Estimating and Classifying Spatial and Temporal Distributions of Flow Conditions for Fish Habitats by Using Geostatistical Approaches with Measured Flow and Fish Data, Lin Yu-Pin, Wang Cheng-Long
Estimating and Classifying Spatial and Temporal Distributions of Flow Conditions for Fish Habitats by Using Geostatistical Approaches with Measured Flow and Fish Data, Lin Yu-Pin, Wang Cheng-Long
DY Atagi MSc Thesis Estuarine Use by Juvenile Coho Salmon ubc_1994-0362
Ähnlich wie Estimating and Classifying Spatial and Temporal Distributions of Flow Conditions for Fish Habitats by Using Geostatistical Approaches with Measured Flow and Fish Data, Lin Yu-Pin, Wang Cheng-Long
Ähnlich wie Estimating and Classifying Spatial and Temporal Distributions of Flow Conditions for Fish Habitats by Using Geostatistical Approaches with Measured Flow and Fish Data, Lin Yu-Pin, Wang Cheng-Long (20)
Estimating and Classifying Spatial and Temporal Distributions of Flow Conditions for Fish Habitats by Using Geostatistical Approaches with Measured Flow and Fish Data, Lin Yu-Pin, Wang Cheng-Long
1. Estimating and Classifying Spatial and Temporal Distributions of Flow Conditions for Fish Habitats by Using Geostatistical Approaches with Measured Flow and Fish Data Advisor:Lin Yu-Pin , PH.D Presenter: Wang Cheng-Long 1 Environmental and Landscape Ecological Lab
4. Streams are heterogeneous environments where organisms exhibit patchy distributions on a spatially and temporally variable physical arena To improve the accuracy of flow conditions judgment, the habitat model identifying the flow conditionsare clearly illustrated by four key variables: water depth, water velocity, substrate composition and in-stream cover. 4 Velocity, depth, river cross-sections, slope, substrate…etc Flow conditions (i.e. Pool, Riffle, Slack, Run) Froude Number method Empirical method
5. This study objectives: (1)Simulate the velocity, depth and fish probability in the investigating reaches. (2)Estimate the flow condition requirement of S. japonicus, in order to find the preference of S. japonicusin reach scale. (3)Discover the relation between the classifications of flow conditions and S. japonicusin the seasonal variations. 5
9. The Krigingestiamtion is divided into two sections : (1)Ordinary Kriging is used to interpolating velocity/depth value in the unsampling sites. (2)Indicator Kriging is applied to estimating the fish probability in the reach. 9
10. 10 Flow classificationmethods Flow conditions of estimated velocity and water depth values are classified by Froude number (Jowett, 1993) and the empirical method (Wong, 2000).
11. The overlapping of the fish probability and flow condition maps. Fish probability + Flow condition fish probability map flow condition maps Fig. 2 overlapped mapping 11
12. Using the combination of flow condition maps and GIS, it could be easy to show the relation between the flow condition and fish probability in topology in Datuan stream . GIS exhibition
14. Empirical method in winter Reach (1) (2) (3) (4) Pool and run occupied the stream area in reach 1,2 and 3 Run appeared at the most area of reach 4, but some pools were distributed in the middle section. Fig. 3a Fig. 3b Fig. 3c Fig. 3d 50m 14
15. 15 Fig 3a. Reach (1) Fig 3b. Reach (2) Fig 3c. Reach (3) Fig 3d. Reach (4) Reach 1 in winter had only one type of flow conditions (pool). The area ratio of pool is reduced except that of the probability of 0~0.2. Run was the only flow condition in reach 2 (Fig. 3b). In addition, the variation of area ratio was increased by the raising of probability. Run occupied the area of reach 3 (Fig. 3c), the area of run was increased except for the probability interval of 0.8~1. The area of run was greater than the other flow condition (pool). It means that run was one of the suitable habitats for S. japonicus.
16. Froude Number method in winter In Fig. 3e and f, the result was close to Fig. 3a and b, but part of run occurred in reach 1. Pool and riffle also occupied the stream area in reach 3. The case differed from the result in the empirical method Run still appeared at the most area of reach 4, but the range of pool distribution is more widely in the Froude number method Fig. 3e Fig. 3f Fig. 3g Fig. 3h 50m 16
17. 17 Fig 3f. Reach (2) Fig 3e. Reach (1) Fig 3g. Reach (3) Fig 3h. Reach (4) There was a difference between the two classifications. Run (Fig. 3c) was replaced with pool and riffle (Fig. 3g), and the areas of pool and riffle were increased except for the probability of 0.8~1. The type of Fig. 3e and f was similar to Fig. 3a and b with the difference of the appearance of run in reach 1 and 2. The type of Fig. 3h was identical to Fig. 3d, but the area of pool was larger.
18. Empirical method in spring The major flow conditions were pool in reach 1 and riffle in reach 2. And reach 2 had high heterogeneity of the flow. Run and riffle had the most two great area in the reach 3 and 4. The flow condition in reach 4 had high heterogeneity as same as which in reach 2. Fig. 4a Fig. 4b Fig. 4c Fig. 4d 50m 18
19. 19 Fig 4b. Reach (2) Fig 4a. Reach (1) Fig 4c. Reach (3) Fig 4d. Reach (4) The type of Fig. 4b was similar with Fig. 3b, riffle was the most important flow condition in reach 2, and the area ratio of it increased. Reach 3 was shared with run and riffle (Fig. 4c). The result was similar with Fig. 3c, but the area of riffle in spring was widely spread. Pool owned the most of area in reach 1, but some area belonged to riffle. Reach 4 had mixed flow conditions (pool, riffle, run, slack) (Fig. 4d)
20. Froude Number method in spring The downstream was mainly categorized as pool and run. Riffle (Fig. 4b) was easy to be identified with run (Fig. 4f) in reach 2. Run covered the most part of reach 3 There was a quite difference between the two flow classifications. The result in the Froude number method was as same as the empirical rule method; besides, part of pool and riffle were inlayed in reach 4. Fig. 4e Fig. 4f Fig. 4g Fig. 4h 50m 20
21. 21 Fig 4e. Reach (1) Fig 4f. Reach (2) Fig 4g. Reach (3) Fig 4h. Reach (4) In reach 3, run is almost the only flow condition, and the area of run increased except for the situation in the highest probability (0.8~1) (Fig. 4g) In reach 1, the area of pool decreased when the probability increased (Fig. 4e). Reach 2 had a mixed flow conditions which was similar to Fig. 3f, and run still owned the largest area in this reach (Fig. 4f). There were three flow conditions (run, pool, riffle) in reach 4, especially, run got the most of area (Fig. 4h)
23. 23 We combined the two classifications and kriging estimation in order to predicts the variability of stream conditions in a fish community, and discover its impact on the distribution in temporal scale. (2) Two key factors, current velocity and stream depth, are the most two important factors in the habitat preference of fish. The pool/riffle series are usually related with rank erosion and the type of substrate.
24. 24 (3) The result of the two classifications were not identical, especially in areas from downstream to middle stream under construction, and the classifications may also lose their accuracy due to the artificial disturbances. (4)Base on the fish’s life cycle (shelter, reproduction, food source), the result shows that the empirical method is more appropriate for Datuan stream than the Froude number method.
26. 26 (1)These results not only describe the abundance and heterogeneity of S. japonicusfrom downstream to upstream, but also quantify the area ratio of the combination of fish probability and flow conditions in each reach. (2) These outcomes reduce the cost in time and money, then provide ecological information for engineers to river restoration, which supply the suitable habitats for the life- cycle of S. japonicus.
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