Modeling drought derivatives in arid regions: a case study in Qatar

Abstract

We propose a stochastic weather model based on temperature, precipitation, humidity and wind speed for Qatar, as a representative arid region, in order to obtain simulated values for a drought index. As a drought index, the Reconnaissance Drought Index (RDI) is commonly accepted in agriculture and is used to measure drought severity. It can be used to price weather derivatives to help farmers reduce nancial losses from drought. RDI, which is the ratio of precipitation to evapotranspiration, is calculated by considering crop growth stages. The use of dierent crop coecient value depending on the growth stage to calculate evapotranspiration can provide improved values for RDI. Additionally, six calculation methods for evapotranspiration using weather data are investigated to obtain accurate values for RDI.

Author Keywords: Evapotranspiration, Markov chains, Mean reversion processes, Reconnaissance Drought Index, Stochastic dierential equations, Stochastic weather models

    Item Description
    Type
    Contributors
    Creator (cre): Paek, Jayoeng
    Thesis advisor (ths): Pollanen, Marco
    Thesis advisor (ths): Abdela, Kenzu
    Degree granting institution (dgg): Trent University
    Date Issued
    2016
    Date (Unspecified)
    2016
    Place Published
    Peterborough, ON
    Language
    Extent
    141 pages
    Rights
    Copyright is held by the author, with all rights reserved, unless otherwise noted.
    Subject (Topical)
    Local Identifier
    TC-OPET-10384
    Publisher
    Trent University
    Degree