Development of regional-scale pedotransfer functions based on Bayesian Neural Networks in the Hetao Irrigation District of China

Zhongyi Qu, Xianyue Li, Dan Tian, Raghavendra B. Jana, Binayak P. Monhanty

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

In order to study determination the soil hydraulic parameters in the distributed hydrological models on farmland environmental effects resulted from water-saving practices of large scale irrigation district, the Bayesian Neural Networks and BP ANN model were applied to establish regional pedotransfer functions models based on the relationship of measured soil characteristic contents (saturated water content s, residual water content r and field water content r), soil particle percentage, organic matter and bulk density and fitted VG model parameters of different soil texture classes from 22 soil water and salt monitoring points 110 soil samples in the Hetao Irrigation District. Then, the adaptability of two kinds of ANN models were evaluated by simulated and predicted results through the statistical results and SWRC figures. The several conclusions were reached: the ANN and BNN are both feasible PTFs methods. But, the training simulated accuracy of traditional BP model is better than that of BNN; however, the predicted accuracy of BNN model generally is better than the BP model. Furthermore, the number of input factors groups has significantly influenced the predictive accuracy of BP model. But there are little influences on the different inputs factors of BNN model. So, the BNN showed good robustness for the simple inputs. Second, the predicted SWRC has better fitness with measured and VG fitted curve than that of ANN. So, the BNN model is better than the traditional artificial neural network model has better adaptability in the peodotransfer function establishment when it uses only soil particle distribution. The BNN method is a practical method for regional pedotransfer function establishment.

Original languageEnglish
Title of host publicationProceedings - 2011 7th International Conference on Natural Computation, ICNC 2011
Pages756-761
Number of pages6
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 7th International Conference on Natural Computation, ICNC 2011 - Shanghai, China
Duration: 26 Jul 201128 Jul 2011

Publication series

NameProceedings - 2011 7th International Conference on Natural Computation, ICNC 2011
Volume2

Conference

Conference2011 7th International Conference on Natural Computation, ICNC 2011
Country/TerritoryChina
CityShanghai
Period26/07/1128/07/11

Keywords

  • Bayesian neural network
  • BP neural networks
  • Hetao Irrigation District
  • Pedotransfer functions

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