Abstract

CASTILLO-CASTILLO, Mónica et al. Meteorological drought forecasting using discrete Kalman filter in the Fuerte river watershed, Mexico. Agrociencia [online]. 2018, vol.52, n.7, pp.911-932. ISSN 2521-9766.

The monitoring and forecasting of droughts are important to evaluate risks, take decisions, as well as undertake effective and timely actions to avoid and reduce their negative effects. Therefore, the objective of this study was to forecast the SPI (Standard Precipitation Index) and SPEI (Standard Precipitation Evapotranspiration Index) drought indices for 14 meteorological stations in the Fuerte River watershed in northwest Mexico. Our hypothesis was that it is possible to achieve such objective through the implementation of the Discrete Kalman filter algorithm (DKF). The Fuerte River watershed, Sinaloa, Mexico, is important for its agricultural production and generation of hydroelectric power. We did the forecast of the SPI and SPEI drought indices for time scales (drought durations) of 3, 6, 12 and 24 months, during the period 1961-2011, and with 1, 2, 3 and 4 months in advance. Two models were implemented using the Discrete Kalman filter: a second-order autoregressive (DKF-AR2), and a second-order autoregressive with exogenous input (DKF-ARX). The climatic variables tested as exogenous were precipitation (Pt), maximum and minimum temperatures (Tmax and Tmin) and reference evapotranspiration (ET0); the exogenous variable precipitation, Pt, recorded better results. The DKF-AR2 methodology presented the best result in the forecast of the indices for six stations located in the upper part of the watershed, with predominance of temperate and semi-cold climates. The DKF-ARX-Pt methodology proved better in the remaining eight stations of the middle and lower parts, located in warm climates. The best forecasts were obtained for scales (drought durations) of 12 and 24 months, and the SPEI forecast was better than that of SPI. The Nash-Sutcliffe indices (E) for 12 and 24 months reached up to 0.92 and 0.96; in the case of 3 and 6 months, the Nash-Sutcliffe indices were approximately 0.5. The anticipation of the prognosis was better for 1 and 2 months.

Keywords : Discrete Kalman filter; autoregressive models; drought indices.

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