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USGS2025

Identifying conditions associated with outliers produced by three different chlorophyll fluorometers: A comparison of instrumentation and development of correction formulae

Measurements of chlorophyll concentration reported by fluorometers (fChl) are used in environmental research and monitoring, as inputs to models, and in the interpretation of remote sensing data. Researchers and managers benefit from understanding how to interpret and ensure the accuracy of fChl data collected by in situ fluorometers. Although fChl values produced by different manufacturers are often in agreement with discrete laboratory-derived Chlorophyll a (Chl a ) concentration measurements, there are instances in which results significantly differ. Further, when measuring fChl side by side, different fluorometers may report values that differ significantly from each other, despite passing calibration checks prior to deployment. We compared environmental conditions and phytoplankton species composition associated with instances in which fChl measurements from three different fluorometers (EXO2 Total Algae Smart Sensor, YSI Inc./Xylem Inc., Yellow Springs, Ohio; FluoroProbe III, bbe Moldaenke GmbH, Kiel, Germany; WETStar, Sea-Bird Scientific, Bellevue, Washington) were significantly different from laboratory-derived Chl a concentrations. Results indicated that elevated primary productivity, as indicated by high pH, dissolved oxygen, and the ratio of Chl a to phaeophytin, were correlated with underestimated fChl values recorded by each sensor. After removing outliers, we determined unique correction guidance for each of the three sensors and demonstrated that after applying correction formulae, fChl measurements produced by each sensor became directly comparable.

California↗

USGS2020

Trends in oyster populations in the northeastern Gulf of Mexico: An assessment of river discharge and fishing effects over time and space

Within the Big Bend region of the northeastern Gulf of Mexico, one of the least developed coastlines in the continental USA, intertidal and subtidal populations of eastern oyster Crassostrea virginica (hereafter referred to as “oyster”) are a critical ecosystem and important economic constituent. We assessed trends in intertidal oyster populations, river discharge, and commercial fishing activity in the Suwannee River estuary within the Big Bend region using fisheries‐independent data from irregular monitoring efforts and publicly available environmental data. We used generalized linear models to evaluate counts of oysters from line‐transect surveys over time and space. We assessed model performance using simulation to understand potential bias and then evaluated whether these counts were related to freshwater inputs from the Suwannee River and commercial oyster fishing effort and landings at different time lags. We found that intertidal oyster counts have declined over time and that most of these declines are found in inshore intertidal oyster bars, which are becoming degraded. We also found a significant relationship between oyster counts and a 1‐year lag on mean daily Suwannee River discharge, but including commercial fishery trips or landings did not improve model fit. It is unclear whether declines in intertidal oyster bars are offset by formation of new oyster reefs elsewhere. These results quantify rapid declines in intertidal oyster reefs in a region of coastline with high conservation value that can be used to inform ongoing and proposed restoration projects in the region.

Florida↗

USGS2019

Predicting persistence of Rio Grande Cutthroat Trout populations in an uncertain future

The Rio Grande Cutthroat Trout Oncorhynchus clarkii virginalis (RGCT ) occupies just 12% of its ancestral range. As the southernmost subspecies of Cutthroat Trout, we expect a warming climate to bring additional stressors to RGCT populations, such as increased stream temperatures, reduced streamflows, and increased incidence of wildfire. We developed a Bayesian network (BN ) model using site‐specific data, empirical research, and expert knowledge to estimate the probability of persistence for each of the 121 remaining RGCT conservation populations and to rank the severity of the threats they face. These inputs quantified the genetic risks (e.g., inbreeding risk and hybridization risk), population demographics (disease risk, habitat suitability, and survival), and probability of stochastic disturbances (stream drying risk and wildfire risk) in an uncertain future. We also created stream temperature and base flow discharge models coupled with regionally downscaled climate projections to predict future abiotic conditions at short‐term (2040s) and long‐term (2080s) time horizons. In the absence of active management, we predicted a decrease in the average probability of population persistence from 0.53 (current) to 0.31 (2040s) and 0.26 (2080s). Only 11% of these populations were predicted to have a greater than 75% chance of persisting to the 2080s. Threat of invasion by nonnative trout had the strongest effect on population persistence. Of the 78 populations that are already invaded or lacking complete barriers, 60% were estimated to be extirpated by 2080 and the remainder averaged only a 10% chance of persistence. In contrast, the effects of increased stream temperatures were predicted to affect the future persistence of only 9% of the 121 RGCT populations remaining, as most have been restricted to high‐elevation habitats that are cold enough to buffer against some stream warming. Our BN model provides a framework for evaluating threats and will be useful to guide management actions that are likely to provide the most benefit for long‐term conservation.

New Mexico, Colorado↗

USGS2022

Alaskan Yelloweye Rockfish fecundity revealed through an automated egg count and digital imagery method

Spawning stock biomass (SSB) is often used as an index for reproductive potential (RP) in fisheries stock assessments. This method assumes that mature female biomass is proportional to total egg production and implies that (1) the fecundity–length relationship follows a cubic function or (2) relative fecundity is constant. For many marine fishes, adequate fecundity estimates to evaluate these relationships are lacking. This study estimated fecundity and fecundity relationships for Yelloweye Rockfish Sebastes ruberrimus and evaluated an automated method of counting eggs and larvae. We collected Yelloweye Rockfish ovaries ( N = 90) from the northern Gulf of Alaska, including Prince William Sound, Alaska, during 2018–2019 and used the gravimetric method and image analysis software to count eggs from digital camera images. To evaluate the speed, accuracy, and precision of the automated counting procedure, one-third of the gravimetric samples were also manually counted. Image analysis software was approximately four times faster but equally accurate and precise for fecundity estimates relative to manual counts. Fecundity ranged from 53,249 to 3.052 × 10 6 eggs (mean ± SD = 896,762 ± 699,504 eggs), and relative fecundity increased with female FL and ranged from 68 to 435 eggs/g of body weight (mean ± SD = 226 ± 87 eggs/g). The use of SSB for Yelloweye Rockfish stock assessment could underestimate the contribution to egg production by larger (>5.6-kg) females, overestimate the contribution by smaller females, and lead to biased biological reference points. This study provides critical information to more realistically model RP and improve stock assessment inputs for the development of harvest control rules for Yelloweye Rockfish. Additionally, the use of image analysis software to count eggs in digital images proved to be an effective fecundity estimation method that could be applied to other highly fecund fish species for which the time demand of manual counting methods would be prohibitive.

Alaska↗

USGS2022

Nutrient restoration of a large, impounded, ultra-oligotrophic western river to recover declining native fishes

Declines in many fish populations in large, western rivers have been primarily attributed to the anthropogenic reduction of nutrient inputs and subsequent impacts to the food web. The largest known river fertilization program was implemented starting in 2005 on the Kootenai River in northern Idaho to restore resident fisheries. Annual electrofishing surveys were conducted at multiple sites in Idaho and Montana before and during nutrient addition to evaluate assemblage and population-level responses. Although few responses in fish assemblage structure were observed, the addition of liquid ammonium polyphosphate fertilizer (3 μg/L) to the Kootenai River increased fish abundance and biomass over the 20-km stretch of river downstream of the treatment site. Increases were most notable in Largescale Suckers Catostomus macrocheilus, Mountain Whitefish Prosopium williamsoni , and Rainbow Trout Oncorhynchus mykiss populations, although increases in catch and biomass were detected for nearly all fish species . The Kootenai River is approximately 30 times larger in discharge than other rivers that have been experimentally fertilized and provides compelling evidence that the mitigation of nutrient declines in rivers of similar size can result in positive influences on the fish populations where primary and secondary production are limiting growth, survival, and recruitment. However, results from our study also highlight the importance of completing evaluations across varying levels of biological organization (e.g., assemblage and population) and over biologically relevant timeframes.

Idaho, Montana↗

USGS2022

Engaging stakeholders to develop a decision support model of conservation risk and management capacity to prioritize investments in Bull Trout recovery

Rarely are sufficient resources available to support the full suite of management actions to promote recovery of a species across their entire distribution. Decision support models are a tool that can inform natural resource management decisions with consideration of the perspectives from a variety of stakeholders who work across large geographic and jurisdictional extents. We offer an example of a decision support model that was developed by several Federal and State natural resource agencies to rank Bull Trout Salvelinus confluentus core areas for prioritizing conservation investment within Oregon, USA. We engaged State level decision makers to identify parameters believed to be influential in determining funding allocations for Bull Trout core areas. Parameters were linked in a model framework that was further refined with input from local Bull Trout experts with knowledge specific to the various core areas. The model produces a relative priority value that is a combination of the conservation risk to the species and the management capacity to address threats. A series of sensitivity analyses suggests that Bull Trout persistence and threat score are most influential in determining the relative priority of a core area, and life-history and genetic diversity are least influential. One of the more powerful products from this work is an interactive web-based application ( https://das.ecosphere.fws.gov/public/obts/ ) that anyone can use to explore how their beliefs in parameter values will affect the relative priority of Bull Trout core areas across Oregon. Our modeling effort is an example of engaging stakeholders with different roles in species recovery and across a large geographic area to create a clearer path forward in allocating limited resources for species recovery. This approach can be employed to address a number of natural resource management situations across species and habitats.

Oregon↗

USGS2013

Extending airborne electromagnetic surveys for regional active layer and permafrost mapping with remote sensing and ancillary data, Yukon Flats ecoregion, central Alaska

Machine-learning regression tree models were used to extrapolate airborne electromagnetic resistivity data collected along flight lines in the Yukon Flats Ecoregion, central Alaska, for regional mapping of permafrost. This method of extrapolation (r = 0.86) used subsurface resistivity, Landsat Thematic Mapper (TM) at-sensor reflectance, thermal, TM-derived spectral indices, digital elevation models and other relevant spatial data to estimate near-surface (0–2.6-m depth) resistivity at 30-m resolution. A piecewise regression model (r = 0.82) and a presence/absence decision tree classification (accuracy of 87%) were used to estimate active-layer thickness (ALT) (< 101 cm) and the probability of near-surface (up to 123-cm depth) permafrost occurrence from field data, modelled near-surface (0–2.6 m) resistivity, and other relevant remote sensing and map data. At site scale, the predicted ALTs were similar to those previously observed for different vegetation types. At the landscape scale, the predicted ALTs tended to be thinner on higher-elevation loess deposits than on low-lying alluvial and sand sheet deposits of the Yukon Flats. The ALT and permafrost maps provide a baseline for future permafrost monitoring, serve as inputs for modelling hydrological and carbon cycles at local to regional scales, and offer insight into the ALT response to fire and thaw processes.

Alaska↗

USGS2018

Validation of the CHIRPS satellite rainfall estimates over eastern Africa

Long and temporally consistent rainfall time series are essential in climate analyses and applications. Rainfall data from station observations are inadequate over many parts of the world due to sparse or non-existent observation networks, or limited reporting of gauge observations. As a result, satellite rainfall estimates have been used as an alternative or as a supplement to station observations. However, many satellite-based rainfall products with long time series suffer from coarse spatial and temporal resolutions and inhomogeneities caused by variations in satellite inputs. There are some satellite rainfall products with reasonably consistent time series, but they are often limited to specific geographic areas. The Climate Hazards Group Infrared Precipitation (CHIRP) and CHIRP combined with station observations (CHIRPS) are recently produced satellite-based rainfall products with relatively high spatial and temporal resolutions and quasi-global coverage. In this study, CHIRP and CHIRPS were evaluated over East Africa at daily, dekadal (10-day) and monthly time-scales. The evaluation was done by comparing the satellite products with rain-gauge data from about 1,200 stations. The CHIRP and CHIRPS products were also compared with two similar operational satellite rainfall products: the African Rainfall Climatology version 2 (ARC2) and the Tropical Applications of Meteorology using Satellite data (TAMSAT). The results show that both CHIRP and CHIRPS products are significantly better than ARC2 with higher skill and low or no bias. These products were also found to be slightly better than the latest version of the TAMSAT product at dekadal and monthly time-scales, while TAMSAT performed better at the daily time-scale. The performance of the different satellite products exhibits high spatial variability with weak performances over coastal and mountainous regions.

Africa↗

USGS2011

Effects of grade control structures on fish passage, biological assemblages, and hydraulic environments in western Iowa streams: a multidisciplinary review

Land use changes and channelization of streams in the deep loess region of western Iowa have led to stream channel incision, altered flow regimes, increased sediment inputs, decreased habitat diversity and reduced lateral connectivity of streams and floodplains. Grade control structures (GCSs) are built in streams to prevent further erosion, protect infrastructure and reduce sediment loads. However, GCS can have a detrimental impact on fisheries and biological communities. We review three complementary biological and hydraulic studies on the effects of GCS in these streams. GCS with steep (≥1:4 rise : run) downstream slopes severely limited fish passage, but GCS with gentle slopes (≤1:15) allowed greater passage. Fish assemblages were dominated by species tolerant of degradation, and Index of Biotic Integrity (IBI) scores were indicative of fair or poor biotic integrity. More than 50% of fish species had truncated distributions. After modification of GCS to reduce slopes and permit increased passage, IBI scores increased and several species were detected further upstream than before modification. Total macroinvertebrate density, biomass and taxonomic diversity and abundance of ecologically sensitive taxa were greater at GCS than in reaches immediately upstream, downstream or ≥1 km from GCS. A hydraulic study confirmed results from fish passage studies; minimum depths and maximum current velocities at GCS with gentle slopes (≤1:15) were more likely to meet minimum criteria for catfish passage than GCS with steeper slopes. Multidisciplinary approaches such as ours will increase understanding of GCS-associated factors influencing fish passage, biological assemblage structure and other ecological relationships in streams.

Iowa↗

USGS2014

The influence of logjams on largemouth bass ( Micropterus salmoides ) concentrations on the lower Roanoke River, a large sand-bed river

This study examines the relation between logjams and largemouth bass (Micropterus salmoides) on the alluvial sand-bed lower Roanoke River. Disparate data sets from previous bank erosion, fisheries, and large wood studies were used to compare the distribution of largemouth bass with logjam frequency. Logjams are related to the frequency of bank mass wasting increasing from near an upstream dam to the middle reach of the study segment and then decreasing as the river approaches sea level. The highest concentration of largemouth bass and logjams was in the middle reach (110 fish per hour and 21 jams per km). Another measure of largemouth bass distribution, fish biomass density (g h1 ), had a similar trend with logjams and was a better predictor of fish distribution versus logjams (R2= 0.6 and 0.8 and p = 0.08 and 0.02 for fish per hour and g h1 versus logjam, respectively). We theorize that the preference for adult bass to congregate near logjams indicates the use of the jams as feeding areas. The results of a principal component analysis indicate that fish biomass concentration is much more related to logjam frequency than channel geometry (width, depth, and bank height), bed grain size, bank erosion, or turbidity. The results of this research support recent studies on in-channel wood and fisheries: Logjams appear to be important for maintaining, or increasing, both largemouth bass numbers and total biomass of fish in large eastern North American rivers. Persistent logjams, important as habitat, exist where relatively undisturbed river reaches allow for bank erosion inputs of wood and available anchoring locations. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

North Carolina↗

USGS2021

The optical river bathymetry toolkit

Spatially distributed information on water depth is essential for many applications in river research and management and, under certain circumstances, can be inferred from remotely sensed data. Although fluvial remote sensing has emerged as a rapidly developing subdiscipline of the riverine sciences, more widespread adoption of these techniques has been hindered by a lack of accessible software. The Optical River Bathymetry Toolkit (ORByT) fills this void by providing a standalone package for mapping water depth from passive optical image data. The ORByT interface enables end users to import images and field‐based depth measurements, create and refine water masks, and perform spectrally based depth retrieval via an Optimal Band Ratio Analysis algorithm. The resulting bathymetric map can be exported as an image file, point cloud, and/or cross section; a thorough accuracy assessment also is incorporated into the workflow. In addition, image‐derived depth estimates can be subtracted from water surface elevations to obtain bed elevations suitable for input to a hydrodynamic model. Potential users of ORByT must bear in mind the inherent limitations of passive optical remote sensing: reliable bathymetry can only be inferred in clear‐flowing, shallow streams; this approach is not appropriate for more turbid, deeper rivers.

River Research and Applications↗

USGS2021

Assessment of a conservative mixing model for the evaluation of constituent behavior below river confluences, Elqui River Basin, Chile

Fate and transport modeling of water-borne contaminants is a data demanding and costly endeavor, requiring considerable expes such, it becomes important to know when a complex modeling approach is required, and when a simpler approach is adequate. This is the main objective herein, where a conservative mixing model is used to characterize the transport of As, Cu, Fe, and SO 4 . The study area is divided into three sectors, corresponding to the upstream, middle, and downstream portions of the Elqui River Basin, Chile. In Sector 1, acidic conditions result in the conservative transport of constituents that are sourced from acid rock drainage. In Sector 2, pH increases and transport is influenced by pH-dependent reactions and the subsequent settling of the particulate phase. In Sector 3, there are no additional constituent inputs, and the constituents are conservatively transported downstream. Conservative transport within Sector 3 is confirmed through the development of a regression model that provides monthly estimates of SO 4 load. Whereas SO 4 and Cu concentrations are adequately approximated by the conservative mixing model, estimates of As and Fe concentrations exhibit larger errors, due to the more reactive behavior of these constituents. The fact that the simple, conservative mixing model describes SO 4 transport is a valuable result, as this constituent is known to be one of the primary indicators of mining-related contamination in rivers. The approach could also be a useful starting point for further evaluations of the effects of climate change and hydrological variability on the water quality of rivers.

Elqui River Basin↗

USGS2026

Non-physical barrier design and environmental conditions alter routing and survival of juvenile Chinook salmon (Oncorhynchus tshawytscha) in the Sacramento-San Joaquin River Delta

Pacific salmon face substantial challenges when migrating through anthropogenically modified river systems, such as the Sacramento-San Joaquin River Delta (the Delta). Non-physical behavioral barriers, such as the bioacoustic fish fence (BAFF), are one potential solution for guiding fish away from hazards without obstructing water flow. However, the effectiveness of these technologies depends on abiotic and biotic conditions. In the Delta, a BAFF was deployed at Georgiana Slough in 2011, 2012, and 2024 to deter juvenile Chinook salmon ( Oncorhynchus tshawytscha ) from migrating into the interior Delta, a region associated with lower survival than the mainstem Sacramento River. We leveraged nine years of acoustic telemetry data to evaluate BAFF performance across flow conditions and two BAFF designs (2011/2012 vs. 2024), and to assess the BAFF's contribution to improving through-Delta survival. The BAFF reduced routing into Georgiana Slough from 26.5% without a barrier to 8.9% in 2011/2012 and 15.9% in 2024. In general, routing into Georgiana Slough increased with the proportion of flow entering the channel during periods without a BAFF and during the 2024 deployment but remained constant during the 2011/2012 deployment. Additionally, BAFF effectiveness declined with increasing input flow. Ultimately, reduced routing into Georgiana Slough during the 2024 BAFF deployment resulted in an increase in estimated through-Delta survival between 0.2 and 1.6 percentage points depending on release group. Our results provide valuable insights into the role of non-physical barriers in complex river systems and inform future management strategies for protecting migrating juvenile Chinook salmon in the Sacramento-San Joaquin River Delta.

California↗

USGS2021

The processes of preferential flow in the unsaturated zone

Preferential flow, a major influence in unsaturated soil and rock almost everywhere, occurs by multiple phenomenologically distinct hydraulic processes. For the mode known as funneled flow, concentrated in particularly conductive portions of the medium, the surface-tension/viscous-flow processes of traditional unsaturated flow theory predominate. Fingered flow, through conductive paths of higher water content than surrounding material, requires amendments to traditional theory concerning instabilities and dynamic flow-regime boundaries. Macropore flow, the most recognized preferential flow mode, poses unanswered questions and major difficulties in practice. Accumulated evidence shows that water flows preferentially mostly through macropores that are (a) only partially filled with water, and (b) surrounded by matrix material that is drier, sometimes much drier, than saturation. With partial filling, geometric characteristics such as aperture have much less influence than was previously thought, and the intra-macropore configuration of the flowing water phase, about which little is conclusively known, is then a dominant controlling influence. With unsaturated surroundings, macropore/matrix exchange interactions control, for given input and medium, the initiating circumstances, conveyed flux, and duration of macropore flow. The multiple processes in play during such interactions have different sensitivities to the matrix water state and different directions of influence. The net influence of matrix water content on macropore flow is thus highly complex and a major research need. Additional high-priority topics are: flowpath connectivity, for watersheds as well as small scales; intra-macropore processes, to discern their importance and possible means of quantification; and the identification of measurable soil and rock properties that can be utilized predictively.

Soil Science Society of America Journal↗

USGS2024

Opportunities and challenges for precipitation forcing data in post-wildfire hydrologic modeling applications

The frequency and extent of wildfires have increased in recent decades with immediate and cascading effects on water availability in many regions of the world. Precipitation is used as primary input to hydrologic models and is a critical driver of post-wildfire hydrologic hazards including debris flows, flash floods, water-quality effects, and reservoir sedimentation. These models are valuable tools for understanding the hydrologic response to wildfire but require accurate precipitation data at suitable spatial and temporal resolutions. Wildfires often occur in data-sparse, headwater catchments in complex terrain, and post-wildfire hydrologic effects are particularly sensitive to high-intensity, short-duration precipitation events, which are highly variable and difficult to measure or estimate. Therefore, the assessment and prediction of wildfire-induced changes to watershed hydrology, including the associated effects on ecosystems and communities, are complicated by uncertainty in precipitation data. When direct measurements of precipitation are not available, datasets of indirect measurements or estimates are often used. Choosing the most appropriate precipitation dataset can be difficult as different datasets have unique trade-offs in terms of spatial and temporal accuracy, resolution, and completeness. Here, we outline the challenges and opportunities associated with different precipitation datasets as they apply to post-wildfire hydrologic models and modeling objectives. We highlight the need for expanded precipitation gage deployment in wildfire-prone areas and discuss potential opportunities for future research and the integration of precipitation data from disparate sources into a common hydrologic modeling framework.

WIREs Water↗

USGS2025

Disparate groundwater responses to wildfire

Post-wildfire investigations of groundwater response reveal a range of outcomes, varying from substantial increases to notable decreases in recharge and baseflow, with some studies indicating negligible or short-lived effects. This review assesses these varied responses within five critical categories: climate, vegetation, hydrogeology, fire characteristics, and the cryosphere, examining both short-term (within 2 years) and intermediate (2–10 years post-fire) effects. Despite considerable variability, some consistent patterns emerge. For instance, in hydroclimatic settings where water input and evaporative demand cycles are out of sync, post-wildfire groundwater responses tend to be positive (i.e., increased flux or storage), whereas under low fire severity conditions or in vegetation types that quickly recover, groundwater responses tend to be negative (i.e., decreased flux or storage). We synthesize relevant findings into a compendium of testable hypotheses aimed at explaining the spatiotemporal variability in observed post-wildfire groundwater responses. A recurring theme is the critical influence of the pre-wildfire groundwater regime on expected response and recovery. We identify opportunities for specific improvements in post-wildfire monitoring and modeling that would further advance capabilities to predict groundwater response. A key area for further research is understanding how wildfire effects on snow dynamics and other cryospheric processes translate to changes in groundwater.

WIREs Water↗

USGS2025

Spatial and temporal variability of perfluoroalkyl and polyfluoroalkyl substances in major rivers of New Mexico, USA

Perfluoroalkyl and polyfluoroalkyl substances (PFAS) are ubiquitous in the environment, but sources that contribute to temporal and spatial variability in surface waters are not well defined. Many states are assessing PFAS in water resources, and insight from these statewide assessments can help guide future sampling efforts. A statewide assessment of 28 PFAS was conducted in New Mexico starting in 2020, and subsequent follow-up sampling has improved understanding of PFAS occurrence and sources throughout the state. PFAS were present in all major rivers of New Mexico (Rio Grande, Pecos River, San Juan River, Animas River, Canadian River, Gila River, Rio Chama, and Rio Puerco) with 13 of 28 analyzed PFAS (PFBA, PFPeA, PFHxA, PFHpA, PFOA, PFNA, PFDA, PFBs, PFPeS, PFHxS, PFOS, PFOSA, 6:2 FTS) detected from at least one sample for samples collected between 2020 and 2024. This study found high temporal and spatial variability—PFAS concentrations ranged from below the laboratory detection level to 156 ng/L, with concentrations generally increasing downstream on the major rivers. PFBS was the most frequently detected and highest concentration PFAS in this study, ranging from 1 to 93 ng/L, followed by PFBA and PFPeA, ranging from 0.9 to 32 ng/L. The average of the sum of PFAS detected increased by an order of magnitude from 4 to 46 ng/L in the Rio Grande as it flows through Albuquerque, the largest urban area in New Mexico. PFAS concentration increased by 58% after a stormflow pulse flushed over Albuquerque and contributed water to the Rio Grande. The contribution of wastewater to surface water resources varied diurnally as well as seasonally. Sampling multiple locations on major rivers across multiple seasons, taking into account known anthropogenic inputs, would enhance characterization of temporal and spatial variability of PFAS concentrations. Increased sampling frequency at sites with wastewater contribution and focused investigations in areas with higher than expected PFAS could increase understanding of potential sources and variability of source contributions.

New Mexico↗

USGS2013

Bridging groundwater models and decision support with a Bayesian network

Resource managers need to make decisions to plan for future environmental conditions, particularly sea level rise, in the face of substantial uncertainty. Many interacting processes factor in to the decisions they face. Advances in process models and the quantification of uncertainty have made models a valuable tool for this purpose. Long-simulation runtimes and, often, numerical instability make linking process models impractical in many cases. A method for emulating the important connections between model input and forecasts, while propagating uncertainty, has the potential to provide a bridge between complicated numerical process models and the efficiency and stability needed for decision making. We explore this using a Bayesian network (BN) to emulate a groundwater flow model. We expand on previous approaches to validating a BN by calculating forecasting skill using cross validation of a groundwater model of Assateague Island in Virginia and Maryland, USA. This BN emulation was shown to capture the important groundwater-flow characteristics and uncertainty of the groundwater system because of its connection to island morphology and sea level. Forecast power metrics associated with the validation of multiple alternative BN designs guided the selection of an optimal level of BN complexity. Assateague island is an ideal test case for exploring a forecasting tool based on current conditions because the unique hydrogeomorphological variability of the island includes a range of settings indicative of past, current, and future conditions. The resulting BN is a valuable tool for exploring the response of groundwater conditions to sea level rise in decision support.

Water Resources Research↗