Difference between revisions of "Modelling tool capability overview"
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A set of commonly used modelling tools in South Africa was reviewed for the [[Model inter-comparison study (2020-21)|WRC “Critical catchment model inter-comparison and model use guidance development” project]]. This set included the major tools developed in South Africa, ACRU and the Pitman model-based tools (WRSM-Pitman and SPATSIM-Pitman), as well as two tools that were developed overseas, but have been used across various contexts globally, SWAT and MIKE-SHE. Locally developed modelling tools can have certain advantages from being designed with the South African context in mind, in terms of local data availability and local climate characteristics, ecosystems, soils and geologic types, as well as land and water management practices. SWAT and MIKE-SHE have resourced development teams behind them that help to continually update the tools and adapt them to make use of developing globally available data sources, such as remote sensing data and linked products, and generally improved access to greater computing power. This suite of tools covers a diversity of model structure and algorithm type options. | A set of commonly used modelling tools in South Africa was reviewed for the [[Model inter-comparison study (2020-21)|WRC “Critical catchment model inter-comparison and model use guidance development” project]]. This set included the major tools developed in South Africa, ACRU and the Pitman model-based tools (WRSM-Pitman and SPATSIM-Pitman), as well as two tools that were developed overseas, but have been used across various contexts globally, SWAT and MIKE-SHE. Locally developed modelling tools can have certain advantages from being designed with the South African context in mind, in terms of local data availability and local climate characteristics, ecosystems, soils and geologic types, as well as land and water management practices. SWAT and MIKE-SHE have resourced development teams behind them that help to continually update the tools and adapt them to make use of developing globally available data sources, such as remote sensing data and linked products, and generally improved access to greater computing power. This suite of tools covers a diversity of model structure and algorithm type options. | ||
| − | The two tables below summarise basic information about these tools: the first gives '''intended uses and broad structural characteristics''' and the second gives an '''overview of modelling capabilities''' across the tools that are likely to be in demand for many typical use-cases. | + | The two tables below summarise basic information about these tools: the first gives [[#Table 1 Anchor|'''intended uses and broad structural characteristics''']] and the second gives an '''overview of modelling capabilities''' across the tools that are likely to be in demand for many typical use-cases. |
{| class="wikitable" | {| class="wikitable" | ||
| − | |+Background & basic characteristics of reviewed modelling tools | + | |+<span id = "Table 1 Anchor"> Background & basic characteristics of reviewed modelling tools</span> |
! Characteristic !! WRSM-Pitman !! SPATSIM-Pitman !! ACRU !! SWAT !! MIKE-SHE | ! Characteristic !! WRSM-Pitman !! SPATSIM-Pitman !! ACRU !! SWAT !! MIKE-SHE | ||
|- | |- | ||
Revision as of 17:23, 27 April 2021
A set of commonly used modelling tools in South Africa was reviewed for the WRC “Critical catchment model inter-comparison and model use guidance development” project. This set included the major tools developed in South Africa, ACRU and the Pitman model-based tools (WRSM-Pitman and SPATSIM-Pitman), as well as two tools that were developed overseas, but have been used across various contexts globally, SWAT and MIKE-SHE. Locally developed modelling tools can have certain advantages from being designed with the South African context in mind, in terms of local data availability and local climate characteristics, ecosystems, soils and geologic types, as well as land and water management practices. SWAT and MIKE-SHE have resourced development teams behind them that help to continually update the tools and adapt them to make use of developing globally available data sources, such as remote sensing data and linked products, and generally improved access to greater computing power. This suite of tools covers a diversity of model structure and algorithm type options.
The two tables below summarise basic information about these tools: the first gives intended uses and broad structural characteristics and the second gives an overview of modelling capabilities across the tools that are likely to be in demand for many typical use-cases.
| Characteristic | WRSM-Pitman | SPATSIM-Pitman | ACRU | SWAT | MIKE-SHE |
|---|---|---|---|---|---|
| Developed in South Africa | yes | yes | yes | no | no |
| Current curator / developer | Bailey & Pitman Water Resources Ltd | Rhodes University, Institute of Water Resources (IWR) | University of KwaZulu Natal,
Centre for Water Resources Research (UKZN-CWRR) |
Texas A&M University &
US Department of Agriculture (USDA) |
Danish Hydrologic Institute (DHI) |
| Free access | yes | yes | yes | yes | no |
| Version reviewed | WRSM-Pitman version 2.9 | SPATSIM GWv3 Global Options Threaded model | ACRU 4 | SWAT & ArcSWAT 2012 | MIKE-SHE & MIKE Hydro River, version 2017 |
| Reference documents | Theory manual: (Bailey, 2015);
User manual: (Bailey and Pitman, 2016) |
Theory papers: (Hughes, 2004, 2013; Kapangaziwiri, 2007);
User manual: (Hughes, 2019) |
Theory manual: (Schulze, 1995);
User manuals: (Clark et al., 2012; Schulze and Davis, 2018) |
Theory manual: (Neitsch et al., 2011);
User manuals: (Arnold et al., 2012) |
Theory manuals:(DHI, 2017a, 2017b);
User’s manuals:(DHI, 2017d, 2017c) |
| Intended spatial scale
(catchment or model area) |
Local to regional:
no suggested min-max model size |
Local to regional:
10-10,000’s of km2, more typical: 100-1,000’s km2 |
Field to regional:
no suggested min-max model size |
Field to regional:
no suggested min-max model size |
Field to regional:
no suggested min-max model size |
| Spatial discretisation | Modules ('runoff' modules/subcatchments,
special sub-areas, channels, reservoirs) linked by routes |
Subcatchments + limited internal sub-area types | HRUs within subcatchments | HRUs within subcatchments | Fully distributed (gridded)
OR combinations of grids and zones for different process calculations within subcatchments (if all process zones align, would act like HRUs) |
| Intended subcat size < 1,000 km2 | Intended subcat size 5-50 km2;
HRU size < 30km2 |
||||
| Timestep | Monthly* | Monthly* | Daily | Daily, sub-daily | Daily, sub-daily
(dynamic timestep length, can vary across processes) |
| Intended modelling applications (as documented): | |||||
| Water balance estimation | yes | yes | yes | yes | yes |
| Design hydrology (flood peaks) | yes | yes | yes | ||
| Supply planning (general) | yes | yes | yes | yes | yes |
| Reservoir yield | yes | yes | yes | yes | yes |
| Irrigation planning | yes | yes | yes | yes | |
| Groundwater recharge | yes | yes | yes | yes | yes |
| Groundwater-surface water (GW-SW) interactions & pumping impacts | yes | yes | yes | ||
| Land cover change impacts | yes | yes | yes | yes | yes |
| Climate change impacts | yes | yes | yes | yes | yes |
| Application limitations (as documented) | Not for peak flow, flood assessment, or design hydrology | Not for peak flow, flood assessment, design hydrology | Not represent deep GW processes - not for GW pumping impact | Not represent deep GW processes | (None listed for the modelling system
as whole, only for certain process representation options.) |
| Specific development focuses particular to tool |
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