Establishing relationship between measured and predicted soil water characteristics using SOILWAT model in three agro-ecological zones of Nigeria
OrevaOghene Aliku and Suarau O. Oshunsanya
Department of Agronomy, University of Ibadan, Nigeria
Received: 27 Jun 2016 – Accepted for review: 11 Aug 2016 – Discussion started: 15 Aug 2016
Abstract. Soil available water (SAW) affects soil nutrients availability and consequently affects crop performance. However, field determination of SAW for effective irrigated farming is laborious, time consuming and expensive. Therefore, experiments were initiated at three agro-ecological zones of Nigeria to compare the measured laboratory and predicted soil available water using SOILWAT model for sustainable irrigated farming.
One hundred and eighty soil samples were collected from the three agro-ecological zones (Savannah, Derived savannah and rainforest) of Nigeria and analysed for physical and chemical properties. Soil texture and salinity were imputed into SOILWAT model (version 6.1.52) to predict soil physical properties for the three agro-ecological zones of Nigeria. Measured and predicted values of field capacity, permanent wilting point and soil available water were compared using T-test.
Predicted soil textural classes by SOILWAT model were similar to the measured laboratory textural classes for savannah, derived savannah and rainforest zones. However, bulk density, maximum water holding capacity, permanent wilting point and soil available water were poorly predicted as significant (p < 0.05) differences existed between measured and predicted values. Therefore, SOILWAT model could be adopted for predicting soil texture for savannah, derived savannah and rainforest zones of Nigeria. However, the model needs to be upgraded in order to accurately predict soil water characteristics of the aforementioned locations for sustainable irrigation planning.
Aliku, O. and Oshunsanya, S. O.: Establishing relationship between measured and predicted soil water characteristics using SOILWAT model in three agro-ecological zones of Nigeria, Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-165, 2016.