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USGS2021

Postwildfire soil‐hydraulic recovery and the persistence of debris flow hazards

Deadly and destructive debris flows often follow wildfire, but understanding of changes in the hazard potential with time since fire is poor. We develop a simulation‐based framework to quantify changes in the hydrologic triggering conditions for debris flows as postwildfire infiltration properties evolve through time. Our approach produces time‐varying rainfall intensity‐duration thresholds for runoff‐ and infiltration‐generated debris flows with physics‐based hydrologic simulations that are parameterized with widely available hydroclimatic, vegetation reflectance, and soil texture data. When we apply our thresholding protocol to a test case in the San Gabriel Mountains (California, USA), the results are consistent with existing regional empirical thresholds and rainstorms that caused runoff‐ and infiltration‐generated debris flows soon after and three years following a wildfire, respectively. We find that the hydrologic triggering mechanisms for the two observed debris flow types are coupled with the effects of fire on the soil saturated hydraulic conductivity. Specifically, the rainfall intensity needed to generate debris flows via runoff increases with time following wildfire while the rainfall duration needed to produce debris flows via subsurface pore‐water pressures decreases. We also find that variations in soil moisture, rainfall climatology, median grain size, and root reinforcement could impact the median annual probability of postwildfire debris flows. We conclude that a simulation‐based method for calculating rainfall thresholds is a tractable approach to improve situational awareness of debris flow hazard in the years following wildfire. Further development of our framework will be important to quantify postwildfire hazard levels in variable climates, vegetation types, and fire regimes.

Journal of Geophysical Research: Earth Surface↗

USGS2013

Effects of climate change and urban development on the distribution and conservation of vegetation in a Mediterranean type ecosystem

Climate and land-use changes are projected to threaten biodiversity over this century. However, few studies have considered the spatial and temporal overlap of these threats to evaluate how ongoing land-use change could affect species ranges projected to shift outside conservation areas. We evaluated climate change and urban development effects on vegetation distribution in the Southwest ecoregion, California Floristic Province, USA. We also evaluated how well a conservation network protects suitable habitat for rare plant species under these change projections and identified primary sources of uncertainty. We used consensus-based maps from three species distribution models (SDMs) to project current and future suitable habitat for 19 species representing different functional types (defined by fire-response – obligate seeders, resprouting shrubs – and life forms – herbs, subshrubs), and range sizes (large/common, small/rare). We used one spatially explicit urban growth projection; two climate models, emission scenarios, and probability thresholds applied to SDMs; and high-resolution (90 m) environmental data. We projected that suitable habitat could disappear for 4 species and decrease for 15 by 2080. Averaged centroids of suitable habitat (all species) were projected to shift tens (up to hundreds) of kilometers. Herbs showed a small-projected response to climate change, while obligate seeders could suffer the greatest losses. Several rare species could lose suitable habitat inside conservation areas while increasing area outside. We concluded that (i) climate change is more important than urban development for vegetation habitat loss in this ecoregion through 2080 due to diminishing amounts of undeveloped private land in this region; (ii) the existing conservation plan, while extensive, may be inadequate to protect plant diversity under projected patterns of climate change and urban development, (iii) regional assessments of the dynamics of the drivers of biodiversity change based on high-resolution environmental data and consensus predictive mapping, such as this study, are necessary to identify the species expected to be the most vulnerable and to meaningfully inform regional-scale conservation.

California↗

USGS2011

Density estimation in a wolverine population using spatial capture-recapture models

Classical closed-population capture-recapture models do not accommodate the spatial information inherent in encounter history data obtained from camera-trapping studies. As a result, individual heterogeneity in encounter probability is induced, and it is not possible to estimate density objectively because trap arrays do not have a well-defined sample area. We applied newly-developed, capture-recapture models that accommodate the spatial attribute inherent in capture-recapture data to a population of wolverines (Gulo gulo) in Southeast Alaska in 2008. We used camera-trapping data collected from 37 cameras in a 2,140-km 2 area of forested and open habitats largely enclosed by ocean and glacial icefields. We detected 21 unique individuals 115 times. Wolverines exhibited a strong positive trap response, with an increased tendency to revisit previously visited traps. Under the trap-response model, we estimated wolverine density at 9.7 individuals/1,000-km 2 (95% Bayesian CI: 5.9-15.0). Our model provides a formal statistical framework for estimating density from wolverine camera-trapping studies that accounts for a behavioral response due to baited traps. Further, our model-based estimator does not have strict requirements about the spatial configuration of traps or length of trapping sessions, providing considerable operational flexibility in the development of field studies.

Alaska↗

USGS2017

Stochastic programming with a joint chance constraint model for reservoir refill operation considering flood risk

Reservoir refill operation modeling attempts to maximize a set of benefits while minimizing risks. The benefits and risks can be in opposition to each other, such as having enough water for hydropower generation while leaving enough room for flood protection. In addition to multiple objects, the uncertainty of streamflow can make decision making difficult. This paper develops a stochastic optimization model for reservoir refill operation with the objective of maximizing the expected synthesized energy production for a cascade system of hydropower stations while considering flood risk. Streamflow uncertainty is addressed by discretized streamflow scenarios and flood risk is controlled by a joint chance constraint restricting the occurrence probability. With the variability of flood risk level, two advancing refill scenarios for exploring operation benefit are presented. Scenario I loosens the current stagewise storage bounds conditions and allows advancing reservoir refills but keeps the flood risk level the same as the refill policies obtained under the current storage bounds. Scenario II keeps the current storage bounds unchanged but allows increases in flood risk level. The proposed methodology is applied to the Xiluodu cascade system of reservoirs in China and investigates the optimal refill policies obtained by both scenarios. Compared with the benchmark obtained under the current storage bounds and lowest flood risk level, the results show (1) the synthesized energy production can be improved by 2.13% without changing the flood risk level under Scenario I, and (2) the synthesized energy production can also be increased by 0.21% at the expense of increasing the flood risk level by 4.4% when Scenario II is employed. As Scenario I produces higher benefit and lower risk than Scenario II, it is recommended to loosen the current stagewise storage bounds but to keep the flood risk level unchanged during refill operations.

Xiluodu Cascade Reservoir↗

USGS2015

Integrating spatially explicit indices of abundance and habitat quality: an applied example for greater sage-grouse management

Predictive species distributional models are a cornerstone of wildlife conservation planning. Constructing such models requires robust underpinning science that integrates formerly disparate data types to achieve effective species management. Greater sage-grouse Centrocercus urophasianus , hereafter “sage-grouse” populations are declining throughout sagebrush-steppe ecosystems in North America, particularly within the Great Basin, which heightens the need for novel management tools that maximize use of available information. Herein, we improve upon existing species distribution models by combining information about sage-grouse habitat quality, distribution, and abundance from multiple data sources. To measure habitat, we created spatially explicit maps depicting habitat selection indices (HSI) informed by > 35 500 independent telemetry locations from > 1600 sage-grouse collected over 15 years across much of the Great Basin. These indices were derived from models that accounted for selection at different spatial scales and seasons. A region-wide HSI was calculated using the HSI surfaces modelled for 12 independent subregions and then demarcated into distinct habitat quality classes. We also employed a novel index to describe landscape patterns of sage-grouse abundance and space use (AUI). The AUI is a probabilistic composite of: (i) breeding density patterns based on the spatial configuration of breeding leks and associated trends in male attendance; and (ii) year-round patterns of space use indexed by the decreasing probability of use with increasing distance to leks. The continuous AUI surface was then reclassified into two classes representing high and low/no use and abundance. Synthesis and application s. Using the example of sage-grouse, we demonstrate how the joint application of indices of habitat selection, abundance, and space use derived from multiple data sources yields a composite map that can guide effective allocation of management intensity across multiple spatial scales. As applied to sage-grouse, the composite map identifies spatially explicit management categories within sagebrush steppe that are most critical to sustaining sage-grouse populations as well as those areas where changes in land use would likely have minimal impact. Importantly, collaborative efforts among stakeholders guide which intersections of habitat selection indices and abundance and space use classes are used to define management categories. Because sage-grouse are an umbrella species, our joint-index modelling approach can help target effective conservation for other sagebrush obligate species, and can be readily applied to species in other ecosystems with similar life histories, such as central-placed breeding.

California, Nevada↗

USGS2001

Pollen-based biomes for Beringia 18,000, 6000 and 0 14C yr BP

The objective biomization method developed by Prentice et al. (1996) for Europe was extended using modern pollen samples from Beringia and then applied to fossil pollen data to reconstruct palaeovegetation patterns at 6000 and 18,000 14C yr BP. The predicted modern distribution of tundra, taiga and cool conifer forests in Alaska and north-western Canada generally corresponds well to actual vegetation patterns, although sites in regions characterized today by a mosaic of forest and tundra vegetation tend to be preferentially assigned to tundra. Siberian larch forests are delimited less well, probably due to the extreme under-representation of Larix in pollen spectra. The biome distribution across Beringia at 6000 14C yr BP was broadly similar to today, with little change in the northern forest limit, except for a possible northward-advance in the Mackenzie delta region. The western forest limit in Alaska was probably east of its modern position. At 18,000 14C yr BP the whole of Beringia was covered by tundra. However, the importance of the various plant functional types varied from site to site, supporting the idea that the vegetation cover was a mosaic of different tundra types.

Journal of Biogeography↗

USGS2010

Modelling community dynamics based on species-level abundance models from detection/nondetection data

1. In large‐scale field surveys, a binary recording of each species’ detection or nondetection has been increasingly adopted for its simplicity and low cost. Because of the importance of abundance in many studies, it is desirable to obtain inferences about abundance at species‐, functional group‐, and community‐levels from such binary data. 2. We developed a novel hierarchical multi‐species abundance model based on species‐level detection/nondetection data. The model accounts for the existence of undetected species, and variability in abundance and detectability among species. Species‐level detection/nondetection is linked to species‐level abundance via a detection model that accommodates the expectation that probability of detection (at least one individuals is detected) increases with local abundance of the species. We applied this model to a 9‐year dataset composed of the detection/nondetection of forest birds, at a single post‐fire site (from 7 to 15 years after fire) in a montane area of central Japan. The model allocated undetected species into one of the predefined functional groups by assuming a prior distribution on individual group membership. 3. The results suggest that 15–20 species were missed in each year, and that species richness of communities and functional groups did not change with post‐fire forest succession. Overall abundance of birds and abundance of functional groups tended to increase over time, although only in the winter, while decreases in detectabilities were observed in several species. 4. Synthesis and applications . Understanding and prediction of large‐scale biodiversity dynamics partly hinge on how we can use data effectively. Our hierarchical model for detection/nondetection data estimates abundance in space/time at species‐, functional group‐, and community‐levels while accounting for undetected individuals and species. It also permits comparison of multiple communities by many types of abundance‐based diversity and similarity measures under imperfect detection.

Journal of Applied Ecology↗

USGS2017

Contribution of manipulable and non-manipulable environmental factors to trapping efficiency of invasive sea lamprey

We identified aspects of the trapping process that afforded opportunities for improving trap efficiency of invasive sea lamprey ( Petromyzon marinus ) in a Great Lake's tributary. Capturing a sea lamprey requires it to encounter the trap, enter, and be retained until removed. Probabilities of these events depend on the interplay between sea lamprey behavior, environmental conditions, and trap design. We first tested how strongly seasonal patterns in daily trap catches (a measure of trapping success) were related to nightly rates of trap encounter, entry, and retention (outcomes of sea lamprey behavior). We then tested the degree to which variation in rates of trap encounter, entry, and retention were related to environmental features that control agents can manipulate (attractant pheromone addition, discharge) and features agents cannot manipulate (water temperature, season), but could be used as indicators for when to increase trapping effort. Daily trap catch was most strongly associated with rate of encounter. Relative and absolute measures of predictive strength for environmental factors that managers could potentially manipulate were low, suggesting that opportunities to improve trapping success by manipulating factors that affect rates of encounter, entry, and retention are limited. According to results at this trap, more sea lamprey would be captured by increasing trapping effort early in the season when sea lamprey encounter rates with traps are high. The approach used in this study could be applied to trapping of other invasive or valued species.

Journal of Great Lakes Research↗

USGS2005

Designing occupancy studies: General advice and allocating survey effort

1. The fraction of sampling units in a landscape where a target species is present (occu pancy) is an extensively used concept in ecology. Yet in many applications the species will not always be detected in a sampling unit even when present, resulting in biased estimates of occupancy. Given that sampling units are surveyed repeatedly within a r elatively short timeframe, a number of similar methods have now been developed to provide unbiased occupancy estimates. However, practical guidance on the efficient design of occupancy studies has been lacking. 2. In this paper we comment on a number of general issues related to designing occu pancy studies, including the need for clear objectives that are explicitly linked to science or management, selection of sampling units, timing of repeat surveys and allocation of survey effort. Advice on the number of repeat surveys per sampling unit is considered in terms of the variance of the occupancy estimator, for three possible study designs. 3. We r ecommend that sampling units should be surveyed a minimum of three times w hen detection probability is high (> 0·5 survey − 1 ), unless a removal design is used. 4. We f ound that an optimal removal design will generally be the most efficient, but we suggest it may be less robust to assumption violations than a standard design. 5. Our results suggest that for a rare species it is more efficient to survey more sampling units less intensively, while for a common species fewer sampling units should be surveyed more intensively. 6. Synthesis and applications . Reliable inferences can only result from quality data. To ma ke the best use of logistical resources, study objectives must be clearly defined; sampling units must be selected, and repeated surveys timed appropriately; and a sufficient n umber of repeated surveys must be conducted. Failure to do so may compromise the integrity of the study. The guidance given here on study design issues is particularly a pplicable to studies of species occurrence and distribution, habitat selection and modelling, metapopulation studies and monitoring programmes.

Journal of Applied Ecology↗

USGS2018

Decision making for mitigating wildlife diseases: From theory to practice for an emerging fungal pathogen of amphibians

Conservation science can be most effective in its decision‐support role when seeking answers to clearly formulated questions of direct management relevance. Emerging wildlife diseases, a driver of global biodiversity loss, illustrate the challenges of performing this role: in spite of considerable research, successful disease mitigation is uncommon. Decision analysis is increasingly advocated to guide mitigation planning, but its application remains rare. Using an integral projection model, we explored potential mitigation actions for avoiding population declines and the ongoing spatial spread of the fungus Batrachochytrium salamandrivorans ( Bsal ). This fungus has recently caused severe amphibian declines in north‐western Europe and currently threatens Palearctic salamander diversity. Available evidence suggests that a Bsal outbreak in a fire salamander ( Salamandra salamandra ) population will lead to its rapid extirpation. Treatments such as antifungals or probiotics would need to effectively interrupt transmission (reduce probability of infection by nearly 90%) in order to reduce the risk of host extirpation and successfully eradicate the pathogen. Improving the survival of infected hosts is most likely to be detrimental as it increases the potential for pathogen transmission and spread. Active removal of a large proportion of the host population has some potential to locally eradicate Bsal and interrupt its spread, depending on the presence of Bsal reservoirs and on the host's spatial dynamics, which should therefore represent research priorities. Synthesis and applications . Mitigation of Batrachochytrium salamandrivorans epidemics in susceptible host species is highly challenging, requiring effective interruption of transmission and radical removal of host individuals. More generally, our study illustrates the advantages of framing conservation science directly in the management decision context, rather than adapting to it a posteriori .

Journal of Applied Ecology↗

USGS2000

Numerical model of frazil ice and suspended sediment concentrations and formation of sediment laden ice in the Kara Sea

A one-dimensional (vertical) numerical model of currents, mixing, frazil ice concentration, and suspended sediment concentration has been developed and applied in the shallow southeastern Kara Sea. The objective of the calculations is to determine whether conditions suitable for turbid ice formation can occur during times of rapid cooling and wind- and wave-induced sediment resuspension. Although the model uses a simplistic approach to ice particles and neglects ice-sediment interactions, the results for low-stratification, shallow (∼20-m) freeze-up conditions indicate that the coconcentrations of frazil ice and suspended sediment in the water column are similar to observed concentrations of sediment in turbid ice. This suggests that wave-induced sediment resuspension is a viable mechanism for turbid ice formation, and enrichment mechanisms proposed to explain the high concentrations of sediment in turbid ice relative to sediment concentrations in underlying water may not be necessary in energetic conditions. However, salinity stratification found near the Ob' and Yenisey Rivers damps mixing between ice-laden surface water and sediment-laden bottom water and probably limits incorporation of resuspended sediment into turbid ice until prolonged or repeated wind events mix away the stratification. Sensitivity analyses indicate that shallow (≤20 m), unstratified waters with fine bottom sediment (settling speeds of ∼1 mm s −1 or less) and long open water fetches (>25 km) are ideal conditions for resuspension.

Kara Sea↗

USGS1997

Permeability and porosity of the Illinois UPH 3 drillhole granite and a comparison with other deep drillhole rocks

Permeability, porosity, and volumetric strain measurements were conducted on granite cores obtained at depths of 0.7 to 1.6 km from the Illinois UPH 3 drillhole at effective confining pressures from 5 to 100 MPa. Initial permeabilities were in the range of 10-17 to 10-19 m2 and dropped rapidly with applied pressure to values between 10-20 and 10-24 m2 at 100 MPa, typical of other deep granite core samples. These values are several decades lower than equivalent weathered surface granites at comparable effective confining pressures, where weathering products in cracks and pores inhibit crack closure with applied pressure. Permeabilities of the Illinois cores were inversely related to sample depth, suggesting that stress relief and thermal microfractures induced during core retrieval dominated the fluid flow. Thus these samples provide an upper bound on in situ matrix permeability values. A comparison of core permeability from UPH 3 and other deep drillholes shows that stress relief damage can often dominate laboratory permeability measurements. We conclude that it may be difficult to make meaningful estimates of in situ permeability based on either borehole samples (possible damage during retrieval) or surface-derived analogs (altered by weathering). Volumetric strain determined from porosity measurements was compared with differential strain analysis (DSA) data reported by other investigators on samples from the same depths in the drillhole. Our strain measurements (0.002 to 0.005 at 100 MPa) were nearly twice as large as the DSA values, probably because of the crack-enhancing effects of fluids present in our samples that are absent in the dry DSA cores, as well as other time-dependent deformation effects. This difference in observed strain magnitudes between the two measurement methods may be an important consideration if strain and/or porosity data from deep core samples are used in models of stress, fluid circulation, and excess fluid pressure generation in the midcrust.

Journal of Geophysical Research B: Solid Earth↗

USGS2020

The influence of climate variability on the accuracy of NHD perennial and non-perennial stream classifications

National Hydrography Dataset (NHD) stream permanence classifications (SPC; perennial, intermittent, and ephemeral) are widely used for data visualization and applied science, and have implications for resource policy and management. NHD SPC were assigned using a combination of topographic field surveys and interviews with local residents. However, previous studies indicate that non‐NHD, in situ streamflow observations (NNO) frequently disagree with NHD SPC. We hypothesized that differences in annual climate conditions between map creation years and the years NNO were collected contributed to disagreement between NNO and NHD SPC. We compared NHD SPC to 10,055 NNO (classified as “wet” or “dry”) collected in the Pacific Northwest between 1977 and 2015. Annual climate conditions were described with the Palmer Drought Severity Index (PDSI). Stream order was added as a covariate to account for different effects along the stream network. NHD SPC agreed with 80.5% of NNO. “Dry” NNO were five times more likely to disagree with NHD than “wet” NNO ( p < 0.0001). Disagreement was greatest on first‐order streams. When NHD SPC were collected during a wetter period than NNO the probability of disagreement increased by a factor of 1.17 ( p < 0.0001) per unit difference in PDSI. The influence of climate on disagreements between NNO and NHD SPC provides support for the continued development of dynamic models representing SPC as opposed to static NHD classifications.

Journal of the American Water Resources Associatio↗

USGS2014

Survival of hatchery Gulf sturgeon ( Acipenser oxyrinchus desotoi Mitchill, 1815) in the Suwannee River, Florida: a 19-year evaluation

An experimental release of 1192 hatchery-reared, individually PIT tagged, 220 days old (296–337 mm TL) Gulf sturgeon, Acipenser oxyrinchus desotoi , was undertaken in 1992 in the Suwannee River, Florida. The original objectives of the 1992 release experiment were to: (1) evaluate survival rate of cultured Gulf sturgeon in the wild vs survival rate of their wild 1992 cohort counterparts, (2) determine the differential effect of release site within the river upon long-term survival, and (3) evaluate comparative growth rates of recaptured hatchery vs captured wild 1992 cohort Gulf sturgeon. The present investigation addressed those original objectives, plus an additional fourth objective: (4) evaluation of hatchery fish recapture rate change over the 19-year experiment. The primary objective was to determine efficacy of potential conservation aquaculture for this species in terms of long-term survival in the wild. Follow-up 1993–2011 gill net sampling in freshwater reaches (rkm 4–237) and the estuarine river mouth (rkm −6 to 4) yielded recaptures representing 13.0% of the total released. Mean annual hatchery fish mortality (including emigration) rate estimated for the 19-year period (1993–2011) was more than twice that for same cohort wild fish. Mark-recapture survival probability (phi) for hatchery fish, 1993–2011, was substantially lower (0.733) than for their wild counterparts (0.888). Mean annual hatchery fish recapture rate, as a percentage of all 1992 cohort fish recaptures, declined significantly after age-7, coinciding with age of onset of migration into the open Gulf of Mexico. Hypothesized causal factors may be differentially lower fitness in the marine habitat or permanent outmigration due to natal river imprinting failure. Hatchery fish recapture rates varied significantly for fish from the ten release sites, being highest near the river mouth, and lowest for the furthest upriver sites in the Suwannee River and its Santa Fe River tributary. Hatchery fish also displayed a significantly lower growth rate than their wild counterparts through age 3000 days. Cumulative hatchery fish mortality of 99.87% over 19 years predicts <3 individuals would have survived through 2011. From the results of the 1992 release experiment, hatchery supplementation as a Gulf sturgeon conservation measure does not appear to be an effective option.

Florida↗

USGS2026

Spatially concentrating logging could mitigate climate-magnified fragmentation risks to a globally endangered bird

1. Rising timber demand is transforming forest structure globally, profoundly affecting biodiversity and climate resilience. Logging-driven fragmentation is potentially a major driver of biodiversity loss in production landscapes, yet its interactions with escalating climate stressors remain poorly understood. 2. We combine two decades of Landsat-derived habitat metrics with 29,000 surveys of the marbled murrelet ( Brachyramphus marmoratus )—an iconic Pacific Northwest old-forest specialist seabird affecting management of >10 million hectares. Controlling for habitat amount and detection probability, increasing landscape-scale forest edge amount sharply reduces murrelet occupancy, with impacts worsening under unfavourable climate-driven ocean conditions. 3. Comparing alternative landscape-scale timber harvest strategies, spatially concentrated logging consistently supports higher murrelet populations than fragmented approaches producing equivalent wood volumes, with benefits amplified under adverse ocean conditions. However, historical harvesting policies in the Pacific Northwest have instead driven severe habitat fragmentation, which we show is eroding the value of core set-aside forests on federal and conservation lands and ultimately rendering murrelets more vulnerable to climate change. 4. Synthesis and applications : We map key opportunities to boost populations by reducing edginess around remaining nesting habitat and investigate these opportunities' spatial distribution across land ownership and timber productivity gradients. Concentrating logging could be critical for mitigating fragmentation and climate threats for murrelets and potentially other forest-dependent species amid rising timber demand.

California, Oregon, Washington↗

USGS2005

The soil physics contributions of Edgar Buckingham

During 1902 to 1906 as a soil physicist at the USDA Bureau of Soils (BOS), Edgar Buckingham originated the concepts of matric potential, soil–water retention curves, specific water capacity, and unsaturated hydraulic conductivity ( K ) as a distinct property of a soil. He applied a formula equivalent to Darcy's law (though without specific mention of Darcy's work) to unsaturated flow. He also contributed significant research on quasi-empirical formulas for K as a function of water content, water flow in capillary crevices and in thin films, and scaling. Buckingham's work on gas flow in soils produced paradigms that are consistent with our current understanding. His work on evaporation elucidated the concept of self-mulching and produced sound and sometimes paradoxical generalizations concerning conditions that favor or retard evaporation. Largely overshadowing those achievements, however, is that he launched a theory, still accepted today, that could predict transient water content as a function of time and space. Recently discovered documents reveal some of the arguments Buckingham had with BOS officials, including the text of a two-paragraph conclusion of his famous 1907 report on soil water, and the official letter documenting rejection of that text. Strained interpersonal relations motivated the departure of Buckingham and other brilliant physicists (N.E. Dorsey, F.H. King, and Lyman Briggs) from the BOS during 1903 to 1906. Given that Buckingham and his BOS colleagues had been rapidly developing the means of quantifying unsaturated flow, these strained relations probably slowed the advancement of unsaturated flow theory.

Soil Science Society of America Journal↗

USGS2006

Quantitative methods to direct exploration based on hydrogeologic information

Quantitatively Directed Exploration (QDE) approaches based on information such as model sensitivity, input data covariance and model output covariance are presented. Seven approaches for directing exploration are developed, applied, and evaluated on a synthetic hydrogeologic site. The QDE approaches evaluate input information uncertainty, subsurface model sensitivity and, most importantly, output covariance to identify the next location to sample. Spatial input parameter values and covariances are calculated with the multivariate conditional probability calculation from a limited number of samples. A variogram structure is used during data extrapolation to describe the spatial continuity, or correlation, of subsurface information. Model sensitivity can be determined by perturbing input data and evaluating output response or, as in this work, sensitivities can be programmed directly into an analysis model. Output covariance is calculated by the First-Order Second Moment (FOSM) method, which combines the covariance of input information with model sensitivity. A groundwater flow example, modeled in MODFLOW-2000, is chosen to demonstrate the seven QDE approaches. MODFLOW-2000 is used to obtain the piezometric head and the model sensitivity simultaneously. The seven QDE approaches are evaluated based on the accuracy of the modeled piezometric head after information from a QDE sample is added. For the synthetic site used in this study, the QDE approach that identifies the location of hydraulic conductivity that contributes the most to the overall piezometric head variance proved to be the best method to quantitatively direct exploration. ?? IWA Publishing 2006.

Journal of Hydroinformatics↗

USGS2025

The joint effect of changes in urbanization and climate on trends in floods: A comparison of panel and single-station quantile regression approaches

Estimates of annual maximum (peak) flow quantiles are needed for basins undergoing changes in both urbanization and climate. Most previous work on the effect of urbanization on peak flows has considered urbanization alone and only the spatial variation in flood quantiles or its mean temporal effect, and most work on the effect of nonstationarity in climate has focused on single-station analyses, which give uncertain results for extreme quantiles. To address these gaps, three approaches to the statistical estimation of the joint effects of changes in impervious cover and climate on the estimation of peak-flow quantiles were compared: single-station quantile regression; a fixed effect panel-quantile regression (pQR) method using a location (mean) shift to homogenize the panel; and a location-scale panel regression model (pQRmom), which accounts for both scale (variance) and location effects. The different approaches were applied to a dataset consisting of instantaneous annual peak flows from 127 minimally nested basins in the midwestern United States with at least 4 % change in imperviousness. The annual maximum daily discharge from a water-balance model was selected as the primary climate predictor; in addition, to provide a comparison of climate predictors, precipitation was also considered. The coefficients from single-station regressions were usually sufficiently certain to determine the effects of climate variation but usually too uncertain to estimate the effects of urbanization. The panel-quantile regression approaches give much more certain results, but their estimates of quantile dependence differ: although both indicate urbanization effects decreasing with decreasing annual exceedance probability (AEP), the pQRmom urbanization coefficients are insignificantly different from zero for AEPs less than 0.10, whereas the pQR coefficients remain positive and are significant except for AEP = 0.01, the smallest AEP value considered. Although the location-scale structure of the pQRmom approach has less flexible quantile dependence than the pQR approach, the pQRmom approach has somewhat lower overall error, and it is found that by subsetting the dataset to homogenize the scale effects, the pQR and pQRmom results become similar, indicating the insignificant urbanization coefficients for small AEPs of the pQRmom results are likely correct for the study dataset.

Arkansas, Illinois, Indiana, Iowa, Michigan, Minne↗