جستجوی مقالات مرتبط با کلیدواژه « brooks » در نشریات گروه « آب و خاک »

The soil water curve is one of the most critical soil hydraulic characteristics. This characteristic is used to determine soil water in the field capacity point and the permanent wilting point (PWP) beside it has a vital role in the application of soil water models in the study of soil-plant-water relationships. This curve is known as the quality soil index which has an effective role in the explanation of agricultural, ecological, and environmental problems. Impressive and efficient management of soil and water resources, water flow and solute transport survey, soil pollution, and contaminant leakage into water sources are dependent upon the accurate estimation of soil water curve parameters. Moreover, this index has a functional role in applying numerical and hydrological models. On the other hand, to better identify and understand its role, different models were provided to describe this curve mathematically. The efficiency of these models depended on the accuracy of estimated parameters in the model structure that was defined. Soil water curve is known as a non-linear relationship that is used to describe the relation between soil and water content or degree of soil saturation. The soil water curve provides essential information for using irrigation methods and about soil resistance and soil mechanical properties. In this research, the performance trend of two meta-heuristic algorithms, including the differential evolution (DE) and particle swarm optimization (PSO), was studied to estimate hydraulic parameters of soil water curves based on the van Genuchten and the Brooks and Cory models in four soil texture classes; loam, silt loam, sandy loam, and sandy clay loam. Besides, this study evaluated the performance of the meta-heuristic algorithm to RETC software. This software has a non-linear square local algorithm. This study can evaluate the ability of the meta-heuristic algorithms to estimate parameters for exponential relationships and nonlinear models.

At the agricultural farm of the University of Birjand, a study was conducted to analyze soil water content in different texture classes. The research involved the random selection of four soil texture classes and the random sampling of 20 points from each class. The soil water content was measured using a sandbox and pressure plate device, covering a broad suction range of 0-15000 cm. In the first phase, soil water curve parameters were estimated for each soil texture using the van Genuchten model and the Brooks and Cory model in the RETC software. Subsequently, the Matlab desktop environment was utilized to apply meta-heuristic algorithms (DE and PSO) to estimate the soil water curve parameters based on the two models. An objective function was defined to minimize the Root Mean Square Error (RMSE) of the meta-heuristic algorithms' performance. Finally, the study compared the performance of the meta-heuristic algorithms (DE and PSO) with the RETC software in estimating soil water curve parameters based on the van Genuchten and Brooks and Cory models, using statistical indices such as RMSE and R2. The soil texture classes play a crucial role in influencing soil water content and nutrient retention, making them an essential factor in agricultural management and crop suitability. The study's findings can contribute to a better understanding of soil water dynamics and the development of improved agricultural practices.

The obtained results of the statistical indices (RMSE and R2) showed that the least value of RMSE was acquired by the differential evolution algorithm (DE) performance. The values of RMSE during the application of the DE algorithm as an estimated method based on the van Genuchten model were 0.0008, 0.0005,0.0004, and 0.0006 also based on the Brooks and Cory were 0.006, 0.006, 0.005, and 0.0005 in sandy clay loam, sandy loam, loam, and silt loam respectively. Also, the highest value of the R2 index was obtained equal to 0.995, 0.996, 0.994, and 0.994 by the utilization of the DE algorithm based on the van Genuchten model in the sandy clay loam, sandy loam, loam, and silt loam respectively. The values of RMSE by the utilization of the PSO algorithm based on the van Genuchten model were 0.0021, 0.006, 0.0057, and 0.006 in the sandy clay loam, sandy loam, loam, and silt loam classes respectively. The highest and lowest values of the RMSE and R2 indices by the application of RETC software were obtained equal to 0.017 and 0.912 (sandy clay loam), 0.01and 0.963 (sandy loam), 0.085 and 0.972 (loam), and 0.01 and 0.924 (silt loam) based on the van Genuchten model.

It could be concluded that RETC software has poor performance in the estimation of soil water curve parameters in all soil texture classes studied based on the van Genuchten and Brooks and Cory models. This trend represents the weakness of the local algorithms to solve multivariable problems where an exponential relationship exists between the variables and they are influenced by each other. On the other hand, the results show the meta-heuristic algorithms have sufficient ability to estimate parameters in multivariable problems. It could be concluded that the meta-heuristic algorithms have better performance in estimating the parameters of soil hydraulic models. The DE algorithm is the best method to estimate soil hydraulic parameters. The PSO algorithm has the nearest performance to the DE algorithm but the best performance to RETC. Finally, meta-heuristic algorithms are suitable options for estimating soil water curve parameters based on various hydraulic models.

Although several mathematical models have been proposed to describe the soil moisture characteristic curves, not one model is suitable for all soil types. The purpose of this study was to determine the best model and Pedotransfer function to describe this curve in Mahidasht plain, Kermanshah province. Soil samples were collected from four locations at three depths. The soil moisture characteristic curve of the samples was determined using sandbox and pressure plates. The coefficients of van Genuchten and Brooks-Cory were determined based on measured data using RETC software. The estimated curve by RETC software was compared with the curve drawn based on measured data. The results showed that all models have almost the same estimations and only the Brooks-Corey model overestimates the moisture at low suctions. Based on the results, it can be stated that among the four studied models, the van Genuchten-Bordin model with m = 1-2/n (RMSE = 0.01 and ME = 0.002) is the most suitable model in the study area. The results also showed that the studied Pedotransfer functions have acceptable accuracy for estimating the soil moisture characteristic curve and the modified Sepaskhah-Bondar model (RMSE = 0.1 and ME = 0.02) is the best Pedotransfer function for soils of the Mahidasht. Then the parameters of the most suitable PEDOTRANSFER function for the soils of the study area were calibrated. Although the results of this study can be useful for use in other soils, the coefficients of these functions should be calibrated in each region.

One of the ways to express physical behavior of soil is to describe the soil structure. Since physical soil could not be measured directly, therefore, the special properties defined as indicators, are used to express the soil physical quality. of different indicators, S-index is used to express the physical quality of the soil which is the slope of the soil water retention curve at inflection point. It seems that little research has been done on the effect of landuse on the S-index, then The purpose of this study was to compare the results of S-index of three different soil water retention curve models of the moisture characteristic of the soil (Van Genuchten, Brooks-Corey and Grant-Groenevelt Models) in 5 different land uses in Jiroft city. For this reason, 350 disturbed and 350 undisturbed soil samples of different landuse (citrus, palm, arable, forest and combinatory) were analyzed. Some of the physical and chemical features of the soil, including sand, silt, and clay percentage, the electronic conductivity at saturation, Bulk Density, the percentage of the total porosity and the percentage of the Organic Matter were measured. Also, the amount of the soil moisture in suctions 0, 10, 30, 50, 100, 300, 500, 1000 and 1500 KPa was determined using pressure plates. The results showed in the study region the best physical quality of the soil was seen in palm land use. All landuses, except forest, had high physical quality. High value of S index in citrus, palm, and arable land uses can indicate better soil management at the start of farming. In combinatory land use, due to Simultaneous cropping of alfalfa and palm, alfalfa causes more organic matter to be returned to the soil and as a result, the soil structure improves. Which is displayed at high value of S index. In general, The S index was higher in landuses where the soil had better structure or management operations were improved. because of the distinction between the soils with closely physical quality, Van Genuchten model was better and more appropriate than the other two models in assessing the physical quality. In general, despite the slight differences in citrus, palm and cultivate landuses, palm landuse had a higher mean of S index. So that their values in Van Genuchten, Brooks-Corey and Grant-Groenevelt models were 0.06, 0.06 and 0.04 respectively. The results of this study showed that the Van Genuchten model accuracy was better in estimating and evaluating the soil quality due to the greater differentiation between the soils with close physical quality. Because the fitting of Soil water characteristic curve had a higher R2 (R2=0.92). However, due to low differences with two other models, in particular the Brooks and Corey model (R2 =0.87), It seems that, in different landuses, a suitable model for assessing soil quality varies. Therefore, it is imperative that this index and other indicators of soil physical quality assessment in different climates are further examined.

The van Genuchten (vG) function is often used to describe the soil water retention curve (SWRC) of unsaturated soils. The objective of this study was to evaluate a method to determine the vG model parameters m and α of 100 soil samples of Guilan province from the fractal dimension of SWRC. Also, we used two models introduced by Lenhard et al and vG for estimating m from pore size distribution index of Brooks and Corey (BC) model. In both of the mentioned methods, the relationship between pore size distribution index of BC and SWRC fractal dimension was used. Also, vG parameters using Rosetta software were estimated and then, the amounts of vG parameters from the Rosetta, fractal method and RETC were compared. Results showed that Rosetta software had a better estimation of vG parameters than the Rosetta. The estimated vG model parameters m and α obtained with the above-mentioned different methods, in conjunction with measured saturated water contents, were used to estimate water contents at different matric potentials and compared with determined values by RETC via fitting of vG model on the measured values. The estimated SWRC data via fractal method were compared with those obtained with the Rosetta model. Results showed that fractal method had more accurate performance for prediction of SWRC than the Rosetta. Even though, the Rosetta software could lead to better estimates of the vG model parameters than the fractal approach, it was not capable of predicting SWRC as accurately as the fractal approach. This is due to the fact that estimation of the water content is a result of an interaction between the estimated vG model parameters, α and m.