Integrating EO Data, Hydrological Modeling to Study Effects of Landcover Change on Flow Regime: Lunsemfwa Basin Zambia
Kampata, J.M; Rientjes, T.H.M; Timmermans, J; Vekerdy, Z

Advances in Earth Observation (EO) have great potential for use in water resource management. Effective monitoring, planning and evaluation of natural resources usage, such as water, can be improved using remote sensing.

The Lunsemfwa River Basin in Zambia faces increasing water demands especially for irrigation and hydropower. It also faces threats of land degradation due to deforestation and agriculture. Like many river basins in Zambia and elsewhere in Africa, hydrological data is scarce making the applications of models challenging. Especially here then remote sensing data will play a vital role in developing and sustaining the hydrological balance.

To meet the various needs of different stake holders, the water resources need to be monitored carefully and effects on the balance such as the land cover change need to be identified. However such changes on hydrological regimes are not consistent, thus the need for continued research to understand the effects at various sites.

This study aims to introduce and apply satellite remote sensing derived data as input parameter to support large]scale hydrogeological modelling in in the Lunsemfwa River Basin in Zambia. This covers an area of 21 944 km2. Due to the scarce hydrological data in the Lunsemfwa River Basin, EO data will be used in the hydrological modelling.

The study will provide an insight in integrating EO data and hydrological modelling to study effects of land cover change on the flow regime. Scenarios will be developed using the hydrological model to evaluate the impact of deforestation and extension of agricultural activities on the flow regime of the river, with special focus on the low]flow periods. Spatial and temporal availability of the water resources will be quantified; it will be possible to define water management ehot spotsf, where extreme situations may occur.

The results will help land use planners and catchment managers to estimate the effects of interactions with the land cover. The developed methods will enable water managers extending the analysis to other sub]catchments of the Zambezi Basin.