Exploring the Feasibility of Mitigating Flood Hazards by an Existing Pond System in Taoyuan, Taiwan
<p>(Overview map) Taoyuan city in the red box is located in northern Taiwan. (Main) The pond system in Taoyuan City (blue) is a multipurpose water facility for various applications, for example: (<b>a</b>) irrigation; (<b>b</b>) fish farming; and (<b>c</b>) ecology parks.</p> "> Figure 2
<p>Bade District in Taoyuan City is the demonstration site for flood detention simulation: (<b>a</b>) an overview of Bade District and pond locations (black polygon); (<b>b</b>) a blow-up view of the orange box in panel (<b>a</b>). The 20-m resolution elevation model from MOI does not appropriately reveal bathymetry in pond locations (red); and (<b>c</b>) The DEM is modified within ponds by depth information from the government database or our fieldwork.</p> "> Figure 3
<p>Workflow for pond measurements and to build an integrated digital elevation model with neighboring terrain.</p> "> Figure 4
<p>(<b>a</b>) A sample of micro-sonar that can measure water depth in 0.6–40 m; and (<b>b</b>) the entire module combines a DJI-P3A UAV, a micro-sonar, and an Android phone in a waterproof bag.</p> "> Figure 5
<p>A schematic diagram of surveying parameters in the target pond, where <span class="html-italic">d</span> is the depth from sonar, O<sub>1</sub> is the highest water level without a water gate, and O<sub>2</sub> is the highest water level when a water gate exists. The slope along the pond edge is assumed a constant <span class="html-italic">S</span>.</p> "> Figure 6
<p>Two examples of the integrated pond model in YM145 (<b>left</b>) and BD033 (<b>right</b>). Color code indicates water depth based on the highest water level.</p> "> Figure 7
<p>A schematic of SPM redrawn from [<a href="#B22-drones-07-00001" class="html-bibr">22</a>,<a href="#B30-drones-07-00001" class="html-bibr">30</a>]: (<b>a</b>) the terrain is illustrated as nine cells with varying elevations; (<b>b</b>) the flood occurs at cell #5 and the steepest slope in this region is shown as the red arrow, between two (cell #1 and #2) out of eight possible flowing directions (orange arrows); the planar angles between the red arrow and directions to cell #1 and #2 (angle a and b) are used as weights to allocate water accumulated in cell #5; and (<b>c</b>) the allocation process is iterated among cells until reaching a balanced water level.</p> "> Figure 8
<p>(<b>a</b>) The Otter Unmanned Surface Vehicle (USV) and a Norbit iWBMS multibeam echosounder scanning bathymetry; (<b>b</b>) Our UAV and a micro-sonar measurement (14 points), and the IDW-interpolated bathymetry; and (<b>c</b>) Scatterplot of depth values over 14 points.</p> "> Figure 9
<p>The 80 selected pond models. Each pond has an area greater than 2500 m<sup>2</sup> and at least 10 measurement points.</p> "> Figure 10
<p>A log scale comparison of: (<b>a</b>) water extent; and and (<b>b</b>) water storage in 80 selected ponds.</p> "> Figure 11
<p>SPM flood simulation under 75 mm rainfall scenario by using pre-emptied ponds: (<b>a</b>) flood patches (blue) and their links to the unfilled ponds (black line); (<b>b</b>) reduced flood patches (red) after floodwater redistribution; and (<b>c</b>) three main routes of water redirection to reduce flood hazard.</p> "> Figure 12
<p>Simulation of the flooded area in Bade District (north up). The terrain declined from south to north. Four panels represent rainfall simulations from 25 mm to 100 mm. The base map adopts Sentinel-2 natural color composite on 17 November 2019.</p> "> Figure 13
<p>The percentage of the reduced flood area and volume based on the TYWR database and the ones based on our fieldwork.</p> "> Figure A1
<p>Land use map of Bade District. (modified from Taiwan MAP Service, National Land Surveying and Mapping Center, <a href="https://maps.nlsc.gov.tw" target="_blank">https://maps.nlsc.gov.tw</a> (accessed on 1 July 2022)).</p> ">
Abstract
:1. Introduction
1.1. Pond Network in Taoyuan
1.2. Methods for Measuring Inland Waterbodies
1.3. A Novel Bathymetry Technique
2. Methodology
2.1. Workflow
2.2. Fieldwork Procedure
2.2.1. Modeling of Terrain DEM
2.2.2. Modeling of Pond DEM
2.3. Flood Simulation
2.3.1. Simplified Inundation Model (SPM)
2.3.2. A Virtual Channel Scheme to Dissipate Floodwater
3. Result
3.1. Validation of UAV Depth Measurements
3.2. Validation of Integrated Pond Models
3.3. Design of Drainage Channels from Virtual Network Dissipating Scheme
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
NUM | ID | S [°] | Min Depth [m] | Max Depth [m] | Estimated Area [m2] | TYWR Area [m2] | Ok [m] | Estimated Storage [m3] | TYWR Storage [m3] |
---|---|---|---|---|---|---|---|---|---|
1 | GI275 | 20 | 1.0 | 2.0 | 68,737 | 71,039 | 0.2 | 106,664 | 163,711 |
2 | CL086 | 60 | 0.5 | 1.5 | 36,456 | 39,632 | 0.6 | 51,313 | 22,194 |
3 | BD293 | 25 | 1.2 | 1.8 | 24,394 | 24,219 | 0.7 | 45,185 | 31,152 |
4 | BD027 | 60 | 0.7 | 1.1 | 25,922 | 25,975 | 0.8 | 39,370 | 39,890 |
5 | YM145 | 25 | 1.1 | 2.2 | 21,350 | 22,033 | 0.5 | 39,399 | 67,300 |
6 | GI277 | 25 | 1.2 | 2.2 | 64,744 | 62,735 | 0.7 | 134,353 | 145,900 |
7 | CL170 | 30 | 0.9 | 2.1 | 31,474 | 29,986 | 0.2 | 43,348 | 16,200 |
8 | CL143 | 27 | 1.3 | 2.5 | 62,326 | 64,182 | 0.5 | 133,196 | 4705 |
9 | HW256 | 30 | 1.4 | 2.9 | 22,477 | 21,696 | 0.5 | 54,315 | 22,060 |
10 | HW279 | 60 | 0.5 | 1.2 | 5732 | 7413 | 0 | 4303 | 12,416 |
11 | GI278 | 60 | 0.5 | 0.7 | 9187 | 9824 | 0 | 4915 | 7398 |
12 | GI279 | 60 | 0.5 | 0.8 | 23,608 | 25,315 | 0 | 13,343 | 19,063 |
13 | GI281 | 30 | 0.8 | 1.5 | 25,078 | 28,369 | 0.6 | 40,726 | 20,450 |
14 | GI283 | 60 | 0.5 | 1.2 | 36,175 | 37,414 | 0 | 28,719 | 21,290 |
15 | CL186 | 60 | 0.7 | 1.5 | 5693 | 5529 | 0 | 5497 | 1493 |
16 | PZ159 | 60 | 1.1 | 1.8 | 8068 | 8104 | 0 | 10,349 | 4537 |
17 | PZ160 | 60 | 0.5 | 1.5 | 4289 | 4239 | 0 | 4338 | 2373 |
18 | BD031 | 30 | 0.5 | 1.4 | 11,026 | 12,093 | 1.5 | 22,346 | 15,001 |
19 | BD032 | 23 | 1.8 | 3.1 | 11,216 | 10,548 | 0.7 | 29,465 | 13,085 |
20 | BD033 | 23 | 1.9 | 4.1 | 13,007 | 13,006 | 0.4 | 42,129 | 16,134 |
21 | GI260 | 30 | 1.0 | 3.2 | 27,918 | 26,917 | 0.6 | 64,578 | 37,331 |
22 | BD089 | 30 | 1.2 | 1.7 | 38,247 | 36,961 | 0.5 | 66,582 | 33,027 |
23 | BD090 | 30 | 0.7 | 2.1 | 12,514 | 8411 | 0.5 | 21,510 | 7516 |
24 | YM421 | 27 | 1.4 | 2.2 | 8661 | 8402 | 0.1 | 13,431 | 6715 |
25 | YM422 | 60 | 1.4 | 1.8 | 2683 | 3610 | 0 | 3530 | 2885 |
26 | YM427 | 30 | 0.9 | 1.8 | 6378 | 4918 | 0 | 6985 | 14,990 |
27 | PZ047 | 28 | 1.4 | 2.7 | 12,712 | 12,427 | 0.4 | 28,408 | 33,626 |
28 | PZ048 | 30 | 1.3 | 2.0 | 6846 | 6510 | 0.3 | 11,599 | 17,616 |
29 | CL233 | 35 | 0.8 | 3.5 | 5648 | 9360 | 0.3 | 9371 | 7696 |
30 | BD025 | 25 | 0.7 | 1.3 | 11,983 | 12,441 | 0 | 10,278 | 4336 |
31 | BD026 | 25 | 0.5 | 1.0 | 4745 | 5118 | 0.4 | 4602 | 1784 |
32 | BD010 | 30 | 1.0 | 1.4 | 5788 | 6340 | 0 | 6619 | 5790 |
33 | BD011 | 30 | 1.0 | 1.9 | 23,093 | 22,898 | 1 | 48,102 | 47,323 |
34 | YM187 | 30 | 2.2 | 4.4 | 40,608 | 38,727 | 0 | 112,656 | 42,380 |
35 | YM189 | 30 | 0.9 | 1.7 | 24,959 | 21,433 | 0.4 | 35,428 | 23,454 |
36 | YM344 | 22 | 0.7 | 1.9 | 86,244 | 86,085 | 0.7 | 155,564 | 247,140 |
37 | CL128 | 60 | 0.5 | 0.8 | 13,516 | 13,763 | 0 | 7378 | 13,073 |
38 | CL120 | 26 | 1.5 | 3.0 | 28,955 | 27,882 | 0.5 | 64,892 | 39,693 |
39 | YM346 | 25 | 0.5 | 0.9 | 63,450 | 65,130 | 0.4 | 60,790 | 137,743 |
40 | HW251 | 60 | 0.5 | 0.7 | 6560 | 6670 | 0.6 | 7169 | 5870 |
41 | YM049 | 25 | 2.1 | 2.7 | 21,001 | 21,473 | 0.3 | 47,260 | 60,638 |
42 | YM300 | 30 | 1.3 | 2.2 | 21,921 | 20,457 | 0.6 | 46,038 | 70,000 |
43 | CL158 | 30 | 0.9 | 2.2 | 14,476 | 14,385 | 0 | 15,972 | 10,450 |
44 | YM029 | 25 | 0.8 | 1.5 | 35,804 | 38,775 | 0.5 | 51,139 | 59,900 |
45 | YM030 | 25 | 1.9 | 3.4 | 22,437 | 23,245 | 0.8 | 66,584 | 29,072 |
46 | YM330 | 25 | 0.9 | 2.7 | 25,951 | 25,184 | 1 | 61,341 | 65,300 |
47 | YM375 | 23 | 2.1 | 3.5 | 22,264 | 20,916 | 0 | 49,162 | 30,800 |
48 | YM377 | 25 | 1.5 | 2.4 | 15,931 | 18,164 | 1.5 | 46,481 | 126,000 |
49 | PZ144 | 30 | 1.9 | 2.2 | 2587 | 3261 | 0.6 | 5918 | 5454 |
50 | PZ145 | 30 | 1.4 | 1.9 | 2712 | 2557 | 0.3 | 4618 | 4276 |
51 | PZ175 | 30 | 0.9 | 1.3 | 5752 | 5391 | 0.5 | 8314 | 5355 |
52 | PZ172 | 60 | 0.6 | 0.8 | 9652 | 10,337 | 0 | 6267 | 6206 |
53 | YM051 | 30 | 2.1 | 3.8 | 46,761 | 45,493 | 0.6 | 137,851 | 12,495 |
54 | YM052 | 27 | 1.9 | 2.5 | 31,836 | 30,557 | 0.4 | 71,891 | 40,334 |
55 | YM343 | 30 | 0.8 | 2.0 | 37,884 | 36,331 | 0.5 | 69,664 | 82,160 |
56 | YM082 | 35 | 1.4 | 1.9 | 14,798 | 15,159 | 0 | 21,119 | 5940 |
57 | HW294 | 30 | 1.2 | 1.5 | 10,794 | 10,408 | 0 | 13,006 | 11,980 |
58 | YM076 | 25 | 0.5 | 1.5 | 52,130 | 51,825 | 1 | 87,449 | 108,110 |
59 | YM095 | 23 | 1.1 | 2.0 | 24,241 | 25,701 | 0.6 | 41,776 | 34,469 |
60 | YM350 | 25 | 1.1 | 2.1 | 24,434 | 24,433 | 0.5 | 43,389 | 31,618 |
61 | YM352 | 25 | 1.7 | 2.5 | 27,336 | 27,713 | 1 | 75,154 | 79,000 |
62 | BD075 | 60 | 1.1 | 1.4 | 3639 | 4237 | 0 | 4154 | 2892 |
63 | BD036 | 30 | 0.8 | 1.6 | 10,233 | 9402 | 0.6 | 15,025 | 9750 |
64 | BD165 | 30 | 0.7 | 1.7 | 10,464 | 10,945 | 0.8 | 17,381 | 13,672 |
65 | YM378 | 30 | 1.5 | 2.9 | 36,501 | 37,547 | 0.5 | 82,852 | 63,390 |
66 | YM379 | 25 | 1.4 | 3.2 | 21,051 | 23,766 | 0.8 | 53,320 | 68,865 |
67 | BD012 | 30 | 1.2 | 1.5 | 5894 | 5382 | 0 | 6943 | 11,123 |
68 | CL273 | 60 | 0.5 | 0.7 | 14,079 | 14,365 | 0 | 7722 | 18,810 |
69 | CL313 | 30 | 0.9 | 1.3 | 3906 | 4960 | 0 | 4060 | 6205 |
70 | YM542 | 30 | 0.5 | 1.4 | 6108 | 6214 | 0.3 | 7016 | 11,380 |
71 | YM520 | 30 | 0.9 | 1.7 | 3074 | 3379 | 0 | 3965 | 3210 |
72 | YM462 | 30 | 0.8 | 1.2 | 5580 | 6647 | 0.6 | 7979 | 12,330 |
73 | YM461 | 60 | 0.5 | 1.8 | 6256 | 7037 | 0 | 5392 | 11,776 |
74 | YM147 | 60 | 0.6 | 0.9 | 5090 | 4703 | 0 | 3576 | 10,380 |
75 | YM310 | 20 | 0.8 | 2.4 | 26,442 | 26,155 | 0.8 | 61,280 | 82,000 |
76 | YM313 | 20 | 1.5 | 3.4 | 27,814 | 26,497 | 0.5 | 66,586 | 36,329 |
77 | HW259 | 60 | 0.5 | 0.9 | 3462 | 4333 | 0 | 2192 | 5769 |
78 | HW260 | 60 | 0.7 | 1.6 | 4444 | 3856 | 0 | 3904 | 5400 |
79 | YM120 | 60 | 0.7 | 1.5 | 6448 | 7145 | 0 | 5347 | 10,298 |
80 | YM163 | 30 | 0.8 | 1.5 | 6870 | 5573 | 0 | 6469 | 8034 |
Appendix B
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Tseng, K.-H.; Yang, T.-H.; Chen, P.-Y.; Chien, H.; Chen, C.-F.; Hung, Y.-C. Exploring the Feasibility of Mitigating Flood Hazards by an Existing Pond System in Taoyuan, Taiwan. Drones 2023, 7, 1. https://doi.org/10.3390/drones7010001
Tseng K-H, Yang T-H, Chen P-Y, Chien H, Chen C-F, Hung Y-C. Exploring the Feasibility of Mitigating Flood Hazards by an Existing Pond System in Taoyuan, Taiwan. Drones. 2023; 7(1):1. https://doi.org/10.3390/drones7010001
Chicago/Turabian StyleTseng, Kuo-Hsin, Tsun-Hua Yang, Pei-Yuan Chen, Hwa Chien, Chi-Farn Chen, and Yi-Chan Hung. 2023. "Exploring the Feasibility of Mitigating Flood Hazards by an Existing Pond System in Taoyuan, Taiwan" Drones 7, no. 1: 1. https://doi.org/10.3390/drones7010001