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MIKE SHE Public Data Catalog

Papua New Guinea

Version: 0.1 test template
Purpose: Country-specific public dataset catalog for building simple to advanced MIKE SHE models
Region: Papua New Guinea (mainland New Guinea east of 141°E, Bismarck Archipelago, Bougainville and other islands)

Quick Start

Minimum Public Datasets for Recharge Modelling with MIKE SHE (Papua New Guinea)

If your objective is to calculate distributed groundwater recharge (without simulating groundwater flow or rivers), only five dataset categories are required.

National public datasets are scarce in Papua New Guinea, so the recommended stack relies mainly on free global datasets that cover the whole country. Local data held by government agencies, mining operators and development projects should be requested wherever possible.

MIKE SHE Input Dataset Type Recommended Dataset Spatial Availability Why recommended
Topography (DEM) Gridded FABDEM Global Copernicus-based 30 m DEM with forest canopy and buildings removed, which is essential in Papua New Guinea's dense rainforest, where surface models overestimate ground elevation by tens of metres.
Land Cover Gridded ESA WorldCover Global 10 m land cover for 2020 and 2021, suitable for assigning forest, grassland, cropland, wetland and settlement classes.
Soil Hydraulic Properties Gridded SoilGrids Global 250 m soil texture, bulk density and organic carbon at six depth intervals. Van Genuchten parameters must be derived with pedotransfer functions.
Precipitation Gridded CHIRPS for daily, long-term modelling

GPM IMERG or GSMaP for sub-daily modelling		 Global (tropics fully covered) CHIRPS provides daily rainfall from 1981 at ~5 km, blended with available gauges. IMERG and GSMaP provide half-hourly or hourly satellite rainfall at ~10 km for storm events.
Time Series NOAA GHCN-Daily

PNG National Weather Service and project gauges		 Sparse station network Useful for checking and bias-correcting satellite rainfall where records exist. Mining and hydropower operators often hold the only reliable long-term local records.
Meteorological Forcing / Potential ET Gridded ERA5-Land

TerraClimate for monthly checks		 Global ERA5-Land provides hourly temperature, humidity, wind and radiation for calculating FAO-56 reference ET. TerraClimate provides a monthly ~4 km reference ET for plausibility checks.
Time Series NOAA GHCN-Daily

Project weather stations		 Station-dependent Appropriate when complete local meteorological observations are available.

Optional Improvements

Dataset Purpose
ALOS World 3D (AW3D30) Alternative 30 m DEM for comparison
MERIT Hydro Hydrologically consistent flow directions and river network
MODIS MCD15A3H Dynamic Leaf Area Index (LAI)
GLEAM Validation of simulated actual evapotranspiration
Global Mangrove Watch Mapping of coastal mangroves
SMAP Regional soil-moisture validation (limited under dense forest)
  1. Download FABDEM for the model domain.
  2. Delineate the model domain and prepare the terrain model, checking drainage against MERIT Hydro.
  3. Download ESA WorldCover and assign MIKE SHE vegetation classes.
  4. Download SoilGrids and derive van Genuchten parameters using pedotransfer functions.
  5. Choose your meteorological forcing:
  6. Option A (recommended): Use CHIRPS or IMERG/GSMaP for precipitation and ERA5-Land for the other climate variables.
  7. Option B: Use local station records, where available, to bias-correct the gridded products or force the model directly.
  8. Let MIKE SHE calculate evapotranspiration internally using the selected vegetation and soil parameters.
  9. Check simulated actual ET against GLEAM or MODIS MOD16.
  10. 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 Papua New Guinea.

The catalog is organized according to the typical MIKE SHE model-building workflow. Because national datasets are limited, it gives particular weight to global and satellite products and to data held by projects and operators.

1.2 Intended Use

This catalog is intended for:

  • rapid screening models
  • catchment water-balance models
  • water supply and groundwater studies for towns and communities
  • mining and hydropower water assessments
  • flood and sediment studies
  • climate variability and drought assessments
  • applied MIKE SHE model setup

1.3 General Notes for Papua New Guinea

  • Most national agencies publish little data online. Data are usually obtained by request, through development projects (e.g. Asian Development Bank, World Bank, UN agencies), or from mining, oil and gas, and hydropower operators.
  • Customary land ownership covers most of the country. Field access, monitoring installation and data use require engagement with landowner communities.
  • The national datum is PNG94; projected models typically use PNGMG94 (zones 54–56).
  • Frequent cloud cover limits optical satellite data; radar products are often more reliable.

2. Hydrological Characteristics of Papua New Guinea

2.1 Climate

  • humid tropical climate with high rainfall almost everywhere
  • annual rainfall ranging from around 1,000 mm (Port Moresby) to more than 6,000 mm in parts of the Gulf and Western provinces
  • monsoonal seasonality with north-west (wet) and south-east (drier) seasons
  • cooler highland climate with occasional frost at high altitude
  • strong ENSO influence, with severe droughts and frosts in El Niño years (e.g. 1997–1998, 2015–2016)
  • very intense orographic and convective rainfall

2.2 Topography

  • central cordillera and highlands rising above 4,000 m
  • very large lowland river systems (Fly, Sepik, Purari, Ramu)
  • extensive swamps and floodplains in the south and along the Sepik
  • karst limestone plateaus in the highlands and Western Province
  • active volcanic islands (e.g. New Britain, Bougainville)
  • coastal plains and deltas with mangroves

2.3 Major Hydrological Challenges

  • very sparse hydrometeorological monitoring
  • extreme rainfall and landslides in steep, tectonically active terrain
  • mine-derived sediment and water-quality impacts on large rivers (e.g. Fly River system)
  • water supply for fast-growing towns and remote communities
  • groundwater in karst and volcanic aquifers with little data
  • drought impacts on subsistence agriculture and water supply
  • hydropower planning under data scarcity
  • sea-level rise and saltwater intrusion on low islands and atolls

2.4 Major Aquifer Systems

Groundwater systems are poorly mapped. Important settings include:

  • highland and Western Province karst limestone aquifers
  • alluvial aquifers of the large river valleys (e.g. Markham, Ramu, Fly)
  • coastal sand and alluvial aquifers (e.g. around Port Moresby and Lae)
  • volcanic aquifers on New Britain, Bougainville and other islands
  • freshwater lenses on low coral islands and atolls

3. Recommended Dataset Stack

Component Recommended Dataset Alternative Dataset Importance
DEM FABDEM Copernicus GLO-30, AW3D30 ★★★★★
Land cover ESA WorldCover Dynamic World ★★★★★
LAI MODIS MCD15A3H Sentinel-2 derived LAI ★★★★☆
Precipitation CHIRPS GPM IMERG, GSMaP ★★★★★
Climate forcing ERA5-Land TerraClimate ★★★★★
Potential ET FAO-56 from ERA5-Land TerraClimate ★★★★☆
Rivers MERIT Hydro HydroRIVERS ★★★★★
Lakes / surface water JRC Global Surface Water HydroLAKES ★★★★☆
Soil SoilGrids HWSD v2 ★★★★☆
Hydrogeology MRA geological maps WHYMAP, GLHYMPS ★★★★☆
Groundwater heads Project and operator data IGRAC GGIS ★★★☆☆
Streamflow calibration Project and operator gauges GRDC ★★★★☆
Actual ET validation GLEAM MODIS MOD16, SSEBop ★★★★☆
Soil moisture validation ESA CCI Soil Moisture SMAP ★★★☆☆
Total water storage GRACE / GRACE-FO – ★★☆☆☆

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 Format MIKE SHE Suitability Advantages Limitations Recommendation
FABDEM Global 30 m GeoTIFF Primary DEM Forest canopy removed Licence restricts commercial use; check terms ★★★★★
Copernicus GLO-30 Global 30 m GeoTIFF Backup DEM High-quality surface model Includes forest canopy ★★★★☆
AW3D30 Global 30 m GeoTIFF Comparison Independent optical DEM Voids in cloudy areas ★★★☆☆
NASADEM / SRTM Near-global 30 m GeoTIFF Fallback Easy access Canopy bias, older ★★☆☆☆
MERIT DEM Global 90 m GeoTIFF Regional models Vegetation and noise errors removed Coarse ★★★☆☆

4.3 Typical Preprocessing

  • reproject to PNGMG94 or a suitable UTM zone
  • clip to model domain plus buffer
  • compare FABDEM and Copernicus GLO-30 in forested areas
  • condition drainage using MERIT Hydro flow directions
  • resample to model grid
  • smooth only where needed for numerical stability

4.4 Quality Checks

  • check river channels in low-gradient swamps and floodplains
  • check steep slopes and valley bottoms for artefacts
  • compare derived catchments with MERIT Hydro and HydroBASINS
  • verify coastal and delta elevations

5. Surface Water

5.1 Rivers

Dataset Coverage Format MIKE SHE / MIKE 1D Use Advantages Limitations Recommendation
MERIT Hydro Global Raster (flow direction, width) River network, catchments, river width Hydrologically consistent, includes river width 90 m resolution ★★★★★
HydroRIVERS / HydroBASINS Global Vector River network and basins Easy to use Generalized ★★★★☆
OpenStreetMap Global Vector Local rivers and drains Sometimes detailed near towns Incomplete ★★☆☆☆

5.2 Lakes, Swamps and Wetlands

Dataset Use Recommendation
JRC Global Surface Water Water occurrence and seasonality since 1984 ★★★★☆
HydroLAKES Lake polygons ★★★☆☆
Global Mangrove Watch Mangrove extent ★★★★☆
Sentinel-1 SAR Flooding and swamp inundation under cloud and forest ★★★★☆

5.4 Typical Preprocessing

  • simplify river network
  • align river network with DEM
  • estimate channel geometry from MERIT Hydro widths and field data
  • represent large swamps and floodplains as overland-flow storage
  • assign river 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, and impervious areas.

6.2 Dataset Comparison

Dataset Coverage Resolution Format MIKE SHE Use Advantages Limitations Recommendation
ESA WorldCover Global 10 m Raster Primary land-cover zones High resolution 2020 and 2021 only ★★★★★
Dynamic World Global 10 m Cloud / Earth Engine Recent changes Near-real-time Cloud gaps ★★★★☆
Copernicus Global Land Cover Global 100 m Raster Time series 2015–2019 Includes cover fractions Coarser ★★★☆☆
Hansen Global Forest Change Global 30 m Raster Forest loss since 2000 Annual loss maps Forest only ★★★★☆
PNG Forest Authority forest base maps PNG Vector Vector Forest types National forest typology Access by request ★★★☆☆

6.3 Vegetation Datasets

Parameter Dataset Use Recommendation
LAI MODIS MCD15A3H Seasonal LAI (often cloud-affected) ★★★☆☆
Canopy height GEDI / global canopy height maps Forest structure and interception ★★★☆☆
Crop coefficient FAO-56 Gardens, oil palm, coffee ★★★☆☆

6.4 Typical Preprocessing

  • reclassify land cover into MIKE SHE vegetation zones
  • separate lowland rainforest, montane forest, grassland, gardens, plantations (e.g. oil palm), swamp forest and mangroves
  • assign high LAI and interception capacity to tropical forest
  • consider forest loss from logging and mining for long simulations

7. Meteorological Forcing

7.1 Precipitation

Dataset Coverage Resolution Temporal Resolution MIKE SHE Use Advantages Limitations Recommendation
CHIRPS 50°S–50°N ~5 km Daily, since 1981 Long-term forcing Gauge-blended, long record Few PNG gauges in blend ★★★★★
GPM IMERG Global ~10 km 30 min, since 2000 Event and sub-daily forcing High temporal resolution Underestimates orographic rainfall ★★★★★
GSMaP Global ~10 km Hourly Event forcing Strong Asia-Pacific performance Bias correction needed ★★★★☆
ERA5-Land Global ~9 km Hourly Backup forcing Physically consistent Poor convective rainfall ★★★☆☆
MSWEP Global ~10 km 3-hourly Merged product Combines gauges, satellite and reanalysis Licence for commercial use ★★★★☆

7.2 Climate Variables

Variable Recommended Dataset Alternatives MIKE SHE Use
Air temperature ERA5-Land TerraClimate ET; frost in highlands
Wind speed ERA5-Land TerraClimate Penman-Monteith
Humidity ERA5-Land TerraClimate Vapour-pressure deficit
Solar radiation ERA5-Land NASA POWER ET energy term
Reference ET FAO-56 from ERA5-Land TerraClimate PET forcing

7.3 Notes

  • apply elevation lapse rates to temperature in the highlands, since ERA5-Land is too coarse for steep terrain
  • bias-correct satellite rainfall against any available local gauges
  • snow and ice are negligible except on the highest peaks

8. Soil Data

8.1 Purpose in MIKE SHE

Soil data control infiltration, water retention, ET limitation, recharge, capillary rise, and runoff generation.

8.2 Dataset Comparison

Dataset Coverage Resolution Parameters MIKE SHE Use Advantages Limitations Recommendation
SoilGrids Global 250 m Texture, bulk density, organic carbon Primary UZ parameterization Six depth intervals, uncertainty Few PNG profiles underlying model ★★★★☆
HWSD v2 Global ~1 km Soil units and properties Comparison Harmonized soil units Coarse ★★★☆☆
PNG Resource Information System (PNGRIS) PNG 1:500,000 Resource mapping units (landform, soils, rainfall) Soil and land context Country-specific Coarse; access by request ★★★☆☆

8.3 Typical Preprocessing

  • derive van Genuchten parameters with pedotransfer functions suited to tropical soils
  • treat volcanic ash soils (andosols) and peat soils separately
  • assign thick, highly weathered profiles where appropriate
  • calibrate against discharge and any local soil data

9. Hydrogeology

9.1 Dataset Comparison

Dataset Coverage Use Advantages Limitations Recommendation
Mineral Resources Authority (Geological Survey) PNG Geological maps and reports National geology Hydrogeological interpretation required ★★★★☆
WHYMAP Global Hydrogeological overview Consistent global classification Very generalized ★★★☆☆
GLHYMPS Global Permeability screening Quantitative values Generalized ★★☆☆☆
GLiM Global Lithology Global lithological map Generalized ★★☆☆☆
Mining and project reports Local Local aquifer data Often the only detailed data Access by request ★★★★★

9.2 Conceptual Model Recommendations

  • karst conduits and large springs in limestone areas
  • deep weathering profiles over bedrock
  • volcanic aquifers with high permeability and springs
  • alluvial aquifers connected to large rivers
  • freshwater lenses on small islands

10. Groundwater Data

Dataset Coverage Use Recommendation
Project and operator monitoring (mining, water supply) Local Heads, pumping ★★★★★
IGRAC Global Groundwater Information System Global Available monitoring data and aquifer information ★★☆☆☆
Water PNG and town water-supply records Local Water-supply wells ★★★★☆

Boundary conditions usually have to be derived conceptually (coastlines, rivers, catchment divides), since regional groundwater data are rarely available.

11. Water Management

11.1 Relevant Processes

  • town water supply (e.g. Port Moresby, Lae)
  • rural water supply from springs, rainwater and shallow wells
  • hydropower (e.g. Ramu system)
  • mine water management, dewatering and tailings
  • oil and gas operations
  • small-scale and plantation agriculture

11.2 Key Institutions

Topic Institution
Water resources regulation Conservation and Environment Protection Authority (CEPA)
Geology and mining Mineral Resources Authority
Climate data PNG National Weather Service
Forest data PNG Forest Authority
Urban water supply Water PNG, Eda Ranu

12. Remote Sensing Products

Dataset Coverage Resolution Use Recommendation
GLEAM Global ~25 km Actual ET and evaporation components ★★★★☆
MODIS MOD16 Global 500 m Actual ET ★★★☆☆
Sentinel-1 SAR Global 10 m Flooding and wetness under cloud ★★★★★
Sentinel-2 Global 10 m Land cover (cloud-limited) ★★★☆☆
ESA CCI Soil Moisture Global ~25 km Soil moisture trends ★★★☆☆
GRACE / GRACE-FO Global ~300 km Large-basin storage change ★★☆☆☆
JRC Global Surface Water Global 30 m Inundation occurrence ★★★★☆

13. Calibration Datasets

Target Dataset Use Recommendation
River discharge Project and operator gauges, GRDC Streamflow calibration ★★★★★
Groundwater heads Project monitoring SZ calibration ★★★★☆
Actual ET GLEAM, MODIS MOD16 ET plausibility ★★★★☆
Inundation extent Sentinel-1, JRC GSW Floodplain and swamp validation ★★★★☆
Soil moisture ESA CCI UZ plausibility ★★☆☆☆

Under data scarcity, models should be checked for water-balance plausibility (runoff coefficients, ET fractions) and tested with remote sensing, rather than calibrated only against short discharge records.

14. Typical MIKE SHE Workflow

  1. Define modelling objective and domain.
  2. Prepare the DEM from FABDEM and check drainage against MERIT Hydro.
  3. Build the river network from MERIT Hydro.
  4. Prepare land cover from ESA WorldCover.
  5. Assign vegetation parameters from MODIS LAI and literature.
  6. Prepare precipitation from CHIRPS or IMERG/GSMaP, bias-corrected with local gauges.
  7. Prepare climate forcing and reference ET from ERA5-Land.
  8. Prepare soil properties from SoilGrids.
  9. Build a conceptual hydrogeological model from MRA maps and project data.
  10. Add pumping and water use where relevant.
  11. Couple rivers and groundwater.
  12. Calibrate against available discharge and heads.
  13. Validate ET and inundation with remote sensing.
  14. Document assumptions and uncertainties.

15. Minimum Dataset Package

Model Element Dataset
DEM FABDEM
Land cover ESA WorldCover
Precipitation CHIRPS
Climate forcing and PET ERA5-Land
Rivers MERIT Hydro
Soils SoilGrids
Hydrogeology WHYMAP + MRA geology
Validation GLEAM

16. Recommended Dataset Package

Model Element Dataset
DEM FABDEM + Copernicus GLO-30 comparison
Precipitation IMERG or GSMaP, bias-corrected against local gauges
Climate forcing ERA5-Land with elevation lapse rates
Land cover ESA WorldCover + Hansen forest change
Soils SoilGrids + local soil data
Hydrogeology MRA geology + project reports
Discharge and heads Project and operator monitoring
Actual ET GLEAM + MODIS MOD16
Inundation Sentinel-1

17. Premium Dataset Package

Dataset Type Possible Source Purpose
Airborne LiDAR Mining and infrastructure projects Accurate terrain under forest
Dedicated rain gauges and weather stations Project installation Local forcing and bias correction
Discharge gauging and rating curves Project installation Calibration
Boreholes and pumping tests Water-supply and mining projects Aquifer parameters
Field soil sampling Project surveys Soil hydraulic parameters
Stable isotopes Project sampling Recharge sources and flow paths

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

  • [ ] FABDEM downloaded and licence checked
  • [ ] DEM projected and clipped
  • [ ] drainage checked against MERIT Hydro

Surface Water

  • [ ] river network prepared
  • [ ] swamps and floodplains identified
  • [ ] boundary conditions assigned

Land Cover and Vegetation

  • [ ] land cover reclassified
  • [ ] forest loss checked
  • [ ] LAI and rooting depths assigned

Weather

  • [ ] satellite precipitation downloaded
  • [ ] local gauges obtained and compared
  • [ ] ERA5-Land downloaded and lapse rates applied
  • [ ] reference ET calculated

Soil

  • [ ] SoilGrids downloaded
  • [ ] pedotransfer functions applied
  • [ ] volcanic and peat soils checked

Groundwater

  • [ ] geology and project data collected
  • [ ] conceptual model defined
  • [ ] boundary conditions defined

Calibration and Validation

  • [ ] discharge data obtained
  • [ ] GLEAM / MOD16 prepared
  • [ ] Sentinel-1 inundation prepared

20. References and Official Data Portals

21. Notes on Uncertainty

  • very sparse rain gauges and bias in satellite rainfall, especially orographic rainfall
  • DEM errors under dense forest canopy
  • soil parameters derived from global products with few local profiles
  • almost no groundwater monitoring
  • short or discontinuous discharge records
  • landslides and river-bed changes in active terrain
  • mining impacts on sediment and channel form
  • large ENSO-driven climate variability

A defensible model should document dataset choices, preprocessing assumptions, calibration strategy, validation results, and known limitations. Under data scarcity, uncertainty ranges and scenario analyses are more informative than single calibrated results.