Articles | Volume 26, issue 1
Hydrol. Earth Syst. Sci., 26, 71–89, 2022
https://doi.org/10.5194/hess-26-71-2022
Hydrol. Earth Syst. Sci., 26, 71–89, 2022
https://doi.org/10.5194/hess-26-71-2022
Research article
 | Highlight paper
06 Jan 2022
Research article  | Highlight paper | 06 Jan 2022

Improved representation of agricultural land use and crop management for large-scale hydrological impact simulation in Africa using SWAT+

Albert Nkwasa et al.

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Revised manuscript accepted for HESS
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Cited articles

Abaci, O. and Papanicolaou, A. T.: Long-term effects of management practices on water-driven soil erosion in an intense agricultural sub-watershed: Monitoring and modelling, Hydrol. Process. Int. J., 23, 2818–2837, 2009. 
Alemayehu, T., van Griensven, A., and Bauwens, W.: Evaluating CFSR and WATCH Data as Input to SWAT for the Estimation of the Potential Evapotranspiration in a Data-Scarce Eastern-African Catchment, J. Hydrol. Eng., 21, 05015028, https://doi.org/10.1061/(ASCE)HE.1943-5584.0001305, 2016. 
Alemayehu, T., van Griensven, A., Woldegiorgis, B. T., and Bauwens, W.: An improved SWAT vegetation growth module and its evaluation for four tropical ecosystems, Hydrol. Earth Syst. Sci., 21, 4449–4467, https://doi.org/10.5194/hess-21-4449-2017, 2017. 
Arnold, J., Bieger, K., White, M., Srinivasan, R., Dunbar, J., and Allen, P.: Use of decision tables to simulate management in SWAT+, Water, 10, 713, https://doi.org/10.3390/w10060713, 2018. 
Arnold, J. G., Srinivasan, R., Muttiah, R. S., and Williams, J. R.: Large Area Hydrologic Modeling and Assessment Part I: Model Development1, JAWRA J. Am. Water Resour. Assoc., 34, 73–89, https://doi.org/10.1111/j.1752-1688.1998.tb05961.x, 1998. 
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We present an approach on how to incorporate crop phenology in a regional hydrological model using decision tables and global datasets of rainfed and irrigated cropland with the associated cropping calendar and management practices. Results indicate improved temporal patterns of leaf area index (LAI) and evapotranspiration (ET) simulations in comparison with remote sensing data. In addition, the improvement of the cropping season also helps to improve soil erosion estimates in cultivated areas.