Catchment Monitoring Research Articles

Hydroclimatic non-stationarity drives stream hydrochemistry dynamics through controls on catchment connectivity and water ages

We used data from 17 years of routine stream flow sampling to characterise hydrochemical dynamics in the Girnock Burn, an internationally important long-term catchment monitoring site. We combined hydrochemical time series analysis with hydrological modelling to understand short- and long-term dynamics in relation to dominant runoff processes. Isotopic tracer data employed within the model enabled flux tracking of water as it transited the catchment, facilitating water age estimates. The stream drains an upland 31 km2 catchment with complex topography and variable geology, which influences soil distributions; peaty soils dominate valley bottoms which receive drainage from more permeable podzolic soils on steeper slopes. Short-term hydrochemical dynamics largely reflect the relative dominance of hydrological sources: summer low flows are dominated by alkaline groundwater high in weathering products (Ca2+, Mg2+, SiO2) whilst high flows generated by overland flow from peaty soils are more acidic, DOC enriched, and dominated by atmospheric solutes (Na+, Cl-, SO42-). Baseflows are dominated by older groundwater (>∼3years) in contrast to storm runoff dominated by younger (<∼0.5 years), near-surface, waters. Usual seasonal distributions of stream flows, with high flows in winter and summer low flows, result in strong seasonality in most solutes. However, coupled effects of hydroclimatic variability and catchment heterogeneity dictates marked scatter in flow-concentration relationships for most determinands. A long-term decreasing trend was evident for SO42-concentrations, reflecting continuing effects of reductions in atmospheric deposition of pollutants from coal burning. Reductions in large storm event frequency post-2016 and protracted periods of low flows in the droughts of 2018 and 2022 have resulted in the catchment becoming dominated by low flows, derived from older groundwater with more alkaline chemistry for longer periods. Changing climatic conditions and stream flow responses seem likely to continue to cause changes in stream water quality and associated ecosystem services of the Girnock Burn and similar upland catchments.

Land-Use Change Prediction in Dam Catchment Using Logistic Regression-CA, ANN-CA and Random Forest Regression and Implications for Sustainable Land–Water Nexus

For sustainable water resource management within dam catchments, accurate knowledge of land-use and land-cover change (LULCC) and the relationships with dam water variability is necessary. To improve LULCC prediction, this study proposes the use of a random forest regression (RFR) model, in comparison with logistic regression–cellular automata (LR-CA) and artificial neural network–cellular automata (ANN-CA), for the prediction of LULCC (2019–2030) in the Gaborone dam catchment (Botswana). RFR is proposed as it is able to capture the existing and potential interactions between the LULC intensity and their nonlinear interactions with the change-driving factors. For LULCC forecasting, the driving factors comprised physiographic variables (elevation, slope and aspect) and proximity-neighborhood factors (distances to water bodies, roads and urban areas). In simulating the historical LULC (1986–2019) at 5-year time steps, RFR outperformed ANN-CA and LR-CA models with respective percentage accuracies of 84.9%, 62.1% and 60.7%. Using the RFR model, the predicted LULCCs were determined as vegetation (−8.9%), bare soil (+8.9%), built-up (+2.49%) and cropland (−2.8%), with water bodies exhibiting insignificant change. The correlation between land use (built-up areas) and water depicted an increasing population against decreasing dam water capacity. The study approach has the potential for deriving the catchment land–water nexus, which can aid in the formulation of sustainable catchment monitoring and development strategies.

Is Nontarget Analysis Ready for Regulatory Application? Influence of Peak-Picking Algorithms on Data Analysis.

The use of peak-picking algorithms is an essential step in all nontarget analysis (NTA) workflows. However, algorithm choice may influence reliability and reproducibility of results. Using a real-world data set, the aim of this study was to investigate how different peak-picking algorithms influence NTA results when exploring temporal and/or spatial trends. For this, drinking water catchment monitoring data, using passive samplers collected twice per year across Southeast Queensland, Australia (n = 18 sites) between 2014 and 2019, was investigated. Data were acquired using liquid chromatography coupled to high-resolution mass spectrometry. Peak picking was performed using five different programs/algorithms (SCIEX OS, MSDial, self-adjusting-feature-detection, two algorithms within MarkerView), keeping parameters identical whenever possible. The resulting feature lists revealed low overlap: 7.2% of features were picked by >3 algorithms, while 74% of features were only picked by a single algorithm. Trend evaluation of the data, using principal component analysis, showed significant variability between the approaches, with only one temporal and no spatial trend being identified by all algorithms. Manual evaluation of features of interest (p-value <0.01, log fold change >2) for one sampling site revealed high rates of incorrectly picked peaks (>70%) for three algorithms. Lower rates (<30%) were observed for the other algorithms, but with the caveat of not successfully picking all internal standards used as quality control. The choice is therefore currently between comprehensive and strict peak picking, either resulting in increased noise or missed peaks, respectively. Reproducibility of NTA results remains challenging when applied for regulatory frameworks.

Modeling the heat transfer of rainfall runoff in the typical catchment of Beijing

The stormwater runoff formed on the urban impervious surface in summer may carry a large amount of heat, which will have a negative impact on the urban receiving water bodies. In order to simulate the process of runoff generation, confluence, and heat transfer, evaluate the degree of thermal pollution of stormwater runoff, and better quantify the heat of stormwater runoff, a simplified urban stormwater runoff temperature model is developed according to the runoff process of pervious surface and impervious surface and pipe network during rainfall, combined with the heat transfer principle in the process, to calculate the runoff flow and temperature from the small catchment. The heat transfer model mainly considers the heat exchange between runoff and surface, runoff and atmosphere, and runoff and pipe. The proposed model was evaluated by monitoring of typical urban catchment in the summer of 2021–2022, and the calculation formula of Event Mean Temperatures (EMT) in the catchment was proposed based on the model principle. The average root mean square error (RMSE) between the predicted value and the monitoring value of the model is 0.6 ℃. Long duration rainfall and short duration high intensity rainfall could lead to large simulation errors. Runoff temperature is easily affected by air temperature, solar radiation, pre-rain temperature and type of impervious surface. The average error between the EMT calculated by the formula and the actual monitoring EMT is 0.6 ℃, and its significant error rainfall frequency is consistent with the model. The results show that the model and formula can be used to predict the runoff heat in typical catchments, providing a more convenient method for the analysis of runoff heat in small catchments.

Understanding groundwater storage and drainage dynamics of a high mountain catchment with complex geology using a semi-distributed process-based modelling approach

Mountainous groundwater systems are usually characterized by great geological complexity and highly heterogeneous hydraulic properties. For that reason, proper system characterization, monitoring and modelling remain challenging. In this study, we investigated a geologically complex alpine catchment (from 1400 to 2900 m asl) in the Dolomites (Italian Alps) by combining hydrogeological field investigation, hydrological monitoring and modelling. A semi-distributed process-based hydrological model was applied to simulate the continuous measured catchment discharge in a period of three years, which covers a large variation of hydrodynamic conditions. The model structure couples the sequential hydrogeological units within the studied catchment: (1) the fractured dolomitic rocks as bedrock aquifer and 2) the unconsolidated deposits accumulating on the slopes and at the valley floor as porous aquifer. In order to evaluate the model structure and parameterization in depth, we applied a multi-step evaluation approach considering both parameter sensitivity and uncertainty. The modelling results demonstrate that the newly developed model can reproduce most discharge behavior of aquifers. The model indicates a seasonal dynamic linkage between surface and subsurface storage units during different flow conditions. Besides the matrix and conduit flow in fractured dolomitic aquifer, it highlights the important role of unconsolidated sediments (porous aquifer) to the storage and discharge behavior of the entire groundwater system. Furthermore, with the comprehensive model evaluation we learned the model performance deficit during extreme high flow conditions and proposed a more detailed hydrogeological conceptual model. We believe that the proposed modelling approach can be transferred to other high mountain catchments with similar hydro(geo)logical characteristics to characterize the collective behavior of aquifer systems, explore conceptual model weakness and optimize catchment monitoring work.

Twenty years of catchment monitoring highlights the predominant role of long-term phosphorus balances and soil phosphorus status in affecting phosphorus loss in livestock-intensive regions

Livestock husbandry has raised enormous environmental concerns around the world, including water quality issues. Yet there is a need to document long-term water quality trends in livestock-intensive regions and reveal the drivers for the trends based on detailed catchment monitoring. Here, we assessed the concentration and load trends of dissolved reactive phosphorus (DRP) in streamwater of a livestock-intensive catchment in southwestern Norway, based on continuous flow measurements and flow-proportional composite water sampling. Precipitation and catchment-level soil P balance were monitored to examine the drivers. At the field level, moreover, the relationship between soil P balance and soil test P (measured using the ammonium lactate extraction method, P-AL) was assessed. Results showed that on average of 20 years 95 % of the P was applied to the catchment during March–August, when 40 % of annual precipitation and 25 % of annual discharge occurred. The low runoff helped reduce P loss following P applications. However, flow-weighted annual mean DRP concentration significantly increased with increasingly cumulative soil P surplus (R2 = 0.55, p = 0.0002). With a mean annual P surplus of 8.8 kg ha−1, the annual mean DRP concentration (range: 49–140 μg L−1; mean: 80 μg L−1) and annual DRP load (range: 0.35–1.46 kg ha−1; mean: 0.65 kg ha−1) significantly increased over the 20-year monitoring period (p = 0.001 and 0.0003, respectively). At the field level, P-AL concentrations were positively correlated with soil P balances (R2 = 0.48, p < 0.0001), confirming the long-term impact of P balances on the risks of P loss. The study highlights the predominant role of long-term P balances in affecting DRP loss in livestock-intensive regions through the effect on soil test P.

Co‐design of a citizen science study: Unlocking the potential of eDNA for volunteer freshwater monitoring

Abstract Citizen science is increasingly being promoted as a means of gathering more data to help inform the management of ecosystems. Involving the participants in the design of data collection activities is a form of co‐design often proposed by those calling for a translational ecology. In addition, novel monitoring approaches have the potential to improve the quality of data collected by citizen scientists. We explored the potential of environmental DNA (eDNA) for vertebrate (mainly fish) species monitoring through a co‐designed catchment monitoring strategy. Having been introduced to the potential of eDNA, citizen scientists designed and executed an eDNA‐based survey of a small chalk stream catchment to explore questions of concern. The eDNA survey provided data about fish and other vertebrate diversity in the catchment which would have otherwise required sampling approaches difficult for citizen scientists. These data give a preliminary answer to some of the citizen scientists' priority questions and are comparable to fish data collected through traditional electrofishing surveys. Recommendations are offered for co‐design and the use of novel research techniques by citizen scientists.

Nitrogen and phosphorus losses in Nordic and Baltic agricultural monitoring catchments – Spatial and temporal variations in relation to natural conditions and mitigation programmes

Nitrogen (N) and phosphorus (P) losses via agricultural drainage water have negative impacts on receiving water bodies and large-scale programmes to reduce nutrient losses have been established in the Nordic and Baltic countries, together with agricultural catchment monitoring programmes. This study evaluated time series (9–40 years) of data from 34 selected Nordic-Baltic catchments for spatial and temporal variations in area-specific water discharge (mm) and in concentrations and transport of total nitrogen (TN) and total phosphorus (TP).Water discharge from the catchments varied from 125 mm (Denmark) to > 1000 mm (Norway). Catchments with low TN concentrations (≤3 mg L-1) were dominated by clay or grass leys or were undrained with reduction of nitrate (NO3) in shallow groundwater. Catchments with high TN concentrations (≥10 mg L-1) had loams and cereal crops. TP concentrations were highest (≥0.45 mg L-1) in catchments with erosive soils, relatively high water discharge and cereal crops, and lowest (≤0.07 mg L-1) in catchments with permeable soils.Generalised additive mixed model (GAMM) analysis of time series of transport and flow-weighted concentrations of TN and TP for temporal patterns revealed decreases in TN concentrations in seven catchments and increases in eight, while four had periods with opposing trends. TN concentrations decreased in Denmark and Sweden in 1990–2010, following introduction of mitigation programmes. TP concentrations decreased in eight catchments and increased in six, while one showed opposing trends. Decreases in TP coincided with improved P balance in catchments with sand and loam. To further reduce N and P losses, a tailored set of mitigation measures is needed for each combination of soil, climate, geohydrology and agricultural production. Intensive monitoring of small catchments can reveal how N and P losses relate to natural conditions and to changes in agricultural production.

Climate Elasticity of Annual Runoff: Observation in Fifteen Forested Catchments on a Latitudinal Gradient in East Asia

In order to overview the impact of climate change on runoff from forested catchments over Asian countries, we collected water balance data from fifteen long-term catchment monitoring stations (total monitoring period 1975–2018, not continuous), spanning from Sabah, Malaysia (our southernmost site), to Hokkaido, Japan (our northernmost site). We then employed an elasticity analysis to the dataset to examine how the annual runoff from each catchment responded to inter-annual fluctuations in annual rainfall and annual mean air temperature. As a result, we found that (1) the annual runoff was sensitive to annual rainfall for all the catchments examined. In addition, (2) the annual runoff from seven of the fifteen catchments was sensitive to inter-annual changes in the mean air temperature, which was likely due to changes in forest evapotranspiration. Three catchments, however, exhibited an increased runoff in a hot year. Finally, (3) the annual rainfall from the previous year (carry-over soil moisture) was important in explaining the variation in annual runoff in two tropical montane forest catchments. This study may serve as one of the pilot studies toward a comprehensive understanding of the climate elasticity of runoff in countries over Asia, because the examined catchments are unevenly and sparsely distributed over the area.

Machine‐Learning Reveals Equifinality in Drivers of Stream DOC Concentration at Continental Scales

AbstractResearch at long‐term catchment monitoring sites has generated a great volume, variety, and velocity of data for analysis of stream water chemistry dynamics. To harness the potential of these big data and extract patterns that are indicative of underlying functional relationships, machine learning tools have advantages over traditional statistical methods, and are increasingly being applied for dimension reduction, feature extraction, and trend identification. Still, as examples of complex systems, catchments are characterized by multivariate factor interactions and equifinality that are not easily identified by most machine‐learning methods. Using dissolved organic carbon (DOC) dynamics as an illustration, we applied a new evolutionary algorithm (EA) to extract geologic, topographic, meteorologic, hydrologic, and land use attributes that were correlated to mean stream DOC concentration in forested catchments distributed across the continental United States. The EA reduced dimensionality of our attribute dataset to identify the combination of factors, and their specific value ranges, that interacted to drive membership in High or Low mean DOC clusters. High mean DOC concentrations were associated with two distinct geographic locations of variable climatic and vegetative conditions, indicating equifinality. Our findings underscore the importance of critical zone structure in mediating hydrological and biogeochemical processes to govern DOC dynamics at the catchment scale. This multi‐scale, pattern‐to‐process approach is being applied to refine hypotheses for process‐based modeling of DOC dynamics in forested headwater streams at catchment to site scales.

Using check dam deposits to reconstruct changes in the sediment response of a small catchment on the Loess Plateau in China, during the period 1960–1990

AbstractInformation on both the magnitude and relative contributions of inter‐gully and gully areas to the sediment yield from small catchments in the Loess Plateau of China represents an important requirement for understanding catchment sediment dynamics, assessing the sensitivity of catchment sediment budgets to environmental change and developing effective soil and water conservation strategies. Contemporary catchment monitoring programmes can provide such information, but there is also a need to consider past behaviour. Where long‐term records are lacking, attention has been directed to the potential for using the sediment deposits behind check dams to reconstruct the sediment response of the upstream catchment. This contribution reports a study of the 0.181 km2 Nianyangou catchment located in the hilly region of the Chinese Loess Plateau, in Shaanxi Province, China, which has extended a previous study aimed at using individual flood couplets preserved in the check dam deposits to reconstruct the record of annual sediment yield, to include the use of sediment source fingerprinting techniques to document changes in the annual sediment contribution from inter‐gully and gully areas for the period 1960–1990. The sediment response of the catchment provided evidence of two change points in 1964 (Period 1–Period 2) and 1983 (Period 2–Period 3), which reflect the introduction of soil and water conservation measures in the mid 1960s through to the 1970s and a change in the land tenure system in 1983. The annual sediment yields from inter‐gully and gully areas follow the trend P1 &gt; P3 &gt; P2, whereas the equivalent information on the relative contribution of inter‐gully and gully areas follow different trends P3 &gt; P1 &gt; P2 and P2 &gt; P1 &gt; P3, respectively.

Effects of sampling strategy in rivers on load estimation for Nitrate-Nitrogen and total Phosphorus in a lowland agricultural area

The transport of nutrients into water bodies is one of the main causes of water eutrophication. It is therefore important to estimate the loads of nutrients. Discharge and nutrient concentrations are the fundamental elements to estimate the loads of nutrients, the latter can be affected by sampling strategies. As conducting sampling campaign and laboratory analysis are both expensive, it is necessary to find the best effective sampling strategy. The aim of this paper is to show how autocorrelation and standard statistical methods can be used to test the effects of different sampling strategies on the nutrient load estimation and to find the optimal sampling strategy. The data set in this study is from the 50 km² Kielstau catchment, a UNESCO demo site for ecohydrology in Northern Germany and consists of 14 years daily values of climate, hydrology, and water quality from 2006 to 2019. We calculated the autocorrelation (AC) of discharge (Q), precipitation, Nitrate-Nitrogen (NO3-N) and total Phosphorus (Ptot). Then we tested the effects of sampling intervals from 7 to 56 days (1–8 weeks) on the nutrient loads. Our results showed a high AC of Q and NO3-N for a long period, but the AC of Ptot and precipitation decreased very fast. An increase of the sampling interval (less frequent) increased the error of estimating the concentrations and loads. Consequently, we recommend that (1) the optimal sampling strategy for nutrient load estimation in an agriculture-dominant catchment should be continuously monitoring discharge combined with periodic grabbed samples; (2) the sampling frequency for NO3-N is suggested to be monthly (every 28 days) and for Ptot weekly (every 7 days). The information will help those tasked with catchment monitoring to design appropriate sampling strategy to ensure adequate data for nutrients load estimation in lowland rivers.

Drivers of Anaerobic Methanogenesis in Sub-Tropical Reservoir Sediments

Anaerobic methanogenesis is dependent on key macronutrients (carbon, nitrogen and phosphorus) and trace metals (including iron, nickel and cobalt) to drive methane production. Reservoir derived methane emissions have correlated to eutrophication status, with elevated emissions associated with more eutrophic systems. Additionally, sediment organic matter can enhance methane emissions, particularly through the ebullition pathway. As such, it is critical to understand how organic carbon and nutrient inputs into reservoir water columns and sediments drive methanogenesis to improve flooded land greenhouse gas emission estimates. In this study we examine the methane potential of sediments in mesotrophic (Little Nerang Dam) and eutrophic (Lake Wivenhoe) sub-tropical reservoirs under different nutrient and organic carbon availabilities using biological methane potential (BMP) tests. BMP tests were conducted with sediments incubated under anaerobic conditions using replicate controls (reservoir bottom waters) or treatments (excess nutrient and/or organic carbon availability). The results indicated that these systems are carbon limited. The addition of organic carbon significantly increases anaerobic methanogenesis by 20-fold over controls. Analysis of sediment samples from the reservoirs showed that both reservoirs were replete in key macronutrient and trace metal content for methanogenesis. Finally, a comprehensive catchment monitoring program of Little Nerang Dam measuring catchment inflow events, lateral transport of forest litter, and bulk atmospheric deposition showed that catchment inflows and lateral transport of forest litter were strongly linked to rainfall and accounted for more than 99% of the total annual load. This suggests the frequency of rainfall events is a critical driver of organic matter inputs that drive reservoir methane emissions in the humid, sub-tropical region.

Passive sampling as an alternative strategy to monitor metals and PAHs trends at an upstream and rural catchment: a French case study

The study presents an alternative strategy to conventional spot sampling for monitoring metals and polycyclic aromatic hydrocarbons (PAHs) at an upstream, rural and karstic catchment in the north eastern part of France, in order to get insight into their spatial and temporal variability. Passive samplers, as diffusive gradients in thin films (DGT) and semipermeable membrane device (SPMD), are monthly deployed from August 2012 to March 2016 at five of the catchment monitoring stations located on the Saulx and Ornain Rivers. An improvement of the frequency of quantification (by a factor 2 to 8, depending on the targeted compound) is observed allowing us to better identify spatial and temporal variability. For instance, the upstream monitoring station on the Saulx River is characterized by high concentrations of Ni and Mn whereas the upstream monitoring station on the Ornain River is enriched in Cu and Zn. Furthermore, five metals (Al, Fe, Mn, Ni, Zn) and three PAHs (fluoranthene, pyrene and chrysene) show significant variations with water levels when grouped in three categories (low, medium and high water levels) in relation with hydrological and climatic patterns. This study leads to a more accurate assessment of the background pollution in metals and PAHs within surface waters than when based on spot sampling data.

Monitoring invasive alien macroinvertebrate species with environmental DNA

AbstractRegular monitoring of ecosystems can be used for the early detection of invasive alien species (IAS), and provide information for management and preventing them from becoming established or advancing into new areas. Current methods of monitoring freshwater systems for IAS can be both financially costly and time‐consuming, with routine monitoring often carried out at low intensity and at only a small number of sites. In this study, we evaluate how environmental DNA (eDNA) metabarcoding for monitoring freshwater macroinvertebrate IAS compares to traditional kick‐net sampling as part of a national (Switzerland) and a catchment monitoring programme. Kick‐net sampling was more fruitful for the detection of several well‐known target macroinvertebrate IAS. However, eDNA samples proved complementary for the detection of IAS that belong to species often being unnoticed by traditional sampling due to methodological or taxonomic reasons. Specifically, the invasive jellyfish Craspedacusta sowerbii, hardly detectable using classic kick‐net sampling, was found to be widespread in both the national and the catchment‐scale monitoring with the eDNA method only. Our study shows that IAS detection using eDNA is easily implemented in both national‐ and catchment‐scale monitoring campaigns. However, successful detection of target IAS is still highly dependent on primer choice, species' biology, and availability of adequate markers. Specifically, multiple markers should be considered for detecting IAS from several different taxonomic groups, such as those under the ‘freshwater macroinvertebrate’ umbrella term. While eDNA is still developing in terms of these fundamental methodological requirements, surveillance for both target and non‐target IAS using eDNA is likely to increase efficiency in early detection of IAS in freshwater systems.

Remote clinical assessment of inflammatory bowel disease using smartphone applications

INTRODUCTION Inflammatory bowel disease (IBD) is a chronic, relapsing disease requiring ongoing monitoring. Smartphone applications will allow remote monitoring of a large geographical catchment of Waitematā District Health Board (WDHB). IBDSmart (Otago University/Gut Health Network) is a phone application for patients to self-report flares and monitor disease using validated scoring systems. IBDSmart has been shown to be non-inferior to standard care and to reduce face-to-face appointments. IBD-Disk® provides validated visual representation of Quality of Life (QoL), allowing for patient-centred discussions in clinic and tracking QoL with treatment. The aim of this study was to understand if these applications are feasible in the outpatient setting in terms of patient/clinician feedback and validity of patient’s scores. METHODS IBD patients attending WDHB gastroenterology clinics were recruited over the phone, emailed brochures, and asked to complete IBDSmart/IBD-Disk® surveys one to two weeks before their appointments. Clinicians were provided with Harvey Bradshaw Index (HBI)/ Simple Clinical Colitis Activity Index (SCCAI) at appointment and reminded to discuss IBD-Disk® responses. Feedback was collected using five-point scoring of five affirmative statements. RESULTS Eighty-four participants were contacted; 45 used IBDSmart and 10 used IBD-Disk®. Nine clinicians were involved. There were technical issues; IBDSmart links expired within 48hours, and IBD-Disk® does not work in Android Operating Systems 9.0–11.0. The majority (≥60%) of participants and clinicians either completely agreed or agreed with statements. Correlation between clinician and patient scores was moderate (R2 for HBI 0.52, for SCCAI 0.49). CONCLUSIONS Both applications are highly useable and accepted by patients and clinicians. However, technological issues need to be addressed. Correlation of scores could be improved through increased patient education and application design.

Spatiotemporal trends and annual fluxes of pharmaceuticals in a Scottish priority catchment

Pharmaceuticals (a class of emerging contaminants) are continuously introduced into effluent-receiving surface waters due to their incomplete removal within wastewater treatment plants (WWTPs). This work investigated the presence and distribution of eight commonly used human pharmaceuticals in the River Dee (Scotland, UK), a Scottish Environment Protection Agency priority catchment that is a conservation site and important raw water source. Grab sampling and passive sampling (Polar Organic Chemical Integrative Sampler, POCIS) was performed over 12 months, targeting: paracetamol, ibuprofen, and diclofenac (analgesics/anti-inflammatories); clarithromycin and trimethoprim (antibiotics); carbamazepine and fluoxetine (psychoactive drugs); and 17α-ethynylestradiol (estrogen hormone). Sampling sites spanned from the river's rural source to the heavily urbanised estuary into the North Sea. Ibuprofen (ranging 0.8–697 ng/L), paracetamol (ranging 4–658 ng/L), trimethoprim (ranging 3–505 ng/L), diclofenac (ranging 2–324 ng/L) and carbamazepine (ranging 1–222 ng/L) were consistently detected at the highest concentrations through grab sampling, with concentrations generally increasing down river with increasing urbanisation. However, POCIS revealed trace contamination of most compounds throughout the river (commonly <0.5 ng/L), indicating pollution may be related to diffuse sources. Analysis of river flows revealed that low flow and warm seasons corresponded to statistically significantly higher concentrations of diclofenac and carbamazepine, two compounds of environmental and regulatory concern. Below the largest WWTP, annual average fluxes ranged 0.1 kg/yr (clarithromycin) to 143.8 kg/yr (paracetamol), with 226.2 kg/yr for total target compounds. It was estimated that this source contributed >70% of the total mass loads (dissolved phase) of the target compounds in the river. As the River Dee is an important raw water source and conservation site, additional catchment monitoring is warranted to safeguard water quality and assess environmental risk of emerging contaminants, particularly in relation to unusual weather patterns, climate change and population growth.

Monitoring of Rainfall and Soil Moisture at the Rebaixader Catchment (Central Pyrenees)

ABSTRACT The instrumental monitoring of torrential catchments is a fundamental research task that provides necessary information to improve our understanding of the mechanisms of debris flows. While most monitoring sites include meteorological sensors and analyze the critical rainfall conditions, very few contain soil moisture measurements. In our monitoring site, the Rebaixader catchment, 11 debris flows and 24 debris floods were detected during the last 9 years. Herein, the initiation mechanisms of these torrential flows were analyzed, focusing on the critical rainfall conditions and the soil water dynamics. Comparing the temporal distribution of both rainfall episodes and torrential flows, the Kernel density plots showed maximum values for rainfalls at the beginning of June, while the peak for torrential flows is on July 20. Thus, the antecedent rainfall, and especially the soil moisture conditions, may influence the triggering of torrential flows. In a second step, a new updated rainfall threshold was proposed that included total rainfall duration and mean intensity. The analysis of soil moisture data was more complicated, and no clear trends were observed in the data set. Therefore, additional data have to be recorded in order to quantitatively analyze the role of soil moisture on the triggering of torrential flows and for the definition of thresholds. Some preliminary results show that the soil moisture at the beginning of a rainfall event affects the maximum increase of soil moisture, while a slight trend was visible comparing the initial soil moisture with the necessary rainfall amount to trigger a torrential flow.

Hydrological and meteorological data from research catchments at the Marcell Experimental Forest, Minnesota, USA

AbstractThe Marcell Experimental Forest (MEF) in northern Minnesota, USA, with hydrological research and monitoring of peatland catchments in a low‐topographic relief landscape, contrasts with the mountainous terrain that typifies most research catchments. Six research catchments were instrumented and hydrological and meteorological monitoring was initiated during 1960. Paired‐catchment studies, which started during 1969, have been used to assess land management and environmental change effects on forests, water availability, and biogeochemistry. Over the decades, the research and collaborations have proliferated to include new monitoring and ecosystem experiments. We provide an overview of available datasets and access information for hydrological and meteorological data. Data on streamflow, water table elevation, precipitation, snow, ground frost, air temperature, soil moisture, upland runoff, and water chemistry are discoverable with associated metadata and are archived through several Web‐based, community repositories. The research programme is ongoing and we anticipate updates on an annual or more frequent basis. Additionally, we aim to release other physical, chemical, and isotopic measurements associated with long‐term catchment monitoring and studies at the MEF.

Impact of Escherichia coli from stormwater drainage on recreational water quality: an integrated monitoring and modelling of urban catchment, pipes and lake

In recent years, recreational waterbodies are increasingly favoured in urban areas. In spite of the growing concerns for maintaining the required bathing water quality, the impacts of stormwater drainage are still poorly controlled. In this context, this study originally develops an integrated urban catchment-pipes-lake monitoring and modelling approach to simulate the impacts of microbial quality from stormwater drainage on recreational water quality. The modelling system consists of three separated components: the urban catchment component, the 3D lake hydrodynamic component and the 3D lake water quality component. A series of processes are simulated in the model, such as rainfall-discharge, build-up, wash-off of Escherichia coli (E. coli) on urban surfaces, sewer flows, hydrothermal dynamics of lake water and transport and mortality of E. coli in the lake. This integrated model is tested for an urban catchment and its related recreational lake located in the Great Paris region. Continuous monitoring and samplings were performed at the stormwater drainage outlet and three different sites in the lake. Comparing the measured data with simulation results over 20 months, the modelling system can correctly represent the E. coli dynamics in the stormwater sewer systems and in the lake. Although uncertainties related to parameter values, pollution sources and E. coli mortality processes could be further discussed, the good performance of this modelling approach emphasizes a promising potential for urban bathing water quality management.