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Predicting hydraulic properties of seasonally impounded soils

Published online by Cambridge University Press:  08 October 2009

N. G. PATIL ,
G. S. RAJPUT ,
R. K. NEMA  and
R. B. SINGH
N. G. PATIL*
Affiliation:
NBSS & LUP, Shankarnagar P. O., Amravati road, Nagpur, India
G. S. RAJPUT
Affiliation:
Faculty, College of Agricultural Engineering J. N. K. V. V., Adhartal P. O., Jabalpur, India
R. K. NEMA
Affiliation:
Faculty, College of Agricultural Engineering J. N. K. V. V., Adhartal P. O., Jabalpur, India
R. B. SINGH
Affiliation:
Faculty, College of Agricultural Engineering J. N. K. V. V., Adhartal P. O., Jabalpur, India
*
*To whom all correspondence should be addressed. Email: [email protected]
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Summary

Agricultural crop management decisions often require data on hydraulic properties of soils. Little information is available on hydraulic properties of clay soils that are impounded by rainwater (known as ‘Haveli’ lands) every year during the monsoon season in large tracts of Madhya Pradesh in India. Estimating hydraulic properties using global pedotransfer functions (PTFs) is one possible way to collect such information. Rules in the widely used global PTF Rosetta were executed to obtain estimates of two important hydraulic properties, namely soil water retention characteristics (SWRC) and saturated hydraulic conductivity (Ks). SWRC estimates obtained with maximum input (particle size distribution, bulk density, field capacity and permanent wilting point) in Rosetta were relatively closer to the laboratory-measured data as compared with the estimates obtained with lower levels of input. Root mean square error (RMSE) of estimates ranged from 0·01 to 0·05 m3/m3. Hierarchical PTFs to predict Ks from basic soil properties were derived using statistical regression and artificial neural networks. Evaluation of these indicated that neural PTFs were acceptable and hence could be used without loss of accuracy.

Type
Crops and Soils
Information
The Journal of Agricultural Science , Volume 148 , Issue 2 , April 2010 , pp. 159 - 170
Copyright
Copyright © Cambridge University Press 2009

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