Regional water cycle sensitivity to afforestation: synthetic numerical experiments for tropical Africa

Abstract

Afforestation as a climate change mitigation option has been the subject of intense debate and study over the last few decades, particularly in the tropics where agricultural activity is expanding. However, the impact of such landcover changes on the surface energy budget, temperature, and precipitation remains unclear as feedbacks between various components are difficult to resolve and interpret. Contributing to this scientific debate, regional climate models of varying complexity can be used to test how regional climate reacts to afforestation. In this study, the focus is on the gauged Nzoia basin (12,700 km2) located in a heavily farmed region of tropical Africa. A reanalysis product is dynamically downscaled with a coupled atmospheric-hydrological model (WRF-Hydro) to finely resolve the land-atmosphere system in the Nzoia region. To overcome the problem of Nzoia river flooding over its banks we enhance WRF-Hydro with an overbank flow routing option, which improves the representation of daily discharge based on the Nash-Sutcliffe efficiency and Kling-Gupta efficiency (from −2.69 to 0.30, and −0.36 to 0.63, respectively). Changing grassland and cropland areas to savannas, woody savannas, and evergreen broadleaf forest in three synthetic numerical experiments allows the assessment of potential regional climate impacts of three afforestation strategies. In all three cases, the afforestation-induced decrease in soil evaporation is larger than the afforestation-induced increase in plant transpiration, thus increasing sensible heat flux and triggering a localized negative feedback process leading to more precipitation and more runoff. This effect is more pronounced with the woody savannas experiment, with 7% less evapotranspiration, but 13% more precipitation, 8% more surface runoff, and 12% more underground runoff predicted in the Nzoia basin. This study demonstrates a potentially large impact of afforestation on regional water resources, which should be investigated in more detail for policy making purposes.

Afforestation in West Africa: potential benefits and trade-offs on regional climate extremes

“…This system includes the Weather Research and Forecasting model (WRF;version 4.4;Skamarock et al, 2019) and version 5.2 of the WRF-Hydro hydrological module (Gochis et al, 2020). WRF stands out as one of the widely used Regional Climate Models (RCMs) known for its alignment with observations across various regions (e.g., Arnault et al, 2023;Posada-Marín et al, 2019;Sy et al, 2024). The coupled WRF-Hydro system can resolve atmospheric motion equations on a three-dimensional grid, offering parameterization options for subgridscale physical processes like radiation, turbulence, cumulus convection, cloud microphysics, and terrestrial hydrology (Arnault et al, 2021;Fersch et al, 2020;Furnari et al, 2022;Laux et al, 2021;Rummler et al, 2019;Zhang et al, 2019).…”

“…The coupled WRF-Hydro system can resolve atmospheric motion equations on a three-dimensional grid, offering parameterization options for subgridscale physical processes like radiation, turbulence, cumulus convection, cloud microphysics, and terrestrial hydrology (Arnault et al, 2021;Fersch et al, 2020;Furnari et al, 2022;Laux et al, 2021;Rummler et al, 2019;Zhang et al, 2019). This setup, incorporating surface and subsurface lateral flow with dynamic vegetation descriptions, captures subgrid-scale biophysical effects of LULCC and considers terrestrial hydrological processes (Arnault et al, 2023).…”

“…While climate models can elucidate the effects of afforestation, the model-based results are still subject to uncertainties in representing local biophysical processes (Ge et al, 2021;Sy & Quesada, 2020). One challenge is that landatmosphere interactions in climate models are typically simplified, especially at the river basin scale (Arnault et al, 2021(Arnault et al, , 2023. Studies using coupled atmospheric-hydrological models, such as the WRF-Hydro model, have shown that incorporating surface and subsurface lateral water flow enhances runoff simulation and modifies the atmospheric water cycle, generally leading to increased evapotranspiration and precipitation (e.g., Arnault et al, 2021Arnault et al, , 2023Fersch et al, 2020;Furnari et al, 2022;Rummler et al, 2019).…”

“…One challenge is that landatmosphere interactions in climate models are typically simplified, especially at the river basin scale (Arnault et al, 2021(Arnault et al, , 2023. Studies using coupled atmospheric-hydrological models, such as the WRF-Hydro model, have shown that incorporating surface and subsurface lateral water flow enhances runoff simulation and modifies the atmospheric water cycle, generally leading to increased evapotranspiration and precipitation (e.g., Arnault et al, 2021Arnault et al, , 2023Fersch et al, 2020;Furnari et al, 2022;Rummler et al, 2019). However, this local positive feedback is not supported by observational data (Duveiller et al, 2018b(Duveiller et al, , 2020Spracklen et al, 2018) and is often neglected in LULCC-based modeling studies (Abiodun et al, 2013;Achugbu et al, 2023;Camara et al, 2022;Diba et al, 2018;Ingrosso & Pausata, 2024;Smiatek & Kunstmann, 2023;Sy et al, 2017;Sy & Quesada, 2020).…”

“…Here, for the first time, high-resolution LULCC (deforestation/afforestation) simulations at 3 km, covering the period from 2011 to 2022, were conducted using the fully coupled WRF-Hydro system. This system incorporates surface and subsurface lateral flow while dynamically describing vegetation (Arnault et al, 2016(Arnault et al, , 2023Gochis et al, 2020). Notably, the highresolution experiments under different LULCC scenarios with WRF-Hydro enable the capture of fine-scale biophysical effects of LULCC on climate extremes, accounting for surface hydrological processes.…”