A Forecasting Method of Kostiakov Infiltration Model Parameters Based on Back-Propagation Model

2012 ◽  
Vol 610-613 ◽  
pp. 2899-2903
Author(s):  
Chong Wen Cao ◽  
Gui Sheng Fan
Keyword(s):  
Back Propagation ◽  
Influence Factors ◽  
Propagation Model ◽  
Water Infiltration ◽  
Physical Parameters ◽  
Model Parameters ◽  
Soil Infiltration ◽  
Infiltration Process ◽  
Infiltration Model ◽  
Bp Model

Based on test data of field soil water infiltration, Back-propagation (BP) model of predicting Kostiakov infiltration model parameters was established after analyzing the primary influence factors of water infiltration model parameters. The results indicate that BP model can reflect the non-linear relationship between the model parameters and the physical parameters of the soil; BP model is high accuracy for prediction soil infiltration model parameters. It can be referred as a new method to predict soil infiltration process using soil physical parameters.

scholarly journals Predicted Infiltration for Sodic/Saline Soils from Reclaimed Coastal Areas: Sensitivity to Model Parameters

2014 ◽  
Vol 2014 ◽  
pp. 1-12
Author(s):  
Dongdong Liu ◽  
Dongli She ◽  
Shuang’en Yu ◽  
Guangcheng Shao ◽  
Dan Chen
Keyword(s):  
Water Movement ◽  
Soil Surface ◽  
Coastal Areas ◽  
Model Parameters ◽  
Wetting Front ◽  
Sodic Soils ◽  
Infiltration Process ◽  
Infiltration Model ◽  
Soil Physical Quality ◽  
Cumulative Infiltration

This study was conducted to assess the influences of soil surface conditions and initial soil water content on water movement in unsaturated sodic soils of reclaimed coastal areas. Data was collected from column experiments in which two soils from a Chinese coastal area reclaimed in 2007 (Soil A, saline) and 1960 (Soil B, nonsaline) were used, with bulk densities of 1.4 or 1.5 g/cm3. A 1D-infiltration model was created using a finite difference method and its sensitivity to hydraulic related parameters was tested. The model well simulated the measured data. The results revealed that soil compaction notably affected the water retention of both soils. Model simulations showed that increasing the ponded water depth had little effect on the infiltration process, since the increases in cumulative infiltration and wetting front advancement rate were small. However, the wetting front advancement rate increased and the cumulative infiltration decreased to a greater extent whenθ0was increased. Soil physical quality was described better by theSparameter than by the saturated hydraulic conductivity since the latter was also affected by the physical chemical effects on clay swelling occurring in the presence of different levels of electrolytes in the soil solutions of the two soils.

Infiltration Characteristics of Soil Moisture in Liangping County

2014 ◽  
Vol 641-642 ◽  
pp. 183-186
Author(s):  
Shu Yan ◽  
Juan Gao ◽  
Zhong Yuan Zhang ◽  
Feng Lin Zuo ◽  
Wei Hua Zhang
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Infiltration Rate ◽  
Water Shortage ◽  
Water Infiltration ◽  
Soil Infiltration ◽  
Infiltration Model ◽  
Double Ring ◽  
Soil Water Infiltration ◽  
Relationship Of

In order to relieve water shortage, many countries develop water-saving industries and increase water use rate of irrigation. The research on soil water infiltration has important effect on infiltration and runoff, as well as for irrigation. The study carried out in Liangping district of Chongqing by using double ring infiltration method and exploring the reasonable infiltration model in the study area. The relationship of initial soil moisture and irrigation coefficient was studied as well. The results showed that: the Kostiakov empirical formula could simulate the process of soil water infiltration properly. The soil infiltration rate of Liangping is 0.0320cm/min in the selected location.

Study on Infiltration Kinetics of High Temperature Self-Lubrication Composite by Pressure Infiltration

2011 ◽  
Vol 399-401 ◽  
pp. 1843-1847
Author(s):  
Bin Wang ◽  
Yan Jun Wang
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Influence Factors ◽  
Solid Lubricants ◽  
Infiltration Process ◽  
Pressure Infiltration ◽  
Infiltration Model ◽  
Kinetics Of ◽  
Ordered Porous ◽  
Main Influence

In this paper, the kinetics of infiltration of 60Sn40Pb-10Ag molten solid lubricants into the TiC-Fe-Cr-W-Mo-V ordered porous sintering body were studied and the effective infiltration model which was used to analysis the kinetics of infiltration was established. The infiltration process was simulated by finite element method. The result showed that the main influence factors on the infiltration quality were the pressure ,the temperature and the time.

scholarly journals The determination of reasonable number of soil infiltration test in farmland

2019 ◽  
Vol 136 ◽  
pp. 07020
Author(s):  
Xu Yang ◽  
Jiamin Yu ◽  
Yangren Wang ◽  
Yanjie Li
Keyword(s):  
Statistical Analysis ◽  
Soil Infiltration ◽  
Infiltration Process ◽  
Infiltration Model ◽  
Double Ring ◽  
Reasonable Number ◽  
Cumulative Infiltration ◽  
Infiltration Test ◽  
Experimental Base

At the experimental base of Tianjin Agricultural University, the infiltration process of water was measured by double - ring infiltration instrument at six points. Horton，Philip and Kostiakov-lewis (K-l) infiltration models were fitted with the infiltration data measured and the parameters were correspondingly obtained. Six sets of parameters of the corresponding infiltration model were obtained, and six sets of parameters were used for statistical analysis. The reasonable number of points of the corresponding model was obtained. Then, the statistical analysis of the cumulative infiltration amount was used to obtain the variation of the number of reasonable points in the three models with time. The results show that the imitative effect of accumulative infiltration water and time in K-l model is the best, and the curve of reasonable test points determined by K-l model with time is located under the other two models; The reasonable number of points determined by the parameter K in the K-l model is the least and most reasonable. In view of this, the number of reasonable points was determined by using the parameter K in the K-l model.

scholarly journals Spatial Variability Analysis of Farmland Soil Infiltration Based on Model Parameters

2019 ◽  
Vol 136 ◽  
pp. 07021
Author(s):  
Qingdao Xin ◽  
Hemin Zhu ◽  
Yangren Wang ◽  
Xinrui Fan
Keyword(s):  
Water Movement ◽  
Direct Method ◽  
Correlation Coefficients ◽  
Simulation Method ◽  
Spatial Uncertainty ◽  
Model Parameters ◽  
Soil Infiltration ◽  
Infiltration Process ◽  
Farmland Soil ◽  
Significant Difference

Research on the variation of soil infiltration is helpful to analyze the mechanism of soil water movement in farmland. At the same time, soil infiltration characteristics affect the surface irrigation. Based on the field test data, this study simulated and analyzed the soil infiltration with three soil infiltration models (Kostiakov-Lewis model, Philip model and Horton model). The infiltration uncertainty of farmland soil are investigated, and proposed by using two random simulation methods (direct method and parameter mean method) of infiltration. The evaluated indicators are the interval size and its stability of cumulative infiltration amount changed with 95% confidence. The effects of different random simulations methods and three models on the infiltration process are compared and analyzed. Finally, the model and stochastic simulation method suitable for the infiltration characteristics of the farmland are determined. The results show that the correlation coefficients of the three models are all above 0.98, and there is no significant difference in fitting accuracy. In terms of the degree of spatial uncertainty (determined by standard deviation): direct method > parameter mean method, in which the combination of the Kostiakov-Lewis model and the parameter mean method have less uncertainty, and the combined simulation effect is better, it is more suitable for the simulation of soil infiltration at farmland scale.

Research on Soil Infiltration Law of Different Landues Types in Jinsha River Dry-Hot Valley

2013 ◽  
Vol 726-731 ◽  
pp. 3867-3871 ◽  
Author(s):  
Zhi Qin Liu ◽  
Nan Jun Lang ◽  
Ke Qin Wang
Keyword(s):  
Bulk Density ◽  
Infiltration Rate ◽  
Soil Bulk Density ◽  
Water Infiltration ◽  
Soil Infiltration ◽  
Jinsha River ◽  
Infiltration Process ◽  
The Waste Land ◽  
Waste Land ◽  
Soil Water Infiltration

This article takes four different slope lands as the experimental points in Jinsha River dry-hot volley. The double-rings method is adopted to illustrate the soil moisture infiltration characteristics in four different landuse types. The results show that different landues types have obvious differences in soil infiltration capability among four different patterns of landuse. Arbor forest behaved the best infiltration capability and wasteland the worst; the average infiltration and the steadily infiltration attains 1.67mm/min and 0.5mm/min respectively during the first 120min of soil water infiltration process in arbor forest; the rate of whatever the average infiltration or the steadily infiltration express the same regulation: the arbor forest is a little higher than the shrub land, the grassland, than the waste land; the moisture infiltration rate in different landuse types can all be thoroughly defined through the Horton equation; Water infiltration is affected by the soil bulk density. With the bulk density increasing, the steady infiltration rate decreases. And the two are at an exponential function.

scholarly journals Research on Influence of Soil Moisture Content of Farmland on Infiltration Model Parameters

2020 ◽  
Vol 189 ◽  
pp. 01011
Author(s):  
Zhiwei Zheng ◽  
Zhuozhuo Gao
Keyword(s):  
Moisture Content ◽  
Soil Column ◽  
Initial Moisture Content ◽  
Test Method ◽  
Model Parameters ◽  
Initial Water Content ◽  
Initial Water ◽  
Infiltration Process ◽  
Infiltration Model ◽  
Kostiakov Model

In order to study the influence of the initial moisture content on the parameters of the infiltration model using an indoor soil column test method, and the relationship between the initial moisture content and each model parameter was analyzed by using the Green-Ampt model, the Kostiakov model, and the Horton model. The results show that there is a certain relationship between the initial water content and the parameters of the infiltration model. Based on comprehensive considerations, the Kostiakov model is the best surface irrigation infiltration model, and the Kostiakov model has the best effect when the observation time is not less than 80 minutes to simulate the soil infiltration process.

scholarly journals Rate of water infiltration into soil on a selected location at Žabčice during the growing season 2008

2010 ◽  
Vol 58 (5) ◽  
pp. 399-406 ◽  
Author(s):  
M. Vičanová ◽  
F. Toman ◽  
Bohdan Stejskal ◽  
T. Mašíček ◽  
J. Knotek ◽  
...  
Keyword(s):  
Field Measurement ◽  
Water Infiltration ◽  
First Year ◽  
Physical Parameters ◽  
Soil Infiltration ◽  
Volume Weight ◽  
Cumulative Infiltration ◽  
Water Accumulation ◽  
Graphical Presentation

Purpose of currently running research, which is part of research program Biological and technological aspects of sustainability of controlled ecosystems and their adaptability to climate change at Faculty of Agronomy, is mapping of progress in water infiltration on selected areas at Žabčice locality and to specify possibilities of a water accumulation and retention influence in a landscape.During of the first year of measurement (2008), from April to November, has proceeded field measurement of soil infiltration ability at Žabčice locality. To get statistically conclusive results, measurement runs in three repetitions and data are subsequently averaged. Three sets of homocentric metal cylinders were used for the measurement. Measurement of infiltration has been preceded by an overflow. Empirical equations according to Kosťjak were used for evaluation of field measurement.At the same time there were ensured intact soil samples for laboratory determination of soil physical properties using Kopecky cylinders at depths of 10, 20 and 30 cm, and for the calculation of selected hydro-physical parameters of soil.­ reduced volume weight, actual monture, porosity, aeration and other.Graphical presentation presents process of speed infiltration and cumulative infiltration on selected area Niva IV. A. Non-homogeneity of measured values could be induced by several different factors.

scholarly journals Predicting Tunnel Squeezing Using the SVM-BP Combination Model

2021 ◽  
Author(s):  
Zhen HUANG ◽  
Minxing Liao ◽  
Haoliang Zhang ◽  
Jiabing Zhang ◽  
Shaokun Ma ◽  
...  
Keyword(s):  
Large Scale ◽  
Back Propagation ◽  
Classification Performance ◽  
Propagation Model ◽  
Support Vector ◽  
Characteristic Parameters ◽  
Svm Model ◽  
Tunnel Diameter ◽  
Squeezing Prediction ◽  
Bp Model

Abstract Rock squeezing has a large influence on tunnel construction safety; thus, when designing and constructing tunnels it is highly important to use a reliable method for predicting tunnel squeezing from incomplete data. In this study, a combination SVM-BP (support vector machine-back-propagation) model is proposed to classify the deformation caused by surrounding rock squeezing. We designed different characteristic parameters and three types of classifiers (an SVM model, a BP model, and the proposed SVM-BP model) for the tunnel-squeezing prediction experiments and analysed the accuracy of predictions by different models and the influences of characteristic parameters on the prediction results. In contrast to other prediction methods, the proposed SVM-BP model is verified to be reliable. The results show that four characteristics: tunnel diameter (D), tunnel buried depth (H), rock quality index (Q) and support stiffness (K) reflect the effect of rock squeezing sufficiently for classification. The SVM-BP model combines the advantages of both an SVM and a BP neural network. It possesses flexible nonlinear modelling ability and the ability to perform parallel processing of large-scale information. Therefore, the SVM-BP model achieves better classification performance than do the SVM or BP models separately. Moreover, coupling D, H, and K has a significant impact on the predicted results of tunnel squeezing.

scholarly journals Two-Stage Water Jet Landing Point Prediction Model for Intelligent Water Shooting Robot

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2704
Author(s):  
Yunhan Lin ◽  
Wenlong Ji ◽  
Haowei He ◽  
Yaojie Chen
Keyword(s):  
Pitch Angle ◽  
Back Propagation ◽  
Water Jet ◽  
The State ◽  
Model Parameters ◽  
Propagation Time ◽  
Back Propagation Algorithm ◽  
Angle Error ◽  
Landing Point ◽  
Propagation Algorithm

In this paper, an intelligent water shooting robot system for situations of carrier shake and target movement is designed, which uses a 2 DOF (degree of freedom) robot as an actuator, a photoelectric camera to detect and track the desired target, and a gyroscope to keep the robot’s body stable when it is mounted on the motion carriers. Particularly, for the accurate shooting of the designed system, an online tuning model of the water jet landing point based on the back-propagation algorithm was proposed. The model has two stages. In the first stage, the polyfit function of Matlab is used to fit a model that satisfies the law of jet motion in ideal conditions without interference. In the second stage, the model uses the back-propagation algorithm to update the parameters online according to the visual feedback of the landing point position. The model established by this method can dynamically eliminate the interference of external factors and realize precise on-target shooting. The simulation results show that the model can dynamically adjust the parameters according to the state relationship between the landing point and the desired target, which keeps the predicted pitch angle error within 0.1°. In the test on the actual platform, when the landing point is 0.5 m away from the position of the desired target, the model only needs 0.3 s to adjust the water jet to hit the target. Compared to the state-of-the-art method, GA-BP (genetic algorithm-back-propagation), the proposed method’s predicted pitch angle error is within 0.1 degree with 1/4 model parameters, while costing 1/7 forward propagation time and 1/200 back-propagation calculation time.

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