A Model-Agnostic Representation of Prairie Pothole Hydrology: Enhancing Generality and Implementation Across Hydrological Models
Notice bibliographique
Résumé
This repository contains the HDS standalone software source code and the source codes of the following modified hydrological models, which were modified to accommodate HDS, HYPE, MESH, and SUMMA. This repository also includes the model inputs and results for the three hydrological models at the Smith Creek Research Basin (SCRB). The software and data are part of the following paper "A Model-Agnostic Representation of Prairie Pothole Hydrology: Enhancing Generality and Implementation Across Hydrological Models" submitted to Water Resources Research for publication. The source codes are also available at the following github repositories: HDS: https://github.com/CH-Earth/HDS HYPE: https://sourceforge.net/projects/hype/files/ MESH: https://github.com/MESH-Model/MESH-Dev SUMMA: https://github.com/CH-Earth/summa/tree/develop The following folders are included: HDS_standalone_code: contains the HDS standalone source code along with a hypothetical test case. HYPE: This folder contains the modified HYPE model source code (located under source_code subfolder) and model setup files and results for the comparison of HDSv1 and HDSv2 with uncalibrated model setup (located under runs/HDS_v1_v2_comparison subfolder), HYPE-ilake model (located under runs/HYPE-ilake subfolder), and HYPE-HDS model (located under runs/HYPE-HDS subfolder). MESH: This folder contains the modified MESH model source code (located under source_code subfolder) and model setup files and results for MESH-PDMROF model (located under runs/MESH-PDMROF subfolder) and MESH-HDS model (located under runs/MESH-HDS subfolder) SUMMA: This folder contains the modified SUMMA model source code (located under source_code subfolder) and model setup files and results for SUMMA-noPothole model (located under runs/SUMMA-noPothole subfolder) and SUMMA-HDS model (located under runs/SUMMA-HDS subfolder) Abstract Modelling streamflow in low-lying, flat, and pothole-dominated prairie or Arctic regions is challenging due to variable non-contributing areas that influence how runoff translates to streamflow. Several modelling approaches have been developed to represent these dynamics, but many 1) lump depressions and permit spill only after a fixed capacity is reached, 2) rely heavily on calibration, 3) are unsuitable for large basins, 4) do not account for non-pothole contributions, and/or 5) are not model-agnostic. Here we present HDSv2, a second-generation Hysteretic Depressional Storage (HDS) module that is open-source, model-agnostic, numerically robust, and grounded in long-established physical understanding of prairie potholes. HDSv2 represents dynamic contributing area and storage--discharge hysteresis, enabling realistic simulation of fill-and-spill behavior and cold-region processes. We couple HDSv2 with three hydrological and land-surface models of differing architectures: HYPE (Hydrological Predictions for the Environment), MESH (Modélisation Environnementale communautaire---Surface and Hydrology), and SUMMA (Structure for Unifying Multiple Modelling Alternatives), applied in the Smith Creek River Basin, Canada. Results show that HDSv2 improves numerical stability and process fidelity relative to the original HDS model, which exhibited instabilities affecting contributing-area simulation within HYPE. Across all host models, integrating HDSv2 produces more robust hydrographs than the original configurations and better reproduces observed relationships between depressional storage and contributing area. Although hydrograph improvements vary by host, additional performance metrics show consistent gains in both high and low flow conditions. These findings demonstrate that HDSv2 provides a transferable and scalable pathway for incorporating depressional-storage dynamics into diverse hydrological models and regions.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,051 | 0,022 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».