# [BAM17b] Estimating Daily Evaporation from Poorly – Monitored Lakes using limited Meteorological Data

**Conférence Internationale avec comité de lecture : **
SDEWES 2017,
October 2017,

pp.1-12,
Croatia,

**motcle: **

**Résumé: **
Open water evaporation is influenced by several meteorological parameters such as: irradiance, soil
temperature, relative humidity, atmospheric pressure, and wind speed. However, dealing with that
matter, in a case of measurements scarcity, is a challenging task. To overcome this problem, the
authors sought a less-dimensional method to estimate lake evaporation. This technique takes into
account only three weather variables: Temperature, Relative Humidity and Dew point. In fact, the
approach is summarized as follows: 1- using Levenberg-Marquardt algorithm, a Nonlinear
Regression Model based on Magnus formula is trained and tested to estimate the dew point. 2- a
simplified Penman formula provides an estimate of the lake evaporation rate. To test approach
effectiveness, the suggested method was applied on Qaraoun Lake – Lebanon. Upon testing, the
regression model exhibited high accuracy with a goodness of fit value equal to 0.99. Afterward, the
evaporation rates were estimated using Penman formula. Unfortunately, evaporation measurements
are not available on site to carry the testing procedures. Instead, outcomes were compared with the
monthly evaporation average retrieved from the nearest region to the lake. Estimated rates were
reasonably good with a correlation coefficient equal to 0.8. Overall, achieved results were reliable
enough to carry out a further assessment of the economic impact of evaporation losses from
Qaraoun reservoir on hydropower generation