In Japanese rivers, the decrease of fishery resources such as fresh-water fish species is an important environmental issue. Some researchers hypothesize that the issue is caused by changes in biological productivity due to increase of water depth. We must clarify the influence of increase of water depth on biological productivity. At first step, we started to model biological productivity mechanism considering water depth characteristics, through field observation and model studies in the Chikuma River, a high-productivity Japanese river.
Net Primary Production (NPP) equals Gross Primary Production Including Respiration (GPPIR) minus Grazing Biomass (GB) and Detachment Biomass (DB), as formulated in this equation: NPP = GPPIR - (GB+ DB). Although observation of DB is extremely difficult, NPP can be observed in field.,
GPPIR are estimated in laboratory, GB can be simulated through estimation of aquatic insect biomass fish biomass and their feeding amount. Therefore, we conducted field survey on NPP observation from FY2015-2017 and estimated GPPIR considering relationship light radiation and water depth characteristics in laboratory in FY2016. Through we simulated the biomasses using physical habitat model and estimated feeding rate referencing the presetnt study, we estimated the GB.
IF we succeed to estimate DB in, DB would be similar with (Organic Matters Concentration, OMC). To verify the model, we compared the concentration of DB to OMC. After, we simulated the biological productivity in old river condition such as fifty years ago that had large water area and shallow water depth.
Based on the model, we estimated the DB value as 4.2mg /m3 while observation data gave an OMC value of 1.5mg/m3. The estimated and observed values corresponded approximately in order of magnitude. This result indicated the model have certain accuracy And the model estimated two times of the biological productivity in old river condition.
Masatoshi Denda– Senior Researcher, Public Works Research Institute, Ibaraki-Ken