PINOY RESEARCHER’S STUDY SAYS: Predicting rainfall-induced landslides may be possible

A major landslide buried an entire village in Leyte following heavy rains early last year. Some 2,000 people lost their lives and houses were swamped by the flow of mud. Around the world, landslides kill thousands of people each year and cause extensive property damage or loss, especially in heavily populated mountainous regions.

Recent studies, however, indicate that it may actually be possible for rainfall-induced failures to be predicted by carefully monitoring changes in soil moisture content and deformations at specific areas within the slope.

In a research article which appeared in the National Engineering Center’s Philippine Engineering Journal, Yamaguchi University professor Rolando Orense proposed a simple method of predicting the occurrence of landslides caused by heavy rainfall by installing soil moisture sensors at "critical locations, possibly in areas where seepage forces will develop."

Orense is a civil engineering graduate of UP Diliman (BSCE, 1984, cum laude; MSCE, 1989) now based in Japan.

A landslide is a downward movement of rocks and soil, although sometimes the collapse may involve vegetation, structures, or parts of roadways. Sometimes the soil can liquefy with the slide becoming a mudflow that acts much in the same way as a stream of water.

Landslides may be set off by human activities such as cutting roadways and building dwellings or placing improperly engineered fill on steep slopes.

Earthquakes can also trigger landslides. The most common triggering mechanism, however, is the combination of heavy rainfall, steep slopes, and loose or soft soil.

Orense conducted reconnaissance studies in Quezon and laboratory tests at the University of Tokyo’s Geotechnical Engineering Laboratory to show the correlation between rainfall intensity and the frequency of landslides.

Among Orense’s interesting findings was the fact that numerous landslides occurred even in areas which were heavily forested. By contrast, there are areas where very few landslides take place despite their marginal forest cover. Landslides were also found to occur more likely in steep slopes regardless of whether they are forested or not.

In all the affected areas, soil composition is typically made up of silty sand or sandy silt with very little clay content. Orense believes heavy rainfall saturates the slopes, causing the soil to lose sheer strength and eventually triggering failure.

While environmental conditions, particularly land use and logging may contribute to the impact and scale of the disaster, as far as Orense’s study is concerned they are not the main causes of landslides.

Orense’s observation implies not only that loose soil slopes would undergo more rapid deformation than dense ones when subjected to heavy rainfall, but that more rapid ground movement would be expected for steeper slopes than for mild ones.

This is consistent with the general idea that "slope gradient is a significant factor in establishing the instability state as well as the condition of slopes after the failure."

Slight slope movements and tensile crack formation usually precede slope failure. Cracks are formed due to the decrease in strength at the slip surface related to the pore-water pressure increase. This indicates, according to Orense, that "small-scale" slope movements can also serve as indicator of impending collapse.

If Orense is right, there is no need to install numerous moisture sensors along the slopes. This is a more economical landslide disaster detection and mitigation system.

Soil moisture sensors, says Orense, may be installed only at critical locations where seepage pressures will likely develop. Monitoring devices, on the other hand, may be fixed only at the height when the estimated travel distance of the failed portion of the slope reaches a critical level in which a downslide becomes inevitable.

Even though the system will not be able to predict collapse time accurately, alarm can be issued several minutes before slope failure reaches its critical level to give residents and disaster workers ample time to respond.

Orense, however, admits that further investigations using numerical analyses and actual on-site monitoring may still be necessary to validate the effectiveness of his proposed system.

Nevertheless, he maintains that a carefully laid-out system, along with accurate information on ground conditions, may just spell the difference between life and death.