The utility of spatial data to delineate river riparian functions and management zones: A review.

Riparian zones of rivers are transitional environments between land and water ecosystems with distinct hydrological gradients, soils and habitats strongly related to their functioning. When these functions are intact, they integrate multi-directional processes across the land-river channel (e.g. canopy shade effects on the stream, flood inundation effects on the land) with mutual beneficial effects. In many managed landscapes these functions have been degraded. To restore them, considerable efforts have been directed over the last 20 years to understand and place effective riparian 'buffer' zones, particularly to enhance water quality and biodiversity. Since water quality targets are not easily met by current practices in many managed landscapes (as additive pressures increase), catchment managers will have to increasingly restore riparian functions to enhance aquatic ecosystem resilience to land and climate change. Targeting effective restoration within site-specific contexts requires availability of spatial data, in combinations that inform on individual and multiple functions. There are accelerating developments with spatial data, arising from increased spatial resolution of key underlying datasets, availability of soil and landcover data and increasing secondary derived attributes. Hence, a review is timely into the best practices in the use of these data for delineating riparian functions and management zones for rivers. Our review evaluates the application of spatial data and is structured around three conceptual methods of riparian delineation; fixed width, variable width by river corridor features and variable width by context of local pressures or required outcomes. We explore process representation and incorporation into management across main riparian functions (hydrological connectivity, water quality, shading, resource transfers and habitat provision). Translating spatial data into functions informs the ability to go beyond contemporary, generally fixed width approaches using basic structural components towards planning to better target functional attributes to optimise ecosystem protection.

Evaluation of spot and passive sampling for monitoring, flux estimation and risk assessment of pesticides within the constraints of a typical regulatory monitoring scheme.

In many agricultural catchments of Europe and North America, pesticides occur at generally low concentrations with significant temporal variation. This poses several challenges for both monitoring and understanding ecological risks/impacts of these chemicals. This study aimed to compare the performance of passive and spot sampling strategies given the constraints of typical regulatory monitoring. Nine pesticides were investigated in a river currently undergoing regulatory monitoring (River Ugie, Scotland). Within this regulatory framework, spot and passive sampling were undertaken to understand spatiotemporal occurrence, mass loads and ecological risks. All the target pesticides were detected in water by both sampling strategies. Chlorotoluron was observed to be the dominant pesticide by both spot (maximum: 111.8ng/l, mean: 9.35ng/l) and passive sampling (maximum: 39.24ng/l, mean: 4.76ng/l). The annual pesticide loads were estimated to be 2735g and 1837g based on the spot and passive sampling data, respectively. The spatiotemporal trend suggested that agricultural activities were the primary source of the compounds with variability in loads explained in large by timing of pesticide applications and rainfall. The risk assessment showed chlorotoluron and chlorpyrifos posed the highest ecological risks with 23% of the chlorotoluron spot samples and 36% of the chlorpyrifos passive samples resulting in a Risk Quotient greater than 0.1. This suggests that mitigation measures might need to be taken to reduce the input of pesticides into the river. The overall comparison of the two sampling strategies supported the hypothesis that passive sampling tends to integrate the contaminants over a period of exposure and allows quantification of contamination at low concentration. The results suggested that within a regulatory monitoring context passive sampling was more suitable for flux estimation and risk assessment of trace contaminants which cannot be diagnosed by spot sampling and for determining if long-term average concentrations comply with specified standards.

Integrating economic and biophysical data in assessing cost-effectiveness of buffer strip placement.

The European Union Water Framework Directive (WFD) requires Member States to set water quality objectives and identify cost-effective mitigation measures to achieve "good status" in all waters. However, costs and effectiveness of measures vary both within and between catchments, depending on factors such as land use and topography. The aim of this study was to develop a cost-effectiveness analysis framework for integrating estimates of phosphorus (P) losses from land-based sources, potential abatement using riparian buffers, and the economic implications of buffers. Estimates of field-by-field P exports and routing were based on crop risk and field slope classes. Buffer P trapping efficiencies were based on literature metadata analysis. Costs of placing buffers were based on foregone farm gross margins. An integrated optimization model of cost minimization was developed and solved for different P reduction targets to the Rescobie Loch catchment in eastern Scotland. A target mean annual P load reduction of 376 kg to the loch to achieve good status was identified. Assuming all the riparian fields initially have the 2-m buffer strip required by the General Binding Rules (part of the WFD in Scotland), the model gave good predictions of P loads (345-481 kg P). The modeling results show that riparian buffers alone cannot achieve the required P load reduction (up to 54% P can be removed). In the medium P input scenario, average costs vary from £38 to £176 kg P at 10% and 54% P reduction, respectively. The framework demonstrates a useful tool for exploring cost-effective targeting of environmental measures.