A physically-based surface-subsurface hydrologic model for clear creek watershed

Devastating flooding caused by heavy rains brought economic, social, and environmental impacts in many watersheds across the state of Iowa, USA. From 2011–2013, Iowa suffered eight Presidential Disaster Declarations, encompassing more than 70% of the state. The Clear Creek Watershed covers about 270 km2 with three headwater streams converging in Iowa Township. The watershed comprises 60% of agriculture in the form of corn-soybean rotations, 23% pasture and other grasslands, 10% forest, and 7% urban areas. In this study, a fully coupled distributed surfacesubsurface model, PIHM, was used to predict the hydrologic dynamic response of the Clear Creek Watershed over an annual period. The numerical model takes into account interception, through fall, infiltration, recharge, evapotranspiration, and infiltration, enabling discharge through the surface or subsurface into downstream water bodies or aquifer flows. Evapotranspiration is a function of water content in the soil and vegetation characteristics. The model considers the special distribution of land use and soil type. Overland flow is modeled using the diffusive wave approximation of 2D St. Venant equations. River routing is computed using 1D St. Venant equations. Water content in the soil is modeled using Richard’s equation. Water movement in the unsaturated zone is assumed to be vertical and the saturated groundwater region is modeled using the 2D Dupuit approximation. PIHM uses a finite-volume formulation for solving the system of coupled equations. The resulting ordinary differential equation system is solved with the solver SUNDIALS. The model was calibrated and validated with monitoring data. Model details, convergence challenges and model calibration in the Clear Creek Watershed will be presented and discussed.Publicado en: Mecánica Computacional vol. XXXV, no. 19Facultad de Ingenierí

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Concurrent Sessions D: Downstream Migrant Surface Collectors-What Works and What Doesn\u27t Work - Numerical Study for a Downstream Fish Collector at Cowlitz Falls Dam

Tacoma Power The Cowlitz River hosts numerous fish species including coho and Chinook salmon, steelhead and cutthroat trout. Hydroelectric dams in the Cowlitz River have significantly contributed to reduced natural salmonid populations. A surface collector built in 1996 at the Cowlitz Falls Dam aimed to help with fish restoration. Through relicensing of their hydroelectric projects on the Cowlitz Falls River, Tacoma Power had agreed to further improve fish passage at Cowlitz Falls Dam with a survival objective of 95%. A numerical study was undertaken to identify a number of different fish collection alternatives for Cowlitz Falls Dam. Forty seven simulations were completed to assess the effect of a bank-oriented surface collector on the forebay hydraulics. Different collector entrances, river flow rates and diffusion strategies were evaluated. The influence of a Behavioral Guidance Structure (BGS) and a Guide Net on the flow field were also investigated. This paper presents details of the model development and validation with field data. Forebay flow patterns for different collector designs will be presented and discussed

Concurrent Sessions D: Downstream Migrant Surface Collectors-What Works and What Doesn\u27t Work - Evaluation of Possible Fish Injury in a Spillway Retrofitted with Deflectors

Spill is considered one of the safest fish passage strategies. However, fish traveling over a spillway can be exposed to elevated stresses due to deceleration, strain rate, or pressure changes during their impact with the tailrace. Spillway deflectors, installed to minimize gas super saturation, deflect water horizontally instituting an additional momentum change that might further increase stress experience by passing fish. In addition, since deflectors completely change the flow pattern in the tailrace, possible fish migration delay is also of concern. In this study, a CFD model was developed to evaluate the effect of spillway deflectors on fish injury and tailrace retention time. Free surface simulations were performed to obtain the flow field in the spillway face and tailrace. A particle tracking technique was employed and the history of acceleration, strain rate and pressure changes were calculated. Numerical results were correlated with biological data found in the literature to obtain the probability of fish injury. This paper presents details of the numerical model and discusses results obtained in the Hells Canyon Dam spillway for four operational conditions, with and without deflectors. According to the model, the inclusion of deflectors in a 7Q10 flow increases the percent of fish with minor injuries from approximately 5% to 10%. The percent of major injury increases from 1% to 3%. Residence time of particles released from the spillway decreases with spillway flowrate. The residence time of particles from the powerhouse is affected by powerhouse entrainment into the spillway region. A small level of entrainment increases the residence time since particles are pulled to a deep low velocity region in the stilling basin. As the lateral flow increases, some particles from the powerhouse join the high velocity surface jets decreasing their residence time. According to the model, deflectors decrease significantly the residence time in the tailrace

Session B8: An Integrative Strategy for Understanding Fish Behavior at Hydropower Forebays

Abstract: In the last decade, CFD with agent-based models has emerged as a useful methodology to design and evaluate fishway efficiency. However, despite using sophisticated modeling approaches, actual fishway performance varies widely. For certain species, expensive operational or structural changes of the bypasses are needed after biological information became available. Understanding the behavior of targeted fish species is therefore essential in locating and designing fishway entrances. This study presents a methodology that integrates biology and engineering to link fish behavior to hydrodynamics using an inverse problem approach. Chinook and steelhead swim paths were measured in the forebay of Rocky Reach and Priest Rapids dams. 3D CFD simulations of hydropower forebays were performed to model and fully understand the hydraulics of the system. Fish thrust magnitude and orientation, calculated by combining measured and modeled data at every measured fish location, were used to characterize fish swimming behavior at the forebay. Probabilistic distributions for fish thrust magnitude and direction were generated to capture the inherent stochasticity of animal behavior and will be presented and discussed

Delayed colorectal cancer care during covid-19 pandemic (decor-19). Global perspective from an international survey

Background The widespread nature of coronavirus disease 2019 (COVID-19) has been unprecedented. We sought to analyze its global impact with a survey on colorectal cancer (CRC) care during the pandemic. Methods The impact of COVID-19 on preoperative assessment, elective surgery, and postoperative management of CRC patients was explored by a 35-item survey, which was distributed worldwide to members of surgical societies with an interest in CRC care. Respondents were divided into two comparator groups: 1) ‘delay’ group: CRC care affected by the pandemic; 2) ‘no delay’ group: unaltered CRC practice. Results A total of 1,051 respondents from 84 countries completed the survey. No substantial differences in demographics were found between the ‘delay’ (745, 70.9%) and ‘no delay’ (306, 29.1%) groups. Suspension of multidisciplinary team meetings, staff members quarantined or relocated to COVID-19 units, units fully dedicated to COVID-19 care, personal protective equipment not readily available were factors significantly associated to delays in endoscopy, radiology, surgery, histopathology and prolonged chemoradiation therapy-to-surgery intervals. In the ‘delay’ group, 48.9% of respondents reported a change in the initial surgical plan and 26.3% reported a shift from elective to urgent operations. Recovery of CRC care was associated with the status of the outbreak. Practicing in COVID-free units, no change in operative slots and staff members not relocated to COVID-19 units were statistically associated with unaltered CRC care in the ‘no delay’ group, while the geographical distribution was not. Conclusions Global changes in diagnostic and therapeutic CRC practices were evident. Changes were associated with differences in health-care delivery systems, hospital’s preparedness, resources availability, and local COVID-19 prevalence rather than geographical factors. Strategic planning is required to optimize CRC care