3: ISIMIP2b multi-model data set Multi-type global drought projection using multi-model hydrological simulations 1,2 Yusuke Satoh*, 1 Tokuta Yokohata, 3 Yadu Pokhrel, , 1 Naota Hanasaki, 1 Julien Boulange, 2 Peter Burek, 4 Ted Veldkamp, 1 Kumiko Takata, 1 Hideo Shiogama 1 National Institute for Environmental Studies (NIES), Tsukuba, Japan. 2 International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria 3 Department of Civil and Environmental Engineering, Michigan State University, East Lansing, Michigan, United States of America, 4 Amsterdam University of Applied Sciences, Amsterdam, Netherlands 1: Introduction 5: Models 4: 3-hourly ISIMIP2b forcing data 6: The impact on climate change on hydrological cycle Contact: [email protected] EGU General Assembly 2020 7: Percent changes in drought proxies of three drought types It is anticipated that climate change will exacerbate future drought. However, very few studies with bias-correction have comprehensively discussed future drought considering several drought types within a single study, hence leaving a gap on the holistic picture of change in drought. A multi-drought study that covers several draught types is required to better understand future drought. Water demand: H08 estimates water demand (irrigation, domestic, industrial). Crop growth: PRYSBI2 calculates crop yield. Food and bio- energy crops are explicitly considered. CO2 emission due to land use change GHG budget CO2 emission due to forest fire Afforestation Deforestation Erosion Crop yield Water use （Irr・Ind・Dom） Fartilizer Land use: TELMO projects land-use change (cropland- forest) based on socio-economic scenarios. considers Economic (ex. trade) and natural factors (ex. slope). Land surface hydrology: MATSIRO LSM calculates hydrological variables such as Soil temperature/moisture, runoff, discharge etc. based on water and energy balance. Terrestrial eco- system: VISIT calculates C and N cycle among atmosphere- vegetation-soil. Can estimate change in GHG. Land surface Hydro MIROC-INTEG1 H08 (NIES) Hanasaki et al. 2018 CWatM (IIASA) Bias-corrected climate projection: GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-L, MIROC5 We temporally downscaled ISIMIP forcing data into 3 hourly because land surface model MATSIRO, which is a core component of MIROC-INTEG, at every hourly time step. (ex. @Vienna, in August, 2005, HadGEM2-ES) 8: Summary and Future works Precipitation Soil moisture Ex) Standardized index: Gamma, scale 3, Severe drought runoff # of Total Drought Months # of Total Event Precipitation Soil moisture runoff Evapotranspiration 2: This study presents a comprehensive multi-drought-type assessment on a global-scale from 1861 until 2099. Meteorological (precipitation), agricultural (soil moisture) and hydrological (runoff) droughts are investigated by using the Standardized method, and four drought features; drought intensity, spatial extent, the number of events, dry spell length, are studied, compared to those of the period before the 1960s. To explore potential pathways of drought changes, this study examined the Representative Concentration Pathways (RCP) 2.6, 6.0 and 8.5 scenarios. We use the multi-model data set, which was developed in the Inter-Sectoral Impact Model Inter-comparison Project phase2b. Using a set of multiple state- of-art global hydrological model (GHM) simulations forced by four bias-corrected GCM projections. Results in this poster derive from selected three global hydrological models. Breck et al. 2019 Yokohata et al. 2019 Results demonstrate that the sign of the change (decrease/increase) can differ among drought types in some regions. These inconsistencies and relations need to be sorted out to better understand future drought. Satoh et al. (in prep) further comprehensively assesses future changes in multi-type droughts with more scenarios, GHMs, and drought metrics at the seasonal scale as well. ◼ Yokohata, T. et al. MIROC-INTEG1 : A global bio-geochemical land surface model with human water management , crop growth , and land-use change. 1–57 (2019). ◼ Burek, P. et al. Development of the Community Water Model (CWatM v1.04) A high-resolution hydrological model for global and regional assessment of integrated water resources management. Geosci. Model Dev. Discuss. 08, 1–49 (2019). ◼ Hanasaki, N., Yoshikawa, S., Pokhrel, Y. & Kanae, S. A global hydrological simulation to specify the sources of water used by humans. Hydrol. Earth Syst. Sci. 22, 789–817 (2018). RCP6.0 (2071-2099) v.s. base-period (1861-1960) EGU2020-10748 (Example) HS2.4.1, 07 May 2020 (NIES)
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3: ISIMIP2b multi-model data set
Multi-type global drought projection using multi-model hydrological simulations1,2Yusuke Satoh*, 1Tokuta Yokohata, 3Yadu Pokhrel, , 1Naota Hanasaki, 1Julien Boulange, 2Peter Burek, 4Ted Veldkamp, 1Kumiko Takata, 1Hideo Shiogama
1National Institute for Environmental Studies (NIES), Tsukuba, Japan. 2International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria3Department of Civil and Environmental Engineering, Michigan State University, East Lansing, Michigan, United States of America, 4Amsterdam University of Applied Sciences, Amsterdam, Netherlands
1: Introduction
5: Models
4: 3-hourly ISIMIP2b forcing data
6: The impact on climate change on hydrological cycle
Contact: [email protected] General Assembly 2020
7: Percent changes in drought proxies of three drought types
It is anticipated that climate change will exacerbate future drought. However, very few studies with bias-correction have comprehensively discussed future drought considering several drought types within a single study, hence leaving a gap on the holistic picture of change in drought. A multi-drought study that covers several draught types is required to better understand future drought.
Water demand: H08estimates water demand (irrigation, domestic, industrial).
Crop growth: PRYSBI2calculates crop yield. Food and bio-energy crops are explicitly considered.
CO2 emission due to land use change
GHG budget
CO2 emission due to forest fire
AfforestationDeforestation
Erosion
Crop yield
Water use（Irr・Ind・Dom）
Fartilizer
Land use: TELMOprojects land-use change (cropland-forest) based on socio-economic scenarios. considers Economic (ex. trade) and natural factors (ex. slope).
Land surface hydrology: MATSIRO LSMcalculates hydrological variables such as Soil temperature/moisture, runoff, discharge etc. based on water and energy balance.
Terrestrial eco-system: VISIT
calculates C and N cycle among atmosphere-vegetation-soil. Can estimate change in GHG.
Land surface Hydro
MIROC-INTEG1H08 (NIES)
Hanasaki et al. 2018
CWatM (IIASA)
Bias-corrected climate projection:GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-L, MIROC5
We temporally downscaled ISIMIP forcing data into 3 hourly because land surface model MATSIRO, which is a core component of MIROC-INTEG, at every hourly time step.
(ex. @Vienna, in August, 2005, HadGEM2-ES)
8: Summary and Future works
Pre
cip
itat
ion
Soil
mo
istu
re
Ex) Standardized index:
Gamma, scale 3, Severe drought
run
off
# of Total Drought Months # of Total Event
Precipitation Soil moisture
runoffEvapotranspiration
2: This study presents a comprehensive multi-drought-type assessment on a global-scale from 1861 until 2099. Meteorological (precipitation), agricultural (soil moisture) and hydrological (runoff) droughts are investigated by using the Standardized method, and four drought features; drought intensity, spatial extent, the number of events, dry spell length, are studied, compared to those of the period before the 1960s. To explore potential pathways of drought changes, this study examined the Representative Concentration Pathways (RCP) 2.6, 6.0 and 8.5 scenarios.
We use the multi-model data set, which was developed in the Inter-Sectoral Impact Model Inter-comparison Project phase2b. Using a set of multiple state-of-art global hydrological model (GHM) simulations forced by four bias-corrected GCM projections.
Results in this poster derive from selected three global hydrological models.
Breck et al. 2019
Yokohata et al. 2019
Results demonstrate that the sign ofthe change (decrease/increase) can differ among drought types in some regions.These inconsistencies and relations need to be sorted out to better understandfuture drought. Satoh et al. (in prep) further comprehensively assesses future changes in multi-typedroughts with more scenarios, GHMs, and drought metrics at the seasonal scale as well.
◼ Yokohata, T. et al. MIROC-INTEG1 : A global bio-geochemical land surface model with human water management , crop growth , and land-use change. 1–57 (2019).◼ Burek, P. et al. Development of the Community Water Model (CWatM v1.04) A high-resolution hydrological model for global and regional assessment of integrated water resources management. Geosci. Model Dev. Discuss. 08, 1–49 (2019).◼ Hanasaki, N., Yoshikawa, S., Pokhrel, Y. & Kanae, S. A global hydrological simulation to specify the sources of water used by humans. Hydrol. Earth Syst. Sci. 22, 789–817 (2018).
RCP6.0 (2071-2099) v.s.
base-period (1861-1960)
EGU2020-10748
(Example)
HS2.4.1, 07 May 2020
(NIES)
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