Analysis of Consentration of Total Suspended Solid (TSS) in Porong Sidoarjo River Waters

T. Hariyanto, C. B. Pribadi, A. Kurniawan, B. M. Sukojo, M. Taufik, Luki Indeswari
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Abstract

Porong River is Lapindo mud disposal area that has occurred since 2006 until now. Lapindo Mud river flow into the Porong River has caused higher sedimentation Mud in Porong River. Therefore, observation of TSS (Total Suspended Solid) distribution is needed to know the air quality in the waters. In this research, observation of TSS distribution is done by using remote sensing method by utilizing Landsat 7 Satellite Imagery 7 year 2000, and Landsat 8 in 2013, 2014, 2015, 2016, and 2017, and in situ data in the form of 20 air samples. Landsat-8 L1T satellite image data in 2017 was processed using 5 TSS algorithms namely Syarif Budiman Algorithm (2004), Parwati Algorithm (2006), Guzman & Santaella Algorithm (2009), Nurahida Laili Algorithm (2015), and Jaelani Algorithm (2016). From result of data processing using Algorithm Budhiman (2004), with Normalized Mean Error (NMAE) equal to 19,53%, that value proves that TSS Algoritma Budhiman (2004) is the most appropriate algorithm to explain the condition of TSS constellation in the dimensions of the Porong River Estuary, the algorithm is applied to apply other years of Landsat data. The result of TSS concentration in the waters Porong River which has the highest value of TSS between 11,52 mg / Lt 92,16 mg / L. According to the Decree of the Minister of the Environment. 51 of 2004 on Marine Water Quality Standard for Marine Biota, sea water quality standard for TSS parameter is 80 mg / L meaning in year 2013, and in year 2014 at estuary of Porong River can be said not good because difference of standard quality which have specified.
蒲龙溪道河水体总悬浮物(TSS)浓度分析
从2006年开始到现在,蒲龙江是拉平都岛的泥浆处理场。拉平多泥河流入柏龙江,造成柏龙江泥沙淤积增多。因此,需要通过观察总悬浮固体(TSS)的分布来了解水体的空气质量。本研究利用2000年Landsat 7卫星影像和2013年、2014年、2015年、2016年和2017年Landsat 8卫星影像,利用20个空气样本的现场数据,采用遥感方法对TSS分布进行观测。2017年Landsat-8 L1T卫星图像数据采用Syarif Budiman算法(2004)、Parwati算法(2006)、Guzman & Santaella算法(2009)、Nurahida Laili算法(2015)和Jaelani算法(2016)5种TSS算法进行处理。从Budhiman算法(2004)的数据处理结果来看,其归一化平均误差(NMAE)为19.53%,该值证明TSS算法Budhiman(2004)是最适合解释坡龙江口维度上TSS星座状况的算法,并将该算法应用于其他年份的Landsat数据。TSS浓度的结果地河水域TSS 11之间的最高价值,52毫克/ 92 Lt, 16 mg / L .根据环境部长的命令。51 2004海洋生物对海洋水质标准,海水质量标准对TSS参数是80 mg / L的意义2013年,和2014年地河河口可说不好,因为指定的标准质量的差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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