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Lisa V. Lucas

Publications and source records attributed to Lisa V. Lucas.

15 recordsLinked to original sources
USGS2026

Fifty years of riverine harmful algal bloom modeling: A global synthesis of approaches, challenges, and opportunities

This systematic literature review critically examines 162 articles on harmful algal bloom (HAB) modeling in riverine systems to uncover persistent gaps, redefine critical challenges, and propose trackable opportunities to advance future modeling efforts. Articles largely focused on site-specific applications (93%) across more than 80 rivers worldwide. Most modeled systems were large, eutrophic rivers with flow modifications or obstructions. Geographic clustering of modeled systems was pronounced, with South Korea accounting for 26% of articles, followed by Europe (25%), United States (21%), and China (12%). Modeling approaches were led by process-based models (59%), though use of data-driven models (37%) increased over time, reflecting advances in computing and monitoring technology. Modeling endpoints varied widely across the articles with many focused on gross measures of algal abundance and fewer representing more refined endpoints like algal toxins or community composition. Furthermore, inconsistent units and taxonomic resolution hindered comparability between models. Datasets used for model development and calibration typically spanned 5 years, with weekly to monthly sampling at 1–10 sites, though durations and site counts were positively skewed. Quantitative metrics of model skill were often absent and included a diverse set of metrics when reported. Across all models, nutrients, light availability, streamflow, algal physiological processes, and water temperature emerged as key predictors, though algal processes were rarely incorporated in data-driven models. Scenario analyses primarily were conducted with process-based models and addressed flow management, whereas forecasting applications were less common and typically used data-driven models. After almost 50 years of riverine HAB modeling, persistent challenges include underrepresentation of benthic habitats, neglect of side-channel and backwater influences, insufficient documentation of river features, and weak linkages between modeled endpoints and potential harms. Addressing these gaps through reporting of contextual information, models from other aquatic settings, benchmark datasets, and community-driven tools could advance riverine HAB modeling towards increased transferability and ultimately operational forecasts.

Water Research↗
USGS2025

Gaps in water quality modeling of hydrologic systems

This review assesses gaps in water quality modeling, emphasizing opportunities to improve next-generation models that are essential for managing water quality and are integral to meeting goals of scientific and management agencies. In particular, this paper identifies gaps in water quality modeling capabilities that, if addressed, could support assessments, projections, and evaluations of management alternatives to support ecosystem health and human beneficial use of water resources. It covers surface water and groundwater quality modeling, dealing with a broad suite of physical, biogeochemical, and anthropogenic drivers. Modeling capabilities for six constituents (or constituent categories) are explored: water temperature, salinity, nutrients, sediment, geogenic constituents, and contaminants of emerging concern. Each constituent was followed through the coupled atmospheric-hydrologic-human system, with prominent modeling gaps described for a diverse array of relevant inputs, processes, and human activities. Commonly identified modeling gaps primarily fall under three types: (1) model gaps, (2) data gaps, and (3) process understanding gaps. In addition to potential solutions for addressing specific individual modeling limitations, some broad approaches (e.g., enhanced data collection and compilation, machine learning, reduced-complexity modeling) are discussed as ways forward for tackling multiple gaps. This gap analysis establishes a framework of diverse approaches that may support improved process representation, scale, and accuracy of models for a wide range of water quality issues.

Water↗
USGS2025

Ranking river basins for stream temperature research and monitoring in the contiguous United States

There is a need to prioritize research and data collection in river basins by integrating information from environmental, ecological, and socioeconomic datasets to maintain acceptable water quality for human uses and ecosystem health. Multiple anthropogenic and natural stressors are responsible for driving changes in stream temperatures that can alter ecosystems and degrade water quality. These stressors are variable spatially and temporally, which can be challenging for prioritizing monitoring and research. In this study, an evaluation of variables related to stream temperature was performed for 163 candidate basins of the contiguous United States to highlight potential focal areas. Thirty variables were combined in six components: anthropogenic forcing, natural forcing, climate change, ecological sensitivity, socioeconomic sensitivity, and data availability. The components were incorporated into three themes: vulnerability of streams to thermal change, vulnerability of ecosystems, and vulnerability of communities. By evaluating each theme separately, patterns of vulnerability and potential resiliency were identified as well as consistency in ranks within the themes. For example, results of the national scale ranking indicated the Southern California Coastal basin (within California-Nevada region) was the highest-ranking priority in vulnerability of streams to thermal change and vulnerability of ecosystems. The analysis also identified vulnerable basins with gaps in monitoring. For example, the Missouri-Oahe basin (within the Northern High Plains region) was the highest-ranking priority for vulnerable communities with limitations in data availability. The ranking approach provides insight into basins that are resilient and are ideal candidates for monitoring and research.

Journal of Hydrology↗
USGS2025

A systematic literature review of forecasting and predictive models of harmful algal blooms in flowing waters

Occurrences of harmful algal blooms (HABs) in rivers challenge the belief that rivers are not susceptible to HABs because of their short residence times and fluctuating hydrology. Here we present a systematic literature review of predictive and forecasting models for HABs in flowing waters, including rivers, flowing in-stream reservoirs (e.g., run-of-river reservoirs and lock-and-dam systems) and tidal or estuarine systems with riverine processes. The review aimed to understand current and historical modeling approaches for predicting and forecasting river HABs, without restricting to specific taxa, such as cyanobacteria, or modeling endpoints. The review included 162 articles published over nearly 50 years, covering more than 80 rivers worldwide. Eutrophic, non-wadable rivers with in-stream obstruction were commonly modeled, though diverse environmental characteristics were reported. Most articles used algal biomass or chlorophyll as modeling endpoints, with a quarter using novel or unique endpoints. Algal toxins motivated model development in 23% of the articles, however just 5% used algal toxins as an endpoint. Only 6% of the articles modeled benthic HABs; the rest focused on pelagic HABs. There was no standard model used for modeling river HABs. Process-based models were more common (59%) than data-driven approaches (37%), with model formulations ranging from simple to complex, which contrasts with a lake-focused literature review of HAB models that found data-driven models were more common. Models in river settings shared similar input variables as those previously identified for lakes, such as water temperature, nutrients, and light availability. However, streamflow and other transport metrics took prominence in river models compared to lake models. Algal cell physiology (such as growth, predation, and motility) was routinely included as input data or as mathematical formulations in process-based models and these processes were frequently identified as an important predictor by the articles’ authors. Conversely, data-driven models rarely included these processes, instead using predictors related to environmental conditions, such as nutrients, water quality, water temperature, and streamflow. These important proxy predictors have apparent success with modeling overall algal biomass (irrespective of taxa) whereas other factors, such as those related to algal physiology and other biological processes, are likely responsible for more subtle shifts in community composition. These differences highlight the influence of data availability, especially for processes that are difficult, time-consuming, or expensive to measure, on model development and model outcomes, raising questions about the selection of modeling inputs and endpoints. Challenges to advancing river HAB modeling include the lack of site-specific model inputs representing key processes (e.g., photosynthetic parameters and predation rates), overlooked riverine environments like the benthos and side/back-channel areas, lack of information on environmental settings, and poorly reported model performance metrics. This review emphasizes opportunities for advancing river HAB modeling by learning from well-honed estuarine models, supporting current forecasting and operationalization efforts, and developing common datasets for river HAB model development and evaluation.

BioRxiv↗
USGS2024

The role of spring-neap phasing of intermittent lateral exchange in the ecosystem of a channel-shoal estuary

Lateral variability is a fundamental feature of channel-shoal estuaries, and exchanges between the channel and shoal can play an important role in the dynamics of the ecosystem in each region. This lateral exchange of biomass interacts with vertical structure and variability, particularly in the channel, to define algal biomass accumulation in the estuary. In this paper, we investigate how time-variable lateral exchange affects phytoplankton dynamics with a biophysical model that links two water columns via intermittent exchange. We find that time variability in the exchange influences biomass by increasing concentrations in the shoals and decreasing them in the channel when the time variability happens on a timescale greater than the timescales of biological processes, and the strength of the effect increases with the period of the intermittency. At timescales of variability comparable to the spring-neap cycle, however, the interplay between lateral exchange and the ecosystem response is complicated by the fortnightly development of stratification in the channel and the role that channel-shoal interaction plays in defining that stratification. As a result, for lateral exchange variability with periods of 7 and 14 days, the influence of the shoal ecosystem on the channel ecosystem is sensitive to the phasing of exchange relative to the spring-neap cycle, due to the fact that neap tide exchanges can create stratification events that are larger in magnitude and duration than would occur in the absence of lateral exchange, causing the channel to transition into net positive growth conditions. We conclude that lateral exchange influences the estuarine ecosystem both directly, through the exchange of biomass between shoals with net positive growth and adjoining channels and indirectly through its role in defining stratification events that allow the channel itself to have net positive growth.

Estuaries and Coasts↗
USGS2022

Simple relationships between residence time and annual nutrient retention, export, and loading for estuaries

Simple mathematical models are derived from mass balances for water and transported substance to provide insight into the relationships between import, export, transport, and internal removal for nonconservative substances in an estuary. Extending previous work, our models explicitly include water and substance inputs from the ocean and are expressed in terms of timescales (i.e., mean residence time and the timescale for net removal). Steady-state, timescale-based expressions for ratios of export to import, retention to import, and net export to loading, as well as for loading and annually averaged concentration, are provided. The net export : loading model explains the underlying mechanisms for a well-known empirical relationship between fractional net export and residence time derived by other authors. Although our simplified models are first-order approximations, the relative importance of physical and biochemical processes influencing export or retention of a substance can be assessed using mean residence time and the timescale for net removal. Assumptions employed in deriving the simplified models (e.g., well-mixed, dynamic steady state) may not be met for real estuaries. However, model application to Chesapeake Bay for 1985–2012 demonstrates that interannual variations in total nitrogen (TN) net export : loading can be evaluated, and annual nutrient loadings can be well estimated using numerically modeled time-varying mean residence time, observation-based mean concentration, freshwater inflow, and an appropriately estimated removal timescale. Our model shows that net fractional export of TN loading ranges from 0.3 to 0.5 over the 28-yr period. The models can be employed for other substances and water bodies if the underlying assumptions are applicable.

Limnology and Oceanography↗
USGS2021

Toward improved decision-support tools for Delta Smelt management actions

The Collaborative Science and Adaptive Management Program (CSAMP) has endorsed a goal of reversing the recent downward trajectory of the Delta Smelt population within 5-10 generations, with the long-term aim of establishing a self-sustaining population. An ambitious agenda of management actions is planned, and more management actions are being considered. This White Paper furthers one of the recommendations in the 2019 Delta Smelt Science Plan – the need to predict the potential ecological effects of taking a management action. Existing statistical models can be highly informative in assessing the response of Delta Smelt to changing system conditions and management actions. However, management actions can shift or alter conditions in ways that models based on analysis of historical data may not be able to represent, and short-term or localized effects may be missed with models designed to assess effects at the population level. Decision support tools (DSTs) are computer-based tools developed to assist decision-making, often combining computationally intensive analysis and spatial mapping of environmental relationships. DSTs can be used in planning processes that evaluate an array of actions, such as in Structured Decision Making (SDM), where DSTs are needed to compare among alternatives. DSTs can also be used to explore the potential effects of different approaches to implementing management actions. The goal of this White Paper is to identify plausible options for DSTs that could be developed for future use to evaluate management actions that seek to either reverse the decline of Delta Smelt or minimize or mitigate the effects of other water management actions. Different types of management actions lead to different needs for DSTs. This White Paper was developed using three types of actions currently being considered to enhance the Delta Smelt population: Supplementation with Hatchery Fish, Summer-Fall Habitat, and Food Enhancement actions. These three management actions target different parts of the estuary and different processes, with a variety of possible metrics to gauge performance. Three DSTs are proposed that collectively address management questions related to the management actions considered, with each requiring a slightly different set of processes to be included and producing an array of outputs at varying spatial and temporal scales: DST 1. Modeling Fish Movement, Survival, and Reproduction Across Their Range. This DST can address management questions that require information about Delta Smelt spatial distribution and movement. • DST 1 could be used to compare conditions with and without management actions in place, how the management action performs among different types of water years (with varied flow and associated abiotic conditions), and to assess relative change with different variations and strategies of the management actions. • DST 2. Changes in Habitat Conditions and Delta Smelt Response. This DST is intended to evaluate combinations of conditions that are considered to provide suitable habitat for Delta Smelt, and Delta Smelt response. Delta Smelt habitat is generally described as open water with low salinity (0 to 6), turbidity of at least 12 NTU, suitable temperature conditions, and sufficient food availability to support growth. • DST 3. Regional Effects of Food Subsidy. This DSTs seeks to evaluate effectiveness of food enhancement actions by providing information on responses of the immediate targets of the action (i.e., phytoplankton or zooplankton) and tracing those to projected growth responses of Delta Smelt. There is not a single DST that adequately addresses management questions relevant to all management actions, although there is some overlap in the management questions each of the three DSTs can address. For each of the DSTs a substantial foundation of models and approaches already exists and modeling has already been applied to several of the management actions described. However, a number of outstanding issues remain for further development of the proposed DSTs. These are summarized in this White Paper together with potential approaches that could be applied or tested. Some components for the DSTs are already available and thus development could be relatively easy. However, for several of the topics identified there are gaps in knowledge that currently limit formulation of model structure and process representations. This presents challenges to readily incorporate some needed mechanisms into the models. Eleven next steps, aligned with relevant DSTs, are outlined. The next steps vary in their complexity or technical ‘lift’ required. Many build on existing work, or methods and approaches that have already been developed or are underway, while others require additional thinking to establish a viable approach. Some interim utility for decisions could be gained during initial development of the DSTs with further features added over time. Development of a DST requires engagement of both managers and scientists. Identifying the outputs and resolution needed for management purposes early in development of any DST is essential for effective pursuit of next steps and suitable approaches to address challenges. Dialog between managers and technical experts also informs what process-based simulation can do, and what tradeoffs are acceptable to meet a given purpose. To further develop the DSTs outlined here for application in the estuary requires: - Engagement of a committed group of technical experts with appropriate expertise. - The development of a coordinated workplan including appropriate project management and tracking. - Dialog between potential users (i.e., managers and policy makers) and technical experts. - Resources to pursue DST development including personnel and computational resources. This White Paper demonstrates the potential for moving toward DSTs for a variety of management actions in support of Delta Smelt that include mechanistic representations of physical and biological processes. Through focused effort from technical experts, managers and policy makers, DSTs can be developed to provide quantitative predictions of management effects on the ecosystem, targeting the changes the management actions seek to achieve, how these effects compare to ambient conditions, and how the effects vary among water year types or with timing and location of actions. Importantly, solid foundations exist which can be leveraged, refined, and built upon to specifically inform current and future management decisions.

White Paper↗
USGS2020

Timescale methods for simplifying, understanding and modeling biophysical and water quality processes in coastal aquatic ecosystems: A review

In this article, we describe the use of diagnostic timescales as simple tools for illuminating how aquatic ecosystems work, with a focus on coastal systems such as estuaries, lagoons, tidal rivers, reefs, deltas, gulfs, and continental shelves. Intending this as a tutorial as well as a review, we discuss relevant fundamental concepts (e.g., Lagrangian and Eulerian perspectives and methods, parcels, particles, and tracers), and describe many of the most commonly used diagnostic timescales and definitions. Citing field-based, model-based, and simple algebraic methods, we describe how physical timescales (e.g., residence time, flushing time, age, transit time) and biogeochemical timescales (e.g., for growth, decay, uptake, turnover, or consumption) are estimated and implemented (sometimes together) to illuminate coupled physical-biogeochemical systems. Multiple application examples are then provided to demonstrate how timescales have proven useful in simplifying, understanding, and modeling complex coastal aquatic systems. We discuss timescales from the perspective of “holism”, the degree of process richness incorporated into them, and the value of clarity in defining timescales used and in describing how they were estimated. Our objective is to provide context, new applications and methodological ideas and, for those new to timescale methods, a starting place for implementing them in their own work.

Water↗
USGS2017

What determines water temperature dynamics in the San Francisco Bay-Delta system?

Water temperature is an important factor determining estuarine species habitat conditions. Water temperature is mainly governed by advection (e.g., from rivers) and atmospheric exchange processes varying strongly over time (day-night, seasonally) and the spatial domain. On a long time scale, climate change will impact water temperature in estuarine systems due to changes in river flow regimes, air temperature, and sea level rise. To determine which factors govern estuarine water temperature and its sensitivity to changes in its forcing, we developed a process-based numerical model (Delft3D Flexible Mesh) and applied it to a well-monitored estuarine system (the San Francisco Estuary) for validation. The process-based approach allows for detailed process description and a physics-based analysis of governing processes. The model was calibrated for water year 2011 and incorporated 3-D hydrodynamics, salinity intrusion, water temperature dynamics, and atmospheric coupling. Results show significant skill in reproducing temperature observations on daily, seasonal, and yearly time scales. In North San Francisco Bay, thermal stratification is present, enhanced by salinity stratification. The temperature of the upstream, fresh water Delta area is captured well in 2-D mode, although locally—on a small scale—vertical processes (e.g., stratification) may be important. The impact of upstream river temperature and discharge and atmospheric forcing on water temperatures differs throughout the Delta, possibly depending on dispersion and residence times. Our modeling effort provides a sound basis for future modeling studies including climate change impact on water temperature and associated ecological modeling, e.g., clam and fish habitat and phytoplankton dynamics.

California↗
USGS2012

Changing restoration rules: exotic bivalves interact with residence time and depth to control phytoplankton productivity

Non-native species are a prevalent ecosystem stressor that can interact with other stressors to confound resource management and restoration. We examine how interactions between physical habitat attributes and a particular category of non-native species (invasive bivalves) influence primary production in aquatic ecosystems. Using mathematical models, we show how intuitive relationships between phytoplankton productivity and controllable physical factors (water depth, hydraulic transport time) that hold in the absence of bivalves can be complicated—and even reversed—by rapid bivalve grazing. In light-limited environments without bivalves, shallow, hydrodynamically “slow” habitats should generally have greater phytoplankton biomass and productivity than deeper, “faster” habitats. But shallower, slower environments can be less productive than deeper, faster ones if benthic grazing is strong. Moreover, shallower and slower waters exhibit a particularly broad range of possible productivity outcomes that can depend on whether bivalves are present. Since it is difficult to predict the response of non-native bivalves to habitat restoration, outcomes for new shallow, slow environments can be highly uncertain. Habitat depth and transport time should therefore not be used as indicators of phytoplankton biomass and production where bivalve colonization is possible. This study provides for ecosystem management a particular example of a broad lesson: abiotic ecosystem stressors should be managed with explicit consideration of interactions with other major (including biotic) stressors. We discuss the applicability and management implications of our models and results for a range of aquatic system types, with a case study focused on the Sacramento-San Joaquin Delta (California, USA). Simple mathematical models like those used here can illuminate interactions between ecosystem stressors and provide process-based guidance for resource managers as they develop strategies to augment valued populations, restore habitats, and manipulate ecosystem functions.

Ecosphere↗
USGS2009

Why are diverse relationships observed between phytoplankton biomass and transport time?

Transport time scales such as flushing time and residence time are often used to explain variability in phytoplankton biomass. In many cases, empirical data are consistent with a positive phytoplankton‐transport time relationship (i.e., phytoplankton biomass increases as transport time increases). However, negative relationships, varying relationships, or no significant relationship may also be observed. We present a simple conceptual model, in both mathematical and graphical form, to help explain why phytoplankton may have a range of relationships with transport time, and we apply it to several real systems. The phytoplankton growth‐loss balance determines whether phytoplankton biomass increases with, decreases with, or is insensitive to transport time. If algal growth is faster than loss (e.g., grazing, sedimentation), then phytoplankton biomass increases with increasing transport time. If loss is faster than growth, phytoplankton biomass decreases with increasing transport time. If growth and loss are approximately balanced, then phytoplankton biomass is relatively insensitive to transport time. In analyses of several systems, portions of an individual system, or time periods, apparent insensitivity of phytoplankton biomass to changes in transport time could arise due to the superposition of cases with different phytoplankton‐transport time relationships. Thus, in order to understand or predict responses of phytoplankton biomass to changes in transport time, the relative rates of algal growth and loss must be known.

Limnology and Oceanography↗
USGS2007

Population density, biomass, and age-class structure of the invasive clam Corbicula fluminea in rivers of the lower San Joaquin River watershed, California

Corbicula fluminea is well known as an invasive filter-feeding freshwater bivalve with a variety of effects on ecosystem processes. However, C. fluminea has been relatively unstudied in the rivers of the western United States. In June 2003, we sampled C. fluminea at 16 sites in the San Joaquin River watershed of California, which was invaded by C. fluminea in the 1940s. Corbicula fluminea was common in 2 tributaries to the San Joaquin River, reaching densities of 200 clams · m −2 , but was rare in the San Joaquin River. Biomass followed a similar pattern. Clams of the same age were shorter in the San Joaquin River than in the tributaries. Distribution of clams was different in the 2 tributaries, but the causes of the difference are unknown. The low density and biomass of clams in the San Joaquin River was likely due to stressful habitat or to water quality, because food was abundant. The success of C. fluminea invasions and subsequent effects on trophic processes likely depends on multiple factors. As C. fluminea continues to expand its range around the world, questions regarding invasion success and effects on ecosystems will become important in a wide array of environmental settings.

California↗
USGS2002

A comment on the use of flushing time, residence time, and age as transport time scales

Applications of transport time scales are pervasive in biological, hydrologic, and geochemical studies yet these times scales are not consistently defined and applied with rigor in the literature. We compare three transport time scales (flushing time, age, and residence time) commonly used to measure the retention of water or scalar quantities transported with water. We identify the underlying assumptions associated with each time scale, describe procedures for computing these time scales in idealized cases, and identify pitfalls when real-world systems deviate from these idealizations. We then apply the time scale definitions to a shallow 378 ha tidal lake to illustrate how deviations between real water bodies and the idealized examples can result from: (1) non-steady flow; (2) spatial variability in bathymetry, circulation, and transport time scales; and (3) tides that introduce complexities not accounted for in the idealized cases. These examples illustrate that no single transport time scale is valid for all time periods, locations, and constituents, and no one time scale describes all transport processes. We encourage aquatic scientists to rigorously define the transport time scale when it is applied, identify the underlying assumptions in the application of that concept, and ask if those assumptions are valid in the application of that approach for computing transport time scales in real systems.

Limnology and Oceanography↗
USGS2002

Pulsey, patchy water quality in the delta: Implications for meaningful monitoring

Valuable water quality and biological datasets have been gathered in the Sacramento-San Joaquin Delta for decades, most notably by the Interagency Ecological Program’s Environmental Monitoring Program (EMP). These extensive data have provided a means of analyzing and detecting long-term trends in water quality and ecosystem function (Jassby and others 2002; Kimmerer and Orsi 1996; Orsi and Mecum 1996) and may shape future restoration actions in the region. EMP water quality data—as well as data generated by the San Francisco Estuary Institute’s (SFEI) Regional Monitoring Program (RMP) and research groups like our own—have often focused on single, monthly or seasonal samples taken at several discrete points in space. Although such discrete data often push the practical limits of our equipment and human resources, higher resolution monitoring approaches can reveal limitations (in some cases severe) of these more coarse sampling schemes.

Interagency Ecological Program Newsletter↗