JWSS - Journal of Water and Soil Science

Expert aquatic designers face many problems; among these, in hydrology, defective occurrences in time-series can cause errors in the ultimate results of the study. This more often happens in the regions where the number of hydrometric and rain gauge stations is limited. In addition, assessing, developing and maintaining the use of water resources require accessible long-term and high-quality quality hydrological time-series. Thus, this necessitates correcting the statistical flaws and magnifies the importance of how to deal with the problems in the hydrological analyses. Statistical methods are, currently, used to infill data and statistical gaps. In this study, in order to introduce a multivariate method for estimating the missing data on rainfall and runoff, in a hydrologic homogeneous region in the Mazandaran province, self-organizing map methods were examined under two scenarios and some reliable estimates were obtained. In this regard, the correlation coefficients between the observational data and the model output were calculated for the precipitation data up to 0.92 and up to 0.95 for the runoff data. Therefore, to avoid the reduction of uncertainty caused by the inadequate data in water resource management, this method could be used.

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 regard to wide piers, the pile group rather than single pile is used frequently to bear the loading of the structure in a particular arrangement; piles group composed of only one column of piles in the flow direction has a great effect on supporting the bridge deck. In this study, local scour at a single column arrangement of the piles group made up of four rows of piles characterized by different piles spacing was studied for clear-water conditions with two flow discharges of 20 and 35 l/s (the effect of increasing the flow depth with the same flow intensity). The results indicated that an increase in the flow depth not only greatly enhanced the scour depth and the width of the scour hole. Besides, the investigation of the relative flow depth on scour extent showed the need for revision in deep water conditions, as reported in the literature. The results of the pile group experiments revealed the noticeable impacts of piles spacing on the local scour. The bigger pile spacing caused a feeble interaction of wake-horseshoe vortices, leading to a decrease of the scour depth; the separate view of the scour holes was generated at individual piles. Finally, the results were compared with commonly used comprehensive models. The findings of this study can be applied for the appropriate selection and positioning for the countermeasure of the scour at bridge piers.

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.

This study was conducted to investigate the temporal variations of runoff and rill erosion in various soil textures under different slope gradients. So, a laboratory experiment was set up in three soil textures (loam, clay loam, and sandy clay loam) and four slope gradients (5, 10, 15, and 20%) using the completely randomized design with three replications. Runoff production and rill erosion were measured at a flume with 4 m×0.32 m in dimensions using a simulated water flow with 0.5 lit min^-1 in discharge during 30 min. Results indicated that runoff and rill erosion and their interaction were significantly affected by soil texture and slope gradient (P < 0.001). Significant relations were found between rill erosion and runoff both in three soils and four slope gradients, and the strongest relations were in loam (R²= 0.86) and 15% slope gradient (R²= 0.94). Runoff and rill erosion varied considerably in the soil textures and slope gradients during the experiment. A 10-min pick time was found for runoff and rill erosion. In contrast to runoff, rill erosion appeared an irregular and gradual increasing pattern during the experiment which was associated with the frequency of transportable soil particles. Clay loam had more sensitive particles due to a higher percentage of fine particles and weaker structure, and most of them were washed in early times, and finally, rill erosion was reached to a constant pattern. This study revealed that temporal variation patterns of runoff and rill erosion are influenced by soil type (texture and structure) and slope gradient.

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.

Runoff is formed by spending some time after rain and significantly depends on rainfall intensity, soil moisture, and slope. One of the fundamental questions about runoff is the time that it starts to create. In this research, the runoff start time in sandy loam soil was evaluated experimentally under different conditions using a precipitation simulator machine. The rainfall intensity parameters of (60, 80, and 100 millimeters per hour) and the slope of (0 and 5 percent) were investigated. The rainfall was created in the three soil treatment types completely dry (S_dry), the dry soil that had been saturated 24 hours before the test (S_24hrlag), and the dry soil that had been saturated 48 hours before the test (S_48hrlag). Eighteen tests were conducted on this soil. At the end of each test, the soil moisture was measured. The experimental results were compared with the numerical model of Green-Ampt. According to the Kendall and Spearman correlation test results, as the rainfall be intense, the start time of the runoff is lower. Also, the runoff starts at a faster time in the slope of 5 percent for every three types of soil. Also, the results of starting time of the runoff in the soil with a delay of 48 hours in the rain compared to the soil with a delay of 24 hours in the rain are closer in all of the rainfall intensity and slopes compared to the case of dry soil. Therefore, in the experiments related to a delay of 24 hours, the time of the start of runoff decreases. While in tests with a delay of 48 hours, it was not much different from completely dry soil. Also, the Green-Ampt results are close to the experimental results (R²=0.9775), and the maximum difference between the two mentioned methods is 4.8 minutes. Therefore, it can be used with the Green-Ampt method to calculate the start time of runoff in sandy loam soil in different states of rainfall intensity and bed slope.

Digital elevation models (DEMs) are one of the most important data required in watershed modeling with hydrological models and their spatial resolution has a significant impact on the accuracy of simulating hydrological processes. In the present study, the effect of spatial resolution of five DEMs derived from the topographic map (TOPO) with a scale of 1:25000, ALOS PALSAR, ASTER, SRTM, and GTOPO with a spatial accuracy of 10, 12.5, 30, 90, and 1000 m, respectively, on the estimation of parameters of geomorphological and geomorphoclimatic unit hydrographs models has been evaluated in Amameh watershed. Thirty-four single flood events were used during the years 1970 to 2015. The results showed that in the GUH method, the application of the TOPO and ALOS PALSAR DEMs had the best results with root mean square error (RMSE) of 1.7 and 1.8 m³/s and Nash-Sutcliffe Efficiency (NSE) of 0.4 and 0.3, respectively. While the GTOPO DEM had the least efficiency with RMSE of 2.8 m³/s and NSE of -2. Similarly, the lowest and highest RMSE in the GCUH method belonged to TOPO and GTOPO DEMs with RMSE of 3.8 and 18 m³/s and NSE of 0.2 and -6, respectively. Generally, the GUH method had more favorable results than the GCUH method in all DEMs.

Today, the problems related to floods and inundation have increased, particularly in urban areas due to climate change, global warming, and the change in precipitation from snow to rain. Therefore, there has also been an increasing focus on rainfall-runoff simulation models to manage, reduce, and solve these problems. This research utilized SewerGEMS software to explore different scenarios to evaluate the model's performance based on the number of sub-basins (2 and 8) and return periods (2 and 5 years). Additionally, four methods of calculating concentration time (SCSlag, Kirpich, Bransby Williams, and Carter) were compared to simulate flood hydrographs in Shahrekord city. The results indicated that increasing the return period from 2 to 5 years leads to an increase in peak discharge in all scenarios. Furthermore, based on the calculated continuity error, the Kirpich method is preferred to estimate the concentration-time in scenarios with more sub-basins and smaller areas. For the 2-year return period, a continuity error of 4% was calculated for the scenario with 2 sub-basins, while for the 5-year return period, the continuity error was 19%. On the other hand, the SCSlag method is preferred to estimate the concentration-time in scenarios with fewer sub-basins and larger areas. For the scenario with 8 sub-basins, a continuity error of 16% was calculated for the 2-year return period, and 11% for the 5-year return period.

The growing concern for environmental protection and increasing demand for green approaches to address environmental problems have prompted researchers to explore a sustainable and reliable method for treating dyeing wastewater. One of the sustainable and reliable methods is the electrocoagulation process. In this study, a batch electrocoagulation reactor was designed to evaluate the efficiency of this process in treating dyeing wastewater. The effects of two parameters, electrode distance and retention time, on pollutant removal efficiency were investigated. Electrode distances of 2, 5, and 7 cm were tested, and retention times of 10, 15, 20, 25, and 30 minutes were examined. Results indicated that the optimal electrode distance was 5 cm and the optimal retention time was 20 minutes. Under these conditions, the removal efficiency of BOD, COD, TSS, color, and turbidity reached 83%, 85%, 98%, 98%, and 93%, respectively. The results of this research demonstrate the significant potential of the electrocoagulation system for treating dyeing wastewater.

Proper estimation of soil water infiltration parameters and Manning roughness coefficient is one of the influential factors in the correct design and evaluation of surface irrigation systems. The EDOSIM model, as a surface irrigation simulation-optimization model, uses a combination of simulation with the Volume Balance model and meta-heuristic optimization. In the evaluation part of this model, the Elliott-Walker two-point method is used to estimate the parameters of the Kostiakov-Lewis infiltration equation. In this study, the Manning coefficient and parameters of the Kostiakov-Lewis infiltration equation were calibrated in furrow and border irrigation using observational advance data. This was done through three methods: Volume Balance model with constant shape coefficients (VB-CC), a combination of Volume Balance and Zero Inertia models (VB-ZI), and Volume Balance model with variable shape coefficients (VB-VC), using a total of 10 data series of border and furrow irrigation evaluation. Then, the ability to calibrate the infiltration parameters and roughness coefficient using a superior method was added to the EDOSIM model. The results showed that the VB-CC model had the best calibration accuracy and precision in 10 farms, according to the average statistical indices R2=0.998, NRMSE=2.4%, and MBE=-0.06. The VB-ZI and VB-VC methods underestimated the advance length even with calibrated values. The use of the VB-CC model instead of the Elliott-Walker two-point method in the EDOSIM model increased the accuracy of simulation and optimization by reducing (improving) the objective function from an average of 0.34 to 0.13 in border irrigation and from an average of 0.86 to 0.36 in furrow irrigation. Therefore, it is recommended to use the VB-CC calibration method in the EDOSIM model as a powerful tool for optimal operation of surface irrigation systems.