Improving Water Resource Assessment in Hawaii by Using LiDAR Measurements of Canopy Structure to Estimate Rainfall Interception
03/01/08 – 02/28/09
Water resources in Hawaii continue to experience increasing demand, putting pressure on existing sources and increasing the need for better estimates of resource capacity (Oki 2002). For ground-water sources, in particular, reliable estimates of sustainable yield limits are critically important. Ground-water recharge estimates, in turn, are needed to determine accurate safe yield limits. Recharge is highly spatially variable in Hawaii (Giambelluca 1983), because of extreme gradients in precipitation and evapotranspiration (ET). The accuracy of recharge estimates in Hawaii has been limited by a lack of direct measurements of ET within forested recharge areas. Recent research has improved our knowledge of standlevel ET in Hawaii and pointed to the need to better understand interception loss, the amount of rainfall intercepted by leaves and stems and subsequently evaporated (Giambelluca et al. in prep.). The amount of interception loss, which can vary from 10 to 50% of incoming precipitation (Roth et al. 2007), is strongly influenced by canopy structure, especially canopy gap fraction, leaf, stem and epiphyte storage capacity, and branch angle (Rutter et al. 1975; Gash 1995), and, hence, is highly variable across the forested landscape. Alien trees, some of which-such as Psidium cattleianum (strawberry guava)-are highly invasive, are markedly different in structure from native trees, such as Metrosideros polymorpha (‘ohia). Very little was known about the rate and spatial variability of interception loss and the effects of alien tree introductions on interception in Hawaii. Better estimates of interception were needed to improve water resource assessments. Such improvements are highly valuable to water supply purveyors of the various counties and State water planners. The traditional method for measuring interception, based on canopy water balance, is difficult and very limited in spatial coverage. But, recent advances in ground-based and airborne LiDAR technology offered the promise of spatially-distributed estimates of interception using a physically-based approach (Roth et al. 2007).
Statement of Results or Benefits:
This project allowed us to better characterize canopy properties that control the partitioning of rainfall. This work lead to improved estimates of canopy rainfall interception in Hawaiian forests. Better estimates of canopy rainfall interception has direct benefits in the form of more accurate water resource assessments in Hawaii.
While the evaluation and testing of LiDAR-derived parameters for estimating interception at these two sites made a valuable original contribution, our ultimate goal was to couple these results with airborne LiDAR data to estimate interception loss over large areas in Hawaii. We collaborated on related research with Dr. Gregory Asner of Carnegie Institution, who is a leader in the use of airborne LiDAR and hyperspectral data to investigate ecological processes in tropical forests. For this next step, which followed directly from the study here, we teamed with Dr. Asner to seek extramural support from the NSF Hydrology Program. Using the results obtained with the pilot study described here, we developed a proposal to combine wetcanopy water balance measurements, and ground-based and airborne LiDAR to derive the spatial distribution of interception loss rates over the important recharge areas in Hawaii.
Nature, Scope, and Objectives of the Project:
Canopy water storage has been shown to be highly variable from place to place in Hawai`i’s forests (Mudd, 2004) due to the diversity of structural characteristics related to morphological variability in native species and to the influences of introduced tree species. Ground-based and airborne LiDAR provided unprecedented means to measure the important canopy structural variables that control the amount and disposition of rainfall deposited on plant leaves and stems. This newly available technology facilitated, for the first time, the use of mechanistic models to fully describe the partitioning of rainfall into throughfall (TF), stemflow (SF), canopy storage capacity (S), and interception evaporation (I). The objective of this project was to utilize a newly-acquired LiDAR system and existing state-of-the-art field measurement facilities to develop and test a new method for estimating interception in Hawai`i’s native and invaded forests.
Dr. Thomas Giambelluca
University of Hawaii at Manoa (UH)