Evaluation of climate change impacts on irrigated paddy fields by water balance analysis : A case study of Mwea irrigation scheme, Kenya

概要

Rice is the third most important cereal crop in Kenya (after maize and wheat). It is mainly grown in Mwea Irrigation Scheme (MIS), which is one of the largest irrigation schemes in East Africa, and in Kenya. The scheme faces several challenges, the main one being adequate irrigation water supply to meet the crop water demand. The East African region has an immense irrigation potential which is largely underexploited. The region faces several challenges such as inadequate irrigation infrastructure, poor water management and unreliable water supply. In this regard, effective and adaptive planning measures are required to be put in place to tap into the irrigation potential. Several climate change impact studies in the East African region have analyzed blue water resources (e.g. fresh water from surface streams, reservoirs and groundwater) in the context of stream flow, groundwater, sediment yield, and weather changes.

Analysis of the climate change impacts of green water resources (i.e. the precipitation that temporarily stays on vegetation or stored in soil that eventually evapotranspirates back to the atmosphere) have been not been conducted on the same level at the catchment scale compared to blue water resources. This research therefore aims to develop an in-depth and unique methodological approach that analyzes both blue water and green water with an objective to contribute to more effective planning and management of future irrigation schemes within East Africa and subsequently tap into the development potential of irrigation. The analysis of the blue water aspect i.e. the water supply is evaluated in terms of total available flow using the Soil Water Assessment Tool (SWAT) model while the green water resources i.e. the water demand is evaluated in terms of irrigation water requirement using the CropWat model based on cropping patterns obtained from MIS. Soil Water Assessment Tool (SWAT) model is a hydrological modeling tools that can be used to model and predict some of the hydrological processes. CropWat is a computer program developed by the Land and Water Division of the Food and Agriculture Organization (FAO) for planning and management of irrigation. Climate Change Toolkit (CCT) was used to analyze the climatological data that was used to simulate the future total available flow and future irrigation water requirements.

The first chapter of this thesis reviews the application of SWAT model in Africa various peer-reviewed scientific journals listed on the SWAT website database which is supported by the Centre for Agricultural and Rural Development (CARD). These studies were categorized into five areas, namely applications considering: water resources and streamflow, erosion and sedimentation, land use management and agricultural related context, climate change context and model parameterization and dataset inputs. This chapter sets out to paper summarize the key findings from the identified studies. Challenges and advantages of SWAT model application which range from data availability and prediction uncertainties to the models capability in various applications are incorporated. Discussions on considerations for future simulations such as data sharing and potentials for better future analysis are also highlighted. Increased efforts in local data availability and a multi dimensional approach in future simulations are recommended.

The second chapter presents the methodological approach used, which forms an integral part of the uniqueness of this study. MIS was selected as it is one of the key areas on food security for Kenya and is the largest scheme in the country. This chapter highlights the rational for the integrated model analysis which was mainly guided by two considerations: the models capabilities in analyzing water resources and irrigation water requirements, and the availability of the collected data during the study. The chapter details the programs used and provides information on the study area. The third chapter estimated the total available flow i.e. the water supply that is available for use in irrigation at MIS. An outline of the data inputs to SWAT model were defined and the, model performance assessment. Current and future estimations of water supply are presented. In future scenario, the highest total available flow were observed of May, November and December; and the lowest in the month of February.

The fourth chapter estimated the irrigation water requirements i.e. water demand using CropWat model. The estimations are based on the current cropping pattern and a future proposed cropping pattern. The data sources and modeling using CropWat were elaborated. Chapter five quantifies the extent water supply is able to meet water demand i.e. water availability. It’s important to note that the water demand considered the irrigation water requirements, river environmental flow and existing water rights. The Water Stress Index was used to analyze the water availability.

Based on the WSI categorization, the results indicate a high over exploitation of water resources in the future scenario, particularly between the months of May to October. As MIS plans to incorporate a dam to store water and improve the water availability. A further analysis was done to estimate the proposed dam’s effective storage capacity in comparison to the water demand volume. The months of Jan-Feb and Jun-Sept were observed to have relatively high water demand volume requirement in comparison to the effective dam storage volume.

In conclusion, the results indicated that green water infrastructure development will not be able to address the inadequate water availability. Copping pattern will play an important role in the water management, particularly in the months between Jun-Jul during rice transplanting. This study aspires to contribute to water availability research by presenting a methodological framework for current and future water resource availability for irrigation planning and management in regions where data availability may be inadequate but there exists a future irrigation development potential. The approach of coupling of models offer a clearer and more detailed outlook for assessing climate change impacts not only in terms of river discharge/run off but also in terms of the irrigation water; hence contributing to more effective and adaptable planning measures for unlocking the irrigation potential.