Assessing the impact of tree canopy on interception loss in a small catchment

Abstract

Tree canopies play a pivotal role in determining how rainfall is split between interception loss and runoff, yet many catchment models overlook this process. This work evaluates canopy effects on storm-scale runoff in a 24 km² dry-zone catchment by linking Landsat-8 NDVI with event-based HEC-HMS simulations. NDVI was converted to leaf area index using established formulas, producing spatially distributed maximum canopy‐storage capacities of 1.24–1.38 mm over 2013–2023. A percentile‐based method identified three five-day “dry–rain–dry” storm windows centered on 95th-percentile rainfall events in 2015, 2020, and 2023 to ensure consistent antecedent moisture. After calibration and validation against observed inflows, the model ran three scenarios with canopy-storage set to NDVI-derived values of 0.619, 0.651, and 0.696. Increasing NDVI from 0.619 to 0.696 systematically reduced peak discharge by up to 18 % and reduced total runoff volume. Canopy evapotranspiration outputs confirmed that about 1.3 mm of intercepted water evaporates within 24 hours, accounting for virtually all interception loss. Future work should deploy IoT sensors, couple interception with sediment-transport models, apply machine-learning for parameter regionalization, and test resilience under projected climates.