Pemodelan Direct Runoff sebagai Indikator Degradasi Jasa Ekosistem Pengaturan Aliran Air di Daerah Aliran Sungai Dengkeng Tahun 2014-2044

Satrio Budiman, Prof. Dr. Slamet Suprayogi, M.S.; Dr.Sc. Andung Bayu Sekaranom, S.Si., M.Sc.

2026 | Tesis | S2 Geografi

Jasa ekosistem pengaturan aliran air berperan penting dalam menjaga stabilitas hidrologi DAS. DAS Dengkeng merupakan hulu yang mengalami permasalahan ketersediaan air dan banjir. Tekanan perubahan iklim dan penutup lahan berpotensi meningkatkan limpasan permukaan dan menurunkan kemampuan DAS dalam mengatur aliran air. Oleh karena itu, penelitian ini bertujuan untuk (1) mengkaji potensi direct runoff (DRO) sebagai indikator degradasi jasa ekosistem pengaturan aliran air, mengkaji potensi degradasi jasa ekosistem pengaturan aliran air pada tahun 2014-2044, dan (3) menganalisis respons hidrologis DAS Dengkeng terhadap perubahan iklim dan perubahan penutup lahan.

Potensi DRO diestimasikan menggunakan Seasonal Water Yield Model (SWYM) InVEST. Model iklim EC-Earth3-CC dan MPI-ESM1 dari CMIP6 dengan skenario SSP2-4.5 diolah menggunakan quantile mapping pada Climate Data Bias Corrector (CDBC) untuk memproyeksikan curah hujan dan suhu udara. Perubahan penutup lahan disimulasikan menggunakan Cellular Automata-Artificial Neural Network pada plugin MOLUSCE. Degradasi jasa ekosistem pengaturan aliran air dikalkulasikan berdasarkan selisih antara DRO aktual dan referensi. Respons hidrologis terhadap perubahan iklim dan penutup lahan dianalisis menggunakan analisis sensitivitas One-At-a-Time (OAT), relative importance index (RII), combined effect index (CEI), dan variasi dimensi spasial-temporal (regresi data panel).

Uji Wilcoxon dan Kolmogorov-Smirnov menunjukkan bahwa model iklim hasil koreksi bias tidak berbeda signifikan dengan data observasi (p-value >0,05), sedangkan simulasi penutup lahan menghasilkan akurasi sebesar 86%. Model SWYM InVEST menunjukkan performa yang baik (R2 = 0,79-0,83; NSE = 0,69-0,78). Namun, PBIAS pada periode kalibrasi yang tidak memuaskan (34%) diduga disebabkan oleh banyaknya kejadian hujan dengan intensitas rendah selama bulan musim hujan. DRO tertinggi dan terendah berada pada lahan terbangun (128,03 mm) dan hutan (14,99 mm). Degradasi jasa ekosistem pengaturan aliran air di DAS Dengkeng diproyeksikan meningkat dari 15 juta m3 pada tahun 2014 menjadi 45 juta m3 pada tahun 2044 dan meluas dari bagian hulu menuju bagian tengah DAS. Analisis sensitivitas OAT menunjukkan bahwa curah hujan (SI = 5,13) memiliki respons DRO lebih besar dibandingkan CN (SI = 0,99). RII (-0,696) menunjukkan curah hujan memiliki kepentingan relatif lebih tinggi dibandingkan CN, sedangkan CEI (-0,0117) menunjukkan efek gabungan yang bersifat synergistic, tetapi mendekati independent. Regresi data panel menunjukkan nilai SRC curah hujan sebesar 0,783 dan CN sebesar 0,646 yang berarti respons degradasi jasa ekosistem terhadap variasi curah hujan relatif lebih besar dibandingkan variasi CN dalam SWYM InVEST. Secara keseluruhan, hasil penelitian menunjukkan bahwa degradasi jasa ekosistem pengaturan aliran air di DAS Dengkeng lebih responsif terhadap perubahan curah hujan dibandingkan perubahan penutup lahan.

The hydrological stability of a watershed is largely dependent on water regulation ecosystem services. The Dengkeng Watershed is an upstream area that experiences water availability and flooding. Climate change and land cover changes may increase surface runoff and diminish the watershed's ability to manage water flow. Thus, the objectives of this study are to: (1) assess the potential of direct runoff (DRO) as an indicator of degradation in water flow regulation ecosystem services; (2) assess the potential for degradation of water flow regulation ecosystem services between 2014-2044; and (3) analyze the hydrological response of the Dengkeng Watershed to climate change and land cover change.

The InVEST Seasonal Water Yield Model (SWYM) was utilized to determine DRO potential. Quantile mapping was used in the Climate Data Bias Corrector (CDBC) to estimate precipitation and air temperature from the EC-Earth3-CC and MPI-ESM1 climate models from the CMIP6 under the SSP2-4.5 scenario. The MOLUSCE plugin simulates land cover changes using Cellular Automata-Artificial Neural Network. The degradation of water regulation ecosystem services was calculated using the difference between the actual and reference DRO. Hydrological responses to climate change and land cover were analyzed using One-At-a-Time (OAT) sensitivity analysis, the relative importance index (RII), the combined effect index (CEI), and spatial-temporal variations (panel data regression).

Wilcoxon and Kolmogorov-Smirnov tests showed that the bias-corrected climate model did not differ significantly from the observed data (p-value > 0.05), while the land-cover simulation achieved an accuracy of 86%. The SWYM InVEST model showed good performance (R2 = 0.79-0.83; NSE = 0.69-0.78). However, unsatisfactory calibration period PBIAS (34%) was primarily attributed to the large number of low-intensity rain events during wet months. The highest and lowest DRO values were generated by built-up areas (128.03 mm) and forests (14.99 mm). Ecosystem service degradation was projected to increase from 15 million m3 in 2014 to 45 million m3 in 2044 and expand from the upstream to the middle part of the watershed. OAT sensitivity analysis showed that rainfall (SI = 5.13) produced a greater DRO response than CN (SI = 0.99). The RII (-0.696) indicated that rainfall had greater relative importance than CN, while the CEI (-0.0117) indicated a synergistic combined effect that was close to independent. Panel regression showed SRC values of 0.783 for rainfall and 0.646 for CN, indicating that the response of ecosystem service degradation to rainfall variation was relatively greater than its response to CN variation in SWYM InVEST. Overall, the results indicate that degradation of the water flow regulation ecosystem service in the Dengkeng Watershed was more responsive to changes in rainfall than to changes in land cover.

Kata Kunci : curah hujan, curve number, jasa ekosistem pengaturan aliran air, direct runoff, respons hidrologis DAS