Cloud-base heights over different land-use classes
Learnings of a distributed LogTag network in and around the Guatemalan Cloud Forest
P.K. Trivedi (TU Delft - Civil Engineering & Geosciences)
J.T. van Hooff (TU Delft - Civil Engineering & Geosciences)
A. Sierra Delgado (TU Delft - Civil Engineering & Geosciences)
K.C.A. Laan (TU Delft - Civil Engineering & Geosciences)
A.C. Smook (TU Delft - Civil Engineering & Geosciences)
B.T. van Daal (TU Delft - Civil Engineering & Geosciences)
Linnaea Cahill – Mentor (Community Cloud Forest Conservation)
M.A. Schleiss – Mentor (TU Delft - Atmospheric Remote Sensing)
Miriam Coenders-Gerrits – Mentor (TU Delft - Water Systems Monitoring & Modelling)
R.J. van der Ent – Mentor (TU Delft - Water Systems Monitoring & Modelling)
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Abstract
Cloud Forests play a critical role in regulating regional hydrology through fog interception, biodiversity support, and groundwater recharge. However, increasing deforestation and land‐use change threaten the functionality of these ecosystems, partially by altering cloud formation processes. This study investigates how different land‐use types affect cloud base height (CBH) in the Mestelá River catchment in Alta Verapaz, Guatemala. Using a distributed sensor network of temperature, humidity, and pressure sensors deployed across cloud forest, pine forest, and agricultural land, vertical profiles were collected over multiple field campaigns.
Cloud base height was estimated through a lifting condensation level (LCL) model based on local atmospheric measurements. Results show systematic differences between land‐use types: cloud forests exhibited cooler and more humid conditions, resulting in a lower CBH compared to pine forests and open agricultural areas. Open fields consistently showed the highest daytime temperatures and lowest relative humidity, producing the highest estimated cloud bases. Pine forests exhibited intermediate conditions.
These microclimatic differences were incorporated into the FIESTA fog interception model, improving spatial and temporal representation of fog occurrence and interception efficiency. It was shown that especially improving the temporal accuracy of FIESTA inputs by forcing a diurnal pattern led to more accurate results. In addition, a simplified canopy water balance model was applied to evaluate the hydrological contribution of fog events at stand level. The results confirm that land‐use change alters cloud immersion frequency and potentially reduces dry‐season water inputs in deforested areas.
This study demonstrates that deforestation influences atmospheric processes at local scales with direct hydrological consequences, underscoring the importance of cloud forest conservation for water security in mountainous regions. The deployed sensor network and modeling framework offer a scalable method for monitoring cloud dynamics and evaluating land‐use impacts in other tropical montane systems.