علی افروزی

Snow is an important source for water supply in the agricultural sector, electricity production in factories, groundwater reserves, and rivers. This natural resource is important since it stores water in winter with low demand and releases it in hot seasons with high demand. Melted snow flow can be very useful in low-water seasons. In arid and semi-arid regions, snow is considered a basic source of fresh water. Significant spatiotemporal changes in distribution of snow on the scale of a basin can be important in determining the time and amount of snow melting in spring. The lack of sufficient and correct information about snow reserves can lead to inappropriate use of water resulting from snow melting and, as a result, irreparable damages. Therefore, measuring the surface covered by snow and its water equivalent, along with other information such as snow density, especially in areas where snow accounts for a large share of precipitation, is essential for resource planning and management. However, it is not possible to measure it in many areas due to harsh environmental conditions. Also, the data measured at one point cannot be generalized to a wide area of a basin. Thus, the use of satellite images can be considered as one of the methods of investigating spatial and temporal changes in distribution of snow in a region.

To obtain the monthly values of snow cover (SC), snow water equivalent (SWE) and snow depth (SDepth) from January 1982 to December 2023, the FLDAS (Famine Early Warning Systems Network—FEWS NET—Land Data Assimilation System) product from the Noah 3.6.1 Land Surface model was used. This product is at latitude 90° to -60° and longitude 180° to -180° with a spatial resolution of 0.1°×0.1° in netCDF format and its images are monthly available from January 1982 until now.The non-parametric Mann-Kendall test was used to investigate the increasing, decreasing or constant trend of the data during specific time intervals in the period. The Theil-Sen slope was used to calculate the slope of the trends. The correlation of the temporal distribution of snow cover with the two meteorological parameters of temperature and precipitation was determined using the Pearson's method.

The results showed that the year 1982 with a total of 41043.04 km2 had the highest and the year 2021 with a total of 4048.12 had the lowest SC. These data indicate a 90.13 percent decrease in SC in 42 years, which is understandable considering the 35.08 percent increase in the mean temperature (from 9.49 to 12.82 ºC) in this period. The monthly average of SC in this period showed that there was no snow cover from May to October, and in April and November it was very insignificant and negligible compared to in January, February, March and December. Among these four months, January had the highest average SC.According to the Mann-Kendall test, the trends of SC, SWE and SDepth was decreasing in all the four months of January, February, March and December. Temperature and precipitation values had increasing and decreasing trends, respectively.According to the Teil-Sen slope test, SC had the steepest and gentlest decreasing slope in January and December, respectively. In the case of SWE and SDepth, the steepest decreasing slope was related to February, and the gentlest decreasing slope occurred in December. The increase in temperature had the gentlest slope in the two consecutive months of December and January and the steepest slope in the two consecutive months of February and March. The steepest and gentlest slope of decrease in precipitation occurred in March and February, respectively.The Pearson's correlation coefficient values indicated that SC, SWE and SDepth have inverse correlation with temperature and direct correlation with precipitation. Overall, SC, SWE, and SDepth were more correlated with temperature than precipitation, especially in February and March when temperature was higher than in December and January.

In this study, using the satellite images obtained from the FLDAS product, the data of snow cover, snow water equivalent and snow depth were obtained in the province of Hamedan for the 42-year period of 1982-2023. The results showed a significant decrease in the snow cover during this period, which was expected due to climate change and temperature increase. The snow cover, snow water equivalent and snow depth have had decreasing trends. The trends of the two climatic parameters, temperature and precipitation, have been increasing and decreasing, respectively. The steepest and gentlest slope of the decrease in snow cover occurred in January and December, respectively. There was an inverse correlation of snow cover, snow water equivalent and snow depth with temperature, and a direct correlation with precipitation. In general, the correlation of snowfall parameters with temperature, especially in warmer months, was more than their correlation with precipitation.

Evaporation is known as one of the main factors in reducing surface water resources such as lakes and dam reservoirs. Due to the multitude of components affecting evaporation, its correct estimation has always been of interest to researchers in the field of hydrology. In this research, the daily evaporation from the surface of the Ekbatan dam reservoir has been estimated using the Bowen ratio energy budget method as the basic method and compared with the results of 20 different equations. Investigations indicate that the Brutsaert-Stricker equation with MSE, MAE, and RMSE values equal to 0.36, 0.41, and 0.60 mm/day, respectively, and the NSE and R2 equal to 0.97 and 0.98, respectively, had the best performance in estimating daily evaporation rate from the surface of Ekbatan dam reservoir. On the other hand, Harbeck and Ryan-Harleman equations, in the group of mass transfer equations, have performed the weakest. Also, the relationship presented in this research to calculate evaporation from Ekbatan dam reservoir using weather parameters and without the need to calculate thermal storage of water with MSE, MAE, and RMSE values equal to 0.81, 0.67 and 0.90 mm/day, respectively, and the NSE and R2 equal to 0.93 and 0.94, respectively, for the test data have a good performance in estimating the evaporation rate.

Climate change is a challenging topic for irrigation researchers as it has affected crop water demand. In the present study, the effects of climate change on minimum temperature, maximum temperature, precipitation, and the water demand of 12 crops including wheat, alfalfa, potato, barley, garlic, cucumber, watermelon, pumpkin, sugar beet, rapeseed, grain maize, and bean were investigated and also a trend analysis was carried out up to the year 2050. The impacts of implementing and not implementing the irrigation efficiency enhancement, the cropping pattern changes and the development of the early-maturing cultivars as the adaptation strategies in combination with climate change scenarios were investigated between the water years 1399–1428 (2020–2050). The results showed that without implementing the adaptation strategies, the net irrigation water requirement would increase by 3.98% to 8.38% compared with the recorded data. Growth in the irrigation efficiency up to the potential efficiency would cause a 19.23% reduction in the gross irrigation requirement on the average. By implementing the cropping pattern changes strategy through stopping the cultivation of some water-intensive crops such as alfalfa and developing the cultivation of rapeseed, net irrigation water requirement would decrease by 10.9%. By replacing late-maturing potatoes by the early and medium-maturing cultivars and developing of early-maturing grain maze cultivation, net irrigation requirement decreased by 8.86%. Furthermore, the results revealed that implementing all the above-mentioned adaption strategies would reduce the gross irrigation requirement by 34.0%. Hence, the three above-mentioned strategies can be used as the measures that executive managers and farmers choose to implement in order to adapt to climate change.

Effect of deficit irrigation on evapotranspiration, yield, water use efficiency and some growth parameters of Hamadanian pepper (Bivar) using a completely randomized design (CRD) with a full irrigation treatment (FI) and three deficit irrigation treatments (85, 70 and 55% application of water requirement; DI85, DI70, and DI55, respectively) in five replications was examined. Evapotranspiration in the FI, DI85, DI70, and DI55 treatments during the 66 days of the deficit irrigation application, were 337.8, 307.5, 281.1 and 244.2 mm and in the whole growth period were 396.2, 365.9, 339.5 and 302.6 mm, respectively. The plant’s morphological characteristics were decreased with decreasing the soil water content. However, in 79% of the cases, the difference between FI and DI85 treatments was not significant. Whereas, in all the cases, the difference between DI55 treatment and FI and DI85 treatments was significant. Applying deficit irrigation decreased the number of good-shaped fruits from 33.0/plant in the FI treatment to 15.6/plant in the DI55 treatment and similarly increased the number of bad-shaped fruits from 5.4 to 18.0 per plant. Crop yield and water use efficiency in the FI treatment were 18.98 ton/ha and 4.79 kg/m3, which did not have significant difference with the DI85 treatment (which had a yield of 17.75 ton/ha and a water use efficiency of 4.85 kg/m3). While there is not a statistically significant difference between the crop yields of FI and DI85 treatments, the DI85 treatment uses less water and gives crop yield very close to that of full irrigation treatment. Hence, the DI85 treatment can be recommended in the cultivation of Hamadanian pepper. In the severe water-scarce conditions, the DI70 treatment could be used to yield 13.48 ton/ha, which is 29% less than the FI treatment. Also, water use efficiency in the DI70 treatment was decreased by 17% compared to the FI treatment. Irrigation efficiency was 61.9, 65.3, 69.6 and 73.4% in the FI, DI85, DI70, and DI55 treatments, respectively

Regarding the reliance of the agricultural and industrial sections and the drinking water on the groundwater resources in Hamadan province, the modeling and forecasting groundwater level fluctuations to utilize the resources is a basic necessity. One of the usual method in this way is the utilization of the time series models that give simply and clearly good short-term forecasts if the models are used in the correct way. Therefore, the raw data of piezometers in the plains of Hamadan province are taken and after the preprocessing job and using the Thiessen polygon, the time series of each plain is formed. The Mann-Kendall test showed deterministic trend in all the time series of the plains which consequently it is needed to detrend by excluding the trend term from the time series. Subsequently, the unit root test is carried out for whether the time series are stationary, and then using the Box-Jenkins method, seasonal ARIMA models are applied to the sample data and the bests are selected. Afterwards, the ARIMA models are used in the 12 months forecasting that gives the good out-of-sample forecasts, which in all the plains the lowest Pearson's correlation coefficient and the highest root mean square error are calculated 0.93 and 0.73 m, respectively, for the Hamadan-Bahar plain. Moreover, the best 12-months forecast is obtained in the Kaboudarahang plain with a Pearson's correlation coefficient of 0.99 and a root mean square error of 0.20 m.

In this study the analytical and numerical solutions are used in the steady-state drainage problem in the three rectangular, semicircular, and triangular cross-section trenches. Equations that are derived by conformal mappings and complex potential theory were used for the analytical solution and SEEP/W software was used for the numerical simulation. Furthermore, physical sandbox models are designed for all the three sections in laboratory conditions and the outflows from the drainpipe are measured at 10, 20, 30, 4 and 50 cm depths. According to the three methods, in this study optimum installation depth of drainpipe that has maximum drainage outflow in the both rectangular and semicircular cross-sections is obtained at 40 cm and for the triangular cross-section is 32.5 cm using the analytical solution and 30 cm using the numerical solution and the experimental results. The results are assessed by the differences between the dimensionless discharges obtained from the analytical and numerical solutions and from the experimental conditions using relative root mean square error (RMSE) and coefficient of determination (R2). RMSE in the analytical solution for the triangular section 0.048, the semicircular section 0.061, and the rectangular section 0.071 and the R2 are 0.99, 0.98, and 0.98 and in the numerical solution 0.045, 0.056, and 0.041 for RMSE and 0.87, 0.97, and 0.97 for R2 are obtained, respectively. Comparison of the analytical and numerical solutions results with the experimental results showed that the both methods can simulate seepage flow in the trench with high accuracy. However, the accuracy of numerical solution was more than analytical solution, that it comes from some simplifications and assumptions considered in the analytical solution. In the analytical solution the ponded depth of water is considered small and negligible and the circular perimeter of the drainpipe is taken intoaccount as a line that these are the reasons for the less accurate results of analytical solution. Additionally, the hydraulic of the flow in entrance to the drain pipe is not considered in the analytical solution.

Reference evapotranspiration is one of the most important factors in irrigation timing and field management. Moreover, reference evapotranspiration forecasting can play a vital role in future developments. Therefore in this study, the seasonal autoregressive integrated moving average (ARIMA) model was used to forecast the reference evapotranspiration time series in the Esfahan, Semnan, Shiraz, Kerman, and Yazd synoptic stations.
In the present study in all stations (characteristics of the synoptic stations are given in Table 1), the meteorological data, including mean, maximum and minimum air temperature, relative humidity, dry-and wet-bulb temperature, dew-point temperature, wind speed, precipitation, air vapor pressure and sunshine hours were collected from the Islamic Republic of Iran Meteorological Organization (IRIMO) for the 41 years from 1965 to 2005. The FAO Penman-Monteith equation was used to calculate the monthly reference evapotranspiration in the five synoptic stations and the evapotranspiration time series were formed. The unit root test was used to identify whether the time series was stationary, then using the Box-Jenkins method, seasonal ARIMA models were applied to the sample data.
Table 1. The geographical location and climate conditions of the synoptic stations
Station Geographical location Altitude (m) Mean air temperature (°C) Mean precipitation (mm) Climate, according to the De Martonne index classification
Longitude (E) Latitude (N) Annual Min. and Max.
Esfahan 51° 40' 32° 37' 1550.4 16.36 9.4-23.3 122 Arid
Semnan 53° 33' 35° 35' 1130.8 18.0 12.4-23.8 140 Arid
Shiraz 52° 36' 29° 32' 1484 18.0 10.2-25.9 324 Semi-arid
Kerman 56° 58' 30° 15' 1753.8 15.6 6.7-24.6 142 Arid
Yazd 54° 17' 31° 54' 1237.2 19.2 11.8-26.0 61 Arid
The monthly meteorological data were used as input for the Ref-ET software and monthly reference evapotranspiration were obtained. The mean values of evapotranspiration in the study period were 4.42, 3.93, 5.05, 5.49, and 5.60 mm day−1 in Esfahan, Semnan, Shiraz, Kerman, and Yazd, respectively. The Augmented Dickey-Fuller (ADF) test was performed to the time series. The results showed that in all stations except Shiraz, time series had unit root and were non-stationary. The non-stationary time series became stationary at 1st difference. Using the EViews 7 software, the seasonal ARIMA models were applied to the evapotranspiration time series and R2 coefficient of determination, Durbin–Watson statistic (DW), Hannan-Quinn (HQ), Schwarz (SC) and Akaike information criteria (AIC) were used to determine, the best models for the stations were selected. The selected models were listed in Table 2. Moreover, information criteria (AIC, SC, and HQ) were used to assess model parsimony. The independence assumption of the model residuals was confirmed by a sensitive diagnostic check. Furthermore, the homoscedasticity and normality assumptions were tested using other diagnostics tests.
Table 2- The selected time series models for the stations
Station Seasonal ARIMA model Information criteria R2 DW
SC HQ AIC
Esfahan ARIMA(1, 1, 1)×(1, 0, 1)12 1.2571 1.2840 1.2396 0.8800 1.9987
Semnan ARIMA(5, 1, 2)×(1, 0, 1)12 1.5665 1.5122 1.4770 0.8543 1.9911
Shiraz ARIMA(2, 0, 3)×(1, 0, 1)12 1.3312 1.2881 1.2601 0.9665 1.9873
Kerman ARIMA(5, 1, 1)×(1, 0, 1)12 1.8097 1.7608 1.8097 0.8557 2.0042
Yazd ARIMA(2, 1, 3)×(1, 1, 1)12 1.7472 1.7032 1.6746 0.5264 1.9943
The seasonal ARIMA models presented in Table 2, were used at the 12 months (2004-2005) forecasting horizon. The results showed that the models produce good out-of-sample forecasts, which in all the stations the lowest correlation coefficient and the highest root mean square error were obtained 0.988 and 0.515 mm day−1, respectively.
In the presented paper, reference evapotranspiration in the five synoptic stations, including Esfahan, Semnan, Shiraz, Kerman, and Yazd, were calculated using the FAO Penman-Monteith method for the 41 years, and the time series were formed. The selected models gave good out-of-sample forecasts of the monthly evapotranspiration for all the stations. The models can be used in the short-term prediction of monthly reference evapotranspiration. Note that, the use of models in long-term forecasting was not recommended. The time series model can be used in lost data. Even though more methods are available for model building, the use of time series models in water resources are advocated in modeling and forecasting. Time series can be used as a tool to find lost data.

Forecast and evaluate the effects of climate change can be very useful in planning future managers. Various tools used to achieve this goal. In this research, the SWAT model is used to simulate and evaluate the climate change impacts on the crop yields in Simineh Rood basin and the changing cropping pattern strategy is evaluated as a comparative plan. To model the climate change conditions in the region, under the A2 and B2 scenarios, the HadCM3 atmosphere-ocean general circulation model outputs’ are used. Using the SDSM model, the outputs are downscaled and the minimum and maximum temperature and precipitation data are obtained for the years 2010 to 2033 and the data are used as inputs for the SWAT model. Afterwards, the values of water and temperature tensions, crop yields and the inflow of Urmia Lake in the climate change conditions are estimated and it is named as BAU. The results showed the increase in the average tensions of water and temperature and also the reduction in the crop yields. After evaluating the climate change impacts in the basin, changing the cropping pattern to wheat and barley is evaluated as a comparative strategy that showed 32% and 24% reduction in the water tension under the A2 and B2 scenarios compared to BAU condition. Also the produced calorie and the inflow of the lake showed 15.6% and 15.8% under the A2 scenario and 11.8% and 12.1% under the B2 scenario increase, respectively, compared to the BAU condition.

In this study, relationships of electrical conductivity of the soil saturation extract (ECe) with the ionic composition, the ionic strength and the total dissolved salts are studied in the Sudjan plain; also, the general new method of electrical conductivity calculation that has been presented by McCleskey et al. (2012) is used in order to compare with the proposed equations. Therefore, the 80 soil samples were taken from the Sudjan Plain in Chaharmahal va Bakhtiyari Province and soil salinity parameters by measuring sodium, magnesium, calcium, Potassium, chloride, sulphate, bicarbonate, carbonate, pH and ECe were determined and analyzed. The Pearson’s correlation coefficient at the significance levels 5 and 1 percent between the salinity parameters showed that the carbonate isn’t significantly correlated with other parameters. Also, the correlation of magnesium and ECe was insignificant. The linear model regressions between the ionic composition, sum of ions, cations and anions concentration, ionic strength and total dissolved salts were generalized. The greatest correlation coefficient (0.91) and the lowest root mean square error (0.08 dS m−1) were obtained in the model between the ECe and the ionic composition. The results of research in the studying plain showed that the presented model in this investigation in comparison with the new model of McCleskey et al. (2012) give smaller error and greater correlation. The insignificancy between the carbonate and ECe and the regression models showed that this ion can be neglected in the calculation of ECe.

Drainage of agricultural lands is very important and without drainage a sustainable agriculture isn’t possible. In the absence of natural drainage in agricultural lands, artificial drainage is necessary. Construction of drainage ditches is one of the usual methods of artificial drainage. Study of the governing equations of flow to drainage systems is an interesting subject to researchers. In this study, an analytical solution for steady-state seepage of ponded water into drainage ditches is developed. The ditches are partly penetrating, parallel to each other and excavated by rectangular cross section in a homogeneous and isotropic soil layer. In order to derive the relevant equations of seepage quantities and velocities, first hodograph and complex potential planes were drawn with attention to the boundary conditions of physical plane; then the conformal mappings of physical and hodograph planes on auxiliary planes were found using Schwarz-Christoffel transformation. The chain rule was used to find the relation between complex potential plane and auxiliary plane. This method can be used to calculate the seepage quantities and velocities as well as ditches drainage designing. The results showed that near the ditches, seepage velocity along the ponded surface was very high as compared with that between the ditches, so leaching was non-uniform.

Prediction of water table depth and outflow rate of drainage system are the most important issues in the literature of the drainage engineering. Three models of Kraijenhoff Van de Leur – Maasland، de Zeeuw - Hellinga and Glover – Dumm are frequently used for prediction of water level and discharge rate under unsteady state flow condition. For comparing the ability of these models an experiment was conducted using a laboratorial physical model. Data were collected for constant and variable head conditions in accordance to the boundary conditions of each model. The results showed good agreement with the observation data. For water level rising condition the Kraijenhoff Van de Leur – Maasland and de Zeeuw – Hellinga models، underestimated the outflow rate and overestimated the water table level as compared to the observed data، also Kraijenhoff Van de Leur – Maasland model''s prediction was better than that of de Zeeuw – Hellinga model. For the falling water table state the de Zeeuw – Hellinga model prediction was closer to the observation. The prediction accuracies of all three models decreased and converged while reaching the end of the experiment.