The application of landslide-inventory based models for assessing sediment transport turbidity and landslide susceptibility management in the Gaoping River Basin Taiwan

Abstract

Landslides and sediment delivery processes in watersheds have become one of the greatest geological problems facing Southern Taiwan altering drainage patterns and increasing sediment delivery downstream The influx of landslide-related sediment input is especially important in drinking water designated watersheds as drinking water treatment plants are unable to operate during high turbidity events causing significant stoppages to water services for millions of residents Moreover typhoon-induced landslide hazards pose the greatest risk to property and life in Southern Taiwan This study examines the impacts of storm-triggered landslides on downstream sediment and turbidity responses in the Gaoping River Basin Taiwan using the Soil and Water Assessment Tool (SWAT) Attention is given to analyzing the increased and altered baseline of suspended sediment load and turbidity after the disturbances caused by the rainfall and landslides associated with Typhoon Morakot in 2009 The results show alterations in sediment erosion and transport: (1) drastically increased the turbidity baseline and occurrence of high-turbidity; (2) altered coefficient and exponent values of the sediment rating curve; and (3) altered relationship between rainfall and induced turbidity during major rainfall events The research in this study provides an improved modeling approach to typhoon-induced alterations on river sediment loads and turbidity To assess landslide probability the identification of inventory based landslide susceptibility index (LSI) models based the selection of causative factors functional relationships between factors and integration to a hazard-warning mode is investigated Merged landslide inventories of five typhoon-training events and obtained set of data representing environmental conditions where landslides are likely to occur These well-defined data sets are used to select five representative causative factors including slope angle rock strength drainage curvature and soil type Four bivariate statistical model combinations tested include; linear combination geometric mean and two mixed combinations As a result the modulation effects between (1) rock strength and slope and (2) drainage and curvature were intensified in mixed model 2 (MX2) through factor multiplication The MX2 LSI was integrated with three multivariate landslide hazards warning models and tested with four triggering factor rainfall parameter sets Results show threshold models with terrain influenced rainfall can better approximate hazard warning locations Modulating factor combinations for the hazard warning can also mirror true environmental conditions which allow for more representative model results A framework is developed to assess a mountain community vulnerable geohazards The combination of a landslide susceptibility index (LSI) model landslide inventory datasets and field work is used to identify hazard-prone areas in Maolin District Taiwan Furthermore to identify the challenges and opportunities affecting the sustainable development of mountain communities a pilot survey was conducted in three such communities (Dona Village Wanshan Village and Maolin Village) The results reveal that there are two types of significant mass movement in such areas: debris avalanche and debris flow The results also show that the LSI map and multi-temporal landslide inventory datasets correlate with landslide locations Meander is identified as an important factor in landslide activity The questionnaire results show that the residents of the study area lack awareness of and access to information related to landslide activity Similarly the local residents favor increased environmental protection working within their community and additional government spending in regard to managing geohazards

Date of Award	2020
Original language	English
Supervisor	Chih-Hua Chang (Supervisor)