SOIL MOISTURE INDEX ON THE BASIS OF REFERENCE EVAPOTRANSPIRATION PENMAN MOTEITH METHOD USING REMOTE SENSING METHODS

Apr 23, 2021, 9:50 AM
15m
1221 (Lomonosov st. 9)

1221

Lomonosov st. 9

oral Sustainable Use of Natural Resources Sustainable Use of Natural Resources

Speaker

Daniela Munoz Osorio (PhD Student)

Description

In the Dominican Republic, during the last 30 years, drought episodes have been prolonged in the southern, southwest, and northwest regions of the country (Aquino, 2019), threatening the productive capacity of farmers who must also plan and monitor their work with great uncertainty due to the scarcity of agrometeorological information. Given this challenge, we have developed a dataset and a method useful for agricultural management and planning, especially to determine the condition of agricultural drought. The dataset is made of remote sensors' information, and the method is based on the concept of the soil moisture index, which corresponds to the relationship between precipitation and reference evapotranspiration.
The tool used in this work was Google Earth Engine. With it, we have calculated spatial time-series of reference evapotranspiration (Penman Moteith method), precipitation, specific air humidity, wind speed, net radiation, and daily maximum and minimum temperature. This dataset makes it possible to fill voids on hydro-climatic information from the last 30 years. Also, the effect of altimetry, with a spatial resolution of 10m, is included.
An application of the dataset in the Montecristi province proved that the soil moisture index is an appropriate indicator to characterize drought. Its average value from 2010 to 2019 was between 0.27 and 0.41, which given the thresholds by (Vigil Black et al., 2019) correspond to moderate drought, in the southern zone, and severe drought, in the rest of the area. Also, characteristic hydro-climatological values were estimated, and extreme evapotranspiration zones were identified.
The data set and the humidity index calculation method allow efficient planning of fieldwork, irrigation management, and even calculating the water layer to apply as the crop adapts to the conditions of irrigation frequency. Moreover, the time series of meteorological data has the potential to be used in water demand studies, irrigation plans and modelling of crop yields.

Affiliation of speaker PhD Student
Position of speaker Author
Publication International journal «Resource-Efficient Technologies»

Primary author

Co-authors

Mrs Marina Kustikova (ITMO University) Mr Carlos Gabriel Gonzalez Marin (C.E.O Intelligent Class )

Presentation materials