31,906 research outputs found
Developing a data-driven model for dynamic reservoir operation using a combined hidden Markov-decision tree and classification tree algorithms
No full textReservoir operations are faced with greater challenges than before due to growing water demands and climate change, and thus understanding and improvement of reservoir operations are critical. This study extends the hidden-Markov-decision tree (HM-DT) model developed by Zhao and Cai (2020) and proposes a data-driven reservoir operation model (DROM). The HM-DT model is first applied to individual reservoirs to derive sets of representative operation modules. Then a module classification model based on the Classification and Regression-tree algorithm is developed to determine which module to use for a day. DROM combines the derived operation modules and the module classification model to realize daily release prediction. DROM is tested with 25 reservoirs operated by USBR in north Great Plains regions, and it is shown that DROM can achieve acceptable accuracy in simulating historical releases (NSE > 0.4) and predicting future releases (NSE > 0.2) for 23 reservoirs. Compared with existing data-driven models, DROM shows several advantages including easily satisfied data requirements, transparent model structure, and broad applicability to various reservoirs. Especially, DROM can simulate the dynamic operation patterns through choosing the modules, while other previous models can only derive static operation rules. DROM can be used to better understand real-world reservoir operation behaviors and to explore the improvement of operation via combining with optimization models.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2023-08-01The student, Yanan Chen, accepted the attached license on 2021-07-08 at 14:07.The student, Yanan Chen, submitted this Thesis for approval on 2021-07-08 at 14:18.This Thesis was approved for publication on 2021-07-13 at 11:29.DSpace SAF Submission Ingestion Package generated from Vireo submission #16805 on 2022-01-12 at 12:54:01Made available in DSpace on 2022-01-12T22:35:06Z (GMT). No. of bitstreams: 2
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Previous issue date: 2021-07-13Embargo set by: Seth Robbins for item 121085
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Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemAuthor requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemU of I Onl
Understanding historical reservoir operation rules, dynamics, and deficiencies - opportunities for improvement
No full textSubmission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2026-12-01The student, Yanan Chen, accepted the attached license on 2024-12-04 at 10:00.The student, Yanan Chen, submitted this Dissertation for approval on 2024-12-04 at 10:17.This Dissertation was approved for publication on 2024-12-05 at 18:51.DSpace SAF Submission Ingestion Package generated from Vireo submission #21494 on 2025-03-28 at 14:55:47Reservoirs play a vital role in surface water management, serving various purposes such as flood control, irrigation, water supply, and hydroelectricity. However, reservoir operation has been complicated by rapidly changing environments, including climate, water demand, and operation police changes. This dissertation aims to enhance understanding of historical reservoir operation rules, dynamics, and deficiencies across the contiguous United States (CONUS) and explore ways to improve operation performance. The research is organized into three interconnected parts. The first part develops a generic data-driven reservoir operation model (GDROM) using machine learning (ML) to extract real-world reservoir operation rules. Tested on 467 reservoirs of varying capacities and functions across the CONUS, the GDROM demonstrates comparable accuracy in release simulation to other ML models, with improved interpretability due to its transparent structure. The second part identifies reservoir storage and operational changes between 1990 and 2019 for 256 reservoirs across the CONUS and analyzes the underlying causes. The GDROM model is used as a tool to identify operational changes, including the cases of both operational effectiveness and deficiencies through analyzing the relations of storage and operational changes under environmental changes. To address the operational deficiencies detected in the second part, the third part proposes a new forecast-informed reservoir operation (FIRO) decision support framework that integrates analytically derived hedging policies with empirically based flood control rules. Within this framework, the GDROM is integrated to capture real-world operation specifications that reflect operators’ actual response to various hydrologic conditions. The FIRO framework is tested on Folsom Lake in California, which demonstrates significant improvement in water conservation benefit in the post flood season without increasing flood risks during the flood season. Leveraging historical operation records and the developed date-driven reservoir operation model, this dissertation provides insights into real-world operational rules, dynamics, and existing deficiencies within the CONUS, offering guidance for operation design in response to future changes. Moreover, this research establishes a new FIRO decision support framework, which introduces flexibility to address operational deficiencies and improve reservoir performance under varying hydrological conditions
Chen Chen, 42nd Annual ODU Literary Festival
No full textChen Chen is the author of When I Grow Up I Want to Be a List of Further Possibilities (BOA Editions, 2017), which was long-listed for the National Book Award and won the Thom Gunn Award, among other honors. Bloodaxe Books published a UK edition in June. He is also the author of four chapbooks, most recently You MUST Use the Word Smoothie (Sundress Publications, 2019) and Gesundheit! (in collaboration with Sam Herschel Wein and forthcoming from Glass Poetry Press, fall 2019). His work appears in many publications, including Poem-a-Day, The Massachusetts Review, The Best American Poetry, and The Best American Nonrequired Reading. He has received a Pushcart Prize and fellowships from Kundiman and the National Endowment for the Arts. He holds an MFA from Syracuse University and a PhD from Texas Tech University. He teaches at Brandeis University as the Jacob Ziskind Poet-in-Residence and co-runs the journal, Underblong. He lives in Waltham, Massachusetts, with his partner, Jeff Gilbert, and their pug, Mr. Rupert Gile
sj-docx-1-dmj-10.1177_1089313X231177172 – Supplemental material for Online Dance Injury Monitoring: The Efficacy of Weekly Reporting and Respondent Compliance Over a 30-Week Period
No full textSupplemental material, sj-docx-1-dmj-10.1177_1089313X231177172 for Online Dance Injury Monitoring: The Efficacy of Weekly Reporting and Respondent Compliance Over a 30-Week Period by Yanan Dang, Yiannis Koutedakis, Ruoling Chen and Matthew Wyon in Journal of Dance Medicine & Science</p
sj-docx-3-dmj-10.1177_1089313X231177172 – Supplemental material for Online Dance Injury Monitoring: The Efficacy of Weekly Reporting and Respondent Compliance Over a 30-Week Period
No full textSupplemental material, sj-docx-3-dmj-10.1177_1089313X231177172 for Online Dance Injury Monitoring: The Efficacy of Weekly Reporting and Respondent Compliance Over a 30-Week Period by Yanan Dang, Yiannis Koutedakis, Ruoling Chen and Matthew Wyon in Journal of Dance Medicine & Science</p
sj-docx-4-dmj-10.1177_1089313X231177172 – Supplemental material for Online Dance Injury Monitoring: The Efficacy of Weekly Reporting and Respondent Compliance Over a 30-Week Period
No full textSupplemental material, sj-docx-4-dmj-10.1177_1089313X231177172 for Online Dance Injury Monitoring: The Efficacy of Weekly Reporting and Respondent Compliance Over a 30-Week Period by Yanan Dang, Yiannis Koutedakis, Ruoling Chen and Matthew Wyon in Journal of Dance Medicine & Science</p
sj-docx-2-dmj-10.1177_1089313X231177172 – Supplemental material for Online Dance Injury Monitoring: The Efficacy of Weekly Reporting and Respondent Compliance Over a 30-Week Period
No full textSupplemental material, sj-docx-2-dmj-10.1177_1089313X231177172 for Online Dance Injury Monitoring: The Efficacy of Weekly Reporting and Respondent Compliance Over a 30-Week Period by Yanan Dang, Yiannis Koutedakis, Ruoling Chen and Matthew Wyon in Journal of Dance Medicine & Science</p
Supporting data used in the paper: Xi Chen, 2020, The LMARS based shallow-water dynamical core on generic gnomonic cubed-sphere geometry
No full text# Simulation results of the unstaggered shallow water model
This repository contains the supporting data used in the paper: Xi Chen, 2020, The LMARS based shallow‐water dynamical core on generic gnomonic cubed‐sphere geometry, DOI: 10.1029/2020MS002280
Organization of the repository:
The tar archive with this data submission has a:
doc directory contains a README.md with information regarding naming conventions to label the model configurations for a shallow water test simulation. Additional information can also be found in README.md. Table 4 in the paper provides additional details.
The data directory contains the supporting data files (NetCDF format).Disclaimer: "This was prepared by Xi Chen under award NA18OAR4320123 from the National Oceanic and Atmospheric Administration, U.S. Department of Commerce. The statements, findings, conclusions, and recommendations are those of the author(s) and do not necessarily reflect the views of the National Oceanic and Atmospheric Administration, or the U.S. Department of Commerce.
Artimpaza brevilineata Tian & Chen, 2012 in Tian, Chen & Li 2012
No full textArtimpaza brevilineata Tian & Chen, 2012 in Tian, Chen & Li, 2012: 43, figs. 1–9. (Figs. 28a, b) Type locality: China, Yunnan, Pu’er City, Yutang. Gender: female. Date collected: 2011.V.25 (2010.V.25, in the original description, is incorrect). Collector: Li-Chao TIAN & Gui-Qiang HUANG. Paratypes: 1 female, China, Yunnan, Lincang City, 1980.VI.1, Fen LIU leg. Remarks: In the original description, the type locality is “ Yunnan, Jinghong” while it is “ Yunnan, Yutang” according to the label. “Yutang” is actually in Pu’er, not Jinghong. The first author described the type locality by mistake. In the original description, the collector was only listed as Li-Chao TIAN, which was a mistake.Published as part of Li, Zhu & Chen, Li, 2020, Primary types of longhorned beetles (Coleoptera, Cerambycidae, Vesperidae and Disteniidae) of Southwest University (SWU), pp. 25-46 in Zootaxa 4718 (1) on page 33, DOI: 10.11646/zootaxa.4718.1.2, http://zenodo.org/record/360220
Author contributions
No full textPlease browse the "Files" tag to access the appendix specifying the author - Chen Hsi Tsai's contributions to the seven papers included in the thesis
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