Linyin Cheng Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Associate Professor GEAR 230
faculty
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Linyin Cheng is an Associate Professor at the University of Arkansas at Fayetteville. Her research focuses on hydrology and water resource management, with a particular emphasis on drought dynamics and prediction.
Cheng's work investigates the complexities of drought recovery patterns, using hybrid modeling approaches to predict water levels. She has explored the co-regulation of water and energy in drought resistance and resilience, examining how land-use intensity influences ecological restoration in regions prone to severe soil erosion. Her research also addresses the identification, probability estimation, and prediction of drought and pluvial events, considering observational uncertainty and the interplay between climate and watershed characteristics.
Her scholarship metrics include an h-index of 21, with 42 total publications and over 3,257 citations. Cheng has served as Co-PI on two federal grants totaling $577,935. One grant, funded by the NIH/National Institute on Drug Abuse for $328,030, focuses on tunable multi-timescale cortical dynamics. The other, funded by the NSF for $249,905, is part of the AccelNet-Design initiative towards future U.S. urban resilience (Resilient-NET).
Cheng collaborates with researchers such as Yichan Li and Yaqian He. She maintains an active lab website and leads a research group.
Metrics
- h-index: 21
- Publications: 42
- Citations: 3,320
Selected Publications
-
Divergent hydrological responses to restoration between planted and natural forests basins in drylands (2026)
-
Enhanced Extreme Precipitation Simulation in China using NCAR CESM Based on Realistic Remotely-Sensed Land Cover and Land Use Data from 1982 to 2013 (2025)
-
Earth greening and climate change reshaping the patterns of terrestrial water sinks and sources (2025)
-
Semi-arid rather than arid regions of China deserve the priority in drought mitigation efforts (2024)
-
Vegetation greening accelerated hydrological drought in two-thirds of river basins over China (2024)
-
Temperature forecasts for the continental United States: a deep learning approach using multidimensional features (2024)
-
Observational Uncertainty for Global Drought‐Pluvial Volatility (2023)
-
Evaluating Non-Stationarity in Precipitation Intensity-Duration-Frequency Curves for the Dallas–Fort Worth Metroplex, Texas, USA (2023)
-
Co-regulation of water and energy in the spatial heterogeneity of drought resistance and resilience (2023)
-
Land‐Use Intensity Reversed the Role of Cropland in Ecological Restoration Over the World's Most Severe Soil Erosion Region (2023)
-
Compensating Effects Between Climate and Underlying Characteristics on Watershed Water Loss (2023)
-
Detectable Increase in Global Land Areas Susceptible to Precipitation Reversals Under the RCP8.5 Scenario (2022)
-
A probabilistic framework for sequential drought-fluvial identification, probability estimation and prediction (2022)
-
The Reconstruction and Extension of Terrestrial Water Storage Based on a Combined Prediction Model (2021)
-
Stability of spatial dependence structure of extreme precipitation and the concurrent risk over a nested basin (2021)
Federal Grants 2 $577,935 total
Tunable multi-timescale cortical dynamics: fundamental theory and practical tools
AccelNet-Design: International Networks Towards Future U.S. Urban Resilience (Resilient-NET)
Collaboration Network
Top Collaborators
- Dynamic drought recovery patterns over the Yangtze River Basin
- A hybrid bayesian vine model for water level prediction
- Co-regulation of water and energy in the spatial heterogeneity of drought resistance and resilience
- Land‐Use Intensity Reversed the Role of Cropland in Ecological Restoration Over the World's Most Severe Soil Erosion Region
- A probabilistic framework for sequential drought-fluvial identification, probability estimation and prediction
Showing 5 of 7 shared publications
- A hybrid bayesian vine model for water level prediction
- Land‐Use Intensity Reversed the Role of Cropland in Ecological Restoration Over the World's Most Severe Soil Erosion Region
- A probabilistic framework for sequential drought-fluvial identification, probability estimation and prediction
- Compensating Effects Between Climate and Underlying Characteristics on Watershed Water Loss
- Land‐Use Intensity Reversed the Role of Cropland in Ecological Restoration Over the World's Most Severe Soil Erosion Region
- A probabilistic framework for sequential drought-fluvial identification, probability estimation and prediction
- Compensating Effects Between Climate and Underlying Characteristics on Watershed Water Loss
- Co-regulation of water and energy in the spatial heterogeneity of drought resistance and resilience
- Land‐Use Intensity Reversed the Role of Cropland in Ecological Restoration Over the World's Most Severe Soil Erosion Region
- A probabilistic framework for sequential drought-fluvial identification, probability estimation and prediction
- Dynamic drought recovery patterns over the Yangtze River Basin
- A probabilistic framework for sequential drought-fluvial identification, probability estimation and prediction
- The Reconstruction and Extension of Terrestrial Water Storage Based on a Combined Prediction Model
- The Reconstruction and Extension of Terrestrial Water Storages Based On A Combined Prediction Model
- The Reconstruction and Extension of Terrestrial Water Storage Based on a Combined Prediction Model
- The Reconstruction and Extension of Terrestrial Water Storages Based On A Combined Prediction Model
- The Reconstruction and Extension of Terrestrial Water Storage Based on a Combined Prediction Model
- The Reconstruction and Extension of Terrestrial Water Storages Based On A Combined Prediction Model
- The Reconstruction and Extension of Terrestrial Water Storage Based on a Combined Prediction Model
- The Reconstruction and Extension of Terrestrial Water Storages Based On A Combined Prediction Model
- Land‐Use Intensity Reversed the Role of Cropland in Ecological Restoration Over the World's Most Severe Soil Erosion Region
- Compensating Effects Between Climate and Underlying Characteristics on Watershed Water Loss
- Dynamic drought recovery patterns over the Yangtze River Basin
- A hybrid bayesian vine model for water level prediction
- A probabilistic framework for sequential drought-fluvial identification, probability estimation and prediction
- A probabilistic framework for sequential drought-fluvial identification, probability estimation and prediction
- Compensating Effects Between Climate and Underlying Characteristics on Watershed Water Loss
Similar Researchers
Based on overlapping research topics