Minimum Required Datasets¶
One of the most common questions when starting a new MIKE SHE project is which datasets are required to define an appropriate model domain. Fortunately, a meaningful recharge model can already be established with only a limited number of publicly available datasets. Additional datasets can be incorporated later as the project progresses and more information becomes available.
A model domain should therefore not be regarded as a fixed entity that must be perfectly defined before a project begins. Instead, it should be considered an iterative component of the modelling workflow that evolves together with the understanding of the hydrological and hydrogeological system.
This is particularly important during the tendering phase of a project. Public tenders often describe the hydrological problem that needs to be addressed but do not provide a predefined model domain. In such situations, publicly available datasets are usually sufficient to obtain a first understanding of the catchment and to draft a preliminary model domain for the proposal. At this stage, the model domain does not need to be highly accurate. Its purpose is to demonstrate the intended modelling approach and to estimate the required modelling effort.
Once the project has been awarded, the preliminary model domain can be refined as additional information becomes available. In many projects, the understanding of the hydrological and hydrogeological system improves continuously throughout the modelling process, making adjustments to the model domain both common and expected.
One of the major advantages of MIKE SHE is that the active model domain is defined only during the preprocessing and model setup. As a result, the model domain can easily be modified throughout the project without requiring the entire preprocessing workflow to be repeated from scratch. The only prerequisite is that the preprocessing has been performed using a sufficiently large Data Collection Mask, which defines the overall area for which all spatial datasets have been prepared. Choosing an appropriately sized Data Collection Mask therefore provides the flexibility to expand or refine the active model domain later in the project with minimal additional effort. The workflow for creating the Data Collection Mask is described in the chapter Data Collection Mask.
The following sections describe the minimum datasets recommended for defining an initial model domain.
Building a MIKE SHE model focusing on surface water processes¶
If the objective is to simulate surface water processes or groundwater recharge only, without activating and using the full three-dimensional groundwater flow module of MIKE SHE, the model domain can generally be derived from the surface water catchment.
The minimum recommended datasets are:
- A Digital Elevation Model (DEM) representing the land surface.
- Major rivers and streams defining the primary drainage network.
- Official surface water catchment boundaries, if available.
These datasets are generally sufficient to delineate a suitable model domain. The preprocessing workflow for deriving the the model domain and a suitable preprocessing mask is described in:
Building a fully integrated catchment model in MIKE SHE¶
If the model is intended to represent the whole surface and subsurface catchment incl. the full 3D groundwater component, the model domain should also consider regional groundwater flow conditions.
In addition to the datasets listed above, the following information is recommended:
- Official groundwater contour (isoline) maps, preferably representing long-term average groundwater heads.
- Official groundwater catchments or groundwater body boundaries, if available.
- Hydrogeological maps describing the principal aquifers and geological units.
Even groundwater contour maps with contour intervals of 5–10 m are often sufficient to obtain a first understanding of regional groundwater flow directions and groundwater divides. These datasets help define a model domain that minimizes artificial groundwater boundary effects and provides a physically meaningful basis for future groundwater simulations.
If no groundwater contour maps are available, a useful first approximation can often be generated by interpolating available groundwater monitoring data. Even sparse long-term groundwater observations can provide valuable information when combined with the Digital Elevation Model and regional hydrogeological knowledge.
Finding Public Datasets¶
Many of the datasets described above are publicly available.
The Resources section of this manual provides an overview of recommended data sources, including:
- Global Datasets based primarily on satellite observations and global remote sensing products.
- Regional Datasets, including European datasets such as CORINE Land Cover and other continental-scale products.
- National Datasets, organised by country and, where appropriate, by federal state or regional authority.
These collections are continuously expanded and provide a convenient starting point for assembling the minimum datasets required for a new project.
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Contributing New Data Sources¶
The Resources section is intended to grow continuously.
If you know of additional public datasets for your country, or if you would like to contribute new national or regional data sources, please contact the current MIKE SHE Business Owner:
Philipp Huttner
DHI – MIKE SHE Business Owner
phhu@dhigroup.com
Community contributions help to continuously improve the documentation and make it easier for new users worldwide to start modelling with MIKE SHE.
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