Predicting long‐term streamflow variability in moist eucalypt forests using forest growth models and a sapwood area index. Issue 4 (22nd April 2016)

• Record Type: Journal Article
• Authors: Jaskierniak, D.; Kuczera, G.; Benyon, R.
• Is Part Of: Water resources research. Volume 52:Issue 4(2016:Apr.)
• Page Start: 3052
• Page End: 3067
• Publication Date: 2016-04-22
• Subjects: forest inventory -- forest sapwood area -- streamflow -- Eucalyptus regnans -- LiDAR; Hydrology -- Periodicals; 333.91
• DOI: 10.1002/2015WR018029
• Languages: English
• ISSNs: 0043-1397

Abstract

Abstract: A major challenge in surface hydrology involves predicting streamflow in ungauged catchments with heterogeneous vegetation and spatiotemporally varying evapotranspiration (ET) rates. We present a top‐down approach for quantifying the influence of broad‐scale changes in forest structure on ET and hence streamflow. Across three catchments between 18 and 100 km 2 in size and with regenerating Eucalyptus regnans and E. delegatensis forest, we demonstrate how variation in ET can be mapped in space and over time using LiDAR data and commonly available forest inventory data. The model scales plot‐level sapwood area (SA) to the catchment‐level using basal area (BA) and tree stocking density (N) estimates in forest growth models. The SA estimates over a 69 year regeneration period are used in a relationship between SA and vegetation induced streamflow loss (L) to predict annual streamflow (Q) with annual rainfall (P) estimates. Without calibrating P, BA, N, SA, and L to Q data, we predict annual Q with R 2 between 0.68 and 0.75 and Nash Sutcliffe efficiency (NSE) between 0.44 and 0.48. To remove bias, the model was extended to allow for runoff carry‐over into the following year as well as minor correction to rainfall bias, which produced R 2 values between 0.72 and 0.79, and NSE between 0.70 and 0.79. The model under‐predicts streamflow during drought periods as it lacks representation of ecohydrological processes that reduce L with either reduced growth rates or rainfall interception during drought. Refining the relationship between sapwood thickness and forest inventory variables is likely to further improve results. Key Points: Forest inventory and rainfall data are used to predict annual streamflow in large forested catchments. Forest growth models explain the vegetation‐induced decadal trend in streamflow. Changes in sapwood area during forest regeneration accounts for long‐term changes in evapotranspiration.