JWSS - Journal of Water and Soil Science

The simulation of the rainfall-runoff process in the watershed has particular importance for a better understanding of hydrologic issues, water resources management, river engineering, flood control structures, and flood storage. In this study, to simulate the rainfall-runoff process, rainfall and discharge data were used in the period 1997-2017. After data qualitative control, rainfall, and discharge delays were determined using the coefficients of autocorrelation, partial autocorrelation, and cross-correlation in R Studio software. Then, the effective parameters and the optimum combination were determined by the Gamma test method and used to implement the model under three different scenarios in MATLAB software. Gamma test results showed that today's precipitation parameters, precipitation of the previous day, discharge of the previous day, and discharge of two days ago have the greatest effect on the outflow of the basin. Also, the P_t Q_t-1 and P_t P_t-1 Q_t-1 Q_t-2 Q_t-3 combinations were selected as the most suitable input combinations for modeling. The results of the modeling showed that in the support vector machine model, the Radial Base kernel Function (RBF) has a better performance than multiple and linear kernels. Also, the performance of the Artificial Neural Network model (ANN) is better than the Support Vector Machine model (SVM) with Radial Base kernel Function (RBF).

A compound sharp-crested weir is often used to measure a wide range of flows with appropriate accuracy in open channels. In this study, experiments were performed to investigate the hydraulic flow through a compound weir of circular-rectangular with changes in hydraulic and geometric parameters in free and submerged flow conditions. The characteristics of the weirs include rectangular spans width of 39 cm, a circular radius of 5, 7.5, and 12.5 cm, and heights of 10 and 15 cm. The results showed that by increasing the radius and height of the Weir, upstream water depth increases around 28.4%. At a constant h/p, the discharge coefficient increases with the increasing radius of the circular arc. Also, in the submerged conditions, the discharge coefficient is less (around 40%) than in the free flow condition, which is due to the resistance of the depth of the created stream against the passage of the flow.

The existence of silty sand in the infrastructure under concrete constructions, hydraulic structures, and irrigation systems has always caused challenges. Improving this kind of soil is always a challenging approach to increase compressive strength and shear stress. There is a conception that adding some extra material such as concrete can increase the stability of this soil against contributed forces. The present study investigated the effects of curing time (3, 7, 14, 21, and 28 days) and different percentages of various additives (3%, 5%, and 7%) on the strength of the silty sand soils. A series of laboratory tests were carried out to measure the Uniaxial Compressive Strength (UCS) and California Bearing Ratio (CBR) by evaluating the effect of additives on the strength parameters of silty sand soil. In total, 299 experimental tests have been conducted in the soil mechanics laboratory of SRBIAU. Results indicated that adding additives such as concrete to silty sand soil improved significantly the compressive strength and shear strength. The comparisons among the experimental test illustrate that due to increasing the curing time, the aforementioned parameters were increased significantly; however, Confix and Bentonite aggregates did not have a marginal effect on the compressive strength and shear strength. Also, after the 21^st day of the curing time, the rate of increment of the UCS and CBR reached slightly and then attained a constant value. Also, after this duration, the curing time is an independent factor in the variation of the UCS and CBR tests. Furthermore, the addition of 5% Pozzolana cement and 7% Portland cement with 28 days of curing had the highest CBR number and UCS resistance of 176.26 and 17.58 kg/cm², respectively. Also, the sketch of the different failure patterns was shown during the curing time. Finally, by increasing the curing time, the behavior of specimens from semi-brittle to brittle made them harder.

Inefficient use of limited water resources, along with increasing population and increasing water demand for food production has severely threatened agricultural water resources. One way to overcome this problem is to improve water productivity by introducing new crops that tolerate water stresses such as quinoa. In this study, the effect of water stress at different stages of plant growth (vegetative, flowering, and grain filling) was studied on plant parameters, yield, and water productivity of quinoa (cv. Titicaca). This study was conducted under field conditions and the treatments were performed as a block experiment in a completely randomized design with four replications. Experimental factors were: treatment without water stress or full irrigation (F) and water stress treatment (D) at 50% of the need for full irrigation at different stages of quinoa growth. The application of deficit irrigation during different stages of plant growth decreased stomatal conductance, leaf area index, leaf water potential, seed yield, and water productivity, while deficit irrigation increased the green canopy temperature. According to the results of the present study, the flowering stage of quinoa was very sensitive to water stress leading to produce lower yield compared with the amount of yield obtained when vegetative and or grain filling stages are under water stress conditions.

Drought is one of the most complex natural disasters due to its slow onset and long-term impact. Today, the use of remote sensing techniques and satellite imagery has been considered a useful tool for monitoring agricultural drought. The objective of the present study was to evaluate spatial and temporal monitoring of agricultural drought in the lake Urmia catchment area with the ETDI drought index which is calculated from Nova satellite images based on actual evapotranspiration from the SEBS algorithm and compared with the ground index SPI. For this purpose, 248 AVHRR sensor images and NOAA satellites during the statistical period of 1998-2000 and 17 meteorological stations with a statistical period of 30 years were used to calculate the indicators. To determine agricultural lands, six thousand points were marked for different uses and their actual evapotranspiration was calculated using the SEBS algorithm. The results showed that with the onset of the drought period in 1998, the ETDI index indicated 9.4% in weak drought conditions in May and 90.6% in normal conditions. Over time, in June of 1998, the situation was different with 95% in a weak drought situation and 5% in a normal situation for the city of Tabriz. In July, the entire catchment area experiences a slight drought. Then, in August, 84% of the basin is in normal condition and 16% in Tabriz and Urmia are declared weak drought. It was also founded that the ETDI drought index due to the combination of visible and infrared bands and its combination with terrestrial data has a physical meaning and has high certainty and predicts drought faster and more accurately.

In recent years, indirect methods such as remote sensing and data mining have been used to estimate soil salinity. In this research, the electrical conductivity of 94 soil samples from 0 to 100 cm was measured using the Hypercube technique in the Saveh plain. 23 types of input data were used in the form of topographic and spectral categories. Land area parameters such as the Topographic Wetness Index (TWI), Terrain Classification Index (TCI), Stream Power Index (STP), Digital Elevation Model (DEM), and Length of Slope (LS) were considered as topographic inputs using Arc-GIS and SAGA software. Also, salinity spatial and vegetation indices were extracted from Landsat 8 images and were considered spectral inputs. The GMDH neural network was used to model salinity with a ratio of 70% for training and 30% for validation. The results showed that the soil salinity values were between 0.1 and 18 with mean and standard deviation of 5 and 4.7 dS/m, respectively. Also, the results of modeling indicated that the statistical parameters R², MBE, and NRMSE in the training step were 0.80, 0.06, and 42.1%, respectively. The same values in the validation step were 0.79, 0.13, and 48.7%, respectively. Therefore, the application of spectral, topographic, and GMDH neural network indices for modeling soil salinity is effective.

can provide useful information about P adsorption and the factors affecting it. A batch experiment was performed with phosphorus concentrations (0 to 35 mg/L) in two soils with different electrical conductivity (EC) (2 and 15 dSm^-1) by a variety of biochar treatments including simple apple-grape biochar (BC), rock phosphate- biochar (BC-RP), enriched-biochar (BC-H₃PO₄-RP), enriched-biochar (BC-HCl-RP), triple superphosphate (TSP), and control (Cont). The results indicated that phosphorus sorption capacity varied between the soils. Biochar treatments were effective in reducing the phosphorus adsorption of both soils. Due to BC-H₃PO₄-RP and BC-HCl-RP treatments, the maximum phosphorus adsorption of soils decreased in S1 soil by 14 and 23 % and in S2 soil by 26 and 19%, respectively. Also, the use of these treatments decreased the parameters of Langmuir absorption intensity (K_L) of S1 soil to 0.085 and 0.066, respectively and S2 soil to 0.11 and 0.15, L/mg respectively, and Freundlich absorption capacity (K_F) of S1 soil decreased to 19.2 and 22.5 and S2 soil to 28.2 and 28.1 L/kg, respectively. Enriched biochars significantly reduced the buffering indices of both soils indicating phosphorus adsorption decreased and increased the availability of phosphorus for the plant. The standard phosphorus requirement of S2 soil was lower than S1 soil by both equations. Therefore, enriched biochar can be an effective strategy to increase phosphorus availability and reduce the use of chemical fertilizers in saline and non-saline conditions; however, more field studies are needed for a clear understanding of the potential of P-enriched biochar as a fertilizer alternative.

In sustainable agriculture, cow manure is used for greater productivity, a rich source of E-Coli pathogenic bacteria. The objective of this research was to investigate the simultaneous effect of the fractionation size of cattle manure and irrigation water salinity on the retention of E-Coli bacteria in the depths of the sand column with a height of 10 cm under saturated flow. Four different particle fractions of cow manure (1-2, 0.5-1, 0.25-0.5, and smaller than 0.25 mm) were added to the surface of the sand column at the scale of 30 tons per hectare, then leaching was done with different salinities (0, 0.5, 2.5, 5, and 10 dS/m) up to 10 pore volumes, then samples were taken from the depths of 0, 3, 6, and 12 cm. The number of bacteria in each sample was determined by the live counting method. The results showed that the effect of all sources of change and their interaction effects on the retention of bacteria in the soil is significant at the level of 5%. Salinity had a negative effect on the retention of bacteria, and the highest and lowest values of the relative concentration of bacteria (the result of dividing the number of bacteria in each soil depth by the initial number of bacteria in the desired manure treatment) were in 0 dS/m and 10 dS/m salinity of leaching water, respectively. By decreasing the size of cow manure particles due to the increase in hydrophobicity and blocking of preferential pores, the retention of bacteria decreased in all investigated soil depths. The highest and lowest retention of bacteria in the soil were investigated in the largest cow manure particle size (1-2 mm) and the smallest cow manure particle size (less than 0.25 mm), respectively. In addition, the highest relative concentration of bacteria in the soil was seen in the depth of 0-3 cm, and no significant difference was seen in other soil depths.

Salinity and water scarcity are limiting factors for sustainable agricultural production. The cultivation of resistant plants to environmental stresses is one of the important management factors for sustainable production. The objective of this study was to determine the water requirement and plant response coefficients to water deficit stress (K_y) in different growth stages under the Khuzestan province climate. This study was performed on the quinoa cultivar Titicaca in Ahvaz City in 2019 in a randomized complete block design with 13 treatments and three replications. Treatments include full irrigation and application of three levels of water deficit stress (30, 50, and 70% of allowable soil moisture depletion) at four different stages of plant growth. The duration of the initial, developmental, middle, and late growth stages of quinoa was 24, 28, 32, and 18 days, respectively (total growth period=102 days). The highest quinoa yield was obtained in full irrigation treatment (3700 kg ha^-1) with a water requirement of 312 mm. Plant response coefficient to water deficit stress in the initial, developmental, middle, and late stages were 0.8, 0.65, 0.74, and 0.47, respectively. Although quinoa is a drought-resistance plant, it should be noted that the water stress in the two initial and middle stages (quinoa sensitive growth stages to water stress) reduces the quinoa yield significantly that should be considered in the planning of deficit irrigation.

Awareness of water resources status is essential for the proper management of resources and planning for the future due to the occurrence of climate change in most parts of the world and its impact on different parts of the water cycle. Hence, many studies have been carried out in different regions to analyze the effects of climate change on the hydrological process in the coming periods. The present study examined the effects of climate change on surface runoff using the Atmosphere-Ocean General Circulation Model (AOGCM) in Khomeini Shahr City. The maximum and minimum temperatures and precipitation of the upcoming period (2020-2049) were simulated using a weighted average of three models for each of the minimum and maximum temperatures and precipitation parameters based on the scenario A2 and B1 (pessimistic and optimistic states, respectively) of the AOGCM-AR4 models. The LARS-WG model was also used to measure the downscaling. The HEC-HMS was used to predict runoff. The effects of climate change in the coming period (2020-2049) compared with the observation period (1971-2000), in the A2 scenario, the minimum and maximum temperatures would increase by 1.1 and 1.6 Degrees Celsius, respectively, and the precipitation would decrease 17.8 percent. In the B1 scenario, the minimum and maximum temperatures would increase by 1.1 and 1.4 degrees Celsius, respectively, and the precipitation would decrease by 13 percent. The results of runoff were different in the six scenarios in the way the most runoff reduction is related to the scenario of fixed land use and scenario A2 (22.2% reduction), and the most increase is related to the scenario of 45% urban growth and scenario B1 (5.8% increase). So, according to increase urban texture in the future and consequently enhance the volume of runoff, this volume of runoff can be used to feed groundwater, irrigate gardens, and green space in the city.

Due to the climatic conditions of Iran, increasing water scarcity, and the effect of drought stress on the efficiency of irrigation water consumption and chemical fertilizers application, an experiment was conducted to investigate the effect of irrigation intervals (6, 9, and 12-day intervals), different levels of nitrogen fertilizer (200, 300, and 400 kg urea per hectare) and cultivation methods (on-ridge or heeling up and in-furrow) on yield and productivity of sugarcane as a factorial design based on randomized complete block design in 3 replications at Hakim Farabi Agro-Industry Company in Khuzestan province. The results showed that the maximum (106.73 tons/ha) and minimum (59.10 tons/ha) sugarcane yields were observed in 9-day and 12-day irrigation intervals, respectively. Also, the highest sugarcane yield (99.89 tons per hectare) was obtained in the treatment of 400 kg urea per hectare and the in-furrow planting method resulted in a higher yield compared to the on-ridge planting method. The highest water productivity in sugarcane stem yield and sugar production with 3.55 and 0.34 kg per cubic meter of applied water, respectively, was obtained in a 9-day irrigation interval. A significant increase in water use efficiency in sugarcane stem yield was observed in 400 kg urea/ha compared to the other two fertilizer levels. However, there was no significant difference in water productivity of sugar yield between different fertilizer treatments. The results showed that 6 and 9-day irrigation intervals in most of the studied traits were not significantly different. Therefore, using a 9-day irrigation interval is suggested in the studied area when the sugarcane cultivation area is high and the amount of available water is limited. In-furrow planting method can also be effective in reducing water consumption. Therefore, deficit irrigation and proper nitrogen fertilizer consumption can be very effective in sugarcane cultivation.

Due to water scarcity, it is impossible to utilize all irrigated cropland in arid and semi-arid areas. Therefore, dense cultivation with a drip irrigation system that delivers water directly to the plant's root zone is an appropriate choice to enhance water productivity. The objectives of the present study were to compare wheat yield and water productivity under two different water distribution patterns in the drip-tape irrigation system and surface irrigation in full irrigation and deficit irrigation levels. The experimental treatments consist of two irrigation systems (drip-tape (DT), and surface irrigation (SU)), and three different irrigation levels (a full irrigation level (W1), two deficit irrigation levels, the irrigation interval twice, and the same irrigation depth of W1 level (W2), applied half of the irrigation depth of W1 level at the same time (W3)). The SU was implemented in place with 100% efficiency to avoid runoff. The yield in full irrigation level in DT was 5338.4 kg/ha and in SU was 5772.8 kg/ha. Applying deficit irrigation in two irrigation systems has different effects due to various water distribution patterns. In the DT, the most yield reduction was in W2, and in SU was in W3. The highest water productivity in DT was observed in W3 with a 1.44 kg/m3 value. The highest water productivity in SU was observed in W2 with a 1.46 kg/m3 value. For each irrigation system, some type of deficit irrigation management is optimal.

The different land uses in the irrigation water area of the eleven streams of Khansar city during 1969, 1995, 2014, and 2019 have been identified and their area has been determined by analysis of the aerial photos as well as the satellite images of QuickBird, and Landsat in the Google Earth Engine (GEE) environment. Then, the net and gross areas of land under irrigation water, area of non-agricultural land uses, location and area of agricultural land uses under irrigation of the streams are separated according to the type of agricultural activity (orchard or farmland) for each stream. Aerial photos of the study area dated 1969 are the basis for the assessment of agricultural conditions before the law of Fair Water Allocation. The results showed that non-agricultural and particularly urban and residential land uses have increased since 1969. In other words, land use of part of the agricultural lands has been changed to residential and urban land uses. Despite the decreasing trend of agricultural land uses in the last 50 years, these changes have not been the same between the farm and orchard land uses and the area under orchard plantation showed an increasing trend. These changes have dramatically influenced on water demand of the streams. Land use has not significantly changed from 2014 to 2019 and no noticeable change was observed in the area of the agricultural and green agricultural lands as well as the percentage of the orchard and farming lands during these years. The results of this study confirmed the significant changes in agricultural land use and consequently water consumption in the district of the eleven streams of Khansar in recent decades. This study also highlighted the high efficiency of the combined use of aerial photos, spectral satellite images with medium spatial resolution, and visible spectral satellite data with high spectral resolution, as well as using cloud system capabilities of the Google Earth Engine to study changes in agricultural land uses during last decades.