Alison Appling

40 papers receiving 2.5k citations

Alison Appling's Hit Papers

Deep learning for water quality 2024 · 191 citations
1910+2+4Years since publication100200300

Peers

Alison Appling
Comparison fields: 5 of 101
  • Water Science and Technology 1.1k
  • Environmental Chemistry 605
  • Nature and Landscape Conservation 704
  • Environmental Engineering 794
  • Global and Planetary Change 536
Replace Mariusz Ptak with:
Mariusz Ptak Poland
Jacob A. Zwart United States
Wen-Cheng Liu Taiwan
Arthur E. Mynett Netherlands
Hongwu Tang China
Cláudio Clemente Faria Barbosa Brazil
Yi Luo China
Senlin Zhu China
Jia Du China
Thanh Duc Dang Vietnam
Alison Appling relative to Mariusz Ptak Poland Mariusz Ptak's profile →
Citations per field
00.5×1.5×2×
Mariusz Ptak · 1×
Citations per year

Countries citing papers authored by Alison Appling

Since Specialization
Citations

This map shows the geographic impact of Alison Appling'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 Alison Appling with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alison Appling more than expected).

Fields of papers citing papers by Alison Appling

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alison Appling. 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 Alison Appling. The network helps show where Alison Appling may publish in the future.

Co-authors

The 25 scholars most cited alongside Alison Appling, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Alison Appling Line = papers co-authored together Alison Appling links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Process‐Guided Deep Learning Predictions of Lake Water Temperature
Hit paper breakdown →
2019302
2 2017293
3
Differentiable modelling to unify machine learning and physical models for geosciences
Hit paper breakdown →
2023264
4
Deep learning for water quality
Hit paper breakdown →
2024191
5 2018174
6 2022141
7 2019120
8 202091
9 201582
10 201579
11 202174
12 201972
13 202168
14 202264
15 201960
16 202155
17 201445
18 202241
19 201528
20 201427

About Alison Appling

Alison Appling is a scholar working on Water Science and Technology, Environmental Engineering, Nature and Landscape Conservation, Environmental Chemistry and Global and Planetary Change, having authored 40 papers that have together received 2.5k indexed citations. Recurring topics across this work include Hydrology and Watershed Management Studies (25 papers), Hydrological Forecasting Using AI (24 papers), Fish Ecology and Management Studies (13 papers), Soil and Water Nutrient Dynamics (9 papers), Flood Risk Assessment and Management (8 papers), Reservoir Engineering and Simulation Methods (4 papers), Marine and coastal ecosystems (4 papers) and Model Reduction and Neural Networks (4 papers). The work is most often cited by research in Water Science and Technology (1.1k citations), Environmental Chemistry (605 citations), Nature and Landscape Conservation (704 citations), Environmental Engineering (794 citations) and Global and Planetary Change (536 citations). Alison Appling has collaborated with scholars based in United States, Spain and China. Frequent co-authors include Jordan S. Read, Samantha K. Oliver, Robert O. Hall, Charles Brandon Yackulic, Maite Arroita, Xiaowei Jia, William H. McDowell, Vipin Kumar, Emily S. Bernhardt and James Brendan Heffernan. Their work appears in journals such as Water Resources Research, Limnology and Oceanography, Hydrological Processes, Journal of Geophysical Research Biogeosciences and Ecosphere.

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.

Explore authors with similar magnitude of impact