Preprints
https://doi.org/10.5194/egusphere-2024-2258
https://doi.org/10.5194/egusphere-2024-2258
31 Jul 2024
 | 31 Jul 2024

Coupled water-carbon modelling in data-limited sites: a new approach to explore future agroforestry scenarios

Salim Goudarzi, Chris Soulsby, Jo Smith, Jamie Lee Stevenson, Alessandro Gimona, Scot Ramsay, Alison Hester, Iris Aalto, and Josie Geris

Abstract. Agroforestry is considered an important strategy for mitigating against, and adapting to, climate change. Questions yet remain regarding the potential impacts of different tree species on water/carbon cycling at different locations, scales and under different climatic conditions. There is an urgent need for numerical models capable of quantifying agroforestry impacts on a host ecosystem services including carbon sequestration and soil water/river flow regulation. A key challenge in modelling agroforestry systems is that they depend heavily on soil moisture as the main driver of many biogeochemical processes. Soil moisture itself is highly variable with soil properties (and therefore with location) but also with depth. Given that target sites for agroforestry are often ungauged, location-specific agroforestry modelling must inevitably rely only on data available from satellites and/or nearby weather stations which do not typically cover the subsurface, i.e., there is an incommensurability between data-availability and system complexity. To overcome this, we propose RSEEP, a new ecohydrological model that only requires rainfall, potential evapotranspiration, and surface soil moisture for its calibration. We demonstrate RSEEP’s capability in water cycling for a site in Scotland where soil moisture observations are available for different depths and vegetation types. We then couple RSEEP to the well-known RothC soil carbon model to (i) test RothC’s sensitivity to water cycling method, and to (ii) simulate water-carbon dynamics of three different silvo-pastoral agroforestry systems (all at 400 stems/ha density) in Scotland; these systems are: with evergreen conifer (Scots Pine), deciduous conifer (Hybrid Larch), and deciduous broadleaf (Sycamore) trees. We find that not including more accurate soil moisture accounting methods in RothC can significantly overestimate soil carbon stocks. Under the current future climate pathway (RCP6.0), 40 years after planting trees, above+below ground carbon storage can be 2–5 times (100–250 t/ha) higher under silvo-pasture than under pasture depending on species, with Larch having the highest potential and Sycamore the lowest. Larch also exhibits the highest potential for preserving soil moisture under drier conditions, but Pine shows the highest potential for river flow regulation under both wet and dry conditions at our site. The choice of species is therefore important and should be made site-specifically and based on the ecosystem service and management priorities/objectives. Examining our scenarios under drought- and flood-relevant conditions and scales is a logical next step.

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Salim Goudarzi, Chris Soulsby, Jo Smith, Jamie Lee Stevenson, Alessandro Gimona, Scot Ramsay, Alison Hester, Iris Aalto, and Josie Geris

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-2258', Anonymous Referee #1, 30 Sep 2024
    • AC1: 'Reply on RC1', Salim Goudarzi, 29 Nov 2024
  • RC2: 'Comment on egusphere-2024-2258', Anonymous Referee #2, 21 Nov 2024
    • AC2: 'Reply on RC2', Salim Goudarzi, 29 Nov 2024
Salim Goudarzi, Chris Soulsby, Jo Smith, Jamie Lee Stevenson, Alessandro Gimona, Scot Ramsay, Alison Hester, Iris Aalto, and Josie Geris
Salim Goudarzi, Chris Soulsby, Jo Smith, Jamie Lee Stevenson, Alessandro Gimona, Scot Ramsay, Alison Hester, Iris Aalto, and Josie Geris

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Short summary
Planting trees on farmlands is now considered as one of the potential solutions to climate change. Trees can suck CO2 out of our atmosphere and store it in their trunks and in the soil beneath them. They can promote biodiversity, protect against soil erosion and drought. They can even help reduce flood risk for downstream communities. But we need models that can tell us the likely impact of trees at different locations and scales. Our study provides such a model.