Integrated Assessment Tools in Support of Futuristic Climate Change Towards Rice Production in Nigeria

Abstract

CROPWAT 8.0 model has been an effective multistage climatic induced crop responses to simulate reference evapotranspiration (ET0), effective rainfall, and actual crop evapotranspiration (ETc) which can be of help in determining embedded water (virtual water) in growing a crop and planning irrigation scheduling. This chapter examines the effects of different lengths of recorded morpho-climatic data in predicting rice cultivation for further development at the Lower Benue River Basin, Nigeria using integrated assessment tools (IAT). The explored IAT in the CROPWAT model, the principal component analysis (PCA) technique, and the multivariate inferential regression were utilised in quantifying the basin hydrological response to the varied 10, 25, and 35 years available historical meteorological data. The PCA segregate the physical upper and lower limit of rainfall over the basin to serve as a baseline in quantifying available water and subsequence irrigation schedule planning to facilitate how to manage the watershed in an integrated manner while the multivariate inferential regression relates the past topography conditions to project the future climate scenario. The results show that the net irrigation water requirement per the varied years’ length was 711m3/ha; 1115 m3/ha and 1343 m3/ha respectively, while the average value of 36.05% for ET0 and 49.20% for ETc propose air temperature as a more significant climatic driver irrespective of the varied years’ length of data than precipitation. The effective rainfall findings are possibly accurately predicted by the CROPWAT 8.0 model with more lengths of recorded morpho-climatic datasets, thus supporting futuristic climatic impacts assessment for rice cultivation development. These results are of utmost importance to the stakeholders’ consideration of virtual water strategies for a sustainable transboundary river basin management in extreme hydrological events towards abundant rice production.