4DHydro mHM Tier 2 simulations - exp21 0 15173

Projekt
hydrometeorological data
Beschreibung
Experiment 21 of the mHM Tier2 simulations, part of the 4DHydro ESA project (Work Package 5 deliverables).

This is a DOI reference for the STAC protocol of the 4DHydro project (tarball for all NetCDF files, identical to non-permanent storage under https://minio.ufz.de/4dhydro/mHM/tier2/exp21).

The mHM simulations are based on the Mesoscale Hydrological Model and SCC method (release_5.11.3-dev0, commit 05ece194).

Simulation options:
- Period: 1990-2022
- Region: European setup forcing EMO1 and Tugela River basin setup forced by the CHIRPS product
- Settings: Multi-basin calibration with the objective function of 1.0 - KGE (Kling-Gupta efficiency measure); included modules: basic hydrologic modules. Snow processes are based on the day-degree approach, soil moisture is processed based on the Feddes equation for ET reduction, and a multi-layer infiltration capacity approach (Brooks-Corey-like); direct runoff is based on the linear reservoir exceedance approach; PET is based on the Hargreaves-Samani method; interflow is approximated by a storage reservoir with one outflow threshold and a nonlinear response; groundwater is assumed to be a linear reservoir; river routing is approximated by adaptive timestep, spatially varying celerity.
- Spin-up: Based on a 10-year simulation with 1990-2000 climatology for EMO-1 and a calibration period from 2005-2022 for the spatial resolution of 0.0625 degrees.
- Source code: https://git.ufz.de/mhm/mhm, commit 05ece194
- Resolution: Spatial resolution of 0.125, 0.03125 and 0.015625 degrees (see STAC protocol above for more details)
- Temporal resolution: Hourly (with meteo inputs daily, internal weights based on sub-daily ERA5 values used for disaggregation to hourly).

Input datasets for the mHM setup:
* See Rakovec et al. (2022) and Boeing et al. (2022) for more information.

- **Meteorology** (and pre-processing):
Precipitation, temperature, and reference potential evapotranspiration are based on two datasets: EMO-1 (Thieming et al., 2022; updated ~1 km resolution) and CHIRPS (Funk et al., 2015). The latter was remapped on the 0.0625-degree grid using the nearest neighbor approach. Reference potential evapotranspiration was determined using the Hargreaves-Samani equation (Hargreaves and Samani, 1985). The internal model timestep of mHM is hourly, with temporal disaggregation based on weights derived from the native hourly ERA5 dataset.

- **Soil and topography**:
Soil parameters are based on the SoilGrids dataset (Hengl et al., 2014). Topography parameters are based on GMTED2010 and conditioned on the HydroSHEDS river network.

- **Landcover and vegetation**:
mHM uses three dominant land cover classes (forest, permeable, and impervious) retrieved from the GLOBCOVER database (ESA, 2009). Additionally, vegetation characteristics for interception processes are based on the Leaf Area Index (LAI) from GIMMS MODIS.

- **Groundwater processes**:
Baseflow recession constants are derived from the GLIM data from Universität Hamburg.

- **Output variables**:
Discharge, actual evapotranspiration, soil moisture, total water, upstream area.

References:

Boeing, F., Rakovec, O., Kumar, R., Samaniego, L., Schrön, M., Hildebrandt, A., Rebmann, C., Thober, S., Müller, S., Zacharias, S., Bogena, H., Schneider, K., Kiese, R., Attinger, S., and Marx, A.: High-resolution drought simulations and comparison to soil moisture observations in Germany, Hydrol. Earth Syst. Sci., 26, 5137–5161

Cornes, R., G. van der Schrier, E.J.M. van den Besselaar, and P.D. Jones. 2018: An Ensemble Version of the E-OBS Temperature and Precipitation Datasets, J. Geophys. Res. Atmos., 123. doi:10.1029/2017JD028200

ESA (2009) Globcover v2 http://due.esrin.esa.int/page_globcover.php

Hargreaves, G.H. and Samani, Z.A., 1985. Reference crop evapotranspiration from temperature. Applied engineering in agriculture, 1(2), pp.96-99.

Hartmann, J. and Moosdorf, N., 2012. The new global lithological map database GLiM: A representation of rock properties at the Earth surface. Geochemistry, Geophysics, Geosystems, 13(12).

Hengl, T., Mendes de Jesus, J., Heuvelink, G.B., Ruiperez Gonzalez, M., Kilibarda, M., Blagotić, A., Shangguan, W., Wright, M.N., Geng, X., Bauer-Marschallinger, B. and Guevara, M.A., 2017. SoilGrids250m: Global gridded soil information based on machine learning. PLoS one, 12(2), p.e0169748.

Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz‐Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D. and Simmons, A., 2020. The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730), pp.1999-2049.

Kumar, R., Samaniego, L. and Attinger, S., 2013. Implications of distributed hydrologic model parameterization on water fluxes at multiple scales and locations. Water Resources Research, 49(1), pp.360-379.

Lehner, B., Liermann, C. R., Revenga, C., Vörösmarty, C., Fekete, B., Crouzet, P., ... & Wisser, D. (2011). High‐resolution mapping of the world's reservoirs and dams for sustainable river‐flow management. Frontiers in Ecology and the Environment, 9(9), 494-502. DOI: 10.1890/100125.

Rakovec, O., Kumar, R., Mai, J., Cuntz, M., Thober, S., Zink, M., Attinger, S., Schäfer, D., Schrön, M. and Samaniego, L., 2016. Multiscale and multivariate evaluation of water fluxes and states over European river basins. Journal of Hydrometeorology, 17(1), pp.287-307.

Rakovec, O., Samaniego, L., Hari, V., Markonis, Y., Moravec, V., Thober, S., Hanel, M. and Kumar, R., 2022. The 2018–2020 multi‐year drought sets a new benchmark in Europe. Earth's Future, 10(3), p.e2021EF002394.

Samaniego, L., Kumar, R. and Attinger, S., 2010. Multiscale parameter regionalization of a grid‐based hydrologic model at the mesoscale. Water Resources Research, 46(5).

Samaniego, L., Kumar, R., Zink, M., Cuntz, M., Juliane Mai, Stephan Thober, Christoph Schneider, Giovanni Dalmasso, Jude Musuuza, Oldrich Rakovec, John Craven, David Schäfer, Vladyslav Prykhodko, Martin Schrön, Diana Spieler, Johannes Brenner, Ben Langenberg, Lennart Schüler, Simon Stisen, Cüneyd M. Demirel, Miao Jing, Maren Kaluza, Robert Schweppe, Pallav Kumar Shrestha, Nicola Döring and Sebastian Müller (2023) mhm-ufz/mHM: v5.13.1, Zenodo [Online]. DOI: 10.5281/zenodo.8279545.

Thiemig, V., Gomes, G.N., Skøien, J.O., Ziese, M., Rauthe-Schöch, A., Rustemeier, E., Rehfeldt, K., Walawender, J.P., Kolbe, C., Pichon, D. and Schweim, C., 2022. EMO-5: a high-resolution multi-variable gridded meteorological dataset for Europe. Earth System Science Data, 14(7), pp.3249-3272.

Thober, S., Cuntz, M., Kelbling, M., Kumar, R., Mai, J. and Samaniego, L., 2019. The multiscale routing model mRM v1. 0: Simple river routing at resolutions from 1 to 50 km. Geoscientific Model Development, 12(6), pp.2501-2521.


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LICENCE

CC BY-NC-SA 4.0 DEED
Attribution-NonCommercial-ShareAlike 4.0 International

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DOI
https://doi.org/10.48758/ufz.15173
Zitiervorschlag (APA)
Modiri, E., Rakovec, O., & Samaniego, L. (2024). 4DHydro mHM Tier 2 simulations - exp21. Helmholtz-Centre for Environmental Research. https://doi.org/10.48758/UFZ.15173
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Metadaten Kataloge
Dublin Core
URI
https://www.ufz.de/record/dmp/archive/15173
DOI
10.48758/ufz.15173
Thema
4DHydro mHM tier2 simulations - exp21 for 3 regions of interest (Po, Rhine, and Tugela)
Veröffenlichungsdatum
10.09.2024
Geltungsbereich
Po, Rhine, and Tugela basins
Datenart
Model
Datenqualität
qualitätsgesicherte Daten
Datenstatus
bearbeitete Daten
Datenformat
netcdf
Urheber
Modiri, E.
Rakovec, O.
Samaniego, L.
Herausgeber
Helmholtz-Centre for Environmental Research
Rechteinhaber
Helmholtz-Centre for Environmental Research
Kontakt
ehsan.modiri@ufz.de
oldrich.rakovec@ufz.de
luis.samaniego@ufz.de
Zeitpunkt oder -bereich der Erzeugung der Daten
01.01.1990 - 31.12.2022 24:00
Sprache des Inhalts
Englisch
Zugriffsrechte
freier Zugriff