituents involved and the main affecting factors, especially in field scale applications. The major contribution of this research is to identify the main parameters restricting the application of this method on site. Finally, technical and commercial progress in the industrial adoption of the technology and the main challenges that are ahead for the future research prior to real practical application are briefly discussed.
 
 

In general, engineering designs need to optimize the factors affecting the under-study phenomenon; however, this is often a costly and time-consuming process. In this regard, new methods have been developed to optimize with fewer tests; thus, they can make the whole process more affordable. In this study, Taguchi and Taguchi-GRA methods were used to design the geometric parameters of the protective spur dike in order to optimize their efficiency in reducing the scouring in a series of spur dikes. The results of both methods showed the optimal ratio of the length of the protective spur dike to the length of the first spur dike was 2.5 and the angle of the protective spur dike was 90 °. However, the ratio of the length of the protective spur dike to the length of the main spur dike in the Taguchi method was 0.8 and in the Taguchi-GRA method, it was 0.6. In addition, using variance analysis showed that the distance between the protective spur dike from the first spur dike, the protective spur dike angle, and the length of the protective spur dike were, respectively, the most effective on the performance of the protective spur dike. The results of this study, therefore, indicate that both methods are highly effective in optimization and, therefore, can be useful in the hydraulic engineer studies.