Dataset for: "From Global Exploration to Local Descent: A Massively Parallel Framework and Benchmark for Continental Hydrological Calibration"

This repository contains the comprehensive benchmark calibration results for 36 conceptual hydrological models across 559 catchments from the CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) dataset. These results were generated using the massively parallel calibration framework proposed in the associated paper: "From Global Exploration to Local Descent: A Massively Parallel Framework and Benchmark for Continental Hydrological Calibration". Repository Contents The dataset includes: Calibrated Parameters: The optimal parameter sets derived for each of the 36 models in each of the 559 catchments. Evaluation Metrics: Comprehensive performance indicators (e.g., KGE, NSE) for both the calibration (training) and validation (testing) periods. Key Statistics Models: 36 distinct hydrological model structures (dMoT framework). Study Area: 559 catchments from the CAMELS dataset (US). Method: Hybrid global-local optimization via massively parallel computing.