Alternative Title東日本における流域特性を使用したベースフローと低流量指数の回帰モデリング
Note (General)Baseflow is the portion of streamflow derived from delayed subsurface pathways. The baseflow index (BFI) is a ratio of baseflow to total streamflow, and is an important hydrological variable when linking watershed characteristics to baseflow. In addition, the BFI and runoff trend analysis could be used to assess the impact of climate change and human activity on river systems. The 'smoothed minima' procedure of baseflow separation was applied to streamflow data (29-67 years) from twenty-six gauges of watersheds in eastern Japan. The Mann-Kendall statistical test and Sen's slope estimator were used to identify trends and estimate the rate of change in annual and seasonal runoff and BFI per decade at 0.01 and 0.05 significance levels. According to what I know, this is the first study to investigate long-term trends in runoff and BFI for watersheds in the large-scale region of eastern Japan. Results showed significant trends in annual runoff and BFI, with a concentration of significant seasonal trends occurring in winter, with five gauges showing trends in runoff and nine gauges showing trends in BFI. The results suggest that the response of annual and seasonal runoff and BFI to climate change can already be seen, which implies that policymakers need more information on the impacts of climate change and human activities to manage water resources sustainably. A convenient technique was suggested for the matching strip method in determining the recession constant of the master recession curve using the ratio of flow over successive days (Qn+1/Qn). The procedure was applied to 29 basins (6.1-740km2) in eastern Japan to build linear regression models which estimate low flow indices through the recession constant (λ), and either mean annual precipitation or mean annual runoff. Statistically, significant models with an additive format (no log transformation) were built for dependent variables; Q710 (7-day 10-year low flow), and Q9710 (10-year low flow exceeded 97% of time) in the case of all basins, and in particular, the case of basins classified into sedimentary or igneous lithology with the adjusted R2 up to 0.784. In case of all basins lumped together, regression models based on mean annual runoff as the second independent variable performed better than those based on mean annual precipitation, with adjusted R2 of 0.705 and 0.717 for the Q710 and Q9710 models, respectively. The thesis also developed models with a multiplicative format (log transformation) to estimate annual BFI and Q710 flow index using the mean annual runoff and either mean elevation or maximum elevation. Five out of the six models developed were significant, with adjusted R2 values up to 0.482 (Q710 model for sedimentary lithology). These significant regression models could be applied to poorly gauged watersheds to manage water resources sustainably in eastern Japan and contribute towards achieving SDG6.
新大院博(農)第237号
Collection (particular)国立国会図書館デジタルコレクション > デジタル化資料 > 博士論文
Date Accepted (W3CDTF)2023-06-02T22:06:21+09:00
Data Provider (Database)国立国会図書館 : 国立国会図書館デジタルコレクション