Future malaria environmental suitability in Africa is sensitive to hydrology

Changes in climate shift the geographic locations that are suitable for malaria transmission because of the thermal constraints on vector Anopheles mosquitos and Plasmodium spp. malaria parasites and the lack of availability of surface water for vector breeding. Previous Africa-wide assessments have tended to solely represent surface water using precipitation, ignoring many important hydrological processes. Here, we applied a validated and weighted ensemble of global hydrological and climate models to estimate present and future areas of hydroclimatic suitability for malaria transmission. With explicit surface water representation, we predict a net decrease in areas suitable for malaria transmission from 2025 onward, greater sensitivity to future greenhouse gas emissions, and different, more complex, malaria transmission patterns. Areas of malaria transmission that are projected to change are smaller than those estimated by precipitation-based estimates but are associated with greater changes in transmission season lengths

Can high resolution 3D topographic surveys provide reliable grain size estimates in gravel bed rivers?

High resolution topographic surveys such as those provided by Structure-from-Motion (SfM) contain a wealth of information that is not always exploited in the generation of Digital Elevation Models (DEMs). In particular, several authors have related sub-metre scale topographic variability (or ‘surface roughness’) to sediment grain size by deriving empirical relationships between the two. In fluvial applications, such relationships permit rapid analysis of the spatial distribution of grain size over entire river reaches, providing improved data to drive three-dimensional hydraulic models, allowing rapid geomorphic monitoring of sub-reach river restoration projects, and enabling more robust characterisation of riverbed habitats. However, comparison of previously published roughness-grain-size relationships shows substantial variability between field sites. Using a combination of over 300 laboratory and field-based SfM surveys, we demonstrate the influence of inherent survey error, irregularity of natural gravels, particle shape, grain packing structure, sorting, and form roughness on roughness-grain-size relationships. Roughness analysis from SfM datasets can accurately predict the diameter of smooth hemispheres, though natural, irregular gravels result in a higher roughness value for a given diameter and different grain shapes yield different relationships. A suite of empirical relationships is presented as a decision tree which improves predictions of grain size. By accounting for differences in patch facies, large improvements in D50 prediction are possible. SfM is capable of providing accurate grain size estimates, although further refinement is needed for poorly sorted gravel patches, for which c-axis percentiles are better predicted than b-axis percentiles

Quantifying the Natural Flood Management potential of leaky dams in upland catchments, Part I: A data-based modelling approach

A novel application of data-based time series methods is proposed in this study to help overcome barriers to quantifying the impacts of Natural Flood Management measures from hydrological timeseries data which hitherto have prevented accurate assessment of the effectiveness of interventions. To demonstrate the value of this method, a transfer function noise model was fitted to stage data from a three year before-after-control-impact style monitoring study of leaky dams in an upland catchment in North Yorkshire, England. Using the data-based time series method, uncertainties associated with stage data were overcome. The models were able to simulate the peaks of flood events on one stream to within ±2 cm accuracy for 95% of events recorded during the baseline monitoring period. These simulations are used in this study’s companion paper to quantify leaky dam impacts on flood peak magnitude. The level of accuracy achieved in this study provides proof of concept for application of the approach to data from other environments and natural flood management interventions, which is crucial if natural flood management is to be used as a mainstream flood risk management measure

Quantifying the Natural Flood Management potential of leaky dams in upland catchments, Part II: Leaky dam impacts on flood peak magnitude

Leaky dams are an increasingly popular natural flood management measure, yet their impacts on flood peak magnitude have not yet been empirically quantified for a range of event types and magnitudes, even at the stream scale. In this study, the novel application of a transfer function noise modelling approach to empirical Before-After-Control-Impact stage data from an upland catchment allowed leaky dam effectiveness in reducing flood peak magnitude to be quantified. Flood peak stage and discharge magnitude changes were assessed from empirical data for 50 single and multi-peaked high flow events with return periods ranging from less than one year to six years. Overall, event peak magnitude was significantly reduced following the installation of eight leaky dams on the impact stream. Effectiveness was highly variable, but on average, flood peak magnitude was reduced by 10% for events with a return period up to one year. Some of the variability was explained by the size of the event and whether it was a single or multi-peaked event. This finding emphasises the need to manage expectations by considering both a range of event magnitudes and types when designing or assessing leaky dam natural flood management schemes

Woody debris is related to reach-scale hotspots of lowland stream ecosystem respiration under baseflow conditions

Stream metabolism is a fundamental, integrative indicator of aquatic ecosystem functioning. However, it is not well understood how heterogeneity in physical channel form, particularly in relation to and caused by in‐stream woody debris, regulates stream metabolism in lowland streams. We combined conservative and reactive stream tracers to investigate relationships between patterns in stream channel morphology and hydrological transport (form) and metabolic processes as characterized by ecosystem respiration (function) in a forested lowland stream at baseflow. Stream reach‐scale ecosystem respiration was related to locations (“hotspots”) with a high abundance of woody debris. In contrast, nearly all other measured hydrological and geomorphic variables previously documented or hypothesized to influence stream metabolism did not significantly explain ecosystem respiration. Our results suggest the existence of key differences in physical controls on ecosystem respiration between lowland stream systems (this study) and smaller upland streams (most previous studies) under baseflow conditions. As such, these findings have implications for reactive transport models that predict biogeochemical transformation rates from hydraulic transport parameters, for upscaling frameworks that represent biological stream processes at larger network scales, and for the effective management and restoration of aquatic ecosystems