Cloud Water Interception across Elevation and Forest Structure Gradients in Leeward Kohala, Hawaiʻi
Abstract
Cloud water interception (CWI) is a significant source of water for many tropical montane cloud forests (TMCFs) in Hawaiʻ i and elsewhere. But due to the difficulties of directly measuring CWI, most hydrological studies of TMCFs are limited to individual site scales and are therefore difficult to extrapolate to larger regions of varying elevation, rainfall, and forest characteristics. We measured rainfall (RF) and under-canopy throughfall (TF) in order to derive CWI rates along an elevation and climate gradient on leeward Kohala, Hawaiʻ i Island, allowing us to investigate the spatially-variable contribution of CWI to Kohala's ecosystems. In addition, we collected a suite of forest structure data above each TF sampling point in order to study the gauge- and site-scale influences of forest structure on TF.
We found that TF exceeded RF by 51% over our 133-day study period near the densely-forested crest of Kohala, but that these high CWI rates decline at lower elevations reached less frequently by orographic clouds. Farther downslope at the current man-made transition from closed-canopy ʻ ōhiʻ a forest to pasture, CWI and forest canopy evaporation appear roughly similar in magnitude, although low TF rates at this site appear to be caused in part by the large trees present. An area of mesic koaiʻ a woodland at lower elevations featured a measurable CWI input, with TF exceeding RF by 11% over the study period. While CWI, TF, and RF were positively related to elevation, periods with weaker trade winds flatten these trends due to the waning influence of the orographic moisture responsible for both RF and CWI. Hemispherical photography and ground-based LIDAR scans indicate that denser forest canopies exhibit lower TF at both site and gauge scales, although this pattern weakens in wetter periods due to greater canopy saturation. Broadly speaking, wetness and elevation appear more explanatory than trade wind strength or forest structure for CWI rates in leeward Kohala. A simple regression model finds that RF+CWI predicts streamflow at a nearby gauging station better than RF alone, suggesting CWI may be a significant input of water into leeward Kohala's hydrologic system that is not currently integrated into regional models.- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2020
- Bibcode:
- 2020AGUFMB122...07B
- Keywords:
-
- 3305 Climate change and variability;
- ATMOSPHERIC PROCESSES;
- 0414 Biogeochemical cycles;
- processes;
- and modeling;
- BIOGEOSCIENCES;
- 1631 Land/atmosphere interactions;
- GLOBAL CHANGE;
- 1813 Eco-hydrology;
- HYDROLOGY