Modeling Soil-water Retention of Southwestern Nigeria

Modeling Soil-water Retention of Southwestern Nigeria

by

Anthony Imoudu Oyeogbe Doctoral Fellow, Division of Agronomy, Indian Agricultural Research Institute, New Delhi

Introduction  Soil water is defined as the infiltrated water shallow enough to be used by plants(Kern, 2002).  Water retention is a basic hydrophysical characteristic of soil, described as the dependence between soil water content and soil water potential.  The spatial distribution of water characteristics in the soil is also an important factor in investigations of the consequences of climate change (Walczak et al.,2001).

 Intensive research has been done for the formulation of models, which enables soil water retention to be determined on the basis of easily measured soil properties such as texture, bulk density and organic matter content (Gupta and Larson, 1979; Saxton and Rawls,2006).

Texture predominately determines the water holding characteristics of most agricultural soils (Saxton et al. 1986).

Currently, available models have proven difficult to assemble and apply over a broad range of soil types. Thus, the Objectives of the study was:  To compare prediction made by SOILWAT model with measured soil parameters  To evaluate the general applicability and prediction accuracy of SOILWAT model for tropical soils

Soil-water Characteristics Model: Hydraulic Properties Calculator

Graphical input screen for the model

Site description •The research study was conducted in five states of Southwestern Nigeria on farmlands •Replicated core samples were collected at different depths(0-60cm) of the soil profiles

Map showing the sampled locations

Soil analyses Determination of solid and Liquid Phases of Soil  Particle Size Distribution  Bulk Density  Gravimetric Moisture Content  Field Capacity  Permanent Wilting Point  Available Water  Saturated Hydraulic Conductivity  Organic Carbon  Gravel Content

Statistical Procedure

 Coefficient of determination(R2) as a goodness-of-fit index  Root mean square error (RMSE) was computed .

Comparison of the simulated and measured soil water characteristics for each texture class Textural class Bulk density Sand Loamy sand Sandy loam Saturated hydraulic conductivity Sand Loamy sand Sandy loam Saturated moisture content Sand Loamy sand Sandy loam Field capacity Sand Loamy sand Sandy loam Permanent wilting point Sand Loamy sand Sandy loam Available water content Sand Loamy sand Sandy loam

Linear Regression R2

RMSE

0.59* 0.13ns 0.79*

1.86 0.55 0.46

0.00ns 0.12ns 0.13ns

28.46 29.01 68.83

0.64* 0.17ns 0.62*

19.12 19.27 28.64

0.38ns 0.17ns 0.76*

31.45 68.21 82.71

0.54* 0.52* 0.56*

9.12 8.27 9.73

0.19ns 0.17ns 0.55*

0.89 0.74 0.66

Relationship between Simulated vs Measured Soilwater Characteristics for Sandy loam soil

Verification of the Model Prediction ďƒ˜ SOILWAT model was found to provide a good prediction of the soil water characteristics for sandy loam soil; while for the sand and sandy clay loam, it was reasonably estimated. There appears to be a greater difficulty in estimating the soil water characteristics for loamy sand soil. ďƒ˜ It has been previously noted that it is particularly difficult to estimate the soil water characteristics from particle-size distribution for some texture class. The general soil categories includes: (i) soils that have high amount of coarse-size particles, mixed with few fines, and (ii) soils that have high amount of clay size particles (Fredlund et al., 2002; Hwang and Powers, 2003).The same trend was found to be true for the experimental/sampled soils.

Conclusions • The uncertainty associated with climatic changes and increasing population will pose heavy demands on water resources in the nearest future. Hence, integrated water management principles and cooperation will be required to develop sustainable systems and prevent disasters.

• The ability of SOILWAT to simulate soil water characteristics

for Sandy loam and Sand soils demonstrates the potential of the model when properly initialised and field measurement accurately taken.

Thank you !!