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

Data sets

The shuttle radar topography mission (https://cgiarcsi.community/data/srtm-90m-digital-elevation-database-v4-1/) T. G. Farr, P. A. Rosen, E. Caro, R. Crippen, R. Duren, S. Hensley, M. Kobrick, M. Paller, E. Rodriguez, and L. Roth https://doi.org/10.1029/2005RG000183

Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6 (https://luh.umd.edu/) G. C. Hurtt et al. https://doi.org/10.5194/gmd-13-5425-2020

Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions (https://www.isric.org/projects/africa-soil-information-service-afsis) T. Hengl, G. B. M. Heuvelink, B. Kempen, J. G. B. Leenaars, M. G. Walsh, K. D. Shepherd, A. Sila, R. A. MacMillan, J. M. de Jesus, L. Tamene, and J. E. Tondoh https://doi.org/10.1371/journal.pone.0125814

Climate impacts on global agriculture emerge earlier in new generation of climate and crop models (10.5281/zenodo.5062513) J. Jägermeyr et al. https://doi.org/10.1038/s43016-021-00400-y

Global nitrogen and phosphorus fertilizer use for agriculture production in the past half century: shifted hot spots and nutrient imbalance (10.1594/PANGAEA.863323) C. Lu and H. Tian https://doi.org/10.5194/essd-9-181-2017

EartH2Observe, WFDEI and ERA-Interim data Merged and Bias-corrected for ISIMIP (EWEMBI) S. Lange https://doi.org/10.5880/PIK.2016.004

Global map of irrigation areas version 5 Siebert, S., Henrich, V., Frenken, K., and Burke, J. https://www.fao.org/aquastat/en/geospatial-information/global-maps-irrigated-areas/latest-version/

Model code and software

Agricultural land use and crop management implementation in large-scale SWAT+ model applications A. Nkwasa https://doi.org/10.5281/zenodo.5797553

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Short summary
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.