فصلنامه حفاظت منابع آب و خاک
سال ششم شماره 4 (پیاپی 24، تابستان 1396)

Drought is a natural phenomenon, which has a complex mechanism as a result of interactions of meteorological parameters and usually occurs in all climates. So, predicting drought indices and their chronological evaluation is an effective way for the drought management and adaptation with its consequences. In the current research, prediction of drought indices are carried out for Tabriz synoptic station, using support vector regression, multiple linear regression and standard precipitation index (SPI) for the time period of 1979 to 2012. In this regard, for predicting SPI indices in the periods of 3, 6, 9, 12, 24 and 48 months, six different input combinations including the antecedent correspondent values of the mentioned index have been utilized. The results of statistical analysis showed that both methods had significant accuracy. Nonetheless, the support vector regressions for predicting SPI-6, SPI-9 and SPI-24 had better performances, regarding the root mean squared errors of 0.4985, 0.4340 and 0.2427, respectively. However, the multiple linear regressions showed lower relative errors, for predicting SPI-3, SPI-12 and SPI-48. Meanwhile, it can be concluded that both examined methods including support vector and multiple linear regressions had acceptable predictions of drought index and can be used with an admissible confidentiality for the management of drought consequences.

One of the most important issues in groundwater resources quantitative management is estimating water table level using observation wells network data. The purpose of this study is to estimate the groundwater level using the combination of the geostatistics and soft computing methods. Bam Normashir and Rhmtabad plains (Kerman province) with an area of 1928 km2 was selected as a case study of this work. In this study, Kriging and IDW methods were used along with the data driven ANN, ANFIS and GEP models for predicting the spatial distribution of groundwater level, then, the best model was selected for further sampling in the studied region. Data from 65 wells during the period of 2002 to 2011 were used. RMSE, R2, AARE and MAE statistical indices were used for comparing the applied models. Results showed that for all of the models with two input parameters (including longitude and latitude), ANN and IDW models presented the most accurate results with the lowest RMSE (7.138 and 15.062m, respectively) and AARE (33 and 44%, respectively), and the highest R2 (0.606 and 0.596, respectively) for the point and regional estimation of groundwater table level. Finally, ANN-IDW hybrid model was selected for estimation and zoning the groundwater level for the future investigations.

Aras river due to located in the path of mining activities and having special ecological, economic, social and a variety of different species of aquatic plants and animals is very important and assessment of its quality is essential. This study was conducted to assess pollution of Pb, Cu, Zn and Ni in the Aras free trade-industrial zone. Samples of sediments, water, plant (Typha australis) and fish (Varicorhinus dapoeta) were collected in four sampling sites of 150 km of Aras river in autumn 2013 and summer 2014. The results indicated that the concentration of all elements in water and fish samples aligned with standards, although Cu value exceeded standard level within sedimentation and plant. According to contaminant criteria (contaminant factor, pollution load index, and geoaccumulation index), Cu concentration was very high in all sampling sites except SantSpataneous site. Its reason is likely to overloading Cu from Sungon mine. The magnitude of heavy metal pollutants in all sampling sites was identified as follows: Cu > Zn > Pb = Ni. The bioaccumulation factor of heavy metals in fish samples was found to be lower than 1 indicating they probably were uptaked through fish respiratory and dermal surfaces rather than dietary uptake. The high concentrations of Pb and Zn in Typha australis from Ilganeh river and Gholan and Missen sites exhibited that this species could be utilised to remediate the polluted places to heavy metals.

In the free water surface flow (FW-SF) constructed wetlands, a large number of micro organisms that live around the roots of plants create a suitable environment for wastewater treatment. To study the effect of Vetiver plant and sewage retention time in treatment efficiency of such systems, nine ponds in the Karoun sugarcane Agro-industrial located in the city of Shushtar was built. Units, in parallel with each other and each unit with length 3m, width 1m and height 0.8 meters. Continuously, agricultural wastewater from the washing process of sugarcane from December 2013 until May 2014 was established. Three of the units filled with soil and were transplanted with vetiver (S), three units were cultivated with vetiver on the floating platform (F) and three units were kept unplanted as control (C). The average BOD5 concentration of the wastewater entering the unit was 115±15.69 mg/l and retention times of experiments were 3, 5 and 7 days. During the experiment, the concentration of BOD5 per unit of input and output measurements was analyzed using SAS software. The results of the analysis showed significant differences between plant and non-plant systems, including retention times. The constructed wetland system with plant cultivated and the retention time of 7 days in May had highest value of the average removal rate equal to 68.48 percent. In other words, optimum conditions for maximum BOD5 removal rate of Karoun sugarcane Agro-industrial wastewater in floating constructed wetlands systems was with vetiver cultivated and in the retention time of 7 days.

In this research, the transport process of a non-reactive contaminant through layered sandy soils and dispersion coefficient behavior in different configurations of these soils were investigated. Tracer tests included pollution and leaching experiments conducted in a sandbox with dimensions of 130 cm×10 cm×60 cm. Three types of homogeneous sandy soils (coarse, medium and fine) as a control and six types of layered sandy soils were studied. The results showed that in the homogeneous sandy soils, the dispersion coefficient increased with increasing particle size of sand. For example, the dispersion coefficients of the coarse sandy soil in the pollution and leaching experiments were 8.46 and 7.91 orders of magnitude larger than the dispersion coefficients of the fine sandy soil, respectively. In the layered sandy soils, the type of configuration and the order of layers at each configuration influenced dispersion coefficient. In the pollution and leaching experiments, the least values of dispersion coefficients were equal to 12.50 cm2/min and 17.16 cm2/min, respectively, which were observed in the perpendicular configuration with stratification of coarse-medium-fine. However, the most values of dispersion coefficients in the pollution and leaching experiments were equal to 32.56 cm2/min and 37.31 cm2/min, respectively, which were obtained in the parallel configuration with stratification of coarse-fine- medium (from bottom to top). The dispersion coefficients of the layered sandy soils differed significantly from those of the homogeneous sandy soils. The transport process in the layered sandy soils, compared to the homogeneous sandy soils, had a more deviation from Fickian transport.

This study was conducted to investigate changing of border dimension and the root zone depth in Hamidieh Khuzestan on water application efficiency. Soil of site has heavy soil texture (Clay Loam) and investigation in three farms base of usual method of farmer and direct measurement to calibration of WIN-SRFR model in 2015 was applied. The effective depth of root development of wheat (Chamran verities) 100 days after planting date (Late February ,After flowering) about 40 cm and water application efficiency in border irrigation in farmer situation about 30% were determined. The simulation results by this model in condition of 40 cm root zone depth and 50 cm net depth of irrigation water show that with 18 lit/s discharge, 3-3.5 h cutoff time and border dimension with 180 m length and 10 m width, the possibility of increasing water application efficiency is up to 40% is provided. If root zone depth and net depth of irrigation water increase respectively 50cm and 70 mm (In condition of improving soil) can be water application efficiency increased to 50% in proposed condition that percent relative increase is about 33% more than farmer situation. So by applied convenient operation plowing and soil emendation and also correction of border dimension and irrigation management can be increase percent relative increase of water application efficiency up to 66 percent in comparison of farmer condition.

Soil salinity is one of the important challenges for sustainable agriculture in arid and semi-arid regions. Accumulation of soluble salts within the soil profile adversely affects some physical and chemical properties of soils including osmotic pressure, permeability and hydraulic conductivity. As a consequence, growth and development of plant is seriously reduced or fully ceased. The objective of this study was to assess using desalinization models for scheduling crop rotation of reclamation saline-sodic soils. Consequently, a large area of 45,000 ha with S4A3 (extreme salinity and sodicity) salinity/sodicity class was selected to obtain the required data ,in Khuzestan, Iran. This experiment was conducted with two treatments each with three replicates. In the first treatment, the experiment was conducted by applying just 100 cm water depth in four-25 cm intervals. In the second treatment, 10 Ton gypsum (78% purity rate) was applied prior to salt leaching together with leaching water. Soil samples were taken from 0-25, 25-50, 50-75, 75-100, 100-125 and 125-150 cm soil depths before, during and after each leaching water application interval. The required physical and chemical soil analyses were performed for the collected data. The results indicated that the logarithmic model can estimate the capital leaching requirement much better than other models. Based on the obtained model, the amount of net water needed to reduce initial soil salinity was calculated and finally crop rotation in two options was presented for reclamation of saline-sodic soils. The first option with preliminary leaching and cultivation of barley in continues leaching was assigned as the first priority. The second option with preliminary leaching and alfalfa cultivation and continues leaching was assigned as the next priority. The obtained results further indicated that the inclusion of scheduling crop rotation to the leaching practice, in addition to enhance effective leaching of soluble salts from the soil profile, causes considerable water saving.

Accurate estimation as one of the important elements of the hydrological cycle of evaporation play an important role in the development and management of water resources plays countries facing a water crisis. so far methods, and many empirical formulas in estimating the nonlinear process evaporation of the basin, which provide high accuracy and as well as access to all the input parameters problem or measure they need a lot of time and money.The aim of this study was to compare of ability of Gene expression programming and neuro-fuzzy methods for estimation of evaporation in South Khorasan province. For this purpose daily data collected from occurs six synoptic stations during years 1990-2010. Input parameters are daily mean temperature, relative humidity, max and min temperature, wind speed and sun shine. Finally, to evaluate of models and compare them criteria such as coefficient of determination (R2) and Mean Bias Error (MBE) and Root Mean Square Error (RMSE) and MBE is used. Compression of result in test period showed the GEP Model has better performance than the neuro-fuzzy model to estimate the daily evaporation. The best result of GEP is R2=0.79¡ RMSE= 1.44 and MBE=0.35 in Boshroie station and worst is R2=0.7¡ RMSE= 2.6 and MBE=1.2 in Birgand station. Also the results showed the main factor in estimation of evaporation is mean temperature in all station except that mine temperature is impact parameter.

Rivers flow prediction in river basins has an important role in the operation and correct management of water resources. Determining type and number of estimator models inputs is one of the important steps in rivers flow prediction. Therefore, The Procrustes analysis (PA) method for determining the number of effective inputs was used. In this study, flow prediction was done using the flow data obtained from the Safakhaneh and Santeh hydrometric stations. The Artificial Neural Network (ANN) and The Support Vector Machine (SVM) models was used for flow prediction. The best estimation of flow is done using the MLP and SVM models in Safakhaneh hydrometric station with RMSE equal to 5.68 (m3/s) and 4.85 (m3/s), respectively, and CC equal to 0.73 and 0.78, respectively. While in Santeh hydrometric station RMSE was equal to 6.44 (m3/s) and 6.36 (m3/s) respectively, and CC was equal to 0.78 and 0.79 respectively for MLP and SVM models. PA-SVM model showed better results than SVM model in estimating Safakhaneh hydrometric stations flow with RMSE equal to 5.45 (m3/s) and CC equal to 0.73 during the test period. The results also indicated that SVM and PA-SVM models estimated the flow of Santeh station with RMSE equal to 6.85 (m3/s) and 7.03 (m3/s) respectively. Basically, results indicated that the Procrustes analysis method can be used as one of the Efficient and suitable methods for determining the number of effective inputs. Comparison of the ANN and SVM results indicated that ANN model has more accuracy than SVM model.