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    • This project contains the code required for setting up UK catchments. These can be produced using 1km ascii masks (aligned to the nearest 1000m). The project also includes functions that can be used to analysise the simulations. Simulations are set up from gridded historical climate data (CEH-GEAR and CHESS, 1980-2015) and static input data. The…
      Jupyter Notebook
      0000Updated Jan 15, 2025Jan 15, 2025
    • ngif

      Public
      Plotly Dash app to visualise and download NGIF sensor data
      Python
      1081Updated Nov 11, 2024Nov 11, 2024
    • Classification of diurnal time series patterns. Used with HUUM for parameter adjustment.
      Python
      Apache License 2.0
      0000Updated Aug 25, 2024Aug 25, 2024
    • The HUUM model system.
      Python
      Apache License 2.0
      0000Updated Aug 25, 2024Aug 25, 2024
    • HUUM_io

      Public
      IO methods for HUUM models.
      Python
      Apache License 2.0
      0000Updated Aug 25, 2024Aug 25, 2024
    • CityCAT-FrictionCoeffs-Docker
      Python
      0000Updated Jun 24, 2024Jun 24, 2024
    • Extracts Rainfall_polygon.txt file in CityCAT format from a shape file
      Python
      0000Updated May 7, 2024May 7, 2024
    • Extracts frictionCoeff.txt file in CityCAT format from a shape file
      Python
      0000Updated May 7, 2024May 7, 2024
    • Shetran

      Public
      Shetran Hydrological Model
      Fortran
      GNU General Public License v3.0
      0000Updated Mar 12, 2024Mar 12, 2024
    • FIRM

      Public
      An Agent-Based Model for Flood Incident Management
      Java
      0100Updated May 23, 2023May 23, 2023
    • Quality control procedure for hourly rainfall data
      Python
      91290Updated Jan 24, 2023Jan 24, 2023
    • Development and Baseline Models for usage with HUUM
      Python
      Apache License 2.0
      0000Updated Jan 20, 2023Jan 20, 2023
    • Scripts create/run simulations using UKCP18 drivers. These rely on pre-setup equivalent historical models for static inputs and bias control of meteorological data. Historical simulations can be setup using https://github.com/nclwater/SHETRAN-UK-Generic-Catchment-Setup-Scripts). This code was developed and used for the OpenCLIM project.
      Python
      0000Updated Nov 29, 2022Nov 29, 2022
    • Public version of the Shetran repository. Contains executables but no code
      GNU General Public License v3.0
      0200Updated Sep 23, 2022Sep 23, 2022
    • WOW

      Public
      Contains python code in jupyter notebooks for the processing of WOW data, bonus MIDAS hourly and daily rainfall processing code
      MIT License
      0000Updated Sep 22, 2022Sep 22, 2022
    • Python
      1000Updated Jun 30, 2022Jun 30, 2022
    • A Windows UI to create PDF reports from Davis WeatherLink export files
      Python
      GNU General Public License v3.0
      1002Updated Jun 27, 2022Jun 27, 2022
    • pySHETRAN

      Public
      This repository has all the code developed to create the files require to input in SHETRAN
      Python
      0000Updated Jun 23, 2022Jun 23, 2022
    • Repository containing the process for flood estimation for single site and pool method as per FEH manual
      Jupyter Notebook
      GNU General Public License v3.0
      0000Updated Mar 9, 2022Mar 9, 2022
    • Python
      1000Updated Feb 17, 2022Feb 17, 2022
    • shear-web

      Public
      Kampala Flood Risk and Weather Data Dashboard
      Python
      1200Updated Feb 17, 2022Feb 17, 2022
    • Python script that sends sensor data to the NGIF database
      Python
      1000Updated Feb 17, 2022Feb 17, 2022
    • mesacat

      Public
      Mesa Model of Flood Evacuation using OpenStreetMap
      Python
      2310Updated Feb 17, 2022Feb 17, 2022
    • citycatio

      Public
      Python package for creating CityCAT models and converting results
      Python
      GNU General Public License v3.0
      0000Updated Sep 23, 2021Sep 23, 2021
    • GUI for viewing and exporting SHETran results
      Python
      GNU General Public License v3.0
      0100Updated Jun 22, 2021Jun 22, 2021
    • Contains the functions required to extend GSDR-QC (Intense_qc) to sub-hourly data. First a frequency and resolution check ensure we only work on sub-hourly data. Second, a threshold-based check quality controls the rainfall records.
      Python
      GNU General Public License v3.0
      0100Updated May 21, 2021May 21, 2021
    • JavaScript
      1000Updated Sep 7, 2020Sep 7, 2020
    • JavaScript
      1000Updated Aug 11, 2020Aug 11, 2020
    • shetranio

      Public
      Python package for setting up SHETran models and extracting results
      Python
      GNU General Public License v3.0
      1410Updated Jul 21, 2020Jul 21, 2020