Cloud Water Interception in Hawaiʻi
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2021
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Abstract
Tropical montane cloud forests are unique ecosystems generally defined as forests frequently covered in fog. Cloud water interception, the passive capturing of water from passing clouds by vegetation, is an ecohydrological process that may add considerable amounts of water to the ecosystem. Because of their ability in gaining extra water from clouds, tropical montane cloud forests are believed to increase water supply downstream and benefit water resources. However, evidence about the hydrological benefits of conserving and restoring tropical montane cloud forests is still limited. This is primarily because cloud water interception is difficult to quantify over the spatial and temporal scales adequate for most hydrological analyses to answer questions about water resources. Issues in the quantification of landscape-scale cloud water interception exist at multiple levels. First, cloud water interception is highly heterogeneous because it is affected by many factors that are spatially and temporally variable. Also, existing methods that measure cloud water interception are very limited in their representativeness over large areas because the applicable scales are small and limitations in resources and time restrict the sample size practically achievable by individual studies. Lastly, while individual studies have limited capacity to make measurements of cloud water interception, a large proportion of the existing observational data are not comparable due to inconsistent methodologies and measurement uncertainties. Tropical montane cloud forests in Hawaii and around the world, as well as the hydrological benefits they may provide, are especially vulnerable to climate change and land cover change because of the strong dependence of the ecosystem on clouds and cloud water interception. While climate change, land cover change, and species invasion pose immediate threats to these unique ecosystems, an understanding of how cloud water interception influences the ecosystem and the islands’ hydrology and how that may change in response to future conditions is still lacking. This study aims to advance the current field of cloud water interception study by (1) proposing a standardized method to quantify the atmospheric driver of cloud water interception, (2) investigating the causes of cloud water interception variability to identify major factors, and (3) developing a model capable of predicting cloud water interception over the complex montane landscapes of the Hawaiian Islands.Passive fog gauges are one of the most used methods to study cloud water interception; however, the interpretation of fog gauge measurement is not straightforward, and the long lack of a standard for the methodology has caused confusion and prevented almost all meaningful quantitative comparisons between fog gauge data. In order to fundamentally resolve the problem of inconsistency, this study proposed a new standardized fog gauge method, which requires the raw measurements to be calibrated into the standard unit of cloud liquid water content. The calibration of a Juvik-type fog gauge was provided to demonstrate the concept and practicability of establishing a calibration procedure for a fog gauge. Comparing fog characteristics presented in different units showed that the apparent “fogginess” of a site may change drastically before and after accounting for certain sources of uncertainties and highlighted the importance of fog gauge calibration.
Calibrated fog gauge was used to quantify cloud water supplied by the atmosphere, represented by cloud water flux, which is a major factor of cloud water interception. Variations in cloud water interception and cloud water flux at five study sites across three major Hawaiian Islands were compared for cloud water interception variability and the effects of climate and vegetation characteristics. At all study sites, cloud water interception added several hundreds of millimeters of water to the canopy. At four out of five sites, the water gained from cloud water interception comprised more than 20% of the total water input to the ecosystem. Cloud water interception correlated with cloud water flux; however, although fog frequency most strongly controls cloud water flux, no simple site characteristics could be found to clearly explain the observed differences in annual cloud water interception between sites. This not only suggests that between-site variability is large relative to the limited sample size but predicting cloud water interception by elevation or generic climatic variables may also be inappropriate.
In order to characterize cloud water interception variation over the complex and data-poor landscapes of Hawaii, a cloud water interception model was developed taking the advantage of both empirical and mechanical approaches. The process of cloud water interception is represented as a simple interaction between cloud water flux and the canopy interception efficiency for the cloud water, which depends on the canopy structure. After fitting the model to observational data, the model was tested by trying to predict cloud water interception at the five study sites. The prediction errors decrease when results are aggregated for longer periods. The model predicted annual cloud water interception to be 17% lower than the observations on average but was able to reproduce the relative site differences and monthly fluctuations relatively well. Given its simplicity, the model performed reasonably well compared to other modeling studies. Although proper validation and further improvements of the model, especially the collection of new observational data, are left to future studies, the cloud water interception model developed in this study can have many applications. Depending on the selection of input data, this model may be used to map cloud water interception, project changes under future conditions, and test scenarios and hypotheses about cloud water interception responses to land management and restoration to support a wide range of researchers, practitioners, and policymakers.
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Environmental science, Hydrologic sciences, cloud water interception, ecohydrology, fog, fog gauge, orographic cloud, tropical montane cloud forest
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218 pages
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