Morfometri Danau Kelapa Gading Kota Kisaran, Kabupaten Asahan Provinsi Sumatera Utara

Ridoan, Rizki; Muhtadi, ‪Ahmad; Patana, Pindi

doi:10.13170/depik.5.2.4913

Cited by 5 publications

(11 citation statements)

References 6 publications

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“…The more tightly contour shows deepened. On the contrary increasingly rare contour showed shallow depth (Indrayani et al, 2015;Suprobowati, 2012;Ridoan et al, 2016). In the southeast and west parts clearly seen the contours are very rare because at that location is an area of shallow with a depth of only up <3 m. Based on Figure 3 a, b, c above shows that there is a tidal influence on the condition of the bathymetry of the lake at high tide, low tide, and MSL.…”

Section: Bathymetrymentioning

confidence: 84%

“…It explained that the tidal affected to the physical aspect of subsurface dimension especially lake's depth. It was also affected by lake's volume that would change according to how much water that enter or flow out from the lake (William, 1998;Ridoan et al, 2016). It can also be supported by data from an average slope of 0.13 -0.15% which is the slope of the ramps (Syah and Hariyanto, 2013)…”

Section: Subsurface Dimentionsmentioning

confidence: 92%

“…http://dx.doi.org/10.20884/1.oa.2017.13.2.174 waterbody sustainable management (Ridoan et al, 2016).…”

Section: Research Articlementioning

confidence: 99%

“…The more irregular shape of the lake cause more parts the bay from and connected to the mainland so that the possibility of nutrients entrance from the mainland would also be greater (Pratiwi et al, 2007). In general, the water of both natural and artificial lakes have SDI greater than 2 are Cilala lake (2.55) (Pratiwi et al, 2007), Toba lake (3.61) (Lukman and Ridwansyah, 2010), Kelapa Gading lake (3.55) (Ridoan et al, 2016), Pondok Lapan lake (4.93).…”

Section: Surface Dimentionsmentioning

confidence: 99%

“…Lake's depth has high influenced to water quality (Aldama et al, 2013;Barroso et al, 2014). It was related to lake steered Z r value at another lake in Indonesia was 1.39% at Situ Cilala (Pratiwi et al, 2007), Poso lake 1.18% (Ridwan and Ridwansyah, 2009), Toba lake 1.34% (Ridwan and Ridwansyah, 2010), and Kelapa Gading lake 0.17% (Ridoan et al, 2016), Pondok Lapan 1,40% (unpublished data).…”

Section: Subsurface Dimentionsmentioning

confidence: 99%

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Morphometry Dynamical of Siombak Lake, Medan Indonesia

2017

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Siombak lake (28 ha area) was a salty lake located in Medan coastal, Indonesia. Water fluctuation influenced by the sea tide. Therefore, it needed to do morphometry dynamical study as the first impression of lake physical characteristic. The purpose of this study was to understand the dynamical of Siombak lake morphometry. The research was done in September 2016. Lake mapping was done by making 100 line zig zag and draw with ArcMap. Bathymetry showed that the bottom of the lake was sloping at the center part of west and southeast of the lake, and steeping at north, south and east. Siombak Lake has shoreline length 2,535.78 m, with SDI value 2.70. Maximum length 756 m, with maximum width 246.15 m. Lake maximum depth was 17.7 m at MSL, 18.98 m at highest tide and 16.71 m at lowest tide, with average depth 5.33 m at MSL, 6.30 m at highest tide and 4.30 m at lowest tide. Lake volume was 783,607.16 m3 at MSL, 829,395.52 m3 at highest tide and 355,544.14 m3 at lowest tide, with water debit around 32.50 – 50.17 m3s-1. Water retention time was ± 4.33 – 6.75 hours

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Section: Bathymetrymentioning

confidence: 84%

Section: Subsurface Dimentionsmentioning

confidence: 92%

“…http://dx.doi.org/10.20884/1.oa.2017.13.2.174 waterbody sustainable management (Ridoan et al, 2016).…”

Section: Research Articlementioning

confidence: 99%

Section: Surface Dimentionsmentioning

confidence: 99%

Section: Subsurface Dimentionsmentioning

confidence: 99%

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Morphometry Dynamical of Siombak Lake, Medan Indonesia

2017

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Analysis of Morphometric Changes in Tondano Lake Based on Bathymetric Maps

2021

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This study aims to analyze changes in the morphometry of the lake bottom in a period of ten years, namely from 2006 to 2016. The analysis of morphometric changes is carried out by comparing two bathymetric maps from the mapping in 2006 and 2016. The morphometric aspects studied include the water surface area stated in km2, the volume of water (in m3) and the depth of the lake (in m). The results showed that within 10 years the surface of the lake water has decreased by 1.03 km2, while the total volume of lake water has increased by 10.41 m3. The average depth of the lake in a period of 10 years has barely changed significantly, only silting of about 0.01 meters. Judging from the contour pattern, it shows that there is a tendency for siltation to move not only towards the south but also towards the east. That means more sediment contributions come from the western region. The rain catchment area on the west side of the lake has a larger area when compared to the east side (Eris District). The sediment potential is greater from this area.

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Clustering Lakes in Kampar by Using Morphometry Data and Machine Learning Analysis

Hendrizal

Plaimo

Harjoyudanto

et al. 2021

IOP Conf. Ser.: Earth Environ. Sci.

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Lakes have an important role in hydrological and biochemical cycle. It also has some other crucial role such as domestic and industrial water use as well as irigation. The monitoring and management of this aquatic resources is crucial. But with many numbers of lakes, it is very challenging to manage them all. Clustering lakes can provide the answer so the management of the same cluster lakes may be done efficiently. Within this study, morphometry data of 6 lakes in Kampar Regency, Riau Province, were analyzed by using one of artificial intelligence branch which is machine learning. Morphometrical data are collected by using information geographic system. These data then categorized by using python language. This categorization based on data mining categorization algorithm named K-means. Based on the K-means machine learning clustering, the optimum cluster based on Elbow methid is k=3. But there is a possibility to look around for k=2. Based on K=3, cluster 3 is defined as the lowest values of all atribute. Based on k=2, the lowest value of morphometry data wiil be in the cluster 1.. These data will not only provide basic data such as total area, shape, width and length, but also help to understand the large scale hydrological models.

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Morfometri Danau Kelapa Gading Kota Kisaran, Kabupaten Asahan Provinsi Sumatera Utara

Cited by 5 publications

References 6 publications

Morphometry Dynamical of Siombak Lake, Medan Indonesia

Morphometry Dynamical of Siombak Lake, Medan Indonesia

Analysis of Morphometric Changes in Tondano Lake Based on Bathymetric Maps

Clustering Lakes in Kampar by Using Morphometry Data and Machine Learning Analysis

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