| Title: | Evaluation of irrigation water resources availability and climate change impacts—A case study of Mwea irrigation scheme, Kenya |
| Authors: | Akoko, G., T. Kato and L.H. Tu |
| Year: | 2020 |
| Journal: | Water |
| Volume (Issue): | 12(9) |
| Pages: | |
| Article ID: | 2330 |
| DOI: | 10.3390/w12092330 |
| URL (non-DOI journals): | |
| Model: | SWAT |
| Broad Application Category: | hydrologic only |
| Primary Application Category: | model and/or data interface |
| Secondary Application Category: | climate change assessment |
| Watershed Description: | 1,545 km^2 combined Thiba and Tobere Rivers, which are tributaries of the Tana River located in Kenya. |
| Calibration Summary: | |
| Validation Summary: | |
| General Comments: | |
| Abstract: | Rice is an important cereal crop in Kenya, where it is mainly grown in the Mwea Irrigation Scheme, MIS. The serious challenges of MIS include low water use effciency and limited available water resources. The objective of this study is to analyze the current and future irrigation water resource availability for the improvement of future water management. A Soil Water Assessment Tool (SWAT), a public domain software supported by the United States Department of Agriculture’s Agricultural Research Service in Bushland, TX, USA, was used to estimate the current and future water resources availability from the MIS’s main irrigation water supply sources (River Thiba and River Nyamindi). CropWat, a computer program developed by the Land and Water Division of the Food and Agriculture Organization (FAO), Rome, Italy, was used to estimate irrigation water requirements from 2013–2016 and into the future (2020–2060 and 2061–2099). Future climatic data for total available flow and irrigation requirement estimations were downloaded from three General Circulation Models (GCMs). The data was bias corrected and down-scaled (with observed data) using a Climate Change Toolkit, a toolkit for climate change analysis developed by the Water Weather and Energy Ecosystem, Zurich, Switzerland. The results indicated that the highest irrigation water deficits were experienced in July and August based on the existing cropping pattern. Under a proposed future pattern, estimates show that MIS will experience water deficits mainly from June to October and from January to February. This study recommends that MIS management should put into strong consideration the simulated future estimates in irrigation water availability for the improvement of water management. |
| Language: | English |
| Keywords: | water resources availability; SWAT; climate change |