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USGS2021

An integrated path for spatial capture–recapture and animal movement modeling

Ecologists and conservation biologists increasingly rely on spatial capture–recapture (SCR) and movement modeling to study animal populations. Historically, SCR has focused on population-level processes (e.g., vital rates, abundance, density, and distribution), whereas animal movement modeling has focused on the behavior of individuals (e.g., activity budgets, resource selection, migration). Even though animal movement is clearly a driver of population-level patterns and dynamics, technical and conceptual developments to date have not forged a firm link between the two fields. Instead, movement modeling has typically focused on the individual level without providing a coherent scaling from individual- to population-level processes, whereas SCR has typically focused on the population level while greatly simplifying the movement processes that give rise to the observations underlying these models. In our view, the integration of SCR and animal movement modeling has tremendous potential for allowing ecologists to scale up from individuals to populations and advancing the types of inferences that can be made at the intersection of population, movement, and landscape ecology. Properly accounting for complex animal movement processes can also potentially reduce bias in estimators of population-level parameters, thereby improving inferences that are critical for species conservation and management. This introductory article to the Special Feature reviews recent advances in SCR and animal movement modeling, establishes a common notation, highlights potential advantages of linking individual-level (Lagrangian) movements to population-level (Eulerian) processes, and outlines a general conceptual framework for the integration of movement and SCR models. We then identify important avenues for future research, including key challenges and potential pitfalls in the developments and applications that lie ahead.

Ecology↗

USGS2022

Evaluating hydrologic region assignment techniques for ungaged basins in Alaska, USA

Building continental-scale hydrologic models in data-sparse regions requires an understanding of spatial variation in hydrologic processes. Extending these models to ungaged locations requires techniques to group ungaged locations with gaged ones to make process importance and model parameter transfer decisions to ungaged locations. This analysis (1) tested the utility of fundamental streamflow statistics (FDSS) in defining hydrologic regions across Alaska, USA; (2) evaluated if the hydrologic regions represented different hydrologic processes; and (3) tested the ability of random forest and direct assignment techniques, informed by statistically estimated FDSS (FDSSest) and basin characteristics (BCs), to correctly assign ungaged locations to hydrologic regions. Six hydrologic regions were identified across the domain using FDSS. Differences in mean flow, phase shift of the seasonal cycle, and skewness were the primary characteristics defining each region. Two regions represented arctic and continental climates, generally in the northern portion of the domain; four regions represented the southern, maritime portion of the domain. Random forest modeling with BCs (67% success rate) outperformed FDSSest (58% success rate) suggesting that no statistically estimated streamflow was needed to assign ungaged locations to a region. For regions with many sites, most region assignment techniques performed similarly. Random forest modeling performance declined when BCs and FDSSest were both used to predict region membership, suggesting FDSSest had little information in addition to BCs. This analysis demonstrated that FDSS-based hydrologic regions discern process differences across a data-sparse and hydrologically diverse landscape. Process importance rankings from random forest-derived BCs provided model-independent information for making modeling decisions.

Alaska↗

USGS2006

Rime and graupel: Description and characterization as revealed by low-temperature scanning electron microscopy

Snow crystals, which form by vapor deposition, occasionally come in contact with supercooled cloud droplets during their formation and descent. When this occurs, the droplets adhere and freeze to the snow crystals in a process known as accretion. During the early stages of accretion, discrete snow crystals exhibiting frozen cloud droplets are referred to as rime. If this process continues, the snow crystal may become completely engulfed in frozen cloud droplets. The resulting particle is known as graupel. Light microscopic investigations have studied rime and graupel for nearly 100 years. However, the limiting resolution and depth of field associated with the light microscope have prevented detailed descriptions of the microscopic cloud droplets and the three-dimensional topography of the rime and graupel particles. This study uses low-temperature scanning electron microscopy to characterize the frozen precipitates that are commonly known as rime and graupel. Rime, consisting of frozen cloud droplets, is observed on all types of snow crystals including needles, columns, plates, and dendrites. The droplets, which vary in size from 10 to 100 μm, frequently accumulate along one face of a single snow crystal, but are found more randomly distributed on aggregations consisting of two or more snow crystals (snowflakes). The early stages of riming are characterized by the presence of frozen cloud droplets that appear as a layer of flattened hemispheres on the surface of the snow crystal. As this process continues, the cloud droplets appear more sinuous and elongate as they contact and freeze to the rimed crystals. The advanced stages of this process result in graupel, a particle 1 to 3 mm across, composed of hundreds of frozen cloud droplets interspersed with considerable air spaces; the original snow crystal is no longer discernible. This study increases our knowledge about the process and characteristics of riming and suggests that the initial appearance of the flattened hemispheres may result from impact of the leading face of the snow crystal with cloud droplets. The elongated and sinuous configurations of frozen cloud droplets that are encountered on the more advanced stages suggest that aerodynamic forces propel cloud droplets to the trailing face of the descending crystal where they make contact and freeze.

Scanning↗

USGS2015

Application of science-based restoration planning to a desert river system

Persistence of many desert river species is threatened by a suite of impacts linked to water infrastructure projects that provide human water security where water is scarce. Many desert rivers have undergone regime shifts from spatially and temporally dynamic ecosystems to more stable systems dominated by homogenous physical habitat. Restoration of desert river systems could aid in biodiversity conservation, but poses formidable challenges due to multiple threats and the infeasibility of recovery to pre-development conditions. The challenges faced in restoring desert rivers can be addressed by incorporating scientific recommendations into restoration planning efforts at multiple stages, as demonstrated here through an example restoration project. In particular, use of a watershed-scale planning process can identify data gaps and irreversible constraints, which aid in developing achievable restoration goals and objectives. Site-prioritization focuses limited the resources for restoration on areas with the greatest potential to improve populations of target organisms. Investment in research to understand causes of degradation, coupled with adoption of a guiding vision is critical for identifying feasible restoration actions that can enhance river processes. Setting monitoring as a project goal, developing hypotheses for expected outcomes, and implementing restoration as an experimental design will facilitate adaptive management and learning from project implementation. Involvement of scientists and managers during all planning stages is critical for developing process-based restoration actions and an implementation plan to maximize learning. The planning process developed here provides a roadmap for use of scientific recommendations in future efforts to recover dynamic processes in imperiled riverine ecosystems.

San Rafael River watershed↗

USGS2023

Becoming an actionable scientist: Challenges, competency, and the development of expertise

Demand has grown for actionable science to support real-world decision-making around climate change and related environmental management challenges. Producing actionable science requires scientists to hold a distinct set of competencies, yet relatively little is known about what these competencies are or how to train scientists to develop them. We conducted interviews with mid- and late-career scientists to empirically identify competencies they used when producing actionable science and to understand how they developed those competencies. We describe expertise in terms of 18 competencies—categorised as cognitive, interpersonal, or intrapersonal—that scientists integrated and applied to address the challenges associated with actionable science. We argue that scientists must engage in the social process of producing actionable science (i.e., learning by doing) to become an expert. Expert actionable scientists discussed the importance of learning through different contexts, processes, interactions, and relationships. By naming the competencies that constitute expertise, as well as methods for expertise development, our findings facilitate greater conscious awareness of the process of becoming an actionable scientist, a gradual process that starts during graduate training and continues as a career proceeds. Our results can inform the development of formal learning opportunities as well as the informal learning process that occurs whereby scientists take charge of their own learning.

Environmental Management↗

USGS2005

Geochemistry and the understanding of ground-water systems

Geochemistry has contributed significantly to the understanding of ground-water systems over the last 50 years. Historic advances include development of the hydrochemical facies concept, application of equilibrium theory, investigation of redox processes, and radiocarbon dating. Other hydrochemical concepts, tools, and techniques have helped elucidate mechanisms of flow and transport in ground-water systems, and have helped unlock an archive of paleoenvironmental information. Hydrochemical and isotopic information can be used to interpret the origin and mode of ground-water recharge, refine estimates of time scales of recharge and ground-water flow, decipher reactive processes, provide paleohydrological information, and calibrate ground-water flow models. Progress needs to be made in obtaining representative samples. Improvements are needed in the interpretation of the information obtained, and in the construction and interpretation of numerical models utilizing hydrochemical data. The best approach will ensure an optimized iterative process between field data collection and analysis, interpretation, and the application of forward, inverse, and statistical modeling tools. Advances are anticipated from microbiological investigations, the characterization of natural organics, isotopic fingerprinting, applications of dissolved gas measurements, and the fields of reaction kinetics and coupled processes. A thermodynamic perspective is offered that could facilitate the comparison and understanding of the multiple physical, chemical, and biological processes affecting ground-water systems.

Hydrogeology Journal↗

USGS2006

Landscape attributes and life history variability shape genetic structure of trout populations in a stream network

Spatial and temporal landscape patterns have long been recognized to influence biological processes, but these processes often operate at scales that are difficult to study by conventional means. Inferences from genetic markers can overcome some of these limitations. We used a landscape genetics approach to test hypotheses concerning landscape processes influencing the demography of Lahontan cutthroat trout in a complex stream network in the Great Basin desert of the western US. Predictions were tested with population- and individual-based analyses of microsatellite DNA variation, reflecting patterns of dispersal, population stability, and local effective population sizes. Complementary genetic inferences suggested samples from migratory corridors housed a mixture of fish from tributaries, as predicted based on assumed migratory life histories in those habitats. Also as predicted, populations presumed to have greater proportions of migratory fish or from physically connected, large, or high quality habitats had higher genetic variability and reduced genetic differentiation from other populations. Populations thought to contain largely non-migratory individuals generally showed the opposite pattern, suggesting behavioral isolation. Estimated effective sizes were small, and we identified significant and severe genetic bottlenecks in several populations that were isolated, recently founded, or that inhabit streams that desiccate frequently. Overall, this work suggested that Lahontan cutthroat trout populations in stream networks are affected by a combination of landscape and metapopulation processes. Results also demonstrated that genetic patterns can reveal unexpected processes, even within a system that is well studied from a conventional ecological perspective. ?? Springer 2006.

Landscape Ecology↗

USGS2015

The scaling of geographic ranges: implications for species distribution models

Context The geographic ranges of many species are responding to ongoing environmental change. Processes operating at different levels of biological organization, with corresponding spatial extents and grains and temporal rates, interact with the evolving configuration of environmental conditions to determine range dynamics. Objectives To synthesize understanding of scales and scaling, including relevant biological levels of organization, focusing on the processes that mediate species-environment relationships and the models used to make inferences about species distributions. Methods We review concepts related to the scaling of geographic ranges and implications for the most commonly used analytic methods, using simple simulations to illustrate important issues. Results Many processes lead to species distributions being dependent on environmental conditions within sites and within a neighborhood. Studies with large extents and fine grains can cut across several levels of biological organization (individual, within-population, and metapopulation processes) complicating interpretation. Many geographic ranges are not in dynamic equilibrium, but common models used for inference assume equilibrium. Interspecific interactions shape species distributions at multiple scales, and arguments for ignoring species interactions also assume equilibrium. Conclusions There is a need for timely science to inform policy and management decisions; however, we must also strive to provide predictions that best reflect our understanding of ecological systems. Species distributions evolve through time and reflect responses to environmental conditions that are mediated through individual and population processes. Species distribution models that reflect this understanding, and explicitly model dynamics, are likely to give more accurate predictions.

Landscape Ecology↗

USGS2016

The role of ocean tides on groundwater-surface water exchange in a mangrove-dominated estuary: Shark River Slough, Florida Coastal Everglades, USA

Low-relief environments like the Florida Coastal Everglades (FCE) have complicated hydrologic systems where surface water and groundwater processes are intimately linked yet hard to separate. Fluid exchange within these lowhydraulic-gradient systems can occur across broad spatial and temporal scales, with variable contributions to material transport and transformation. Identifying and assessing the scales at which these processes operate is essential for accurate evaluations of how these systems contribute to global biogeochemical cycles. The distribution of 222 Rn and 223,224,226 Ra have complex spatial patterns along the Shark River Slough estuary (SRSE), Everglades, FL. High-resolution time-series measurements of 222 Rn activity, salinity, and water level were used to quantify processes affecting radon fluxes out of the mangrove forest over a tidal cycle. Based on field data, tidal pumping through an extensive network of crab burrows in the lower FCE provides the best explanation for the high radon and fluid fluxes. Burrows are irrigated during rising tides when radon and other dissolved constituents are released from the mangrove soil. Flushing efficiency of the burrows—defined as the tidal volume divided by the volume of burrows— estimated for the creek drainage area vary seasonally from 25 (wet season) to 100 % (dry season) in this study. The tidal pumping of the mangrove forest soil acts as a significant vector for exchange between the forest and the estuary. Processes that enhance exchange of O2 and other materials across the sediment-water interface could have a profound impact on the environmental response to larger scale processes such as sea level rise and climate change. Compounding the material budgets of the SRSE are additional inputs from groundwater from the Biscayne Aquifer, which were identified using radium isotopes. Quantification of the deep groundwater component is not obtainable, but isotopic data suggest a more prevalent signal in the dry season. These findings highlight the important role that both tidal- and seasonal-scale forcings play on groundwater movement in low-gradient hydrologic systems.

Florida↗

USGS2023

Relative effectiveness of a radionuclide (210Pb), surface elevation table (SET), and LiDAR at monitoring mangrove forest surface elevation change

Sea-level rise (SLR) is one of the greatest future threats to mangrove forests. Mangroves have kept up with or paced past SLR by maintaining their forest floor elevation relative to sea level through root growth, sedimentation, and peat development. Monitoring surface elevation change (SEC) or accretion rates allows us to understand mangrove response to SLR and prioritizes resilient ecosystems for conservation or vulnerable ecosystems for restoration. We compared three methods to measure SEC and accretion in mangrove forests: 210 Pb, surface elevation tables (SETs), and a terrestrial light detection and ranging system (compact biomass LiDAR—CBL). Lead-210 accretion rates were not significantly different than SET SEC rates and differences between the two methods (− 2 to 2 mm/year) were within the error of our measurements. Lead-210 only measures accretion in the upper meter of sediment and cannot capture deeper subsurface processes (e.g., subsidence, compaction) that SETs can. The lack of differences suggests the following: (1) surface processes in the active root zone are influencing forest floor elevation more than subsurface processes, (2) subsurface processes were not large enough to effect elevation, or (3) the SETs were not installed deep enough to capture subsurface processes. CBL SEC rates did not differ significantly from SET SEC rates. The larger spatial scale of the CBL scans resulted in significantly different SEC rates from some of the plots. This was due to the CBL measuring areas missed by the SET. The greater number of points measured by CBL (~ 30,000 vs 36) increased precision and lowered standard error. The traditional SET/rSET method is currently 3–10 × cheaper than the 210 Pb or CBL method, respectively, and can accurately track changes in forest floor elevation. Costs of the use of LiDAR are likely to decrease in the future with the advent of newer and more cost-effective technology.

Estuaries and Coasts↗

USGS2009

Conceptual hierarchical modeling to describe wetland plant community organization

Using multivariate analysis, we created a hierarchical modeling process that describes how differently-scaled environmental factors interact to affect wetland-scale plant community organization in a system of small, isolated wetlands on Mount Desert Island, Maine. We followed the procedure: 1) delineate wetland groups using cluster analysis, 2) identify differently scaled environmental gradients using non-metric multidimensional scaling, 3) order gradient hierarchical levels according to spatiotem-poral scale of fluctuation, and 4) assemble hierarchical model using group relationships with ordination axes and post-hoc tests of environmental differences. Using this process, we determined 1) large wetland size and poor surface water chemistry led to the development of shrub fen wetland vegetation, 2) Sphagnum and water chemistry differences affected fen vs. marsh / sedge meadows status within small wetlands, and 3) small-scale hydrologic differences explained transitions between forested vs. non-forested and marsh vs. sedge meadow vegetation. This hierarchical modeling process can help explain how upper level contextual processes constrain biotic community response to lower-level environmental changes. It creates models with more nuanced spatiotemporal complexity than classification and regression tree procedures. Using this process, wetland scientists will be able to generate more generalizable theories of plant community organization, and useful management models. ?? Society of Wetland Scientists 2009.

Wetlands↗

USGS2025

A review of abrupt permafrost thaw: Definitions, usage, and a proposed conceptual framework

Purpose of Review We review how ‘abrupt thaw’ has been used in published studies, compare these definitions to abrupt processes in other Earth science disciplines, and provide a definitive framework for how abrupt thaw should be used in the context of permafrost science. Recent Findings We address several aspects of permafrost systems necessary for abrupt thaw to occur and propose a framework for classifying permafrost processes as abrupt thaw in the future. Based on a literature review and our collective expertise, we propose that abrupt thaw refers to thaw processes that lead to a substantial persistent environmental change within a few decades. Abrupt thaw typically occurs in ice-rich permafrost but may be initiated in ice-poor permafrost by external factors such as hydrologic change (i.e., increased streamflow, soil moisture fluctuations, altered groundwater recharge) or wildfire. Summary Permafrost thaw alters greenhouse gas emissions, soil and vegetation properties, and hydrologic flow, threatening infrastructure and the cultures and livelihoods of northern communities. The term ‘abrupt thaw’ has emerged in scientific discourse over the past two decades to differentiate processes that rapidly impact large depths of permafrost, such as thermokarst, from more gradual, top-down thaw processes that impact centimeters of near-surface permafrost over years to decades. However, there has been no formal definition for abrupt thaw and its use in the scientific literature has varied considerably. Our standardized definition of abrupt thaw offers a path forward to better understand drivers and patterns of abrupt thaw and its consequences for global greenhouse gas budgets, impacts to infrastructure and land-use, and Arctic policy- and decision-making.

Current Climate Change Reports↗

USGS1987

Higher resolution satellite remote sensing and the impact on image mapping

Recent advances in spatial, spectral, and temporal resolution of civil land remote sensing satellite data are presenting new opportunities for image mapping applications. The U.S. Geological Survey's experimental satellite image mapping program is evolving toward larger scale image map products with increased information content as a result of improved image processing techniques and increased resolution. Thematic mapper data are being used to produce experimental image maps at 1:100,000 scale that meet established U.S. and European map accuracy standards. Availability of high quality, cloud-free, 30-meter ground resolution multispectral data from the Landsat thematic mapper sensor, along with 10-meter ground resolution panchromatic and 20-meter ground resolution multispectral data from the recently launched French SPOT satellite, present new cartographic and image processing challenges. The need to fully exploit these higher resolution data increases the complexity of processing the images into large-scale image maps. The removal of radiometric artifacts and noise prior to geometric correction can be accomplished by using a variety of image processing filters and transforms. Sensor modeling and image restoration techniques allow maximum retention of spatial and radiometric information. An optimum combination of spectral information and spatial resolution can be obtained by merging different sensor types. These processing techniques are discussed and examples are presented.

Acta Astronautica↗

USGS2013

Valley plugs, land use, and phytogeomorphic response: Chapter 14

Anthropogenic alteration of fluvial systems can disrupt functional processes that provide valuable ecosystem services. Channelization alters fluvial parameters and the connectivity of river channels to their floodplains which is critical for productivity, nutrient cycling, flood control, and biodiversity. The effects of channelization can be exacerbated by local geology and land-use activities, resulting in dramatic geomorphic readjustments including the formation of valley plugs. Considerable variation in the response of abiotic processes, including surface hydrology, subsurface hydrology, and sedimentation dynamics, to channelization and the formation of valley plugs. Altered abiotic processes associated with these geomorphic features and readjustments influence biotic processes including species composition, abundance, and successional processes. Considerable interest exists for restoring altered fluvial systems and their floodplains because of their social and ecological importance. Understanding abiotic and biotic responses of channelization and valley-plug formation within the context of the watershed is essential to successful restoration. This chapter focuses on the primary causes of valley-plug formation, resulting fluvial-geomorphic responses, vegetation responses, and restoration and research needs for these systems.

Book chapter↗

USGS2005

Dynamic modeling of Tampa Bay urban development using parallel computing

Urban land use and land cover has changed significantly in the environs of Tampa Bay, Florida, over the past 50 years. Extensive urbanization has created substantial change to the region's landscape and ecosystems. This paper uses a dynamic urban-growth model, SLEUTH, which applies six geospatial data themes (slope, land use, exclusion, urban extent, transportation, hillside), to study the process of urbanization and associated land use and land cover change in the Tampa Bay area. To reduce processing time and complete the modeling process within an acceptable period, the model is recoded and ported to a Beowulf cluster. The parallel-processing computer system accomplishes the massive amount of computation the modeling simulation requires. SLEUTH calibration process for the Tampa Bay urban growth simulation spends only 10 h CPU time. The model predicts future land use/cover change trends for Tampa Bay from 1992 to 2025. Urban extent is predicted to double in the Tampa Bay watershed between 1992 and 2025. Results show an upward trend of urbanization at the expense of a decline of 58% and 80% in agriculture and forested lands, respectively.

Computers & Geosciences↗

USGS2014

MTpy: A Python toolbox for magnetotellurics

We present the software package MTpy that allows handling, processing, and imaging of magnetotelluric (MT) data sets. Written in Python, the code is open source, containing sub-packages and modules for various tasks within the standard MT data processing and handling scheme. Besides the independent definition of classes and functions, MTpy provides wrappers and convenience scripts to call standard external data processing and modelling software. In its current state, modules and functions of MTpy work on raw and pre-processed MT data. However, opposite to providing a static compilation of software, we prefer to introduce MTpy as a flexible software toolbox, whose contents can be combined and utilised according to the respective needs of the user. Just as the overall functionality of a mechanical toolbox can be extended by adding new tools, MTpy is a flexible framework, which will be dynamically extended in the future. Furthermore, it can help to unify and extend existing codes and algorithms within the (academic) MT community. In this paper, we introduce the structure and concept of MTpy . Additionally, we show some examples from an everyday work-flow of MT data processing: the generation of standard EDI data files from raw electric ( E -) and magnetic flux density ( B -) field time series as input, the conversion into MiniSEED data format, as well as the generation of a graphical data representation in the form of a Phase Tensor pseudosection.

Computers & Geosciences↗

USGS2013

Zinc isotope and transition-element dynamics accompanying hydrozincite biomineralization in the Rio Naracauli, Sardinia, Italy

The Rio Naracauli in SW Sardinia drains part of the Ingurtosu Zn–Pb mining district, and contains extreme concentrations of dissolved Zn at near-neutral pH. In the upper reaches of the stream, pH, alkalinity and Zn concentrations are such that hydrozincite [Zn 5 (CO 3 ) 2 (OH) 6 ] precipitates in a biologically mediated process facilitated by a microalga ( Chlorella sp.) and a cyanobacterium ( Scytonema sp.). Values of δ 66 Zn in water and solid samples ranged from − 0.35&permil; to + 0.5&permil; relative to the JMC 3-0749-Lyon standard, and closely follow a mass-dependent fractionation line. Two composite samples of sphalerite, the primary ore mineral in the Ingurtosu deposits, had an average δ 66 Zn of + 0.15&permil;, similar to sphalerite measured elsewhere in hydrothermal mineral deposits. Zinc isotope measurements of the stream water and the hydrozincite forming in the stream show a consistent preference for the heavy isotope, 66 Zn, in the hydrozincite relative to 64 Zn. Synthetic hydrozincites produced without added bacteria have δ 66 Zn identical to the dissolved Zn, thus suggesting a biologically mediated mineralization process in Rio Naracauli. The average fractionation, Δ hdz-water , is 0.35&permil;, the magnitude of which is consistent with other studies, and suggests an extracellular mechanism of the biomineralization process. Zinc concentration and dissolved δ 66 Zn steadily decrease in the reach of the stream where the biomineralization occurs. The biomineralization process also leads to the sequestration of Pb, Cu and Ni in the hydrozincite lattice, and the coeval precipitation of an amorphous CdCO 3 solid, prompting the suggestion that if optimized, the biomineralization process might represent a feasible passive remediation strategy for streams with high Zn and other metals, and with near-neutral pH.

Sardinia↗

USGS2021

Drivers of extreme water levels in a large, urban, high-energy coastal estuary – A case study of the San Francisco Bay

Reliable and long-term hindcast data of water levels are essential in quantifying return period and values of extreme water levels. In order to inform design decisions on a local flood control district level, process-based numerical modeling has proven an essential tool to provide the needed temporal and spatial coverage for different extreme value analysis methods. To determine the importance of different physical processes to the extreme water levels we developed a process-based numerical model (Delft3D Flexible Mesh) and applied it to simulate a large, urban, high-energy coastal estuary (the San Francisco Bay). The unstructured grid with 1D/2DH model elements, allows for efficient model simulations and therefore it was possible to simulate over 70 years between 1950 and 2019. Results show significant skill in reproducing observations for the entire modeled time period with an average root-mean-square error of 8.0 cm. A process-based modeling approach allows for the explicit in- and exclusion of different physical processes to quantify their importance to the extremes. For the 100-year still water level (SWL), tide (70%) and non-tidal residual (NTR) (25%) explain the majority of the simulated high water levels in the Bay relative to Mean Higher High Water (MHHW). However, closer to the Delta, local fluvial inflow increases in importance. For longer return periods, the importance of tide decreases and the importance of remote NTRs and fluvial inflow increases.

California↗