Maria L. Chu

1.7k total citations
58 papers, 1.3k citations indexed

About

Maria L. Chu is a scholar working on Water Science and Technology, Ecology and Global and Planetary Change. According to data from OpenAlex, Maria L. Chu has authored 58 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Water Science and Technology, 25 papers in Ecology and 23 papers in Global and Planetary Change. Recurrent topics in Maria L. Chu's work include Hydrology and Watershed Management Studies (28 papers), Soil erosion and sediment transport (19 papers) and Hydrology and Sediment Transport Processes (15 papers). Maria L. Chu is often cited by papers focused on Hydrology and Watershed Management Studies (28 papers), Soil erosion and sediment transport (19 papers) and Hydrology and Sediment Transport Processes (15 papers). Maria L. Chu collaborates with scholars based in United States, Philippines and South Africa. Maria L. Chu's co-authors include Igor Linkov, Glenn V. Wilson, Garey A. Fox, Gregory A. Kiker, Rafael Muñoz‐Carpena, Jorge A. Gúzman, Matteo Convertino, Daniel N. Moriasi, Richard A. Fischer and Jean L. Steiner and has published in prestigious journals such as The Science of The Total Environment, Global Change Biology and Journal of Hydrology.

In The Last Decade

Maria L. Chu

58 papers receiving 1.3k citations

Peers

Maria L. Chu

ECOLO

GPC

WST

Yuting Cheng China

T. I. Dowling Australia

Pengfei Lin China

Zhongbao Xin China

Travis Nauman United States

Guoce Xu China

Abdul Rahim Nik Malaysia

Gavan McGrath Australia

V.W.P. van Engelen Netherlands

Anke Hildebrandt Germany

Yuting Cheng China

Maria L. Chu

382 ×0.8

ECOLO

320 ×0.7

GPC

337 ×0.9

WST

474 ×1.7

225 ×1.0

Citations per year, relative to Maria L. Chu Maria L. Chu (= 1×) peers Yuting Cheng

Countries citing papers authored by Maria L. Chu

Since Specialization

Citations

This map shows the geographic impact of Maria L. Chu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Maria L. Chu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maria L. Chu more than expected).

Fields of papers citing papers by Maria L. Chu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maria L. Chu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Maria L. Chu. The network helps show where Maria L. Chu may publish in the future.

Co-authorship network of co-authors of Maria L. Chu

This figure shows the co-authorship network connecting the top 25 collaborators of Maria L. Chu. A scholar is included among the top collaborators of Maria L. Chu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Maria L. Chu. Maria L. Chu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Gúzman, Jorge A., et al.. (2025). Prediction of gully erosion susceptibility through the lens of the SHapley Additive exPlanations (SHAP) method using a stacking ensemble model. Journal of Environmental Management. 383. 125478–125478. 2 indexed citations

Chu, Maria L., et al.. (2024). Transport of nitrogen in grassed watersheds accounting for the combined influence of grazing and climate. Ecological Modelling. 496. 110827–110827. 2 indexed citations

Riper, Carena J. van, Suresh C. Sharma, Seunguk Shin, et al.. (2024). Understanding the spatial dynamics of values and disvalues in the Kaskaskia River Watershed, USA through a social-ecological lens. Ecosystems and People. 20(1). 2 indexed citations

Cao, Yong, et al.. (2023). Agricultural conservation may not help Midwestern US freshwater biodiversity in a changing climate. The Science of The Total Environment. 872. 162143–162143. 1 indexed citations

Shipley, Nathan J., Carena J. van Riper, William P. Stewart, et al.. (2023). Pride and guilt as place-based affective antecedents to pro-environmental behavior. Frontiers in Psychology. 13. 1084741–1084741. 9 indexed citations

Chu, Maria L., et al.. (2022). A decision-making framework for evaluating environmental tradeoffs in enhancing ecosystem services across complex agricultural landscapes. Journal of Environmental Management. 314. 115077–115077. 9 indexed citations

Chu, Maria L., et al.. (2022). Risk assessment of harmful algal blooms (HAB) occurrence in the agroecosystem: A hydro-ecologic modeling framework and environmental risk matrix. Ecological Indicators. 145. 109617–109617. 2 indexed citations

Chu, Maria L., Jorge A. Gúzman, Dennis C. Flanagan, et al.. (2022). Integrated modeling for simulating sediment production and transport in agricultural landscapes. Environmental Modelling & Software. 160. 105605–105605. 8 indexed citations

Knouft, Jason H., et al.. (2021). Forested Riparian Buffers as Climate Adaptation Tools for Management of Riverine Flow and Thermal Regimes: A Case Study in the Meramec River Basin. Sustainability. 13(4). 1877–1877. 16 indexed citations

10.

Chu, Maria L., et al.. (2020). Assessing the potential of riparian reforestation to facilitate watershed climate adaptation. Journal of Environmental Management. 277. 111431–111431. 16 indexed citations

11.

Chu, Maria L., et al.. (2020). Modeling field scale nitrogen non-point source pollution (NPS) fate and transport: Influences from land management practices and climate. The Science of The Total Environment. 759. 143502–143502. 39 indexed citations

12.

Chu, Maria L., et al.. (2020). A comprehensive modeling framework to evaluate soil erosion by water and tillage. Journal of Environmental Management. 279. 111631–111631. 25 indexed citations

13.

Chu, Maria L., et al.. (2019). Beyond model metrics: The perils of calibrating hydrologic models. Journal of Hydrology. 578. 124032–124032. 48 indexed citations

14.

Chu, Maria L., et al.. (2019). Field scale nitrogen load in surface runoff: Impacts of management practices and changing climate. Journal of Environmental Management. 249. 109327–109327. 14 indexed citations

15.

Miranda, Jarbas Honório de, et al.. (2019). Impacts of regional climate change on the runoff and root water uptake in corn crops in Parana, Brazil. Agricultural Water Management. 221. 556–565. 26 indexed citations

16.

Chu, Maria L., et al.. (2017). Evaluating the impacts of agricultural land management practices on water resources: A probabilistic hydrologic modeling approach. Journal of Environmental Management. 193. 512–523. 6 indexed citations

17.

Chu, Maria L., et al.. (2017). Riparian erosion vulnerability model based on environmental features. Journal of Environmental Management. 203(Pt 1). 592–602. 22 indexed citations

18.

Convertino, Matteo, Rafael Muñoz‐Carpena, Maria L. Chu, Gregory A. Kiker, & Igor Linkov. (2013). Untangling drivers of species distributions: Global sensitivity and uncertainty analyses of MaxEnt. Environmental Modelling & Software. 51. 296–309. 146 indexed citations

19.

Convertino, Matteo, Gregory A. Kiker, Rafael Muñoz‐Carpena, et al.. (2011). Scale- and resolution-invariance of suitable geographic range for shorebird metapopulations. Ecological Complexity. 8(4). 364–376. 25 indexed citations

20.

Fox, Garey A., et al.. (2008). Seepage Erosion Mechanisms of Bank Collapse: Three-Dimensional Seepage Particle Mobilization and Undercutting. World Environmental and Water Resources Congress 2008. 1–10. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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