JWSS - Journal of Water and Soil Science

Digital soil mapping plays an important role in upgrading the knowledge of soil survey in line with the advances in the spatial data of infrastructure development. The main aim of this study was to provide a digital map of the soil family classes using the random forest (RF) models and boosting regression tree (BRT) in a semi-arid region of Ilam province. Environmental covariates were extracted from a digital elevation model with 30 m spatial resolution, using the SAGAGIS7.3 software. In this study area, 46 soil profiles were dug and sampled; after physico-chemical analysis, the soils were classified based on key to soil taxonomy (2014). In the studied area, three orders were recognized: Mollisols, Inceptisols, and Entisols. Based on the results of the environmental covariate data mining with variance inflation factor (VIF), some parameters including DEM, standard height and terrain ruggedness index were the most important variables. The best spatial prediction of soil classes belonged to Fine, carbonatic, thermic, Typic Haploxerolls. Also, the results showed that RF and BRT models had an overall accuracy and of 0.80, 0.64 and Kappa index 0.70, 0.55, respectively. Therefore, the RF method could serve as a reliable and accurate method to provide a reasonable prediction with a low sampling density.

The present study aimed to evaluate the growth and water use efficiencies of eight late-maturing corn hybrids in comparison to the common use of KSC704 and Maxima-FAO530 under different water-nitrogen management systems. Two irrigation regimes (based on 50% soil-water depletion as the normal irrigation and, on average. 16% less than normal as the deficit irrigation) and two nitrogen (N) application managements (3 and 16 split-application of 150 kg N from Urea, 45% N) were induced using the split-split plot experiment based on a completely randomized block design with four replications at Research Field of Isfahan University of Technology on 2017. The results showed that yield, forage and leaf area index were significantly (P<0.01) affected by the interaction of three studied factors (Irrigation × Nitrogen × Corn hybrid). For different corn hybrids, more water use efficiencies were achieved by deficit-irrigation regime and 16- split-applyication of N; in this regard, the SC719 hybrid had the highest value of 3.45 kg m^-3. Generally, the performances of the studied late maturing corn hybrids were higher than those of the control hybrids of SC704 and SC530 at this planting date, which could be improved by using the deficit-irrigation regime and more split-application of the N fertilizer.

One of the most important and complex processes in the watersheds is the identification and prediction of surface water changes. The main processes associated with surface water include precipitation, percolation, evapotranspiration and runoff. In this research, the semi-distributed model, SWAT, was used to simulate ground water and surface water in Semnan catchment in a monthly scale. A sensitivity analysis was perfomed to evaluate and demonstrate the influence of the model parameters on the four major components of water budget including surface runoff, lateral flow, groundwater and evapotranspiration. River discharge data from 2004 to 2014 were used for the calibration and those of 2014 to 2016 were applied for the validation. The results of sensitivity analysis showed that the most sensitive parameters were: SoL_K(Saturated hydraulic conductivity), CH_K2 (Effective hydraulic conductivity in main channel), RCHRG_DP(Deep aquifer percolation fraction and CN2 (Moisture condition II curve number). The simulation accuracy using Nash-Sutcliffe and coefficient of determination for Shahrmirzad, Darjazin, and Haji Abad hydrometric stations was about 0.60 to 0.80 and 0.80 to 0.90 for the calibration and validation period, respectively, showing a good performance in the simulation of river flow. According to the water balance results, about 87.6% of the total inflow into the watershed was actual evapotranspiration, 3% was surface run off, 3% was percolation, and the rest was related to the soil moisture storage.

Estimating the ecological water footprint and the virtual water trade in different agricultural crops in arid and semi-arid regions can help better manage the limited water resources.This research calculated temporal and spatial ecological water footprint of rain-fed and irrigated almond production in national and provincial scale using during 2008 to 2014. The results show that annual average water footprint in rainfed almond is 9.2 m³/kg, which the share of green and grey water is 72% and 28%, respectively which Ilam and Kohgiloyeh & Boyerahmad have a largest share in green water footprint with 91% and 90%, respectively. In adition to, in irrigated almond, the annual average water footprint is 11.4 m³/kg, which the share of green, blue and grey water is 0.19%, 71% and 10%, respectively. Sistan & Balouchestan, Khuzestana and Hormozgan have the highest share in blue water footprint. The total volume of water footprint of rain-fed and irrigated almond production is 1923 and 8242 MCM, respectively. Also, results show that about 92 percent of the total volume virtual water (equivalent to 9343 MCM per year) in almond production, has been exported to other countries through the virtual water trade.

Given the fact that the DRASTIC index is ineffective in addressing the saltwater uprising issue in coastal plains, in the present study, three factors including land use, distance to shoreline, and differences between groundwater and sea level were added to the DRASTIC index. The proposed modification to DRASTIC was validated using the measured electrical conductivity (EC) data gathered from groundwater monitoring wells throughout the Talesh Plain. The results showed that the coefficient of correlation between the map of EC over the region and the modified DRASTIC was 0.52, while for the original DRASTIC, the coefficient was 0.45, thereby implying a stronger relationship between EC and the modified DRASTIC in the Talesh Plain. Sensitivity analysis also showed that DRASTIC and the modified DRASTIC were the most sensitive to, respectively, depth to groundwater (D) and land use (Lu). According to the single-parameter sensitivity analysis results, depth to water table and net recharge were the most effective parameters in DRASTIC,  whereas the modified DRASTIC was the most sensitive to land use and depth to groundwater. It could be concluded that modifying the DRASTIC index would result in decreasing the area of very high and high vulnerable classes, and the area classified as low and moderate vulnerable could be increased.

Today, one of the biggest challenges facing the world is the lack of water, especially in the agricultural sector. In this research, we investigated the effects of irrigation method and deficit irrigation with the urban refined effluent on biomass, grain yield, yield components and water use efficiency in single grain crosses 704 maize. This research was carried out in a randomized complete block design with two irrigation systems (furrow irrigation (F) and drip irrigation (T)) and three levels of deficit irrigation treatments of 100 (D₁), 75 (D₂) and 55 (D₃) percent of water requirements in three replications, in 2017, at the collage of Abourihan Research field, University of Tehran, in Pakdasht County. The results showed that the highest yield of biomass was 2.426 Kg m^-2 for full drip irrigation treatments; also, there was no significant difference between D₁ and D₂ treatments. The highest grain yield was 1.240 kg m^-2 for the complete drip irrigation treatment. The highest biomass water use efficiency was obtained for the treatment of 75% drip irrigation, which was equal to 5.3 kg per cubic meter of water. Therefore, a drip irrigation system with 75% water requirement is optimal and could be recommended.

The interaction of population growth, technological improvement and climate change have impacted severely on agricultural and environmental sustainability. In Iran, conventional tillage practice has resulted in soil erosion and loss of soil organic matter. In this regard, Conservation Agriculture (CA) forms part of this alternative paradigm to agricultural production systems approaches and can be regarded as a means to enhancing food productivity, reducing poverty, and mitigating the consequences of climate change in rural households. The objectives of this study were to examine the determinants and impacts of CA technology on wheat yield, poverty gap and water use. To this end, an endogenous switching regression (ESR) model was employed to estimate the impacts of CA technology on continuous variables such as wheat yield, poverty gap and water use. A sample of 260 farmers from Zarghan district was selected for interview collection of necessary farm level data. The results indicated that in the select equation of ESR model, ten coefficients (out of 12) are significant at the 5% level or higher. Knowledge of soil quality, access to credit, access to information, education, farm size, ownership of machinery, participation in agricultural extension activities and farmer’ perception have positive and significant effects on the probability of adopting CA. In contrast, variables such as the distance to shopping center and number of land parcels have negative and significant influence on adoption. Also, the results of ESR model and counterfactual analysis showed that wheat yield would increase by 1.05 tons and poverty gap and water use would decrease by 20% and 910 cubic meters per hectare respectively if farmers adopt CA technology.

In the present study, the effects of different levels of irrigation, organic mulch and planting method on the mungbean yield in Badjgah were investigated. The experimental plan in the first year was full randomized block, while in the second year, it was full randomized split-split plot block design, in three repetitions. The results showed that in the FI treatments, the yield was increased up to 2% for the first year and 5% for the second year by changing the planting method from on over-ridge planting method to the in-furrow planting one. Also, the results of the first year showed that there was no significant difference between the yield in the fully-irrigated treatments without mulch and the treatment with mulch and 0.75 FI. The amount of the irrigation water could be decreased up to 25% by adding organic mulch in both planting methods, as compared to the fully-irrigated treatments without mulch. The maximum water productivity equal to 0.4 kg/m³ was observed in 0.5 FI, in-furrow planting method with mulch treatment. It can be, therefore, concluded that the water productivity may be maximized with the application of both deficit irrigation and mulching strategies.

Rainfall may be considered as the most important source of drinking water and watering land in different areas all over the world. Therefore, simulation and estimation of the hydrological phenomenon is of paramount importance. In this study, for the first time, the long-term rainfall in Rasht city was simulated using an optimum hybrid artificial intelligence (AI) model over a 62 year period from 1956 to 2017. The gene expression programming (GEP) and wavelet transform (WT) were combined to develop the hybrid AI model (WGEP). Firstly, the most effective lags of time series data were identified by means of the autocorrelation function (ACF); then eight various GEP and WGEP models were defined. Next, the GEP models were analyzed and the superior GEP model as well as the most influenced lags was detected. For instance, the variance accounting for (VAF), correlation coefficient (R) and scatter index (SI) for the superior GEP model was calculated to be 0.765, 0.508 and 0.709, respectively. Additionally, lags (t-1), (t-2), (t-3) and (t-12) were the most influenced. Then, the different mother wavelets were examined, indicating that the demy mother wavelet was the most optimal one. Moreover, analyzing the numerical simulations showed that the mother wavelet enhanced the performance of the GEP model significantly. For example, the VAF index for the superior WGEP model was increased almost three times after using the mother wavelet. Furthermore, the R and MARE statistical indices for the WGEP model were computed to be 0.935 and 0.862, respectively.

The main purpose of the study is the operational simulation of main irrigation canal and evaluation of water delivery and distribution locally, regionally and overall using adequacy, efficiency, and equity indicators and “Desirability of water delivery and distribution” indicator. To achieve this goal, the hydrodynamic model of Roodasht irrigation network’s main canal was developed. The results of the calibration and validation of the hydrodynamic model showed that the two processes were satisfactory. All available scenarios including normal, water shortages and fluctuations were considered for water delivery and distribution in different conditions. In the local assessment, the adequacy varied from 7 to 85%, and the efficiency in all scenarios was 100%. The adequacy, efficiency, and equity indicators in the regional evaluation varied from 6 to 89, 91 to 100, and 13 to 46%, respectively. The overall evaluation of the canal showed that the most desirable situation is related to a harsh fluctuation increasing with the adequacy, equity and efficiency indicators equal to 82, 23 and 91%, respectively. Calculation of the “Desirability of water delivery and distribution” indicator showed poor performance in all operational scenarios except harsh fluctuation scenario with 82% of which, the canal performance was estimated in fair level.

Public health of common waters in protecting the human's health is considered as "human delinquent" and environmental and natural health as "green offender" (silent offender) due to the terrestrial nature and the lack of the monopoly of works; so, the consequences of violating it in the territory of a particular state are of particular importance in the international public law. Therefore, protection of the harm caused by the breach of the public health of common waters is imperative by international institutions and States members of the international community. The supportive policy is a branch of public policy that "puts" various legal protections from the perpetrators of the violations of norms and regulations "in the form of coherent policies using its principal principles. These principles are a set of doctrines and coherent strategies that determine the policy and consequently, the way in which laws and regulations are imposed; as with the qualitative measure, it provides for the monitoring of rules and regulations. To make the present study, a review of the principles that underlie the principles of public health policy in international treaties and procedures is presented. The principles outlined in these sources are categorized into three categories: "justice-oriented", "cooperative-oriented" and "fair-minded". These principles can be used in protecting Iranian water health rights.

The occurrence of wind erosion and the spread of dust particles can be regarded as one of the most important and threatening environmental factors. Climate change and the frequency of droughts have played an important role in exacerbating or weakening these events. The primary objective of the present study was to investigate the trend of changes in four important climatic elements (precipitation, temperature, wind speed and relative humidity) and dust storm index (DSI) in Qazvin city using the Mann-Kendall pre-whitened test and to determine the relationship between them based on the multiple linear regression method. Assessment of the meteorological drought status based on two standardized precipitation index and standardized precipitation, as well as the evapotranspiration index and analysis of their effect on activity level of dust events, was the other objective of this study in the study area. For this purpose, after preparing and processing the climatic data and calculating the dust storm index, the trend of changes and the relationship between climatic parameters and dust events were investigated. The results showed that the changes of trend in the annual precipitation and relative humidity in Qazvin city were increasing, while the trend of annual changes in the wind speed and the mean air temperature was a decreasing one. Investigation of the monthly changes in the dust events also showed that there was a sharp decrease in the occurrence of wind erosion and the spread of domestic dust particles only in July. On a seasonal scale, with the exception of winter that has been reported without trends, in other seasons, the intensity of these events was significantly reduced. The effect of the meteorological drought on wind erosion was estimated to be 11% at the confidence level of 99%. In general, these findings indicate a decreasing trend of land degradation and desertification caused by wind erosion in Qazvin.

Agricultural water management studies require accurate information on actual evapotranspiration. This information must have sufficient spatial detail to allow analysis on the farm or basin level. The methods used to estimate evapotranspiration are grouped into two main groups, which include direct methods and indirect or computational methods. Basics of the indirect methods are based on the relationship between meteorological parameters, which impedes the use of these data with a lack or impairment. On the other hand, this information is a point specific to meteorological stations, and their regional estimates are another problem of uncertainty of their own. To this end, the use of remote sensing technology can be a suitable approach to address these constraints. Real evapotranspiration can be estimated by satellite imagery that has short and long wavelengths and is estimated using surface energy equations. Examples of such algorithms include SEBAL, METRIC, SEBS. Among the above mentioned algorithms, SEBAL and SEBS have been used. Among the factors of superiority of the SEBAL and SEBS algorithms, in comparison with other remote sensing algorithms, is a satellite imagery analysis algorithm based on physical principles and uses satellite simulation and requires minimum meteorological information from ground measurements or air models. 

Selection of the appropriate distribution function and estimation of its parameters are two fundamental steps in the accurate estimation of flood magnitude. This study relied on the concept of optimization by meta heuristic algorithms to improve the results obtained from the conventional methods of parameter estimation, such as maximum likelihood (ML), moments (MOM) and probability weighted moments (PWM) methods. More specifically, this study aimed to improve flood frequency analysis using the Artificial Bee Colony algorithm (ABC). The overall performance of this algorithm was compared to the conventional methods by employing goodness of fit statistics, correlation coefficient (CC), coefficient of efficiency (CE) and root mean square error (RMSE). The study area, Babolrood catchment located in southern bank of Caspian Sea, has been subjected to annual flooding events. A total of 6 hydrometry stations in the study area were delineated and their data were used in the analysis of 6 distribution functions of Normal, Gumbel, Gamma, Pearson Type 3, General Extreme Value and General Logistic. This analysis indicated that Gamma and Pearson Type 3 were the most appropriate distribution functions for flood appraisal in the study area, according to the ABC and conventional methods, respectively. Also, the results showed that ABC outperformed ML, MOM and PWM; so, Gamma could be recommended as the most reliable distribution function for flood frequency analysis in the study area.

Wind erosion is known as one of the most important land degradation aspects, particularly in arid and semi-arid regions. Soil properties, by affecting soil erodibility, can control the wind erosion rate. The aim of this study was to attribute the soil physical and chemical properties to the wind erosion rate for the purpose of determining the most important property. To this aim, wind erosion rates were measured in-situ at 60 points of Kerman province using a portable wind tunnel facility. The results indicated that wind erosion rates varied from 0.03 g m^-2 min^-1 to 3.41 g m^-2 min^-1. Threshold wind velocity decreased wind erosion rate following a power function (R²=0.81, P<0.001). Clay and silt particles, shear strength, mean weight diameter (MWD), surface gravel, dry stable aggregates (DSA<0.25mm), soil organic carbon (SOC), calcium carbonate equivalent (CCE) and the concentrations of the soluble Ca²⁺, K⁺ and Mg²⁺ were inversely proportional to the wind erosion rates following nonlinear functions. On the other hand, Wind erosion was significantly enhanced with increasing the sand fraction, soluble Na⁺, electrical conductivity (EC) and sodium adsorption ratio (SAR). According to the final results, among the studied soil properties, SAR and MWD were s the most effective properties controlling wind erosion in the soils of Kerman province. Therefore, it is recommended to consider suitable conservation practices in order to prevent the sodification and degradation of arid soils.

The objective of this study was to investigate the impact of land use change (forest and rangelands to agriculture) on some micromorphological indices of soil quality in part of Rakat watershed, southwest of Iran. Accordingly, intact soil samples from 0-15 and 15-30 cm depths were collected from the above-mentioned land uses, and microstructure, type and abundance of voids, redoximorphic features, and humic substances were compared. The results showed that in the natural forest use, most of the voids are in the form of macropores, whereas after their conversion to agriculture, these types of voids have little development. In natural rangelands uses, voids were mainly oriented channels and of macropore type, but after switching from pasture to agriculture, they were mainly of vughy type. The results showed that natural forests (27.73%) and natural grasslands (22.28%) had more abundance of voids than forest to agriculture (19.01%) and grassland to agriculture (18.62%) land uses. In both natural forests and pasture land uses, various types of iron and manganese nodules, coatings, hypo-coatings, and quasi-coatings were significantly higher than agricultural land uses.

In this study, we used the ARIMA time series model, the fuzzy-neural inference network, multi-layer perceptron artificial neural network, and ARIMA-ANN, ARIMA-ANFIS hybrid models for the modeling and prediction of the daily electrical conductivity parameter of daily teleZang hydrometric station over the statistical period of 49 years. For this purpose, the daily data for the 1996-2004 period were used for model training and data for the 1996-2006 period were applied for testing. In order to verify the validity of the fitted ARIMA models, the residual autocorrelation and partial autocorrelation functions and Port Manteau statistics were used. PMI algorithm were   then used to model and predict electrical conductivity for selecting the effective input parameter of the neural fuzzy inference network and the artificial neural network. The daily parameters of magnesium (with two days delay) and sodium (with one day delay), heat (with one day delay), flow rate (with two months delay), and acidity (with one day delay) were obtained with the lowest values of Akaike and highest values of hempel statistics as the input of the neural fuzzy inference network and the artificial neural network for modelling daily electric conductivity predictions; then predictions were made. Also, models evaluation criteria confirmed the superiority of the ARIMA-ANFIS hybrid model with the trapezoidal membership function and with two membership numbers, as compared to other models with a coefficient of determination of 0.86 and the root mean square of 29 dS / m. Also, the Arima model had the weakest performance. So, it could be applied to modeling and forecasting the daily quality parameter of the tele Zang hydrometer station.

Today, the use of organic wastes as fertilizers to improve the physical, chemical and biological properties of soil is common. In this study, to investigate the effect of the sewage sludge on the growth and concentration of chlorophyll, nitrogen, phosphorus and potassium in quinoa plant, a factorial experiment was conducted based on a completely randomized design with three replications in a calcareous soil with electrical conductivity of 13.1 dS m^-1. Treatments included three genotypes of quinoa (Red carina, Titicaca, Q29) and three levels of sewage sludge (0, 20 and 40 t ha^-1). The results showed that the effects of the quinoa genotype, different levels of sewage sludge and the interaction of treatments on the root dry weight, shoot P concentration and chlorophyll concentration were significant. Also, the sewage sludge had a significant effect on the shoot length, shoot dry weight and shoot nitrogen concentration. By increasing the level of the sewage sludge, root length, shoot length, shoot dry weight and shoot N concentration were increased, on average, by 44.7 %, 48.8%, 42.0% and 46.6%, respectively. Also, application of 40 t ha^-1 sewage sludge significantly increased the chlorophyll concentration and shoot P concentration in Q29 and Titicaca genotypes. According to the results of this study, application of sewage sludge can increase the growth of quinoa by improving its nutrition.

In determining the allocation of water resources, the probable conditions of water resources and water demands are considered as the water allocation scenarios in the basin scale. Then, these scenarios are evaluated in the context of integrated water resources management and from the perspective of sustainable development indicators. The best scenario is selected in order to determine the water allocations. In these evaluations, there are spatial distributions and their interactions are simultaneously the key charaterictics in the decision matrix. These features are not often considered in the evaluation process. In the present study, distributed indicators and simple and integrated multi-criteria evaluation models, including ANP and CP methods, were used to evaluate the water allocation scenarios in the Aras Basin. The results showed that modeling of the spatial distribution and interactions of water allocation impacts was not possible through any of the simple multi-criteria evaluation methods. Simplifying and discarding one or two key features in the evaluation process can lead to significant uncertainties on rankings with a Spearman coefficient of -0.1. By implementing the integrated spatial decision-making approach and applying two features simultaneously, the fourth scenario was ranked first. The proposed approach was compared with the individual models, showing more accurate, with the correlation coefficients of 0.5, 0.6 and 0.7.

The scour around the bridge piers is one of the main causes of bridge failure and the extraction of aggregates may aggravate this phenomenon. The present study comprehensively investigated the scour around the groups of bridge piers in the presence of aggregate extraction pits, using different discharges. The bridge piers roughened by gravel had been compared with the simple bridge piers; so, the results showed that the roughening caused the reduction of the scour depth. Scour depth change rate led to an increase in the equilibrium time. The results also showed that the reduction of the scour depth at the downstream groups of piers was more than that in the upstream. For the lowest discharge, the aggregate extraction pits had a considerable effect on the scour depth difference for the groups of piers in the downstream and upstream. On the other hand, the effects were decreased when the rate of discharge was increased. The experimental results obtained by the rough surface models showed that as the discharge was increased, the local scour was increased too; at the same time, the bed profile was posed at the low level. Generally, the scour depth of the groups of piers in the downstream of the extraction pit was more than that in the upstream. The results of the current research, therefore, demonstrated that the surface of the bridge pier roughened by gravel reduced the scour depth.