Creation of Trout Habitat by Constructing Small Dams

Rawa Pening Lake is one of fifteen priority lakes. The problem in Rawa Pening Lake is the rapid sedimentation rate and blooming of water hyacinth which has an impact on the decreasing of storage capacity and water quality. The handling has not shown significant results. Therefore, that it needs to innovate on improvement and maintenance of Rawa Pening Catchment Area that has never done that is in the form of small dam development in Rawa Pening catchment area. The construction of a small dam in the Rawa Pening catchment area can temporarily hold water and prevent the rate of sediment from entering the lake. The purpose of this research is to analyse the influence of small dams in the Rawa Pening catchment area to sedimentation rate in Rawa Pening Lake. Sedimentation is calculated based on soil erosion in the catchment area, using the USLE formula. If There are 40 small-dams in Lake Rawa Pening catchment area, the sedimentation decreased to 78.75%. If there are only 2 small-dams constructed in the Klegung sub-watershed and the Legi sub-watershed, the sedimentation decrease to 67%.

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Use of Landsat ETM+ data for delineation of water bodies in hilly zones

Journal of Hydroinformatics ◽

10.2166/hydro.2010.018 ◽

2010 ◽

Vol 13 (4) ◽

pp. 661-671 ◽

Cited By ~ 18

Author(s):

Vijay S. Bhagat ◽

Kishor R. Sonawane

Keyword(s):

Water Body ◽

Vegetation Index ◽

Thematic Mapper ◽

Water Bodies ◽

Wetness Index ◽

Surface Wetness ◽

Small Dams ◽

Raster Image ◽

Normalised Difference Vegetation Index ◽

Water Based

The remotely sensed Landsat Enhanced Thematic Mapper Plus (ETM+) dataset is used for the detection and delineation of water bodies in hilly zones. The water bodies were detected using Surface Wetness Index (SWI), Normalised Difference Vegetation Index (NDVI) and a slope map. The assessment of areas under dense vegetation in water bodies is omitted in the combined map prepared using classified raster images showing (1) the distribution of ‘water’ and ‘non-water’ based on SWI and (2) the distribution of ‘vegetation’ and ‘non-vegetation’ based on NDVI. The shadows' effect in estimated areas under water bodies is detected and delineated using the combination of (1) a combined raster image (classified SWI and NDVI) and (2) a slope map. About 3.8% (1370 ha) of the total area reviewed is estimated under water bodies with 91.74% overall accuracy. The water bodies include (1) major and minor dams, (2) watered streams, (3) springs distributed in foothill zones and (4) small dams on minor streams. The relatively smaller water body objects, i.e. streams and springs, have estimated less producer's (92–96%) and user's (85–92%) accuracy than the major water bodies, i.e. 96.77% producer's and 100% for user's accuracy.

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Analisis Prioritas Pembangunan Embung Metode Cluster Analysis, AHP dan Weighted Average (Studi Kasus: Embung di Kabupaten Semarang)

MEDIA KOMUNIKASI TEKNIK SIPIL ◽

10.14710/mkts.v21i2.11236 ◽

2016 ◽

Vol 21 (2) ◽

pp. 101 ◽

Cited By ~ 1

Author(s):

Bima Anjasmoro ◽

Suharyanto Suharyanto ◽

Sri Sangkawati

Keyword(s):

Cluster Analysis ◽

Average Method ◽

Weighted Average ◽

Life Time ◽

Water Shortage ◽

Maintenance Cost ◽

Weighted Average Method ◽

Small Dams ◽

Access Road ◽

The Government

The Feasibility study potential of small dams in Semarang District has identified 8 (eight) urgent potential small dams. These potential dams here to be constructed within 5 (five) years in order to overcome the problem of water shortage in the district. However, the government has limited funding source. It is necessary to select the more urgent small dams to be constructed within the limited budget. The purpose of the research is determining the priority of small dams construction in Semarang District. The method used to determine the priority in this study is cluster analysis, AHP and weighted average method. The criteria used to determine the priority in this study consist of: vegetation in the inundated area, volume of embankment, land acquisition area, useful storage, recervoir life time, water cost/m³, access road to the dam site, land status at abutment and inundated area, construction cost, operation and maintenance cost, irrigation service area and raw water benefit. Based on results of cluster analysis, AHP and weighted average method can be conclude that the priority of small dams construction is 1) Mluweh Small Dam (0.165), 2) Pakis Small Dam (0.142), 3) Lebak Small Dam (0.134), 4) Dadapayam Small Dam (0.128), 5) Gogodalem Small Dam (0.119), 6) Kandangan Small Dam (0.114), 7) Ngrawan Small Dam (0.102) and 8) Jatikurung Small Dam (0.096). Based on analysis of the order of priority of 3 (three) method showed that method is more detail than cluster analysis method and weighted average method, because the result of AHP method is closer to the conditions of each dam in the field.

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