Flow Management Decisions Research Articles

Channel restoration in urbanized systems: Guiding design using ecological flow targets and future management scenarios

AbstractRestoration of urban rivers must simultaneously design for ecological habitat while accounting for altered flow regimes associated with urban runoff, flood protection, and industrial/wastewater discharge. The goal of this study was to use ecological flow targets to guide channel restoration of the Los Angeles (LA) River across potential future flow regimes. Using a one‐dimensional hydraulic model, we simulated a range of channel cross section configurations subject to different flow management decisions (wastewater reuse, low‐flow [LF] treatment, and baseflow augmentation). Hydraulic results were assessed relative to ecohydraulic targets for desirable aquatic species in the LA River (willow, steelhead trout, and Santa Ana sucker). Results suggest that, along the mainstem of the LA River, restoration designs that include narrow LF channels may support Santa Ana sucker habitat and steelhead migration if management decisions decrease instream flows (e.g., by reusing treated wastewater). However, the same channel design and management decisions may not provide conditions needed to propagate floodplain vegetation such as willows. In tributary reaches, flows are too low to support habitat conditions for Santa Ana sucker or steelhead but may be able to support riparian habitat if a soft‐bottom LF channel and active floodplain are present. In general, results illustrate the trade‐offs between water management goals and habitat requirements for target species.

Climate change and local anthropogenic activities have altered river flow regimes across Canterbury, New Zealand

River flow regimes influence ecologic, cultural, social, aesthetic, and economic values. Detecting changes in river flows and attributing their causes is important but challenging due to the combined influence of climate and relevant local activities, and the lack of data on water abstraction, drainage modification or land use management. This study assessed the degree to which trends in river flows could be attributed to changes in climate versus local anthropogenic activities across Canterbury, Aotearoa New Zealand. Trends were assessed for a period that started immediately after a change in regulatory regime in 1991 and ended in 2020, that coincided with increases in water abstraction and changes in water management practices. Trends in observed summer conditions indicated that rainfall was stable, temperature increased, and flows decreased for many sites during the assessed period. Models representing flow as a function of rainfall and temperature were trained and tested using cross-validation for an earlier baseline period. Predictions for the 1991–2020 period made with the models were used to account for the effect of change in climate. The difference between predicted and observed flows were attributed to changes in local activities. Decreases in summer flows were partially associated with changes in climate, but changes in summer flows in several catchments were also associated with local activities. The findings indicate changes to both climate and local activities have combined to alter flow regimes, suggesting that hydrological impacts of local activities should be considered alongside climate change when making river flow management decisions.

Predicting and planning airport acceptance rates in metroplex systems for improved traffic flow management decision support

Efficient planning of Airport Acceptance Rates (AARs) is key for the overall efficiency of Traffic Management Initiatives such as Ground Delay Programs (GDPs). Yet, precisely estimating future flow rates is a challenge for traffic managers during daily operations as capacity depends on a number of factors/decisions with very dynamic and uncertain profiles. This paper presents a data-driven framework for AAR prediction and planning towards improved traffic flow management decision support. A unique feature of this framework is to account for operational interdependency aspects that exist in metroplex systems and affect throughput performance. Gaussian Process regression is used to create an airport capacity prediction model capable of translating weather and metroplex configuration forecasts into probabilistic arrival capacity forecasts for strategic time horizons. To process the capacity forecasts and assist the design of traffic flow management strategies, an optimization model for capacity allocation is developed. The proposed models are found to outperform currently used methods in predicting throughput performance at the New York airports. Moreover, when used to prescribe optimal AARs in GDPs, an overall delay reduction of up to 9.7% is achieved. The results also reveal that incorporating robustness in the design of the traffic flow management plan can contribute to decrease delay costs while increasing predictability.

A hybrid ARIMA-SVR approach for forecasting emergency patient flow

The goal of this study is to explore and evaluate the use of a hybrid ARIMA-SVR approach to forecast daily radiology emergency patient flow. Owing to the fact that emergency patient flow is highly uncertain and dynamic, the forecasting problem is regarded as a complicated task. As the emergency patient flow may have both linear and nonlinear patterns, this paper presents a hybrid ARIMA-SVR approach, which hybridizes autoregressive integrated moving average (ARIMA) model and support vector regression (SVR) model to predict emergency patient arrivals. The proposed model is applied to 4 years of daily emergency visits data in the radiology department of a large hospital to justify the performance of the hybrid model against single models. The MAPE, RMSE and MAE of the hybrid model are 7.02%, 19.20 and 14.97, respectively. Furthermore, the hybrid model achieves better prediction performance than its competitors because it can capture the linear and nonlinear patterns simultaneously. Experimental results indicate that the proposed hybrid ARIMA-SVR approach is a promising alternative for forecasting emergency patient flow. These findings are beneficial for efficient patient flow management and scheduling decisions optimization.

Science to support the management of riverine flows

Abstract The last two decades has seen introduction or reform of water legislation in many river basins of the world, and river managers are under increasing pressure to make effective and efficient flow management decisions. To support those decisions, the roles that freshwater scientists must fulfil are rapidly evolving, and now is a good time to ask: What roles must scientists fulfil to best support those decisions? What are the major barriers to seeing those roles fulfilled? How can those barriers be removed? We offer potential answers to these questions. To ensure our arguments are grounded within real policy and decision problems, they are framed within the context of Australia's Murray‐Darling Basin Plan—legislation to guide the management of environmental flows—and its associated Watering Strategy. These problems are not unique, so the challenges and solutions we identify have broader applicability to flow management. Indeed, many of the policy and decision problems we present are common to all ecosystem types, so our arguments will likely be applicable beyond freshwater ecosystems. We argue that scientists must fulfil four roles to support flows management: (1) Monitoring and evaluation of ecosystems to support scientifically defensible reporting of outcomes, and to reduce uncertainty through adaptive management. (2) Modelling to support spatial and temporal projections of ecosystem change under different flow scenarios, resulting in more effective management decisions; improved causal inference about flow effects; identification of threats to the efficacy of flow management; and scaling flow‐response dynamics to broader spatial extents. (3) Fundamental research, resulting in improved outcomes through the identification of non‐flow management interventions that work in synergy with environmental flows and improved understanding of the ecological limitations of current policy. (4) Decision science, leading to more defensible environmental flow decisions and more efficient use of resources. We identify key barriers specific to each role and offer possible remedies. We argue that a major impediment to seeing these roles fulfilled is the ad hoc nature of much of the current research effort. Investment in research must (1) be developed at the basin scale, to ensure science supports decision problems that span multiple scales; (2) be developed as a collaboration between all stakeholders to ensure that science investments remain aligned with decision problems; (3) recognise the need to build and maintain technical capacity within the four roles.

Selection of minimum indicators of hydrologic alteration of the Gorai river, Bangladesh using principal component analysis

The use of a few indicators of hydrologic alteration can minimize statistical redundancy which can lead to take effective environmental flow management decisions. The aim of the research is to select representative dominant indicators of hydrological alteration through reducing the dimensionality of multivariate data for the Gorai river, Bangladesh. The required mean daily discharge data (1976–2006) of the Gorai have been collected from the Bangladesh Water Development Board. The Range of Variability Approach and anomaly of the river flow show hydrologic alteration in recent years comparing with past. Principal component analysis (PCA) in Kendall and Pearson methods has been performed by the XLSTAT software (version 2.9). Depending on eigenvalues (>1.0), seven and six Principal components (PCs) are selected for Kendall and Pearson methods, respectively, for further analysis. Since the eco-flow metrics of eco-deficit of the river has poor correlation with the indicators of hydrologic alteration, the resultant loadings are subjected to the Kaiser–Meyer–Olkin (KMO) Measure of Sampling Adequacy (MSA) method which is classified into marvelous, meritorious, middling, mediocre, and miserable based on the PC loading values. Seven indicators have been found whose PC loadings are in marvelous class and are common for both Kendall and Pearson methods. These indicators, named March mean flow, 1-day minimum mean, 3-day minimum mean, 7-day minimum mean, 30-day minimum mean, 90-day minimum mean, and 30-day maximum mean flows, are the desired indicators of hydrologic alteration of the Gorai river.

The Bus Decision: A Case Study Employing Capital Budgeting And Creative Thinking

This paper presents a case whose setting is a regional university situated approximately twenty-five miles away from a community. The community is home to a significant number of the university’s faculty, staff, and students. The university is asked to provide a commuter bus to transport people to and from the community. The university, in turn, approaches the community municipal bus service asking if it (the municipal bus service) could provide the requested route. The case incorporates cash flow management decision making including: (1) identifying necessary information for the analysis, (2) identifying appropriate analytical tools for the analysis, and (3) performing the analysis. This case is appropriate for first year graduate students, as well as upper level undergraduate business students. The case is designed to be taught in one class hour and is expected to require two hours of outside preparation by the students.

A simulation tool for managing environmental flows in regulated rivers

Environmental flows provide river flow regimes to restore and conserve aquatic ecosystems, creating considerably different demands compared to conventional water extraction. With increasing incorporation of environmental flows in water planning worldwide, governments require decision support tools to manage these flows in regulated rivers. We developed the Environmental Water Allocation Simulator with Hydrology (eWASH), a fast, flexible and user-friendly scenario-based hydrological modelling tool, supporting environmental flow management decisions for single- or multi-reservoir systems. Environmental flow demands and management rules are easily specified via the graphical user interface, and batch processing functions aid in uncertainty assessment. eWASH modelled main processes of complex regulated rivers and the tool is widely applicable. We calibrated eWASH for the Gwydir and Macquarie Rivers of Australia's Murray–Darling Basin. Modelled monthly environmental flow allocations exhibited Nash–Sutcliffe efficiencies of 0.55 for the Gwydir and 0.72 for the Macquarie catchments respectively when validated.

A Social‐Ecological Framework to Integrate Multiple Objectives for Environmental Flows Management

Abstract“Environmental flows” is a research discipline that emphasizes freshwater allocation in rivers to sustain desired ecological conditions and human well‐being. The basis for environmental flow requirements has traditionally relied on hydrological and ecological data. Contemporary methods focus on detailed hydro‐ecological relationships within river ecosystems; however, there is currently no structured approach to systematically incorporate socially relevant data into the environmental flows discipline. To address this limitation we developed a flexible framework that applies a social‐ecological systems approach to account for multiple flow‐related objectives that reflect both biophysical sustainability and societal preferences. First, we conceptualize the freshwater social‐ecological system as a hierarchy of human and environmental domains. Then, we recommend stepwise procedures to assess flow‐related vulnerabilities of important system attributes, address their feedbacks, and translate these assessments to a common classification for comparative analyses that guide holistic flow management decisions.

Determining Stochastic Airspace Capacity for Air Traffic Flow Management

Deterministic air traffic flow management (TFM) decisions—the state of the art in terms of implementation—often result in unused airspace capacity. This is because the inherent uncertainties in weather predictions make it difficult to determine the number of aircraft that can be safely accommodated in a region of airspace during a given period. On the other hand, stochastic TFM algorithms are not amenable to implementation in practice due to the lack of valid stochastic mappings between weather forecasts and airspace capacity to serve as inputs to these algorithms. To fill this gap, we develop a fast simulation-based methodology to determine the stochastic capacity of a region of airspace using integrated weather-traffic models. The developed methodology consists of combining ensemble weather forecast information with an air traffic control algorithm to generate capacity maps over time. We demonstrate the overall methodology through a novel conflict resolution procedure and a simple weather scenario generation tool, and also discuss the potential use of ensemble weather forecasts. An operational study based on comparisons of the generated capacity distributions with observed impacts of weather events on air traffic is also presented.

Fish habitat availability simulations using different morphological variables

Fish habitat availability simulations using different morphological variables Fish habitat modelling results are strongly influenced by velocity and depth patterns as well as by morphological parameters of the riverbed (i.e., substrate and refuge cover). Studies regarding the use of substrate in habitat modelling are well represented in the literature, whereas the use of cover in such models is commonly neglected because it is difficult to quantify the refuges or the instream areas where fish can hide from predators. However, there is clear evidence that fish habitat use and preferences are associated with refuge cover. Ignoring this variable can lead to incorrect restoration and flow management decisions based on misleading results. To avoid this, river restoration goals should only be set with reference to habitat conditions found at undisturbed sites rather than with the aim of improving habitat heterogeneity. The aim of this study is to compare the habitat availability for two cyprinid fishes, the Southwestern arched-mouth nase (Iberochondrostoma almacai) and the Arade chub (Squalius aradensis), at undisturbed (i.e., near-natural state) and disturbed sites (i.e., sites impacted by agricultural activities that have led to nutrient enrichment, destruction of riparian woodlands, straightening of the river channel and water abstraction). This is done by alternately considering substrate or refuge cover in a weighted usable area (WUA) determination to understand the interactive effects of these morphological variables as well as their influence on habitat availability. Different outcomes were generated by the use of refuge cover and substrate in habitat simulation. The results underline the importance of considering refuge cover in habitat models and also point to the need to take into account minimally disturbed or undisturbed sites within the same river upon developing future management actions.

Evaluation of an Integrated Traffic Flow Management Decision Making Approach

An integrated traffic flow management decision-making approach that sequentially schedules and reroutes flights subject to actual and forecast weather induced airspace capacity constraints is presented, and used to conduct 80 fast-time simulation experiments. These experiments considered variations in the severity and location of en route convective weather, and the traffic flow management strategies implemented to mitigate these weather impacts. Strategic flight scheduling, in which pre-departure and airborne delays were assigned to individual flights, was found to be effective at alleviating capacity constraints in sectors and at airports. However, tactical rerouting was found to be more effective than flight scheduling at avoiding en route weather hazards when the scheduling algorithms used weather impacted sector capacities as a proxy for weather location. In general, the distribution of the delays amongst the users was found to be most equitable when scheduling flights using a heuristic scheduling algorithm, such as ration-by-schedule. On the other hand, equity decreased by 77% when using a scheduling algorithm that took into account the number of seats aboard each flight. Interestingly, traffic flow management solutions that included scheduling and rerouting increased the equity of the solutions by 9% to 18% over comparable solutions that involved flight scheduling alone. Finally, the modeled results were compared with actual levels of delay, sector congestion and the number of weather incursions under three historical convective weather scenarios. The agreement between the modeled and actual results was found to be strongly dependent on the weather scenario and the number of constraints that were binding in the scheduling algorithm.

Development of representative indicators of hydrologic alteration

summary In an ideal world, a few overall indicators of hydrologic alteration would adequately describe the degree of hydrologic alteration caused by various forms of river regulation. Currently over 170 hydrologic indicators have been developed to describe different components of flow regimes, including the widely used Indicators of Hydrologic Alteration (IHA) that characterize the impact of river regulation on flow regimes in environmental flow studies. Many of these IHA indicators are intercorrelated, resulting in considerable information redundancy, which could lead to ineffective environmental flow management decisions. The objective of this research is to develop a small set of independent and representative hydrologic indicators that can best characterize hydrologic alteration caused by reservoirs and other forms of river regulation. Two sets of pre- and post-dam streamflow records are used: (1) based on artificial simulations of a wide range of reservoir release rules and (2) streamflow records for 189 gaging stations throughout the United States. Principal component analysis was used to address the intercorrelation among the IHA parameters. Results revealed that the recently introduced metrics termed ecodeficit and ecosurplus can provide a good overall representation of the degree of alteration of a streamflow time series. Across both datasets, 32 individual IHA statistics and several potential generalized indices, three indices based on the ecodeficit and ecosurplus explained the most variability associated with the ensemble of 32 IHA statistics.

Interactive effects of cover and hydraulics on brown trout habitat selection patterns

AbstractHabitat modelling results are extremely sensitive to the habitat suitability criteria (HSC) used in the simulations. HSCs are usually expressed as univariate habitat suitability curves, although such univariate approach has been long questioned, since overlooking interactions between hydraulic variables may misrepresent the complexity of fish behaviour in habitat selection. It could lead to adopt erroneous flow management decisions based on misleading results. Furthermore, the interactive effects of hydraulic variables on habitat selection may be driven by the structural features of the channel, which determine cover availability. Therefore, we compared brown trout habitat selection patterns through multivariate resource selection functions (RSFs) in structurally contrasting rivers to unveil the interactive effects of hydraulics and cover elements and their consequences in univariate HSC results. Microhabitat preferences of young‐of‐the‐year (0+) trout were similar across fast and slow waters, meanwhile juvenile (1+) and adult (>1+) preferences significantly changed. RSFs for young‐of‐the‐year trout were consistent with univariate results and did not differ among water types. However, RSFs for older trout varied among water types and revealed complex interactions among hydraulic variables and between hydraulics and structural elements, which were not described accurately by univariate curves. Therefore, results suggest that interactions between water depth and current velocity have a significant effect on habitat selection patterns in juvenile and adult brown trout, this effect being controlled by cover availability. Copyright © 2008 John Wiley & Sons, Ltd.

Long‐term brown trout populations responses to flow manipulation

AbstractDespite the many habitat simulations that have been undertaken around the world, not enough biological monitoring has been performed following flow manipulations. It is difficult, however, to refine flow management decisions without a better understanding of the links between amounts, durations and seasonality of flow deliveries and population dynamics.Trout populations were monitored before and after flow alterations in five trout streams, involving 17 study sites over a 4‐ to 12‐year period, depending on the sites.A comparison of the trout populations observed to theoretical habitat/population models pointed up several helpful lessons. Various factors slow increases in population size, including the availability and quality of spawning grounds, the general connectivity of the bypass section (BPS) and severe spate events. In addition to these site‐dependent factors, hydrological dynamics may explain why it is so difficult to clearly identify relationships between habitat availability and real fish stocks. Moreover, opportunities to observe population changes are improved when the pre‐enhancement instream flow value is very low, and when there is a considerable difference between pre‐ and post‐enhancement values. A population dynamics model that incorporates different habitat limitations and demographic background can be a very precious tool to improve understanding of the different situations and to build scenarios of population recovery. Copyright © 2008 John Wiley & Sons, Ltd.

I See What You're Thinking: Using Cognitive Models to Represent Working Memory Usage for Traffic Flow Management Decision Support Prototypes

A unique method was developed for explicitly and quantitatively representing working memory in an NGOMSL model (Estes, 2001). Applying this method, MITRE CAASD evaluated alternative designs of a research prototype for TFM ((Air) Traffic Flow Management). The NGOMSL modeling made it possible to quantify the physical workload and working memory benefits of an interface which integrates multiple steps into one window and one thread of interaction, as compared to the prototype's original design. It was found that the integrated design places little burden on working memory, more readily provides information about the task, and allows for less interaction with the interface. This design is planned for use in future TFM research, and some aspects of the design are already planned to be incorporated into operational TFM software.

STREAM DISCHARGE PREDICTION VIA A GRID BASED SOIL WATER ROUTING WITH PADDY FIELDS1

ABSTRACT: A grid based daily hydrologic model for a watershed with paddy fields was developed to predict the stream discharge. ASCII formatted elevation, soil, and land use data supported by the GRASS Geographic Information System are used to generate distributed results such as surface runoff and subsurface flow, soil water content, and evapotranspiration. The model uses a single flow path algorithm and simulates a water balance at each grid element. A linear reservoir assumption was used to predict subsurface runoff components. The model was applied to a 75.6 km2 watershed located in the middle of South Korea, and observed stream flow hydrographs from 1995 and 1996 were compared to model predictions. The stream flow predictions of 1995 and 1996 generally agreed with the observed flow, resulting in a Nash‐Sutcliffe efficiency R2 of 0.60 and 0.62, respectively. The hydraulic conductivity for percolating water through the saturated layer affected baseflow generation. The levee height of the paddy influenced the time and magnitude of the surface runoff, depending on irrigation management. The model will be used for making low flow management decisions by evaluating the role of each land use to stream flow, especially in case of paddy decrease by gradual urbanization of a watershed.

Predictive Models for Air Traffic Arrival Flows at Capacity-Constrained Airports

Traffic flow management (TFM) decision support relies heavily on forecasting of future air traffic demand. Flow managers need to anticipate situations and intervene where appropriate in a proactive rather than reactive mode. The accuracy of the prediction function is of critical importance. The prediction function is accomplished by means of a model, a representation of salient features of the real world. This paper investigates and compares some predictive models. No attempt is made to find or build the ultimate, best predictive model; rather the aim is to explore a framework for comparing models and metrics.The comparison of predictive models of arrival flows was performed by comparing the model currently used by flow managers with several linear regression models. Not knowing in advance what measure of predictive accuracy was best, we selected seven metrics for comparison. Since TFM manages air traffic flows as opposed to individual flights, these metrics generally are oriented toward aggregates of flights. For the comparison, 42 test data sets of flights subject to departure-delay-type flow management for 14 major arrival airports around the country during 1992-1993 were used. An historical database of about 15,000 flights was used for the model building.The selection of best model was not straightforward, since other independent variables, namely performance metric and arrival airport, may also explain differences in predictive accuracy. An analysis of variance (ANOVA) model with the following form was therefore employed to examine the significance of effects:predictive accuracy = f(predictive model, performance metric, arrival airport)The ANOVA model is explicitly a linear function of the (categorical) independent variables. Both main effects and interaction effects were examined.

Seasonal and Diel Passage of Juvenile Salmonids at John Day Dam on the Columbia River

-This paper documents the seasonal and diel movements of seaward-migrating juvenile Pacific salmonids Oncorhynchus spp. passing John Day Dam on the Columbia River. During the 1987–1989 and 1991–1993 seasons, the 10, 50, and 90% passage dates each fell within a 2-week period for yearling chinook salmon O. tshawytscha, steelhead O. mykiss, coho salmon O. kisutch, and sockeye salmon O. nerka. For subyearling chinook salmon, the 10 and 90% passage dates varied by as much as 1 month, although the median passage dates occurred within a 10-d period. The percentage of fish that passed at night (2200–0600 hours) averaged 80.7% for yearling chinook salmon, 75.7% for subyearling chinook salmon, 77.9% for steelhead, 88.6% for coho salmon, and 78.3% for sockeye salmon. Information concerning the hourly and seasonal movements of juvenile salmonids through hydroelectric dams are essential in making wise fisheries resource and river flow management decisions.

Sensitivity of a salmon population model to alternative formulations and initial conditions

Salmon populations in many Pacific coast rivers are in serious decline and in danger of becoming threatened or endangered. A fish population model ( salmod) that tracks fall chinook salmon has been developed for the Trinity River, California. The model considers the principal environmental factors influencing movement and mortality of young-of-the-year salmon from the time of spawning and egg deposition until they leave freshwater rivers as juveniles. Numbers of salmon produced by alternative managed flow regimes can be estimated using salmod. This paper explores the consequences of alternative model construction and formulation choices on model behavior, and the impact of the number of spawners returning from the ocean on development of a robust flow management decision. Results show that salmod is responsive to the user's choice of spawner nesting behavior (superimposition), but relatively insensitive to spatial scale describing fish rearing habitat quality. The choice of a suitable managed flow regime is sensitive to the number of adult fish returning to spawn and even more so to their distribution throughout the study area at time of spawning. It would be possible to tailor an adaptive annual flow regime based on monitoring of spawner numbers and their distribution.