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).

Last updated 4 years ago

7.10 score 11 stars 77 scripts 330 downloads

CSHShydRology - Canadian Hydrological Analyses

A collection of user submitted functions to aid in the analysis of hydrological data.

Last updated 3 years ago

5.26 score 4 stars 23 scripts 324 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>).

Last updated 13 days ago

4.70 score 1 stars

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>).

Last updated 20 days ago

4.00 score

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>.

Last updated 1 years ago

2.70 score 3 scripts 198 downloads