Model Peringatan Dini Perubahan Mutu Air dan Strategi Pengelolaan Mutu Air Sungai dengan Pendekatan Sistem Dinamik

Zubaidah, Tien (2019) Model Peringatan Dini Perubahan Mutu Air dan Strategi Pengelolaan Mutu Air Sungai dengan Pendekatan Sistem Dinamik. Doctoral thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Permasalahan pencemaran sungai yang kompleks, dapat didekati dengan model sistem dinamik. Tujuan utama penelitian ini adalah membangun model peringatan dini perubahan mutu air sungai yang didasari metode sistem dinamik. Model ini dibangun dari dua parameter pencemar air sungai yaitu BOD dan COD. Model peringatan dini perubahan mutu air sungai ditunjukkan oleh penurunan nilai DO menuju ke arah indikator berwarna merah yang mengindikasikan bahwa kualitas air sungai dalam kondisi tercemar berat. Model ini dapat berjalan dengan baik pada sungai dengan kondisi tanpa dipengaruhi oleh pasang surut. Langkah pertama dalam penelitian ini adalah melakukan analisis kondisi eksisting Sungai Martapura dan pembuatan model clustering daerah rawan pencemaran air dan model clustering sumber pencemar domestic. Langkah kedua yaitu menentukan beban pencemaran dan menentukan kapasitas asimilasi sungai. Langkah ketiga yaitu membangun 7 sub model yang didasari metode sistem dinamik meliputi kependudukan, limbah pemukiman, limbah rumah makan, limbah hotel, limbah pasar, limbah tempat umum lainnya dan beban pencemaran. Selanjutnya sub model tersebut terintegrasi dalam model peringatan dini perubahan mutu air sungai. Langkah keempat yaitu memvisualisasikan hasil simulasinya melalui dashboard Microsoft Power BI. Hasil penelitian menunjukkan kualitas air untuk parameter BOD, COD dan total coliform telah melampaui baku mutu air kelas I. Model clustering daerah rawan pencemaran bervariasi menurut waktu dan titik pengamatan. Model clustering sumber pencemar domestik menunjukkan sumber pencemar utama yang mencemari badan air berasal dari rumah tangga. Beban pencemaran yang masuk telah melebihi kemampuan kapasitas asimilasi sungai. Hasil simulasi kondisi eksisting beban pencemar yang masuk ke badan air bervariasi menurut titik pengamatan, di akhir periode simulasi beban pencemar maksimal untuk parameter BOD sebesar 672,22 ton/tahun, COD sebesar 937,16 ton/tahun. Sementara untuk simulasi parameter indikator peringatan dini yaitu DO, di akhir periode simulasi, terjadi penurunan nilai DO di semua titik pengamatan menuju ke status mutu air tercemar berat (nilai DO < 2 mg/L). Hasil simulasi kondisi moderat beban pencemar yang masuk ke badan air bervariasi menurut titik pengamatan, di akhir periode simulasi beban pencemar maksimal untuk parameter BOD sebesar 443,15 ton/tahun, COD sebesar 585,17 ton/tahun. Sementara untuk simulasi parameter indikator DO, di akhir periode simulasi, titik pengamatan 4 dan 5, nilai DO pada status mutu air tercemar sedang (DO ≥ 2 – 4,4 mg/L). Hasil simulasi kondisi optimis beban pencemar yang masuk ke badan air menunjukkan simulasi beban pencemar maksimal untuk parameter BOD sebesar 160,88 ton/tahun, COD sebesar 211,73 ton/tahun. Sementara untuk simulasi parameter DO, di akhir periode simulasi, semua titik pengamatan berada pada status mutu air tidak cermar/tercemar ringan (DO ≥ 4,5 mg/L). Dari ke tiga simulasi skenario di atas, strategi yang paling efektif untuk menurunkan beban pencemar dan meningkatkan nilai oksigen terlarut (DO) air sungai adalah skenario pada kondisi optimis yaitu (1) Peningkatan partisipasi masyarakat (2) pengadaann IPAL (3) Penegakan hukum lingkungan dan (4) Kerjasama lintas sektoral. Penerapan skenario ini memberikan penurunan yang memberi dampak pada kenaikan nilai DO sebagai indikator kesehatan perairan dengan besar penurunan beban pencemar BOD sebesar 80 persen dan COD sebesar 73 persen, sehingga kualitas badan air sesuai dengan baku mutu peruntukannya sebagai badan air Kelas I (satu).
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Complex pollution problems in the river can be solved using a dynamic system model approach. The research's main objective is to initiate an early warning model for changes in river water quality based on dynamic system methods. This model is built on two river water pollution parameters, the BOD and COD. Early warning for river water quality changing is indicated by a decrease in DO values, which leads to a red indicator, as a sign that the river is in a heavily polluted condition. In this study, the model was designed based on the magnitude of DO simulation values change, set in monthly units and for long-term strategies (four years predictions). In this dissertation, an early warning model of changes in water quality can work well in rivers whose conditions are not affected by tides. The first step of this research is to analyze the existing condition of the Martapura River. The research location is divided into five observation points as a reference for making clustering models for areas that are prone to water pollution and dominant domestic pollutant sources. The second step is determining the pollution load and measuring the assimilation capacity of the river. The third step is to build various sub-models, which include : Population, Settlement waste, Restaurants waste, Hotel waste, Market waste, Other public waste and Pollution load. In the third step, the sub models will be used to develop a dynamic-early warning model for river water quality changes. The fourth step is to visualize the simulation results through Microsoft Power BI dashboard. Water quality assessment has shown that BOD, COD and total coliform parameters have exceeded the class 1 of water quality standards. The water quality data were clustered to determine the pollution-prone areas clustering model, which varied according to time and observation point. In the clustering of domestic pollutant sources on the river has shown the fact that households have become the primary and dominant pollutant source in the waters of the Martapura River. Regarding the river's assimilation capacity, the Martapura River has received pollution loads that exceed its capacity. The highest waste load simulation results for BOD, COD and TSS had been indicated at #4th point flow, while the smallest one occurs at #1st point flow. The Existing simulation results also show variations in pollutant load rates on each parameter. At the end of the current simulation period, the BOD range was 58.66 to 672.22 tons/year, and 82.26 to 937.16 tons/year for COD. While for DO simulation, at the end of the simulation period, it has indicated that all observation points are in heavily polluted conditions (red indicator). For the moderate condition simulation, it reported different result at the end of the simulation period. In moderate conditions, the BOD concentration reaches a range of 27.62 to 443.15 tons/year, while COD reaches 40.63 to 585.17 tons/year. As for early warning simulations, DO indicators show green indicators (lightly polluted and not polluted) at observation points 1, 2 and 3. While for optimistic condition simulation, also confirmed the different result at the end of the simulation period. In the optimist conditions, BOD concentrations reached 10.84 up to 160.88 tons/year, while COD reached 15.94 to 221.73 tons/year. For the simulation of the early warning itself, the DO indicator shows all observation points in a non-polluted condition (indicated green).From those three scenario simulations, optimistic condition scenario had shown the most effective and possible strategy to be adapted to reduce pollutant load and increase the river’s dissolved oxygen (DO) levels. The implementation of the scenario will have an impact on BOD decrease by 80 per cent and COD by 73 per cent. The reduction will affected the DO values, which is considered as a healthy river indicator so that the Martapura river function as a 1st Class water body can be achieved.

Item Type:	Thesis (Doctoral)
Uncontrolled Keywords:	klasterisasi, pencemar domestik, model peringatan dini, model sistem dinamik
Subjects:	T Technology > TD Environmental technology. Sanitary engineering > TD420 Water pollution
Divisions:	Faculty of Civil, Environmental, and Geo Engineering > Environmental Engineering > 25001-(S3) PhD Theses
Depositing User:	Tien Zubaidah
Date Deposited:	22 Jul 2026 07:03
Last Modified:	22 Jul 2026 07:03
URI:	http://repository.its.ac.id/id/eprint/70793

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