Skip to main content
PyPI Version DOI Tests Status

The Soil Moisture Accounting and Routing for Transport [SMART] model (Mockler et al., 2016) is a bucket-type rainfall-runoff model.

SMART is an enhancement of the SMARG (Soil Moisture Accounting and Routing with Groundwater) lumped, conceptual rainfall–runoff model developed at National University of Ireland, Galway (Kachroo, 1992), and based on the soil layers concept (O’Connell et al., 1970; Nash and Sutcliffe, 1970). Separate soil layers were introduced to capture the decline with soil depth in the ability of plant roots to extract water for evapotranspiration. SMARG was originally developed for flow modelling and forecasting and was incorporated into the Galway Real-Time River Flow Forecasting System [GFFS] (Goswami et al., 2005). The SMART model reorganised and extended SMARG to provide a basis for water quality modelling by separating explicitly the important flow pathways in a catchment.

The surface layer component of SMART consists in meeting the potential evapotranspiration demand either with rainfall alone under energy-limited conditions or with rainfall and soil moisture under water-limited conditions – throughfall is only generated under energy-limited conditions. Note, unlike the original SMART model, this component calculates the available soil moisture from the soil water stress coefficient provided by the sub-surface component – in the original SMART model, the available soil moisture is iteratively depreciated with soil layer depth. This unavoidable simplification may overestimate the soil moisture available compared to the original SMART model.

The sub-surface component of SMART comprises the runoff generation and land runoff routing processes. This sub-surface component is made up of six soil layers of equal depth and five linear reservoirs. The six soil layers are vertically connected to allow for percolation and evaporation. The five linear reservoirs represent the different pathways for land runoff. Note, the river routing of SMART is not included in this component.

The open water component of SMART consists in routing the streamflow through the river network by means of a linear reservoir.

contributors:

Thibault Hallouin [1,2], Eva Mockler [1,3], Michael Bruen [1]

affiliations:
  1. Dooge Centre for Water Resources Research, University College Dublin

  2. Department of Meteorology, University of Reading

  3. Ireland’s Environmental Protection Agency

licence:

GPL-3.0

copyright:

2020, University College Dublin

codebase:

https://github.com/unifhy-org/unifhycontrib-smart

How to install

This package is available on PyPI, so you can simply run:

pip install unifhycontrib-smart

Metadata

Release files for unifhycontrib-smart 0.1.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for unifhycontrib-smart 0.1.1
File Size Uploaded
unifhycontrib-smart-0.1.1.tar.gz 7.9 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for unifhycontrib-smart 0.1.1
File Interpreter ABI Platform
unifhycontrib_smart-0.1.1-py3-none-any.whl Python 3 none any Details

Total release size: 19.5 kB

Release files / unifhycontrib-smart-0.1.1.tar.gz

Download URL unifhycontrib-smart-0.1.1.tar.gz
Size 7.9 kB
Tags Source
SHA-256 checksum
How to use checksums
d6507a59357d531adbec59ce77df59af8fe2bca5b02f1327d5da2a0a65e218e3
BLAKE2b-256 checksum
How to use checksums
3249905dc350f31eb85aef6c9e02c7c2aa430414d0b20c3491376f628e9996d7
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.0 CPython/3.8.5

Release files / unifhycontrib_smart-0.1.1-py3-none-any.whl

Download URL unifhycontrib_smart-0.1.1-py3-none-any.whl
Size 11.6 kB
Tags Python 3
SHA-256 checksum
How to use checksums
f6846dcf96c571e8ec8b2686fe8f7ec6a079b8c2835caae4e183d5bf9fe1cb96
BLAKE2b-256 checksum
How to use checksums
8e9471915148985f4ea15627b1c3828c1e21da7efb2aae9a7cb092f18abd7fb7
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.0 CPython/3.8.5

Release history Release notifications | RSS feed

This release

0.1.1 This release

2 release files

0.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page