PEMODELAN SPASIAL-TEMPORAL CBOD DAN DO SUNGAI LAWA MENGGUNAKAN WATER QUALITY ANALYSIS SIMULATION PROGRAM (WASP)

Edhi Sarwono, Marlon I Aipassa, Ndan Imang, Yohanes Budi Sulistioadi, Komsanah Sukarti, Henny Pagoray, Sri Wahyuningsih

Abstract


Sungai Lawa merupakan badan air penerima dari aktivitas pertambangan batubara dan perkebunan kelapa sawit di sekitar sungai. Penelitian ini bertujuan memodelkan penyebaran Carbonaceous Biochemical Oxygen Demand (CBOD) dan dissolved oxygen (DO) di Sungai Lawa menggunakan Water Quality Analysis Simulation Program (WASP8 US EPA), menganalisis perubahan konsentrasi berdasarkan jarak hulu ke hilir, serta mengevaluasi perubahan temporal enam waktu simulasi. Ruas Sungai Lawa sepanjang 69,38 km dimodelkan menjadi 18 segmen utama dengan masukan lateral dari anak sungai dan saluran buangan. Simulasi dilakukan pada 22-23 Desember 2025 dengan keluaran pada enam waktu. Data BOD hasil pengukuran lapangan digunakan sebagai dasar input dan pembanding parameter organik, sedangkan keluaran model dianalisis sebagai CBOD sesuai variabel keadaan dalam WASP. Validasi model menggunakan MAE, RMSE, MAPE dan R2. Hasil simulasi menunjukkan CBOD berubah secara longitudinal sebagai respons masukan beban organik dan proses degradasi, sedangkan DO menunjukkan variasi yang dipengaruhi beban organik, reaerasi, dan kondisi hidraulik. Validasi terbaik CBOD terjadi pada 22 Desember 2025 pukul 00.00 WITA dengan MAE 0,26 mg/L, RMSE 0,30 mg/L, dan MAPE 9,86%; sedangkan validasi terbaik DO pada waktu yang sama, MAE 0,32 mg/L, RMSE 0,37 mg/L, dan MAPE 13,86%. Model WASP dapat digunakan untuk menggambarkan kecenderungan spasial-temporal CBOD dan DO Sungai Lawa sebagai dasar evaluasi kualitas air.


Keywords


CBOD; DO; Kualitas Air; Sungai Lawa; WASP

Full Text:

PDF

References


D. Alfrianti and A. Sudradjat, “Managing organic pollutant loads in the Lower Cileungsi River, Indonesia,” Water Policy, vol. 26, no. 10, pp. 959–977, Oct. 2024, doi: 10.2166/wp.2024.023.

K. C. Deepa Varsa, A. W. A. Rahiman, E. Arunbabu, K. J. Antony, and N. Priyadharshini, “Water quality simulation using the WASP model for eutrophication control in a South Indian Reservoir,” Water Pract. Technol., vol. 18, no. 11, pp. 2740–2758, Nov. 2023, doi: 10.2166/wpt.2023.173.

M. Żelazny, M. Bryła, B. Ozga-Zielinski, and T. Walczykiewicz, “Applicability of the WASP Model in an Assessment of the Impact of Anthropogenic Pollution on Water Quality—Dunajec River Case Study,” Sustainability (Switzerland), vol. 15, no. 3, Feb. 2023, doi: 10.3390/su15032444.

N. Obin, H. Tao, F. Ge, and X. Liu, “Research on water quality simulation and water environmental capacity in lushui river based on wasp model,” Water (Switzerland), vol. 13, no. 20, Oct. 2021, doi: 10.3390/w13202819.

D. Castillo et al., “Modeling Metal(loid)s Transport in Arid Mountain Headwater Andean Basin: A WASP-Based Approach,” Water (Switzerland), vol. 17, no. 13, Jul. 2025, doi: 10.3390/w17131905.

NASA POWER, “NASA POWER Data Access Viewer,” NASA Langley Research Center. Accessed: Apr. 09, 2026. [Online]. Available: https://power.larc.nasa.gov/data-access-viewer/

Z. Liao, C. Zhou, W. Tian, T. Hu, and R. Guo, “CBR-based integration of a hydrodynamic and water quality model and GIS—a case study of Chaohu City,” Environmental Science and Pollution Research, vol. 26, no. 7, pp. 6436–6449, Mar. 2019, doi: 10.1007/s11356-018-3862-5.

J. Vasilev, P. Petrov, and J. Jordanov, “A Practical Approach of Data Visualization from Geographic Information Systems by Using Mobile Technologies,” International Journal of Interactive Mobile Technologies, vol. 18, no. 3, pp. 4–15, 2024, doi: 10.3991/ijim.v18i03.46655.

A. Das, “A data-driven approach utilizing machine learning (ML) and geographical information system (GIS)-based time series analysis with data augmentation for water quality assessment in Mahanadi River Basin, Odisha, India,” Discover Sustainability, vol. 6, no. 1, Dec. 2025, doi: 10.1007/s43621-025-01464-7.

T. O. Hodson, “Root-mean-square error (RMSE) or mean absolute error (MAE): when to use them or not,” Jul. 19, 2022, Copernicus GmbH. doi: 10.5194/gmd-15-5481-2022.

M. M. Mundu, J. I. Sempewo, A. Goparaju, and D. E. Uti, “Comparative Analysis of Model Evaluation Metrics in Energy Systems, Environmental Modeling, and Sustainability Science,” Int. J. Energy Res., vol. 2026, no. 1, 2026, doi: 10.1155/er/6170467.

A. A. Mamun, M. Nuruzzaman, and M. N. Salleh, “Assessing Reaeration Rate Equations for Modelling Dissolved Oxygen of Pusu River in Malaysia,” ASM Science Journal, vol. 18, 2023, doi: 10.32802/asmscj.2023.1193.

A. Jaffar, N. M. Thamrin, M. S. A. M. Ali, M. F. Misnan, A. I. M. Yassin, and N. M. Zan, “Spatial interpolation method comparison for physico-chemical parameters of river water in Klang River using MATLAB,” Bulletin of Electrical Engineering and Informatics, vol. 11, no. 4, pp. 2368–2377, Aug. 2022, doi: 10.11591/eei.v11i4.3615.

A. Muhammad et al., “A Localized Evaluation of Surface Water Quality Using GIS-Based Water Quality Index along Satpara Watershed Skardu Baltistan, Pakistan,” ISPRS Int. J. Geoinf., vol. 13, no. 11, Nov. 2024, doi: 10.3390/ijgi13110393.




DOI: http://dx.doi.org/10.30872/jtlunmul.v10i1.27439

Refbacks

  • There are currently no refbacks.


Copyright (c) 2026 Jurnal Teknologi Lingkungan UNMUL





Program Studi Teknik Lingkungan
Fakultas Teknik
Universitas Mulawarman
Jl. Sambaliung No 9, Kampus Gunung Kelua, Samarinda, Indonesia