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CoSMoS - Complete Stochastic Modelling Solution

Makes univariate, multivariate, or random fields simulations precise and simple. Just select the desired time series or random fields’ properties and it will do the rest. CoSMoS is based on the framework described in Papalexiou (2018, <doi:10.1016/j.advwatres.2018.02.013>), extended for random fields in Papalexiou and Serinaldi (2020, <doi:10.1029/2019WR026331>), and further advanced in Papalexiou et al. (2021, <doi:10.1029/2020WR029466>) to allow fine-scale space-time simulation of storms (or even cyclone-mimicking fields).

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cppopenmp

7.54 score 15 stars 77 scripts 501 downloads

CSHShydRology - Canadian Hydrological Analyses

A collection of user-submitted functions to aid in the analysis of hydrological data, particularly for users in Canada. The functions focus on the use of Canadian data sets, and are suited to Canadian hydrology, such as the important cold region hydrological processes and will work with Canadian hydrological models. The functions are grouped into several themes, currently including Statistical hydrology, Basic data manipulations, Visualization, and Spatial hydrology. Functions developed by the Floodnet project are also included. CSHShydRology has been developed with the assistance of the Canadian Society for Hydrological Sciences (CSHS) which is an affiliated society of the Canadian Water Resources Association (CWRA). As of version 1.2.6, functions now fail gracefully when attempting to download data from a url which is unavailable.

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5.32 score 4 stars 26 scripts 602 downloads

CMIP6VisR - Visualization and Analysis of Coupled Model Intercomparison Project, Phase-6 (CMIP6) Hydroclimatic Data

Data manipulation for Coupled Model Intercomparison Project, Phase-6 (CMIP6) hydroclimatic data. The files are archived in the Federated Research Data Repository (FRDR) (Rajulapati et al, 2024, <doi:10.20383/103.0829>). The data set is described in Abdelmoaty et al. (2025, <doi:10.1038/s41597-025-04396-z>).

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4.30 score 2 stars 276 downloads

HGDMr - Hysteretic and Gatekeeping Depressions Model

Implementation of the Hysteretic and Gatekeeping Depressions Model (HGDM) which calculates variable connected/contributing areas and resulting discharge volumes in prairie basins dominated by depressions ("slough" or "potholes"). The small depressions are combined into a single "meta" depression which explicitly models the hysteresis between the storage of water and the connected/contributing areas of the depressions. The largest (greater than 5% of the total depressional area) depression (if it exists) is represented separately to model its gatekeeping, i.e. the blocking of upstream flows until it is filled. The methodolgy is described in detail in Shook and Pomeroy (2025, <doi:10.1016/j.jhydrol.2025.132821>).

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3.70 score 259 downloads

gumboot - Bootstrap Analyses of Sampling Uncertainty in Goodness-of-Fit Statistics

Uses jackknife and bootstrap methods to quantify the sampling uncertainty in goodness-of-fit statistics. Full details are in Clark et al. (2021), "The abuse of popular performance metrics in hydrologic modeling", Water Resources Research, <doi:10.1029/2020WR029001>.

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2.70 score 5 scripts 368 downloads