MIKE SHE Public Data Catalog
India
Version: 0.1 test template
Purpose: Country-specific public dataset catalog for building simple to advanced MIKE SHE models
Region: Republic of India
Quick Start
Minimum Public Datasets for Recharge Modelling with MIKE SHE (India)
If your objective is to calculate distributed groundwater recharge (without simulating groundwater flow or rivers), only five dataset categories are required.
India has strong national gridded rainfall and groundwater datasets. Large-scale topographic maps were historically restricted; the National Geospatial Policy 2022 has liberalized access, but high-resolution data may still require requests.
| MIKE SHE Input |
Dataset Type |
Recommended Dataset |
Spatial Availability |
Why recommended |
| Topography (DEM) |
Gridded |
Bhuvan (NRSC/ISRO) CartoDEM
Copernicus GLO-30 |
India / global |
CartoDEM (~30 m) is the national DEM; Copernicus GLO-30 is often more accurate and easier to process. |
| Land Cover |
Gridded |
Bhuvan (NRSC/ISRO) LULC (1:50,000)
ESA WorldCover |
India |
National land-use/land-cover with Indian agricultural classes (kharif, rabi, double-cropped). |
| Soil Hydraulic Properties |
Vector / gridded |
NBSS&LUP soil maps
SoilGrids |
India |
NBSS&LUP soil maps (1:250,000 state-wise, more detailed in places); SoilGrids for gridded texture. |
| Precipitation |
Gridded |
IMD gridded rainfall (IMD Pune) (0.25°, daily, since 1901) |
India |
Gauge-based national gridded rainfall with a very long record — the standard for Indian hydrology. |
|
Gridded |
GPM IMERG / GSMaP |
Global |
Sub-daily rainfall for flood events. |
| Meteorological Forcing / Potential ET |
Gridded |
IMDAA regional reanalysis (NCMRWF)
ERA5-Land |
India / global |
IMDAA (~12 km) is a regional reanalysis for India; ERA5-Land for hourly variables. IMD gridded temperature is also available. |
|
Time Series |
IMD station data (Data Supply Portal) |
Stations |
Usually charged; free for some research. |
Optional Improvements
Recommended Workflow
- Download Copernicus GLO-30 or CartoDEM for the model domain.
- Delineate the model domain and prepare the terrain model.
- Download Bhuvan LULC and assign MIKE SHE vegetation classes.
- Download NBSS&LUP or SoilGrids and derive van Genuchten parameters using pedotransfer functions.
- Choose your meteorological forcing:
- Option A (recommended): Use IMD gridded rainfall and IMDAA/ERA5-Land for other variables.
- Option B: Use IMD station data.
- Let MIKE SHE calculate evapotranspiration internally using the selected vegetation and soil parameters.
- Represent kharif and rabi cropping seasons and groundwater irrigation.
- Check simulated actual ET against MODIS MOD16 or SSEBop.
- Export the distributed groundwater recharge for use in MODFLOW, FEFLOW, or other groundwater models.
1. Introduction for advanced data sources
1.1 Purpose
This document summarizes public datasets that can be used to construct a physically based MIKE SHE model for India.
The catalog is organized according to the typical MIKE SHE model-building workflow. It covers terrain, land cover, meteorological forcing, ET, rivers, soils, hydrogeology, groundwater, water management, and calibration.
1.2 Intended Use
This catalog is intended for:
- groundwater depletion and recharge studies
- managed aquifer recharge assessments
- river basin water-balance models
- flood studies
- irrigation command-area studies
- applied MIKE SHE model setup
1.3 General Notes for India
- Water is a state subject; state groundwater and irrigation departments hold much of the detailed data.
- Coordinate systems: WGS 84 / UTM 42N–47N (legacy Everest 1830 in older maps).
- The National Geospatial Policy 2022 has eased access to geospatial data, but defence-sensitive areas remain restricted.
2. Hydrological Characteristics of India
2.1 Climate
- south-west monsoon (June–September) delivering 70–90% of annual rainfall in most regions
- north-east monsoon in Tamil Nadu and south-east coast
- annual rainfall from under 200 mm (Thar Desert) to more than 10,000 mm (Meghalaya)
- Himalayan snow and glacier melt in the north
- high year-to-year monsoon variability
2.2 Topography
- Himalaya and northern mountains
- Indo-Gangetic Plain
- Deccan Plateau and peninsular uplands
- Western and Eastern Ghats
- coastal plains and deltas
- Thar Desert
2.3 Major Hydrological Challenges
- groundwater depletion in north-west India (Punjab, Haryana, Rajasthan)
- limited storage in hard-rock aquifers
- floods (e.g. Brahmaputra, Kosi, Kerala 2018)
- groundwater quality (arsenic, fluoride, salinity)
- urban water scarcity
- interstate water sharing
2.4 Major Aquifer Systems
Important aquifer settings include:
- Indo-Gangetic alluvial aquifers
- Deccan basalt aquifers
- crystalline hard-rock aquifers of the peninsula
- coastal and deltaic aquifers
- Himalayan and hill aquifers with springs
3. Recommended Dataset Stack
4. Terrain Model
4.1 Purpose in MIKE SHE
Terrain data are required for model surface elevation, overland-flow gradients, surface storage, catchment delineation, river network verification, and floodplain connectivity.
4.2 Dataset Comparison
| Dataset |
Coverage |
Resolution |
MIKE SHE Suitability |
Advantages |
Limitations |
Recommendation |
| Copernicus GLO-30 |
Global |
30 m |
Primary |
Accurate |
— |
★★★★★ |
| Bhuvan (NRSC/ISRO) CartoDEM |
India |
~30 m |
Alternative |
National |
Artefacts |
★★★☆☆ |
| FABDEM |
Global |
30 m |
Forested areas |
Canopy removed |
Licence |
★★★☆☆ |
4.3 Typical Preprocessing
- reproject to UTM (zones 42N–47N)
- clip to model domain plus buffer
- condition drainage and check against the river network
- resample to model grid
- smooth only where needed for numerical stability
4.4 Quality Checks
- check flat Gangetic plains for drainage artefacts
- check canal embankments
5. Surface Water
5.1 Rivers
| Dataset |
Coverage |
MIKE SHE / MIKE 1D Use |
Advantages |
Limitations |
Recommendation |
| India-WRIS |
India |
Rivers, basins, gauges |
Official |
Some data restricted |
★★★★★ |
| MERIT Hydro |
Global |
Flow directions |
Consistent |
90 m |
★★★★☆ |
5.2 Lakes, Reservoirs and Wetlands
5.3 Tanks and Check Dams
- traditional tanks and many check dams in peninsular India strongly affect recharge
- map them from JRC Global Surface Water and Sentinel-2
5.4 Typical Preprocessing
- simplify river network
- align river network with DEM
- define channel geometry from surveys or estimated widths
- represent floodplains and wetlands as overland-flow storage
- assign river, reservoir and tidal boundary conditions
6. Land Cover and Vegetation
6.1 Purpose in MIKE SHE
Land cover and vegetation define interception, ET parameters, root depth, crop coefficients, Manning roughness, irrigation zones, and impervious areas.
6.2 Dataset Comparison
| Dataset |
Coverage |
Resolution |
MIKE SHE Use |
Advantages |
Limitations |
Recommendation |
| Bhuvan (NRSC/ISRO) LULC |
India |
1:50,000 |
Primary |
Indian crop classes |
Snapshot years |
★★★★★ |
| ESA WorldCover |
Global |
10 m |
Detail |
Consistent |
2020–2021 |
★★★★☆ |
6.3 Vegetation Datasets
| Parameter |
Dataset |
Use |
Recommendation |
| LAI |
MODIS MCD15A3H |
Seasonal LAI |
★★★★☆ |
| NDVI |
Sentinel-2 / Landsat |
Crop calendars and phenology |
★★★★☆ |
| Crop coefficient |
FAO-56 |
Rice, wheat, cotton, sugarcane, pulses |
★★★★☆ |
6.4 Typical Preprocessing
- separate kharif, rabi and double-cropped areas
- identify groundwater- and canal-irrigated areas
7. Meteorological Forcing
7.1 Precipitation
| Dataset |
Coverage |
Resolution |
Temporal Resolution |
MIKE SHE Use |
Advantages |
Limitations |
Recommendation |
| IMD gridded rainfall (IMD Pune) |
India |
0.25° |
Daily |
Primary |
Gauge-based, since 1901 |
Coarse for small basins |
★★★★★ |
| GPM IMERG |
Global |
~10 km |
30 min |
Events |
Sub-daily |
Bias |
★★★★☆ |
| CHIRPS |
50°S–50°N |
~5 km |
Daily |
Alternative |
Higher resolution |
Bias in mountains |
★★★☆☆ |
| APHRODITE |
Monsoon Asia |
0.25° |
Daily |
History |
Gauge-based |
Ends 2015 |
★★☆☆☆ |
7.2 Climate Variables
7.3 Notes
- use IMD gridded temperature for long records
- include snow and glacier melt in Himalayan basins
8. Soil Data
8.1 Dataset Comparison
| Dataset |
Coverage |
Resolution |
MIKE SHE Use |
Advantages |
Limitations |
Recommendation |
| NBSS&LUP soil maps |
India |
1:250,000 (more detailed in places) |
Primary zonation |
National |
Access varies |
★★★★☆ |
| SoilGrids |
Global |
250 m |
Gridded |
Consistent |
Less local |
★★★☆☆ |
8.2 Typical Preprocessing
- treat black cotton soils (vertisols) with shrink–swell behaviour
- derive parameters with pedotransfer functions
9. Hydrogeology
9.1 Dataset Comparison
9.2 Conceptual Model Recommendations
- thick alluvial aquifers in the north
- weathered and fractured hard rock with limited storage
- basalt aquifers with layered flows
- coastal saline interfaces
10. Groundwater Data
| Dataset |
Coverage |
Use |
Recommendation |
| India-WRIS / Central Ground Water Board |
India |
Monitoring wells (measured several times per year) |
★★★★★ |
| State groundwater departments |
States |
Denser monitoring |
★★★★★ |
| INGRES |
India |
Recharge and extraction estimates |
★★★★☆ |
11. Water Management
11.1 Relevant Processes
- groundwater irrigation from millions of wells
- canal irrigation commands
- reservoirs and interbasin transfers
- managed aquifer recharge (check dams, tanks)
11.2 Regulatory Framework
- water is a state subject under the Constitution
- Central Ground Water Authority regulates abstraction (no-objection certificates)
- Atal Bhujal Yojana for community groundwater management
11.3 Key Institutions
12. Remote Sensing Products
13. Calibration Datasets
Recommended strategy: calibrate pre- and post-monsoon heads with pumping estimates; check regional trends against GRACE.
14. Typical MIKE SHE Workflow
- Define modelling objective and domain.
- Prepare the DEM from Copernicus GLO-30.
- Build the river network from India-WRIS.
- Prepare land cover from Bhuvan LULC.
- Assign vegetation parameters, rooting depths and crop calendars.
- Prepare precipitation from IMD gridded rainfall.
- Prepare climate forcing and reference ET from IMDAA or ERA5-Land.
- Prepare soil properties from NBSS&LUP and SoilGrids.
- Build hydrogeological layers from CGWB aquifer maps.
- Add pumping and irrigation from INGRES and state data.
- Couple rivers and groundwater.
- Calibrate against CGWB heads and discharge.
- Validate with GRACE and ET products.
- Document assumptions and uncertainties.
15. Minimum Dataset Package
16. Recommended Dataset Package
17. Premium Dataset Package
| Dataset Type |
Possible Source |
Purpose |
| State monitoring data |
State groundwater departments |
Dense heads |
| Well census |
Minor Irrigation Census |
Pumping |
| Pumping tests |
CGWB / projects |
Parameters |
18. Dataset Comparison Table Template
| Dataset |
Coverage |
Spatial Resolution |
Temporal Resolution |
Time Period |
Format |
API / Access |
License |
MIKE SHE Use |
Advantages |
Limitations |
Recommendation |
|
|
|
|
|
|
|
|
|
|
|
★☆☆☆☆ |
19. Data Preparation Checklist
Terrain
- [ ] DEM downloaded (or requested) and licence checked
- [ ] DEM projected and clipped
- [ ] drainage checked against river network
Surface Water
- [ ] river network prepared
- [ ] reservoirs, wetlands and floodplains identified
- [ ] boundary conditions assigned
Land Cover and Vegetation
- [ ] land cover reclassified
- [ ] irrigated areas and crop calendars defined
- [ ] LAI and rooting depths assigned
Weather
- [ ] precipitation prepared and compared with station data
- [ ] climate forcing prepared
- [ ] reference ET calculated
Soil
- [ ] soil data downloaded or requested
- [ ] hydraulic parameters derived
Groundwater
- [ ] geology and hydrogeology collected
- [ ] heads and pumping data requested
- [ ] boundary conditions defined
Calibration and Validation
- [ ] discharge data obtained
- [ ] ET and remote-sensing validation data prepared
- [ ] calibration and validation periods defined
India-specific
- [ ] state data requests made
- [ ] cropping seasons defined
20. References and Official Data Portals
National and regional sources
Global sources
21. Notes on Uncertainty
- unmetered groundwater pumping
- monsoon variability
- hard-rock heterogeneity
- tank and check-dam recharge
- restricted data in border areas
A defensible model should document dataset choices, preprocessing assumptions, calibration strategy, validation results, and known limitations.
22. Key Regional Settings
Detailed data are held by state groundwater, irrigation and water resources departments.
| Region |
Key States |
Hydrological Focus |
| North-west |
Punjab, Haryana, Rajasthan |
Groundwater depletion, canal irrigation |
| Indo-Gangetic Plain |
Uttar Pradesh, Bihar, West Bengal |
Alluvial aquifers, floods, arsenic |
| Peninsular hard rock |
Maharashtra, Karnataka, Telangana, Andhra Pradesh, Tamil Nadu |
Limited storage, tanks, managed recharge |
| Coastal |
Gujarat, Tamil Nadu, Kerala, Odisha |
Seawater intrusion, deltas |
| Himalaya and North-east |
Himachal, Uttarakhand, Assam, Meghalaya |
Snowmelt, springs, Brahmaputra floods |