Creating Integrated Scientific Knowledge for Disaster Risk Reduction,
Climate Change Adaptation and Sustainable Development
Toshio Koike1,2
1

Department of Civil Engineering, School of Engineering, The University of Tokyo
2
International Centre for Water Hazard and Risk Management (ICHARM),
Email: tkoike@hydra.t.u-tokyo.ac.jp

Our actions for development, meeting human needs such as food, water, energy andhealth, together with rapid increase in population have brought about societal problems suchas improper land use changes, disorderly urbanization, and unstable governance.
Development has also resulted in unwanted global-scale environmental issues such as climatechange, desertification, deforestation and loss of biodiversity. All of these are obstacles foreach state to achieving truly needed development goals, and even have become causes ofdevastating damage when coupled with intensifying hazards.
Under such serious circumstances, important global decisions were made and came tofruit in 2015, the Sendai Framework for Disaster Risk Reduction in March, the Sustainable
Development Goals in September and the Paris Agreement on Climate Change in December.
To clearly recognize and improve the connection among disaster resilience, sustainable
development and climate change and build resilient and sustainable societies, it is criticallyimportant to create holistic knowledge which is applicable to cross-disciplinary issues. We
need to establish interdisciplinary and transdisciplinary cooperative frameworks so thatscientific and technological knowledge can transcend disciplines and be realized by society.
The IPCC AR5 modeling strategy addresses climate change with a collaboration
between the climate models, integrated assessment models including energy, economy,agriculture, health, and the models of adaptation, vulnerability, and human settlement andinfrastructure. These models identify water as central to these systems. If a water expert candevelop an interrelated system including each component, the integrated crisis can beaddressed by collaboration with various disciplines. To realize this purpose, we aredeveloping a water-related data- and model-integration system called a water cycle integrator(WCI).
Various satellite data were archived to provide various hydrological information such as
cloud, rainfall, soil moisture, or land-surface snow. These satellite products were validated
using land observation in-situ data. Water cycle models can be developed by coupling in-situ
and satellite data. River flows and other hydrological parameters can be simulated andvalidated by in-situ data. Model outputs from weather-prediction, seasonal-prediction, andclimate-prediction models are archived. Some of these model outputs are archived on an
online basis, but other models, e.g., climate-prediction models are archived on an offline basis.
After models are evaluated and biases corrected, the outputs can be used as inputs into thehydrological models for predicting the hydrological parameters. Additionally, we havealready developed a data-assimilation system by combining satellite data and the models. Thissystem can improve our capability to predict hydrological phenomena. The WCI can provide
better predictions of the hydrological parameters for integrated water resources management
and climate change impact assessment.
We need to collaborate with other disciplines to make maximum use of hydrologicalinformation in other socioeconomic areas, including urban engineering, agriculture, andbiodiversity. With the cross-disciplinary exchange of data and models, usable information forenvironmental conservation and agricultural support can be provided by the WCI.
In November 2005, we developed the Global Earth Observation System of Systems-7-(GEOSS) Asian Water Cycle Initiative (AWCI) under this framework to promote integrated
water resource management by making available usable information from GEOSS. Eachmember country identified a river basin in their country as a WCI demonstration basin for
promoting transdisciplinary cooperation. Based on these experiences in Asia, we are now
working with African countries. We have agreed to a basic idea for implementation. Then, thefirst GEOSS Africa & Asia Joint Water Cycle Symposium was held in Tokyo at the end ofNovember, 2013.
We should accelerate such interdisciplinary and transdisciplinary cooperation to achieve
holistic solutions for seeking sustainable development, climate change mitigation andadaptation, and disaster risk reduction. The WCI is a supporting tool for guiding people tobuild resilient and sustainable societies.
REFERENCES
Hydrological Modeling and FloodLei Wang, Toshio Koike, Kun Yang, Thomas J. Jackson, Rajat Bindlish, and Dawen Yang
(2009):Development of a distributed biosphere hydrological model and its evaluation withthe Southern Great Plains Experiments (SGP97 and SGP99), J. Geophys. Res., VOL. 114,D08107, doi:10.1029/2008JD010800.
Oliver C. Saavedra Valeriano, Toshio Koike, Kun Yang, Tobias Graf, Xin Li, Lei Wang andXujun Han: Decision support for dam release during floods using a distributed biospherehydrological model driven by quantitative precipitation forecasts, Water Resources
Research, VOL. 46, W10544, doi:10.1029/2010WR009502, 2010
Shrestha, M., T. Koike, Y. Hirabayashi, Y. Xue, L. Wang, G. Rasul, and B. Ahmad (2015),
Integrated simulation of snow and glacier melt in water and energy balance-based,
distributed hydrological modeling fr amework at Hunza River Basin of Pakistan
Karakoram region, J. Geophys. Res. Atmos., 120, 4889-4919, doi:10.1002/2014JD022666.
Hydrological Modeling and Drought:
Patricia Ann Jaranilla-Sanchez, Lei Wang, and Toshio Koike, Modeling the hydrologic
responses of the Pampangga River Basin, Philippines: A quantitative approach for
identifying droughts, Water Resources Research, vol 47, Issue3, March 2011, doi.
10.1029/2010WR009702.
Yohei Sawada, Toshio Koike and Patricia Ann Jaranilla-Sanchez: Modeling Hydrologic andEcologic Responses using a New Eco-hydrological Model for Identification of Droughts,
Water Resources Research, 50, 6214-6235
Sawada, Y., T. Koike, and J. P. Walker(2015), A land data assimilation system forsimultaneous simulation of soil moisture and vegetation dynamics, J. Geophys. Res.
Atmos., 120, doi:10.1002/ 2014JD022895.

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