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Effective nutrient pollution mitigation measures require in‐depth understanding of spatio‐temporal controls on water quality which can be obtained by analyzing export regime and hysteresis patterns in concentration‐discharge (c−Q) relationships. Such analyses require high‐frequency data (hourly or higher resolution), hampering the assessment of hysteresis patterns in widely available low‐frequency (monthly, biweekly) regulatory water quality data. We propose a reproducible classification of c−Q relationships considering export regime (dilution, constancy, enrichment) and long‐term average hysteresis pattern (clockwise, no hysteresis, anticlockwise) applicable to low‐frequency water quality data. The classification is based on power‐law c−Q models with separate parametrization for low and high discharge and rising and falling hydrograph limb, enabling a better representation of c−Q dynamics. The classification has been applied to a 30‐years record of daily streamflow and monthly spot samples of solute concentrations in 45 Scottish catchments with contrasting characteristics in terms of topography, climate, soil and land cover. We found that c−Q classification is solute‐ and catchment‐specific and linked to upland versus lowland catchments and streamflow variability. However as the relationship between solute behavior and catchment characteristics is variable, we propose that future typologies should integrate both water quality response, that is, c−Q classification, and catchment characteristics. The data‐driven c−Q classification allows us to increase the information content of low‐frequency water quality data and thus inform mitigation measures, monitoring strategies, and modeling approaches. Such approaches open up an ability to characterize processes and best management for a wider number of catchments, subject to regulatory surveillance and outside of research catchments. Key Points: A reproducible classification of concentration‐discharge relationships was developedExport regime and hysteresis pattern of low‐frequency water quality data are consideredCatchment concentration‐discharge classification varies spatially and among solutes [ABSTRACT FROM AUTHOR]

Environmental and ecological risk assessments are defined as the process for evaluating the likelihood that the environment may be impacted as a result of exposure to stressors. Although this definition implies the calculation of probabilities, risk assessments traditionally rely on nonprobabilistic methods such as calculation of a risk quotient. Bayesian network (BN) models are a tool for probabilistic and causal modeling, increasingly used in many fields of environmental science. Bayesian networks are defined as directed acyclic graphs where the causal relationships and the associated uncertainty are quantified in conditional probability tables. Bayesian networks inherently incorporate uncertainty and can integrate a variety of information types, including expert elicitation. During the last 2 decades, there has been a steady increase in reports on BN applications in environmental risk assessment and management. At recent annual meetings of the Society of Environmental Toxicology and Chemistry (SETAC) North America and SETAC Europe, a number of applications of BN models were presented along with new theoretical developments. Likewise, recent meetings of the European Geosciences Union (EGU) have dedicated sessions to Bayesian modeling in relation to water quality. This special series contains 10 articles based on presentations in these sessions, reflecting a range of BN applications to systems, ranging from cells and populations to watersheds and national scale. The articles report on recent progress in many topics, including climate and management scenarios, ecological and socioeconomic endpoints, machine learning, diagnostic inference, and model evaluation. They demonstrate that BNs can be adapted to established conceptual frameworks used to support environmental risk assessments, such as adverse outcome pathways and the relative risk model. The contributions from EGU demonstrate recent advancements in areas such as spatial (geographic information system [GIS]–based) and temporal (dynamic) BN modeling. In conclusion, this special series supports the prediction that increased use of Bayesian network models will improve environmental risk assessments. Integr Environ Assess Manag 2021;17:53–61. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC) [ABSTRACT FROM AUTHOR]

The broken phosphorus (P) cycle has led to widespread eutrophication of freshwaters. Despite reductions in anthropogenic nutrient inputs that have led to improvement in the chemical status of running waters, corresponding improvements in their ecological status are often not observed. We tested a novel combination of complementary statistical modeling approaches, including random‐effect regression trees and compositional and ordinary linear mixed models, to examine the potential reasons for this disparity, using low‐frequency regulatory data available to catchment managers. A benthic Trophic Diatom Index (TDI) was linked to potential stressors, including nutrient concentrations, soluble reactive P (SRP) loads from different sources, land cover, and catchment hydrological characteristics. Modeling suggested that SRP, traditionally considered the bioavailable component, may not be the best indicator of ecological impacts of P, as shown by a stronger and spatially more variable negative relationship between total P (TP) concentrations and TDI. Nitrate‐N (p < 0.001) and TP (p = 0.002) also showed negative relationship with TDI in models where land cover was not included. Land cover had the strongest influence on the ecological response. The positive effect of seminatural land cover (p < 0.001) and negative effect of urban land cover (p = 0.030) may be related to differentiated bioavailability of P fractions in catchments with different characteristics (e.g., P loads from point vs. diffuse sources) as well as resilience factors such as hydro‐morphology and habitat condition, supporting the need for further research into factors affecting this stressor–response relationship in different catchment types. Advanced statistical modeling indicated that to achieve desired ecological status, future catchment‐specific mitigation should target P impacts alongside multiple stressors. Core Ideas: Soluble reactive P (SRP) alone was not the best indicator of diatom response.Total P (TP) association with diatoms was more spatially variable than SRP.Nitrate‐N and TP have a combined negative effect on the ecological response.Seminatural land use had the most important influence on ecological response.We recommend catchment‐specific mitigation of multiple stressors. [ABSTRACT FROM AUTHOR]

Quantifying the extent of soil erosion at a fine spatial resolution can be time consuming and costly; however, proximal remote sensing approaches to collect topographic data present an emerging alternative for quantifying soil volumes lost via erosion. Herein we compare terrestrial laser scanning (TLS), and both unmanned aerial vehicle (UAV) and ground photography (GP) structure-from-motion (SfM) derived topography. We compare the cost-effectiveness and accuracy of both SfM techniques to TLS for erosion gully surveying in upland landscapes, treating TLS as a benchmark. Further, we quantify volumetric soil loss estimates from upland gullies using digital surface models derived by each technique and subtracted from an interpolated pre-erosion surface. Soil loss estimates from UAV and GP SfM reconstructions were comparable to those from TLS, whereby the slopes of the relationship between all three techniques were not significantly different from 1:1 line. Only for the TLS to GP comparison was the intercept significantly different from zero, showing that GP is more capable of measuring the volumes of very small erosion features. In terms of cost-effectiveness in data collection and processing time, both UAV and GP were comparable with the TLS on a per-site basis (13.4 and 8.2 person-hours versus 13.4 for TLS); however, GP was less suitable for surveying larger areas (127 person-hours per ha−1 versus 4.5 for UAV and 3.9 for TLS). Annual repeat surveys using GP were capable of detecting mean vertical erosion change on peaty soils. These first published estimates of whole gully erosion rates (0.077 m a−1) suggest that combined erosion rates on gully floors and walls are around three times the value of previous estimates, which largely characterize wind and rainsplash erosion of gully walls. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Sedimentation is a major cause of river impairment and water pollution worldwide. However, setting an ecologically meaningful sedimentation target is proving challenging due to significant gaps in the understanding of quantitative links between sedimentation and ecological response as well as variability between different types of surface waters. This study evaluates the utility of a new pressure-specific macroinvertebrate index, Proportion of Sediment-sensitive Invertebrates ( PSI), to act as a simple tool for measuring sedimentation impacts and setting ecologically relevant sedimentation targets., Five macroinvertebrate indices were calculated from 51 samples taken from 13 sampling locations across two neighbouring, but contrasting study catchments in spring and autumn 2010 and 2011. For four of these, environmental quality indices ( EQIs) were also calculated as a proportion of observed to expected ( O: E) macroinvertebrate scores, which were predicted for a theoretical pristine invertebrate community using the River Invertebrate Prediction and Classification System model., Principal component analysis has shown a clear hydromorphological and sedimentation gradient within the two study catchments. A generalised hierarchical mixed model with site as a random factor and % fine bed sediment as a fixed factor found a significant relationship between PSI and O:E PSI and % fine bed sediment cover at reach-scale sampling resolution over a moderate gradient of impact. Lotic Index for Flow Evaluation ( LIFE) scores and Ephemeroptera- Plecoptera- Trichoptera ( EPT) % abundance were also related to % fine bed sediment cover. However, PSI was more strongly related to % fine bed sediment cover than either LIFE or EPT % abundance. While PSI and O:E PSI were correlated with LIFE and O:E LIFE, PSI was not correlated with EPT % abundance, which suggests a differentiated response of these metrics to multiple stressors., The relationship between PSI and other invertebrate metrics should be subjected to further testing along a pronounced gradient of multiple stressors, as our findings suggest that PSI and % fine bed sediment cover have the potential to provide simple, sensitive and effective tools for setting of 'twin' ecological and physical sedimentation targets and add additional exploratory power to the existing suite of macroinvertebrate indices. [ABSTRACT FROM AUTHOR]