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USGS2026

Where will the cat cross the road? Comparing camera and GPS-based models for identifying wildlife corridors

Designing effective wildlife corridors is a critical conservation challenge in fragmented landscapes. GPS-based step selection functions strongly predict dispersal corridors and connectivity, but GPS collaring can be expensive and invasive. Camera-based occupancy models are widely used for connectivity analyses but may involve trade-offs in data resolution. Despite widespread use of both approaches, few studies have directly compared them using concurrent datasets. We developed a stacked single-species, single-season occupancy model and a Circuitscape connectivity surface for mountain lions (Puma concolor) on Washington’s Olympic Peninsula, USA, and compared them with a connectivity surface from an existing integrated step selection function. Both models predicted mountain lion GPS locations well, with binned Spearman rank correlations of 1 for Circuitscape and 0.96 for the step selection function, though step selection better identified habitat use by dispersers. Connectivity predictions were moderately correlated across the landscape ( r = 0.26), but agreement was strongest in human-dominated areas most critical for corridor planning. We conclude that GPS-based approaches are advantageous when data collection is feasible and the focus is on dispersal or fine-scale movement. However, camera-based approaches may be preferable for multi-species monitoring, large spatial and temporal scales, noninvasive sampling, when resources are limited, or when fine-scale or dispersal-specific inference is not required.

Washington↗

USGS1998

Satellite imagery of the north-central Gulf of Mexico, June 1993-May 1997

This CD contains imagery collected by the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA polar-orbiting weather satellites. The AVHRR provides almost daily coverage of a site at a resolution of approximately 1 km. The data types included are sea surface temperature (SST), water reflectance (REF), and a false-color infrared overview (FCI).

Alabama, Florida, Louisiana, Mississippi↗

USGS2023

Preliminary geologic map of the Southern Santa Rosa Mountains and Borrego Badlands, San Diego County, Southern California

This investigation delineates the geologic framework of an area of 75 square kilometers (km 2 ) located west of the Salton Sea in southern California (fig. 1, on sheet 1). The study area encompasses the south flank of the Santa Rosa Mountains and the eastern part of the Borrego Badlands (sheet 1). In this study area, regionally important stratigraphic and structural elements collectively inform the late Cenozoic geologic evolution of the Anza-Borrego sector of the Salton Trough province. Critical stratigraphic and structural elements in the map area include the following: The well exposed sequence of late Cenozoic, nonmarine sedimentary rocks that filled the Anza-Borrego subbasin (fig. 1) of the Salton Trough; A tectonic boundary that—in the southern Santa Rosa Mountains—separates the sedimentary strata from underlying crystalline rocks of Peninsular Ranges type. This tectonic boundary, named the West Salton Detachment Fault System by Axen and Fletcher (1998), is projected to underlie all late Cenozoic sedimentary strata in the Anza-Borrego subbasin of the Salton Trough; A variety of transpressional, transtensional, and strike-slip structures that have deformed the late Cenozoic sedimentary strata and collectively guided syntectonic and posttectonic depositional events within the Anza-Borrego subbasin of the Salton Trough; and The southeasternmost surface expression of the Clark Fault, a major strand of the dextral San Jacinto Fault Zone. Geologic mapping and analysis for this investigation focused on clarifying geologic relations among these four stratigraphic and structural aspects in the map area.

California↗

USGS2026

Deep groundwater total dissolved solids mapping in the Dakota Group, Williston Basin, USA

Growing concern about the quantity of available freshwater around the world has led to interest in surveying groundwater total dissolved solids (TDS) below water well depths. Deep TDS has not been systematically mapped, and there is much to learn about the distribution and controls on deeper groundwater. In sedimentary basins across the United States, groundwater resources often overlie hydrocarbon resources, providing an opportunity to use borehole geophysical data collected for hydrocarbons to characterize groundwater and pore space resources. This study adapts a recently developed subsurface geostatistical and geophysical modeling approach to continuously map groundwater TDS, porosity, and temperature in the Dakota Group of the Williston Basin—an undercharacterized regional aquifer system overlying deeper hydrocarbon reservoirs. Groundwater TDS in the Dakota Group ranges from approximately 4800 to 26,900 mg/L. TDS patterns are stratified with higher TDS in the lower and upper Dakota Group, and relatively lower TDS in the middle Dakota Group. The lower TDS in the middle zone may represent a preferential regional flow path for lower-TDS meteoric recharge from the west. The alternating pattern of TDS may also be evidence of higher-TDS inflows into the Dakota Group from underlying and potentially from overlying aquifers. Porosity is lower near the center of the Williston Basin and tends to be higher to the east, which may be related to grain size distributions. The new regional TDS and porosity modeling serves as a quantitative reference for water users and provides supporting evidence for hypotheses on Dakota Group recharge.

Montana, North Dakota, South Dakota↗

USGS2025

Timescales of surface faulting preservation in low-strain intraplate regions from landscape evolution modeling and the geomorphic and historical record

Large surface-rupturing intraplate earthquakes in stable continental regions (SCRs) are uncommon globally and have recurrence intervals of thousands to hundreds of thousands of years based on the paleoseismic and geomorphic record, challenging accurate active fault identification in these regions. To constrain the timescales of preservation for scarps created by surface ruptures from dip-slip earthquakes, we use a two-dimensional scarp diffusion model for typical intraplate settings and explore which parameters influence fault scarp preservation. These parameters include the coseismic vertical surface offset, the recurrence interval of similar magnitude earthquakes, diffusivity (as a proxy for mean annual precipitation rate), and the erodibility of the surficial material. We constrain parameter ranges from a compilation of historical surface ruptures in intraplate settings in a variety of climates, including the Central and Eastern United States, Australia, Europe, Central Asia (Mongolia, China), India, and West Africa. The timescales of scarp preservation from landscape evolution modeling agree well with observations of scarp preservation in low-strain SCR and intraplate tectonic settings, with some notable exceptions for Australian scarps. We find that the erodibility of the surficial material and earthquake recurrence interval have a stronger effect on the timescales of scarp preservation than diffusivity or coseismic vertical surface offset. Our model results may aid in identifying and characterizing subtle, slow-moving active faults in low-strain SCR and intraplate tectonic settings for different tectonic, geomorphic, and climatic characteristics. Accurate fault locations and characterization from the landscape record has implications for both probabilistic seismic and fault displacement hazard analyses.

Journal of Geophysical Research Solid Earth↗

USGS2026

Fully contained laboratory earthquakes: The effect of asperity aspect ratio and free surfaces

Corner frequency ( f c ) and seismic moment ( M 0 ) are key parameters derived from seismic signals that are used to characterize earthquake stress drop, rupture area, and slip. These parameters are also affected by fault geometry and boundary conditions. However, the systematic study of these effects in laboratory settings has been challenging. This study presents laboratory earthquake experiments that examine how rupture dynamics are influenced by (a) the aspect ratio of rectangular PMMA velocity-weakening (VW) asperities surrounded by the Teflon velocity-strengthening (VS) patches, and (b) whether the sides of a VW asperity are confined with VS patches or are free surfaces. We found that increasing confinement by reducing free surfaces or increasing the VW asperity aspect ratio stabilizes fault slip, so that higher normal stress is required to transition from aseismic to seismic slip. Increased confinement and high aspect ratios also reduced M 0 and increased f c , both of which were determined from the radiated seismic waves. M 0 and f c were primarily controlled by the shorter dimension of the VW asperity. Analysis of high-frequency acoustic emission signals revealed that ruptures on high-aspect-ratio VW asperities propagated more unidirectionally, whereas ruptures on square VW asperities were more complex. Further, the high-aspect-ratio asperities were more likely to be eroded by surrounding VS regions while low-aspect-ratio asperities were more likely to rupture into the VS surroundings. These results demonstrate that both the confinement from surrounding stable areas and the geometry of the seismogenic patch can affect rupture nucleation, propagation, and seismic source characteristics.

JGR Solid Earth↗

USGS2025

Updating regional‐scale geospatial liquefaction models with locally available geotechnical data

We present a method to update the geospatial liquefaction model used by the U.S. Geological Survey’s near‐real‐time ground failure product with subsurface geotechnical data. The geospatial model estimates liquefaction probability from peak ground velocity (via ShakeMap) and geospatial susceptibility proxies. In many regions, additional information relevant to constraining liquefaction likelihood is also available, including surface geology maps and subsurface geotechnical measurements. There is currently no mechanism to use these data in the ground failure product liquefaction model, even though these data could provide more precise constraints on spatial variations in the lithologic character of the soil (surface geology) and direct measurements of the subsurface mechanical properties that affect liquefaction occurrence and severity (geotechnical measurements). In this study, we develop a method to integrate these data with the geospatial model and assess how these data can improve regional‐scale predictions. We develop a Bayesian updating framework and apply it to the 1989 magnitude 6.9 Loma Prieta, California, earthquake, for which mapped observations are available to evaluate performance. We constrain the Bayesian framework with 373 Northern California cone penetration tests and liquefaction susceptibility classes based on the mapped surface geology. This Bayesian model incorporates geotechnical information into the geospatial model and more accurately predicts liquefaction occurrences than the geospatial model, while sacrificing less accuracy in terms of predicting the absence of liquefaction than the geotechnical model. In future applications, this approach could be adapted to update other geospatial models using locally available subsurface data.

California↗

USGS2025

Fault displacement model for surface principal rupture of strike-slip faults

The probability distribution model for principal displacement accommodated on the surface main trace is a critical input to the fault displacement hazard analysis. This article presents a new model for strike-slip ruptures in the moment magnitude ( M ) range of 6 to 8.3. The new model is the outcome of a multi-year research effort to update the widely used model developed by Petersen and others in 2011. Updates include the adoption of the Fault Displacement Hazard Initiative database and enhancements to rupture and displacement data preparation. Statistical formulation and estimation have also been updated substantially. A three-parameter modified normal distribution that we refer to as the negative Exponentially Modified Gaussian distribution is adopted to model the probability distribution of the natural logarithm of principal displacement. Formulation for the mean parameter of the modified normal includes a random earthquake term, a nonlinear scaling relation with M , and an ellipse function for along-main-trace variation. The aleatory variability of the updated model now depends on M as well as site’s along-main-trace position. These updates not only significantly improve the fit to the distribution of the observed displacements but also yield reasonable 95th percentile predictions for M > 7.5 events. Alternative models representing the estimation uncertainty of the M -scaling relation are also developed. These new models are compared to the previous model in terms of percentile predictions and the calculated hazard curves. The steeper hazard curves from the new models yield a lower exceedance rate than the normal-distribution based model developed previously by Petersen and others.

Earthquake Spectra↗

USGS2026

Estimation of parental abundance using hierarchical Bayesian modeling with data augmentation

Pedigree-based estimation methods leverage the fact that each offspring in a cohort is genotypically “marked” by its parents and represent a recent and promising toolset for estimating population dynamics. This includes pedigree accumulation estimators that model the “accumulation” of inferred unique parents within a given cohort to estimate parental abundance. Unlike close-kin mark-recapture approaches, which rely on intercohort comparisons, pedigree accumulation modeling can be completed solely using intracohort samples. This is particularly advantageous for semelparous species, where intercohort pairs are impossible and adult life stages can be difficult to sample without affecting their likelihood of successfully reproducing. Previous work has evaluated a range of estimators for such datasets, concluding that the non-parametric Chao estimator provides the most accurate and precise estimates for feasible levels of sampling effort. We used simulated data to evaluate an alternative estimator based on hierarchical modeling and data augmentation in a Bayesian framework. Results indicate that estimates from the hierarchical Bayesian estimator had comparable accuracy and better precision than both the previously tested Chao1 estimator and the improved iChao formulation across a range of sample sizes and sex ratios. Furthermore, the Bayesian estimator was far more robust to simulated errors in pedigree reconstruction, especially the presence of false negatives. Hierarchical Bayesian pedigree accumulation models can also provide additional insight into underlying reproductive ecology through their use of an explicit observation process, allowing for the incorporation or estimation of species- and population-specific reproductive dynamics. More broadly, the parametric nature of these models offers opportunities to efficiently pool information among datasets as well as to propagate uncertainty within more complex models.

Ecology and Evolution↗

USGS2024

High resolution identification and quantification of diffuse deep groundwater discharge in mountain rivers using continuous boat-mounted helium measurements

Discharge of deeply sourced groundwater to streams is difficult to locate and quantify, particularly where both discrete and diffuse discharge points exist, but diffuse discharge is one of the primary controls on solute budgets in mountainous watersheds. The noble gas helium is a unique identifier of deep groundwater discharge because groundwater with long residence times is commonly enriched in helium. In this study, a portable mass spectrometer was used to measure longitudinal variation in dissolved helium concentrations in two mountainous rivers at high spatial resolution not feasible with traditional sampling techniques. Helium profiles were then simulated using a mass-balance model to quantify longitudinal variation in groundwater discharge to the receiving rivers. Results indicate helium concentrations were enriched by multiple orders of magnitude above atmospheric equilibrium in both rivers and that this persisted for up to 18 km below observed pulse inputs in the Colorado River. Helium mass-balance models match observed longitudinal patterns with the exception of sharp initial increases in helium observed in the rivers. Increased longitudinal groundwater discharge rates correspond to mapped geologic structures in both watersheds that likely transport deep geothermal water. Models show variable sensitivity to spatial assignment of input variables representing the groundwater source, illustrating the importance of collecting data from discrete groundwater discharges where possible. The methodology shows promise for field experiments designed to assess air–water exchange rates and to quantify total groundwater discharge from a combination of discrete and diffuse sources.

Colorado, Utah↗

USGS2025

Preserving and increasing water resources—Natural infrastructure in dryland streams in Baja California Sur, Mexico

The Los Planes watershed of Baja California Sur, Mexico, and its underlying aquifer are experiencing groundwater decline owing to low average annual rainfall (28.1 centimeters per year) and rising water demand from population growth and agricultural activities. This decline in water availability can lead to desertification—a process that changes arable land to desert by degrading soil and vegetation—and can pose serious challenges to livelihoods that depend on the land. To address these issues, a ranch in the Los Planes watershed has installed many natural infrastructures in dryland streams (NIDS) in channels for soil and water conservation. In 2022, the U.S. Geological Survey (USGS) began working with regional researchers and land managers to investigate the effects of NIDS on natural biological, geochemical, and physical processes and determine the efficacy of NIDS for water augmentation in the Los Planes watershed. The USGS also worked with local academic institutions and nonprofit organizations to create public educational opportunities focused on the area’s hydrogeology. These and other collaborative efforts with the U.S. Water Partnership and Innovaciones Alumbra aim at enhancing water resources in the Baja California Sur region and promoting water security and safeguarding community well-being. Resume La cuenca de Los Planes, ubicada en Baja California Sur, México, y su acuífero subyacente, están sufriendo una disminución de las aguas subterráneas debido a la baja precipitación media anual (28.1 centímetros por año) y la alta demanda de agua por parte de una población creciente y la actividad agrícola. Esta disminución de la disponibilidad de agua puede conducir a la desertificación—un proceso que por medio de la degradación del suelo y la vegetación convierte a la tierra cultivable en desierto—representando un serio desafío para los medios de vida de las personas. Para abordar estos problemas, un rancho en la cuenca de Los Planes ha instalado numerosas obras de Infraestructura Natural en Arroyos de Tierras Áridas (INATS) para conservación del suelo y del agua. En 2022, el Servicio Geológico de los Estados Unidos (USGS, por sus siglas en inglés) comenzó a trabajar con investigadores regionales y gestores de tierras para estudiar los efectos de INATS en los procesos biológicos, geoquímicos y físicos, y determinar su eficacia en el aumento de los recursos hídricos en la cuenca de Los Planes. El USGS se ha asociado con instituciones académicas y organizaciones locales sin fines de lucro para crear oportunidades educativas públicas centradas en la hidrogeología de la zona. Estos y otros esfuerzos colaborativos con la Asociación del Agua de Estados Unidos (U.S. Water Partnership) e Innovaciones Alumbra, tienen como objetivo mejorar el uso de los recursos hídricos en la región de Baja California Sur, promover la seguridad hídrica y proteger el bienestar de la comunidad.

Baja California Sur↗

USGS2025

Laboratory assessment for recovery of porcine circovirus 2 and porcine reproductive and respiratory syndrome virus using two types of commercially available hollow-fiber ultrafilters

Groundwater near swine farms is an uninvestigated reservoir for porcine reproductive and respiratory syndrome virus (PRRSV) and porcine circoviruses (PCVs). Enteric microorganisms are often collected from groundwater via dead-end ultrafiltration, but recovery of PRRSV and PCV with this method has not been assessed. We recovered PRRSV2 and PCV2 by dead-end ultrafiltration followed by polyethylene glycol (PEG) precipitation, nucleic acid extraction, and reverse-transcription quantitative real-time PCR. We also compared 2 commercial hemodialysis ultrafilters (Asahi Kasei Rexeed-25A, Nipro Elisio-25H) and compared PRRSV2 recovery in these filters to other waterborne microorganisms. On average, 8 ± 1% of PRRSV2 was recovered by dead-end ultrafiltration and PEG precipitation, compared to 25 ± 6% for adenovirus 41. Full-process recovery of bacteria in the same filters was 5–15%; Cryptosporidium parvum recovery was 42 ± 12%. PCV2 was detected in 4 of 12 replicate filters, but low stock concentrations precluded quantitative recovery estimates. Elisio-25H ultrafilters performed similarly to Rexeed-25A filters for all organisms tested and is an effective replacement for the Rexeed-25A, which is no longer available in the United States. Our recovery of PRRSV2 and PCV2 by dead-end ultrafiltration in the laboratory suggests that PRRSV2 detection limits are as low as 3–50 genomic copies/L in sample volumes of 100–1,500 L. Based on quantitative microbial risk assessment, these concentrations are relevant to PRRSV2 infection rates in the U.S. swine herd.

Journal of Veterinary Diagnostic Investigation↗

USGS2026

Status and understanding of groundwater quality in the San Joaquin Valley Kern County subbasin domestic-supply aquifer study unit, 2022—California GAMA Priority Basin Project

The quality of water accessed by domestic wells (here referred to as domestic groundwater resources) in the San Joaquin Valley Kern County subbasin (basin number 5-022.14) was assessed as part of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project (GAMA-PBP), in cooperation with the California State Water Resources Control Board. Kern County is at the southern end of the San Joaquin Valley in California, and about 30,000 residents are estimated to use privately owned domestic wells for drinking water. Domestic wells typically draw from shallower parts of the aquifer system than public-supply wells and can be more vulnerable to effects from surface activities. Kern County is host to a highly productive agricultural industry, with Bakersfield as the main urban center. The Kern River runs through Bakersfield from the southern Sierra Nevada and intersects the Kern Water Bank, one of the largest groundwater banking operations in California, at the Kern River Intertie. The section of the Kern River running through the Kern Water Bank is dry most years. Kern County also encompasses some of the most productive oil and gas basins in California, with extensive underground and surface disposal of oil-field wastewater. This study was based on data collected from 33 sites sampled by the U.S. Geological Survey for the GAMA-PBP in 2022. To provide context for the water quality assessment, measured concentrations were compared to regulatory and non-regulatory health-based and aesthetic benchmarks. A grid-based method was used to estimate the proportions of the groundwater resources used for domestic-supply wells that have water-quality constituents below (low relative concentration), approaching (moderate relative concentration), or above (high relative concentration) benchmark concentrations. At least one measured constituent with a regulatory benchmark was categorized as having a high relative concentration in 72 percent of the aquifer area used for domestic groundwater resources. Inorganic constituents were detected at high concentrations in 45 percent of the domestic groundwater resources, and the constituents detected above regulatory benchmarks were arsenic, nitrate, and uranium. At least one organic constituent was detected at high concentrations in 41 percent of the domestic groundwater resources, and the constituents exceeding regulatory benchmarks were the fumigants 1,2,3-trichloropropane (1,2,3-TCP), 1,2-dibromo-3-chloropropane (dibromochloropropane [DBCP]), 1,2-dibromoethane (EDB), and the per-and polyfluoroalkyl substance (PFAS) perfluorooctanesulfonate. The disinfection by-product chloroform, the fumigant 1,2-dichloropropane, the herbicides atrazine and hexazinone, and the herbicide degradates 2-chloro-6-ethylamino-4-amino-s-triazine, 2-chloro-4,6-diamino-s-triazine, 4-hydroxychlorothalonil, and metolachlor sulfonic acid were detected in more than 10 percent of domestic groundwater resources, but concentrations did not exceed regulatory benchmarks. Land use, groundwater age (fraction of modern water and mean age), and geochemical environment (oxic or anoxic conditions, pH, alkalinity) were associated with the distribution of high relative concentrations of inorganic and organic constituents. Young, oxygenated water is recharged along the Kern River and adjacent recharge ponds, or as irrigation water in the agricultural areas. High concentrations of nitrate and volatile organic compounds occurred in the oxic water in urban and agricultural areas. The fumigants 1,2,3-TCP, DBCP, and EDB were reported throughout the agricultural areas, whereas chloroform, tetrachloroethene, and PFAS were associated with urban land use. High uranium concentrations were associated with young, modern groundwater in agricultural areas with low pH and high bicarbonate. Total dissolved solids increased with distance from the Kern River, as the contributions of fresh, oxic water decreased. High concentrations of arsenic were present in older anoxic or alkaline groundwater away from areas of recharge. Overall, groundwater age, redox conditions, and the source of recharge as a result of different land uses contribute to large aquifer-scale portions of domestic groundwater resources that exceed health-based benchmarks for nitrate, uranium, and fumigant concentrations.

California↗

USGS2026

Transcriptional changes in wild Yukon River Chinook Salmon associated with Ichthyophonus infections

Objective We compared differentially expressed genes in Chinook Salmon Oncorhynchus tshawytscha with three divergent Ichthyophonus statuses (undetected, subclinical infections, or clinical disease; n = 100) to investigate associated transcriptomic responses. Disease associated with the fish parasite Ichthyophonus sp. was first diagnosed in adult Chinook Salmon from the Yukon River in the late 1980s and has subsequently been implicated in premature host mortality. Methods Chinook Salmon tissue sample collections and Ichthyophonus infection data were leveraged from a multi-agency collaboration during summer 2022 at three locations along the main-stem Yukon River that spanned nearly 2,000 km of freshwater migration (lower, middle, and upper river). We sequenced the transcriptome and compared this to infection status based on routine diagnostic procedures. Results Among the 17,569 genes for which messenger RNA was detected, we identified a transcription signature in the skeletal muscle that was associated with Ichthyophonus infections and included 53 differentially expressed genes. The differentially expressed genes and their pathways included those known for involvement in immune functions, energy synthesis, cellular breakdown, and reproduction—all processes that are known to be influenced by senescence during spawning migrations. Conclusions Results demonstrate a clear transcriptional difference between diseased fish (clinical disease group) and those in which Ichthyophonus was undetected, including identifying candidate markers for infection in this population. These results provide a foundation for development of nonlethal biomarkers to evaluate potential Ichthyophonus infections in Chinook Salmon based on gene transcription, protein products, or gene variants (e.g., polymorphisms).

Journal of Aquatic Animal Health↗

USGS2024

Surficial geology and Quaternary fault map of the Las Vegas Valley, Clark County, Nevada

The Surficial Geology and Quaternary Fault Map of the Las Vegas Valley, Clark County, Nevada is a 1:50,000-scale compilation of published 1:24,000-scale geologic maps integrated with new field and desktop mapping. This geologic map compilation and GIS database are part of a broader study on the Quaternary faults in the Las Vegas Valley, the results of which are summarized in this report. The map compilation utilized a variety of digital base maps to evaluate the characteristics of surficial deposits and Quaternary fault scarps including lidar data in undeveloped parts of the valley and orthorectified historical aerial photos in the urbanized center of the valley. The map distinguishes twenty surficial map units including alluvial-fan and ephemeral-wash deposits, groundwater discharge deposits of the Las Vegas Formation, and alluvium deposits of Las Vegas Wash. Quaternary faults include the Quaternary Las Vegas Valley fault system in the center of the valley and the Frenchman Mountain fault system along the eastern margin. All Quaternary fault traces in the valley were evaluated, and the previously published fault mapping was modified as needed. The new mapping and uniform correlation of surficial deposits displaced by Quaternary faults yields a consistent valley-wide characterization of the recency of fault activity. The map and GIS database include a Quaternary geochronology compilation of 119 previously published surficial deposit ages of various types, 35 new luminescence ages, and 3 new radiocarbon ages. The new age data further bracket the ages of the Las Vegas basin Quaternary stratigraphy and provide new constraints on the timing of Quaternary fault activity.

Nevada↗

USGS2025

How do hydrological variability and human activities control the spatiotemporal changes of riverine nitrogen export in the Upper Mississippi River Basin?

Excessive nitrogen export from agricultural watersheds remains a critical water quality challenge, with the Upper Mississippi River Basin (UMRB) significantly contributing to downstream eutrophication and hypoxia in the Gulf. This study investigates the spatiotemporal dynamics of riverine nitrate plus nitrite (NO 3 – + NO 2 – -N) export across the UMRB at high spatial resolution (12-digit Hydrologic Unit Codes or HUC12 subwatershed scale) during 2001–2020 and quantifies the effects of anthropogenic activities and hydrological variability on riverine NO 3 – + NO 2 – -N export changes in the region between 2001–2005 and 2016–2020. Our results revealed hotspots of substantial increases in NO 3 – + NO 2 – -N yields across the UMRB, with distinct regional patterns in driving factors. Over the entire UMRB, NO 3 – + NO 2 – -N yields increased by 9.7 kg/ha/yr on average from 2001–2005 to 2016–2020, with anthropogenic activities contributing 4.8 kg/ha/yr and hydrological variability contributing 4.9 kg/ha/yr. The northern and western UMRB had combined influences from both anthropogenic activities and hydrological variability, while the east-central regions had predominantly hydrologically driven changes. Agricultural sources, including fertilizer, manure, and biological nitrogen fixation, collectively contributed over 80% of NO 3 – + NO 2 – -N loading throughout the basin. This framework for disentangling human and hydrological impacts provides critical insights for developing effective and targeted watershed management strategies to reduce nutrient losses and improve water quality.

Upper Mississippi River Basin↗

USGS2025

Toward a new framework to evaluate process-based model configurations and quantify data worth prior to calibration

Model criticism, discrimination, and selection methods often rely on calibrated model outputs. Because calibration can be computationally expensive, model criticism can first be undertaken by assessing model outputs obtained from limited prior parameter ensembles. However, such prior-based methods are often heuristic and do not formalize the notion of balancing model consistency with data and model complexity (i.e., model adequacy). We present a new framework to discriminate among candidate models prior to calibration that formalizes prior-to-calibration model adequacy into a metric to implicitly balance prior model output data coverage with model complexity represented by prior output (co)variance. The prior model adequacy metric “Mahalanobis distance deviation” quantifies the deviation of (a) the set of squared Mahalanobis distances of data from a prior model output distribution from (b) the set of squared Mahalanobis distances of data from their own distribution. A new data worth metric “discernment value” is also presented which quantifies the value of data for screening less-adequate models prior to calibration. Discernment value is calculated from the change in variance of a weighted average of prior model outputs from all candidate models due to less-adequate model outputs receiving lower weight. The framework is demonstrated using a one-dimensional groundwater flow model with eight possible configurations. A synthetic data network is used to test the framework. Results show the framework identifies the candidate models most similar to the true model used to create the synthetic data. Discernment values show variation in the value of different data types and locations for screening less-adequate models.

Water Resources Research↗

USGS2024

The spatially adaptable filter for error reduction (SAFER) process: Remote sensing-based LANDFIRE disturbance mapping updates

LANDFIRE (LF) has been producing periodic spatially explicit vegetation change maps (i.e., LF disturbance products) across the entire United States since 1999 at a 30 m spatial resolution. These disturbance products include data products produced by various fire programs, field-mapped vegetation and fuel treatment activity (i.e., events) submissions from various agencies, and disturbances detected by the U.S. Geological Survey Earth Resources Observation and Science (EROS)-based Remote Sensing of Landscape Change (RSLC) process. The RSLC process applies a bi-temporal change detection algorithm to Landsat satellite-based seasonal composites to generate the interim disturbances that are subsequently reviewed by analysts to reduce omission and commission errors before ingestion them into LF’s disturbance products. The latency of the disturbance product is contingent on timely data availability and analyst review. This work describes the development and integration of the Spatially Adaptable Filter for Error Reduction (SAFER) process and other error and latency reduction improvements to the RSLC process. SAFER is a random forest-based supervised classifier and uses predictor variables that are derived from multiple years of pre- and post-disturbance Landsat band observations. Predictor variables include reflectance, indices, and spatial contextual information. Spatial contextual information that is unique to each contiguous disturbance region is parameterized as Z scores using differential observations of the disturbed regions with its undisturbed neighbors. The SAFER process was prototyped for inclusion in the RSLC process over five regions within the conterminous United States (CONUS) and regional model performance, evaluated using 2016 data. Results show that the inclusion of the SAFER process increased the accuracies of the interim disturbance detections and thus has potential to reduce the time needed for analyst review. LF does not track the time taken by each analyst for each tile, and hence, the relative effort saved was parameterized as the percentage of 30 m pixels that are correctly classified in the SAFER outputs to the total number of pixels that are incorrectly classified in the interim disturbance and are presented. The SAFER prototype outputs showed that the relative analysts’ effort saved could be over 95%. The regional model performance evaluation showed that SAFER’s performance depended on the nature of disturbances and availability of cloud-free images relative to the time of disturbances. The accuracy estimates for CONUS were inferred by comparing the 2017 SAFER outputs to the 2017 analyst-reviewed data. As expected, the SAFER outputs had higher accuracies compared to the interim disturbances, and CONUS-wide relative effort saved was over 92%. The regional variation in the accuracies and effort saved are discussed in relation to the vegetation and disturbance type in each region. SAFER is now operationally integrated into the RSLC process, and LANDFIRE is well poised for annual updates, contingent on the availability of data.

Fire↗