PRAKIRAAN KESESUAIAN PERAIRAN UNTUK BUDI DAYA RUMPUT LAUT DI WPPNRI 715

Abstrak – Pemanfaatan output model numerik laut dapat digunakan untuk mengetahui kondisi dan dinamika perairan laut dalam bentuk informasi spasio-temporal serta memperkirakan potensi daya dukung perairan. Penelitian ini bertujuan untuk mengidentifikasi kesesuaian perairan terhadap potensi budi daya rumput laut di Wilayah Pengelolaan Perikanan Negara Republik Indonesia (WPPNRI) 715 yang meliputi Teluk Tomini, Laut Maluku, Laut Halmahera, Laut Seram, dan Teluk Berau dengan menggunakan analisa scoring dan weighting (pembobotan). Data yang digunakan adalah data oseanografi fisik dan biologi dengan resolusi spasial 5 menit, terdiri dari  kedalaman perairan (ETOPO5), tinggi gelombang, kecepatan arus, suhu, salinitas, kecerahan,  pH, fosfat, nitrat, dan amonia yang merupakan produk dari Copernicus Marine Environment  Monitoring Service (CMEMS). Untuk validasi, digunakan data dari Argofloat, buoy pantai, dan satelit. Seluruh data diintegrasi dan disusun dalam format netCDF menggunakan software ferret. Validasi data suhu dan salinitas dari model CMEMS dengan data observasi diperoleh selisih nilai yaitu 0.25 ± 0.65 0C untuk suhu dan -0.10 ± 0.14 psu untuk salinitas, sehingga data model dapat digunakan sebagai input model. Topografi  perairan pantai di WPPNRI 715 sebagian besar curam dengan karakteristik kedalaman perairan  yang bertambah secara signifikan dengan bertambahnya jarak dari garis pantai. Pada perhitungan skor kesesuaian area budi daya, pembobotan batimetri merupakan faktor dominan sebesar 90% pada formula submodel fisik. Oleh sebab itu, hasil perkiraan kawasan yang sesuai untuk budi daya rumput laut di WPPNRI 715 terletak di sebagian kecil Maluku, Kepulauan Raja Ampat, dan Teluk Berau di Papua, dengan nilai skor kesesuaian yaitu 3 hingga 4 yang relatif  tetap pada setiap bulannya, mengikuti faktor dominan kondisi batimetri yang relatif tidak berubah.  Kata Kunci: Kesesuaian Perairan, Budi Daya Rumput Laut, WPPNRI 715, Model Oseanografi    Abstract – The output of marine numerical model can be used to determine the conditions and marine waters dynamics in the form of spatio-temporal information and estimate the carrying capacity potential of the sea waters. The aim of study is to identify the suitability of the waters for seaweed cultivation potential in the Fisheries Management Area of the Republic of Indonesia (WPPNRI) 715 which includes Tomini Bay, Maluku Sea, Halmahera Sea, Seram Sea, and Berau Bay using scoring and weighting analysis. The 5 minutes resolution in temporal of physical and biological oceanographic data is used. Consist of water depth (ETOPO5), wave height, current speed, temperature, salinity, brightness, pH, phosphate, nitrate, and ammonia which are products of the Copernicus Marine Environment. Monitoring Service (CMEMS). For validation, data from Argofloat, coastal buoys, and satellite data.  Ferret software were used to integrate and compile in netCDF format. Validation of temperature and salinity data from the CMEMS model with observation obtained a difference in values of 0.25 ± 0.65 0C for temperature and -0.10 ± 0.14 PSU for salinity. These values assumed that the numerical model data can be used as cultivation model input. The topography of the coastal waters in WPPNRI  715 is mostly steep, indicated by the depth of water increases significantly from the shoreline. In the suitability score calculation of the cultivation area, the bathymetri is the dominant factor (90 % of weighting) in the physical submodel formula. Therefore, the results of suitable areas estimation for seaweed cultivation in WPPNRI 715 are located in a few part of Maluku, Raja Ampat Islands, and Berau Bay in Papua. These areas have suitability score of 3 to 4 which is relatively constant by the time following the unchanging bathymetri as dominant factor.  Keywords: water suitability, seaweed cultivation, WPPNRI 715, oceanographic numerical mode

Detection of Potential Fishing Zones of Bigeye Tuna (Thunnus Obesus) at Profundity of 155 m in the Eastern Indian Ocean

Remotely sensed data and habitat model approach were employed to evaluate the present of oceanographic aspect in the Bigeye tuna's potential fishing zone (PFZ) at a profundity of 155 m. Vessel monitoring system was employed to acquire the angling vessels for Bigeye tuna from January through December, 2015-2016. Daily data of sub-surface temperature (Sub_ST), sub-surface chlorophyll-a (Sub_SC), and sub-surface salinity (Sub_SS) were downloaded from INDESO Project website. Vessel monitoring system and environmental data were employed for maximum entropy (maxent) model development. The model predictive achievement was then estimated applying the area under the curve (AUC) value. Maxent model results (AUC>0.745) exhibited its probable to understand the Bigeye tuna's spatial dispersion on the specific sub-surface. In addition, the results also showed Sub_ST (43,1%) was the most affective aspect in the Bigeye tuna dispersion, pursued by Sub_SC (35,2%) and Sub_SS (21,6%)

Characteristics Fishing Areas of Bigeye Tuna (Thunnus Obesus) in Depth of 155 m Based on Remotely Sensed Data

Bigeye tuna (Thunnus obesus) is one of the commercially important pelagic species that caught mostly in the eastern Indian Ocean. This species prefers to stay close, and is usually below the thermocline layer. Remotely sensed data was used to determine the characteristics of Bigeye tuna fishing areas at a depth of 155 meter. Fishing vessels for Bigeye tuna were obtained from vessel monitoring systems (VMS) from January through December, 2015-2016. Daily data on sub-surface temperature (SST), sub-surface chlorophyll-a concentration (SSC), and sub-surface salinity (SSS) were obtained from the INDESO Project website. All oceanographic parameter data were selected at a depth of 155 m. The position of Bigeye tuna and oceanographic data were then grouped into 2 group monsoon, southeast monsoon (April – September) and northwest monsoon (October – March). The results showed that, during the southeast and northwest monsoon, Bigeye tuna mostly found in SSC of 0.03 – 0.05 mg/m3, SST of 16° - 18°C and salinity of 34 psu. These results showed that at depth of 155 m, Bigeye Tuna prefers to stay in small chl-a (0.03 – 0.04 mg/m3), low SST (16° - 18°C) and salinity of 34 psu. These information were essential and could be used to support fisheries management decisions especially for Bigeye Tuna in the eastern Indian Ocean

ANALISIS PENERAPAN METODE GAP FILLING UNTUK OPTIMALISASI PEROLEHAN DATA SUHU PERMUKAAN LAUT BEBAS AWAN DI SELAT BALI

Sea Surface Temperature (SST) sensed from infrared satellite sensors has a limitation caused by clouds cover. This limitation affects SST data to be not optimal because there are many empty areas without SST information. Gap Filling is a simple method for combining multitemporal satellite data to generate cloud free data. This research will apply Gap Filling method from two SST data, namely Himawari-8 and Multiscale Ultrahigh Resolution Sea Surface Temperature (MUR-SST). Cloud free daily SST data generated by this method has ~2 Km spatial resolution and daily temporal resolution. Validation of cloud-free SST data using in situ measurement data shows Mean Absolute Deviation (MAD) value 0.29 is smaller than MAD value from MUR-SST and Himawari-8 data. High correlation between cloud free SST data and insitu data is reflected from Kendall's Tau correlation value of 0.7966 or 79.66% and R2 with 0.93 value. These results indicate that the cloud free daily SST data can be used as valid estimation of SST condition in Bali Strait

TIDE AND TIDAL CURRENT IN THE BALI STRAIT, INDONESIA

Tide and tidal current model of the Bali Strait in Indonesia is produced by using a Coupled Hydrodynamical-Ecological Model for Regional and Shelf Seas (COHERENS). With its resolutions in the horizontal (500meters) and the vertical (4layers), the model well reproduces the four major tidal constituents, namely M2, S2, K1, and O1 tides, and their currents. Furthermore the model is used to investigate the tide-induced residual flow and tidal front in the Bali Strait. As a results, the tide-induced residual flow in the Bali Strait during the spring tide on May 16th in 2010 can be attributed to the variation of the strength of two eddies. The first one is the clockwise circulation in the shallow area at the wide part of the strait, while the second one is the small clockwise circulation in the south of the narrow strait. On the other hand, as suggestion from Simpson and Hunter (1974), the tidal front is determined by the value of log(H/U3) (where is the water depth in meters and the amplitude oftidal current amplitude in ms-1). The front detected by the image of sea surface temperature distribution from the satellite corresponds with the contour log(H/U3) of 6.5

Analisis Penerapan Metode Gap Filling Untuk Optimalisasi Perolehan Data Suhu Permukaan Laut Bebas Awan Di Selat Bali = Analysis Of The Application Gap Filling Method For Optimization Cloud Free Sea Surface Temperature Data In Bali Strait

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