FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2738388934> ?p ?o ?g. }

• W2738388934 abstract "Landsliding is one of the most damaging natural disasters in the mountainous and hilly terrain in the tropics. Landslides occur frequently in the rainy season, which shows that it is the main triggering factor. But how much rain for how long period causes landsliding in the humid tropics is not yet clear. The study tries to understand the relationship between rainfall intensity and duration for triggering landslides. The study uses historical landslide inventory and long term climatic data to define rainfall thresholds. The result shows that for triggering a landslide antecedent rainfall of up to five days and minimum rain of 37 mm is required on the day of slope failure. Slope susceptibility to failure depends very much on terrain hydrological condition which is influenced by soil type and land use practices. Study shows that sloping areas having soils with high clay content are more susceptible to slope failure. INTRODUCTION Landsliding, defined as movement of a mass of rock, debris or earth down a slope (Cruden, 1991; Dai et al., 2002), occurs when the shear stress of the material is higher than its shear strength (Pack et al., 1998; Pack et al., 2001; Van Westen et al., 2009), and it normally occurs on steeper area especially in the mountainous and hilly region. This movement is influenced by various factors, such as slope gradient, soil properties, ground water table, geomorphology, land use change (Karsli et al., 2008), rainfall and also by human intervention such as deforestations, undercutting of slope for road construction or expansion of settlement areas. In addition to these, landslide also occurs as an effect of other natural disasters, such as earthquake and volcanic activity. Slope failures can be caused by combination of both factors, human and natural, mentioned above (Highland et al., 2008). The disaster related to landsliding cannot be avoided, however the impact can be significantly reduced by understanding the process so that proper mitigation measures can be implemented in time (Daag, 2003). In Indonesia landsliding occurs in a yearly basis which causes lots of property damages and also loss of human lives. It is reported that during the period 1998 – 2007, 569 landslide events took place which caused 1,362 fatalities, 315 people injured, around 1,100 people missing, and around 170,000 people were evacuated (BNPB, 2009). Moreover, these landslides also damaged around 42,000 houses, 290 public facilities, 420 km road, and around 387,000 hectares of crops, plantation, and forest. Similar study by Marfai et al. (2008) reveals that between 1990 and 2005 1,112 people died and 395 people were wounded due to landslides in the island of Java. The study also reports the increase of landslide events on a year by year basis due to deforestation, excavation for construction materials (rock and soil), and expansion of settlement in unstable slopes. Rainfall can be considered as one of the main triggering factors in landslides, since most of the landslides are reported to occur during the rainy season (Shrestha, 2004; Marfai et al. 2008; Dahal et al., 2008; Sengupta et al., 2009). Antecedent rainfall influences the saturation of soil and groundwater level making the slope unstable (Van Asch et al., 1999; Guzzetti et al., 2007; Sengupta et al., 2009; Crosta, 1998). Besides, the presence of water in the soil or rock supplements the overall weight of the slope, which increases the shear forces causing the slope less stable (Smith et al., 2008) . Landsliding is one of the most damaging natural disasters in the tropics due to heavy rain. Although rainfall has long been well known as the main cause of landslides, however, the relationship between landslide and rainfall (intensity and duration) is still unclear and it seems to vary from one region to the other (Van Asch et al., 1999; Glade et al., 2000; Guzzetti et al., 2007; Dahal et al., 2008; Guzzetti et al., 2008; Hasnawir et al., 2008; Zˆezere et al., 2008; Sengupta et al., 2009). For minimising damage and for preventive measures, it will be important to know the rainfall thresholds for landslides in the humid tropical environment. The present study shows how long term rainfall data can be analysed in relation to historical landslide data to derive rainfall thresholds (critical intensity or duration of rainfall) for the initiation of landslides. The study was carried out in Central Java, Indonesia. Table 1: Historical Data of Landslide in Indonesia in year 1998 – 2007 MATERIALS AND METHODS / EXPERIMENTAL Study Area Study area is located in a watershed in Wonosobo District, Central Java Province – Indonesia (Figure 1). The watershed is located between 711’’ 736’’ S and 10943’’ 11004’’ E and the elevations varies from 185 – 1,100 m above sea level with surface area extending 11,183 Ha. The study area consists of mountainous region in eastern and north-eastern part of the catchment and gently sloping to hilly/undulating region in the lowlands. Agriculture is the main occupation of the people. Five land cover/land use types exist: forest cover in the mountainous areas, shifting cultivation on the steeper slopes, rainfed and irrigated rice near the river and its tributaries and mixed orchard in the footslope areas. Crops grown are cassava, banana, coffee, kapulaga (Amomum cardamomum), etc. The fast growing Sengon tree (Albazia falcataria), introduced by The Indonesian Ministry of Forestry in early 1990s can be found throughout the study area. There are few settlements in the area. The monthly precipitation in the study area ranges from 34 – 511 mm with mean annual rainfall of around 3500 mm. The rainy season begins in October and continuous to April in the following year. About 50 % of annual rainfall is received during the period January to April and 30 % in October to December ( Figure 2). Landslides occur mainly in the rainy season. Historical data shows that Wonosobo, one of regencies in Central Java Province, has stricken by landslides frequently which damages houses and infrastructures including loss of human lives. The last recorded landslides occurred on 23th/24th January and on 26th/27th February 2009. According to local people, the landslides occurred due to prolonged rainfall (Anonymous, 2009a). Landslide Inventory Land slide data of the study area for the period 2001 to 2008 was available as shown in Table 2 (Anonymous, 2009). The available landslide historical data was classified. Landslide types being used in this research are deep-seated rotational landslides and creep caused by environmental factors, meanwhile the human induced landslides due to under cutting of slopes for constructing road and settlements were left out. During fieldwork the landslide type (environment or human induced) was verified and their geographical position was noted using GPS. Head of landslide scarp was taken as the position of geographic coordinates for the landslides. Data on the date of slope failure was also recorded through interview with local people. Rainfall Data Daily rainfall data from the study area was available for the period 1980 – 2008 (Kaliwiro and Wadaslintang rainfall stations) and for the period 1980 – 2002 (Limbangan station). Because of the presence of few rain gauses in the area, the data from the nearest station was used to correlate rainfall with the landslide event. Total 24-hour rainfall (mm) or continued precipitation of many days at a station was considered the event rainfall for the corresponding landslide event (Dahal et al., 2008). Figure 2: Average monthly rainfall in the area Source: National Disaster Management Agency (2009) Rainfall Frequency Analysis To determine the recurrence of extreme rainfall events causing slope failures and landsliding, Gumbel Distribution model, known as Extreme Value Distribution Type I, was used. This method calculates return period of particular rainfall intensity, or vice versa, based on yearly maximum precipitation in a certain period. The resulted formula from linear trend line is used to derive the intended return period or rainfall intensity (Wilson, 1969). This method is one of the most widely used probability density function (pdf) that calculates extreme values in hydrological and meteorological studies (Kotz et al., 2000; Subyani, 2009). Rainfall Threshold Analysis Rainfall thresholds analysis which i used in this study are intensity – duration (ID) thresholds and antecedent rainfall Figure 1: The Study Area N thresholds calculated empirically. ID thresholds are used to define the lowest boundary of rainfall intensity (mm/day) and the minimum duration that triggers landslide. The relationship between rainfall and landslide can be obtained by means of simple power law method. In intensity – duration (ID) thresholds, a database consisting of rainfall intensity (mm/day) and rainfall duration (day) of landslide events is first made. The two data sets were then used to generate a scattered graph, in which rainfall intensity is used as y-axis and duration as x-axis. By choosing simple power law method, a trend line can be added and the graph shows the equation of rainfall threshold. Generally, intensity – duration (ID) thresholds is presented by the following equation;" @default.
• W2738388934 created "2017-07-31" @default.
• W2738388934 creator A5043986317 @default.
• W2738388934 creator A5075406015 @default.
• W2738388934 creator A5079173597 @default.
• W2738388934 date "2014-10-27" @default.
• W2738388934 modified "2023-09-27" @default.
• W2738388934 title "A slope stability assessment in the tropics" @default.
• W2738388934 cites W1542459729 @default.
• W2738388934 cites W1577971080 @default.
• W2738388934 cites W1585874505 @default.
• W2738388934 cites W191575298 @default.
• W2738388934 cites W1964769134 @default.
• W2738388934 cites W1966272519 @default.
• W2738388934 cites W1975872024 @default.
• W2738388934 cites W1979295289 @default.
• W2738388934 cites W2003269946 @default.
• W2738388934 cites W2044622173 @default.
• W2738388934 cites W2048618120 @default.
• W2738388934 cites W2049323155 @default.
• W2738388934 cites W2072094012 @default.
• W2738388934 cites W2076464824 @default.
• W2738388934 cites W2076497114 @default.
• W2738388934 cites W2091221103 @default.
• W2738388934 cites W2092523977 @default.
• W2738388934 cites W2124593695 @default.
• W2738388934 cites W2134955829 @default.
• W2738388934 cites W2137611024 @default.
• W2738388934 cites W2141282148 @default.
• W2738388934 cites W2157291760 @default.
• W2738388934 cites W2164612088 @default.
• W2738388934 cites W2314389726 @default.
• W2738388934 cites W2584692625 @default.
• W2738388934 cites W278480961 @default.
• W2738388934 cites W2893095293 @default.
• W2738388934 hasPublicationYear "2014" @default.
• W2738388934 type Work @default.
• W2738388934 sameAs 2738388934 @default.
• W2738388934 citedByCount "0" @default.
• W2738388934 crossrefType "journal-article" @default.
• W2738388934 hasAuthorship W2738388934A5043986317 @default.
• W2738388934 hasAuthorship W2738388934A5075406015 @default.
• W2738388934 hasAuthorship W2738388934A5079173597 @default.
• W2738388934 hasConcept C112972136 @default.
• W2738388934 hasConcept C119857082 @default.
• W2738388934 hasConcept C127313418 @default.
• W2738388934 hasConcept C153294291 @default.
• W2738388934 hasConcept C205649164 @default.
• W2738388934 hasConcept C39432304 @default.
• W2738388934 hasConcept C41008148 @default.
• W2738388934 hasConcept C49204034 @default.
• W2738388934 hasConcept C505870484 @default.
• W2738388934 hasConcept C50660011 @default.
• W2738388934 hasConcept C86803240 @default.
• W2738388934 hasConceptScore W2738388934C112972136 @default.
• W2738388934 hasConceptScore W2738388934C119857082 @default.
• W2738388934 hasConceptScore W2738388934C127313418 @default.
• W2738388934 hasConceptScore W2738388934C153294291 @default.
• W2738388934 hasConceptScore W2738388934C205649164 @default.
• W2738388934 hasConceptScore W2738388934C39432304 @default.
• W2738388934 hasConceptScore W2738388934C41008148 @default.
• W2738388934 hasConceptScore W2738388934C49204034 @default.
• W2738388934 hasConceptScore W2738388934C505870484 @default.
• W2738388934 hasConceptScore W2738388934C50660011 @default.
• W2738388934 hasConceptScore W2738388934C86803240 @default.
• W2738388934 hasOpenAccess W2738388934 @default.
• W2738388934 hasRelatedWork W1964174181 @default.
• W2738388934 hasRelatedWork W2016315718 @default.
• W2738388934 hasRelatedWork W2052531245 @default.
• W2738388934 hasRelatedWork W2059218273 @default.
• W2738388934 hasRelatedWork W2084703733 @default.
• W2738388934 hasRelatedWork W2090607112 @default.
• W2738388934 hasRelatedWork W2186371083 @default.
• W2738388934 hasRelatedWork W2369645373 @default.
• W2738388934 hasRelatedWork W2562131513 @default.
• W2738388934 hasRelatedWork W2614677616 @default.
• W2738388934 hasRelatedWork W2766727619 @default.
• W2738388934 hasRelatedWork W2782249018 @default.
• W2738388934 hasRelatedWork W2906674365 @default.
• W2738388934 hasRelatedWork W2910131191 @default.
• W2738388934 hasRelatedWork W3008629900 @default.
• W2738388934 hasRelatedWork W3011378324 @default.
• W2738388934 hasRelatedWork W3036266784 @default.
• W2738388934 hasRelatedWork W3143640439 @default.
• W2738388934 hasRelatedWork W3201171869 @default.
• W2738388934 hasRelatedWork W839086965 @default.
• W2738388934 isParatext "false" @default.
• W2738388934 isRetracted "false" @default.
• W2738388934 magId "2738388934" @default.
• W2738388934 workType "article" @default.