Beavers can profoundly alter riparian environments, most conspicuously by creating dams and wetlands. Eurasian beaver (Castor fiber) populations are increasing and it has been suggested they could play a role in the provision of multiple ecosystem services, including natural flood management. Research at different scales, in contrasting ecosystems is required to establish to what extent beavers can impact on flood regimes. Therefore, this study determines whether flow regimes and flow responses to storm events were altered following the building of beaver dams and whether a flow attenuation effect could be significantly attributed to beaver activity. Four sites were monitored where beavers have been reintroduced in England. Continuous monitoring of hydrology, before and after beaver impacts, was undertaken on streams where beavers built sequences of dams. Stream orders ranged from 2nd to 4th, in both agricultural and forest-dominated catchments. Analysis of >1000 storm events, across four sites showed an overall trend of reduced total stormflow, increased peak rainfall to peak flow lag times and reduced peak flows, all suggesting flow attenuation, following beaver impacts. Additionally, reduced high flow to low flow ratios indicated that flow regimes were overall becoming less "flashy" following beaver reintroduction. Statistical analysis, showed the effect of beaver to be statistically significant in reducing peak flows with estimated overall reductions in peak flows from −0.359 to −0.065 m 3 s −1 across sites. Analysis showed spatial and temporal variability in the hydrological response to beaver between sites, depending on the level of impact and seasonality. Critically, the effect of beavers in reducing peak flows persists for the largest storms monitored, showing that even in wet conditions, beaver dams can attenuate average flood flows by up to ca. 60%. This research indicates that beavers could play a role in delivering natural flood management.

a b s t r a c tShallow, degraded peatlands differ in both their structure and function from deeper, peatland ecosystems. Previous work has shown that shallow, drained peatlands demonstrate rapid storm runoff that is only minimally controlled by antecedent hydrological conditions. However, such peatlands are also known to exhibit significant variation in ecohydrological organisation and structure across different spatial scales. In addition, predictions of hydrological response using spatially distributed numerical models of rainfall-runoff may be flawed unless they are evaluated with datasets describing the spatial variability of hydrological responses. This paper evaluates to what extent, flow generation and water storage within shallow, degraded peatland catchments may be controlled by the spatial attributes of the contributing area of the peatland, the drainage ditch size, morphology and geometry.Results from an experiment conducted over multiple spatial scales and multi-annual timescales highlights that subtle variations in the local slope and topography account for the long-term spatial patterns of water table depth. Neither the local scale of the drainage feature or the topographic contributing area is shown to be a definitive predictor of runoff in the studied catchments. Results also highlight the importance of using spatially distributed observations to ensure that estimates of water storage and runoff are representative of the fine scale spatial variability that occurs in such damaged and shallow peatlands.

Peatlands are recognised as an important but vulnerable ecological resource. Understanding the effects of existing damage, in this case erosion, enables more informed land management decisions to be made. Over the growing seasons of 2013 and 2014 photosynthesis and ecosystem respiration were measured using closed chamber techniques within vegetated haggs and erosional peat pans in Dartmoor National Park, southwest England. Below-ground total and heterotrophic respiration were measured and autotrophic respiration estimated from the vegetated haggs. The mean water table was significantly higher in the peat pans than in the vegetated haggs; because of this, and the switching from submerged to dry peat, there were differences in vegetation composition, photosynthesis and ecosystem respiration. In the peat pans photosynthetic CO 2 uptake and ecosystem respiration were greater than in the vegetated haggs and strongly dependent on the depth to water table (r 2 [ 0.78, p \ 0.001). Whilst in the vegetated haggs, photosynthesis and ecosystem respiration had the strongest relationships with normalised difference vegetation index (NDVI) (r 2 = 0.82, p \ 0.001) and soil temperature at 15 cm depth (r 2 = 0.77, p = 0.001). Autotrophic and total below-ground respiration in the vegetated haggs varied with soil temperature; heterotrophic respiration increased as water tables fell. An empirically derived net ecosystem model estimated that over the two growing seasons both the vegetated haggs (29 and 20 gC m -2 ; 95% confidence intervals of -570 to 762 and -873 to 1105 gC m -2 ) and the peat pans Wetlands Ecol Manage (2019) 27:187-205 https://doi.org/10.1007/s11273-019-09652-9( 0123456789().,-volV) ( 01234567 89().,-volV) (7 and 8 gC m -2 ; 95% confidence intervals of -147 to 465 and -136 to 436 gC m -2 ) were most likely net CO 2 sources. This study suggests that not only the visibly degraded bare peat pans but also the surrounding vegetated haggs are losing carbon to the atmosphere, particularly during warmer and drier conditions, highlighting a need for ecohydrological restoration.

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Drinking water treatment works are increasingly placed under external stressors including climatic variability, land use and management, and pollution incidents. Routine high-frequency water quality monitoring is an integral part of operational control and is used to inform the treatment process and support the identification of risks. However, in order to improve decision making using the complex, time-series of water quality data that are generated (and typically archived), there must be distinction between basic sensor errors, artefacts of system design and management, and process driven patterns. This paper explores these complex data in order to support synthesis of uncleaned (or raw), high-frequency data; extracting information value from routine catchment wide monitoring. The data are presented in a form that enhances the capability and capacity to utilise existing complex data; improves understanding of complex surface water systems; and helps facilitate data driven models to investigate and forecast the dynamics between water quality determinands during hard-to-treat spate (or rainfall-runoff) events.