EVALUATING THE IMPACT OF SUSTAINABLE LAND MANAGEMENT ON RUNOFF IN WUTAME MICRO-WATERSHED OF OMO GIBE BASIN, ETHIOPIA

Abstract

Evaluating the impacts of sustainable land management (SLM) interventions on surface water resources is essential to report the effectiveness of the investment. A significant amount of resources has been invested on SLM in Ethiopian watersheds. However, there is no clear understanding of the impact of the interventions on hydrological processes. SLM is introduced in Wutame micro-watershed whereas rainfall, groundwater level and stream water level, flow velocity data were collected by citizen scientists. The goals of this study are to evaluate the potential of the field and remote sensing data to map hillside, degraded side, and valley of micro-watershed, examine the usefulness of citizen science data to calibrated a rainfall-runoff model i.e, Land Resource Management (LRM), and quantify runoff change caused by watershed management. To address these objectives, a map of a hillside, degraded side, and valley of micro-watershed was prepared. Analysis of hydro-meteorological data, sensitivity analysis, model calibration (2017 - 2018), and validation (2020) was carried out. Evaluation of the model, performance was evaluated using Nash-sutcliffe efficiencies (NSE) and Relative volume error (RVE) objective functions. The model efficiency on the biweekly time step for discharge simulation during calibration was NSE=0.76 and RVE=+25%. However, the model performance deteriorated for the validation period. The total simulated discharge was 642.93 mm/year and 616.8 mm/year before and after SLM interventions, respectively. The simulated discharge was decreased by 26.13 mm /year as a result of the interventions. The baseflow increased from 248.7 mm/year to 270 mm/year as a result of the interventions. The study shows that the watershed management interventions have an overall positive impact on the hydrological process. The findings of this research indicate that the integration of citizen science and remote sensing information for modeling provides an opportunity to evaluate the impact of watershed interventions. The calibration result showed that quality control is needed to increase the usability of citizen science. This study shows that citizen science fills data gaps for hydrological impact evaluation of SLM but it requires strong coordination between communities, woreda experts, and relevant stakeholders.