Hong-Yi Li

Hong-Yi Li

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Hong-Yi Li

Department of Civil and Environmental Engineering, University of Houston, Houston, 77204, USA

Research Focus & Metrics

Academic Career Length

19Years (2008-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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3 August 2022 in Nature
Verified
Journal Article
Open access
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HKHeidi Kreibich
Heidi Kreibich
ALAnne Van Loon
Anne Van Loon
KSKai Schröter
Kai Schröter
PWPhilip J. Ward
Philip J. Ward
Maurizio MazzoleniMaurizio Mazzoleni
Maurizio Mazzoleni
GBGiuliano Di Baldassarre
Giuliano Di Baldassarre
Risk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing3. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change3.

1 June 2013 in Journal of Hydrometeorology
Verified
Journal Article
Open access
HLHongyi Li
Hongyi Li
MWMark S. Wigmosta
Mark S. Wigmosta
HWHuan Wu
Huan Wu
MHMaoyi Huang
Maoyi Huang
YKYinghai Ke
Yinghai Ke
LLL. Ruby Leung
L. Ruby Leung
A new physically based runoff routing model, called the Model for Scale Adaptive River Transport (MOSART), has been developed to be applicable across local, regional, and global scales. Within each spatial unit, surface runoff is first routed across hillslopes and then discharged along with subsurface runoff into a “tributary subnetwork” before entering the main channel. The spatial units are thus linked via routing through the main channel network, which is constructed in a scale-consistent way across different spatial resolutions. All model parameters are physically based, and only a small subset requires calibration. MOSART has been applied to the Columbia River basin at ⅙°, ⅛°, ¼°, and ½° spatial resolutions and was evaluated using naturalized or observed streamflow at a number of gauge stations. MOSART is compared to two other routing models widely used with land surface models, the River Transport Model (RTM) in the Community Land Model (CLM) and the Lohmann routing model, included as a postprocessor in the Variable Infiltration Capacity (VIC) model package, yielding consistent performance at multiple resolutions. MOSART is further evaluated using the channel velocities derived from field measurements or a hydraulic model at various locations and is shown to be capable of producing the seasonal variation and magnitude of channel velocities reasonably well at different resolutions. Moreover, the impacts of spatial resolution on model simulations are systematically examined at local and regional scales. Finally, the limitations of MOSART and future directions for improvements are discussed.

15 March 2014 in Water Resources Research
Verified
Journal Article
Open access
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HWHuan Wu
Huan Wu
RARobert F. Adler
Robert F. Adler
YTYudong Tian
Yudong Tian
GHGeorge Huffman
George Huffman
HLHongyi Li
Hongyi Li
JWJianJian Wang
JianJian Wang
A widely used land surface model, the Variable Infiltration Capacity (VIC) model, is coupled with a newly developed hierarchical dominant river tracing‐based runoff‐routing model to form the Dominant river tracing‐Routing Integrated with VIC Environment (DRIVE) model, which serves as the new core of the real‐time Global Flood Monitoring System (GFMS). The GFMS uses real‐time satellite‐based precipitation to derive flood monitoring parameters for the latitude band 50°N–50°S at relatively high spatial (∼12 km) and temporal (3 hourly) resolution. Examples of model results for recent flood events are computed using the real‐time GFMS (http://flood.umd.edu). To evaluate the accuracy of the new GFMS, the DRIVE model is run retrospectively for 15 years using both research‐quality and real‐time satellite precipitation products. Evaluation results are slightly better for the research‐quality input and significantly better for longer duration events (3 day events versus 1 day events). Basins with fewer dams tend to provide lower false alarm ratios. For events longer than three days in areas with few dams, the probability of detection is ∼0.9 and the false alarm ratio is ∼0.6. In general, these statistical results are better than those of the previous system. Streamflow was evaluated at 1121 river gauges across the quasi‐global domain. Validation using real‐time precipitation across the tropics (30°S–30°N) gives positive daily Nash‐Sutcliffe Coefficients for 107 out of 375 (28%) stations with a mean of 0.19 and 51% of the same gauges at monthly scale with a mean of 0.33. There were poorer results in higher latitudes, probably due to larger errors in the satellite precipitation input.

28 September 2012 in Water Resources Research
Verified
Journal Article
Closed access
PDF file
HWHuan Wu
Huan Wu
JKJohn S. Kimball
John S. Kimball
HLHongyi Li
Hongyi Li
MHMaoyi Huang
Maoyi Huang
LLL. Ruby Leung
L. Ruby Leung
RARobert F. Adler
Robert F. Adler

8 July 2015 in Energy & Environmental Science
Verified
Journal Article
Closed access
PDF file
Yuyu ZhouYuyu Zhou
Yuyu Zhou
MHM. Hejazi
M. Hejazi
SSS. Smith
S. Smith
JEJ. Edmonds
J. Edmonds
HLH. Li
H. Li
ATA. Thomson
A. Thomson
This study provides the first comprehensive quantification of global hydropower potential including gross, technical, economic, and exploitable estimates.

30 September 2013 in Hydrology and Earth System Sciences
Verified
Journal Article
Open access
PDF file
NVN. Voisin
N. Voisin
HLH. Li
H. Li
DWD. Ward
D. Ward
MHMaoyi Huang
Maoyi Huang
MWM. Wigmosta
M. Wigmosta
LLLai Yung Ruby Leung
Lai Yung Ruby Leung
Human influence on the hydrologic cycle includes regulation and storage, consumptive use and overall redistribution of water resources in space and time. Representing these processes is essential for applications of earth system models in hydrologic and climate predictions, as well as impact studies at regional to global scales. Emerging large-scale research reservoir models use generic operating rules that are flexible for coupling with earth system models. Those generic operating rules have been successful in reproducing the overall regulated flow at large basin scales. This study investigates the uncertainties of the reservoir models from different implementations of the generic operating rules using the complex multi-objective Columbia River Regulation System in northwestern United States as an example to understand their effects on not only regulated flow but also reservoir storage and fraction of the demand that is met. Numerical experiments are designed to test new generic operating rules that combine storage and releases targets for multi-purpose reservoirs and to compare the use of reservoir usage priorities and predictors (withdrawals vs. consumptive demands, as well as natural vs. regulated mean flow) for configuring operating rules. Overall the best performing implementation is with combined priorities rules (flood control storage targets and irrigation release targets) set up with mean annual natural flow and mean monthly withdrawals. The options of not accounting for groundwater withdrawals, or on the contrary, of assuming that all remaining demand is met through groundwater extractions, are discussed.