Water Resources Planning Lab., TUAT, Japan 

Research

Balancing Water, Agriculture and Ecosystems!

Water, agriculture and ecosystems are the main research components of this laboratory. We aim to find a balance between the three components for better water resources and ecosystems management for improved agricultural production and enhanced ecosystem services. To this end, field surveys will be conducted and then the observation data are analysed and used for mathematical modelling. Our research can be characterized by two approaches, namely data-driven modelling and process-based modelling. In data-driven modelling, machine learning and computational intelligence are applied in the fields of ecohydraulics, ecoinformatics, hydroinformatics, etc. Process-based modelling is mainly for spatio-temporal modelling of fish behaviour and watershed hydrology, in which machine learning and other data-driven will be used supplementarily. Most of our research topics are based on joint works with domestic and international colleagues.

Data-driven modelling

 Ecohydraulics 

Ecohydraulics is an integrated science, linking hydraulics with ecology. This interdisciplinary approach is highly applicable when understanding the responses of aquatic ecosystems to hydrodynamic conditions in a target site. In ecohydraulics, various modelling approaches are used: for instance, habitat suitability models, hydrodynamic models (1D, 2D, 3D), fish behaviour models (mainly for fish pass studies), etc. With emerging survey technologies such as biotelemetry and ADCP (acoustic Doppler current profiler), this research field is now advancing in both ecology and engineering. The Water Resources Planning Laboratory employs both equipment for better understanding and modelling aquatic ecology under various hydrodynamic conditions.

 Ecoinformatics 

Ecoinformatics is an emerging research field in which new techniques for data analysis and modelling are being developed. Recent development in machine learning allows for predictive modelling and knowledge extraction useful for a better understanding of target ecosystems or species, contributing to improved management strategies under a given condition. Specifically, we apply various machine learning methods as a data-driven modelling method for habitat suitability assessment, species distribution modelling and the assessment of species invasions.  

 Hydroinforamtics 

Hydroinformatics has devoted to time-series analysis in hydrology such as rainfall-runoff modelling and is one of the major fields where advanced machine learning has been employed. This approach, in general, is more accurate compared to complex process-based models in which large amount of model parameters need to be optimised. Hydroinformatics can thus be a useful tool for short-term forecasting of hydrologic events and water quality dynamics.

 Data-driven modelling of pre-harvest and post-harvest systems 

Improving agricultural productivity is an important step for counteracting the increasing food demands for rapidly growing world population. In addition, food safety has become an emerging concern in globalised food supply chains. The Water Resources Planning Laboratory applies data-driven approaches to better model pre-harvest and post-harvest systems and extract various information useful for improved management systems.

 

Process-based modelling

 Spatiotemporal modelling of fish behaviour 

With spatiotemporal data from advanced biotelemetry surveys, we aims to model fish behaviour under dynamic environments, for which mathematical models based on ecological knowledge will be developed. Model results shall be used for assessing habitat use and migration patterns of target fish species in target rivers and agricultural canals. Numerical simulations will then be made for better management strategies that can balance benefits for human and aquatic ecosystems.

 Hydrologic modelling 

In contrast to the hydroinformatics approach, process-based hydrologic models are useful for understanding the detailed hydrologic processes in a watershed. For instance, hydrologic cycle and water quality dynamics in a watershed are both affected by topographic features and landuse patterns in the watershed. Although there are a lot of model parameters to be optimised in a process-based hydrologic model, such parameters can illustrate hydrologic processes, based on which improved management strategies for landuse planning and agricultural practices can be proposed. We seek for better modelling approaches according to local conditions and data availability in our target systems.

Laboratory

Our laboratory has re-established on February 17, 2014 when Dr. Shinji Fukuda joined TUAT. Thanks to the achievement in the previous phase of this laboratory, we could start research activities right after the restart. We welcome highly motivated and active students. Please come and visit us anytime you want (but, I would highly appreciate if you could send me a message prior to your visit).  Also, please click here to check our activities!!!

Members

	Position	Name	E-mail*	Research
	Professor	Shinji Fukuda TUAT,ORCID	shinji-f	Ecological modelling; Ecoinformatics; Ecohydraulics; *Targeting in and around irrigation and drainage systems
	Postdoctoral researcher	Koji Nishisue		Deep learning and image analysis for tracking insect movement
	Office administrator	Atsuko Hatakeyama		Essential works at the laboratory
	DC3	Yuto Kamiwaki		Advanced sensing system for crop production system
	MS2	Wataru Ishikawa		Image-based underwater monitoring system
	MS2	Tomoya Ohgami		Instream habitat assessment of macroinvertebrates in the Yagawa/Fuchu Yosui system
	MS1	Shunsuke Fujimori		Image-based assessment of fish behavior
	MS1	Shunsuke Kodera	-	Underwater monitoring system for small stream
	MS1	Nanami Koto	-	Hydrodynamic modelling of the Yagawa/Fuchu Yosui systems
	MS1	Yuki Hoshino		Data-driven modelling for assessing the impact of climate change in rice production
	MS1	Naoto Yamada		Application of robotics and informatics to model movement trajectories of a pest insect under a spatiotemporally dynamic wind field
	MS1	Yuto Yamazaki		Laboratory and field assessment of fish behaviour against flow intermittency
	UG4	Sumika Akahane		Impact of flow intermittency on species distributions in the Yagawa and Fuchu Yosui Irrigation System
	UG4	Taichi Iwama		Numerical modelling of hydrodynamics in Yagawa and Fuchu Yosui Irrigation System
	UG4	Ko Ogawa		Modelling and visualization of spatial distributions of water flow and habitat suitability in the Yagawa river and Fuchu Yosui Irrigation System
	UG3/MS1	Join us!!!	-	Balancing Water, Agriculture and Ecosystems!!! Ecohydraulics, Ecoinformatics, Innovative measurement, Data-driven modelling, Irrigation and drainage, etc.

*followed by @cc.tuat.ac.jp

OB/OG

Photo	Position	Name	Research
	PhD	Yuki Matsuzawa	Modelling habitat suitability and species interactions of Lefua echigonia in a small spring-fed urban river
	MSc	Taichi Jibiki	Data-driven modelling of spatiotemporal distribution and population dynamics of the Candidia temminckii in a small spring-fed river
	MSc	Risa Kawashima	Topographical survey and two-dimensional hydrodynamic modelling in a river channel with wando backwater
	MSc	Takuma Nishimura	Assessment of model performance of YOLO and its explainability for the detection and species identification of waterfowl
	BSc	Naoyuki Ishida	Species-specific distribution models for fishes in the Yagawa River and Fuchu Yosui Irrigation System
	MSc	Koki Asano	One-dimensional hydrodynamic modelling and fish habitat assessment considering the impact of Ba Lai gate in the Mekong Delta
	MSc	Taichi Kasahara	Multivariate analysis for the assessment of freshwater fish communities in the Miyara River, Ishigaki Island
	MSc	Akihiro Tanaka	Analyzing the relationships between habitat heterogeneity and fish fauna at different spatial scales
	BSc	Takahiko Kawasaki	2D hydraulic analysis and habitat assessment of freshwater fish in Yagawa River
	BSc	Seitaro Fujii	Water level assessment using a convolutional neural network
	MSc	Grant Thompson	Barrier-driven morphological differentiation of Rhinogobius nagoyae in Kanagawa and Chiba Prefectures, Japan
	MSc	Masato Kondo	An integrated habitat assessment based on fish migration analysis and one-dimensional hydrodynamic modelling
	MSc	Gao Shuo	Quantitative evaluation of water quality improvement by using composite zeolite-based photocatalyst
	MSc	Phen Bunthoeun	Random Forests model to assess the current situation of marine fisheries resources management in small fisheries community, Cambodia
	MSc	Seiya Aihara	Fish habitat assessment based on morphotypes of aquatic vegetation and physical habitat conditions
	BSc	Kan Funakoshi	Assessing the effects of aquatic vegetation on velocity distribution and fish behavior
	BSc	Mayu Shimada	Study on soil water dynamics and vegetation diversity at abandoned rice fields in small valley
	AIMS	Muhammad Hairul Izam Bin K. Abdul Rahman	Aquatic vegetation in the Fuchu Yosui irrigation system
	MSc	Yuki Matsuzawa	Modelling habitat suitability of Lefua echigonia and species coexistence patterns using Random Forests
	BSc	Hideyuki Okano	The applicability of environmental DNA to the estimation of spatial distributions of Japanese eight-barbeled loach (Lefua echigonia)
	BSc	Kurea Kawai	Ultrasonic biotelemetry for assessing spatial distributions and behaviors of freshwater fish in a small stream
	UG	Eriko Marukawa	Data-driven fish habitat assessment using fine-scale hydraulic data
	BSc	Kosei Aoki	Quantitative evaluation of the effectiveness of habitat restoration based on the critical swimming speed of Lefua echigonia
	AIMS	Amira L Safira	Community-based management of a reservoir
	BSc	Shiho Saito	Random forests as a tool for modelling range-expanding mammal species distributions in Japan
	BSc	Satoshi Onoue	Assessing genetic disturbance by Pseudorasbora Parva and its functional responses
	Postdoctoral Researcher	Mitsuru Ohira	Biodiversity, freshwater fish, macroinvertebrates
	SSSV (2015)	Giulia Lembo Caterina	Efficient Eucalyptus production under climate change (Application of Random Forests for water use estimation)

Publications and Academic Activities

Please find the links below for our achievement (partly in Japanese).

• Papers (peer-reviewed) [Journal, Conference]
• Papers (without peer-review) [Journal, Conference]
• Books, reports and invited talks [link]
• Conferences [International, Domestic]
• Awards [link]
• Research funds [link]
• Academic activities [link] 

Lab. Activities

Please check here.

Access

Water Resources Planning Laboratory
Division of Environmental and Agricultural Engineering,
Institute of Agriculture
Tokyo University of Agriculture and Technology

Address:

3-5-8 Saiwai-cho, Fuchu, Tokyo 183-8509, Japan
 (Fuchu Campus, Building 3, Room 311)

See TUAT Website for access information.