Impact model: SWAP

SWAP is one of the 15 regional hydrology models following the ISIMIP2a protocol which form the base of simulations for the ISIMIP2a regional water sector outputs; for a full technical description of the ISIMIP2a Simulation Data from Water (regional) Sector, see this DOI link: http://doi.org/10.5880/PIK.2018.007

ISIMIP2b
ISIMIP2a

Person responsible for model simulations in this simulation round

Georgy Ayzel: hydrogo@yandex.ru, 0000-0001-5608-9110, Water Problems Institute of RAS (Russia)

Evgeny E. Kovalev: eekovalev@gmail.com, 0000-0002-4119-3828, Water Problems Institute of RAS (Russia)

Olga Nasonova: olniknas@yandex.ru, 0000-0002-3111-3337, Water Problems Institute of RAS (Russia)

Additional persons involved: Olga Nasonova, Yeugeny Gusev, Evgeny Kovalev

Basic information

Model Version: The same model version as in ISIMIP2a

Simulation Round Specific Description: * Data in embargo period: not yet publicly available, but currently only shared among the ISIMIP participants

Reference Paper: Main Reference: Gelfan A., Kalugin A., Krylenko I., Nasonova O., Gusev Ye., Kovalev E. et al. Does a successful comprehensive evaluation increase confidence in а hydrological model intended for climate impact assessment? . Climatic change,163,1165-1185,2020

Resolution

Spatial aggregation: regular grid

Horizontal resolution: 0.5°x0.5°

Temporal resolution of input data: climate variables: daily

Temporal resolution of input data: soil: constant

Input data

Simulated atmospheric climate data sets used: IPSL-CM5A-LR, HadGEM2-ES, GFDL-ESM2M, MIROC5

Other data sets used: Land-sea mask

Climate variables: hurs, sfcWind, tas, rlds, rsds, ps, pr

Spin-up

Was a spin-up performed?: Yes

Spin-up design: The first year (1971) was simulated 4 times for spin-up (according to our experience it is enough to reach equilibrium by our model).

Natural Vegetation

Natural vegetation dynamics: no

Natural vegetation cover dataset: We aggregated parameters taken from ECOCLIMAP for 0.5 deg grid cells

Management & Adaptation Measures

Management: no

Methods

Potential evapotranspiration: SWAP simulates potential evapotranspiration. See papers.

Snow melt: Energy balance

Vegetation

How is vegetation represented?: Fixed monthly vegetation characteristics.

Routing

Runoff routing: Kinematic wave equation for water transfer within a grid cell and a linear routing scheme by Oki et al. (1999) for water transfer in a river channel.

Routing data: We prepared routing data by ourselves

Calibration

Was the model calibrated?: Yes

Which years were used for calibration?: Varied depending on the data availability in different basins

Which dataset was used for calibration?: WFD

How many catchments were callibrated?: 2

Modelled catchments

Modelled catchments: Lena, MacKenzie

Person responsible for model simulations in this simulation round

Georgy Ayzel: hydrogo@yandex.ru, 0000-0001-5608-9110, Water Problems Institute of RAS (Russia)

Yeugeniy Gusev: sowaso@yandex.ru, 0000-0003-3886-2143, Water Problems Institute of RAS (Russia)

Evgeny E. Kovalev: eekovalev@gmail.com, 0000-0002-4119-3828, Water Problems Institute of RAS (Russia)

Olga Nasonova: olniknas@yandex.ru, 0000-0002-3111-3337, Water Problems Institute of RAS (Russia)

Additional persons involved: Olga Nasonova

Output Data

Experiments: historical (Lena, Darling, MacKenzie, Mississippi, Amazon, Rhine, Tagus, Niger, Ganges, Yellow, Yangtze)
Climate Drivers: None
Date: 2017-02-20

Basic information

Model Version: SWAP

Model Output License: CC0

Reference Paper: Main Reference: Gusev Ye.M., Nasonova O.N. et al. Modelling heat and water exchange in the boreal spruce forest by the land-surface model SWAP. J. Hydrology,280,162-191,2003

Reference Paper: Other References: Gusev, E.M., Nasonova, O.N., Kovalev, E.E. et al. Modeling the components of heat and water balance for the land surface of the globe. Water Resources. ,33,616-627,2006

Resolution

Spatial aggregation: regular grid

Horizontal resolution: 0.5°x0.5°

Temporal resolution of input data: climate variables: daily

Temporal resolution of input data: land use/land cover: fixed monthly vegetation parameters from ECOCLIMAP

Temporal resolution of input data: soil: fixed over time

Input data

Observed atmospheric climate data sets used: WATCH (WFD)

Other data sets used: Land-sea mask

Additional input data sets: Vegetation and soil parameters were taken or derived from ECOCLIMAP

Climate variables: tas, rlds, wind, rhs, rsds, ps, pr

Spin-up

Was a spin-up performed?: Yes

Spin-up design: We started the simulations from 1July 1969 and the first year was simulated 4 times for spin-up (according to our experience it is enough to reach equilibrium by our model).

Natural Vegetation

Natural vegetation partition: We aggregated parameters taken from ECOCLIMAP for 0.5 deg grid cells

Natural vegetation dynamics: Prescribed monthly vegetation parameters.

Natural vegetation cover dataset: We aggregated parameters taken from ECOCLIMAP for 0.5 deg grid cells

Management & Adaptation Measures

Management: no

Extreme Events & Disturbances

Key challenges: Time step should be finer to reproduce high flow more accurately.

Methods

Potential evapotranspiration: See papers

Snow melt: Energy balance

Vegetation

Is co2 fertilisation accounted for?: No

How is vegetation represented?: prescriped

Routing

Runoff routing: Kinematic wave equation for water transfer within a grid cell and a linear routing scheme by Oki et al. (1999) for water transfer in a river channel.

Routing data: Routing data were prepared by ourselves

Calibration

Was the model calibrated?: Yes

Which years were used for calibration?: Up to 8 years depending on available observations in different basins

Which dataset was used for calibration?: WFD

How many catchments were callibrated?: 11

Modelled catchments

Modelled catchments: Lena, Darling, MacKenzie, Mississippi, Amazon, Rhine, Tagus, Niger, Ganges, Yellow, Yangtze