HydroCNHS: A Python Package of Hydrological Model for Coupled Natural–Human Systems
Publication: Journal of Water Resources Planning and Management
Volume 148, Issue 12
Abstract
Modeling coupled natural–human systems (CNHS) to inform comprehensive water resources management policies or describe hydrological cycles in the Anthropocene has become popular in recent years. To fulfill this need, we developed a semidistributed hydrological model for coupled natural–human systems, HydroCNHS. HydroCNHS is an open-source Python package supporting four application programming interfaces (APIs) that enable users to integrate their human decision models, which can be programmed with the agent-based modeling concept, into HydroCNHS. Specifically, we designed Dam API, RiverDiv API, Conveying API, and InSitu API to integrate, respectively, customized man-made infrastructures such as reservoirs, off-stream diversions, transbasin aqueducts, and drainage systems that abstract human behaviors (e.g., operator and farmer water use decisions). Each of the HydroCNHS APIs has a unique plug-in structure that respects within-subbasin and inter-subbasin (i.e., river) routing logic for maintaining the water balance. In addition, HydroCNHS uses a single model configuration file to organize input features for the hydrological model and case-specific human systems models. Also, HydroCNHS enables model calibration using parallel computing power. We demonstrate the functionalities of the HydroCNHS package through a case study in the Northwest United States. Given the integrity of the modeling framework, HydroCNHS can benefit water resources planning and management in various aspects, including uncertainty analysis in CNHS modeling and more complex agent design.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article. The HydroCNHS Python package was developed under Python 3.8. The code, user manual, and TRB example (including input data) can be downloaded at https://github.com/philip928lin/HydroCNHS. The weather data originated from Livneh et al. (2015). The streamflow and Hagg reservoir were obtained from the US Bureau of Reclamation Hydromet platform (https://www.usbr.gov/pn/hydromet/tuatea.html) and Bonn (2020). Detailed station information is provided in Table S1 .
Acknowledgments
The work described in this paper was supported by the US National Science Foundation (NSF): CBET #1941727. We thank the editor, the associate editor, and two anonymous reviewers for their comments and suggestions to improve the quality of the manuscript.
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Journal of Water Resources Planning and Management
Volume 148 • Issue 12 • December 2022
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© 2022 American Society of Civil Engineers.
History
Received: Feb 13, 2022
Accepted: Aug 27, 2022
Published online: Oct 13, 2022
Published in print: Dec 1, 2022
Discussion open until: Mar 13, 2023
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