JWSS - Journal of Water and Soil Science

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.

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.

Optimal use of water resources seem to be necessary due to climate change and the recent drought conditions. One of the most important and effective management strategies is increasing water productivity in agriculture. Irrigation method and the use of different levels of nitrogen fertilizer are the effective factors in increasing the water productivity. Therefore, this study was conducted to investigate the effect of the irrigation method and nitrogen fertilizer on the harvest index and water productivity of two wheat cultivars with 36 treatments as a split-split plot based on a completely randomized design with three replications in the research farm of Natural Resources and Agricultural Research Center of Kashmar, during the 2018-2019 time period. The treatments were two irrigation methods including end blocked border and drip irrigation (tape) as  the main plots, three levels of the nitrogen fertilizer from urea source including 0, 50 and 100 kg/ha as the  sub plots and two cultivars of wheat including Pishgam and Sirvan as the sub-sub plots. The results showed that by changing the border irrigation method to the drip irrigation (tape) method, the harvest index and water productivity were increasesignificantly. The results also showed that grain yield and its components, including harvest index and water productivity, had no significant difference in 50 and 100 kg/ha nitrogen levels. On the other hand, grain yield and its components, harvest index and water productivity, were significantly higher in the Sirvan cultivar rather than the Pishgam one (P<0.01). According to the results obtained from this study, the drip irrigation method, 50 kg/ha nitrogen level and Sirvan cultivar could be recommended for the study region. 

In order to study and evaluate the drought stress indices in surface irrigation by furrow method on grain yield, the yield components and water use efficiency, an experiment was conducted at Behbahan Agricultural Research Station in 2014-16. The experiment was conducted as a split plot in a randomized complete block design with 4 replications. Irrigation at two levels (irrigation after 100 and 200 mm evaporation from Class A pan, respectively) was evaluated as the main factor and corn cultivar was considered at 6 levels as the sub-factor. Comparison of the  mean water use efficiency in irrigation and cultivar interactions showed 100 mm evaporation from Class A pan and cultivars V4 (PH1), V5 (PH3) and V2 (SC Mobin) were ranked the first and foremost, respectively, with the  yields of 1.353, 1.299 and 1.296 kg of corn per kg of water consumed, respectively. The mean water consumed in 2014 of the experiment in 100 and 200 mm evaporation from Class A pan was 521.2 and 462.4 mm, respectively. Pearson correlation coefficient results  also showed that with increasing the  yield components, such as the  number of grains per row and number of rows, the  1000-grain weight was  increased due to  the highly significant correlation coefficient of 1000-grain weight with grain yield (r = 0.8776).  Consequently, grain yield was also increased. The highest values of SSI, STI, MP, TOL, GMP HM and YI indices were calculated in V4 (PH1). The higher values of the above indices in cultivar V4 (PH1) than other cultivars caused this treatment to be introduced as the superior one. The decreasing trend of corn yield, which was caused by water deficit stress, increased SSI, STI, MP, TOL, GMP and YI indices, while it decreased corn yield, leading to incremental changes in the YSI indices.

Due to drought and climate change, estimation and prediction of rainfall is quite important in various areas all over the world. In this study, a novel artificial intelligence (AI) technique (WGEP) was developed to model long-term rainfall (67 years period) in Anzali city for the first time. This model was combined using Wavelet Transform (WT) and Gene Expression Programming (GEP) model. Firstly, the most optimized member of wavelet families was chosen. Then, by analyzing the numerical models, the most accurate linking function and fitness function were selected for the GEP model. Next, using the autocorrelation function (ACF), the partial autocorrelation function (PACF) and different lags, 15 WGEP models were introduced. The GEP models were trained, tested and validated in 37, 20- and 10-years periods, respectively. Also, using sensitivity analysis, the superior model and the most effective lags for estimating long-term rainfall were identified. The superior model estimated the target function with high accuracy. For instance, correlation coefficient and scatter index for this model were 0.946 and 0.310, respectively. Additionally, lags 1, 2, 4 and 12 were proposed as the most effective lags for simulating rainfall using hybrid model. Furthermore, results of the superior hybrid model were compared with GEP model that the hybrid model had more accuracy.

Water allocation needs to adhere to the principles of efficiency, equity, and sustainability, but, equity usually is less considered. Foumanat irrigation area with five command areas is one of the three areas of Sefidroud irrigation and drainage network that more than 90% of it is covered by paddy fields. Since water plays a key role in paddy fields, the lack of uniform distribution of water resources throughout the irrigation area during the rice cultivation period causes irrigation water scarcity and severe damage to some irrigation areas. In this study, the equity of groundwater withdrawal and the received surface water from Sefidroud irrigation and drainage canals according to the shared water resources among Foumanat’s command areas were evaluated using the Gini coefficient. Therefore, a water allocation optimization model was developed to maximize the equity in the allocation of groundwater and surface water of canals according to the minimum current economic benefit in the command areas. The results showed that in optimum conditions, the equity of groundwater and surface water resources allocation was increased by 46.3% and 43.7%, respectively. The evaluation of the optimal allocation of available water resources also showed that the amounts of groundwater withdrawal and the received surface water from canals are distributed equally among command areas.

To investigate and evaluate the effects of different levels of drip irrigation on grain yield and yield components, oil yield, seed oil percentage, and seed water use efficiency, an experiment was performed at Behbahan Agricultural Research Station during two crop years 2018-19 and 2019-20. The experiment was conducted in split plots based on a randomized complete block design with 3 replications. The amount of water in tape drip irrigation was compared at four levels of 40, 60, 80, and 100% water requirement in main plots and two sesame cultivars Local of Behbahan and Shevin in subplots from the beginning of flowering. Comparison of mean interaction effects of irrigation levels and cultivars showed that the treatment of 100% water requirement in the Behbahan local cultivar with the yield of 1218.0 kg/ha was ranked first and foremost. Water consumption in the highest treatment (100% water requirement and Behbahan local cultivar) was calculated to be 5389.4 m³/ha. Treatments of 100% and 80% of water requirement in superior cultivar (local Behbahan) with water use efficiency of 0.226 and 0.210 kg/m³ had no significant difference, respectively, and were in the first place. Pearson correlation coefficient calculated for the measured traits showed that the highest correlation of water volume was calculated (r = 0.9271) with the weight of one thousand seeds. Significant correlations of water volume with grain yield and yield components indicated that sesame was susceptible to drought stress and attention to optimal water management in sesame cultivation. Therefore, decreasing the volume of water consumed and consequently drought stress in sesame reduced yield and yield components.

In the present study, CanESM2 climate change model and stormwater management model (SWMM) were employed to investigate the climate change effects on the quantity and quality of urban runoff in a part of Karaj watershed, Alborz Province. The base period (1985-2005) and future period (2020-2040) are considered for this purpose. Based on the existing main and lateral drainage system and to be more accurate, the watershed was divided into 37 sub-watersheds by ArcGIS software. To simulate rainfall-runoff, the intensity-duration-frequency (IDF) curve has been prepared for a 2-hour duration and 10-year return period, for the base period and RCP2.6 and RCP8.5 climate change scenarios based on the obtained precipitation data from Karaj synoptic station. Results showed that mean 24-hour precipitation values in RCP2.6 and RCP8.5 scenarios will increase by 21% and 11%, respectively, and maximum 24-hour precipitation values will decrease by 17% and 23%, respectively, as compared to the observed values in the base period. Also, based on the results of quantitative and qualitative runoff modeling in the study watershed, and according to the outflow hydrograph in the RCP2.6 and RCP8.5 scenarios, the outlet runoff discharge will decrease by 5.8% and 7.1%, respectively. Also, the flooded areas in the watershed will decrease by 13% and 15.28%, respectively. The concentration of pollutants in the RCP2.6 and RCP8.5 scenarios, compared to the base period, including total suspended solids (TSS), will increase by 7.48% and 9.24%, total nitrogen (TN) will increase by 6.93% and 8.48%, and lead (Pb) will increase by 7.32% and 8.91%, respectively.

The present study is investigated the earth dam stability during drawdown based on both numerical and experimental aspects. To validate the numerical model, a model was performed experimentally. Some soil mechanic tests were carried out through the hydraulic experiments to attain the usage factors of the numerical investigation. To investigate the effect of hydraulic conductivity on the rapid drop of water level and the use of hydraulic parameters of materials, seepage flow in the model was modeled by seep/w software. The input information to the software including hydraulic conductivity and water volume were measured by performing a constant load test and using a disc penetration meter, respectively. After validation of hydraulic conductivity with the experimental model, the results were compared with observed data. Comparison between numerical and laboratory discharge illustrated that the numerical model with laboratory model is well confirmed. In addition, saturated and unsaturated simulations demonstrated that the unsaturated model is highly consistent with the experimental model. It is assumed that due to the drawdown conditions, unsaturated models can achieve high accuracy for simulating the flow through a homogeneous earth dam.

In this study, the Drainmod-S model was used to vary soil salt concentration and the effect of underground drainage on the amount of leaching in a physical model (large lysimeter). A soil extractor was installed at depths of 40, 50, and 70 cm at a distance of 35 cm from the drainage to measure the salinity of the soil solution. In this study, three scenarios were applied including salinity profiles under conventional conditions (mid-season and end-season drainage), soil salinity profiles under different drainage conditions, and prior scenarios with saline irrigation. The second and third scenarios were applied in four drainage stages, respectively. These stages include transplanting and mid-season drainage (days 15 to 20), mid-season drainage (days 35 to 40), mid-season and end-season drainage (days 55 to 60), and end-season drainage (days 75 to 80). The results showed that after simulating the total solute concentration overtime at a depth of 40 cm and comparing it with the measured values, the coefficient of determination (R²) was 0.77 indicating an acceptable Drainmod-S model simulation. This parameter for simulating solute concentration at 50 and 70 cm depth was 0.76 and 0.75, respectively. The mean absolute error parameter (MAE) value was also negligible.

To study the soil-landscape change in the Chaldoran region, 9 representative soil profiles were studied in 5 dominant geomorphic units of the study area including piedmont plain, mantled pediment, alluvial fan, plain, and flood plain. The results showed that the accumulation of pedogenic carbonate in some soils was concretion and light in color. In control soils in the piedmont plain (profile 5 and 7), mantled pediment (profile 6), and flood plain (profile 8) clay transferred from the surface horizons and accumulated in the lower horizon, due to relatively good rainfall in the region and distinct dry and wet seasons has led to the formation of argillic horizons along with the formation of crust on the surfaces of aggregates and building units and has formed the Alfisoils order. Mineralogical results showed the presence of chlorite, illite, kaolinite, and smectite minerals. According to the evidence, illite, chlorite, and kaolinite minerals were inherited and smectite minerals were formed due to weathering and evolution of illite, chlorite, or palygorskite minerals. Also, the results of the CIA index in the region indicated that the soils of the region are in the stage of weak to moderate weathering. In general, the results indicated the critical role of drainage, land use, and parent materials in the soils of the study area.

Surface runoff is one of the most significant components of the water cycle, which increases soil erosion and sediment transportation in rivers and decreases the water quality of rivers. Therefore, accurate prediction of hydrological response of watersheds is one of the important steps in regional planning and management plans. In this regard, the rainfall-runoff modeling helps hydrological researchers, especially in water engineering sciences.  The present study was conducted to analyze the rainfall-runoff simulation in the Gorganrood watershed located in northeastern Iran using AWBM, Sacramento, SimHyd, SMAR, and Tank models. Daily rainfall, daily evapotranspiration, and daily runoff of seven hydrometric stations in the period of 1970-2010 and 2011-2015 were used for calibration and validation, respectively. The automated calibration process was performed using genetic evolutionary search algorithms and SCE-UA methods, using Nash Sutcliffe Efficiency (NSE) and root mean of square error (RMSE) evaluation criteria. The results indicated that the SimHyd model with NSE of 0.66, TANK model using Genetic Algorithm and SCE-UA methods with NSE of 0.67 and 0.66, and Sacramento model using genetic algorithm and SCE-UA methods with NSE of 0.52 and 0.55 have the best performance in the validation period.

Splash (raindrop) erosion plays an significant role in soil loss, especially in arid and semi-arid regions with poor vegetation. In this paper, by analyzing the pattern of rainfalls that occurred during 26 years in four basins located in Semnan County, their effect on the pattern of eroded sediments from the basin was investigated. Sedimentary layers from the sampling of retarding reservoir sediments in 2017 were related to the corresponding precipitations. Due to the occurrence of the highest amount of rainfall in each quarter of rainfall, rainfall hyetographs were divided into four categories. Cumulative precipitation curves with similar quartiles were drawn in one shape and compared with sediment curves and vice versa taking into account the physical characteristics of the basin. The results showed that the Aliabad basin (with less slope and more elongation) with an effective quarter of type 3 had the highest similarity in precipitation and sediment patterns. Also, the Western Soldereh basin (with the highest slope and the least elongation) with an effective quarter of type 2 had the least similarity in precipitation and sediment patterns. The results indicate the vital role of rainfall patterns on the resulting sediment patterns, which show up to 85% similarity.

The objective of the current study was to zone flood probability in the Marzdaran watershed. Since the allocated budget for management work is limited and it is not possible to carry out operations in the whole area, having a map that has prioritized different areas in terms of the probability of flood occurrence will be very useful and necessary. A well-known data mining model namely MaxEnt (ME) is applied due to its robust computational algorithm. Flood inventories are gathered through several field surveys using local information and available organizational resources, and the corresponding map is created in the geographic information system. The twelve predisposing variables are selected and the corresponding maps are generated in the geographic information system by reviewing several studies. The area under the curve (ROC) is used to evaluate the modeling results. Then, the most prone areas of flood occurrence which are prioritized for management operations are identified based on the prepared map. Based on the results, about 100 km2 of the study area is identified as the most prone area for management operations. The results showed that the accuracy of the maximum entropy model is 98% in the training phase and 95% in the validation phase. The distance from the river, drainage density, and topographic wetness index are identified as the most effective factors in the occurrence of floods, respectively.

In the present paper, crop pattern criteria have been evaluated relying on sustainable development to increase agricultural water productivity. Seven criteria were selected as the main environmental and economic criteria and were prioritized and reviewed for important and strategic products in the Tajan catchment of Mazandaran province. Criteria prioritization was done using optimization through a genetic algorithm with an objective function based on sustainable development. Then, physical and economic productivity indices were calculated to determine the productivity value. Based on the results, in the selection of the crop pattern, firstly, the category of economic criteria and finally the category of environmental criteria have been given attention to the farmers in the current situation. But in the genetic optimization algorithm, all priorities have a similar order from the environmental point of view and then from the economic point of view although each product has its order of criteria. By this prioritization, the parameters of the cultivated area, the volume of water consumed, and the amount of chemical fertilizers have decreased on average by 26%, 34%, and 21%, respectively, and the parameters of product performance and profitability have increased by 43% and 61%, respectively. In addition to providing environmental standards and increasing sustainable development, this prioritization causes an average increase in physical productivity by 84% and an increase in economic productivity by 72%.