## 4 Results
### Sediment Export Estimation Using SDR Model  
In general, the SDR model reports soil erosion, sediment retention, sediment deposition, and sediment export. For this study, sediment export was selected to describe ecosystem services in the study area by each LULC allocation scenario (Scenarios I-III).  
The statistical performance of the model under the calibration and validation periods provided a high correlation between the observed and estimated sediment export, with R\({}^{2}\) values of 0.697 and 0.824, respectively, indicating the good and very good fitting performance rate of the model for nitrogen export estimation, as suggested by [51; 52]. These findings are consistent with the previous study of [55], who applied the SDR model to analyze sediment at the Rmel river basin, and found that the correlation between the estimated and observed sediment export in the calibration process was relatively high, with R\({}^{2}\) values of 0.84 and 0.706.  
\begin{table}
\begin{tabular}{l c c c c c c c c c c} \hline \hline \multicolumn{1}{c}{**LULC Types**} & \multicolumn{1}{c}{\multirow{2}{*}{**2020**}} & \multicolumn{1}{c}{\multirow{2}{*}{**2021**}} & \multicolumn{1}{c}{\multirow{2}{*}{**2022**}} & \multicolumn{1}{c}{\multirow{2}{*}{**2023**}} & \multicolumn{1}{c}{\multirow{2}{*}{**2024**}} & \multicolumn{1}{c}{\multirow{2}{*}{**2025**}} & \multicolumn{1}{c}{\multirow{2}{*}{**2026**}} & \multicolumn{1}{c}{\multirow{2}{*}{**2027**}} & \multicolumn{1}{c}{\multirow{2}{*}{**2028**}} & \multicolumn{1}{c}{\multirow{2}{*}{**2029**}} \\ \cline{2-2} \cline{6-11}  & **2020** & **2021** & **2022** & **2023** & **2024** & **2025** & **2026** & **2027** & **2028** & **2029** \\ \hline Urban and built-up area & 33.20 & 33.78 & 33.94 & 34.56 & 34.76 & 35.41 & 35.75 & 36.10 & 36.65 & 36.96 \\ Paddy field & 226.72 & 232.67 & 238.65 & 244.54 & 250.55 & 256.39 & 262.42 & 268.46 & 274.37 & 280.20 \\ Field crop & 23.08 & 24.26 & 25.54 & 26.74 & 27.93 & 29.15 & 30.40 & 31.62 & 32.79 & 34.11 \\ Para rubber & 19.78 & 19.83 & 19.85 & 19.87 & 19.89 & 19.89 & 19.89 & 19.88 & 19.59 & 19.78 \\ Perennial trees and orchards & 74.06 & 68.78 & 63.62 & 58.31 & 53.13 & 47.91 & 42.65 & 37.46 & 32.17 & 26.94 \\ Forest land & 433.30 & 429.61 & 425.98 & 422.30 & 418.60 & 414.93 & 411.24 & 407.57 & 403.96 & 400.22 \\ Water body & 34.34 & 34.93 & 35.73 & 36.43 & 37.07 & 37.96 & 38.71 & 39.48 & 40.47 & 41.11 \\ Rangeland & 27.86 & 28.46 & 29.06 & 29.68 & 30.61 & 30.94 & 31.56 & 32.14 & 32.78 & 33.44 \\ Wetland & 16.22 & 16.10 & 15.97 & 15.78 & 15.63 & 15.43 & 15.29 & 15.11 & 14.96 & 14.85 \\ Miscellaneous land & 2.79 & 2.92 & 3.00 & 3.14 & 3.18 & 3.34 & 3.44 & 3.53 & 3.61 & 3.73 \\ \hline
**Total** & **891.35** & **891.35** & **891.35** & **891.35** & **891.35** & **891.35** & **891.35** & **891.35** & **891.35** & **891.35** \\ \hline \hline \end{tabular}
\end{table}
Table 18: Area of predicted LULC between 2020 and 2029 under Scenario III.  
Figure 6: Spatial distribution of LULC data under Scenario III: (**a**) in 2020 and (**b**) in 2029.  
Meanwhile, the PBIAS values under the calibration period provided a good fit between the estimated and observed sediment export, with a value of \(-27.03\%\), while the PBIAS value under the validation period delivered an unsatisfactory fit between the estimated and observed sediment export, with a value of \(65.60\%\), in accordance with [51; 52]. The optimum local model parameters and domain values under the calibration period of the SDR model are summarized in Table 19.