Recent disastrous heavy rain events and floods caused severe damages including human damages and house damages. Those include 119 fatalities and 213 totally destroyed houses due to 2018 Japan floods (July 2018) , 104 fatalities and 3308 totally destroyed houses due to Typhoon 19 (Hagibis, October 2019) and subsequent heavy rain events , and 84 fatalities and 1621 totally destroyed houses due to July 2020 heavy rain disaster . As the climate change progresses such disastrous heavy rain events and floods may occur more frequently, and it is important to establish reliable sources of information concerning land water areas such as rivers, reservoirs, and coastal areas.
This study focuses on construction of underwater topography based on data obtained in field measurement. Apparatuses including a RTK-GPS (real time kinematic global positioning system) in VRS (virtual reference station) mode and an echo sounder were used in measurement conducted in Kojima Lake, Okayama Prefecture, Japan. Measurement was conducted on September 28th, 2019, October 4th, 2019, December 25th, 2019, January 6th, 2020, December 26th, 2020, January 27th, 2021, March 17th, 2021, and March 20th, 2021    . Previous studies developed numerical techniques to construct surfaces based on data. Those techniques were applied to data sets obtained in the field measurement for construction of surfaces representing underwater topography. Numerical results show sedimentation during period from January 2020 to January 2021.
2. Application of Numerical Techniques to Data Sets
Numerical techniques developed in previous studies     were reapplied to two data sets. One data set, which we call data set 1, consisted of results of measurement conducted on September 28th, 2019, October 4th, 2019, December 25th, 2019, and January 6th, 2020. The other data set, which we call data set 2, consisted of results of measurement conducted on December 26th, 2020, January 27th, 2021, March 17th, 2021, and March 20th, 2021.
The Gauss-Krüger projection transformed latitude components and longitude components of GPS data to xy components of a rectangular coordinate. Combination of those components with vertical components including output results from an echo sounder leads to three dimensional data that lay in an underwater topography. In particular, z component of three dimensional data are given by , where is the GPS antenna height, is the distance between the oscillator of echo sounder and the bottom, is the geodetic height of the mean sea level, and L is the distance between the antenna and the oscillator. Figure 1 shows three dimensional data of Kojima Lake topographic data.
An underwater topography was represented by a piecewise linear function defined on a triangular mesh. An initial triangular mesh that contains GPS tracks was set in an xy plane. A sequence of triangular meshes were constructed from the initial mesh. A triangular mesh in the sequence was constructed by dividing each element of into four congruent triangles. Figure 2 shows an initial triangular mesh . Figure 2 also shows an approximate outline of Kojima Lake based on data obtained with an online software .
Suppose that triangular mesh consists of m elements , and nodes , that elevation of topography at node is given for , and that an element contains p data , and that coordinates of vertices of are , , and . Note that xy coordinates of the first three data are those of the vertices of , and that and are elevations at the vertices , , and , respectively. Consider a linear function such that the values of coefficients a, b, and c are those that minimize the square sum
Figure 1. Three dimensional topographic data of Kojima Lake.
Figure 2. Initial mesh. Three dimensional topographic data are also shown.
Once those coefficients are evaluated, value of f1 is updated, that is, f1 = ax1 + by1 + c. With this new value of f1, values of coefficients a, b, and c that minimize the square sum (1) are updated and the value of f2 is updated with equation f2 = ax2 + by2 + c. With those new values of f1 and f2, values of coefficients a, b, and c that minimize the square sum (1) are updated, and the value of f3 is updated with equation f3 = ax3 + by3 + c. After those operations are completed , the operations are repeated for the element . One cycle of iterations is completed for the triangular mesh when k reaches m, z component or elevation associated with the n nodes, are obtained.
Denote by the n dimensional vector whose components are elevation associated with n nodes after q iterations. The iteration is terminated when the residual becomes less than , that is
Values of initial elevation in T0 are all set equal to 0, and values of initial elevation for are obtained from values of final elevation for . Figure 3 and Figure 4 show surfaces obtained with . The results shown in Figure 3 and Figure 4 lead to sedimentation during period from January 2020 to January 2021 (Figure 5).
A triangular mesh is set in a part of region covered the triangular mesh shown by Figureby Figure2 and numerical procedures described in the previous section were repeated. Figure6 shows the initial mesh. Figure7 shows the
Figure 3. Surface over based on data set 1 with , wireframe representation (top), surface with color according to elevation (color).
Figure 4. Surface over based on data set 2 with , wireframe representation (top), surface with color according to elevation (bottom).
Figure 5. Sedimentation over region over the region covered by the initial mesh shown by Figure 2 during period from January 2020 to January 2021, contour lines [m] and [m] (top), sedimentation with color according to amount (bottom).
Figure 6. Initial mesh. Three dimensional topographic data are also shown.
sedimentation during period from January 2020 to January 2021.
The area of region covered by the initial mesh shown by Figure 2 is approximately 150,000 m2, and the total sedimentation over the equal to region is approximately 5700.569784 m3. It follows that average increase in elevation of underwater topography over the region is 0.038004 m. The area of region covered by the initial mesh shown by Figure 6 is approximately 25,000 m2, and the total sedimentation over the equal to region is approximately 1508.789762 m3. It follows that average increase in elevation of underwater topography over the region is 0.060352 m.
Major sources of water in Kojima Lake are inflow flow from two rivers Kurashiki River and Sasagase River. Kojima Lake was separated from Kojima Bay by embankment. There are six gates set on the embankment (Figure 2). The water
Figure 7. Sedimentation over the region covered by the initial mesh shown by Figure 6 during period from January 2020 to January 2021, contour lines [m] and [m] (top), sedimentation with color according to amount (bottom).
level of Kojima Lake is controlled by discharge of water through the gates into Kojima bay during low tide. A possible reason for higher sedimentation over the region shown by Figure 7 is stronger effect of flow generated by the discharge.
This study was partly supported by a 2020 research grant from the Public Interest Incorporated Foundation Wesco Promotion of Learning Foundation.
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