〓 Research Area : Irrigation and Drainage

Study on balancing agricultural practices with nature
to protect water resources
Agriculture is essential to modern civilization but often has unintended negative effects upon the natural environment,
especially regarding water quality. Overuse of fertilizers is costly both economically and environmentally. We evaluatedregional agricultural cultivation practices to determine optimal irrigation and fertilizer, timing and amounts, to maximize
production while minimizing nutrient-driven eutrophication of local water bodies.
Agricultural fields are used not only by farmers, but also by wildlife. We studied the effects of the Tundra Swan onnutrient levels in rice paddies. Tundra Swans, from Far East Russia, overwinter in flooded paddy-fields from November to March. They roost in the paddy-fields at night and forage nearby in other agricultural fields during the day. We
measured Tundra Swan manure-nutrient component of paddy-field soil and water nutrient concentrations to determine
optimal farmer-applied fertilizer amendments required for rice production, without over-applying.
Our ultimate goal is to find a win-win-win relationship among the environment, humans (farmers), and wildlife with respect to water quality.

Study on irrigation management for stabilizing agricultural production〓 Assoc. Prof.
SOMURA Hiroaki

Water is critical for agriculture and irrigation practice is an important part of farm management. Irrigation water isoften wasted or poorly applied (i.e., amount or timing) leading to lowered agricultural production from poor crop healthor damage. It is important to evaluate water resource availability to effectively manage irrigation timing and amounts
required for efficient crop production.
We assessed watershed-level water availability upon a local irrigation scheme. Data were gathered through fieldobservations and farmer questionnaires. Data were evaluated by computer modeling. At the watershed level, irrigationwater allocation is spatially unbalanced among upstream, midstream, and downstream observations. We attempted todetermine alternative management methods and/or improve current methods for efficiently allocating irrigation water
equally to the fields.
By improving irrigation water use efficiency through better allocation management, there is an apparent increase in wateravailability. This will lead to an expanded cultivation area, higher production, and ultimately, better agricultural stability.

〓 Research Area : Catchment Hydrology

Development of real-time forecasting system usinghydrological model and data assimilation technique

Recently, flood damage has become serious problem around the world due to the changes in climate condition. Flood forecast system using hydrological model is useful tool to mitigate the flood damage. One of the main topics in our research team is to develop real-time flood
forecasting system using distributed/lumped hydrological models and radar rainfall data. In addition, to improve forecasting accuracy, weintroduce data assimilation techniques like Kalman Filter and Particle Filter into the forecasting system, and investigate the uncertainties
caused by hydrological modeling including parameter setting and by weather/climate forcing data as an input to the hydrological models.

Fig u r e 1 S p a tia l
distribution of rainfall based on radar
dataFigure 2 Exampleof real-time flood
forecasting.

The impact assessment of climate change on hydrological cycle using hydrological model andclimate scenarios. -Uncertainty analysis of impacts of climate change on snow processesThe impact of climate change on snow water equivalent (SWE) and its uncertainty were investigated in snowy areas in Japan by using a snow process modeland climate projections derived from general circulation models (GCMs). In particular, we examined how the uncertainty due to GCMs propagated through thesnow model, which contained nonlinear processes defined by thresholds. The uncertainty analysis demonstrated that when the peaks of the distributions ofdaily mean temperature projected by GCMs cross the key thresholds set in the snow model, the GCM uncertainty, even if tiny, can be amplified by the nonlinear propagation through the snow process model. This amplification results in large uncertainty in projections of CC impact on snow processes.

〓 Prof.
CHIKAMORI Hidetaka〓 Assoc. Prof.
KUDO Ryoji

Figure 3 Changes in
SWE for the emission
scenarios: near future,
RCP2.6, RCP4.5, andRCP8.5.

Figure 4 Projection
ranges of regionallyaveraged changes in
winter-mean temperature and SWE.

Graduate School of Environmental and Life Science, Okayama University21