Utilization of geographic information system technology as a tool for evaluating watersheds

Chia sẻ: Nguyễn Thảo | Ngày: | Loại File: PDF | Số trang:7

Thêm vào BST

Báo xấu

16
lượt xem 1
download

Download Vui lòng tải xuống để xem tài liệu đầy đủ

The problem of flooding and drought is believed to be the impact of the water system in the poor watershed area. The flooding that later resulted in the accumulation of sediment in the downstream region and reservoir area, this was related to the condition of the forest in the upper part of the base.

Chủ đề:

Bình luận(0) Đăng nhập để gửi bình luận!

Lưu

Nội dung Text: Utilization of geographic information system technology as a tool for evaluating watersheds

International Journal of Mechanical Engineering and Technology (IJMET) Volume 10, Issue 03, March 2019, pp. 1873-1879. Article ID: IJMET_10_03_190 Available online at http://www.iaeme.com/ijmet/issues.asp?JType=IJMET&VType=10&IType=3 ISSN Print: 0976-6340 and ISSN Online: 0976-6359 © IAEME Publication Scopus Indexed UTILIZATION OF GEOGRAPHIC INFORMATION SYSTEM TECHNOLOGY AS A TOOL FOR EVALUATING WATERSHEDS Deril Alfiance Kaligis and Gerzon Jokomen Maulany Department of Informatics Engineering, Faculty of Engineering, Musamus University, Merauke, Indonesia ABSTRACT The problem of flooding and drought is believed to be the impact of the water system in the poor watershed area. The flooding that later resulted in the accumulation of sediment in the downstream region and reservoir area, this was related to the condition of the forest in the upper part of the base. The method carried out in this study was an observational description method, namely conducting research or observing symptoms and factors to obtain data as a foundation in presenting in accordance with the intent and purpose. While the operational actions include the stages of collecting data both primary data and secondary data, for primary data collection data by purposive sampling. Based on the field data analysis there are 109 terrain units, with the following conclusions: The research area has various types of land criticality classes including very critical 3907.79 ha (11.29%); critical 16943.34 ha (48.95%); semi-critical 13037.03 ha (37.66%); and a critical potential of 725.27 ha (2.10%). With these conditions it is necessary to carry out efforts to conserve and rehabilitate the land which is adjusted to the results of analysis and existing land use. Based on the analysis results obtained as follows: 1991.62 ha one seasonl crop cultivation area (4.27%); annual crop cultivation area 23058.02 ha (49.45%); buffer zone 13249.57 ha (28.42%); protected area 8327.31 ha (17.86%). Keywords: landslide, land use change, monitoring, evaluation, Geographic Information System Cite this Article Deril Alfiance Kaligis and Gerzon Jokomen Maulany, Utilization of Geographic Information System Technology as a Tool for Evaluating Watersheds, International Journal of Mechanical Engineering and Technology, 10(3), 2019, pp. 1873-1879. http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=10&IType=3 1. INTRODUCTION Watersheds (DAS) are a serious problem, this is because the area of critical land and changes in land in the watershed area is increasing. One of the watersheds that reflects these conditions http://www.iaeme.com/IJMET/index.asp 1873 editor@iaeme.com
Utilization of Geographic Information System Technology as a Tool for Evaluating Watersheds is the Citarik watershed sub-district, West Java. Watershed management with complex problems. Natural resources in the form of forests (vegetation), soil, and water have an important role in the survival of humans so that their utilization needs to be carried out optimally and sustainably. The damage to forest natural resources that has occurred at this time has caused disruption of the environmental balance of the watershed as reflected in the frequent occurrence of erosion, floods, droughts, siltation of rivers and reservoirs and irrigation channels. The need for up-to-date data with high accuracy, on a large area is needed to monitor changes in one watershed management unit. Data obtained from Remote Sensing that have been checked in the field are used as inputs for Geographic Information Systems (GIS) to be subsequently processed and analyzed so that accurate land cover maps are obtained. Through the SIG process data from PJ can be used to detect land cover change detection on a watershed. In this case, GIS is needed to help limited funds, time and labor with the results obtained have high accuracy, easy, fast and cheap, can be done at any time. The condition of land cover and variation in soil types in watershed management will greatly affect the type and level of erosion that occurs. Areas that are critically affected by erosion can be analyzed visually and digitally with PJ. (Harjadi, 2005). So that it is expected that GIS can help calculation for erosion analysis both qualitatively for long-term and quantitative planning for short-term planning. The purpose of this study is to examine the benefits of GIS for watershed monitoring and evaluation. 2. MATERIALS AND METHODS 2.1. Time and Place of Research The study was conducted in the Citarik watershed sub-section which is part of the upstream Citarum watershed. Geographically the study area is located at 6º49 "LS-7º18" LS and 107º30 "BT-106º57" BT and administratively the Citarik watershed area is included in the regencies of Bandung, Sumedang and Garut. The area of the Citarik watershed is 25046 ha with annual rainfall ranging from 1477 mm / year to 2523 mm / year (Tosin, 2003). The location of the study is presented in (Figure 1). This research was conducted starting in March 2017. Figure. 1. Map of Research Area http://www.iaeme.com/IJMET/index.asp 1874 editor@iaeme.com
Deril Alfiance Kaligis and Gerzon Jokomen Maulany 2.2. Research Method The method used in the analysis is the overlay method for the three themes. Other useful methods were used (Fransiskus et al., 2019; Mangkoedihardjo, 2006, 2010 ; Nasra et al., 2019). Table 1. Slope Factors (Hardjowigeno and Widiatmaka, 2007) No Class Slope Description 1 I 0–8% Flat 2 II 8 – 15 % Sloping 3 III 15 – 25 % A little steep 4 IV 25 – 40 % Steep 5 V >40 % Very steep 2.3. Research Data The data used in this research is secondary data. Data can be obtained from previous research or from relevant agencies. These data consist of two types of data, namely spatial data and text data (attributes). Data to be collected are DEM map, watershed boundary, river network, land use map, land map and data, slope map, daily rainfall data, maximum and minimum air temperature, solar radiation, wind speed, air humidity, daily discharge data and coordinate point. 3. RESULTS AND DISCUSSION 3.1. General Conditions of Watershed Citarik watershed is part of the upstream part of the Citarum watershed which is in the coorsinate between 6 ° 47'37 "S - 7 ° 18'14" S and 107 ° 39'53 "E - 107 ° 57'5" E with a height of 700 - 1500 masl. The Citarik watershed has an area of 25984.2 ha and is administratively located between Bandung and Sumedang Regencies. Hydrologically, the Citarik watershed is within the management area of the Upper Citarum watershed. 3.2. Climate Conditions of the Watershed Climate conditions such as rainfall, temperature, wind speed, solar radiation and air humidity are the most important elements in the hydrological process. Daily rainfall data is obtained from the Rancaekek Rain Station and Cipaku-Paseh Rain Station. Maximum and minimum temperature data, wind speed, solar radiation and air humidity were obtained from the Meteorology, Climatology and Geophysics Agency (BMKG Bandung). The average rainfall of 2 rain stations, namely Rancaekek and cipaku-paseh for 7 years (2008-2014) showed that the maximum rainfall occurred in March of 343.0 mm and followed by December at 311.8 mm. Minimum rainfall occurs in August, which is 33.3 mm. Based on data from the Bandung Meteorology, Climatology and Geophysics Agency (BMKG Bandung) in 2005-2014 the average maximum temperature occurred in September at 30.2 ° C and the minimum average temperature in July was 18.4 ° C, presented in the table 2. http://www.iaeme.com/IJMET/index.asp 1875 editor@iaeme.com
Utilization of Geographic Information System Technology as a Tool for Evaluating Watersheds Table 2. Average maximum and minimum temperatures for 2005-2014 Temperature ◦C Month Maximum Minimum January 28.1 20.3 February 28.1 20.2 March 28.7 20.1 April 29 20.1 May 29 19.8 June 28.8 19.3 July 28.9 18.4 August 29.5 18.5 September 30.2 19 October 30 19.6 November 29 20 December 28.4 20.2 Based on data from the Bandung Meteorology, Climatology and Geophysics Agency (BMKG Bandung) in 2005-2014. The highest average wind speed occurs in August and September reaching 1.7 m / sec and conversely the smallest wind speed average occurs in May and November, which is equal to 1.3 m / sec. Data can be seen in Table 3. Table 3. Average Wind Speed for 2005-2014 Wind speed Month (m/sec) January 1.6 February 1.6 March 1.5 April 1.4 May 1.3 June 1.5 July 1.6 August 1.7 September 1.7 October 1.5 November 1.3 December 1.4 The greater average solar radiation occurs in August to October. Sunlight reaches its peak in August 29.1 MJ m-2 days-1. During the period of November-March the average sun radiation is 18.7 MJ m-2 days-1. December is the month that has the smallest solar radiation which is equal to 16.7 MJ m-2 days-1. http://www.iaeme.com/IJMET/index.asp 1876 editor@iaeme.com
Deril Alfiance Kaligis and Gerzon Jokomen Maulany Table 4. Average Solar Radiation for 2005-2014 Solar radiation Month (MJ/m-2day-1) January 18.9 February 18.8 March 20.3 April 19.1 May 23.1 June 24.6 July 27.6 August 29.1 September 25.1 October 23.1 November 18.9 December 16.7 3.3. Type of soil Each type of soil has a texture with different levels of infiltration. the more rough the texture of the soil, the faster the infiltration process will occur. The type of soil has the potential for surface flow under soil cover conditions and in certain rainfall conditions. There are 5 types of soil in the Citarik sub-watershed, namely Alluvial Brownish Gray, Alluvial Gray & Alluvial Brownish Brown Association, Andosol and Regosol Chocolate Association, Reddish Brown Latosol Association and Brown Latosol, and Latosol Reddish Dark Brown. 3.4. Flow Discharge Analysis In this study river flow discharge analysis was carried out using ArcSWAT 2012. ArcSWAT is a distributed model that is connected with Geographical Information Systems (GIS) and integrates spatial DSS (Decision Support System). In the SWAT analysis several processes were carried out including the delineation process, the formation of the Hydrological Response Unit (HRU), the formation of climate data, the simulation process and calibration and validation of the results of model simulations. 3.5. Delineation Process This delineation phase basically divides watershed areas into several rain catchments. The delineation process is done automatically using ArcSWAT by requiring data input in the form of DEM, watershed boundaries, river networks and outlet points. The data generated from this process are in the form of watershed boundaries, sub-sub-watershed boundaries, river networks and watershed topography which are fully studied. In this study, only one outlet was used, namely the Citarum-Majalaya outlet. 3.6. Slope Class Scoring Based on the results of data processing with ArcMap 10.1 there are five slope classes found in the Citarik watershed area which are dominated by flat topography which is 0-8% with an area of 9631.69 ha or 54.51% of the total total watershed. http://www.iaeme.com/IJMET/index.asp 1877 editor@iaeme.com
Utilization of Geographic Information System Technology as a Tool for Evaluating Watersheds Table 1. Slope Class Scoring Class Slope Description Score Area (Ha) Percentage (%) 1 0-8 Flat 20 9631.69 54.51 2 8-15 Sloping 40 3852.40 21.80 3 15-25 A little steep 60 3054.62 17.29 4 25-40 Steep 80 1065.83 6.03 5 >40 Very steep 100 66.00 0.37 Total 17670.54 100.00 3.7. Rainfall Intensity Class Scoring The average daily rainfall intensity is obtained from the average rainfall data divided by the rainy days for 7 years 2008-2014 obtained from the Rancaekek and Cipaku-Paseh Stations. Table 6. Rainfall Intensity Class Scoring Class Interval Description Score 1 0 - 13.6 Very low 10 3.8. Soil Type Class Scoring The results of the soil type class score according to erosion sensitivity in the Citarik watershed sub-area can be seen in table 7. Table 7. Soil Type Class Scoring Class Soil type Description Score Area (Ha) Percentage (%) 1 Alluvial Not sensitive 15 8824.75 49.94 2 Latosol Rather sensitive 30 2486.90 14.07 5 Regosol Very sensitive 75 6358.87 35.99 Total 17670.53 100 Slope class data, soil type and rainfall intensity with scores and criteria each previously separate are combined using the ArcMap 10.1 application using the overlay or overlapping method. Overlay is a function of the Geographical Information System (GIS) which aims to produce new spatial data from two or more spatial data that are input (Prahasta 2014). The assessment of each parameter is determined by multiplying the class value by the weight of each parameter so that the number / score of an area is obtained which is then classified in the area function class. The results of the overlay process get three regional status, namely the protected function area, the buffer function area and the cultivation function area. The status of the widest area in the Citarik watershed is the cultivation function area with an area of 12220.09 ha or 69.23% of the total area of the watershed, which is 17651.48 ha, see table 8. Table 8. Status of the Citarik Watershed Area Area Status Area (Ha) Percentage (%) Protected area 63.54 0.36 Buffer Area 5367.85 30.41 Cultivation Area 12220.09 69.23 http://www.iaeme.com/IJMET/index.asp 1878 editor@iaeme.com
Deril Alfiance Kaligis and Gerzon Jokomen Maulany 4. CONCLUSION Characteristics of a watershed are determined by the morphos of a watershed, namely, among others, the condition of the river, drainage patterns, the length of the river and others. The shape of the land in the upstream area is dominated by mountains and hills, while in the middle area it is dominated by alluvial landforms and pied-mont plan, while in the lower reaches of most plains and Alluvial-Colluvial deposits. The type of rock in the upper area is more igneous, most of which have begun to decay so that landslides occur easily, while in the east apart from igneous rocks there are limestone sediments, and metamorphic rocks. Watershed conditions and soil conservation to slope of more than 45% are still of moderate quality, so the field is very narrow. The types of soil that can be found in the Grindulu watershed include Entisols, Inceptisols, Ultisols with soil colors dominated by brown to reddish, with soil acidity between 6 (slightly sour) to close to 7 (neutral). REFERENCES [1] Fransiskus Xaverius Manggau and Stanly Hence Dolfi Loppies, 2019. Inventory Information System of Pharmaceutical Warehouse of Health Office of Merauke District, International Journal of Mechanical Engineering and Technology, 10(2), pp. 18–26. [2] Harjadi, B., 2005. Detekti Kekritisan Lahan dengan Penginderaan Jauh dan Sistem Informasi Geografis (Studi Kasus Lahan Kritis di Sub DAS Alang, Wonogiri). Forum Geografi, Vol.19 (1) Juli 2005: 1-15. [3] Harjadi, B., 2007. Aplikasi Penginderaan Jauh dan SIG untuk Penetapan Tingkat Kemampuan Penggunaan Lahan (KPL) (Studi Kasus di DAS Nawagaon-Maskara, Saharanpur-India). Forum Geografi, Vol. 21 (1) Juli 2007: 69-77. [4] Mangkoedihardjo, S. 2006. Biodegradability improvement of industrial wastewater using hyacinth. Journal of Applied Sciences, 6(6), 1409-1414. [5] Mangkoedihardjo, S. 2010. A new approach for the Surabaya sewerage and sanitation development programme 2020. Advances in Natural and Applied Sciences 4 (3): 233-235. [6] Morgan, R.P.C., D.D.V. Morgan dan H.J. Finney, 1984. A Predictive Model for the Assessment of Soil Erosion Risk.J.Agric. Engng. Res., 30, 245-253. [7] Nasra Pratama Putra, Gerzon Jokomen Maulany, Frans Xaverius Manggau and Philipus Betaubun, 2019. Attitude Quadrotor Control System with Optimization of PID Parameters Based On Fast Genetic Algorithm, International Journal of Mechanical Engineering and Technology, 10(1), pp. 335–343. [8] Poveda, German dan Salazar F.Luis. 2004. Annual and Interannual (ENSO) Variability of Spatial Scaling Properties of a Vegetation Index (NDVI) in Amazonia. Journal of Remote Sensing of Environment 93 (2004) 391 – 401. [9] Singh, S., 1994. Remote Sensing in The Evaluation of Morpho-hydrological Characteristics of The Drainage Basin of Jojri Catchment. J.,of Arid Zone 33(4) : 273-278. http://www.iaeme.com/IJMET/index.asp 1879 editor@iaeme.com