Persepsi masyarakat terhadap bencana banjir monsun di Malaysia: Kajian kes Kota Bharu, Kelantan

Abstrak

Banjir monsun merupakan bencana alam semulajadi yang tidak dapat dielak daripada menimpa masyarakat Kota Bharu Kelantan. Pelbagai kaedah penggunaan teknologi moden masih tidak dapat menghalang bencana banjir untuk terus menghantui masyarakt setempat. Kajian penyelidikan dijalankan untuk memahami masyarakat Kota Bharu menyesuaikan diri dan mengurangkan kesan bencana banjir. Kajian ini melibatkan kaedah soal selidik yang menumpukan kepada kawasan bandar Kota Bharu sahaja, dengan melibatkan seramai 400 responden yang tinggal berdekatan dengan Sungai Kelantan. Hasil analisis menunjukkan kebanyakan responden adalah terdiri daripada etnik Melayu dengan kategori umur dalam 30 hingga 45 yang menetap lebih daripada 10 tahun di kawasan bencana banjir, amat bersetuju bahawa kebanyakan rumah dibina bertiang dan tinggi daripada permukaan bentuk muka bumi (45%), tetapi amat tegas dalam melihat peranan jarak rumah yang jauh daripada sungai dapat mengurangkan kesan bencana banjir. Ketersediaan menghadapi bencana banjir melalui penyediaan sumber makanan seperti sardine, telur, dan beras sangat diperlukan bagi mengelak daripada mengalami ‘darurat’. Selain itu, perahu digunakan sebagai pengangkutan (45.75%), manakala pelampung (49.25%) digunakan sebagai ‘jaket keselamatan’ atau bermain air banjir oleh kanak-kanak. Oleh itu, penyediaan pelampung membuktikan bencana banjir juga mendatangkan suasana keriangan atau pesta kepada penduduk setempat, walaupun kejadian ini tidak disokong oleh segelintir responden.

Kata Kunci: banjir monsun, ketersediaan masyarakat, pengangkutan banjir, pengurusan banjir, peralatan penyelamatan banjir, tanggapan bencana banjir

Abstract
Monsoon floods are natural disasters whose routine occurances may elicit different perceptions by the very people experiencing them . This study examined the perceptions of the local public of Kota Bharu, Kelantan regarding monsoon floods that visited them anually. Primary data were gathered from questionnaire-based field survey of 400 residents within the vicinity of the Kelantan river. Analysis results of these over-10 years local residents indicated that community flood preparedness in terms of food, transportation and rescue facilities and resources helped them to cope favourably with the situation and prevented them from being in a state of emergency. In addition, the ready availability of certain rescue implements such as life buoys proved that flood disaster could also bring joy and fun to certain quarters of the local ‘victim’ population.

Keywords: community preparedness, flood management, flood perception, flood rescue equipments, flood transportation, Monsun floods


Citation of Article:
Ang, K. H. (2017). Persepsi masyarakat terhadap bencana banjir monsun di Malaysia: Kajian kes Kota Bharu, Kelantan. Geografia-Malaysian Journal of Society and Space, 12(9), 24-31.


Pengenalan

Banjir boleh ditafsirkan sebagai kuantiti air yang sangat banyak atau berlebihan yang boleh menggelamkan sesuatu kawasan yang luas atau harta benda. Disebabkan itu, peristiwa banjir diiktirafkan sebagai bencana alam semula jadi (Web Portal World Meteorological Organization). Definisi bencana ialah suatu kejadian yang berlaku boleh mengakibatkan gangguan aktiviti masyarakat dan urusan negara, menyebabkan kehilangan nyawa, kerosakan harta benda, kerugian ekonomi dan kemusnahan alam sekitar yang melangkaui kemampuan masyarakat untuk mengatasinya dan memerlukan tindakan penggemblengan sumber yang ekstensif (Majlis Keselamatan Negara, 2012). Bencana banjir boleh dikaitkan dengan beberapa jenis seperti banjir pantai, banjir kilat, banjir sungai, banjir air bawah tanah, dan banjir pembentungan (Web Portal Environment Law Organization) (Edmund and Handmer, 1988) (Rosalind, 1989). Banjir pantai berlaku apabila ribut atau cuaca yang melampau digabung dengan air pasang yang tinggi menyebabkan paras air laut meningkat melebihi normal, memaksa air laut untuk melimpah ke permukaan tanah dan menyebabkan banjir pantai; banjir kilat berlaku apabila hujan lebat yang menimpa sesuatu kawasan dimana kuantiti air yang berkumpul secara banyak dan cepat serta sukar untuk mengalir keluar daripada kawasan tersebut akibat daripada sistem perparitan yang tidak mencukupi atau disekat oleh sampah sarap atau bahan terasing; banjir sungai berlaku apabila hujan turun dalam tempoh yang berpanjangan dan kuantiti yang banyak menyebabkan air mengalir secara bebas dengan memenuhi takungan sungai dan menggelami kawasan tersebut; banjir air bawah tanah boleh berlaku apabila paras air bawah tanah meningkat melebihi paras normal dengan menghampiri permukaan dan keadaan ini boleh dikaitkan dengan jangka waktu hujan; dan banjir pembentungan berlaku apabila terdapat kegagalan dalam mengawal sistem pembentungan akibat daripada tidak mempunyai kapasiti yang mencukupi untuk menakung disertakan dengan hasil dari hujan lebat atau kesan banjir yang menimpa (Web Portal Environment Law Organization).

Malaysia merupakan sebuah negara yang membangun setaraf dengan negara-negara asia seperti Singapura, Brunei, Thailand, dan lain-lain, yang mempunyai visi dan misi dalam mencapai wawasan 2020. Kerajaan telah banyak merancang dalam membangunkan negara melalui pelbagai projek besar, sebagai contohnya pembinaan Menara Berkembar Petronas atau KLCC, yang menjadi salah satu tunggak utama pembangunan negara Malaysia dan mampu berdaya saing dengan negara asia yang lain. Namun sesetengah perkara masih tidak dapat diselesaikan dengan peningkatan pembangunan tersebut, seperti bencana banjir. Di Malaysia, peristiwa yang sering kali menghantui penduduk warga kota mahupun warga kampung adalah bencana banjir yang berlaku hampir setiap tahun dan berjaya memusnahkan harta benda awam serta harta persendirian (Messner & Meyer, 2005). Bencana banjir yang terdapat di Malaysia adalah bencana banjir kilat dan bencana banjir sungai (selalunya dirujuk sebagai banjir monsun). Kajian penyelidikan ini dijalankan bertujuan untuk mengeksploitasi masyarakat Kota Bharu dalam mengadaptasi terhadap bencana banjir monsun yang berlaku di negeri Kelantan. Secara amnya, bencana banjir monsun merupakan kejadian alam semula jadi yang berlaku akibat daripada peredaran bumi di paksinya yang menghasilkan pergerakan angin yang berbeza berlaku, dimana peredaran angin (dikenali sebagai angin monsun timur laut) yang mengandungi wap air yang banyak bergerak dari kawasan tekanan tinggi ke kawasan tekanan rendah (Ooi et al., 2013; Braesicke et al., 2012). Jika dirujuk kepada teori fiziknya pula, bencana banjir monsun yang berlaku adalah pada bulan November hingga Mac atau musim sejuk sahaja kerana sinaran cahaya matahari adalah jatuh pada kawasan Hemisfera Selatan dan membentuk suatu kawasan tekanan rendah di Australia, manakala di Hemisfera Utara pula membentuk suatu kawasan tinggi di Asia Tengah. Oleh kerana radiasi penyejukan dan olakan udara sejuk secara berterusan mewujudkan suatu lapisan udara yang sangat sejuk dan stabil dekat Siberia dan di bahagian Utara China dengan pergerakan di haling di Barat Daya oleh Dataran Tinggi Tibet. Keadaan ini meningkatkan kekuatan “zon Baroklinik” di antara jisim udara sejuk kebenuaan dan jisim udara panas Tropika ke Selatan. Oleh itu, suatu jurang atas dalam di latitude pertengahan meningkatkan “anticyclogenesis” dekat Tengah China dan “cyclogenesis” dekat Laut China Timur berlaku (Ooi et al., 2013; Ooi et al., 2012).

Ikatan kecerunan tekanan permukaan seberang Perairan China Timur memulakan suatu luruan sejuk ke arah Laut China Selatan. Luaran sejuknya bertindak dengan jurang Khatulistiwa (near-equatorial trough) untuk menjanakan penambahan perolakan dan dikaitkan dengan jangka waktu hujan lebat di semenanjung Malaysia dan persekitarannya (Ooi et al., 2013; Ooi et al., 2012). Jadi, keadaan ini telah menyebabkan berlakunya bencana banjir akibat daripada hujan lebat yang dibawa oleh angin monsun timur laut. Hujan lebat yang turun hanya di beberapa negeri sahaja seperti negeri Kelantan, negeri Terengganu, dan negeri Pahang. Mengikut kedudukan geografi, negeri Kelantan adalah terletak di sebelah timur yang bersebelahan dengan Laut China Selatan dan berjiran dengan negeri Terengganu, negeri Pahang, negeri negeri Perak, dan negara Thiland (Rajah 1). Kedudukan yang terdedah kepada Laut China Selatan menambahkan lagi keberangkalian untuk menimpa angin monsun timur laut disertakan dengan hujan yang lebat boleh menyebabkan bencana banjir untuk tidak mustahil tidak berlaku.

Metodologi

Kajian penyelidikan ini dijalankan hanya tertumpu kepada masyarakat Kota Bharu yang tinggal di bandar Kota Bharu terutama responden yang tinggal berdekatan dengan sungai Kelantan (Rajah 2), kerana sungai Kelantan mengalir melalui bandar tersebut dan juga terdedah kepada kerapnya berlaku bencana banjir monsun. Kajian ini melibatkan kaedah kuantitatif, dimana pengumpulan maklumat adalah melalui soal selidik. Borang soal selidik ini adalah direka cipta dalam bentuk “close-ended”, dimana responden hanya perlu menjawab soalan yang mempunyai jawapan yang telah disediakan dan tidak perlu untuk memberikan sebarang cadangan atau komen. Oleh itu, kebanyakan soalan yang disediakan adalah dalam bentuk “Likert-Scale” atau skala Likert yang boleh dirungkaikan kepada 5 bentuk skala, iaitu 1-sangat tidak setuju, 2- tidak setuju, 3-normal, 4-setuju, dan 5-sangat setuju.

Borang soal selidik ini boleh dibahagikan kepada dua bahagian, iaitu bahagian A dan bahagian B. Bahagian A akan memperolehi maklumat tentang profil atau demografi responden seperti jantina, umur, bangsa, taraf pendidikan, hak milik tanah, tempoh menetap (tahun), dan jenis rumah (Jadual 1); manakala bahagian B pula akan memberikan penekanan tentang faktor dalaman responden bagi menyesuaikan diri terhadap kesan bencana banjir monsun seperti kedudukan rumah, rumah bertiang, jarak berdekatan sungai, dan penyediaan semasa banjir (Jadual 2). Dalam bahagian A, Borang soal selidik bagi kajian penyelidikan ini memerlukan sejumlah 400 responden sahaja (Krejcie and Morgan, 1970), dan tidak terhad kepada penambahan jumlah responden tersebut. Oleh itu, penambahan dalam jumlah responden dapat menambahkan lagi kejituan dan ketepatan dalam menghasilkan maklumat baru kepada kajian penyelidikan ini.

Keputusan

Keputusan yang diperolehi daripada borang soal selidik akan dimasukkan ke dalam komputer melalui applikasi SPSS atau ‘Statistical Package for Social Sciences’ versi 19. Sebanyak 400 soal selidik berjaya dikumpul semula selepas respoden memberikan jawapan dan pendapat mereka terhadap bencana banjir monsun ini. Analisis bagi kajian ini akan melibatkan diskriptif sahaja, dimana maklumat baru akan dihasilkan dan diterangkan secara keseluruhan bagi menggambarkan keadaan sebenar masyarakat Kota Bharu menghadapi bencana banjir monsun.

Merujuk kepada analisis bahagian A, kebanyakan responden yang terlibat dalam membantu memberi jawapan dan informasi tentang bencana banjir monsun ialah lelaki dengan jumlah 207 orang dan perempuan sebanyak 193 orang. Manakala kategori umur pula, ranking yang paling tinggi adalah 36 hingga 40 dengan angka 164 orang, diikuti 21 hingga 35 dengan angka 138 orang, 41 hingga 45 sebanyak 84 orang, bawah 21 sebanyak 10 orang, dan umur 46 keatas hanya 4 orang sahaja. Bagi penglibatan responden dalam kategori bangsa yang paling banyak adalah melayu dengan 348 orang, diikuti oleh bangsa cina sebanyak 31 orang, dan bangsa india sebanyak 21 orang. Taraf pendidikan dalam kajian ini melihatkan sebanyak 330 responden yang berjaya menghabiskan pelajarannya di peringkat sekorah rendah, diikuti oleh 51 responden di peringkat sekolah menengah, 16 responden di peringkat kolej, dan 3 responden sahaja di peringkat universiti. Disebabkan hak milik tanah yang dimiliki adalah rumah sendiri dengan sebanyak 228 responden, maka kebarangkalian bagi responden untuk menetap di kawasan tersebut dalam 11 tahun hingga 20 tahun adalah 156 orang, atau 1 tahun hingga 10 tahun dan 21 tahun hingga 30 tahun mempunyai jumlah yang sama dengan 72 orang, dan lebih 30 tahun adalah 54 orang. Namun demikian, keadaan adalah disebaliknya apabila seramai 172 responden adalah sewa di kawasan tersebut untuk menetap kurang daripada 1 tahun adalah seramai 46 responden sahaja. Oleh itu, kebanyakan rumah yang dibina terdiri daripada kayu-kayan dengan sejumlah 263 orang dan rumah berbatu sebanyak 137 orang.

Analisis demografi profil dalam bahagian A menunjukkan suatu informasi yang drastik, dimana kebanyakan responden adalah terdiri daripada lelaki yang berbangsa melayu dengan usia dalam lingkungan 21 tahun hingga 40 tahun yang bergiat aktif dengan aktiviti luar seperti bekerja. Manakala responden perempuan pula dapat dilihat bahawa kebanyakan mereka hanya berada di dalam rumah, yang bekerja sepenuh masa sebagai suri rumah dan keadaan ini membuktikan bahawa taraf pendidikan tidak begitu dititikberatkan dalam kehidupan seharian atau penting untuk dijadikan sebagai sumber utama dalam membina kerjaya individu. Terdapat segolongan responden yang agak berusia seperti 41 tahun ke atas, juga terdiri daripada bangsa cina dan india mempunyai taraf pendidikan sekurang-kurangnya di peringkat kolej, telah menetap di kawasan bencana banjir monsun yang agak lama seperti melebihi 20 tahun kerana hak milik tanah tersebut merupakan tanah sendiri yang ditinggalkan oleh nenek moyang masing-masing. Namun terdapat sesetengah responden yang memilih untuk sewa sementara waktu kerana tana lot tersebut bukan hak milik dan terikat dengan pekerjaan tertentu di kawasan bandar. Kebanyakan rumah responden yang dibina dalam lingkungan kawasan banjir adalah jenis yang kayu-kayan dengan kedudukan rumah yang agak tinggi daripada bentuk muka bumi dan jenis rumah yang berbatu pula dibina di atas permukaan bumi dengan dua tingkat. Tujuan utama rumah berbatu yang dibina dua tingkat adalah untuk memindah barangan atau responden masih dapat tinggal di kawasan yang agak tinggi daripada ditenggelami oleh banjir.

Bahagian B pula adalah berkaitan dengan faktor dalaman responden bagi menyesuaikan diri terhadap kesan bencana banjir monsun di bandar Kota Bharu, menunjukkan keputusan yang agak positif atau setuju dengan pandangan dan cadangan dalam memilih jawapan bagi penyelidikan ini. Sebagai contohnya, faktor kedudukan rumah yang dibina adalah agak tinggi atau berada pada kedudukan bentuk muka bumi yang tinggi menunjukkan kebanyakan responden memilih sangat setuju dengan peratusannya ialah 45 daripada 100 peratus. Faktor kedua ialah rumah bertiang dapat mengelakkan banjir daripada memasuki rumah dengan sebanyak 191 responden memilih sangat setuju dalam pandangan mereka. Selain itu, barangan penting dinaikkan dengan penduduk berpindah ke kawasan yang berkedudukan tinggi adalah lebih selamat menunjukkan responden memilih sangat setuju dengan jawapan tersebut sebanyak 53.25% dan 47.25%. Manakala faktor bagi kebanyakan rumah yang dibina berdekatan dengan sungai adalah dibina menggunakan kayu melihatkan kepada responden memberi pilihan jawapan yang positif kepada setuju sebanyak 42.75%. Faktor kelima melibatkan jarak yang jauh antara rumah dengan sungai dapat mengurangkan kesan masalah banjir menunjukkan responden memilih untuk setuju dengan peratusan sebanyak 30.25 daripada 100 peratus. Seterusnya, kebanyakan responden berpendapat bahawa beras dan makanan simpanan lama seperti sardin atau telur, pukat, dan pelampung adalah amat diperlukan semasa banjir dengan memilih jawapan untuk setuju sebanyak 46.5%, 35.25%, dan 49.25%. Bukan setakat itu sahaja, penggunaan perahu semasa banjir untuk dijadikan sebagai pengangkutan dan menangkap ikan sebagai aktiviti sampingan menunjukkan sebanyak 183 responden memilih sangat setuju dan 162 responden memilih setuju. Akhir sekali, faktor bagi banjir mendatangkan suasana keriangan atau pesta membawa kepada keputusan yang positif dengan seramai 196 responden memilih setuju atau 49% dalam memberi cadangan dan pendapat untuk menyesuaikan diri dan mengurangkan kesan banjir.

Maklumat yang dihasilkan melalui analisis dalam bahagian B tentang faktor dalaman responden bagi menyesuaikan diri terhadap kesan bencana banjir monsun di bandar Kota Bharu, Kelantan, menampakkan satu perubahan yang besar terhadap kesan bencana banjir yang melanda. Bencana banjir monsun yang kerap berlaku pada musim tengkujuh atau bulan November sehingga bulan Mac menunjukkan sejumlah air yang banyak dibawa dalam bentuk wap air melalui angin monsun timur laut merentasi garisan khatulistiwa dan menimpa beberapa negeri di kawasan pantai timur seperti Kelantan, Terengganu, dan Pahang. Ditambah dengan kedudukan negeri Kelantan, terutama bandar Kota Bharu yang terletak berhampiran dengan sungai Kelantan dan merupakan hiliran sungai yang berdekatan dengan muara sungai yang menghala ke Laut China Selatan adalah terdedah sepenuhnya kepada kewujudan bencana banjir monsun untuk berlaku. Pembangunan pesat di bandar Kota Bharu juga menjadi faktor ‘minor’ yang boleh menyumbangkan kepada bencana banjir monsun untuk berlaku, namun tidak sama sekali kepada banjir kilat kerana luas takungan sungai Kelantan adalah sangat besar (Web Portal Sumber Asli dan Alam Sekitar) dan berupaya untuk menampung jumlah air hujan yang banyak bagi satu tempoh yang singkat. Oleh itu, banjir monsun merupakan bencana yang berlaku secara semula jadi yang tidak dapat dielakkan walaupun menggunakan teknologi canggih seperti pengepam air dalam mengurangkan bencana banjir monsun ini.

Bencana banjir monsun mendatangkan pelbagai kesan impak yang positif dan negatif kepada masyarakat penduduk setempat. Disebabkan keadaan ini, masyarakat Kota Bharu mengambil satu pendekatan untuk menghadapi bencana banjir dengan menyesuaikan diri dan mengurangkan kesan banjir melalui beberapa kaedah. Antaranya ialah membina rumah yang agak tinggi daripada bentuk muka bumi seperti pembinaan rumah bertiang agar dapat mengelakkan kesan banjir daripada memasuki rumah. Keadaan ini membuktikan bahawa kebanyakan rumah yang bertiang adalah dibina dengan menggunakan kayu kerana rumah yang berkonkrit akan membawa kepada tidak stabilnya tiang untuk menyokong rumah tersebut. Aliran sungai yang deras semasa banjir melanda juga mempunyai kebarangkalian untuk meranapkan rumah berkonkrit dengan melanggar tiang-tiang rumah tersebut. Selain itu, responden juga berpendapat bahawa penduduk yang berpindah ke kawasan tinggi dapat menyelamatkan nyawa yang disayangi daripada mengalami dan ditenggelami banjir yang merbahaya ini. Walau bagaimanapun, sesetengah penduduk beranggapan bahawa jarak rumah yang dibina adalah jauh daripada sungai tidak semestinya akan tidak mengalami bencana banjir tersebut. Hal ini kerana kebanyakan rumah dibina adalah berada pada paras laut yang agak rendah dan mudah untuk terdedah kepada banjir walaupun dibina jauh daripada sungai Kelantan. Oleh itu, kebanyakan responden amat positif dengan pendirian mereka bahawa penyediaan semasa banjir adalah sangat diperlukan seperti beras dan makanan simpanan lama (sardine dan telur), dan perahu yang digunakan sebagai pengangkutan air. Namun, mereka hanya memilih untuk bersetuju bahawa pukat dan pelampung juga diperlukan semasa banjir kerana kedua-dua peralatan ini digunakan untuk memenuhi masa luang seperti menangkap ikan atau bermain air banjir. Keadaan ini juga menunjukkan bahawa penggunaan pelampung secara meluas membuktikan bencana banjir dapat mendatangkan suasana keriangan atau pesta kepada penduduk setempat kerana pada masa itu kebanyakan responden tidak dapat pergi bekerja dan hanya tinggal di dalam rumah untuk menjaga barangan penting serta anak-anak yang masih kecil dan suka bermain air banjir.

Kesimpulan

Secara keseluruhanya menunjukkan bahawa kajian penyelidikan ini mencapai objektif, dimana masyarakat Kota Bharu depat menyesuaikan diri dan mengurangkan kesan banjir. Dengan kata lain, kebanyakan respoden adalah sangat peka dengan keadaan sekeliling terutama pada musim tengkujuh yang hampir melanda di negeri tersebut. Hal ini kerana penduduk tempatan yang tinggal bagi tempoh yang agak lama dan berdekatan dengan sungai Kelantan akan mengalami kesan banjir terdahulu sebelum bencana tersebut menggelami ‘berjaya’ menggelami bandar Kota Bharu. Selain itu, perubahan fizikal seperti ketinggian rumah dan jarak rumah memainkan peranan penting dalam mengurangkan faktor banjir untuk berlaku adalah sangat tinggi. Oleh itu, keadaan ini membuktikan bahawa pembinaan rumah yang berkonsepkan kayu adalah sebih selamat daripada rumah berkonkrit kerana barangan penting tidak diperlukan dinaikkan untuk menyelamat daripada terkena banjir jika dibandingkan dengan rumah berkonkrit yang bertingkat dua. Ditambahkan dengan ketersediaan darisegi makanan dan perahu banyak mengurangkan kesengsaraan masyarakt Kota Bharu untuk menghadapi bencana banjir tersebut. Maka, kajian penyelidikan ini membuktikan kebanyakan masyarakat Kota Bharu berjaya mengurangkan kesan bencana banjir dan dapat menyesuaikan diri.

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Spatial Variation Assessment of River Water Quality Using Environmetric Techniques

Abstract

The Malacca River provides water resources, recreational activities, and habitat for aquatic animals, as well as serving as a tourist attraction. Nevertheless, the Malacca has experienced water quality changes as a result of urbanization and population growth. Environmetric techniques incorporating hierarchical cluster analysis (HCA), discriminant analysis (DA), and principal component analysis (PCA) have been applied to understand the spatial variation of water quality in nine sampling locations within the river basin. HCA has grouped the nine sampling locations into two clusters based on physico-chemical and biological water quality data and trace elements in water. DA analysis indicated that temperature, salinity, coliform, EC, DO, BOD, COD, As, Hg, Cd, Cr, and Zn are the most significant parameters that reflect the overall river water quality for discrimination in clusters 1 and 2. PCA resulted in six components in cluster 1 and eight components in cluster 2. Agricultural activities and residential areas are the main sources of pollution within cluster 1, while a sewage treatment plant and industrial activities are the main sources of pollution in cluster 2. This study has provided useful information for identifying and investigating the pollutant sources through the water quality variations in the river. However, continuous evaluation of river water quality will help in greater understanding of river water quality for a more holistic management of the river basin.

Keywords: spatial variation, hierarchical cluster analysis, discriminant analysis, principal component analysis, Malacca River water quality


Citation of Article:
Hua, A. K., Kusin, F. M., & Praveena, S. M. (2016). Spatial Variation Assessment of River Water Quality Using Environmetric Techniques. Polish Journal of Environmental Studies, 25(6).


Introduction

Every day, two million tons of industrial and agricultural waste are discharged globally into water, in which the estimated amount of wastewater produced annually is about 1,500 [1]. The National Geographic Portal [2] has reported that developing countries produce 70% of industrial wastes that are dumped untreated into waters, and that an average of 99 million pounds (45 million kg) of fertilizers and chemicals are used each year. The deterioration of water quality of rivers is due to growing population, rapid urban development, anthropogenic inputs (e.g., municipal and industrial wastewater discharges, agricultural runoff), natural processes (e.g., chemical weathering and soil erosion) [3-5], human and ecological health, drinking water availability, and further economic development [6-8].

Since 2008 Malacca state has served as an official historical tourism center [9]. Nevertheless, increased development and urbanization in certain areas within the Malacca River basin has led to undesirable effects toward natural resources such as river water quality. The Malaysian Department of Environment [10] has classified the Malacca as class III, which means slightly polluted and which can adversely affect aquatic species, even leading to death [11-16]. The degradation of water quality has altered species composition and decreased the overall health of aquatic communities within the river basin [17-19]. Therefore, a practical and reliable assessment of water quality is required for sustainable water resource use with respect to ecosystem health and social development concerning prevention and control of water pollution [20-21].

Techniques that include regression analysis, discriminant analysis (DA), hierarchical cluster analysis (HCA), and principle component analysis (PCA) are the best for data classification and modeling so as to avoid misinterpretation of environmental monitoring data [22]. These techniques have advantages of visualization of large amounts of raw analytical measurements and extraction of additional information about possible sources of pollution [23]. Environmentric techniques have also been applied to characterize and evaluate river water quality as well as identifying spatial variation caused by natural and anthropogenic factors [24-25]. Hence, the increase volume of literature on environmetric techniques and applications have proven that HCA, DA, and PCA are practical in various types of hydrochemistry data [26-28]. HCA provides an average of the clusters made by individual participants that represent the result of the group as a whole [22, 29]. HCA organizes observation into discrete classes or groups such that within a group similarity is maximized and among-group similarity is minimized according to some objective criteria [30]. It assesses the relationship within a single set of variables where no attempt is made to define the relationship between a set of independent variables and one or more dependent variables, etc. [31]. Meanwhile, DA is able to discriminate variables between two or more naturally occurring groups [4]. DA is used to identify water quality variables responsible for spatial and temporal variations in river water quality [24, 32]. PCA describes the correlated variables by reducing the numbers of variables and explaining the same amount of variance with fewer variables (principle components). In others words, the goals of PCA are to extract the most important information from the data table, compress
the size of the data set by keeping only the important information, simplify the description of the data set, and analyze the structure of the observations and the variables [33].

Therefore, this study was performed to evaluate the spatial variations in river water quality data using environmetric techniques by incorporating HCA, DA, and PCA. HCA was used to classify 20 variables into clusters with respect to the nine sampling stations. Furthermore, DA was used to identify significant variables that have discriminant patterns between clusters provided from HCA analysis, and PCA was applied to normalize the 20 variables separately based on the clustering in HCA technique and to obtain the pollutant sources based on spatial variation. Hence, the output of environmetric techniques via HCA, DA, and PCA within the river basin will provide valuable insights on spatial variation of pollutants and areas needing attention in future environmental management plans [34]. In fact, a catchment-scale water quality study would be essential for pollutant characterization and to understand the extent to which the water has been contaminated [35-36].


Materials and Methods

Study Area

Malacca state is located southwest of peninsular Malaysia with geographical coordinates of 2°23’16.08”N to 2°24’52.27”N and longitude of 102°10’36.45”E to 102°29’17.68”E. The increasing local population has led to increasing public facilities like transportation, healthcare, accommodation, sewage, and water supply services [37]. However, rapid development in the Strait of Malacca has caused several changes, especially from a land-use perspective. Historically, the Strait of Malacca has become the busiest shipping route between China and India, causing most local citizens to live nearer the Malacca River to gain benefits like water and food sources, transportation, and purchase of imported materials or items from abroad. Land use has continuously developed until today, which is in line with the vision and mission of a sustainable tourism sector for the state. Indirectly, this has contributed to economic growth, political changes, and strengthening social and cultural relationships, but has also created environmental consequences – especially regarding water quality of the Malacca River.

Field Sampling

A total of nine sampling stations were chosen along the Malacca River, where every station is located at the confluence of each sub-basin and the Malacca River within the river basin (Fig. 1). The locations of sampling stations were recorded using a GPS device. The collection of water quality samples was carried out monthly from January to December 2015. The purpose of primary data collection was to obtain recent water quality data and for field data verification. Additionally, secondary data from 2001 to 2012 was obtained from Malaysia’s Department of the Environment. The river water quality data consists of the physico-chemical parameters: pH, temperature, electrical conductivity (EC), salinity, turbidity, total suspended solids (TSS), dissolved solids (DS), dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), ammoniacal-nitrogen (NH3-N), trace elements (i.e., mercury, cadmium, chromium, arsenic, zinc, lead, and iron), and biological parameters (i.e., Escherichia coliform and total coliform).

Water Quality Analysis

In-situ measurements include measurement of pH, turbidity, temperature, EC, TDS, salinity, and DO. pH was measured using a SevenGo Duo pro probe (Mettler Toledo AG), turbidity using a portable turbidity meter (Handled Turbidimeter Hach 2100), and temperature, EC, DS, salinity, and DO using a multi-parameter probe (Orion Star Series Portable Meter). On the other hand, NH3N was analyzed using a spectrophotometer at a specific wavelength using Hach Method 8038, while COD was measured using the APHA 5220B open reflux technique, BOD using APHA 5210B (or Hach Method 8043), and TSS using the APHA 2540D method. Both E-coli and total coliform were analyzed using the membrane filtration method based on APHA 9221B. For trace metal analysis, water samples of 500 mL were filtered through a 0.45 μm Whatman filter paper and acidified with nitric acid (HNO3) to pH lower than 2, and analyzed using inductive-coupled plasma-mass spectrometry (ICP-MS, ELAN DRC-e, Perkin Elmer, which required 40 MHz in frequency and 1,600 watts for conducting the analysis).

Quality Assurance and Quality Control

Before conducting the laboratory analysis, the laboratory apparatus and polyethylene bottles were washed using 5% (v/v) of nitric acid and soaking overnight to remove contaminants and traces of cleaning reagent [38]. On the other hand, for BOD analysis the BOD bottles were wrapped with aluminum foil. The river water samples were preserved using 1% (v/v) nitric acid (HNO3) for trace metals and analyzed within one month. Each sample was analyzed in triplicate before calculating the mean value, and standard deviation (SD) was used as an indication of the precision of each parameter measured with less than 20%. All the probe meters and instruments used were first calibrated prior to analysis. In all cases, the standards and blanks were treated in the same way as the representative river water samples to minimize matrix interference during analysis. Accuracy of ICP-MS performance is based on the diluting preparation using ICP Multi-Element Mixed Standard III (Perkin Elmer) into concentration with the same acid mixture used for sample dissolution. The recovery of samples for all target elements fell within the standard requirements (90-110%).

Data Analysis

River water quality data were analyzed using the Statistical Package for Social Sciences version 19 (SPSS 19) for descriptive analysis and environmetric techniques using HCA, DA, and PCA.

Hierarchical Cluster Analysis

HCA has an advantage of sorting different objects into the same group based on similarities and associations between the objects, which involves several procedures:

1. Ward’s method, which uses variance analysis to evaluate the distance between clusters with minimized sum of squares (SS) for any two clusters that are formed at each step [24, 39].

2. Measuring similarity by squared Euclidean distance, which is to provide the similarity between two samples and a distance that can be represented by differences between analytical values from the samples [24, 32, 39].

3. Results from dendrogram that have the ability to group high similarity with small distances between clusters while dissimilarity between groups is represented by the maximum of all possible distances between clusters [40]. In this study, HCA was employed to investigate the grouping of the sampling sites (spatial).

Discriminant Analysis

Discriminant analysis determines variables that discriminate between two or more groups or clusters. It constructs a discriminant function (DF) for each group [41], which can be defined using:

…where i is the number of groups (G), ki is the constant inherent to each group, n is the number of parameters used to classify a set of data into a given group, and wij is the weight coefficient assigned by DF analysis (DFA) to a given parameter (Pij). In this study, DA was used to define whether the mean of variables differ within the groups and the variables will be used to predict the group pattern. Based on the grouping of HCA results, the raw data are applied into DA using standard, forward stepwise, and backward stepwise modes to develop the DFs in evaluating spatial variations of river water quality. Generally, the stations (spatial) are assigned as dependent variables (referred to as grouping), and all parameters are independent variables.

Principal Components Analysis

PCA has the ability to provide information on most significant parameters due to spatial and temporal
variations that define the whole data set by excluding less significant parameters with minimum loss of original information [4, 24, 32]. PCA can be explained as:

…where z is the component score, a is component loading, x is the measured value of the variable, I is the component number, j is the sample number, and m is the total number of variables. General procedures used in PCA are: 1) the hypothesis in an original data group are then reduced to dominant components or factors (source of variation) that influence the observed data variance and 2) the whole data set is extracted through eigenvalues and eigenvectors from the square matrix produced by multiplying the data matrix [42]. Eigenvalues greater than 1 are considered significant enough [43] to perform a new group of variables, namely varimax factors (VFs). VF coefficients that have a correlation greater than 0.75 are considered “strong,” 0.75 to 0.50 as “moderate,” and 0.50 to 0.30 as “weak” [44] (only factor loadings above 0.6 were taken into account). In this study, PCA was applied to the normalized data set (20 variables) separately based on different spatial regions obtained from the HCA technique.


Results and Discussions

The mean and standard deviation values of Malacca River water quality data for physico-chemical and biological parameters and the trace elements from 2001 to 2015 are presented in Table 2. Table 2 indicates that most physico-chemical parameters are in class 1, such as temperature (S1 to S9), salinity (S4 to S6 and S8 to S9), electrical conductivity (S2 to S6 and S8 to S9), and dissolved solids (S3 to S6 and S8 to S9) (Table 1). However, there are some stations that continue to be polluted with respect to turbidity (S1 to S6) from class 2 to class 5, and total suspended solid (S2 to S6) from class 1 to class 3; while some stations are classified as being less polluted with respect to dissolved solids (S1 to S3) and salinity (S1 to S4) from class 5 to class 1 (Table 1). The possible causes of changes in increasing turbidity and total suspended solids are the increasing land clearing for agricultural activities, while decreasing in dissolved solids and salinity are potentially due to reduction from big to small-scale animal husbandry activities. Meanwhile, parameters like chemical oxygen demand (S1 to S7), biological oxygen demand (S1 to S7), and dissolved oxygen (S1 to S3 and S7 to S8) were mostly in class 3. There was an increasing level of pollution with respect to ammoniacal nitrogen (S6 to S8) from class 2 to class 5, but improved levels in station 2 to station 4 from class 5 to class 3. The reason for this is because of the changes in land use, i.e., residential activities that change from upstream and the middle parts to the downstream part of the river. All the trace metals are in class 1, but biological parameters are classified as class 5 (Tables 1 and 2).

HCA results showed that two clusters were identified from the nine sampling stations (Fig. 2). Cluster 1 consists of S1, S2, S7, and S8, while cluster 2 consists of S3, S4, S5, S6, and S9. The results showed that S1, S2, S7, and S8 are considered moderate-pollution sources (MPS), while S3, S4, S5, S6, and S9 are considered high pollution sources (HPS). The areas that constitute MPS are Kampung Kelemak sub-basin (S1), Kampung Sungai Petai sub-basin (S2), and Kampung Batu Berendam subbasin (S7), while the HPS are from Kampung Panchor sub-basin (S3), Kampung Harmoni Belimbing Dalam sub-basin (S4), Kampung Tualang sub-basin (S5), and Kampung Cheng sub-basin (S6). Based on land uses in the Malacca River basin, the potential sources of pollution within cluster 1 (MPS) result from the widely used land for agricultural activities and residential areas, while in cluster 2 (HPS) the sources may result from effluent discharge from sewage.

Discriminant analysis (DA) was used to further evaluate the spatial variation of two main clusters resulting from HCA output. The results show that spatial classification for both clusters in standard mode are 92% with 20 variables, forward stepwise are 81% with six variables, and backward stepwise are 85% with 12 variables. Therefore, the mode shows that temperature, salinity, coliform, EC, DO, BOD, COD, As, Hg, Cd, Cr, and Zn are found to be the most significant parameters having high variation in terms of their spatial distribution. The results indicate that temperature, salinity, coliform, EC, DO, BOD, COD, Cr, and Zn in cluster 1 have higher values than in cluster 2 (except for As, Hg, and Cd, which have almost similar values in both clusters. Fig. 3 shows box and whisker plots of these water quality parameters for 13 years (2001 to 2012 and 2015).

Principal component analysis was applied to compare composition patterns between the water quality parameters and to determine the factors that influence the identified regions (clusters 1 and 2). In cluster 1, six PCs were obtain with eigenvalues larger than 1 with 54% of total variance, while cluster 2 indicated eight PCs with eigenvalues more than 1 having 62% of total variance. Corresponding principal components, variable loadings, and variance are explained based on Table 3.

In cluster 1 (Fig. 4a), principal component 1 loadings with 17.3% of total variance have strong positive loadings on DS, EC, and salinity, but moderate negative loadings of NH3N. The existence of some physical parameter contaminations can be connected with the erosion of riverbanks due to dredging in the river and the agricultural runoff from non-point source pollution [45]. Meanwhile, salinity and NH3N pollution can be connected with pesticide usage for agriculture in oil palm rubber plantations and animal husbandry (chicken, cow, and goat), which are carried out by some local residents along the Malacca River. This condition has resulted in non-point source pollution that leads to surface runoff and water flows into the nearby sub-basin before entering the river. On the other hand, principal component 2 loadings explain strong positive loadings on turbidity but moderate positive loadings on TSS, with a total variance of 8.4%. This can be related to soil erosion – especially interruption from human activities toward hydrologic modifications (such as dredging, water diversions, and channelization) causing disruption in the river [11]. A small percentage of discharge from urban development areas – including land clearings [46] and erosion of road edges due to surface runoff [47] – can also happen within residential areas close to urban areas. Principal component 3 shows moderate positive loadings on COD of 8.1% of total variance, which is usually related to the discharge of municipal wastes [25]. These results from residential areas located within the Kampung Batu Berendam sub-basin, Kampung Kelemak sub-basin, and Kampung Sungai Petai subbasin. Principal component 4 loadings indicate that 8% of total variance have moderately positive DO loadings and moderately negative E. coli loadings. The existence of E. coli can originate from animal husbandry and municipal wastes. Principal component 5 loadings described 6.1% of total variance being moderately negative on Cd. The presence of Cd is potentially from agricultural activity through fertilizer applications and leachate from a nearby dumpsite [48]. Based on site observations, we found that there is a dumpsite located near the river in close vicinity to the residential area. Lastly, principal component 6 showed moderate positive loadings of Pb and Zn total variance of 6%. The connection with Zn pollution may be due to the large number of houses and building areas that use metallic roofs coated with Zn, which can be mobilized into the atmosphere and waterways when in contact with acid rain or smog [25], while the existence of Pb can be attributed to agricultural activities [42].

In the case of cluster 2 (Fig. 4b), principal component 1 indicated 15.3% of total variance for strong positive loadings on DO, EC, and salinity, and moderately positive loadings of NH3N. Principal component 2 loadings showed strong positive turbidity and TSS loadings of 9.2%. As discussed earlier, the principal component 1 and 2 loadings for DO, EC, turbidity, and TSS originate from riverbank erosion and interruption of human activities toward hydrological modifications, causing the river to be polluted through the Kampung Panchor sub-basin. Meanwhile, salinity and NH3N can be connected with effluent from sewage treatment plants that are located within the Kampung Harmoni Belimbing Dalam sub-basin near the river. Meanwhile, principal component 3 has moderately positive loading on BOD and COD, with total variance of 7.6%. This can be related to anthropogenic sources and possibly comes from point source pollution like sewage treatment plants [25, 35]. Next, principal component 4 loadings highlighted the moderately positive of E. coli and coliform loadings with total variance of 6.7%, which are strongly connected with raw and municipal sewage from domestic use, poultry farms, surface runoff, and discharge from wastewater treatment plants [25, 49]. Principal component 5 explained the moderately positive Fe loading with 6.6% total variance, which is suspected from industrial effluents. Principal component 6 explained the strong positive Cr loading with 6.1% total variance, which has a connection with urban storm runoff [50]. Principal component 7 explained the moderately positive of Cd loading with 5.4% total variance and being subjected to leachate from a dumpsite near the residential area [48]. Principal component 8 explained moderately positive of Hg loading with 5.1% total variance, which is suspected of being linked with plastic waste [51]. Generally, principal components 5-8 are subjected to point-source pollution that discharges directly into the river.

Conclusion

Environmetric techniques (HCA, DA, and PCA) were applied to explore and identify the spatial variation and potential sources of pollution in the Malacca River. HCA categorized the nine sampling stations into two clusters, in which cluster 1 comprises S1, S2, S7, and S8 (indicating MPS), and cluster 2 is S3, S4, S5, S6, and S9 (indicating HPS). The MPS occurs within Alor Gajah sub-basin (S1 and S2) and the middle part of Malacca Central sub-basin (S7 and S8), while the HPS are from the lower part of the Alor Gajah sub-basin and Malacca Central sub-basin. DA analysis showed that temperature, salinity, coliform, EC, DO, BOD, COD, As, Hg, Cd, Cr, and Zn are the most significant parameters reflecting the overall quality of the river water as determined from the backward stepwise mode. PCA showed that six components with 54% of total variance were extracted in cluster 1, while eight components with 62% of total variance were extracted in cluster 2. The major sources of pollution come from agricultural and residential areas along the Malacca, as well as from sewage treatment plants and industrial activities.

This study has provided useful information in identifying the pollution sources. Identification of problematic areas through spatial variation output will help in proper management and understanding of the river water quality within the basin in the coming future. Additionally, the study has also provided a water quality database for future references in developing water and land use policies.


Acknowledgement

The authors would like to thank the Malaysian Department of the Environment (DOE), the Department of Irrigation and Drainage (JPS), and the Department of Town and Country Planning (JPBD) for providing water quality data, river information, and GIS map-based information – including land use activities in Malacca State.


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