Mapping soil-water profile utilizing non-linear neural network based model

Muhammad Mukhlisin, Ahmed El-Shafie, Mohd. Raihan Taha

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Modeling unsaturated water flow in soil requires knowledge of the hydraulic properties of soil. However correlation among soil hydraulic properties such as the relationship between saturated soil water content θ s and saturated soil hydraulic conductivity Ks as function of soil depth is in stochastic pattern. On the other hand, soil-water profile process is also believed to be highly nonlinear, time-varying, spatially distributed, and not easily described by simple models. In this study, the potential of implementing Artificial Neural Networks ANN model was proposed and investigated to map the soil-water profile in terms of Ks and θ s with respect to the soil depth d. Site experimental data sets on the hydraulic properties of weathered granite soils were collected. These data sets include the observed values of saturated and unsaturated hydraulic conductivities, saturated water contents, and retention curves.The proposed ANN model was examined utilizing 49 records data collected from field experiments. The results showed that the ANN model has the ability to detect and extract the stochastic behaviour of the water in the soil and draw the water-soil profile with relatively high accuracy.

Original languageEnglish
Title of host publicationUnsaturated Soils - Proceedings of the 5th International Conference on Unsaturated Soils
Pages887-893
Number of pages7
Volume2
Publication statusPublished - 2011
Event5th International Conference on Unsaturated Soils - Barcelona
Duration: 6 Sep 20108 Sep 2010

Other

Other5th International Conference on Unsaturated Soils
CityBarcelona
Period6/9/108/9/10

Fingerprint

neural networks
soil water
hydraulic property
soil hydraulic properties
soil
soil depth
granite soils
hydraulic conductivity
unsaturated hydraulic conductivity
water content
saturated hydraulic conductivity
unsaturated flow
water flow
soil profiles
soil water content
water retention
fluid mechanics
artificial neural network
soil profile
granite

ASJC Scopus subject areas

  • Soil Science

Cite this

Mukhlisin, M., El-Shafie, A., & Taha, M. R. (2011). Mapping soil-water profile utilizing non-linear neural network based model. In Unsaturated Soils - Proceedings of the 5th International Conference on Unsaturated Soils (Vol. 2, pp. 887-893)

Mapping soil-water profile utilizing non-linear neural network based model. / Mukhlisin, Muhammad; El-Shafie, Ahmed; Taha, Mohd. Raihan.

Unsaturated Soils - Proceedings of the 5th International Conference on Unsaturated Soils. Vol. 2 2011. p. 887-893.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Mukhlisin, M, El-Shafie, A & Taha, MR 2011, Mapping soil-water profile utilizing non-linear neural network based model. in Unsaturated Soils - Proceedings of the 5th International Conference on Unsaturated Soils. vol. 2, pp. 887-893, 5th International Conference on Unsaturated Soils, Barcelona, 6/9/10.
Mukhlisin M, El-Shafie A, Taha MR. Mapping soil-water profile utilizing non-linear neural network based model. In Unsaturated Soils - Proceedings of the 5th International Conference on Unsaturated Soils. Vol. 2. 2011. p. 887-893
Mukhlisin, Muhammad ; El-Shafie, Ahmed ; Taha, Mohd. Raihan. / Mapping soil-water profile utilizing non-linear neural network based model. Unsaturated Soils - Proceedings of the 5th International Conference on Unsaturated Soils. Vol. 2 2011. pp. 887-893
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