Remote sensing application to estimate fish kills by Saprolegniasis in a reservoir

BONANSEA, MATIAS; FERRERO, SUSANA; MANCINI, MIGUEL; RODRIGUEZ, CLAUDIA; LEDESMA, MICAELA; PINOTTI, LUCIO

SCIENCE OF THE TOTAL ENVIRONMENT

ELSEVIER SCIENCE BV

Lugar: Amsterdam; Año: 2019 vol. 669 p. 930 - 937

0048-9697

Saprolegniasis is one of the most economical and ecologically harmful diseases in different species of fish. Low water temperature is one of the most important factors which increases stress and creates favourable conditions for the proliferation of Saprolegniasis. Therefore, the monitoring of water surface temperature (WST) is fundamental for a better understanding of Saprolegniasis. The objective of this studywas to develop a predictive algorithm to estimate the probability of fish kills caused by Saprolegniasis in Río Tercero reservoir (Argentina). WST was estimated by Landsat 7 and 8 imagery using the Single-Channel method. Logistic regression was used to relateWST estimated from 2007 to 2017with different episodes of fish kills by Saprolegniasis registered in the reservoir during this period of time. Results showed that the algorithm created with the first quartile (25th percentile) of the WST values estimated by Landsat sensors was the most suitable model to estimate Saprolegniasis in the studied reservoir.