Impact model: MPI-HM

The MPI-HM is a global hydrological model. It is used to investigate hydrological research questions mostly related to high resolution river routing. While hydrological processes are implemented in similar complexity as in full land surface models, the MPI-HM does not compute any energy related fluxes. MPI-HM is one of the 13 global hydrology models following the ISIMIP2a protocol which form the base of simulations for the ISIMIP2a global water sector outputs; for a full technical description of the ISIMIP2a Simulation Data from Water (global) Sector, see this DOI link: http://doi.org/10.5880/PIK.2017.010

Sector
Water (global)
Region
global
Contact Person

Information for the model MPI-HM is provided for the simulation rounds shown in the tabs below. Click on the appropriate tab to get the information for the simulation round you are interested in.

Basic information
Model Version: v1.2
Reference Paper: Main Reference: Stacke T, Hagemann S et al. Development and evaluation of a global dynamical wetlands extent scheme. Hydrology and Earth System Sciences,16,2915-2933,2012
Person Responsible For Model Simulations In This Simulation Round: Tobias Stacke
Output Data
Experiments: I, II, III
Climate Drivers: IPSL-CM5A-LR, GFDL-ESM2M, MIROC5
Date: 2017-09-08
Resolution
Spatial Aggregation: regular grid
Spatial Resolution: 0.5°x0.5°
Additional Spatial Aggregation & Resolution Information: subgrid heterogeneity taken into account for the computation of surface runoff and evapotranspiration
Temporal Resolution Of Input Data: Climate Variables: daily
Temporal Resolution Of Input Data: Co2: not used
Temporal Resolution Of Input Data: Land Use/Land Cover: annual
Temporal Resolution Of Input Data: Soil: constant
Input data sets used
Simulated Atmospheric Climate Data Sets Used: IPSL-CM5A-LR, GFDL-ESM2M, MIROC5
Observed Atmospheric Climate Data Sets Used: EWEMBI
Land Use Data Sets Used: Historical, gridded land use (HYDE 3.2)
Other Data Sets Used: Land-sea mask, River-routing network
Climate Variables: tas, pr
Additional Information About Input Variables: PET (derived from tas, tasmin, tasmax, rhs, ps, rsds, rlds and wind)
Additional Input Data Sets: GLWD for lakes and wetlands
Exceptions to Protocol
Exceptions: none
Spin-up
Was A Spin-Up Performed?: Yes
Spin-Up Design: Simulations were started with initialized states from a comparable simulation. Checks were performed to check for any remaining spin-up signals.
Natural Vegetation
Natural Vegetation Partition: Prescribed natural vegetation climatology based on LSP2 and irrigation climatology based on MIRCA. Irrigation climatology was then scaled with the annual fractions provided by ISI-MIP.
Natural Vegetation Dynamics: A fixed vegetation climatology from LSP2 is used.
Natural Vegetation Cover Dataset: LSP2 (Hagemann, 2002)
Management & Adaptation Measures
Management: no
Extreme Events & Disturbances
Key Challenges: Probably missing impacts of reservoirs on the mitigation of extreme flow events. Extreme values are probably also affected by the missing soil layering (bucket only) as well as using a reference PET method.
Additional Comments: All remaining parameters are used in the default mode which are set in the run script
Technological Progress
Technological Progress: No
Soil
Soil Layers: 1 layer, bucket style, soil defined by field capacity
Water Use
Water-Use Types: Irrigation only
Water-Use Sectors: Irrigation
Routing
Runoff Routing: Linear reservoir cascade
Routing Data: DDM30 network
Dams & Reservoirs
Dam And Reservoir Implementation: No explicit dams or reservoirs are included. However, irrigation is limited by the available river water in a given grid cell.
Vegetation
How Is Vegetation Represented?: Climatology of vegetation fraction
Methods
Potential Evapotranspiration: Penman-Monteith reference ET
Snow Melt: Degree-day scheme
Basic information
Model Version: R44
Reference Paper: Main Reference: Stacke T, Hagemann S et al. Development and evaluation of a global dynamical wetlands extent scheme. Hydrology and Earth System Sciences,16,2915-2933,2012
Output Data
Experiments: historical
Climate Drivers: GSWP3, PGMFD v.2 (Princeton), WATCH (WFD), WATCH+WFDEI
Date: 2016-05-11
Resolution
Spatial Aggregation: regular grid
Spatial Resolution: 0.5°x0.5°
Additional Spatial Aggregation & Resolution Information: subgrid heterogeneity taken into account for the computation of surface runoff and evapotranspiration
Temporal Resolution Of Input Data: Climate Variables: daily
Temporal Resolution Of Input Data: Co2: not used
Temporal Resolution Of Input Data: Land Use/Land Cover: constant
Temporal Resolution Of Input Data: Soil: constant
Input data sets used
Observed Atmospheric Climate Data Sets Used: GSWP3, PGMFD v.2 (Princeton), WATCH (WFD), WATCH+WFDEI
Climate Variables: tas, pr
Additional Information About Input Variables: PET (derived from tas, tasmin, tasmax, rhs, ps, rsds, rlds and wind)
Additional Input Data Sets: GLWD for lakes and wetlands
Exceptions to Protocol
Exceptions: none
Spin-up
Was A Spin-Up Performed?: Yes
Spin-Up Design: Simulations were started from the first time step provided by the forcing data. Thus, all storages are well initialialized at the time of the reporting period.
Natural Vegetation
Natural Vegetation Partition: Prescibed natural vegetation climatology based on LSP2, only differentiation is between natural vegatation and irrigated crops
Management & Adaptation Measures
Management: no
Extreme Events & Disturbances
Key Challenges: Probably missing impacts of reservoirs on the mitigation of extreme flow events. Extreme values are probably also affected by the missing soil layering (bucket only) as well as using a reference PET method
Additional Comments: All remaining parameters are used in the default mode which are set in the run script
Technological Progress
Technological Progress: No
Soil
Soil Layers: 1 layer, bucket style
Water Use
Water-Use Types: Irrigation only
Water-Use Sectors: Irrigation
Routing
Runoff Routing: DDM30 network, linear reservoirs
Land Use
Land-Use Change Effects: none
Dams & Reservoirs
Dam And Reservoir Implementation: none
Vegetation
How Is Vegetation Represented?: Climatology of vegetation fraction
Methods
Potential Evapotranspiration: "Penman-Monteith reference ET "
Snow Melt: Degree-day scheme