# Dynamic Modeling of Sediment Budget in Shihmen Reservoir Watershed in Taiwan

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## Abstract

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## 1. Background

## 2. Study Area—Shihmen Reservoir Watershed

## 3. Introduction to GSPTM

#### 3.1. Rainfall–Runoff Model

#### 3.2. Sediment Production Prediction

#### 3.2.1. Landslide Model

#### 3.2.2. Soil Erosion Prediction

#### 3.3. Mass Movement Simulation

#### 3.4. Runoff Simulation

#### 3.5. Sediment Transport

#### 3.6. Model Verification and Performance Elevation

## 4. Result and Discussion—Reconstruction of Typhoon Morakot Event

#### 4.1. Mass Production by Landslide and Soil Erosion

#### 4.2. Sediment Transport Condition

#### 4.3. Sediment Delivery Condition

## 5. Concluding Remarks

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 1.**Shihmen Reservoir watershed and the watersheds of interest. The measurements of riverflow and sediment discharges at Yufeng and Xiuluan stations were used for verification. The watersheds upstream to Yufeng and Xiuluan stations are marked by solid black lines.

**Figure 2.**Landslide inventory in the 10 typhoon events in Shihmen Reservoir watershed. Solid black lines denote the watersheds of interest for calibration and verification.

**Figure 3.**Framework and flowchart of Grid-based Sediment Production and Transport Model (GSPTM). USLE, Universal Soil Loss Equation.

**Figure 4.**Predicted landslide area using Equation (2) before and after recalibration in terms of the observed landslide inventory of the nine typhoons.

**Figure 6.**Spatial distribution of mass produced by landslide and soil erosion, runoff, and sediment discharges in Xiuluan and Yufeng watersheds at three instants. (

**a**) Cumulative landslide and soil erosion; (

**b**) runoff; (

**c**) sediment.

**Figure 7.**Hydrograph of the two curves of simulated soil water index (SWI) at two simulated landslides. For further discussion of the landslide A and B, refer to the following section and Figure 6a.

**Figure 8.**Hydrograph of simulated runoff and sediment discharge at Xiuluan (left column) and Yufeng (right column) gauge stations during Typhoon Morakot. The spatial distributions at the time marked by the three dashed are illustrated in Figure 6. (

**a**) Xiuluan runoff; (

**b**) Yufeng runoff; (

**c**) Xiuluan sediment; (

**d**) Yufeng sediment.

**Figure 9.**Cumulative sediment production and discharge and the sediment delivery ratio of Typhoon Morakot.

Attribute (unit) | Variable | Coefficient b | Standard Error of the Mean (%) | Wald | p-Value |
---|---|---|---|---|---|

elevation (m) | $\mathit{ele}$ | 8.0 × ${10}^{-4}$ | 0.000 | 106.810 | 0.000 |

inclination (${}^{\circ}$) | $\mathit{slp}$ | 0.058 | 0.002 | 554.326 | 0.000 |

aspect sine (-) | $\mathit{aps}$ | 0.076 | 0.028 | 7.211 | 0.007 |

aspect cosine (-) | $\mathit{apc}$ | −0.45 | 0.028 | 274.032 | 0.000 |

longitudinal curvature (m${}^{-1}$) | $\mathit{cpf}$ | −1.84 | 0.710 | 6.740 | 0.009 |

planar curvature (m${}^{-1}$) | $\mathit{cpl}$ | −1.67 | 0.684 | 5.942 | 0.015 |

topographic wetting index (m) | $\mathit{twi}$ | 0.25 | 0.016 | 245.940 | 0.000 |

distance to river (km) | $\mathit{drv}$ | −9.0 × ${10}^{-4}$ | 0.000 | 58.786 | 0.000 |

distance to ridge (km) | $\mathit{drd}$ | 5.0 × ${10}^{-3}$ | 0.000 | 27.411 | 0.000 |

distance to road (km) | $\mathit{dro}$ | 4.0 × ${10}^{-5}$ | 0.000 | 8.967 | 0.003 |

geological category ${}^{\u2020}$ | $\mathit{geo}$ | 1.0 | 0.000 | 106.810 | 0.000 |

soil water index (m) | $\mathit{swi}$ | 0.00657 | 0.000 | 985.196 | 0.000 |

constant (-) | $\mathit{a}$ | −7.534 | 0.275 | 695.069 | 0.000 |

**Table 2.**Regression values for the categorical variable of $geo$ in terms of different lithological types.

Category | Value | Category | Value |
---|---|---|---|

Erhchiu formation (Eh) | −0.297 | Kangkou formation (Kk) | −1.008 |

Tapu Formation (Tp) | 1.271 | Tsuku Formation (Tu) | −0.175 |

Mushan Form (Ms) | 0.237 | Terrace Deposits (t) | −2.302 |

Paling Form (Pl) | 0.714 | Piling Shale (Pi) | 0.000 |

Peiliao Formation (Pe) | 0.136 | Shihti Formation (St) | −0.058 |

Szeleng Sandstone (Ss) | −0.158 | Hsitsun Formation (Ht) | −0.300 |

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**MDPI and ACS Style**

Chen, Y.-C.; Wu, Y.-H.; Shen, C.-W.; Chiu, Y.-J. Dynamic Modeling of Sediment Budget in Shihmen Reservoir Watershed in Taiwan. *Water* **2018**, *10*, 1808.
https://doi.org/10.3390/w10121808

**AMA Style**

Chen Y-C, Wu Y-H, Shen C-W, Chiu Y-J. Dynamic Modeling of Sediment Budget in Shihmen Reservoir Watershed in Taiwan. *Water*. 2018; 10(12):1808.
https://doi.org/10.3390/w10121808

**Chicago/Turabian Style**

Chen, Yi-Chin, Ying-Hsin Wu, Che-Wei Shen, and Yu-Jia Chiu. 2018. "Dynamic Modeling of Sediment Budget in Shihmen Reservoir Watershed in Taiwan" *Water* 10, no. 12: 1808.
https://doi.org/10.3390/w10121808