Spatial Variability of Sea Surface Temperature Effect in Utah and Long-term Streamflow Forecasting Using Relevance Vector Machine

TL;DRAbstract

Long-term prediction of streamflow plays an important role on planning and decision making in the river basin scale. This information provides how much water will be available in the next season so that the farmers can plan accordingly how much land to irrigate, and how much livestock to purchase. Financial commitment made early in the season can result in substantial economic losses if the resulting seasonal flow do not subsequently supply enough irrigation water. So, predicting the future water availability is a key step to successful water resource management in arid regions: The data driven model derived from statistical learning theory was made a choice. It relates input/output without trying to understand the underlying physical process. They are characterized by their ability to quickly capture the underlying physics and provide predictions of system behavior using historical data. The model is developed in the form of Multivariate Relevance Vector Machine (MVRVM). Prediction is

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