Articles | Volume 26, issue 1
https://doi.org/10.5194/hess-26-71-2022
https://doi.org/10.5194/hess-26-71-2022
Research article
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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, Celray James Chawanda, Jonas Jägermeyr, and Ann van Griensven

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This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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A High-Resolution Global SWAT+ Hydrological Model for Impact Studies
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Combined impacts of climate and land-use change on future water resources in Africa
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Representation of seasonal land use dynamics in SWAT+ for improved assessment of blue and green water consumption
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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.
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