A novel application of remote sensing for modelling impacts of tree shading on water quality

• DOI: 10.1016/j.jenvman.2018.09.037
• Publication Date: 2018-09-25T04:50:00Z
• Authors: N. Bachiller-Jareno; M.G. Hutchins; M.J. Bowes; M.B. Charlton; H.G. Orr
• Keywords: Shading; Tree (set theory)

Uncertainty in capturing the effects of riparian tree shade for assessment algal growth rates and water temperature hinders predictive capability models applied river basin management. Using photogrammetry-derived canopy data, we quantified hourly along River Thames (UK) used it to estimate reduction amount direct radiation reaching surface. In addition tested suitability freely-available LIDAR data map ground elevation. Following removal buildings objects other than trees from dataset, results revealed considerable differences between photogrammetry- LIDAR-derived methods variables including mean height (10.5 m 4.0 respectively), percentage occupancy zones by (45% 16% respectively) mid-summer fractional penetration (65% 76% respectively). The generated on daily 2010 were as input a network quality model (QUESTOR). Impacts shading assessed terms upper quartile levels, revealing substantial indicators such biochemical oxygen demand (BOD) (1.58–2.19 mg L−1 (20.1 21.2 °C 'shaded' 'non-shaded' inputs. Whilst extent derived two are appreciable they only make small Thames. However may prove more critical smaller rivers. We highlight importance accurate estimation modelling recommend use high resolution remotely sensed spatial characterise canopies. Our paper illustrates how is now possible better reach scale estimates aggregations these at scale. This will allow provision effective guidance management programmes currently possible. important support adaptation future warming maintenance standards.