Representation of seasonal land-use dynamics in SWAT+ for improved assessment of blue and green water consumption

Abstract

Abstract. In most (sub)-tropical African cultivated regions, more than one cropping cycle exists following the (one or two) rainy seasons. During the dry season, an additional cropping cycle is possible when irrigation is applied, which could result in 3 cropping seasons. In most agro-hydrological model applications such as SWAT+ in Africa, only one cropping season per year is represented. In this paper, we derived dynamic and static trajectories from seasonal land-use maps to represent the land- use dynamics following the major growing seasons, for the purpose of improving simulated blue and green water consumption from simulated evapotranspiration (ET) in SWAT+. This study builds upon earlier research that proposed an approach on how to incorporate seasonal land use dynamics in the SWAT+ model but mainly focused on the temporal pattern of LAI and tested the approach in a small catchment (240 km2). Together with information obtained from the cropping calendar, we implemented agricultural management operations for the dominant trajectory of each agricultural land-use class for the Kikuletwa basin (6650 km2 area coverage) in Tanzania. A comparison between the default SWAT+ (with static land use representation) set up, and a dynamic SWAT+ model (with seasonal land use representation) is done by spatial mapping of the evapotranspiration (ET) results. The results show that ET with seasonal representation is closer to remote sensing estimations, giving higher performance than default: the Root Mean Squared Error decreased from 181 to 69 mm/year; the percent bias decreased from 20 % to 13 % and Nash Sutcliffe Efficiency increased from −0.46 to 0.4. It is concluded that representation of seasonal land-use dynamics produces better ET results which provide better estimations of blue and green agricultural water consumption.