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Journal articles on the topic 'Shimen Reservoir'

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Published: 4 June 2021
Last updated: 4 March 2023

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1

Chen, Li-Yu, Wen-Zhe Hsieh, and Rung-Jiun Chou. "The Impact of the Construction of Large Reservoirs on the Cultural Landscape: A Case Study of the Shimen Reservoir, Taiwan." Land 10, no. 11 (October 29, 2021): 1161. http://dx.doi.org/10.3390/land10111161.

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Reservoirs are large-scale water facilities with multiple functions, such as water supply, power generation, and tourism. This paper introduces the new community and cultural landscape formed by the indigenous people, engineers, workers who left their homes, and many migrating families at the Shimen Reservoir in Taoyuan, Taiwan, as an example. We analyzed how the community value of reservoir construction contributed to the development of the landscape through fieldwork, document review, and in-depth interviews. First, the new communities created to meet the needs of the immigrants influenced the surrounding environment and shaped a particular lifestyle. Secondly, new immigrants have formed a community consensus, and changes in the diet and natural landscape have promoted local tourism and affected the function of the reservoir. This study concludes that promoting local values through autonomous community action is a sustainable approach to community development. Tourism development with its symbiotic relationship with the reservoir can meet the needs of local socio-economic and cultural development. For sustainable development, a vulnerability study based on the Shimen Reservoir tourism is necessary.
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2

Hung, Cheng-Wei, and Lin-Han Chiang Hsieh. "Analysis of Factors Influencing the Trophic State of Drinking Water Reservoirs in Taiwan." Water 13, no. 22 (November 14, 2021): 3228. http://dx.doi.org/10.3390/w13223228.

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Eutrophication is an environmental pollution problem that occurs in natural water bodies. Regression analyses with interaction terms are carried out to identify the factors influencing the Shimen, Mingde, and Fongshan Reservoirs in Taiwan. The results indicate that the main factor influencing these reservoirs is total phosphorus. In the Shimen and Mingde Reservoirs, the influence of total phosphorus, when interacting with other factors, on water quality trophic state is more serious than that of total phosphorus per se. This implies that the actual influence of total phosphorus on the eutrophic condition could be underestimated. Furthermore, there was no deterministic causality between climate and water quality variables. In addition, time lagged effects, or the influence of their interaction with other variables, were considered separately in this study to further determine the actual relationships between water trophic state and influencing factors. The influencing patterns for three reservoirs are different, because the type, size, and background environment of each reservoir are different. This is as expected, since it is difficult to predict eutrophication in reservoirs with a universal index or equation. However, the multiple linear regression model used in this study could be a suitable quick-to-use, case-by-case model option for this problem.
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3

Liou, Yuei-An, Tai-Sheng Wang, and Hai-Po Chan. "Impacts of Pond Change on the Regional Sustainability of Water Resources in Taoyuan, Taiwan." Advances in Meteorology 2013 (2013): 1–6. http://dx.doi.org/10.1155/2013/243456.

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Taoyuan tableland faces the increasing water demand associated with the expansion of industrialization and urbanization. The county currently relies on the Shihmen Reservoir as the single water supply system. It will be of great concern in the shortage of water resources. This study aims to explore the impact of changes in farm ponds on the regional agricultural environment in Taoyuan County with multiyear (1993, 2003, and 2010) SPOT satellite imagery. Results show that farm ponds have decreased by 10.55 million m2from 1993 to 2010, and the existing farm ponds were 18.80 million m2in 2010, equivalent to the irrigation water of 21.10~31.65 million m3(tons) and 37.61~56.41 million m3(tons), respectively. The existing farm ponds are able to provide the water supply for 1.88~2.82 thousand hectares of agricultural land, accounting for 6.70%~10.50% of total agricultural area of Taoyuan County. Corresponding to the government’s promotion policy (2012) on activating fallow land, if we redeploy the existing farm ponds for activating fallow fields, it will lessen the water supply burden of Shimen Reservoir. Thus, farm ponds remain the significant water facilities. For the sustainable agriculture, farm ponds shall be classified and cherished as a public asset for the future development.
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4

Yang, Jun-He, Ching-Hsue Cheng, and Chia-Pan Chan. "A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method." Computational Intelligence and Neuroscience 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/8734214.

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Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir’s water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir’s water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.
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5

Zhang, Di. "Numerical Simulation Analysis for Foundation Settlement Sensitivity on LiShuiGou Aqueduct of ShiMen Reservoir." Applied Mechanics and Materials 71-78 (July 2011): 1601–4. http://dx.doi.org/10.4028/www.scientific.net/amm.71-78.1601.

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The foundation of LiShuiGou Aqueduct of ShiMen Reservoir is composed of long-short and large diameter piles, with great diameter and length differences between these new and old piles. Numerical simulation of the FEM software ADINA and the orthogonal experimental design theory are applied to explore the sensitivity of long-short pile foundation settlement, under different pile length, pile diameter, pile space, and soil constitutive model, with foundation settlement as the evaluation index. The results show that the descending order of the sensitivity of four factors is: pile length > pile diameter > pile space > soil constitutive mode. Some scientific and rational approaches and basis are consequently provided to explore the most effective reinforcement measures and design method for long-short and large diameter piles.
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6

Huang, Cheng-Chia, Yong G. Lai, Jihn-Sung Lai, and Yih-Chi Tan. "Field and Numerical Modeling Study of Turbidity Current in Shimen Reservoir during Typhoon Events." Journal of Hydraulic Engineering 145, no. 5 (May 2019): 05019003. http://dx.doi.org/10.1061/(asce)hy.1943-7900.0001590.

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7

Lai, J. S., and F. Tsai. "VERIFICATION AND RISK ASSESSMENT FOR LANDSLIDES IN THE SHIMEN RESERVOIR WATERSHED OF TAIWAN USING SPATIAL ANALYSIS AND DATA MINING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXIX-B2 (July 25, 2012): 67–70. http://dx.doi.org/10.5194/isprsarchives-xxxix-b2-67-2012.

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8

Lin, Tzu-Hui. "Ponds of landuse in Yangmei District and Pingzhen District, Taoyuan City, Taiwan." Abstracts of the ICA 1 (July 15, 2019): 1. http://dx.doi.org/10.5194/ica-abs-1-218-2019.

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<p><strong>Abstract.</strong> The purpose of this study is to explore the land use of the pond in Taoyuan where located in north Taiwan. Apply ponds to gather water to irrigate the paddy field is a special landscape in this area. In this study, six maps from 1921 to 2015 were selected to digitize the change of the landuse, and intersection, erase analysis functions of GIS were used to show the growth and decline process of ponds, combined with literature analysis to discuss the background of the landuse development. The results reveal that from 1921 to 1989, 91% ponds were converted to paddy field. In 1989 to 1993, only 68% paddy fields and 30% settlements exist. The reasons for the conversion of ponds to paddy field were the construction of Shimen Reservoir in that time led to decline people’s willingness to use the pond to irrigate; the reason for the increase in settlements was the increase in population. This study proved that the growth and decline of pond was absolutely related to human interaction, and has an absolute impact on agricultural use in all days.</p>
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9

Huang, Chien-Lin, Nien-Sheng Hsu, Chih-Chiang Wei, and Chun-Wen Lo. "Using Artificial Intelligence to Retrieve the Optimal Parameters and Structures of Adaptive Network-Based Fuzzy Inference System for Typhoon Precipitation Forecast Modeling." Advances in Meteorology 2015 (2015): 1–22. http://dx.doi.org/10.1155/2015/472523.

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This study aims to construct a typhoon precipitation forecast model providing forecasts one to six hours in advance using optimal model parameters and structures retrieved from a combination of the adaptive network-based fuzzy inference system (ANFIS) and artificial intelligence. To enhance the accuracy of the precipitation forecast, two structures were then used to establish the precipitation forecast model for a specific lead-time: a single-model structure and a dual-model hybrid structure where the forecast models of higher and lower precipitation were integrated. In order to rapidly, automatically, and accurately retrieve the optimal parameters and structures of the ANFIS-based precipitation forecast model, a tabu search was applied to identify the adjacent radius in subtractive clustering when constructing the ANFIS structure. The coupled structure was also employed to establish a precipitation forecast model across short and long lead-times in order to improve the accuracy of long-term precipitation forecasts. The study area is the Shimen Reservoir, and the analyzed period is from 2001 to 2009. Results showed that the optimal initial ANFIS parameters selected by the tabu search, combined with the dual-model hybrid method and the coupled structure, provided the favors in computation efficiency and high-reliability predictions in typhoon precipitation forecasts regarding short to long lead-time forecasting horizons.
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10

Tseng, Chao-Heng, Ling-Ling Chen, Hsing-Cheng Hsi, and Meng-Chu Lee. "Modeling of exposure to mercury in different environmental media over a 30-year period: A case study of Shimen reservoir, northern Taiwan." Human and Ecological Risk Assessment: An International Journal 26, no. 5 (March 1, 2019): 1379–90. http://dx.doi.org/10.1080/10807039.2019.1579047.

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11

Huang, Lingzhi, Shouyi Li, and Zheng Si. "Research on the dynamic control of the flood control level of Shimen Reservoir in the mode of pre-storage and pre-discharge regulation." IOP Conference Series: Earth and Environmental Science 128 (March 2018): 012012. http://dx.doi.org/10.1088/1755-1315/128/1/012012.

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12

Liu, Wen-Cheng, Wei-Che Huang, and Chih-Chieh Young. "Uncertainty Analysis for Image-Based Streamflow Measurement: The Influence of Ground Control Points." Water 15, no. 1 (December 29, 2022): 123. http://dx.doi.org/10.3390/w15010123.

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Large-scale particle image velocimetry (LSPIV) provides a cost-effective, rapid, and secure monitoring tool for streamflow measurements. However, surveys of ground control points (GCPs) might affect the camera parameters through the solution of collinearity equations and then impose uncertainty on the measurement results. In this paper, we explore and present an uncertainty analysis for image-based streamflow measurements with the main focus on the ground control points. The study area was Yufeng Creek, which is upstream of the Shimen Reservoir in Northern Taiwan. A monitoring system with dual cameras was set up on the platform of a gauge station to measure the surface velocity. To evaluate the feasibility and accuracy of image-based LSPIV, a comparison with the conventional measurement using a flow meter was conducted. Furthermore, the degree of uncertainty in LSPIV streamflow measurements influenced by the ground control points was quantified using Monte Carlo simulation (MCS). Different operations (with survey times from one to nine) and standard errors (30 mm, 10 mm, and 3 mm) during GCP measurements were considered. Overall, the impacts in the case of single GCP measurement are apparent, i.e., a shifted and wider confidence interval. This uncertainty can be alleviated if the coordinates of the control points are measured and averaged with three repetitions. In terms of the standard errors, the degrees of uncertainty (i.e., normalized confidence intervals) in the streamflow measurement were 20.7%, 12.8%, and 10.7%. Given a smaller SE in GCPs, less uncertain estimations of the river surface velocity and streamflow from LSPIV could be obtained.
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13

Lee, Fong-Zuo, Jihn-Sung Lai, and Tetsuya Sumi. "Reservoir Sediment Management and Downstream River Impacts for Sustainable Water Resources—Case Study of Shihmen Reservoir." Water 14, no. 3 (February 6, 2022): 479. http://dx.doi.org/10.3390/w14030479.

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Sustainable water resources of reservoirs depend on preserving the valuable storage capacity. Sediment management is a crucial task in reservoir operations. Extreme floods caused by typhoon events have brought a massive amount of sediments from the watershed of Shihmen Reservoir in Taiwan. In the case study of Shihmen Reservoir, the primary purpose of the sediment management strategies is to minimize sediment deposition and recover reservoir capacity. Two assessment indexes, the capacity–inflow ratio (CIR) and the capacity–sediment ratio (CSR) are investigated to provide a feasible assessment of desilting techniques. Three desilting projects have been planned and implemented in progress, including one modified power plant penstock and two desilting tunnels. Without effective sediment management strategies, the projected storage capacity may drop to 32.9% of the initial storage capacity in the next fifty years. On the other hand, if sediment management is implemented as per the project schedule, 70.3% of the initial storage capacity may be retained, enabling the provision of sustainable water supplies to meet projected water demands. In investigating the impacts caused by the desilting operations, the floodwater level and riverbed variations along the downstream river of the dam are simulated by the hydromorphological model. From simulated results, the downstream river morphology may adjust toward the equilibrium state under the long-term desilting operations of Shihmen Reservoir. Although relatively high sediment concentration is released during the desilting operation, it decays gradually along the downstream river. In addition, riverbed deposition does not significantly affect the floodwater level caused by the increment of riverbed elevation in desilting operations.
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14

Savira Agatha Putri, Marsha, Jr-Lin Lin, Lin-Han Chiang Hsieh, Yasmin Zafirah, Gerry Andhikaputra, and Yu-Chun Wang. "Influencing Factors Analysis of Taiwan Eutrophicated Reservoirs." Water 12, no. 5 (May 7, 2020): 1325. http://dx.doi.org/10.3390/w12051325.

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Treatment cost and quality of domestic water are highly correlated with raw water quality in reservoirs. This study aims to identify the key factors that influence the trophic state levels and correlations among Carlson trophic state index (CTSI) levels, water quality parameters and weather factors in four major reservoirs in Taiwan from 2000 to 2017. Weather (e.g., air temperature, relative humidity, total precipitation, sunlight percentage and cloud cover) and water quality parameters (e.g., pH, chemical oxygen demand, suspended solids (SS), ammonia, total hardness, nitrate, nitrite and water temperature) were included in the principal component analysis and absolute principal component score models to evaluate the main governing factors of the trophic state levels (e.g., CTSI). SS were washed out by precipitation, thereby influencing the reservoir transparency tremendously and contributing over 50% to the CTSI level in eutrophicated reservoirs (e.g., the Shihmen and Chengchinghu Reservoirs). CTSI levels in the mesotrophic reservoir (e.g., Liyutan Reservoir) had strong correlation with chlorophyll-a and total phosphorus. Results show that rainfall/weather factors were the key driving factors that affected the CTSI levels in Taiwan eutrophicated reservoirs, indicating the need to consider basin management and the impacts of extreme precipitation in reservoir management and future policymaking.
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15

Yang, Sheng-Chi, and Tsun-Hua Yang. "Uncertainty Assessment: Reservoir Inflow Forecasting with Ensemble Precipitation Forecasts and HEC-HMS." Advances in Meteorology 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/581756.

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During an extreme event, having accurate inflow forecasting with enough lead time helps reservoir operators decrease the impact of floods downstream. Furthermore, being able to efficiently operate reservoirs could help maximize flood protection while saving water for drier times of the year. This study combines ensemble quantitative precipitation forecasts and a hydrological model to provide a 3-day reservoir inflow in the Shihmen Reservoir, Taiwan. A total of six historical typhoons were used for model calibration, validation, and application. An understanding of cascaded uncertainties from the numerical weather model through the hydrological model is necessary for a better use for forecasting. This study thus conducted an assessment of forecast uncertainty on magnitude and timing of peak and cumulative inflows. It found that using the ensemble-mean had less uncertainty than randomly selecting individual member. The inflow forecasts with shorter length of cumulative time had a higher uncertainty. The results showed that using the ensemble precipitation forecasts with the hydrological model would have the advantage of extra lead time and serve as a valuable reference for operating reservoirs.
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16

Kirichek, Alex, Katherine Cronin, Lynyrd de Wit, Ebi Meshkati, Johan Pennekamp, Arjan Wijdeveld, and Kees Sloff. "Water Injection Dredging for improving and preserving reservoir storage capacity: modelling and measuring tools." E3S Web of Conferences 346 (2022): 01021. http://dx.doi.org/10.1051/e3sconf/202234601021.

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Water Injection Dredging (WID) has been successfully applied for removing sediment deposits in reservoirs, which results in an increase of their storage capacity. This dredging method is based on the fluidization of the top sediment layer by pressurized injection of water by a dredging vessel. The fluidized sediment can be transported towards the dead storage of the reservoir or sluiced out of the reservoir through the bottom outlets of a dam. This flow can either occur by gravity induced flow or especially directed by the dredging strategy of the WID vessel. This dredging technique can increase the water storage capacity of the reservoir and prevent the erosion of the river downstream, hence the sediment blockage. Recent developments in modelling and measuring tools have enabled stakeholders to design, optimize and monitor WID in reservoirs. In this paper, we will demonstrate how modelling and measuring tools can be used to evaluate alternative dredging strategies for reservoir maintenance. In particular, we show how a mid-field and far-field modelling can be applied for designing WID actions and predicting sediment plume dynamics in a given reservoir. Additionally, we will present recently-developed in-situ measuring tools, that are currently used for monitoring turbidity in a water column and sediment properties during and after WID actions. Finally, potential benefit of applying WID in Shihmen Reservoir (Taiwan) is discussed.
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17

Liu, W. C., H. H. Chen, W. H. Hsieh, and C. H. Chang. "Linking watershed and eutrophication modelling for the Shihmen Reservoir, Taiwan." Water Science and Technology 54, no. 11-12 (December 1, 2006): 39–46. http://dx.doi.org/10.2166/wst.2006.834.

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The Shihmen Reservoir, located in northern Taiwan, features the second storage volume of impoundments on the island. The watershed of the Shihmen Reservoir has been subjected to serious pollutants due to anthropogenic interference. This study applies a watershed model, BASINS, to simulate the flow and nutrients loads from the watershed. BASINS then drives the CE-QUAL-W2 model for water quality predictions in the reservoir. The watershed modelling results are compared with field data. They reveal that significant nutrient loads were generated from the watershed during storms. The model calibration and verification were achieved with water surface elevation, temperature, and water quality constituents including nutrients, dissolved oxygen, and chlorophyll a in the reservoir using the eutrophication model.
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18

Chou, F. N. F., and C. W. Wu. "Determination of cost coefficients of a priority-based water allocation linear programming model – a network flow approach." Hydrology and Earth System Sciences 18, no. 5 (May 21, 2014): 1857–72. http://dx.doi.org/10.5194/hess-18-1857-2014.

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Abstract. This paper presents a method to establish the objective function of a network flow programming model for simulating river–reservoir system operations and associated water allocation, with an emphasis on situations when the links other than demand or storage have to be assigned with nonzero cost coefficients. The method preserves the priorities defined by rule curves of reservoir, operational preferences for conveying water, allocation of storage among multiple reservoirs, and transbasin water diversions. Path enumeration analysis transforms these water allocation rules into linear constraints that can be solved to determine link cost coefficients. An approach to prune the original system into a reduced network is proposed to establish the precise constraints of nonzero cost coefficients, which can then be efficiently solved. The cost coefficients for the water allocation in the Feitsui and Shihmen reservoirs' joint operating system of northern Taiwan was adequately assigned by the proposed method. This case study demonstrates how practitioners can correctly utilize network-flow-based models to allocate water supply throughout complex systems that are subject to strict operating rules.
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19

Chou, F. N. F., and C. W. Wu. "Determination of cost coefficients of priority-based water allocation linear programming model – a network flow approach." Hydrology and Earth System Sciences Discussions 10, no. 12 (December 10, 2013): 15033–70. http://dx.doi.org/10.5194/hessd-10-15033-2013.

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Abstract. This paper presents a method to establish the objective function of a network flow programming model for simulating river/reservoir system operations and associated water allocation, with an emphasis on situations when the links other than demand or storage have to be assigned with nonzero cost coefficients. The method preserves the priorities defined by rule curves of reservoir, operational preferences for conveying water, allocation of storage among multiple reservoirs, and trans-basin water diversions. Path enumeration analysis transforms these water allocation rules into linear constraints that can be solved to determine link cost coefficients. An approach to prune the original system into a reduced network is proposed to establish the precise constraints of nonzero cost coefficients which can then be efficiently solved. The cost coefficients for the water allocation in the Feitsui and Shihmen Reservoirs joint operating system of northern Taiwan was adequately assigned by the proposed method. This case study demonstrates how practitioners can correctly utilize network-flow-based models to allocate water supply throughout complex systems that are subject to strict operating rules.
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20

Wu, Ray-Shyan, Wen-Cheng Liu, and Wen-Hsiung Hsieh. "Eutrophication Modeling in Shihmen Reservoir, Taiwan." Journal of Environmental Science and Health, Part A 39, no. 6 (December 27, 2004): 1455–77. http://dx.doi.org/10.1081/ese-120037846.

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21

Thomas, Kent, Walter Chen, Bor-Shiun Lin, and Uma Seeboonruang. "Evaluation of the SEdiment Delivery Distributed (SEDD) Model in the Shihmen Reservoir Watershed." Sustainability 12, no. 15 (August 2, 2020): 6221. http://dx.doi.org/10.3390/su12156221.

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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.
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22

Lin, Bor-Shiun, Chun-Kai Chen, Kent Thomas, Chen-Kun Hsu, and Hsing-Chuan Ho. "Improvement of the K-Factor of USLE and Soil Erosion Estimation in Shihmen Reservoir Watershed." Sustainability 11, no. 2 (January 11, 2019): 355. http://dx.doi.org/10.3390/su11020355.

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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.
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23

Liu, Yi-Hsin, Kieu Anh Nguyen, Walter Chen, Jatuwat Wattanasetpong, and Uma Seeboonruang. "Comparing watershed soil erosion of Taiwan and Thailand." MATEC Web of Conferences 192 (2018): 02041. http://dx.doi.org/10.1051/matecconf/201819202041.

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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.
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Nguyen, Kieu Anh, Walter Chen, Bor-Shiun Lin, Uma Seeboonruang, and Kent Thomas. "Predicting Sheet and Rill Erosion of Shihmen Reservoir Watershed in Taiwan Using Machine Learning." Sustainability 11, no. 13 (July 1, 2019): 3615. http://dx.doi.org/10.3390/su11133615.

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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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25

Lo, Kwong Fai A. "Quantifying soil erosion for the Shihmen reservoir watershed, Taiwan." Agricultural Systems 45, no. 1 (January 1994): 105–16. http://dx.doi.org/10.1016/s0308-521x(94)90283-6.

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Liu, Yi-Hsin, Dong-Huang Li, Walter Chen, Bor-Shiun Lin, Uma Seeboonruang, and Fuan Tsai. "Soil Erosion Modeling and Comparison Using Slope Units and Grid Cells in Shihmen Reservoir Watershed in Northern Taiwan." Water 10, no. 10 (October 3, 2018): 1387. http://dx.doi.org/10.3390/w10101387.

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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.
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Hu, Ming-Che, Chihhao Fan, Tailin Huang, Chi-Fang Wang, and Yu-Hui Chen. "Urban Metabolic Analysis of a Food-Water-Energy System for Sustainable Resources Management." International Journal of Environmental Research and Public Health 16, no. 1 (December 30, 2018): 90. http://dx.doi.org/10.3390/ijerph16010090.

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Urban metabolism analyzes the supply and consumption of nutrition, material, energy, and other resources within cities. Food, water, and energy are critical resources for the human society and have complicated cooperative/competitive influences on each other. The management of interactive resources is essential for supply chain analysis. This research analyzes the food-water-energy system of urban metabolism for sustainable resources management. A system dynamics model is established to investigate the urban metabolism of food, water, and energy resources. This study conducts a case study of Shihmen Reservoir system, hydropower generation, paddy rice irrigation of Taoyuan and Shihmen Irrigation Associations, and water consumption in Taoyuan, New Taipei, and Hsinchu cities. The interactive influence of the food-water-energy nexus is quantified in this study; the uncertainty analysis of food, water, and energy nexus is presented.
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Hwang, Ji-Sen. "Eradication ofSolenopsis invictaby pyriproxyfen at the Shihmen Reservoir in northern Taiwan." Insect Science 16, no. 6 (December 2009): 493–501. http://dx.doi.org/10.1111/j.1744-7917.2009.01279.x.

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Chen, Yi-Chin, Ying-Hsin Wu, Che-Wei Shen, and Yu-Jia Chiu. "Dynamic Modeling of Sediment Budget in Shihmen Reservoir Watershed in Taiwan." Water 10, no. 12 (December 8, 2018): 1808. http://dx.doi.org/10.3390/w10121808.

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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.
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Wei, Chih-Chiang. "Wavelet Support Vector Machines for Forecasting Precipitation in Tropical Cyclones: Comparisons with GSVM, Regression, and MM5." Weather and Forecasting 27, no. 2 (April 1, 2012): 438–50. http://dx.doi.org/10.1175/waf-d-11-00004.1.

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Abstract This study presents two support vector machine (SVM) based models for forecasting hourly precipitation during tropical cyclone (typhoon) events. The two SVM-based models are the traditional Gaussian kernel SVMs (GSVMs) and the advanced wavelet kernel SVMs (WSVMs). A comparison between the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) and statistical models, including SVM-based models and linear regressions (regression), was made in terms of performance of rainfall prediction at the Shihmen Reservoir watershed in Taiwan. Data from 73 typhoons affecting the Shihmen Reservoir watershed were included in the analysis. This study designed six attribute combinations with different lag times for the forecast target. The modified RMSE, bias, and estimated threat score (ETS) results were employed to assess the predicted outcomes. Results show that better attribute combinations for typhoon climatologic characteristics and typhoon precipitation predictions occurred at 0-h lag time with modified RMSE values of 0.288, 0.257, and 0.296 in GSVM, WSVM, and the regression, respectively. Moreover, WSVM having average bias and ETS values close to 1.0 gave better predictions than did the GSVM and regression models. In addition, Typhoons Zeb (1998) and Nari (2001) were selected for comparison between the MM5 model output and the developed statistical models. Results showed that the MM5 tended to overestimate the peak and cumulative rainfall amounts while the statistical models were inclined to yield underestimations.
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31

Lee, Lai, Guo, and Sumi. "Scouring of Replenished Sediment through Reservoir Flood Discharge Affects Suspended Sediment Concentrations at Downstream River Water Intake." Water 11, no. 10 (September 25, 2019): 1998. http://dx.doi.org/10.3390/w11101998.

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Dredging is a commonly used sedimentation management strategy to remove mechanically deposited sediment from reservoirs. However, dredged sediment disposal is costly. Dredged sediment can be considered a beneficial resource and used for riverbed replenishment to prevent downstream riverbed degradation and improve aquatic habitats. This study investigated the feasibility of using dredged deposits with cohesive sediment for replenishment at the Shihmen Reservoir. Using the criterion of critical scour velocity, we conducted hydraulic assessments and identified the feasible replenishment area as the experimental domain. A physical model was developed to mimic the scouring process in the replenishment area. By applying dynamic similarity for scouring fine replenished sediment, we derived the regression relationship between flow-critical velocity and sediment-dry density, and used it for model ratio scaling of the grain size, dry density, and concentration in the physical model. Scoured sediment concentrations were measured to study the scour ratio at various flood discharges. Experimental results indicated that the scour ratio was related to factors such as flood discharge, flood duration, and water content of the replenished sediment. The reduction ratio of the concentration of sediment scoured from the replenishment area to the concentration of sediment at the downstream water intake was approximately 90% in the present study.
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32

Anh Nguyen, Kieu, and Walter Chen. "Estimating sediment delivery ratio by stream slope and relief ratio." MATEC Web of Conferences 192 (2018): 02040. http://dx.doi.org/10.1051/matecconf/201819202040.

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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.
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33

Wang, K. H., J. C. Yang, and C. H. Wu. "3D Modeling of Flood Induced Flows and Sediment Concentration in Shihmen Reservoir." Journal of Coastal Research 10052 (November 2008): 71–78. http://dx.doi.org/10.2112/1551-5036-52.sp1.71.

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34

Tsai, Zong-Xian, Gene J. Y. You, Hong-Yuan Lee, and Yu-Jia Chiu. "Modeling the sediment yield from landslides in the Shihmen Reservoir watershed, Taiwan." Earth Surface Processes and Landforms 38, no. 7 (September 7, 2012): 661–74. http://dx.doi.org/10.1002/esp.3309.

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35

Liu, Hou-Chun, Chen-Feng You, Chuan-Hsiung Chung, Kuo-Fang Huang, and Zhi-Fei Liu. "Source variability of sediments in the Shihmen Reservoir, Northern Taiwan: Sr isotopic evidence." Journal of Asian Earth Sciences 41, no. 3 (May 2011): 297–306. http://dx.doi.org/10.1016/j.jseaes.2011.02.013.

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36

Hsieh, Tung-Chou, Yan Ding, Keh-Chia Yeh, and Ren-Kai Jhong. "Numerical Investigation of Sediment Flushing and Morphological Changes in Tamsui River Estuary through Monsoons and Typhoons." Water 14, no. 11 (June 2, 2022): 1802. http://dx.doi.org/10.3390/w14111802.

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The removal of reservoir silt and the restoration of existing reservoir capacities through land excavation and hydraulic sediment flushing have become necessary. Hydraulic sediment flushing discharge changes flow and sediment conditions of the downstream river channel. In the Tamsui River estuary in Taiwan, sediment flushing from the Shihmen reservoir upstream has potential impacts on the morphology of the navigation channels and the adjacent coasts. This study employed a validated coastal and estuarine processes model to investigate: (1) the influence of sediment flushing and tidal levels on morphological changes during flood and flushing-discharge operations of the reservoir, and (2) the differences in morphological changes on the estuary between monsoon and typhoon seasons. The prediction of the morphological changes was carried out by simulating hydrodynamic and morphodynamic processes under multi-year synthetic conditions combined by northeast monsoon and three historical typhoon events. The simulation results reveal that during the operation of sediment flushing when the peak discharge of river flood flow reaches the estuary section at ebb tides, more sediment can be transported to the open sea than that at flood tides. Additionally, the nature reserve area on the left bank of the estuary is eroded during monsoon and silted in typhoon seasons.
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37

Zhang, Kuihua, Yarong Wang, Guanlong Zhang, Tao Xu, Wei Xiong, Shengzhu Wang, Ji Ma, and Tingbin Sun. "Discovery of Seismites in the Carboniferous Formation of the Shibei Sag (China) and Its Petroleum Geological Significance." Minerals 12, no. 12 (December 2, 2022): 1560. http://dx.doi.org/10.3390/min12121560.

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To promote oil and gas exploration of the Carboniferous formation in the Shibei sag, the northeastern margin of Junggar Basin, recently drilled rocks from Well ZB6 with typical seismics were characterized. Through systematic core observation, the identification marks of seismites were described, a vertical sequence of seismites was established, and its oil and gas geological significance was analyzed. The results show that the seismites have typical identification marks, such as soft-sediment deformation structures (including five typical marks: liquefied stone vein, liquefied crinkled deformation structure, ball–pillow structure, flame structure and load cast, water release structure and liquefied breccia), brittle fracture structures (including three typical marks: seismic fractures, synsedimentary microfractures and seismic fracture rock) and special rock types, such as seismic grain-supported conglomerates. The stratigraphic succession reconstructed in Well ZB6 was characterized, from base to top, by (1) a basal non-seismic interval; (2) a seismic interval made up of a grain-supported conglomerate level, brittle fracture level, soft-sediment deformation level; and (3) a non-seismic interval. The discovery of seismites has oil and gas geological significance for improving reservoir performance and forming favorable source–reservoir–cap assemblages. The research describes the new reservoir genetic type and exploration direction of the Carboniferous formation in the Shibei sag (China), which has important guiding significance for the next step of oil and gas exploration.
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38

Chang, Chiwen, and Wenrui Huang. "Hydrological modeling of typhoon-induced extreme storm runoffs from Shihmen watershed to reservoir, Taiwan." Natural Hazards 67, no. 2 (February 21, 2013): 747–61. http://dx.doi.org/10.1007/s11069-013-0600-7.

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39

Liu, Wen-Cheng, Ray-Shyan Wu, Edward Ming-Yang Wu, Yu-Pei Chang, and Wei-Bo Chen. "Using water quality variables to predict light attenuation coefficient: case study in Shihmen Reservoir." Paddy and Water Environment 8, no. 3 (April 20, 2010): 267–75. http://dx.doi.org/10.1007/s10333-010-0207-5.

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40

Huang, Chuen-Ming, Chyi-Tyi Lee, Liu-Xuan Jian, Lun-Wei Wei, Wei-Chia Chu, and Hsi-Hung Lin. "Using Fuzzy Neural Networks to Model Landslide Susceptibility at the Shihmen Reservoir Catchment in Taiwan." Water 14, no. 8 (April 8, 2022): 1196. http://dx.doi.org/10.3390/w14081196.

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Machine learning algorithms are commonly employed in landslide susceptibility assessments. Recently, algorithms that utilize artificial intelligence have come into prominence. This study attempts to adapt the most fundamental framework of deep learning and introduces fuzzy theory concepts to analyze landslide susceptibility while updating the network parameters with trial-and-error methods. The final analysis results will compare with those of logistic regression (LR). In order to assess the ability of the model to identify landslides in a more objective way, two typhoon events were used as a training event and a validation event, respectively. The results of the analysis show that the area under the curve (AUC) of the fuzzy neural network (FNN) for the training event is 0.915, but the AUC for the validation event drops to 0.746. Although the results of the FNN for training events were better than those of LR, they did not differ much from those of LR in predicting future events. The reason for this is that the difference between the landslide distributions of the training and validation events is too large, making the model biased in its identification. Overall, FNN is still a recommended method for analyzing landslide potential and can be used as a reference for LR.
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41

Liu, Wen-wen, Enmin Zhao, Yi-Ming Kuo, and Cheng-Shin Jang. "Identifying the relationships between trophic states and their driving factors in the Shihmen Reservoir, Taiwan." Limnologica 64 (May 2017): 38–45. http://dx.doi.org/10.1016/j.limno.2017.04.004.

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42

Shiau, J. T. "Water Release Policy Effects on the Shortage Characteristics for the Shihmen Reservoir System during Droughts." Water Resources Management 17, no. 6 (December 2003): 463–80. http://dx.doi.org/10.1023/b:warm.0000004958.93250.8a.

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43

Li, Pei-Hao, Hyun-Han Kwon, Liqiang Sun, Upmanu Lall, and Jehng-Jung Kao. "A modified support vector machine based prediction model on streamflow at the Shihmen Reservoir, Taiwan." International Journal of Climatology 30, no. 8 (May 12, 2009): 1256–68. http://dx.doi.org/10.1002/joc.1954.

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44

Chen, How Ji, Wen Po Tsai, and Ming Der Yang. "Time-Dependent Properties of Lightweight Concrete Using Sedimentary Lightweight Aggregate." Advanced Materials Research 168-170 (December 2010): 2235–40. http://dx.doi.org/10.4028/www.scientific.net/amr.168-170.2235.

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A kind of lightweight aggregate (LWA) has been successfully developed in Taiwan, which was made by expanding under heat fine sediments dredged from the Shihmen Reservoir. In this study the performances of concrete made from the aforementioned LWA were tested and compared with those of the companion normal weight concrete (NC). The test results show that the so produced lightweight concrete (LWAC) exhibited a comparable time-dependent properties (i.e., compressive strength, elastic modulus, drying shrinkage, and creep) as compared with those of the companion NC. Based on the results, it can be concluded that the use of prewetted LWAs and the incorporation of pozzolan materials can effectively control the drying shrinkage of LWAC. The specific creep of the LC mixture was obviously higher than that of the NC mixture at the same curing time.
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45

CHANG, Chia-Ling, Ying-Sung HSU, Bing-Jean LEE, Chuan-Yi WANG, and Li-Jung WENG. "A cost-benefit analysis for the implementation of riparian buffer strips in the Shihmen reservoir watershed." International Journal of Sediment Research 26, no. 3 (September 2011): 395–401. http://dx.doi.org/10.1016/s1001-6279(11)60103-0.

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46

Yang, Ming-Der, Yeh-Fen Yang, Tung-Ching Su, and Kai-Siang Huang. "An Efficient Fitness Function in Genetic Algorithm Classifier for Landuse Recognition on Satellite Images." Scientific World Journal 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/264512.

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Genetic algorithm (GA) is designed to search the optimal solution via weeding out the worse gene strings based on a fitness function. GA had demonstrated effectiveness in solving the problems of unsupervised image classification, one of the optimization problems in a large domain. Many indices or hybrid algorithms as a fitness function in a GA classifier are built to improve the classification accuracy. This paper proposes a new index, DBFCMI, by integrating two common indices, DBI and FCMI, in a GA classifier to improve the accuracy and robustness of classification. For the purpose of testing and verifying DBFCMI, well-known indices such as DBI, FCMI, and PASI are employed as well for comparison. A SPOT-5 satellite image in a partial watershed of Shihmen reservoir is adopted as the examined material for landuse classification. As a result, DBFCMI acquires higher overall accuracy and robustness than the rest indices in unsupervised classification.
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47

Bojang, Pa Ousman, Tao-Chang Yang, Quoc Bao Pham, and Pao-Shan Yu. "Linking Singular Spectrum Analysis and Machine Learning for Monthly Rainfall Forecasting." Applied Sciences 10, no. 9 (May 6, 2020): 3224. http://dx.doi.org/10.3390/app10093224.

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Monthly rainfall forecasts can be translated into monthly runoff predictions that could support water resources planning and management activities. Therefore, development of monthly rainfall forecasting models in reservoir watersheds is essential for generating future rainfall amounts as an input to a water-resources-system simulation model to predict water shortage conditions. This research aims to examine the reliability of linking a data preprocessing method (singular spectrum analysis, SSA) with machine learning, least-squares support vector regression (LS-SVR), and random forest (RF), for monthly rainfall forecasting in two reservoir watersheds (Deji and Shihmen reservoir watersheds) located in Taiwan. Merging SSA with LS-SVR and RF, the hybrid models (SSA-LSSVR and SSA-RF) were developed and compared with the standard models (LS-SVR and RF). The proposed models were calibrated and validated using the watersheds’ observed areal monthly rainfalls separated into 70 percent of data for calibration and 30 percent of data for validation. Model performances were evaluated using two accuracy measures, root mean square error (RMSE) and Nash–Sutcliffe efficiency (NSE). Results show that the hybrid models could efficiently forecast monthly rainfalls. Nonetheless, the performances of the hybrid models vary in both watersheds which suggests that prior knowledge about the watershed’s hydrological behavior would be helpful to implement the appropriate model. Overall, the hybrid models significantly surpass the standard models for the two studied watersheds, which indicates that the proposed models are a prudent modeling approach that could be employed in the current research regions for monthly rainfall forecasting.
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Chiu, Yu-Jia, Hong-Yuan Lee, Tse-Lin Wang, Junyang Yu, Ying-Tien Lin, and Yeping Yuan. "Modeling Sediment Yields and Stream Stability Due to Sediment-Related Disaster in Shihmen Reservoir Watershed in Taiwan." Water 11, no. 2 (February 15, 2019): 332. http://dx.doi.org/10.3390/w11020332.

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Accurate and reliable estimates of sediment yields from a watershed and identification of unstable stream reaches due to sediment-related disaster are crucial for watershed management, disaster prevention, and hazard mitigation purposes. In this study, we added hydrodynamic and sediment transport modules in a recently developed model to estimate sediment yields and identify the unstable stream reaches in a large-scale watershed (> 100km2). The calibrated and verified models can well reproduce the flow discharge and sediment discharge at the study site, the Shihmen Reservoir Watershed in Taiwan, during several typhoon events. For the scenario applications, the results revealed that the contribution (> 96%) of landslides on sediment supply is much more significant than compared to soil erosion (< 4%). The sediment contribution from the upstream of the hydrological station-Yufeng is approximately 36–55% of the total sediment supply for the rainfall events of 25, 50, 100, and 200 years return period. It also indicates that 22–52% of sediment still remain at foot of the slope and the streams, which become a potential source for sediment hazards in the future. Combining with the bed erosion and deposition depths, flow-induced shear stress from the SRH-2D model, and probability of slope failure within 250 m of stream reaches, the relatively stability of stream reaches can be identified. The results could provide the water resource authorities for reference to take precautionary measures in advance on the stream reaches with high-degree instability.
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Hsieh, Tung-Chou, Yan Ding, Keh-Chia Yeh, and Ren-Kai Jhong. "Investigation of Morphological Changes in the Tamsui River Estuary Using an Integrated Coastal and Estuarine Processes Model." Water 12, no. 4 (April 10, 2020): 1084. http://dx.doi.org/10.3390/w12041084.

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This study is to investigate morphological changes in the Tamsui River Estuary in Taiwan driven by multiple physical processes, such as river flows, tides, waves, and storm surges, and then to study the impacts of sediment flushing operated at the Shihmen reservoir upstream on the river estuary. An integrated coastal and estuarine processes model (CCHE2D-Coast) (Center for Computational Hydroscience and Engineering Two-Dimensional-Coast) was validated by simulating these physical processes in the estuary driven by three historical typhoons in 2008. The site-specifically validated model was then applied to simulate morphological changes in the estuary in response to reservoir sediment flush scenarios from the upstream. For the impact assessment of sediment flushing, a synthetic hydrological event was designed by including a historical typhoon and a typical monsoon. It was found that during the typhoon, the sediments will be mostly deposited in the estuarine river reach of Tamsui and the Wazihwei sandy beach. During the monsoon period, most of the sediments tend to be deposited in the second fishing port of Tamsui, the northern breakwater, and the estuary, while the Wazihwei sandy beach in the river mouth would be scoured by backflow. Simulations of the complex flow fields and morphological changes will facilitate the best practice of sediment management in the coastal and estuarine regions.
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Wei, Chih-Chiang. "RBF Neural Networks Combined with Principal Component Analysis Applied to Quantitative Precipitation Forecast for a Reservoir Watershed during Typhoon Periods." Journal of Hydrometeorology 13, no. 2 (April 1, 2012): 722–34. http://dx.doi.org/10.1175/jhm-d-11-03.1.

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Abstract The forecast of precipitations during typhoons has received much attention in recent years. It is important in meteorology and atmospheric sciences. Hence, the study on precipitation nowcast during typhoons is of great significance to operators of a reservoir system. This study developed an improved neural network that combines the principal component analysis (PCA) technique and the radial basis function (RBF) network. The developed methodology was employed to establish the quantitative precipitation forecast model for the watershed of the Shihmen Reservoir in northern Taiwan. The results obtained from RBF, multiple linear regression (MLR), PCA–RBF, and PCA–MLR models included the forecasts of L-ahead (L = 1, 3, 6) hourly accumulated precipitations. The deducted prediction results were compared in terms of four measures [mean absolute error (MAE), RMSE, coefficient of correlation (CC), and coefficient of efficiency (CE)] and four skill scores [percentage error (PE), area-weighted error score (AWES), bias score (BIAS), and equitable threat score (ETS)]. The results showed that predictions obtained using RBF and PCA–RBF were better than those produced by MLR and PCA–MLR. Although both RBF and PCA–RBF can provide good results on average, the network architecture and the learning speed of the PCA–RBF network are superior to those of the simple RBF network. This is because PCA technique could greatly reduce the input parameters and simplify concurrently the network structure. Consequently, the PCA–RBF neural networks can be regarded as a reliable model for predicting precipitation during typhoons.
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