Transposability and evaluation of pedotranfer functions for predicting properties of water retention on soils of low chelif. Algeria

TRANSPOSABILITY AND EVALUATION OF PEDOTRANSFER FUNCTIONS FOR

PREDICTING PROPERTIES OF WATER RETENTION ON SOILS OF LOW

CHELIFF. ALGERIA.

Introduction

1

_{Sami Touil,}

1

_{Djamel Saidi,}

2

_{Aurore Degré}

1

_{Institute of agronomy, University of Hassiba BenBouali of Chlef, BP151, Chlef, Algeria;}

_{Soil – Water Systems, Univ. Liège, Gembloux Agro-Bio Tech, Belgium.}

 research has focused on the discussion of the ability of PTF to estimate more or less accurately the water content measured for the sample that have relatively the same kind of soil constituents.

 An important question remains about PTF’s transposability to others agropedoclimatic contexts. Models developed and validated in a particular bioclimatic context, were relatively little tested in other contexts.

Objectives

 The evaluation of PTF to estimate water

retention at field capacity pF 2.5 (-330 hPa) and at wilting point pF 4.2 (-15000 hPa) of some soils of Lower Cheliff . Algeria.

 Discuss the relevance of application of PTF in agropedoclimatic contexts different from those of their developments.

 134 samples collected from soils of Lower Cheliff  Eight (08) PTF selected.

 Evaluation Criteria: The root mean square error (RMSE), the Akaike information criterion (AIC)

the geometric mean error (GMER).

Authors

mathematical formalism

Number of

samples Origin of soils

Inputs

Pressure Sa Li Ar OM BD

Rawls et al. (1982) MRNL 2541 USA pF 2.5 + + +

pF 4.2 + +

Rawls et Brakensiek

(1985) MRNL 5320 USA

pF 2.5 + + +

pF 4.2 + + +

Vereecken et al(1989) MRNL 182 Belgium pF 2.5 + + + + +

pF 4.2 + + + + +

Saxton et al. (1986) MRNL np _USA

pF 2.5 + +

pF 4.2 + +

Rosetta-H3

(Schaap et al. 2002) ANN 24691

North America and Europe pF 2.5 + + + ₊ pF 4.2 + + + ₊ Campbell (1974) MRNL 1400 USA pF 2.5 + + + pF 4.2 + + + Ghorbani Dashtak

Homaee (2004) Type1 MRNL 234 Iran

pF 2.5 + ₊ + + pF 4.2 + Ghorbani Dashtak Homaee (2004) Type3 MRL/ANN _{234 Iran} pF 2.5 + + + pF 4.2 + + +

OM: organic matter, BD: bulk density, Ar, Li, Sa: clay, silt and sable.np: unspecified, MRL; MRNL: Multiple

regression linear and nonlinear ANN: artificial neural network

0.10 0.20 0.30 0.40 0.50 0.60 - 0.20 0.40 0.60 0.80

Vereecken And al.(1989)

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0 0.2 0.4 0.6

Vereecken And al.(1989)

0.05 0.10 0.15 0.20 0.25 0.30 0.35 0 0.2 0.4 0.6 0.8 Campbell(1974) 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0 0.2 0.4 0.6 Campbell(1974) 0.10 0.20 0.30 0.40 0.50 0.60 - 0.50 1.00

Saxton And al.(1986)

0 0.1 0.2 0.3 0.4 0.5 0 0.2 0.4 0.6

Saxton And al.(1986)

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0 0.1 0.2 0.3 0.4 0.5

Rawls And al.(1982)

0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 - 0.20 0.40 0.60 0.80

Ghorbani dashtaki And Homaee (2004) type1 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0 0.2 0.4 0.6

Ghorbani dashtaki And Homaee (2004) type1 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 - 0.20 0.40 0.60 0.80

Ghorbani dashtaki And Homaee (2004) type3 0 0.05 0.1 0.15 0.2 0.25 0.3 0 0.2 0.4 0.6

Ghorbani dashtaki And Homaee (2004) type3 0 0.1 0.2 0.3 0.4 0 0.2 0.4 0.6 0.8

Rawls And Brakensiek (1989) 0 0.2 0.4 0.6 0.8 0 0.2 0.4 0.6

Rawls And Brakensiek (1989) 0.10 0.20 0.30 0.40 0.50 0.60 0.70 - 0.20 0.40 0.60 0.80

Rawls And al.(1982)

The application data The Mathematical Formalisms Organic Matter

The geographical origin of data sets.

The choice of inputs and

methods adopted in building of PTF (MRL, MRNL, ANN)

 The results showed that the best models in the estimation are Rawls et al, (1982) and GH-1 (2004), at field capacity and wilting point

respectively.

Selection Tools

Results

Discussions

Conclusion

 The transferability of PTF derived from a wide

range of soil variation (heterogeneity) behave much better than other models derived from data sets

from specific agropedoclimatic contexts.

 The mathematical formulation of the PTF is a

important element in improving the estimation of the soil water retention.

References

 Pachepsky, Y.A, Rawls, W.J. 2004, development of Pedotransfer functions in soil hydrology.

 Donatelli M., Wösten J.H.M., Belocchi G., Acutis M.,

Nemes A., Fila G., 2004, Methods to evaluate pedotransfer

functions. Elsevier B.V. 30, 357–411.

 S. Ghorbani Dashtaki., M. Homaee &

H. Khodaverdiloo. 2010, Derivation and validation of

pedotransfer functions for estimating soil water retention curve using a variety of soil data

0.10 0.20 0.30 0.40 0.50 - 0.20 0.40 0.60 0.80 Rosetta-H3 0.05 0.10 0.15 0.20 0.25 - 0.20 0.40 0.60 Rosetta-H3

  At field capacity ( -330 hpa) (measure vs estimation)

  At wilting point ( -15000 hpa) (measure vs estimation)

 At field capacity ( -330 hpa)

 At wilting point ( -15000 hpa)

0.200 0.400 0.600 0.800 1.000 1.200 Ө (330 hpa) GMER RMSE 0.200 0.400 0.600 0.800 1.000 1.200 1.400 Ө (15000 hpa)