Open Access Open Access  Restricted Access Subscription Access

Pedo-Transfer Functions for Saturated Hydraulic Conductivity of Cultivated Soils in the Mid Hills of Sikkim


Affiliations
1 Department of Irrigation and Drainage Engineering, College of Agricultural Engineering and Post Harvest Technology, Ranipool 737 135, India
2 Department of Agricultural Engineering, North Eastern Regional Institute of Science and Technology, Nirjuli 791 109, India
 

In this study, pedotransfer functions (PTFs) are developed for saturated hydraulic conductivity (Ks) using multiple linear regression (MLR) technique for the cultivated terraced land of East Sikkim district, North East India. Soil samples were collected for 29 stations and Ks values were measured using the constant head permeameter. The various combinations of measured soil properties, including percentage of sand, silt, clay, bulk density (BD), particle density (PD), porosity, organic carbon (OC) content were used for the development of the models. The Ks value varied from 0.97 to 29.38 cm/day and the mean value was 8.04 cm/day in the study area. The correlation between predicted and measured values was found to be better for the combination, including five input variables. The results indicated a negative correlation of Ks with silt, clay and BD, whereas sand, PD, OC and porosity had a positive correlation. The recommended MLR model 5 consisting of five input variables for the prediction of Ks in the study area had R2 values of 0.81 and 0.83 during model development and model validation, and showed goodness-of-fit with the observed Ks value. The PTFs developed in this study would be helpful for the planning and design of water resources structures in the hilly state of Sikkim.

Keywords

Cultivated Land, Multiple Linear Regression, Pedotransfer Functions, Saturated Hydraulic Conductivity, Soil Property.
User
Notifications
Font Size

  • Obiero, J. P. O., Gumbe, L. O., Christian, T., Omuto, C. T., Hassan, M. A. and Agullo, J. O., Development of pedotransfer functions for saturated hydraulic conductivity. Open J. Mod. Hydrol., 2013, 3, 154–164.
  • Patil, N. G., Rajput, G. S., Singh, R. B. and Singh, S. R., Development and evaluation of pedotransfer functions for saturated hydraulic conductivity of seasonally impounded clay soils. Agropedology, 2009, 19(1), 47–56.
  • Gwenzi, W., Hinz, C., Holmes, K., Philips, I. and Ian, J. M., Fieldscale spatial variability of saturated hydraulic conductivity on a recently constructed artificial ecosystem. Geoderma, 2011, 166(1), 43–56.
  • Dharumarajan, S., Hegde, R., Lalitha, M., Kalaiselvi, B. and Singh, S. K., Pedotransfer functions for predicting soil hydraulic properties in semi-arid regions of Karnataka Plateau, India. Curr. Sci., 2019, 116(7), 1237–1246; doi:10.18520/cs/v116/i7/1237-1246.
  • Montzka, C., Herbst, M., Weihermüller, L., Verhoef, A. and Vereecken, H., A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves. Earth Syst. Sci. Data, 2017, 9(2), 529–543.
  • Ryczek, M., Kruk, E., Malec, M. and Klatka, S., Comparison of pedotransfer functions for the determination of saturated hydraulic conductivity coefficient. Environ. Prot. Nat. Resour., 2017, 28(71), 25–30; doi:10.1515 /OSZN-2017-0005.
  • Chakraborty, D. et al., Prediction of hydraulic conductivity of soils from particle-size distribution. Curr. Sci., 2006, 90(11), 1526–1531.
  • Patil, N. G. and Singh, S. K., Pedotransfer functions for estimating soil hydraulic properties: a review. Pedosphere, 2016, 26(4), 417– 430.
  • Boadu, F. K., Hydraulic conductivity of soils from grain-size distribution: new models. J. Geotech. Environ. Eng., 2000, 126(8), 739–746.
  • Cronican, A. E. and Gribb, M. M., Hydraulic conductivity prediction for sandy soils. Groundwater, 2004, 42(3), 459–464.
  • Merdun, H., Cnar, O., Ramazan Meral, R. and Apan, M., Comparison of artificial neural network and regression pedotransfer functions for prediction of soil water retention and saturated hydraulic conductivity. Soil Tillage Res., 2005, 90, 108–116.
  • Lake, H. R., Akbarzadeh, A. and Mehrjardi, R. T., Development of pedo transfer functions to predict soil physico-chemical and hydrological characteristics in southern coastal zones of the Caspian sea. J. Ecol. Nat. Environ., 2009, 1(7), 160–172.
  • Bouma, J., Using soil survey data for quantitative land evaluation. Adv. Soil Sci., 1989, 9, 177–213.
  • Jarvis, N. J. et al., Indirect estimation of near-saturated hydraulic conductivity from readily available soil information. Geoderma, 2002, 108, 1–17.
  • Nemes, A., Rawls, W. J. and Pachepsky, Y. A., Influence of organic matter on the estimation of saturated hydraulic conductivity. Soil Sci. Soc. Am. J., 2005, 69, 1330–1337.
  • Moosavi, A. K. and Sepaskhah, A. R., Pedotransfer functions for prediction of near saturated hydraulic conductivity at different applied tensions in medium texture soils of a semi-arid region. Plant Knowl., 2012, 1(1), 1–9.
  • Aminifard, M. and Siosemarde, M., Relationship between the saturated hydraulic conductivity and the particle size distribution. Indian J. Fundam. Appl. Life Sci., 2014, 4(4), 73–80.
  • Aimrun, W. and Amin, M. S. M., Pedo-transfer function for saturated hydraulic conductivity of low land paddy soils. Paddy Water Environ., 2009, 7, 217–225.
  • Jarvis, N., Koestel, J., Messing, I., Moeys, J. and Lindah, A., Influence of soil, land use and climatic factors on the hydraulic conductivity of soil. Hydrol. Earth Syst. Sci., 2013, 17, 5185–5195.
  • Arshad, R. R., Sayyad, G. H., Mosaddeghi, M. and Gharabaghi, B., Predicting saturated hydraulic conductivity by artificial intelligence and regression models. ISRN Soil Sci., 2013; http://dx.doi.org/10.1155/2013/308159.
  • Nath, N. T. and Bhattacharya, K. G., Influence of soil texture and total organic matter content on soil hydraulic conductivity. Int. Res. J. Chem., 2014, 1(1), 002–009.
  • Sarki, A., Mirjat, M. S., Mahessar, A. A., Kori, S. M. and Qureshi, A. L., Determination of saturated hydraulic conductivity of different soil texture materials. J. Agric. Vet. Sci., 2014, 7(12), 56–62.
  • Patle, G. T., Sikar, T. T., Rawat, K. S. and Singh, S. K., Estimation of infiltration rate from soil properties using regression model for cultivated land. Geol. Ecol. Landsc., 2018; https://doi.org/ 10.1080/24749508.2018.1481633.
  • Mbagwu, J. S. C., Saturated hydraulic conductivity in relation to physical properties of soils in the Nsukka Plains, south eastern Nigeria. Geoderma, 1995, 68, 51–66.
  • Pikul, J. L. and Allmaras, R. R., Physical and chemical properties of a Haploxeroll after fifty years of residue management. Soil Sci. Soc. Am. J., 1986, 50, 214–219.
  • Rawls, W. J., Nemes, A. and Pachepky, Y. A., Effect of soil organic matter on soil hydraulic properties. In Development of Pedotransfer Functions in Soil Hydrology (eds Pachepsky, Y. A. and Rawls, W. J.), Elsevier, Amsterdam, 2005, pp. 95–114.

Abstract Views: 337

PDF Views: 90




  • Pedo-Transfer Functions for Saturated Hydraulic Conductivity of Cultivated Soils in the Mid Hills of Sikkim

Abstract Views: 337  |  PDF Views: 90

Authors

G. T. Patle
Department of Irrigation and Drainage Engineering, College of Agricultural Engineering and Post Harvest Technology, Ranipool 737 135, India
P. C. Vanlalnunchhani
Department of Agricultural Engineering, North Eastern Regional Institute of Science and Technology, Nirjuli 791 109, India

Abstract


In this study, pedotransfer functions (PTFs) are developed for saturated hydraulic conductivity (Ks) using multiple linear regression (MLR) technique for the cultivated terraced land of East Sikkim district, North East India. Soil samples were collected for 29 stations and Ks values were measured using the constant head permeameter. The various combinations of measured soil properties, including percentage of sand, silt, clay, bulk density (BD), particle density (PD), porosity, organic carbon (OC) content were used for the development of the models. The Ks value varied from 0.97 to 29.38 cm/day and the mean value was 8.04 cm/day in the study area. The correlation between predicted and measured values was found to be better for the combination, including five input variables. The results indicated a negative correlation of Ks with silt, clay and BD, whereas sand, PD, OC and porosity had a positive correlation. The recommended MLR model 5 consisting of five input variables for the prediction of Ks in the study area had R2 values of 0.81 and 0.83 during model development and model validation, and showed goodness-of-fit with the observed Ks value. The PTFs developed in this study would be helpful for the planning and design of water resources structures in the hilly state of Sikkim.

Keywords


Cultivated Land, Multiple Linear Regression, Pedotransfer Functions, Saturated Hydraulic Conductivity, Soil Property.

References





DOI: https://doi.org/10.18520/cs%2Fv118%2Fi5%2F771-777