Predicting Post-Fire Change in West Virginia, USA from Remotely-Sensed Data

Prescribed burning is used in West Virginia, USA to return the important disturbance process of fire to oak and oak-pine forests. Species composition and structure are often the main goals for re-establishing fire with less emphasis on fuel reduction or reducing catastrophic wildfire. In planning prescribed fires land managers could benefit from the ability to predict mortality to overstory trees. In this study, wildfires and prescribed fires in West Virginia were examined to determine if specific landscape and terrain characteristics were associated with patches of high/moderate post-fire change. Using the ensemble machine learning approach of Random Forest, we determined that linear aspect was the most important variable associated with high/moderate post-fire change patches, followed by hillshade, aspect as class, heat load index, slope/aspect ratio (sine transformed), average roughness, and slope in degrees. These findings were then applied to a statewide spatial model for predicting post-fire change. Our results will help land managers contemplating the use of prescribed fire to spatially target landscape planning and restoration sites and better estimate potential post-fire effects

Dissolved organic carbon uptake in streams: A review and assessment of reach‐scale measurements

Quantifying the role that freshwater ecosystems play in the global carbon cycle requires accurate measurement and scaling of dissolved organic carbon (DOC) removal in river networks. We reviewed reach‐scale measurements of DOC uptake from experimental additions of simple organic compounds or leachates to inform development of aquatic DOC models that operate at the river network, regional, or continental scale. Median DOC uptake velocity (vf) across all measurements was 2.28 mm min−1. Measurements using simple compound additions resulted in faster vf (2.94 mm min−1) than additions of leachates (1.11 mm min−1). We also reviewed published data of DOC bioavailability for ambient stream water and leaf leachate DOC from laboratory experiments. We used these data to calculate and apply a correction factor to leaf leachate uptake velocity to estimate ambient stream water DOC uptake rates at the reach scale. Using this approach, we estimated a median ambient stream DOC vf of 0.26 mm min−1. Applying these DOC vf values (0.26, 1.11, 2.28, and 2.94 mm min−1) in a river network inverse model in seven watersheds revealed that our estimated ambient DOC vf value is plausible at the network scale and 27 to 45% of DOC input was removed. Applying the median measured simple compound or leachate vf in whole river networks would require unjustifiably high terrestrial DOC inputs to match observed DOC concentrations at the basin mouth. To improve the understanding and importance of DOC uptake in fluvial systems, we recommend using a multiscale approach coupling laboratory assays, with reach‐scale measurements, and modeling

An extended Bayesian sediment fingerprinting mixing model for the full Bayes treatment of geochemical uncertainties

Recent advances in sediment fingerprinting research have seen Bayesian mixing models being increasingly employed as an effective method to coherently translate component uncertainties into source apportionment results. Here, we advance earlier work by presenting an extended Bayesian mixing model capable of providing a full Bayes treatment of geochemical uncertainties. The performance of the extended full Bayes model was assessed against the equivalent empirical Bayes model and traditional frequentist optimisation. The performance of models coded in different Bayesian software (‘JAGS’ and ‘Stan’) was also evaluated, alongside an assessment of model sensitivity to reduced source representativeness and non-conservative fingerprint behaviour. Results revealed comparable accuracy and precision for the full and empirical Bayes models across both synthetic and real sediment geochemistry datasets, demonstrating that the empirical treatment of source data here represents a close approximation of the full Bayes treatment. Contrasts in the performance of models coded in JAGS and Stan revealed that the choice of software employed can impact significantly upon source apportionment results. Bayesian models coded in Stan were the least sensitive to both reduced source representativeness and non-conservative fingerprint behaviour, indicating Stan as the preferred software for future Bayesian sediment fingerprinting studies. Whilst the frequentist optimisation generally yielded comparable accuracy to the Bayesian models, uncertainties around apportionment estimates were substantially greater and the frequentist model was less effective at dealing with non-conservative behaviour. Overall, the effective performance of the extended full Bayes mixing model coded in Stan represents a notable advancement in source apportionment modelling relative to previous approaches. Both the mixing model and the software comparisons presented here should provide useful guidelines for future sediment fingerprinting studies

Diagnosing Down-the-Drain Disposal of Unused Pharmaceuticals at a River Catchment Level:Unrecognized Sources of Environmental Contamination That Require Nontechnological Solutions

Down-the-drain disposal of pharmaceuticals remains an overlooked and unrecognized source of environmental contamination that requires nontechnological “at-source” solutions. Monitoring of 31 pharmaceuticals over 7 days in five wastewater treatment plants (WWTPs) serving five cities in South-West UK revealed down-the-drain codisposal of six pharmaceuticals to three WWTPs (carbamazepine and propranolol in city A, sildenafil in city B, and diltiazem, capecitabine, and sertraline in city D), with a one-off record codisposal of estimated 253 pills = 40 g of carbamazepine and estimated 96 pills = 4 g of propranolol in city A accounting for their 10- and 3-fold respective increases in wastewater daily loads. Direct disposal of pharmaceuticals was found to affect the efficiency of wastewater treatment with much higher pharmaceutical removal (decrease in daily load) during “down-the-drain disposal” days. This is due to lack of conjugated glucuronide metabolites that are cleaved during “consumption-only” days, with the release of a parent pharmaceutical counterbalancing its removal. Higher removal of pharmaceuticals during down-the-drain disposal days reduced pharmaceutical loads reaching receiving environment, albeit with significant levels remaining. The estimated daily loads in receiving water downstream from a discharge point accounted for 13.8 ± 3.4 and 2.1 ± 0.2 g day–1 of carbamazepine and propranolol, respectively, during consumption-only days and peaked at 20.9 g day–1 (carbamazepine) and 4.6 g day–1 (propranolol) during down-the-drain disposal days. Actions are needed to reduce down-the-drain disposal of pharmaceuticals. Our recent work indicated that down-the-drain disposal of pharmaceuticals doubled since the last study in 2005, which may be due to the lack of information and messaging that informs people to dispose of unused medicines at pharmacies. Media campaigns that inform the public of how to safely dispose of medicines are key to improving rates of return and reducing pharmaceutical waste in the environment. The environment is a key motivator for returning unused medicines to a pharmacy and so messaging should highlight environmental risks associated with improper disposal

Analysis of Meandering River Morphodynamics Using Satellite Remote Sensing Data—An Application in the Lower Deduru Oya (River), Sri Lanka

River meandering and anabranching have become major problems in many large rivers that carry significant amounts of sediment worldwide. The morphodynamics of these rivers are complex due to the temporal variation of flows. However, the availability of remote sensing data and geographic information systems (GISs) provides the opportunity to analyze the morphological changes in river systems both quantitatively and qualitatively. The present study investigated the temporal changes in the river morphology of the Deduru Oya (river) in Sri Lanka, which is a meandering river. The study covered a period of 32 years (1989 to 2021), using Landsat satellite data and the QGIS platform. Cloud-free Landsat 5 and Landsat 8 satellite images were extracted and processed to extract the river mask. The centerline of the river was generated using the extracted river mask, with the support of semi-automated digitizing software (WebPlotDigitizer). Freely available QGIS was used to investigate the temporal variation of river migration. The results of the study demonstrated that, over the past three decades, both the bend curvatures and the river migration rates of the meandering bends have generally increased with time. In addition, it was found that a higher number of meandering bends could be observed in the lower (most downstream) and the middle parts of the selected river segment. The current analysis indicates that the Deduru Oya has undergone considerable changes in its curvature and migration rates.publishedVersio

Review of risk from potential emerging contaminants in UK groundwater

This paper provides a review of the types of emerging organic groundwater contaminants (EGCs) which are beginning to be found in the UK. EGCs are compounds being found in groundwater that were previously not detectable or known to be significant and can come from agricultural, urban and rural point sources. EGCs include nanomaterials, pesticides, pharmaceuticals, industrial compounds, personal care products, fragrances, water treatment by-products, flame retardants and surfactants, as well as caffeine and nicotine. Many are relatively small polar molecules which may not be effectively removed by drinking water treatment. Data from the UK Environment Agency’s groundwater screening programme for organic pollutants found within the 30 most frequently detected compounds a number of EGCs such as pesticide metabolites, caffeine and DEET. Specific determinands frequently detected include pesticides metabolites, pharmaceuticals including carbamazepine and triclosan, nicotine, food additives and alkyl phosphates. This paper discusses the routes by which these compounds enter groundwater, their toxicity and potential risks to drinking water and the environment. It identifies challenges that need to be met to minimise risk to drinking water and ecosystems

Water quality improvements offset the climatic debt for stream macroinvertebrates over twenty years

Many species are accumulating climatic debt as they fail to keep pace with increasing global temperatures. In theory, concomitant decreases in other stressors (e.g. pollution, fragmentation) could offset some warming effects, paying climatic debt with accrued environmental credit. This process may be occurring in many western European rivers. We fit a Markov chain model to ~20,000 macroinvertebrate samples from England and Wales, and demonstrate that despite large temperature increases 1991–2011, macroinvertebrate communities remained close to their predicted equilibrium with environmental conditions. Using a novel analysis of multiple stressors, an accumulated climatic debt of 0.64 (±0.13 standard error) °C of warming was paid by a water-quality credit equivalent to 0.89 (±0.04)°C of cooling. Although there is finite scope for mitigating additional climate warming in this way, water quality improvements appear to have offset recent temperature increases, and the concept of environmental credit may be a useful tool for communicating climate offsetting

High-temporal resolution fluvial sediment source fingerprinting with uncertainty: a Bayesian approach

This contribution addresses two developing areas of sediment fingerprinting research. Specifically, how to improve the temporal resolution of source apportionment estimates whilst minimizing analytical costs and, secondly, how to consistently quantify all perceived uncertainties associated with the sediment mixing model procedure. This first matter is tackled by using direct X-ray fluorescence spectroscopy (XRFS) and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) analyses of suspended particulate matter (SPM) covered filter papers in conjunction with automatic water samplers. This method enables SPM geochemistry to be quickly, accurately, inexpensively and non-destructively monitored at high-temporal resolution throughout the progression of numerous precipitation events. We then employed a Bayesian mixing model procedure to provide full characterization of spatial geochemical variability, instrument precision and residual error to yield a realistic and coherent assessment of the uncertainties associated with source apportionment estimates. Applying these methods to SPM data from the River Wensum catchment, UK, we have been able to apportion, with uncertainty, sediment contributions from eroding arable topsoils, damaged road verges and combined subsurface channel bank and agricultural field drain sources at 60- and 120-minute resolution for the duration of five precipitation events. The results presented here demonstrate how combining Bayesian mixing models with the direct spectroscopic analysis of SPM-covered filter papers can produce high-temporal resolution source apportionment estimates that can assist with the appropriate targeting of sediment pollution mitigation measures at a catchment level