Gamma spectroscopy was performed on Marinelli beaker standards containing soil with different densities of ρ=1 to 1.5 gr cm-3 upon using a HPGe detector. The spectra were analyzed by a specific software and then the efficiency vs. energy was calculated for each sample. The calculated efficiencies for different densities were compared with the efficiency of the reference sample, and the self-absorption correction factors were calculated for soil samples in the range of 59-1408 keV energy. The obtained correction factors were applied successfully for the calculation of the activity of an unknown sample.

SWAP model is called an agro-hydrological, agronomical-hydrological and eco-hydrological model. In this research, SWAP model was studied for estimation of soybean crop yield, biological yield and available moisture percentage in soil during growing season. In this study, first of all results were sensitivity analyzed and calibrated based on soybean cultivation for four furrow irrigation scenarios in agronomical years 2008-2009. Then it was validated based on field results in agronomical year 2009-2010. The results of this study showed that this model simulated crop yield better than biological yield. Also sensitivity analysis of the model showed that SWAP model is sensitive to input data of residual moisture and saturation hydraulic conductivity and with the least variation in soil input including saturation hydraulic conductivity and residual moisture, output results varied greatly. Based on statistical analyses, with a lot of existing variables, SWAP model can estimate the soil moisture, leaf area index, water use efficiency and crop yield well because in all cases coefficients of determination are higher than 0.8 (are equal to 0.86, 0.87, 0.89 and 0.93 respectively) and root mean square error is less than standard deviation of data and mean comparison T-test did not show significant differences between the simulated and measured amounts.

The lack of required datasets over the catchments impose basic problems for applying hydrologic models. By increasing the satellite-based technologies over the past decades, several water balance components have been developed by using remote sensing and data assimilation techniques. This research addresses the efficiency of evapotranspiration values which are obtained from the reanalysis models (GLEAM, W3RA and HBV) for calibration of VIC-3L hydrologic model over the SefidRood basin (SRB). Results showed that using the evapotranspiration dataset, which is estimated by GLEAM, is the best for calibration of VIC-3L (NS=0. 56 and CC=0. 80) and simulating the streamflow at the outlet of SRB. Also, using the HBV reanalysis model’ s results, in both daily and monthly time scales, with the KGE=0. 64 leads to the better performance in simulating streamflow when comparing to the base scenario (calibration of VIC-3L model with the observed streamflow data). Finally, results indicated that using W3RA and GLEAM datasets improved the VIC-3L performance in estimation of runoff volume and the maximum relative error restricted to only 4. 0 %.

During last decades hydrological models were extesively used in rainfall-runoff modeling. These models contain some constant parameters that must be optimized through appropraite mthods. In addation to model structur, the efficieny of hydrological models depend on these optimized parameters. In this study, the efficiency of three automatic optimizing algorithms including Dynamically Dimensioned Search (DDS), Shuffled Complex Evolution and Genetic algorithms in calibration lumped hydrological model HyMod in Ghorchay Ramian Catchment were investigated. For these mehods, convergence speed and variability of final optimized values were investigated. Results showed that Genetic algorithm converged faster than two other methods. Following, DDS algorithm converged faster than Shuffled Complex Evolution algorithm. Shuffled Complex Evolution and Genetic algorithms took shorter and longer time per each epock, respectively. Highest and the least variability of final results were obtained for DDS and Shuffled Complex Evolution algorithms, respectively. With respect to final results variability, Shuffled Complex Evolution algorithm was more satable and had better performance than other methods. Using analyse variance and comper means in Shuffled Complex Evolution algorithms for complexes less than 12, the model performance was increased as the number of complexe increased. As alpha value increased, the model performance decreased and model had the best performance at the value of 0. 58. Conversely, model performance was increase as beta values increasd and the best perfromnce was obtained for beta equal to 1. For Genetic algorithm, the best performance was obtained when the value of values crossover, mutation and chromosome number was equal to 0. 2 and 0. 3 and 16, respectively.

Wheat ground beetle Zabrus tenebrioides (Goeze) (Coleoptera: Carabidae) is an important wheat pest in Iran and some regions of the world. This pest causes damage to wheat by feeding on the root, stalk, and leaves. Farmers try to control this pest by the foliar application of different insecticides, but this method causes damage to the environment. To find an effective method to control this pest, the thiamethoxam insecticide (Cruiser®) efficiency was evaluated using seed treatment in this study. An experiment based on a randomized complete block design with four treatments and four replications was conducted in a field in Ramhormoz city, Khuzestan province (Iran). The treatments were 150 and 200 ml of thiamethoxam plus 2350 ml of water for seed treatment, 2,000 ppm of diazinon by field spraying at the wheat tillering stage, and a control. The results indicated that the average plant density in 150 and 200 ml of thiamethoxam (333.58 and 333.28 plant/m2, respectively) was more than those of diazinon (258.28 plant/m2) and the control (182.12 plant/m2). The average ear density in 150 and 200 ml of thiamethoxam (513.78 and 506.12 plant/m2, respectively) was more than those of diazinon (321.22 plant/m2) and the control (260.86 plant/m2). According to the present results, farmers can use 150 ml of thiamethoxam plus 2350 ml of water for 100 kg of seeds to control this pest by seed treatment.

Streamflow simulation in watersheds is necessary to runoff management and understanding watershed response. Different hydrological models were developed for rainfall-runoff modelling. The BILAN model was used to simulate daily runoff in 23 river gauge stations in a 20-year period using observed rainfall, temperature, humidity and discharge time series. The values of model parameters including Spa, Dgm, Dgw. Alf, Mec, Wic, Soc, and Gid have been calibrated using the genetic algorithm. The monthly values of streamflow data were simulated in the selected watersheds. The efficiency of the calibrated model was evaluated using statistical measures. The statistical measures were coefficient of efficiency (CE), root mean square error (RMSE) and coefficient of determination (R2). The results showed that in the calibration period, the ranges of values of R2 evaluation indicators were acceptable in Shams Abad (92%), Neneh Karan (42%), Mashiran (38%) and Barouq (51%) watersheds. Also, the results of the BILAN model validation showed that the efficiency of the model in Amoghin, Atashgah, Nir, Namin, Samian, Viladaragh and Shams Abad watersheds had a good agreement with the R2 values more than 60%. Meanwhile, the performance of the BILAN model in Gilandeh, Iril, Ahmadkandi, Barouq and Poleh Almas stations was not acceptable according to the R2 values less than 5%. In general, according to the results of model performance evaluation, it can be said that the BILAN model has a relatively acceptable performance in some of studied stations. Therefor the BILAN model can be implemented based on the available input data of the model.