From 658aa588e4f9490c284f6550c4557d02bb99d4de Mon Sep 17 00:00:00 2001 From: Chung-Yi Lin Date: Sun, 3 Nov 2024 01:33:15 -0400 Subject: [PATCH] correct link --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index f939cc5..3e5c1e4 100644 --- a/README.md +++ b/README.md @@ -4,7 +4,7 @@ # HydroCNHS A Python Package of Hydrological Model for Coupled Natural–Human Systems -Complex Adaptive Water System +Complex Adaptive Water System 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 semi-distributed Hydrological model for Coupled Natural–Human Systems, HydroCNHS. The 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 the HydroCNHS. Specifically, we design Dam API, RiverDiv API, Conveying API, and InSitu API to integrate, respectively, customized man-made infrastructures such as reservoirs, off-stream diversions, trans-basin aqueducts, and drainage systems that abstract human behaviors (e.g., operator and farmers’ 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, the HydroCNHS uses a single model configuration file to organize input features for the hydrological model and case-specific human systems models. Also, HydroCNHS enables the 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 the uncertainty analysis in CNHS modeling and more complex agent design.