11 May 2021
11 May 2021
Status: a revised version of this preprint is currently under review for the journal HESS.

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

Anna Msigwa1,2, Celray James Chawanda2, Hans Charles Komakech1, Albert Nkwasa2, and Ann van Griensven2,3 Anna Msigwa et al.
  • 1The Nelson Mandela African Institution of Science and Technology, Arusha 447, Tanzania
  • 2Department of Hydrology and Hydraulic Engineering, Vrije Universiteit, Pleinlaan 2 -1050, 1050 Brussel, Belgium
  • 3IHE-Delft Institute for Water Education; Westvest 7, 2611 AX Delft, The Netherlands

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.

Anna Msigwa et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-171', Anonymous Referee #1, 19 May 2021
  • RC2: 'Comment on hess-2021-171', Anonymous Referee #2, 14 Jun 2021
  • RC3: 'Comment on hess-2021-171', Anonymous Referee #3, 30 Jun 2021
  • EC1: 'Editor Comment on hess-2021-171', Elena Toth, 30 Jun 2021
    • AC1: 'Reply on EC1', Anna Msigwa, 30 Jun 2021

Anna Msigwa et al.

Anna Msigwa et al.


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Short summary
Agro-hydrological model applications in Africa basins do not represent different cropping seasons as they exist. Seasonal land-use dynamic represented in SWAT+ improved the model performance: the PBIAS reduced by 7.8 % and the NSE increased from −0.46 to 0.4 for monthly ET analysis as compared with remote sensing ET. The representation of season land-use dynamics is essential to correctly simulate the agricultural (blue and green) water consumption in African cultivated catchments.