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


Centre for Ecology & Hydrology, Maclean Building, Crowmarsh Gifford, Wallingford, Oxfordshire, OX10 8BB, UK. Electronic address: [Email]


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


GIS analysis,LIDAR,National Tree Map,QUESTOR,Riparian shading,Water quality,