Sampling Program Research Articles

Are more data always better? – Machine learning forecasting of algae based on long-term observations

Bloom-forming algae present a unique challenge to water managers as they can significantly impair provision of important ecosystem services and cause health risks to humans and animals. Consequently, effective short-term algae forecasts are important as they provide early warnings and enable implementation of mitigation strategies. In this context, machine learning (ML) emerges as a promising forecasting tool. However, the performance of ML models is heavily dependent on the availability of appropriate training data. Consequently, it is essential to determine the volume of data necessary to develop reliable ML forecasts. Understanding this will guide future monitoring strategies, optimize resource allocation, and set realistic expectations for management outcomes. In this study, we used 30 years of fortnightly measurements of 13 different parameters from a lake in the English Lake District (UK) to examine the impact of training data duration on the performance of ML models for forecasting chlorophyll-a two weeks in advance. Once training data availability exceeded four years, a Random Forest model was found to consistently outperform naive benchmarks (mean absolute percentage error 16.4 % lower than the best-performing benchmark). With more than 5 years of training data, model performance generally continued to improve, but with diminishing returns. Furthermore, it was found that equivalent and, in some cases, better performance could be achieved by only using a subset of the most important input features. Additionally, it was found that reducing the sampling frequency had negative impacts on performance, both due to the reduced number of training observations available, and increased forecast horizon. Our findings demonstrate that for lakes ecologically similar to the study site, a consistent and regular sampling programme focused on monitoring a limited number of key parameters can provide sufficient observations for generating short-term algae forecasts after approximately five years of data collection. Importantly, this result provides justification for the initiation of new monitoring programmes for sites where algal blooms are a concern, and suggests that there are likely many pre-existing monitoring datasets which would be suitable for training algae forecast models.

Impact energy absorption in 3D printed bio-inspired PLA structures

3D printing is an effective technique for designing and producing products with unique shapes that cannot be made using traditional methods. Polylactic acid (PLA) filaments, commonly used in 3D printing, are a promised material for fabricating composites and lightweight structures. This study investigates the fracture and damping properties of biodegradable PLA samples with a bio-inspired structure and different density under dynamical (ballistic) loading. PLA samples were fabricated using a 3D printer and a Fusion Deposition Modeling (FDM) method. A unique computer program for cellular samples with Schwartz-Diamond minimal surface topology was developed. The impact absorption energy under ballistic loading of PLA samples with Schwarz-Diamond surface structure was found to depend on their density and impact velocity. The internal structure of 3D-printed PLA cellular samples with a Schwarz-Diamond triply periodic minimal surface and the fracture mechanism of the cellular samples with different densities were demonstrated using scanning electron microscopy. It was found that the fracture mechanism changed from ductile to quasi-brittle with increasing sample density. This work provides a foundation for understanding the fabrication of plastic cellular products using 3D printing.

Presentation of representative shape parameters of porous media based on mathematical computation on images

The shape parameters of porous media are really important to describe the petrophysical and geomechanical parameters of reservoirs. In addition, shape analysis can provide essential information about the origin, transport, deposition history of particles, etc. Because macroscopic properties (such as permeability, diffusion, etc.) are influenced by microscopic properties (such as pore size, grain shape, etc.). So far, various studies have been conducted to calculate some shape parameters, however, there is no comprehensive study that first includes most of the geometric parameters of the shape and then presents the representative shape parameters. Therefore, the aim of this study is to present representative shape parameters of porous media based on mathematical computation on images. The shape parameters studied included roundness, circularity, angularity, convexity, compactness, sphericity, aspect ratio, elongation, eccentricity, shape factor, and regularity. Calculation of shape parameters is done digitally using the developed program. The necessary data for the desired analysis are obtained from real sandstone samples. To develop this research, first, the mentioned shape parameters are calculated using the developed program for all rock samples. Then, by establishing a relationship between the mentioned parameters, the representative parameters that can show the shape of the porous medium are expressed. The results of this study show that the representative shape parameters of the porous medium are compactness, shape factor-round, and aspect ratio, which are good indicators for the shape of the porous medium.

Providing quality-assessed and standardised soil data to support global mapping and modelling (WoSIS snapshot 2023)

Abstract. Snapshots derived from the World Soil Information Service (WoSIS) are served freely to the international community. These static datasets provide quality-assessed and standardised soil profile data that can be used to support digital soil mapping and environmental applications at broad scale levels. Since the release of the preceding snapshot in 2019, refactored ETL (extract, transform and load) procedures for screening, ingesting and standardising disparate source data have been developed. In conjunction with this, the WoSIS data model was overhauled, making it compatible with the ISO 28258 and Observations and Measurements (O&M) domain models. Additional procedures for querying, serving and downloading the publicly available standardised data have been implemented using open software (e.g. GraphQL API). Following up on a short discussion of these methodological developments we discuss the structure and content of the “WoSIS 2023 snapshot”. A range of new soil datasets was shared with us, registered in the ISRIC World Data Centre for Soils (WDC-Soils) data repository and subsequently processed in accordance with the licences specified by the data providers. An important effort has been the processing of forest soil data collated in the framework of the EU-HoliSoils project. We paid special attention to the standardisation of soil property definitions, description of the soil analytical procedures and standardisation of the units of measurement. The 2023 snapshot considers soil chemical properties (total carbon, organic carbon, inorganic carbon (total carbonate equivalent), total nitrogen, phosphorus (extractable P, total P and P retention), soil pH, cation exchange capacity and electrical conductivity) and physical properties (soil texture (sand, silt and clay), bulk density, coarse fragments and water retention), grouped according to analytical procedures that are operationally comparable. Method options are defined for each analytical procedure (e.g. pH measured in water, KCl or CaCl2 solution, molarity of the solution, and soil / solution ratio). For each profile we also provide the original soil classification (i.e. FAO, WRB and USDA system with their version) and pedological horizon designations as far as these have been specified in the source databases. Three measures for “fitness for intended use” are provided to facilitate informed data use: (a) positional uncertainty of the profile's site location, (b) possible uncertainty associated with the operationally defined analytical procedures and (c) date of sampling. The most recent (i.e. dynamic) dataset, called wosis_latest, is freely accessible via various web services. To permit consistent referencing and citation, we also provide a static snapshot (in this case, December 2023). This snapshot comprises quality-assessed and standardised data for 228 000 geo-referenced profiles. The data come from 174 countries and represent more than 900 000 soil layers (or horizons) and over 6 million records. The number of measurements for each soil property varies (greatly) between profiles and with depth, this generally depending on the objectives of the initial soil sampling programmes. In the coming years, we aim to gradually fill gaps in the geographic distribution of the profiles, as well as in the soil observations themselves, this subject to the sharing of a wider selection of “public” soil data by prospective data contributors; possible solutions for this are discussed. The WoSIS 2023 snapshot is archived and freely available at https://doi.org/10.17027/isric-wdcsoils-20231130 (Calisto et al., 2023).

Modeling Urban Temperature Using Measurements from Mobile and Stationary Monitoring Stations

Heat waves are occurring more frequently worldwide as global warming continues, and urban heat islands can threaten conventional life in cities. Measuring, analyzing, and simulating weather data at fine spatial and temporal scales are essential to prevent and reduce the damage caused by extreme heat waves. In urban environments, handling complex micrometeorological situations using current meteorological stations and global simulation models (e.g., weather research forecasting models) is challenging. In this study, the thermal environments of urban areas were measured using a mobile meteorological measurement platform. Both mobile and stationary datasets were incorporated into the meteorological modeling process to simulate the spatial and temporal distribution of temperature. Additionally, various mobile observation implementation scenarios for temperature modeling were examined. We compared simulation combinations with the temperature field generated from the total dataset to obtain a better sampling campaign and properly incorporate mobile data scenarios. When collecting mobile data, it is important to consider spatial features to improve the efficiency of sampling programs. This can substantially reduce the cost of mobile data collection, together with the sensor error bound.

An ecological niche model that considers local relationships among variables: The Environmental String Model

AbstractMany methods have been proposed to model the spatial distribution of a species. While some methods have been specifically designed for this purpose, others are well‐known statistical tools that can be used in many scientific fields. In this paper, I propose a new ecological niche model, called the Environmental String Model (ESM), that is based on the concept of environmental string, which is defined as being a combination of environmental variables, with as many nodes as environmental variables. There are two types of environmental strings: (1) the abundance‐known string and (2) the abundance‐unknown string (or target string) for which an estimation of abundance is searched. The novelty of the model is that it assesses the abundance associated with a target string from nearby abundance‐known strings, which preserve the local multidimensional relationships with the target string. The model does not provide an abundance estimate in the absence of data from a similar environment and it can therefore deal with truncated spatial distributions or niches. It is tested in the North Atlantic Ocean on two key copepod species, Calanus finmarchicus and Calanus helgolandicus, which have been monitored by the Continuous Plankton Recorder (CPR) survey for decades. I investigate the influence of variables on model performance. I show that the model reconstructs the mean spatial distribution and seasonal fluctuations in both Calanus well. When compared with generalized linear models (GLMs), generalized additive models (GAMs) and generalized regression neural network (GRNN), the ESM gives the best performance. I propose a number of indicators to evaluate the robustness of estimated abundance in space and time and show how the model may be extended to presence/absence or presence‐only data. I think that the ESM could be used to fill gaps in any sampling program such as the CPR survey and many satellite databases (e.g., ocean color and photosynthetically active radiation).

Case Study: Understanding H2S Occurrence: Bakken Production Using Sulfur Isotopes

_ Souring—or H2S generation—in the Bakken petroleum system (BPS) production is becoming problematic for oil producers and pipeline operators because of the sporadic occurrence and associated economic and HSE impacts. Paradoxically, crude oil produced from the tight Middle Bakken (MB) and underlying Three Forks (TF) reservoirs of the BPS has historically been light (40 °API to 50 °API) with low sulfur content (<0.2 wt.%), typically exhibiting nonexistent to low (<10 parts per million) H2S concentrations. Additionally, neither the MB nor the TF reservoirs have public records indicating the presence of H2S during drillstem tests (DST). However, based on previous work performed by the University of North Dakota Energy & Environmental Research Center (EERC), the frequency of H2S occurrence in BPS wells has increased from 2010 to 2023. Even though the observed H2S increases correlate with larger, multistage well stimulation and completion practices in the BPS, the unclear geographical and temporal trends make the exact mechanisms responsible for souring an open research question. At least five known mechanisms can potentially lead to H2S occurrence in the oil production stream of BPS wells, including: 1. Thermochemical sulfate reduction (TSR) 2. Bacterial sulfate reduction (BSR) 3. Source rock generation 4. Migration from deeper or shallower H2S reservoirs 5. Geochemical mechanisms related to reservoir stimulation work (Table 1). Understanding the mechanisms of H2S generation might reduce the risk of souring in new wells and enable more effective mitigation and management strategies in the wells already producing H2S. Samples Used in the Study This study is focused on oil and gas operations in the North Dakota portion of the Williston Basin and the H2S occurrences in the BPS, which includes two main oil-producing reservoirs: the MB and the TF. In the simplified stratigraphic sequence, the BPS comprises three distinctive lithofacies. From deepest to shallowest, those lithofacies are the Lower Bakken Shale (LBS), the MB reservoir, and the Upper Bakken Shale (UBS). Underlying the BPS is the TF, the upper part of which is the oil-rich TF reservoir, considered part of the BPS. The UBS and LBS are the source rocks for the oil in MB and TF reservoirs and consist of black, organic-rich, siliciclastic mudstones (i.e., shale). Directly overlying the BPS is the Madison Group, a carbonate-dominated Mississippian section that is subdivided into three formations—the Lodgepole (LP), Mission Canyon (MC), and Charles. The Birdbear Formation lies beneath the TF and on top of the Duperow Formation. Both the Duperow and Birdbear Formations produce oil and are dominated by carbonate deposits of shallow marine limestone and dolostones. A sampling program was developed to investigate areas of the BPS with varying levels of souring in the production stream and multiple organic-rich formations representing potential source rocks, including the UBS, LBS, LP, and MC. The samples were collected from locations and formations with different lithologies and maturity levels. Over 70 sour wells were identified for H2S sampling in western North Dakota.

A Conceptual Site Model for Per‐ and Polyfluoroalkyl Substance Water Supply Impacts in a Residential Community

ABSTRACTAt a Class 4 State Superfund site located in a densely developed residential/commercial area in a suburb of New York City, emerging contaminant sampling for PFAS was performed as part of a statewide data‐gathering project. Two per‐ and polyfluoroalkyl substances (PFAS), perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS), were detected at concentrations in excess of drinking water standards in bedrock and overburden monitoring wells at the State Superfund site. A bedrock private water supply well sampling program and a PFAS source investigation, consisting of overburden investigations near potential sources (i.e., sites with a history of known or suspected use, storage, or discharge of PFAS), were undertaken to assess exposures and identify and potentially eliminate sources of PFAS contaminants in the bedrock drinking water supply.Relative ratios of PFAS (i.e., PFAS signatures) were plotted geospatially to facilitate comparison of the characteristics of overburden groundwater sampling results to that of nearby bedrock private water supply sampling results. In addition, total PFAS concentrations in overburden groundwater and bedrock private water supply samples were compared to identify potential sources of bedrock groundwater impacts. The PFAS signature analysis revealed that (1) PFAS signatures of overburden groundwater samples were generally consistent with nearby bedrock private water supply samples; (2) total PFAS concentrations detected in overburden groundwater samples were marginally higher than concentrations detected in nearby bedrock private water supplies; (3) there was generally low variability in PFAS signatures throughout the study area (Assessment Area); and (4) overburden groundwater and bedrock private water supply PFAS signatures were similar to that of the nearby wastewater treatment plant effluent discharge, which represents a composite average PFAS signature for domestic wastewater from the area. Finally, septic system tracers were also detected in bedrock private water supply and overburden groundwater samples. Based on the results of the investigation, multiple lines of evidence support the Conceptual Site Model, which is likely applicable to many PFAS‐contaminated drinking water supplies with conditions similar to the Assessment Area: consumer product use and discharge to domestic septic systems in a densely developed residential area, lacking area‐wide municipal water and sewer, with shallow groundwater and bedrock, and a vertical downward groundwater gradient, have resulted in the widespread presence of PFAS in private water supply wells.

Monitoring of Larinus spp. (Coleoptera Curculionidae) infesting cardoon and development of a binomial sampling plan for the estimation of Larinus cynarae infestation level in Mediterranean conditions

The cultivation of cardoon, Cynara cardunculus var. altilis, for multi-purpose uses has increased substantially in recent decades. However, in some cardoon growing areas, the production of achenes is threatened by several insects, especially the weevils Larinus cynarae and Larinus scolymi. Due to the lack of specific monitoring and sampling programs for these pests, the aims of this work were to test the reliability of chromotropic traps for adult Larinus spp. monitoring and to develop binomial sequential sampling plans to assess the infestation level of L. cynarae in cardoon cultivations in a Mediterranean area. Field observations were conducted in two different cardoon growing areas in Sardinia (Italy) in 2019 and 2020. Purple- and red-colored cross-vane traps, placed at 1 m and 2 m above the ground, were utilized for monitoring Larinus spp. adults, and binomial sequential sampling plans were developed for L. cynarae based on the count of egg masses on flower heads for sample sizes of 30, 40, 50, 60, and 70 flower heads. The purple traps at 2 m above the ground were effective in monitoring L. scolymi, whereas red and purple traps were ineffective in monitoring L. cynarae adults at both 1 m and 2 m above the ground. Among different binomial sampling plans, a sample size of 70 flower heads is needed to obtain reliable estimates of L. cynarae infestations at or above 25% of infested flowers. Our findings constitute a baseline for the development of an integrated pest management program for the control of Larinus spp. infestations in cardoon-growing areas in Mediterranean environment.

Pharmacy Compounding Regulation in the German Pharmaceutical Market. Part 2. Organisational Features (Review)

INTRODUCTION. The Russian Federation has decided to restore the system of compounding pharmacies as an element of the critical national healthcare infrastructure and pharmaceutical supply chain. To improve Russian regulatory practices, develop novel advanced approaches to pharmacy compounding and quality control, and implement these approaches, it is necessary to study relevant good compounding practices applied in healthcare systems of other countries.AIM. The study aimed to analyse the German experience in the organisation and regulation of pharmaceutical compounding to suggest recommendations for the development and implementation of Russian guidelines on good compounding and dispensing practices.DISCUSSION. This work continues a comprehensive study that delves into the current provisions of German legislation governing the system of good compounding practices. This article examines the differences between approaches to compounding by medical and pharmaceutical specialists. According to the findings, compounding by medical specialists is guided by the “free practice of medicine” principle and is subject to minimal regulatory oversight. All pharmacy organisations operate as compounding pharmacies, thereby enhancing the physical accessibility of compounded medicinal products to the population. The authors highlight the features of a process-based quality assurance system encompassing production process controls and quality control methods for compounded medicinal products. Additionally, the authors discuss the applicability of rapid test methods to compounding. In accordance with the German concept of good pharmacy practices, a compounding pharmacy may use the available validation, qualification, and verification tools in the pharmaceutical development of compounded medicinal products and may outsource its internal quality control function. Using the concept of risk ranking, compounding pharmacies may design their own sampling programmes. The article describes approaches to and requirements for organising the evaluation of compounding prescriptions. In Germany, compounding pharmacies may independently assign shelf lives to the compounded medicinal products they produce.CONCLUSIONS. Some German solutions are of considerable practical importance and are applicable to the development and implementation of Russian guidelines on good compounding and dispensing practices. In particular, pharmacy organisations may outsource the quality control of their compounded medicinal products. Additionally, pharmacies can conduct the full-scale pharmaceutical development of compounding technologies and quality control methods (including rapid test methods) using the validation, qualification, and verification tools available to drug manufacturers. Moreover, pharmacy organisations may independently assign shelf lives to the compounded medicinal products they produce. Finally, pharmacy organisations may design their individual sampling programmes.

Overview of the MOSAiC expedition: Ecosystem

The international and interdisciplinary sea-ice drift expedition “The Multidisciplinary drifting Observatory for the Study of Arctic Climate” (MOSAiC) was conducted from October 2019 to September 2020. The aim of MOSAiC was to study the interconnected physical, chemical, and biological characteristics and processes from the atmosphere to the deep sea of the central Arctic system. The ecosystem team addressed current knowledge gaps and explored unknown biological properties over a complete seasonal cycle focusing on three major research areas: biodiversity, biogeochemical cycles, and linkages to the environment. In addition to the measurements of core properties along a complete seasonal cycle, dedicated projects covered specific processes and habitats, or organisms on higher taxonomic or temporal resolution in specific time windows. A wide range of sampling instruments and approaches, including sea-ice coring, lead sampling with pumps, rosette-based water sampling, plankton nets, remotely operated vehicles, and acoustic buoys, was applied to address the science objectives. Further, a broad range of process-related measurements to address, for example, productivity patterns, seasonal migrations, and diversity shifts, were made both in situ and onboard RV Polarstern. This article provides a detailed overview of the sampling approaches used to address the three main science objectives. It highlights the core sampling program and provides examples of habitat- or process-specific sampling. The initial results presented include high biological activities in wintertime and the discovery of biological hotspots in underexplored habitats. The unique interconnectivity of the coordinated sampling efforts also revealed insights into cross-disciplinary interactions like the impact of biota on Arctic cloud formation. This overview further presents both lessons learned from conducting such a demanding field campaign and an outlook on spin-off projects to be conducted over the next years.

Fluoride geochemistry in groundwater at regulated industrial sites.

Few studies apply geochemical concepts governing fluoride fate and transport in natural waters to geochemical conditions at contaminated industrial sites. This has negative implications for designing sampling and compliance monitoring programs and informing remediation decision-making. We compiled geochemical data for 566 groundwater samples from industrial waste streams associated with elevated fluoride and that span a range of geochemical conditions, including alkaline spent potliner, near-neutral pH coal combustion, and acidic gypsum stack impoundments. Like natural systems, elevated fluoride (hundreds to thousands of ppm) exists at the pH extremes and is generally tens of ppm at near-neutral pH conditions. Geochemical models identify pH-dependent fluoride complexation at low pH and carbonate stability at high pH as dominant processes controlling fluoride mobility. Limitations in available thermochemical, kinetic rate, and adsorption/desorption data and lack of complete analyses present uncertainties in quantitative models used to assess fluoride mobility at industrial sites. PRACTITIONER POINTS: Geochemical fundamentals of fluoride fate and transport in groundwater are communicated for environmental practitioners. Fluoride is a reactive constituent in groundwater, and factors that govern attenuation are identified. Geochemical models are useful for identifying fluoride attenuation processes, but quantitative use is limited by thermodynamic data uncertainties.

Volatile organic compounds and cancer risk assessment in an intensive care unit.

Changes caused by air-cleaning devices in the amounts of volatile organic compounds in an intensive care unit were monitored in the study. The cancer risk and hazard index were calculated. The measurements were made for one month at isolated room and two different points and times in the intensive care unit. According to the sampling program, the air-cleaning devices were turned off in weeks 1 and 4 and turned on in weeks 2 and 3. Volatile organic compounds were collected by active sampling. Samples were analyzed by a thermal desorber coupled to a gas chromatography-mass spectrometry instrument with selective ion monitoring. The results showed that the concentrations of benzene, toluene, and o-xylene decreased by about 70% after the air-cleaning devices were installed. The cancer risk assessment for naphthalene was recorded at the highest level of cancer risk (Class A). The hazard index value of naphthalene was recorded at the harmful level when air-cleaning devices were not installed. The concentrations of benzene (p = 0.01), toluene (p = 0.02), ethylbenzene (p = 0.02), styrene (p = 0.01), and m, p-xylene (p = 0.04) before the air-cleaning devices were installed were significantly different from those recorded when the air-cleaning devices were turned on.

Particle size distribution of total suspended sediments in urban stormwater runoff: Effect of land uses, precipitation conditions, and seasonal variations

Understanding particle size distribution (PSD) of total suspended sediments in urban runoff is essential for pollutant fate and designing effective stormwater treatment measures. However, the PSDs from different land uses under different weather conditions have yet to be sufficiently studied. This research conducted a six-year water sampling program in 15 study sites to analyze the PSD of total suspended sediments in runoff. The results revealed that the median particle size decreased in the order: paved residential, commercial, gravel lane residential, mixed land use, industrial, and roads. Fine particles less than 125 μm are the dominant particles (over 75%) of total suspended sediments in runoff in Calgary, Alberta, Canada. Roads have the largest percentage of particles finer than 32 μm (49%). Gravel lane residential areas have finer particle sizes than paved residential areas. The results of PSD were compared with previous literature to provide more comprehensive information about PSD from different land uses. The impact of rainfall event types can vary depending on land use types. A long antecedent dry period tends to result in the accumulation of fine particles on urban surfaces. High rainfall intensity and long duration can wash off more coarse particles. The PSD in spring exhibits the finest particles, while fall has the largest percentage of coarse particles. Snowmelt particles are finer for the same land use than that during rainfall events because the rainfall-runoff flows are usually larger than the snowmelt flows.

Nitrogen and phosphorus cycling for aquaculture ponds with artificially-controlled drainage: Sources, sinks and treatment strategies

Nitrogen (N) and phosphorus (P) loss from freshwater aquaculture ponds has been an on-going challenge due to its direct link to lake/river eutrophication. However, characterizing N & P cycling and its response to treatment strategies for the ecosystems is difficult due to the complexity of artificially-controlled drainage and biogeochemical cycling. To address this challenge, this study specifically developed a nutrient dynamic model (Pond-NP) for aquaculture ponds to track the daily sources, sinks and biogeochemical cycling of N & P. A month sampling program was carried out at a typical Chinese mitten crab (Eriocheir sinensis) culture pond during 2020–2022 to evaluate the model performance. The model achieved a model fit of Nash-Sutcliffe efficiency >0.43. Our modelling practices revealed that the studied pond had a total inputs of 187.3 kg N/ha/yr and 29.8 kg P/ha/yr, with N & P use efficiencies of 35.4% and 28.1%, respectively. Among the used N & P, macrophytes had a larger (>51.2%) contribution than the cultivated animals, resulting in a limited improvement (<2%) of nutrient use efficiency via the stocking strategies. More input N & P was lost to sediment (31.4% and 63.4% of total inputs) than surrounding rivers (17.6% and 8.5% of total inputs). Ex-situ ecological treatment was estimated to reduce N & P significantly (>40%) for aquaculture tail water, and was thus recommended to control N & P loss together with sediment reuse. This study demonstrated the high value of our newly-developed model in quantifying N & P loss, and thus supporting the design of N & P mitigation strategies for aquaculture ponds.

De-risking green energy from mine waters by developing a robust hydrogeological conceptual model of the UK Geoenergy Observatory in Glasgow

Mine-water geothermal resources have potential to provide low-carbon heating and cooling in many areas; however, this potential has not been fully realised due to technical, economic and policy challenges. The UK Geoenergy Observatory (UKGEOS) in Glasgow was developed to provide an at-scale research facility designed to help de-risk mine-water geothermal usage. The limited knowledge of the hydrogeological systems altered by former mining activities is a key determinant of the long-term sustainability of water and heat abstraction/reinjection. This work presents a hydrogeological conceptual model developed using groundwater monitoring data obtained during the construction of the Observatory between 2020 and 2022, results from initial pumping tests performed in 2020, and results of hydrochemistry analysis from 25 sampling rounds collected between 2019 and 2022. The analysis of the data provides evidence of the dominant role of mine workings in controlling groundwater flow, with high intra-mine connectivity; increased fracturing in sandstones above mine workings; and limited inter-mine connectivity. Groundwater recharge is meteoric, mean residence times are >50 years, and there is a general upwards circulation from the deeper mine levels to the superficial deposits and the River Clyde. Faults play a significant role in limiting the extent of the highly transmissive mine workings, but there remains uncertainty surrounding the role of the faults in connecting different mine workings and their hydraulic behaviour in nonmined units. The conceptual model, that will be refined as new data become available, will be used to help guide monitoring and sampling programs and plan research activities in the Observatory.

Is comprehensive event sampling necessary for constraining process models of water quality? A comparison of high and low frequency phosphorus sampling programs for constraining the HYPE water quality model

Model parameter calibration is an important step in process-based watershed water quality modelling. Calibration is commonly performed using readily available water quality data from long-term monitoring programs that collect samples periodically at a relatively low frequency (i.e. monthly). Higher frequency synoptic and targeted event data is becoming available from more intensive monitoring programs, yet there remains little consensus on whether relatively lower frequency data are sufficient to constrain process-based watershed water quality models. To investigate the effects of using water quality data from differing sampling regimes for calibration, we use an implementation of HYPE (HYdrological Predictions for the Environment), a process-based watershed water quality model, in Southern Ontario, Canada. HYPE was calibrated with two stream water quality datasets, one associated with the long-term Ontario Provincial (Stream) Water Quality Monitoring Network and characterized by routine approximately monthly sampling frequency, and one associated with the Multi-Watershed Nutrient Study and characterized by semi-regular synoptic sampling during baseflow and at increased frequency (∼4 to 8 h) during event flow. Performances varied widely between sites, with validation ranges of daily predictions having Nash-Sutcliffe Efficiencies (NSE) from > −1 to 0.48 for flow and > −1 to 0.98 for total Phosphorus. Medians for daily data during validation ranged from 0.15 to 0.24 for flow and from 0.19 to 0.36 for total phosphorus. We found that model performance and simulated total phosphorus loads were similar for the two calibration datasets, potentially suggesting that the dataset with approximately monthly water quality sampling was adequate to constrain the HYPE model. We attribute this to a combination of similar levels of statistical variability in the calibration datasets and prior knowledge in the HYPE model structure. Furthermore, while model performance was similar when HYPE was calibrated with datasets of differing sampling strategies, there was a large range in model performance within each modelling domain. Results suggest that this range in performance could be due in part to poor representation of cold-weather processes in the HYPE model, as sites with higher mean annual temperature and fewer freezing days had better model performance.

Using Heavy Metals Pollution Index (HPI) and Metal Index (MI) for Assessing quality of drinking water in Bardarash-Akre basin in Duhok governorate northern Iraq

A total of forty-four groundwater samples were collected from several groundwater wells located at diverse depths and locations throughout the Kre-Bardarash basin in the Duhok governorate. The sample program began in May 2023 and includes the examination of several heavy elements, including but not limited to (As, Cd, Cu, Pb, Va, Ni, Zn, Bo, Cr, Co, Li, Mn, Se, and Ag)The essential goals of this research are to find that the samples have concentrations within the acceptable limits as prescribed in Iraqi drinking water standards. The average Heavy metal Pollution Index (HPI) concentration is 955, which is considerably less than the crucial index value of 100. The percentage of groundwater samples that exceeds the 100-index value is 5%, indicating that the water is completely unsuitable unfit for drinking, while 90 percent are rang from excellent to very poor quality according to HPI. The MI concentration was 0.16 with 88.6 % percent of groundwater samples were found to be very pure water class. The results show that the groundwater in the Akre-Bardarash basin of wells 1,2, and 3 is highly polluted in the northeast part, and wells 22 and 30 are also highly polluted in the south-east part. All of the wells mentioned above are unfit for human consumption. The impact of human activity and industrial activity on the study area has played an important role in the pollution of groundwater quality in the northeast and southwestern parts of the Akre-Bardarash Basin. According to the findings of the current study, it can be concluded that the water can be used safely for drinking without any negative effect on human health, except wells 1,2, and 3 in the northeast part and wells 22 and 30 in the southwest part.

Geoscience Visual Presentation G02: Source rocks of the Birrindudu Basin: perspectives from a new sampling program

Geoscience Visual Presentation G02: Source rocks of the Birrindudu Basin: perspectives from a new sampling program

Estuarine residency and habitat preferences of Atlantic Tripletail in the northwestern Gulf of Mexico

AbstractObjectiveThe Atlantic Tripletail Lobotes surinamensis is a globally distributed subtropical and tropical fish species that inhabits estuaries throughout the northern Gulf of Mexico (GOM), particularly during warm months. Little is known about distribution and residency patterns within estuaries, as the species is rarely caught in the recreational fishery, and virtually no commercial fishery exists for the species in the GOM.MethodsWe used data from a long‐term fishery‐independent gill‐net survey to model estuarine distribution throughout Texas and to relate environmental variables to the Atlantic Tripletail catch.ResultAlthough there were no observable temporal trends in catch over the time series (1990–2022), the most recent 6 years included record catch in six of the 10 major Texas estuaries, possibly indicating a recent pulse in abundance. Catch throughout the time series was spatially aggregated in a small number of “hot spots” observed coastwide. Latitude was the best predictor of catch, although wind fetch and wind aspect (wind direction in relation to shoreline direction) were important predictors, and catch was highest near GOM inlets. The Texas Parks and Wildlife Department gill‐net sampling program caught a range of Atlantic Tripletail between 171 and 880 mm total length, indicating a potential gear bias against juveniles.ConclusionDespite this gear bias, these data shed light on the factors that drive Atlantic Tripletail estuarine distribution and abundance in the northwestern GOM. Wind‐driven passive movements in the estuary, combined with active selection of polyhaline habitats near GOM inlets, might be primary drivers of Atlantic Tripletail catch, thus supporting findings from previous studies.