scholarly journals Dynamic Modeling of Sediment Budget in Shihmen Reservoir Watershed in Taiwan

Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1808 ◽  
Author(s):  
Yi-Chin Chen ◽  
Ying-Hsin Wu ◽  
Che-Wei Shen ◽  
Yu-Jia Chiu
Keyword(s):  
Sediment Transport ◽  
Soil Erosion ◽  
Landslide Susceptibility ◽  
Delivery Ratio ◽  
Mountainous Area ◽  
Sediment Discharge ◽  
Rainfall Runoff ◽  
Sediment Production ◽  
Shihmen Reservoir ◽  
Reservoir Watershed

Qualifying sediment dynamic in a reservoir watershed is essential for water resource management. This study proposed an integrated model of Grid-based Sediment Production and Transport Model (GSPTM) at watershed scale to evaluate the dynamic of sediment production and transport in the Shihmen Reservoir watershed in Taiwan. The GSPTM integrates several models, revealing landslide susceptibility and processes of rainfall–runoff, sediment production from landslide and soil erosion, debris flow and mass movement, and sediment transport. For modeling rainfall–runoff process, the tanks model gives surface runoff volume and soil water index as a hydrological parameter for a logistic regression-based landslide susceptibility model. Then, applying landslide model with a scaling relation of volume and area predicts landslide occurrence. The Universal Soil Loss Equation is then used for calculating soil erosion volume. Finally, incorporating runoff-routing algorithm and the Hunt’s model achieves the dynamical modeling of sediment transport. The landslide module was calibrated using a well-documented inventory during 10 heavy rainfall or typhoon events since 2004. A simulation of Typhoon Morakot event was performed to evaluate model’s performance. The results show the simulation agrees with the tendency of runoff and sediment discharge evolution with an acceptable overestimation of peak runoff, and predicts more precise sediment discharge than rating methods do. In addition, with clear distribution of sediment mass trapped in the mountainous area, the GSPTM also showed a sediment delivery ratio of 30% to quantify how much mass produced by landslide and soil erosion is still trapped in mountainous area. The GSPTM is verified to be useful and capable of modeling the dynamic of sediment production and transport at watershed level, and can provide useful information for sustainable development of Shihmen Reservoir watershed.

scholarly journals Estimating sediment delivery ratio by stream slope and relief ratio

2018 ◽  
Vol 192 ◽  
pp. 02040 ◽  
Author(s):  
Kieu Anh Nguyen ◽  
Walter Chen
Keyword(s):  
Soil Erosion ◽  
Storage Capacity ◽  
Length Ratio ◽  
Delivery Ratio ◽  
Sediment Delivery Ratio ◽  
Sediment Delivery ◽  
Transportation Process ◽  
Shihmen Reservoir ◽  
Reservoir Watershed ◽  
Steep Terrain

Nowadays, the storage capacity of a reservoir reduced by sediment deposition is a concern of many countries in the world. Therefore, understanding the soil erosion and transportation process is a significant matter, which helps to manage and prevent sediments entering the reservoir. The main objective of this study is to examine the sediments reaching the outlet of a basin by empirical sediment delivery ratio (SDR) equations and the gross soil erosion. The Shihmen reservoir watershed is used as the study area. Because steep terrain is a characteristic feature of the study area, two SDR models that depend on the slope of the mainstream channel and the relief-length ratio of the watershed are chosen. It is found that the Maner (1958) model, which uses the relief-length ratio, is the better model of the two. We believe that this empirical research improves our understanding of the sediment delivery process occurring in the study area.

scholarly journals Evaluation of the SEdiment Delivery Distributed (SEDD) Model in the Shihmen Reservoir Watershed

2020 ◽  
Vol 12 (15) ◽  
pp. 6221
Author(s):  
Kent Thomas ◽  
Walter Chen ◽  
Bor-Shiun Lin ◽  
Uma Seeboonruang
Keyword(s):  
Sediment Yield ◽  
Economic Cost ◽  
Future Research ◽  
Delivery Ratio ◽  
Sediment Delivery ◽  
Sediment Control ◽  
Watershed Prioritization ◽  
Aerial Photogrammetry ◽  
Shihmen Reservoir ◽  
Reservoir Watershed

The sediment delivery ratio (SDR) connects the weight of sediments eroded and transported from slopes of a watershed to the weight that eventually enters streams and rivers ending at the watershed outlet. For watershed management agencies, the estimation of annual sediment yield (SY) and the sediment delivery has been a top priority due to the influence that sedimentation has on the holding capacity of reservoirs and the annual economic cost of sediment-related disasters. This study establishes the SEdiment Delivery Distributed (SEDD) model for the Shihmen Reservoir watershed using watershed-wide SDRw and determines the geospatial distribution of individual SDRi and SY in its sub-watersheds. Furthermore, this research considers the statistical and geospatial distribution of SDRi across the two discretizations of sub-watersheds in the study area. It shows the probability density function (PDF) of the SDRi. The watershed-specific coefficient (β) of SDRi is 0.00515 for the Shihmen Reservoir watershed using the recursive method. The SY mean of the entire watershed was determined to be 42.08 t/ha/year. Moreover, maps of the mean SY by 25 and 93 sub-watersheds were proposed for watershed prioritization for future research and remedial works. The outcomes of this study can ameliorate future watershed remediation planning and sediment control by the implementation of geospatial SDRw/SDRi and the inclusion of the sub-watershed prioritization in decision-making. Finally, it is essential to note that the sediment yield modeling can be improved by increased on-site validation and the use of aerial photogrammetry to deliver more updated data to better understand the field situations.

scholarly journals Soil Erosion Modeling and Comparison Using Slope Units and Grid Cells in Shihmen Reservoir Watershed in Northern Taiwan

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1387 ◽  
Author(s):  
Yi-Hsin Liu ◽  
Dong-Huang Li ◽  
Walter Chen ◽  
Bor-Shiun Lin ◽  
Uma Seeboonruang ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Grid Cell ◽  
Extreme Rainfall ◽  
Rainfall Erosivity ◽  
Grid Cells ◽  
Cell Method ◽  
Slope Unit ◽  
Shihmen Reservoir ◽  
Reservoir Watershed ◽  
Northern Taiwan

Soil erosion is a global problem that will become worse as a result of climate change. While many parts of the world are speculating about the effect of increased rainfall intensity and frequency on soil erosion, Taiwan’s mountainous areas are already facing the power of rainfall erosivity more than six times the global average. To improve the modeling ability of extreme rainfall conditions on highly rugged terrains, we use two analysis units to simulate soil erosion at the Shihmen reservoir watershed in northern Taiwan. The first one is the grid cell method, which divides the study area into 10 m by 10 m grid cells. The second one is the slope unit method, which divides the study area using natural breaks in landform. We compared the modeling results with field measurements of erosion pins. To our surprise, the grid cell method is much more accurate in predicting soil erosion than the slope unit method, although the slope unit method resembles the real terrains much better than the grid cell method. The average erosion pin measurement is 6.5 mm in the Shihmen reservoir watershed, which is equivalent to 90.6 t ha−1 yr−1 of soil erosion.

Sediment transport by shallow flows impacted by pulsed artificial rainfall

Soil Research ◽  
1993 ◽  
Vol 31 (2) ◽  
pp. 199 ◽  
Author(s):  
PIA Kinnell
Keyword(s):  
Sediment Transport ◽  
Soil Erosion ◽  
High Intensity ◽  
Influence Factors ◽  
High Energy ◽  
Sediment Discharge ◽  
Natural Conditions ◽  
Artificial Rainfall ◽  
Shallow Flows

In many experiments using rainfall simulators, rainfall is applied to the target as a high intensity pulse so that there are often long periods when the soil receives no rain and there are short periods when the soil receives rain at an extremely high intensity. Because concerns exist about the use of such methods of applying rain in experiments designed to help predict erosion under natural conditions, experiments using intermittent and continuous artificial rainfall were performed and analysed in terms of a recently developed theory on erosion by rain-impacted flow. The results indicate that the manner in which the rain is applied does not significantly influence the time-averaged sediment discharge from the sediment transport perspective. However, if high intensity, high energy pulses of rain influence factors which affect the susceptibility of the soil to erosion differently to continuous rain, then concerns about the use of intermittent rainfall in soil erosion experiments remain.

scholarly journals Improvement of the K-Factor of USLE and Soil Erosion Estimation in Shihmen Reservoir Watershed

2019 ◽  
Vol 11 (2) ◽  
pp. 355 ◽  
Author(s):  
Bor-Shiun Lin ◽  
Chun-Kai Chen ◽  
Kent Thomas ◽  
Chen-Kun Hsu ◽  
Hsing-Chuan Ho
Keyword(s):  
Soil Erosion ◽  
Water Conservation ◽  
Large Scale ◽  
Chemical Properties ◽  
Past Research ◽  
Area Of Interest ◽  
K Factor ◽  
Shihmen Reservoir ◽  
The Difference ◽  
Reservoir Watershed

The estimation of soil erosion in Taiwan and many countries of the world is based on the widely used universal soil loss equation (USLE), which includes the factor of soil erodibility (K-factor). In Taiwan, K-factor values are referenced from past research compiled in the Taiwan Soil and Water Conservation Manual, but there is limited data for the downstream area of the Shihmen reservoir watershed. The designated K-factor from the manual cannot be directly applied to large-scale regional levels and also cannot distinguish and clarify the difference of soil erosion between small field plots or subdivisions. In view of the above, this study establishes additional values of K-factor by utilizing the double rings infiltration test and measures of soil physical–chemical properties and increases the spatial resolution of K-factor map for Shihmen reservoir watershed. Furthermore, the established values of K-factors were validated with the designated value set at Fuxing Sanmin from the manual for verifying the correctness of estimates. It is found that the comparative results agree well with established estimates within an allowable error range. Thus, the K-factors established by this study update the previous K-factor system and can be spatially estimated for any area of interest within the Shihmen reservoir watershed and improving upon past limitations.

Geographic information system-coupling sediment delivery distributed modeling based on observed data

2014 ◽  
Vol 70 (3) ◽  
pp. 495-501 ◽  
Author(s):  
S. E. Lee ◽  
S. H. Kang
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Soil Erosion ◽  
Soil Loss ◽  
Geographic Information ◽  
Delivery Ratio ◽  
Sediment Discharge ◽  
Sediment Delivery Ratio ◽  
Sediment Delivery ◽  
Spatially Distributed

Spatially distributed sediment delivery (SEDD) models are of great interest in estimating the expected effect of changes on soil erosion and sediment yield. However, they can only be applied if the model can be calibrated using observed data. This paper presents a geographic information system (GIS)-based method to calculate the sediment discharge from basins to coastal areas. For this, an SEDD model, with a sediment rating curve method based on observed data, is proposed and validated. The model proposed here has been developed using the combined application of the revised universal soil loss equation (RUSLE) and a spatially distributed sediment delivery ratio, within Model Builder of ArcGIS's software. The model focuses on spatial variability and is useful for estimating the spatial patterns of soil loss and sediment discharge. The model consists of two modules, a soil erosion prediction component and a sediment delivery model. The integrated approach allows for relatively practical and cost-effective estimation of spatially distributed soil erosion and sediment delivery, for gauged or ungauged basins. This paper provides the first attempt at estimating sediment delivery ratio based on observed data in the monsoon region of Korea.

scholarly journals Comparing watershed soil erosion of Taiwan and Thailand

2018 ◽  
Vol 192 ◽  
pp. 02041
Author(s):  
Yi-Hsin Liu ◽  
Kieu Anh Nguyen ◽  
Walter Chen ◽  
Jatuwat Wattanasetpong ◽  
Uma Seeboonruang
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Soil Erodibility ◽  
Erosion Model ◽  
Shihmen Reservoir ◽  
Soil Erodibility Factor ◽  
Tropical Watersheds ◽  
Reservoir Watershed ◽  
Soil Loss Equation ◽  
Steepness Factor

Tropical watersheds in Taiwan and Thailand face the same severe soil erosion problem that is increasing at an alarming rate. In order to evaluate the severity of soil erosion, we quantitatively investigate the issue using a common soil erosion model (Universal Soil Loss Equation, USLE) on the Shihmen reservoir watershed of Taiwan and the Lam Phra Ploeng basin of Thailand, and compare their respective erosion factors. The results show an interesting contrast between the two watersheds. Some of the factors (rainfall factor, slope-steepness factor) are higher in the Shihmen reservoir watershed, while others (soil erodibility factor, cover and management factor) are higher in the Lam Phra Ploeng basin. The net result is that these factors cancel each other out, and the amount of soil erosion of the two watersheds are very similar at 68.03 t/ha/yr and 67.57 t/ha/yr, respectively.

scholarly journals Predicting Sheet and Rill Erosion of Shihmen Reservoir Watershed in Taiwan Using Machine Learning

2019 ◽  
Vol 11 (13) ◽  
pp. 3615 ◽  
Author(s):  
Kieu Anh Nguyen ◽  
Walter Chen ◽  
Bor-Shiun Lin ◽  
Uma Seeboonruang ◽  
Kent Thomas
Keyword(s):  
Random Forest ◽  
Soil Erosion ◽  
Random Sampling ◽  
Training Data ◽  
Stratified Random Sampling ◽  
Rill Erosion ◽  
Random Forest Algorithm ◽  
Testing Data ◽  
Shihmen Reservoir ◽  
Reservoir Watershed

Shihmen Reservoir watershed is vital to the water supply in Northern Taiwan but the reservoir has been heavily impacted by sedimentation and soil erosion since 1964. The purpose of this study was to explore the capability of machine learning algorithms, such as decision tree and random forest, to predict soil erosion (sheet and rill erosion) depths in the Shihmen reservoir watershed. The accuracy of the models was evaluated using the RMSE (Root Mean Squared Error), MAE (Mean Absolute Error), and R2. Moreover, the models were verified against the multiple regression analysis, which is commonly used in statistical analysis. The predictors of these models were 14 environmental factors which influence soil erosion, whereas the target was 550 erosion pins installed at 55 locations (on 55 slopes) and monitored over a period of approximately three years. The data sets for the models were separated into 70% for the training data and 30% for the testing data, using the simple random sampling and stratified random sampling methods. The results show that the random forest algorithm performed the best of the three methods. Moreover, the stratified random sampling method had better results among the two sampling methods, as anticipated. The average error (RMSE relative to 1:1 line) of the stratified random sampling method of the random forest algorithm is 0.93 mm/yr in the training data and 1.75 mm/yr in the testing data, respectively. Finally, the random forest algorithm predicted that type of slope, slope direction, and sub-watershed are the three most important factors of the 14 environmental factors collected and used in this study for splits in the trees and thus they are the three most important factors affecting the depth of sheet and rill erosion in the Shihmen Reservoir watershed. The results of this study can be employed by decision-makers to improve soil conservation planning and watershed remediation.

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