The Coupled Hydrology–Human Activity Information (CHHAI) Dataset: A Global Benchmark Dataset for Model Comparison and Evaluation

Authors

• Azara Boschee, Samueli School of Engineering
• Aneseh Alborzi, Samueli School of Engineering
• Augustina Clara Alexander, University of Dar es Salaam
• Berit Arheimer, Swedish Meteorological and Hydrological Institute
• Salsebil Bel Hadj Ali, Ecole Supérieure des Ingénieurs de Medjez El Bab
• Günter Blöschl, TU Wien
• Andrea Castelletti, Politecnico di Milano
• Xi Chen, University of Cincinnati
• Aniya Dogra, San Jose State University
• Erhu Du, Hohai University
• Jesse Duku, Samueli School of Engineering
• Aldo Fiori, Università degli Studi Roma Tre
• Margaret Garcia, Ira A. Fulton Schools of Engineering
• Salvatore Grimaldi, Università degli Studi della Tuscia Viterbo
• Naota Hanasaki, The University of Tokyo
• Yeonjoo Kim, Yonsei University
• Heidi Kreibich, GFZ Helmholtz Centre for Geosciences
• Chenyuan Li, Institute of Atmospheric Physics Chinese Academy of Sciences
• Ali Mehran, San Jose State UniversityFollow
• For full author list, see comments below

Publication Date

7-4-2026

Document Type

Article

Publication Title

Hydrological Sciences Journal

Volume

71

Issue

10

DOI

10.1080/02626667.2026.2663050

First Page

2031

Last Page

2043

Abstract

To enhance hydrologic modeling, the hydrology community has developed benchmark datasets (e.g. Model Parameter Estimation Experiment, MOPEX), providing standardized data for model evaluation and parameter estimation. However, these datasets primarily focus on modeling natural hydrologic processes, leaving a critical gap in understanding the role of human influences. Here, we introduce the Coupled Hydrology-Human Activity Information (CHHAI) dataset, a benchmark dataset that integrates coupled human–water data from regions across all continents, excluding Antarctica. CHHAI incorporates data from 25 regions that cover various human impacts such as reservoir management, flood protection, river management policies, land use changes, and water use. Each basin reflects distinct challenges, providing a diverse and globally representative resource for researchers studying these processes. By offering standardized datasets for modeling and analysis, CHHAI aims to enhance our understanding of interactions between people and water and to support the development of improved strategies for managing coupled human–water systems.

Funding Number

DGE2235784

Funding Sponsor

National Science Foundation

Keywords

Coupled human–water systems, hydrologic data, sociohydrologic modeling, sociohydrology

Comments

Full author list:

Azara Boschee, Aneseh Alborzi, Augustina Clara Alexander, Berit Arheimer, Salsebil Bel Hadj Ali, Günter Blöschl, Andrea Castelletti, Xi Chen, Aniya Dogra, Erhu Du, Jesse Duku, Aldo Fiori, Margaret Garcia, Salvatore Grimaldi, Naota Hanasaki, Yeonjoo Kim, Heidi Kreibich, Chenyuan Li, Mir Matin, Pedro Medeiros, Ali Mehran, Antônio Alves Meira Neto, Fuko Nakai, Shinichiro Nakamura, Phu Nguyen, Joel Nobert, Afua Owusu, Saritha Padiyedath Gopalan, Bruno Pereira, Parsa Pouladi, Mehrsa Pouladi, Mahendran Roobavannan, Mojtaba Sadegh, Matteo Sangiorgio, Lukas Schoppa, Ashish Shrestha, Murugesu Sivapalan, Deborah Sousa, Sai Veena Sunkara, Fuqiang Tian, Fatma Trabelsi, Naga Velpuri, Elena Volpi, Jiale Wang, Shuo Wang, Jiefeng Wu, Xing Yuan, and Amir AghaKouchak

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Department

Civil and Environmental Engineering

Recommended Citation

Boschee, A., Alborzi, A., Alexander, A. C., Arheimer, B., Bel Hadj Ali, S., Blöschl, G., … AghaKouchak, A. (2026). The coupled hydrology–human activity information (CHHAI) dataset: a global benchmark dataset for model comparison and evaluation. Hydrological Sciences Journal, 71(10), 2031–2043. https://doi.org/10.1080/02626667.2026.2663050