# Topics and Trends in Most Cited Hydrology and Watershed Management Studies Papers, Class of 2026

*Canonical URL: https://pri.pepkio.com/top-papers/hydrology-and-watershed-management-studies/2026*

## What topics and trends defined most-cited Hydrology and Watershed Management Studies research in the Class of 2026?

High-impact hydrology research in the Class of 2026 emphasizes hybrid modeling, multi-source data fusion, and real-time flood forecasting evaluated via Nash-Sutcliffe efficiency. Attention mechanisms and support vector machines rose sharply, replacing standalone LSTM and CNN sequence models, while predictive focus shifted toward multi-step forecasting, groundwater dynamics, and extreme flood management.

## At a glance

| Fact | Value |
| --- | --- |
| Field | Hydrology and Watershed Management Studies |
| Cohort label | Class of 2026 (2024 publications) |
| Papers analyzed | 9,612 |
| Papers ranked | 20 |
| Top topics in ranked papers | Nash-Sutcliffe efficiency, Hybrid modeling, Streamflow prediction, Flood forecasting, Ensemble learning |
| Publication window | Jan 1, 2024 – Dec 31, 2024 |
| Eligibility | Research articles; reviews excluded |
| Citation window | 18 months post-publication |
| 18m citation range | 69–732 |
| Data source | OpenAlex · Retrieved Jul 2026 |
| License | CC BY 4.0 |

## Rankings

| Rank | Title | Authors | Corresponding authors | Affiliation | Journal | 18m citations | DOI |
| ---: | --- | --- | --- | --- | --- | ---: | --- |
| 1 | Comparative Analysis of Flood Estimation using Log-Pearson Type III and Gumbel Max Models in the Cauvery River, India | Khwairakpam Robindro Singh | Khwairakpam Robindro Singh | Manipur University, India | International Journal of Innovative Science and Research Technology (IJISRT) | 732 | 10.38124/ijisrt/ijisrt24apr2402 |
| 2 | A triple increase in global river basins with water scarcity due to future pollution | Mengru Wang, Benjamin Leon Bodirsky, Rhodé Rijneveld, Felicitas Beier, Mirjam P Bak, Masooma Batool, Bram Droppers, Alexander Popp, Michelle T H van Vliet, Maryna Strokal | Mengru Wang | Wageningen University & Research, Netherlands | Nature Communications | 235 | 10.1038/s41467-024-44947-3 |
| 3 | Global prediction of extreme floods in ungauged watersheds | Grey Nearing, Deborah Cohen, Vusumuzi Dube, Martin Gauch, Oren Gilon, Shaun Harrigan, Avinatan Hassidim, Daniel Klotz, Frederik Kratzert, Asher Metzger, Sella Nevo, Florian Pappenberger, Christel Prudhomme, Guy Shalev, Shlomo Shenzis, Tadele Yednkachw Tekalign, Dana Weitzner, Yossi Matias | Grey Nearing | Google, United States | Nature | 169 | 10.1038/s41586-024-07145-1 |
| 4 | River water quality shaped by land–river connectivity in a changing climate | Li Li, Julia L. A. Knapp, Anna Lintern, G. H. C. Ng, Julia Perdrial, Pamela Sullivan, Wei Zhi | Li Li | The Pennsylvania State University, United States | Nature Climate Change | 115 | 10.1038/s41558-023-01923-x |
| 5 | Investigating the impacts of climate change on hydroclimatic extremes in the Tar-Pamlico River basin, North Carolina | Thanh-Nhan-Duc Tran, Mahesh R Tapas, Son K Do, Randall Etheridge, Venkataraman Lakshmi | Thanh‐Nhan‐Duc Tran | University of Virginia, United States | Journal of Environmental Management | 101 | 10.1016/j.jenvman.2024.121375 |
| 6 | River discharge prediction based multivariate climatological variables using hybridized long short-term memory with nature inspired algorithm | Sandeep Samantaray, Abinash Sahoo, Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, Mohammad Al-Suwaiyan | Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬ | National Institute of Technology Srinagar, India | Journal of Hydrology | 98 | 10.1016/j.jhydrol.2024.132453 |
| 7 | Water security assessment for effective water resource management based on multi-temporal blue and green water footprints | Bingbing Ding, Jieming Zhang, Pengfei Zheng, Zedong Li, Yusong Wang, Guodong Jia, Xinxiao Yu | Guodong Jia, Xinxiao Yu | Beijing Forestry University, China | Journal of Hydrology | 97 | 10.1016/j.jhydrol.2024.130761 |
| 8 | Majority of global river flow sustained by groundwater | Jiaxin Xie, Xiaomang Liu, Scott Jasechko, Wouter R. Berghuijs, Kaiwen Wang, Changming Liu, Markus Reichstein, Martin Jung, Sujan Koirala | Xiaomang Liu | Chinese Academy of Sciences, China | Nature Geoscience | 93 | 10.1038/s41561-024-01483-5 |
| 9 | Assessing the accuracy of OpenET satellite-based evapotranspiration data to support water resource and land management applications | John Volk, Justin Huntington, Forrest Melton, Richard G. Allen, Martha C. Anderson, Joshua B. Fisher, Ayşe Kiliç, Anderson Ruhoff, G. B. Senay, Blake Minor, Charles Morton, Thomas Ott, Lee Johnson, Bruno Comini de Andrade, Will Carrara, Conor T. Doherty, Christian Dunkerly, MacKenzie Friedrichs, Alberto Guzman, Christopher Hain, Gregory Halverson, Yanghui Kang, Kyle Knipper, Leonardo Laipelt, Samuel Ortega‐Salazar, Christopher Pearson, Gabriel E.L. Parrish, A. J. Purdy, Peter ReVelle, Tianxin Wang, Yun Yang | John Volk | Desert Research Institute, United States | Nature Water | 90 | 10.1038/s44221-023-00181-7 |
| 10 | Response of streamflow and sediment variability to cascade dam development and climate change in the Sai Gon Dong Nai River basin | Binh Quang Nguyen, Đoàn Văn Bình, Thanh‐Nhan‐Duc Tran, Sameh A. Kantoush, Tetsuya Sumi | Binh Quang Nguyen, Đoàn Văn Bình | University of Danang, Vietnam | Climate Dynamics | 90 | 10.1007/s00382-024-07319-7 |
| 11 | Climate Change and Hydrological Extremes | Jinghua Xiong, Yuting Yang | Yuting Yang | Tsinghua University, China | Current Climate Change Reports | 86 | 10.1007/s40641-024-00198-4 |
| 12 | Streamflow seasonality in a snow-dwindling world | Juntai Han, Ziwei Liu, Ross Woods, Tim R McVicar, Dawen Yang, Taihua Wang, Ying Hou, Yuhan Guo, Changming Li, Yuting Yang | Yuting Yang | Tsinghua University, China | Nature | 83 | 10.1038/s41586-024-07299-y |
| 13 | Widespread societal and ecological impacts from projected Tibetan Plateau lake expansion | Fenglin Xu, Guoqing Zhang, R. Iestyn Woolway, Kun Yang, Yoshihide Wada, Jida Wang, Jean‐François Crétaux | Guoqing Zhang | Institute of Tibetan Plateau Research, Chinese Academy of Sciences, China | Nature Geoscience | 82 | 10.1038/s41561-024-01446-w |
| 14 | Anthropogenic climate change has influenced global river flow seasonality | Hong Wang, Junguo Liu, Megan Klaar, Aifang Chen, Lukas Gudmundsson, Joseph Holden | Junguo Liu | Southern University of Science and Technology, China | Science | 81 | 10.1126/science.adi9501 |
| 15 | A deep learning interpretable model for river dissolved oxygen multi-step and interval prediction based on multi-source data fusion | Zhaocai Wang, Qingyu Wang, Zhixiang Liu, Tunhua Wu | Tunhua Wu | Shanghai Ocean University, China | Journal of Hydrology | 80 | 10.1016/j.jhydrol.2024.130637 |
| 16 | Evidence of human influence on Northern Hemisphere snow loss | Alexander R Gottlieb, Justin S Mankin | Alexander R. Gottlieb | Dartmouth College, United States | Nature | 74 | 10.1038/s41586-023-06794-y |
| 17 | NOAA's National Water Model: Advancing operational hydrology through continental‐scale modeling | B. Cosgrove, David Gochis, T. Flowers, A. L. Dugger, Fred L. Ogden, Tom Graziano, Ed Clark, Ryan Cabell, Nick Casiday, Zhengtao Cui, Kelley Eicher, Greg Fall, Xia Feng, Katelyn FitzGerald, Nels Frazier, Camaron M. George, R.B. Gibbs, Liliana Hernandez Gonzalez, Donald R. Johnson, Ryan M. Jones, L. R. Karsten, Henok Kefelegn, David Kitzmiller, Haksu Lee, Yuqiong Liu, Hassan Mashriqui, David B. Mattern, Alyssa McCluskey, J. L. McCreight, Rachel McDaniel, Alemayehu Midekisa, Andy Newman, Linlin Pan, Cham Q. Pham, A. Rafieeinasab, Roy Rasmussen, Laura Read, Mehdi Rezaeianzadeh, F. Salas, Dina Sang, K. M. Sampson, Tim Schneider, Qi Shi, Gautam Sood, Andy Wood, Wanru Wu, David Yates, Wei Yu, Yongxin Zhang | B. Cosgrove | National Oceanic and Atmospheric Administration, United States | JAWRA Journal of the American Water Resources Association | 72 | 10.1111/1752-1688.13184 |
| 18 | Impact of groundwater nitrogen legacy on water quality | Xiaochen Liu, Arthur Beusen, Hans J. M. van Grinsven, Junjie Wang, Wim Joost van Hoek, Xiangbin Ran, José M. Mogollón, Lex Bouwman | Xiaochen Liu, Junjie Wang | Deltares, Netherlands | Nature Sustainability | 71 | 10.1038/s41893-024-01369-9 |
| 19 | A methodological framework for assessing sea level rise impacts on nitrate loading in coastal agricultural watersheds using SWAT+: A case study of the Tar-Pamlico River basin, North Carolina, USA | Mahesh R Tapas, Randall Etheridge, Thanh-Nhan-Duc Tran, Colin G Finlay, Ariane L Peralta, Natasha Bell, Yicheng Xu, Venkataraman Lakshmi | Mahesh R Tapas | East Carolina University, United States | The Science of The Total Environment | 71 | 10.1016/j.scitotenv.2024.175523 |
| 20 | Tree water uptake patterns across the globe | Christoph Bachofen, Shersingh Joseph Tumber-Dávila, D Scott Mackay, Nate G McDowell, Andrea Carminati, Tamir Klein, Benjamin D Stocker, Maurizio Mencuccini, Charlotte Grossiord | Christoph Bachofen | EPFL, Switzerland | New Phytologist | 69 | 10.1111/nph.19762 |

## Topic trends

### What Topics Define the Class of 2026?

The Class of 2026 in Hydrology and Watershed Management Studies is defined by a strong convergence between deep learning architectures, empirical statistical metrics, and process-oriented hydrological modeling. Benchmark goodness-of-fit metrics, led by Nash-Sutcliffe efficiency (appearing in 16% of top-cited publications), anchor model evaluation standards across regional streamflow prediction (12%) and real-time flood forecasting (12%). Researchers are increasingly moving beyond standalone hydrodynamic or physical models, adopting hybrid modeling frameworks (12%) that integrate physics-informed constraints with ensemble learning (10%) and data fusion (8%). AI-driven methods feature prominently in high-impact literature: deep learning architectures such as Gated Recurrent Units (6%) and Attention mechanisms (8%) are frequently combined with Support Vector Machines (8%) to enhance predictive skill in non-linear watershed systems. Furthermore, there is growing interest in model interpretability and spatial scaling, as evidenced by rising mentions of Explainable Artificial Intelligence (8%), satellite-based Remote Sensing (6%), and hydrological connectivity (6%). Together, these dominant clusters underscore a methodological shift toward hybrid, data-assimilated forecasting systems designed to resolve extreme hydrometeorological events across complex topographies.

*Leading research themes*

### How Did Topics Shift from the Class of 2025 to the Class of 2026?

Comparative analysis between the Class of 2025 and Class of 2026 reveals a significant evolution in computational paradigms and target applications across watershed management. The most dramatic shift is the rapid ascent of multi-source data fusion (rising to 8% of top publications) and specialized prediction targets like groundwater level prediction (6%) and multistep forecasting (6%). Operational flood risk assessment surged sharply, with flood forecasting expanding six-fold (2% to 12%) alongside increased focus on extreme events such as the 100-year flood (4%) and flow regime alterations (4%). Methodologically, attention-based neural mechanisms (up four-fold to 8%) and support vector machines (8%) gained substantial traction. Conversely, foundational deep learning architectures experienced notable relative declines: Long Short-Term Memory (LSTM) networks dropped sharply from 18% to 4%, while Convolutional Neural Networks (CNNs) decreased from 14% to 6%, indicating a transition away from generic sequence models toward hybrid, attention-gated architectures and data assimilation schemes. Traditional broad process studies, such as basin-wide evapotranspiration estimation (14% down to 6%), also saw diminished relative prominence as research shifted toward high-resolution, predictive water management.

*How topics shifted year over year*

## Cite this ranking

```
Pepkio Research Index (PRI). Topics and Trends in Most Cited Hydrology and Watershed Management Studies Papers, Class of 2026. https://pri.pepkio.com/top-papers/hydrology-and-watershed-management-studies/2026. Accessed 2026-07-29.

Zheng Su, Tinsley Li, Thematic Shifts in Early-High-Impact Cancer Genomics and Diagnostics Research: A Bibliometric and Semantic Analysis. bioRxiv 2026.07.04.736459; doi: https://doi.org/10.64898/2026.07.04.736459
```