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蛇行河川の内部接続性に関する 実 験　－ 埋 蔵されたチャンネルへの適用に向けて

蛇行河川の内部接続性に関する 実 験　－ 埋 蔵されたチャンネルへの適用に向けて EXPERIMENTAL STUDY OF CONNECTIVITY IN MEANDERING RIVERS: IMPLICATIONS FOR STRATIGRAPHIC STRUCTURE OF BURIED CHANNELS. STRATODYNAMICS WORKSHOP Nagasaki University , August 28, 2013 Matthew Czapiga and Gary Parker

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蛇行河川の内部接続性に関する 実 験　－ 埋 蔵されたチャンネルへの適用に向けて

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  1. 蛇行河川の内部接続性に関する実験　－ 埋蔵されたチャンネルへの適用に向けて EXPERIMENTAL STUDY OF CONNECTIVITY IN MEANDERING RIVERS: IMPLICATIONS FOR STRATIGRAPHIC STRUCTURE OF BURIED CHANNELS STRATODYNAMICS WORKSHOP Nagasaki University, August 28, 2013 Matthew Czapiga and Gary Parker Dept. of Civil & Environmental Engineering and Dept. of Geology University of Illinois Urbana-Champaign, USA

  2. 実験を行ったのはMatthew Czapigaという、私の院生です。 My student Matt Czapigaperformed the experiments

  3. 蛇行河川の内部接続性とは How is internal connectivity defined for meandering rivers? A A点とB点を考える Consider points A and B そしてある属性を考える And some attribute  B Wampool River, UK

  4. 蛇行河川の内部接続性とは How is internal connectivity defined for meandering rivers? たとえば、 ＝流速、または水深 For example,  = velocity or depth A ある水理条件において、２点をつなぐ、l<  < uという条件を満たす、連続した経路が存在する確立を求める。 At a given flow, we look for the probability of a path between two points for which the condition l<  <  is satisfied. B

  5. 層序学ー埋蔵されたチャンネルへ適用性 Stratigraphy - Applicability to buried channels  ＝炭化水素の透性係数  = hydraulic conductivityof hydrocarbon 吸い出せるかな Can I suck it out? http://sepwww.stanford.edu/oldsep/david/Thai/cube.gif Abreu, Sullivan, Pirmez, Mohrig (2006)

  6. 事例として河川における、船の航行可能性を考える事例として河川における、船の航行可能性を考える As an example, we consider river navigability(traversability)  = H = 水深 depth 船が座礁せずに航行するには水深がある最低値Hminを下回ってはいけない。ここに、H  Hminを満たす、距離Lの連続した経路の存在確率PT(HHmin, L)を求める。 A minimum depthHmin is required in order for a ship to navigate without going aground. What is the probability PT(HHmin, L) that a continuous path of length L exists satisfying H  Hmin? 大丈夫かな？

  7. ２０１２年、ミシシピ川流域の渇水 Mississippi River basin, drought of 2012

  8. 断面ではなくて区間平均の満杯水理幾何パラメータ断面ではなくて区間平均の満杯水理幾何パラメータ Hydraulic Geometry Parameters based on Reach Averaging rather than Cross-section bf = 満杯状態における水面高 water surface elevation at bankfullflow Hbf = 満杯水深 bankfull depth Bbf = 満杯川幅 bankfull width Wabash River, USA

  9. 満杯水理幾何のパラメータで無次元化する Dimensionless Formulation using Parameters of Hydraulic Geometry  = （あるときの）水面高　　ｂｆ water surface elevationat a given time  bf Hmin = 航行するに必要とする最低水深（喫水） minimum depth required for navigation (draft) L = 縦断方向の航行経路距離（任意） length of navigation path Pc = L距離に渡って、連続した経路が存在する確立 Probability that H  Hmin over continuous path of length L We assume that と仮定する

  10. 無次元パラメータの意味 Meaning of Dimensionless Parameters 喫水が増大する　draft increases, Pc 水位が下がる　stage decreases, Pc 航行距離が増大する　navigation path lengthens, Pc

  11. 固定河床近似 Frozen Bed Approximation とをひとつのパラメータ=  + に組み込む Roll  and  Into a Single Parameter  =  +  喫水が増大することと水深が減少ことを同等であると考える Assume that increased draft is equivalent to shallower flow この条件を正確に満たすには、川床形状は水位に対して不変でなければなない。 In order for this condition to hold precisely, the bed shape must be invariant to stage. 従ってハイドログラフを伴う、局所洗掘と堆積を無視することになる。 So local scour and fill associated with the flow hydrograph is neglected.

  12. 実河川の計算例 Sample Calculation for a River Trinity River USA data from V. Smith, D. Mohrig Pc   • ~ 指数関数形 • exponential function? • ~ 正規分布形 • Gaussian distribution?

  13. 固定河床近似の適用例 Example of Application of Frozen Bed Approximation Vermillion River, Minnesota, USA Estimated Connectivity Assuming  = 0.6  = bf - 0.6 Hbf Computed Bankfull Connectivity,  = 0 「台地」 Pc=1 「山腹」 Pc 「盆地」Pc=0   Path Width = 0.01*BBF

  14. 水位が下がると接続性が減少する As stage falls, connectivity is reduced Computed Bankfull Connectivity,  = 0 Estimated Connectivity Assuming  = 0.6  

  15. Previous Work でもその近似はどうかな？ Is the Frozen-bed Approximation Realistic? Qw=34,300 m3 s-1 Qw=6120 m3 s-1 Q = 34,300 m3/s Q = 6120 m3/s Mississippi River Cour. J. Nittrouer

  16. では、実験で試してみよう OK, Let’s test it experimentally Kinoshita Flume, VenTe Chow Hydrosystems Laboratory

  17. 河床材料　－クルミ殻粉 Sediment- Walnut shells D50=1.1mm Flow: Q= 3 L/s H=3-4 cm C.S.# 20 C.S.# 10

  18. 「満杯流量」における平衡状態に達してから流量を下げて間もなく、局所再編成を調べる「満杯流量」における平衡状態に達してから流量を下げて間もなく、局所再編成を調べる After equilibrium is reached at “bankfull flow”, we lower the flow and investigate bed reorganization shortly afterward 「満杯流量」 “Bankfull flow” Q = 12.3 l/s tEQ = 4 hrs 「流量を下げて５分後」 5 minutes after lowering discharge Q = 10 l/s tEQ = 0.33 hrs

  19. クソッ! 流量を下げると接続性が増えた！ Aw Shit! Connectivity was higher at the lower flow! Predicted low flow, frozen-bed Actual low flow, frozen-bed Bankfull Probability of Connectivity Pc     Width = 0.01*BBF More connected here!

  20. 水深の残差 Residual Difference in Depth Bankfull is Deeper Bedforms have migrated in some places Ripple section shows more depth in QH,EQ->M Low Flow is Deeper

  21. 流量が下がったのに、接続性が増えた原因は河床形態が再編成し、波長も波高もさがったことにあるようである 　 Connectivity apparently increased at low flow due to reorganization of bedforms: shorter wavelength and amplitude 「満杯流量」 “Bankfull flow” 「流量を下げて５分後」 Five minutes after lowering discharge

  22. 結論ー 実河川における、固定河床近似の妥当性を追及するには、 ハイドログラフのさまざまな時点での音波調査が必要である。 Conclusion: In order to investigate the frozen-bed approximation in rivers, sequential seismic bed surveys at different points of a hydrograph are necessary.

  23. ご清聴ありがとうございます Thank you for your attention

  24. ここから先は添削しなくても結構です！

  25. How do depth fluctuations compare from QH,Eq to QH,EqM? Root mean square fluctuations are normalized by the average channel depth within the reach. For both cases, the fluctuations occur on the order of the average channel depth; this is significantly larger than our accompanying analysis of river data. Bedforms occurring in the Kinoshita flume are more similar to bars than dunes. This is likely caused by the large sediment size used (D50 = 1 mm , S.G. = 1.3), which is very mobile, but too large to form dune features. Overall trends in fluctuations are quite similar between these experiments; therefore, the increase in connectivity is related to the local reorganization of bed material which opens up more or larger connective paths. Normalized Root Mean Square fluctuation magnitude QH,EQ QH,EQ->M Normalized Width

  26. 解析の対象としている蛇行河川 Meandering Rivers being Analyzed 25 Km 500 m Scaling

  27. 解析の対象としている蛇行河川 Meandering Rivers being Analyzed Vermillion River, USA Trinity River Downstream, USA Trinity River Upstream, USA Wabash River, USA Mississippi River, USA

  28. 面積高度曲線 Hypsometric Curves 超過確率 尾根が流れ方向なのかそれと直角なのかわからないから接続性の定量化に直接適用できない。 Not directly adaptable to connectivity because whether the high points extend streamwise or lateral is not specified. H/Hbf

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