William Lidberg

1.1k total citations
30 papers, 735 citations indexed

About

William Lidberg is a scholar working on Water Science and Technology, Ecology and Environmental Engineering. According to data from OpenAlex, William Lidberg has authored 30 papers receiving a total of 735 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Water Science and Technology, 15 papers in Ecology and 10 papers in Environmental Engineering. Recurrent topics in William Lidberg's work include Hydrology and Watershed Management Studies (16 papers), Peatlands and Wetlands Ecology (10 papers) and Soil erosion and sediment transport (4 papers). William Lidberg is often cited by papers focused on Hydrology and Watershed Management Studies (16 papers), Peatlands and Wetlands Ecology (10 papers) and Soil erosion and sediment transport (4 papers). William Lidberg collaborates with scholars based in Sweden, United Kingdom and Spain. William Lidberg's co-authors include Anneli Ågren, Hjalmar Laudon, Mats Nilsson, Paul A. Arp, Jae Ogilvie, Monika Strömgren, Ryan A. Sponseller, Eva Ring, Reiner Giesler and Carl‐Magnus Mörth and has published in prestigious journals such as The Science of The Total Environment, Water Resources Research and Journal of Environmental Management.

In The Last Decade

William Lidberg

27 papers receiving 720 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
William Lidberg Sweden 13 271 255 251 201 160 30 735
Rasmus Sørensen Sweden 8 291 1.1× 248 1.0× 187 0.7× 221 1.1× 87 0.5× 13 878
Mattias Winterdahl Sweden 9 205 0.8× 277 1.1× 167 0.7× 89 0.4× 104 0.7× 13 704
Lenka Kuglerová Sweden 17 596 2.2× 403 1.6× 257 1.0× 108 0.5× 132 0.8× 37 1.1k
Shanshan Qiao China 6 306 1.1× 264 1.0× 148 0.6× 47 0.2× 108 0.7× 9 728
Kara L. Webster Canada 24 719 2.7× 233 0.9× 447 1.8× 116 0.6× 308 1.9× 66 1.3k
Zoltán Gribovszki Hungary 13 146 0.5× 468 1.8× 429 1.7× 292 1.5× 114 0.7× 61 825
Jakub Jankovec Czechia 8 122 0.5× 165 0.6× 182 0.7× 97 0.5× 145 0.9× 9 581
Harbin Li United States 11 459 1.7× 142 0.6× 442 1.8× 64 0.3× 143 0.9× 14 826
Zhen Xu China 16 150 0.6× 282 1.1× 263 1.0× 112 0.6× 201 1.3× 31 714
Xudong Zhu China 20 558 2.1× 87 0.3× 540 2.2× 132 0.7× 247 1.5× 54 1.1k

Countries citing papers authored by William Lidberg

Since Specialization
Citations

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

Fields of papers citing papers by William Lidberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of William Lidberg

This figure shows the co-authorship network connecting the top 25 collaborators of William Lidberg. A scholar is included among the top collaborators of William Lidberg 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 William Lidberg. William Lidberg is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ågren, Anneli, et al.. (2025). Automatic detection of ditches and natural streams from digital elevation models using deep learning. Computers & Geosciences. 196. 105875–105875.
2.
Lidberg, William. (2025). Deep learning-enhanced detection of road culverts in high-resolution digital elevation models: Improving stream network accuracy in Sweden. Journal of Hydrology Regional Studies. 57. 102148–102148. 1 indexed citations
3.
Greenberg, Larry, et al.. (2025). Riparian buffers mitigate downstream effects of clear-cutting on instream metabolic rates. Journal of Environmental Management. 379. 124740–124740.
4.
5.
Sandström, Camilla, et al.. (2024). Forest owners’ perceptions of machine learning: Insights from swedish forestry. Environmental Science & Policy. 162. 103945–103945. 1 indexed citations
6.
Lidberg, William, et al.. (2024). Detection of Hunting Pits using Airborne Laser Scanning and Deep Learning. Journal of Field Archaeology. 49(6). 395–405. 2 indexed citations
7.
Akselsson, Cecilia, et al.. (2024). Riparian buffer zones in production forests create unequal costs among forest owners. European Journal of Forest Research. 143(3). 1035–1046. 2 indexed citations
8.
Ågren, Anneli, Olivia S. Anderson, William Lidberg, Mats Öquist, & Eliza Maher Hasselquist. (2024). Ditches show systematic impacts on soil and vegetation properties across the Swedish forest landscape. Forest Ecology and Management. 555. 121707–121707. 2 indexed citations
9.
Peacock, Mike, et al.. (2024). An upscaling of methane emissions from Swedish flooded land. Carbon Management. 16(1). 1 indexed citations
10.
Lupon, Anna, Lluís Gómez‐Gener, Megan L. Fork, et al.. (2023). Groundwater‐stream connections shape the spatial pattern and rates of aquatic metabolism. Limnology and Oceanography Letters. 8(2). 350–358. 12 indexed citations
11.
Peng, Haijun, Jelmer Nijp, Joshua L. Ratcliffe, et al.. (2023). Climatic controls on the dynamic lateral expansion of northern peatlands and its potential implication for the ‘anomalous’ atmospheric CH4 rise since the mid-Holocene. The Science of The Total Environment. 908. 168450–168450. 5 indexed citations
12.
Ågren, Anneli, Mats B. Nilsson, Joshua L. Ratcliffe, et al.. (2023). Catchment characteristics control boreal mire nutrient regime and vegetation patterns over ~5000 years of landscape development. The Science of The Total Environment. 895. 165132–165132. 6 indexed citations
13.
Lidberg, William, et al.. (2022). Predicting soil moisture conditions across a heterogeneous boreal catchment using terrain indices. Hydrology and earth system sciences. 26(19). 4837–4851. 19 indexed citations
14.
Laudon, Hjalmar, William Lidberg, Ryan A. Sponseller, et al.. (2022). Emerging technology can guide ecosystem restoration for future water security. Hydrological Processes. 36(10). 13 indexed citations
15.
Biester, Harald, Christian Bigler, William Lidberg, et al.. (2019). Environmental footprint of small-scale, historical mining and metallurgy in the Swedish boreal forest landscape: The Moshyttan blast furnace as microcosm. The Holocene. 29(4). 578–591. 4 indexed citations
16.
17.
Lidberg, William, Mats Nilsson, & Anneli Ågren. (2019). Using machine learning to generate high-resolution wet area maps for planning forest management: A study in a boreal forest landscape. AMBIO. 49(2). 475–486. 53 indexed citations
18.
Hasselquist, Eliza Maher, William Lidberg, Ryan A. Sponseller, Anneli Ågren, & Hjalmar Laudon. (2017). Identifying and assessing the potential hydrological function of past artificial forest drainage. AMBIO. 47(5). 546–556. 34 indexed citations
19.
Lidberg, William, Mats Nilsson, Tomas Lundmark, & Anneli Ågren. (2017). Evaluating preprocessing methods of digital elevation models for hydrological modelling. Hydrological Processes. 31(26). 4660–4668. 58 indexed citations
20.
Ågren, Anneli, William Lidberg, Monika Strömgren, Jae Ogilvie, & Paul A. Arp. (2014). Evaluating digital terrain indices for soil wetness mapping – a Swedish case study. Hydrology and earth system sciences. 18(9). 3623–3634. 138 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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