International Journal of Erosion Control Engineering
Online ISSN : 1882-6547
ISSN-L : 1882-6547
Volume 7 , Issue 3
Showing 1-4 articles out of 4 articles from the selected issue
Invited Commentary
  • Kosit LORSIRIRAT
    Type: Invited Commentary
    2014 Volume 7 Issue 3 Pages 69-74
    Published: December 01, 2014
    Released: December 01, 2014
    JOURNALS FREE ACCESS
    Owing to recent climate and land use changes, which affect reservoir sedimentation, reductions in reservoir capacity and shortening of reservoir lifespan have occurred. Meanwhile, water resource management and planning strategies have becomes less effective. Such issues are likely to worsen unless sediment deposition can be predicted precisely and sedimentation can be prevented or controlled appropriately. Accordingly, a model for predicting changes in reservoir capacity due to changes in hydrological characteristics is necessary. The present study aims to assess the factors contributing to reservoir sedimentation in Thailand and to derive a predictive model of reservoir sedimentation using geomorphological factors and forest cover from 25 reservoirs throughout Thailand. In particular, mathematical statistical models predicting reservoir sedimentation (RS) were formulated through multiple regression analysis using data from these 25 reservoirs. The results of the study demonstrate that sediment volumes range from 0.0072 to 4.7218 million m3/year, with an average of 0.49 million m3/year. Six variables were found to have a significant effect on sedimentation in the model: annual volume of inflow (Q), average annual rainfall (R), drainage area (DA), relief ratio (Sr), compactness coefficient (Kc), and stream length ratio (Si). The most applicable equation for predicting RS for reservoirs in Thailand appears to be as follows: RS=exp{3.19007 + 0.00176R - 0.00087DA - 0.00065Cap + 0.03364WSA + 16.44675Sr - 1.29256Kc - 1.07294Si} R0.99986 DA0.00014 This equation produced the highest adjusted R2 (0.9125) with the smallest standard error of estimate (0.4963) and highly significant in prediction. Thus, this model can be applied to predict annual sedimentation in other reservoirs in Thailand. This equation can also be applied to forecast the volume of sediment deposition in other reservoirs and ascertain the real water supply of a given reservoir. Accordingly, it can achieve reductions in operational costs through reservoir capacity surveys, reducing government budgets by an average of 1,900,000 baht per project, and can reduce the time required for each survey by an average of 14 months. The prediction results can be used in the simulation of reservoir operations, improving the efficiency of irrigation operations and ensuring the sustainable management of water resources.
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Original Article
  • Hiroshi KISA, Takao YAMAKOSHI, Tadanori ISHIZUKA
    Type: Original Article
    2014 Volume 7 Issue 3 Pages 75-84
    Published: December 01, 2014
    Released: December 01, 2014
    JOURNALS FREE ACCESS
    Owing to the large quantities of volcanic ash that falls continuously on basins, it is generally known that debris flows can be easily triggered by even a small rainfall in such circumstances. The process of occurrence of debris flow is explained that the infiltration capacities of slopes are reduced because of the accumulation of ash, and therefore, rainfall events induce large quantities of surface runoff and subsequent increase in erosion. The authors established the observation slope at Sakurajima Volcano, one of the most active volcanos in Japan. Surface runoff was observed on the bare slope on which volcanic ash accumulates continuously by eruptions. The purpose of observation is better understanding the relationship between the amount of ash fall and the rainfall threshold for debris flow occurrence. The rainfall conditions necessary for the occurrence of surface runoff were investigated over an observation period that included periods of relatively high ash fall rates and periods with relatively low ash fall rates. Results reveal that there is no evident difference in rainfall intensity that causes surface runoff or in the apparent infiltration capacity of the slope in the case of short-term temporal changes in volcanic ash fall. It was also revealed that if a no-rain period lasts for a long time, the amount of rainfall loss from the onset of rains to the occurrence of surface runoff will increase to some extent.
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  • Fumiaki AKAZAWA, Akikazu IKEDA, Satoshi HAYAMI, Norio HARADA, Yoshifum ...
    Type: Original Article
    2014 Volume 7 Issue 3 Pages 85-91
    Published: December 01, 2014
    Released: December 01, 2014
    JOURNALS FREE ACCESS
    Recently, climate change has resulted in an increasing number of heavy rainfall events. Heavy rainfalls tend to cause large-scale landslides and create large landslide dams. Large landslide dams retain a large amount of water and often burst causing floods and catastrophic damage in the downstream area. Therefore, the study of landslide dam deformation is essential for predicting potential floods to implement effective flood risk management. To understand the landslide dam deformation process and dam outflow discharge characteristics, we carried out field experiments of landslide dam erosion by overtopping flow. In the field experiments, we observed the landslide dam deformation process directly. In a third experimental case, small slope failure occurred and we found that small slope failure affects the outflow discharge. In addition, we developed a numerical model to simulate landslide dam erosion by overtopping flow. To improve the prediction of the outflow discharge, we incorporated the inertial debris flow model, the side bank erosion model, and the slope collapse model into our numerical model. The resulting proposed model is tested by comparing the results of simulation with observation. The numerical model is capable of predicting outflow discharge by landslide dam burst.
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Technical Note
  • Yasuhiro SHUIN, Ikumi OTSUKA, Keigo MATSUE, Kazuhiro ARUGA, Toshiaki T ...
    Type: Technical Note
    2014 Volume 7 Issue 3 Pages 92-100
    Published: December 01, 2014
    Released: December 01, 2014
    JOURNALS FREE ACCESS
    In this study, two indices were used to examine the influence of rainstorms on landslides. The first was a soil water index (SWI) derived from the three-layer tank model that has been applied to the actual evacuation warning system in Japan since 2007. The second was a potential landslide area index (PLAI) derived by combining SWI and a distributed-landslide conceptual model consisting of groundwater table calculation and infinite-slope stability analyses. These two methods were applied to the Utsunomiya University Forest in Funyu, Tochigi, Japan. In August 1998, a heavy rainfall event caused many shallow landslides in the study area, whereas other heavy rainfall events in 1979–2011 did not cause severe landslides. For 26 heavy rainfall events from 1979 to 2011 detected based on the value of SWI, the two indices were used to discriminate between rainstorms with and without landslides. The responses of the two indices to rainfall events showed similar trends, confirming the commonality of the two indices. However, comparing values from both indices between heavy rainfall events with and without landslides showed that PLAI had better sensitivity, suggesting the superiority of this index.
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