Agricultural management practices can have a significant impact on downstream water resources for humans and animals. Facing the need to increase agricultural production for a growing population, sustainable agricultural intensification (SAI) has been promoted in Sub-Saharan Africa to minimize the negative impacts of conventional agriculture. This SAI paradigm promotes practices that are site and community specific, yet many of the most popular practices (reduced tillage and drip irrigation) are given a blanket recommendation in East Africa without quantifying impacts specific to local soils and rainfall distributions. It is also important to determine how field-level impacts may scale when quantifying watershed-level outcomes such as water quantity and quality. This project seeks to understand the connections between field and watershed-level processes and impacts by testing the relationship in the Laikipia, Kenya watershed, where a steep rainfall gradient and varied large and smallholder farms provide a test case for this scaling at the edge of conservation savanna.
During this project, over 2 years of streamflow and soils data were collected across over 40 sites in the Mount Kenya region. These data are currently under review as part of a publication and will be imminently available publicly in an open-data repository on CUAHSI HydroShare.
The CUENCA link-and-node model was developed to test the research questions associated with this project. This model requires relatively few data inputs compared to other models and was developed to be sensitive to tillage practices.
This project was conducted at University of Florida under the advisement of Dr. Rafael Muñoz-Carpena and Dr. Cheryl Palm.
Field team developing rating curves to quantify stream flow.
The endangered Grevy's zebra lives downstream of the test watershed, and was used as an indicator species to test improved ecosystem outcomes based on SAI.
Smallholder agriculture featuring drip irrigation infrastructure.
Streamflow data collected over 2 years.
Soil sampling plan