JOURNAL OF WATER AND SOIL RESOURCES CONSERVATION
Year:2013 | Volume:2 | Issue:3|Papers Count:6

Crop models are appropriate and low-cost tools for investigating the effect of agricultural inputs on water and soil resources and crop production. The objective of this study was to evaluate the OILCROP-SUN model for Euroflor hybrid of sunflower in order to gain a suitable base to conserve soil and water resources. This study was conducted as a strip-plot statistical design with randomized complete blocks design with three replications for each treatment. Total biomass, seed weight, seed yield, percentage of seed oil, and seed nitrogen were measured. Using collected field data, OILCROP-SUN model was calibrated and evaluated for different levels of water and nitrogen applications. Six genetic coefficients were then derived from calibration of OILCROP-SUN model for Euroflor hybrid. The results indicated that seed yields were simulated reasonably well for 12 treatments with NRMSE value of 18.5%, and the d-index of 0.92. The d value of different treatments of water and nitrogen for seed nitrogen was 0.93, and for oil production per hectare was 0.91.

Estimating total sediment load in rivers is an important and practical issue for water resources planning and management. The sediment concentration can be calculated by both direct and indirect measurements, but direct methods are usually costly and time-consuming. Further, total sediment load can be determined by several sediment load transport models. These equations, however, are applicable in certain circumstances, and in most cases the outcomes do not agree with each other and with measured data. The objective of this study was to propose a method based on artificial neural networks (ANN) to predict total sediment load concentration. Consequently, two ANNs including multilayer perceptrone (MLP) and radial basis function (RBF) with 200 data were used for the modeling purposes. For training and testing the ANN models, 75 and 25 percent of data were used, respectively. The input variables were designated to be average flow velocity, average depth, water surface slope, canal width and median particle diameter of sediment, while the models output was total sediment load concentration. The input variables were included to the models step wisely and the results were evaluated to find out the most suitable ANN models. The predicted values were then compared with five known sediment load transport equations. The conducted statistical analyses indicated that ANNs models in particular MLP can provide better prediction for total sediment load with correlation coefficient of 0.96. It was further concluded that to enhance the accuracy of ANN model, training of the network should be accomplished using both hydrological and sediment data. The Ackers and White equation was very overestimating the total sediment load, while all other equations were underestimating. Based on the results obtained in this study, the ANN-based models provide better concurrence with the observed data, particularly MLP network which can reasonably well predict the peak point of total sediment.

Parametric soil water retention functions are important inputs for soil water conservation models. The objective of this study was to derive some spectrotransfer functions (STFs) to estimate soil water retention functions, using spectral reflectance. Consequently, proximal spectral reflectance of the soil samples within the VIS-NIR and SWIR (400-2500 nm) ranges was measured by using a handheld spectroradiometer apparatus. After (pre) processing the spectral data, the correlation between all wavelengths and soil water contents at matric potentials of -15000, -10000, -5000, -3000, -1000 and -330 cm were determined. Then, the transfer functions in the form of partial least square regression (PLSR) and bootstrap aggregation with PLSR (Bagging-PLSR) were derived. These new transfer functions were called point spectrotransfer functions (PSTFs). Results indicated that the derived PSTFs can well estimate soil water retention characteristics. The derived PLSR-based STFs provided more accuracy (RMSE=0.012 to 0.022 cm3 cm-3) than Bagging-PLSR based STFs (RMSE=0.012 to 0.029 cm3 cm-3) for estimating soil water contents at all designated matric potentials. On the other hands, performance of PSTSs for soil water contents at -15000, -10000 and -5000 cm were more reasonable than that of water contents at -3000, -1000 and -330 cm. It may be then concluded that PSTFs can be used as a reasonable indirect method for estimating soil water retention particularly at high soil water pressure heads.

Soil contamination with crude oil and its derivatives is one of the most dangerous type of environmental pollution. The objective of this study was to evaluate and optimize the indigenous soil microorganisms using nitrogen, phosphorus and potassium fertilizers and municipal compost contaminated with fuel oil (130g/kg), and their reclamation influence as well as optimum mixing ratio with soil. For this purpose, different levels of municipal composts with two ratios of NPK (5, 10. 15 percent) fertilizers (10:2:1 and 10:1:1 ratios) were applied into experimental soil samples. After initial equilibrium period (10 days), the amount of hydrocarbon contaminants in soil under aerobic conditions were determined. The results showed an increased percentage in the compost and declined soil emissions of oil such that treatment of 15% had the highest reduction rate between 59 to 62 percent. The results of two applied fertilizers, confirmed the usefulness of 10:2:1 ratio. The applied amendments to all treatments lead to effective oil degrading bacteria, especially during first week after equilibrium. This can be related to faster breakdown of short-chain compounds such as alkanes. The results further indicated an effective correlation between rate of TPH decomposition and CO2 of microbial activity. There was a direct correlation between crude oil degradation and microorganisms activity. Simultaneous treatment of municipal solid waste compost (15%) and NPK fertilizers (10:2:1 ratio) with six weeks was an effective treatment to clean up oil-contaminated soils by decomposition rate of 62 percent.

For design and implementation of soil conservation programs, accurate and optimized mapping of soil properties is required. The type of interpolation method is one of the most important issue involved in mapping soil properties. Six ordinary methods of spatial interpolation were compared to determine their suitability for estimating some quality properties of topsoil including clay content, electrical conductivity, equivalent calcium carbonate and organic carbon in the Naqade region farmlands located in west Azerbaijan. The area of study region was about 8300 ha. For this purpose, 282 topsoil samples were collected randomly and tested for laboratory analysis. Deterministic methods (radial basis function and global polynomial interpolation) as well as geostatistical estimators (ordinary Kriging) were utilized to map related soil properties. The highest and lowest CV was obtained for EC and clay content variables, respectively. For clay and electrical conductivity, the exponential model, for equivalent calcium carbonate the Gaussian model, and for organic carbon the spherical were the best fitting models to calculate the experimental variogram. According to the results, the ordinary Kriging approach characterized with the minimum error indicator of bias-variance trade-off (BVTO) for evaluating clay, electrical conductivity, equivalent calcium carbonate and organic carbon. The thin plat spline model of radial basis function showed the maximum error in assessment of studied attributes. Eventually, the interpolation maps were generated regard to the most appropriate interpolators.

Tape drip irrigation is one of the relatively new methods which can be considered as an effective tool in improving irrigation efficiency as well as agricultural and horticultural crop production. The so-called physical clogging of emitters is the most important problem in tape drip irrigation system that causes decreasing of emission uniformity and increasing of operating costs. Despite appropriate filtration system, some fine particles with less than 0.1 mm in diameter (minimum diameter of the screen filter mesh) can cross through the filters, causing the emitter clogging. The objective of this study was to investigate the effect of fine particle diameters on emitter clogging in drip irrigation tapes system. The result indicated that the effect of fine particle diameter on emitters clogging is statistically significant (at 1% level of significance). The results also indicated that by reducing the particle diameters, emitter clogging is increased. Such that the maximum clogging can occur by particles that have less than 0.037 mm diameter.