Seminarreflectionpaperoct 28

Strategies that are used to Predict EarthquakesGeological processes such as volcanic eruptions, earthquakes landslides and floods can cause great harm that can constitute to major hazards. Some of the ways to reduce these effects are building structures and lifelines out of harm’s way through evaluating threatened areas and building structures that withstands the effects of hazards (Asim, Idris, Iqbal, & Martinez-Álvarez, 2018). These actions require people to anticipate areas that these hazards are likely to occur and to respond to it in an appropriate manner. The paper provides a discussion on some of the prediction strategies that can be used to prevent earthquakes from occurring.Predicting the possibility of geological hazards occurring plays a crucial role in estimating the consequences of the events. Further, prediction of the events is necessary for the development of a mitigation and response plan. The possibilities of predicting the event and its effects and multiple scenarios are also helpful for planning purposes. Currently, there exists a high-speed computational and communication system in place that makes it possible to predict the effects of a specific geological hazard have taken place (Asim, Idris, Iqbal, & Martinez-Álvarez, 2018). Use of near real time mapping can also be used as a predictor of the development of ash clouds as a result of volcanic eruption. Prevailing wind patterns, trajectories of ash clouds that can disable airplanes can be predicted and traffic airliners can then be warned of impending danger. Impending danger that results from volcano eruption can be predicted through assessing where the flow of water and mud through the valley can reach the city through the use of sufficient lead time and by implementing emergency measures before a river flow.It takes a considerable period of time for stresses that cause earthquakes to occur and build up. This provides a long-term strategy for predicting earthquakes. Researchers should also have a general understanding of the earthquake history fault zone and its readiness to generate future earthquakes. Faults also provide a basis for long term future predictions through estimating the effects and assessment of hazards (Ogata, 2013). Defining fault zones is also useful in identifying high risk areas to create mitigation strategies that can help in establishing warning systems. Such knowledge is used for planning purposes and establishing standards for structures and planning in urban development.Another strategy is through methodology of pattern recognition. This involves conducting a correlation ship among numerous parameters that is associated with occurrence of a strong earthquake. Methodology of pattern creating involves establishing criteria for anomalous variations in each of the parameters and defining the significance occurrence of earthquake. For instance, occurrence of moderate earthquake activity is regarded as a harbinger of larger shock in a particular region in a certain time frame (Asim, Idris, Iqbal, & Martinez-Álvarez, 2018). As a result, recognizing the anomalous seismicity can be done through raising a flag to warn people of impending danger. Furthermore, use of computer modeling of physical changes caused by an earthquake is an efficient strategy that can be used in redistribution of stress. This method alters stresses released on the causative fault and those on the rocks. A change at the stress field alters the potentiality of earthquakes from occurring.In conclusion there is need for more advanced research to obtain a proper understanding of landslides, advance the methods used in assessing landslides and increasing the application of landslides and hazard evaluation in developing areas. Furthermore, there is need for real time hazard monitoring systems for hazard evaluation and timing.ReferencesAsim, K. M., Idris, A., Iqbal, T., & Martinez-Álvarez, F. (2018). Earthquake prediction model using support vector regressor and hybrid neural networks.PloS one,13(7), e0199004.Ogata, Y. (2013). A prospect of earthquake prediction research.Statistical science, 521-541.