Development and accuracy assessment of a 12-digit hydrologic unit code based real-time climate database for hydrologic models in the US

2020 ◽  
Vol 586 ◽  
pp. 124817
Author(s):  
Jungang Gao ◽  
Katrin Bieger ◽  
Michael J. White ◽  
Jeffrey G. Arnold
2018 ◽  
Vol 1 (2) ◽  
pp. 112-130
Author(s):  
Allen D. Roberts

AbstractThis study examined past, current, and projected landscape configuration (LC) impacts on streamflow within a 3,553 square kilometer (km2) Hydrologic Unit Code (HUC)-8 Rocky River (RR) watershed of the Charlotte, North Carolina metropolitan region (CMR). Utilizing a monthly model, Thornthwaite Water Balance (TWB) simulations incorporating LC (blended contagion (CON)-adjusted curve numbers (CNs)) derived from two previous (2001, 2006) and one current (2011) US scale land cover/land use (LC/LU) time snapshots outperformed a blended original (ORG) CN watershed model during the 15-year (180-month) period from January 1999 to December 2013. Findings were confirmed using evaluations from several statistically based, hydrologic model performance predictors. Five-year comparisons of the 2001 time snapshot with the 2006 time snapshot and 2011 time snapshot indicated the least underestimation/overestimation of measured streamflow occurred during the 2001 time snapshot. This period had the highest measured runoff and points towards LC influences on streamflow simulation being potentially more quantifiable during periods of greater watershed precipitation. Watershed LC/LU and climatic data were also projected to the 2030 time snapshot under five different scenarios. Streamflow was projected to be about 2.6% higher in volume than what was estimated for the current (2011) time snapshot using a blended CON-adjusted TWB model.


<em>Abstract</em>.—Native fish conservation areas (NFCAs) are watersheds where management emphasizes proactive conservation and restoration for long-term persistence of native fish assemblages while allowing for compatible uses. Native fish conservation areas are intended to complement traditional fisheries management approaches that are often reactive to population stressors and focused on single-species conservation efforts rather than complete assemblages. We identified potential NFCAs in the upper Snake River basin above Hells Canyon Dam using a process that ranked all subwatersheds (Hydrologic Unit Code 12) and used empirical data on distribution, abundance, and genetics for three native trout species (Bull Trout <em>Salvelinus confluentus</em>, Columbia River Redband Trout <em>Oncorhynchus mykiss gairdneri</em>, and Yellowstone Cutthroat Trout <em>O. clarkii bouvieri</em>, including the fine-spotted form) and both known occurrences and modeled potential distributions of native nongame fishes. Rankings also incorporated drainage network connectivity and land-protection status (e.g., national park, wilderness). Clusters of high-ranking subwatersheds were identified as potential NFCAs that were then classified according to the presence of nongame fishes identified as species of greatest conservation need in state wildlife action plans. The Pacific Creek and Goose Creek watersheds ranked high in the upper basin (above Shoshone Falls), and Little Jacks Creek and Squaw Creek ranked high in the lower basin. We then contrasted characteristics of a select few potential NFCAs, discuss the practical implementation and benefits of NFCAs for both fishes and other aquatic species in the upper Snake River basin, examined how the NFCA approach could enhance existing conservation partnerships, and discuss how designating select watersheds as NFCAs can create higher public awareness of the value of native fishes and other aquatic species and their habitats.


<i>Abstract.</i>—Fluvial threat assessments characterize the potential for fluvial habitat conditions to be degraded by differing types and intensities of anthropogenic activities occurring on the landscape, ultimately affecting stream biota. We present a threat assessment for fluvial habitats in Alaska based on six anthropogenic disturbance indices representing urbanization, agriculture/timber harvest, stream fragmentation, point-source pollution, infrastructure, and mines. These indices were combined to develop an overall index of contemporary threat of habitat alteration throughout Alaska using the 12-digit U.S. Geological Survey hydrologic unit code (HUC-12) framework (<i>n </i>= 13,997) and at a finer spatial resolution using local and network catchments for individual stream reaches within Southeast Alaska (<i>n </i>= 207,092). Overall, contemporary threat of habitat alteration indices showed that ~96% of fluvial habitats both statewide and for Southeast Alaska were at low or very low levels; however, anadromous fish habitats were under greater human pressure with nearly double the amount of moderately to severely disturbed habitats when compared to all fluvial habitats. We further evaluated potential future threats to fluvial habitats from mineral mining activities and climate change. More than 86% of existing mine claims statewide and 99% of claims in Southeast Alaska occur in areas of low and very low contemporary threat to fluvial habitats for anadromous fishes. Under climate change, July air temperatures are projected to increase ~1.9°C, on average, by mid-century within HUC-12s containing anadromous fish streams, indicating immense potential to warm streams with anadromous fishes within the state. This fluvial threat assessment demonstrates that overall threats from contemporary anthropogenic disturbance factors are generally low with localized areas of high intensity. However, future threats from mining and climate change have considerable potential to alter fluvial habitats for anadromous fishes in Alaska, particularly those currently unaltered by anthropogenic disturbances.


2017 ◽  
Vol 49 (3) ◽  
pp. 648-657 ◽  
Author(s):  
Jozsef Szilagyi

Abstract Continuous simulation of monthly evapotranspiration rates for 1979–2015 was performed by the latest, calibration-free version of the complementary relationship of evaporation over the conterminous United States. The results were compared to similar estimates of the WREVAP program and the North American Regional Reanalysis (NARR) project. Validation of the three methods was performed by the Parameter-Elevation Regressions on Independent Slopes Model precipitation and Hydrologic Unit Code level-6 runoff data. The present method outperforms the WREVAP and NARR estimates with a root-mean-square error (RMSE) of 89 mm yr−1, an R2 value of 0.87, an absolute bias (σ) of −5 mm yr−1, and slope (m) and intercept (c) values of 0.97 and 22 mm yr−1, respectively, for the best-fit line, in comparison to similar values (RMSE = 161 mm yr−1, R2 = 0.8, σ = 124 yr–1 mm yr−1, m = 0.88, c = 191 mm yr−1; and RMSE = 195 mm yr−1, R2 = 0.81, σ = 146 mm yr−1, m = 1.05, c = 120 mm yr−1) of the latter two methods. The value of the Priestley–Taylor (PT) coefficient was determined by inversion of the PT-equation via a model-independent identification of wet cells and their estimated surface temperatures.


2021 ◽  
Author(s):  
Fahd Siddiqui ◽  
Mohammadreza Kamyab ◽  
Michael Lowder

Abstract The economic success of unconventional reservoirs relies on driving down completion costs. Manually measuring the operational efficiency for a multi-well pad can be error-prone and time-prohibitive. Complete automation of this analysis can provide an effortless real-time insight to completion engineers. This study presents a real-time method for measuring the time spent on each completion activity, thereby enabling the identification and potential cost reduction avenues. Two data acquisition boxes are utilized at the completion site to transmit both the fracturing and wireline data in real-time to a cloud server. A data processing algorithm is described to determine the start and end of these two operations for each stage of every well on the pad. The described method then determines other activity intervals (fracturing swap-over, wireline swap-over, and waiting on offset wells) based on the relationship between the fracturing and wireline segments of all the wells. The processed data results can be viewed in real-time on mobile or computers connected to the cloud. Viewing the full operational time log in real-time helps engineers analyze the whole operation and determine key performance indicators (KPIs) such as the number of fractured stages per day, pumping percentage, average fracture, and wireline swap-over durations for a given time period. In addition, the performance of the day and night crews can be evaluated. By plotting a comparison of KPIs for wireline and fracturing times, trends can be readily identified for improving operational efficiency. Practices from best-performing stages can be adopted to reduce non-pumping times. This helps operators save time and money to optimize for more efficient operations. As the number of wells increases, the complexity of manual generation of time-log increases. The presented method can handle multi-well fracturing and wireline operations without such difficulty and in real-time. A case study is also presented, where an operator in the US Permian basin used this method in real-time to view and optimize zipper operations. Analysis indicated that the time spent on the swap over activities could be reduced. This operator set a realistic goal of reducing 10 minutes per swap-over interval. Within one pad, the goal was reached utilizing this method, resulting in reducing 15 hours from the total pad time. The presented method provides an automated overview of fracturing operations. Based on the analysis, timely decisions can be made to reduce operational costs. Moreover, because this method is automated, it is not limited to single well operations but can handle multi-well pad completion designs that are commonplace in unconventionals.


2020 ◽  
Author(s):  
◽  
Tareq Abdulqader

The study's aim was to develop a non-contact, ultrasound (US) based respiration rate and respiratory signal monitor suitable for babies in incubators. Respiration rate indicates average number of breaths per minute and is higher in young children than adults. It is an important indicator of health deterioration in critically ill patients. The current incubators do not have an integrated respiration monitor due to complexities in its adaptation. Monitoring respiratory signal assists in diagnosing respiration rated problems such as central Apnoea that can affect infants. US sensors are suitable for integration into incubators as US is a harmless and cost-effective technology. US beam is focused on the chest or abdomen. Chest or abdomen movements, caused by respiration process, result in variations in their distance to the US transceiver located at a distance of about 0.5 m. These variations are recorded by measuring the time of flight from transmitting the signal and its reflection from the monitored surface. Measurement of this delay over a time interval enables a respiration signal to be produced from which respiration rate and pauses in breathing are determined. To assess the accuracy of the developed device, a platform with a moving surface was devised. The magnitude and frequency of its surface movement were accurately controlled by its signal generator. The US sensor was mounted above this surface at a distance of 0.5 m. This US signal was wirelessly transmitted to a microprocessor board to digitise. The recorded signal that simulated a respiratory signal was subsequently stored and displayed on a computer or an LCD screen. The results showed that US could be used to measure respiration rate accurately. To cater for possible movement of the infant in the incubator, four US sensors were adapted. These monitored the movements from different angles. An algorithm to interpret the output from the four US sensors was devised and evaluated. The algorithm interpreted which US sensor best detected the chest movements. An IoMT system was devised that incorporated NodeMcu to capture signals from the US sensor. The detected data were transmitted to the ThingSpeak channel and processed in real-time by ThingSpeak’s add-on Matlab© feature. The data were processed on the cloud and then the results were displayed in real-time on a computer screen. The respiration rate and respiration signal could be observed remotely on portable devices e.g. mobile phones and tablets. These features allow caretakers to have access to the data at any time and be alerted to respiratory complications. A method to interpret the recorded US signals to determine respiration patterns, e.g. intermittent pauses, were implemented by utilising Matlab© and ThingSpeak Server. The method successfully detected respiratory pauses by identifying lack of chest movements. The approach can be useful in diagnosing central apnoea. In central apnoea, respiratory pauses are accompanied by cessation of chest or abdominal movements. The devised system will require clinical trials and integration into an incubator by conforming to the medical devices directives. The study demonstrated the integration of IoMT-US for measuring respiration rate and respiratory signal. The US produced respiration rate readings compared well with the actual signal generator's settings of the platform that simulated chest movements.


2021 ◽  
Vol 8 ◽  
Author(s):  
Mojtaba Akbari ◽  
Jay Carriere ◽  
Tyler Meyer ◽  
Ron Sloboda ◽  
Siraj Husain ◽  
...  

During an ultrasound (US) scan, the sonographer is in close contact with the patient, which puts them at risk of COVID-19 transmission. In this paper, we propose a robot-assisted system that automatically scans tissue, increasing sonographer/patient distance and decreasing contact duration between them. This method is developed as a quick response to the COVID-19 pandemic. It considers the preferences of the sonographers in terms of how US scanning is done and can be trained quickly for different applications. Our proposed system automatically scans the tissue using a dexterous robot arm that holds US probe. The system assesses the quality of the acquired US images in real-time. This US image feedback will be used to automatically adjust the US probe contact force based on the quality of the image frame. The quality assessment algorithm is based on three US image features: correlation, compression and noise characteristics. These US image features are input to the SVM classifier, and the robot arm will adjust the US scanning force based on the SVM output. The proposed system enables the sonographer to maintain a distance from the patient because the sonographer does not have to be holding the probe and pressing against the patient's body for any prolonged time. The SVM was trained using bovine and porcine biological tissue, the system was then tested experimentally on plastisol phantom tissue. The result of the experiments shows us that our proposed quality assessment algorithm successfully maintains US image quality and is fast enough for use in a robotic control loop.


Author(s):  
Alison G. Vredenburgh ◽  
Gail L. Sunderman ◽  
Rodrigo J. Daly Guris ◽  
Sreekanth R. Cheruku

In this follow-up panel, we discuss what we have learned over the last year about responding to an epidemic or pandemic that has demonstrated a level of transmission unprecedented in the modern era. Two medical doctors that have worked on the front of this pandemic share their experiences transitioning from the “sharp end” of the response. Decisions about how to mitigate hazards have occurred at the personal, institutional, and health policy levels, in real-time, with frequent adaptation, and often in advance of concrete evidence. Over the course of the pandemic, hospital systems revised existing protocols to manage perceived risks in real time using emerging information from other centers. With the introduction of vaccines, there is a new type of risk perception. Is the vaccine perceived to be safe? Is there a disparity in perception among different population groups? That said, analyses are also complicated by emerging viral mutations with unclear implications. What factors increase or decrease public compliance with precautions? How are US education policymakers deciding about face-to-face classroom instruction? This panel includes a warnings expert, an expert on education policy, and two practicing physicians.


2006 ◽  
pp. 165-182
Author(s):  
Franz Seitz ◽  
Christina Gerberding ◽  
Andreas Worms

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