Global Drought and Flood. Группа авторов. Читать онлайн. Newlib. NEWLIB.NET

Автор: Группа авторов
Издательство: John Wiley & Sons Limited
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Жанр произведения: География
Год издания: 0
isbn: 9781119427216
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Williams et al., 2015). Chikamoto et al. (2017) demonstrated that droughts enhance wildfire probabilities in forested systems that take a huge toll on the economy, environment, and local communities in the countryside. Wildfire smoke tremendously increases the level of air pollution and therefore proliferates mortality, and respiratory and cardiovascular morbidity. Accurate measurement of relative humidity is essential for retrieving Aerosol Optical Thickness (AOT) and quantifying particulate matter (PM). Aerosol optical thickness can be derived from the MODIS on board NASA’s Terra and Aqua satellites. The humid air surrounding hygroscopic aerosols causes swelling and this will substantially increase the scattering efficiency of the particles (Hess et al., 1998; Twohy et al., 2009). Gupta et al. (2006) found that a relative humidity ranging from 50% to 80% would increase AOT less than 5%, whereas a relative humidity range of 98–99% results in a more pronounced increase (more than 25%). These results indicate that relative humidity data can be used to enhance the measurements of PM and devise mitigation strategies (Bowman & Johnston, 2005) to reduce the adverse impacts of the hazard (i.e., drought‐associated events such as wildfires).

      1.2.4. Evapotranspiration

      Evapotranspiration (ET) is an important variable in agriculture, accurate estimation of which is essential for modeling agricultural drought. Evapotranspiration directly affects socioeconomic systems and agriculture, as irrigation water demand and crop yield are determined by this variable. Ecosystem and agriculture responses to drought are depicted by the ratio between actual ET (AET) and potential ET (PET) (Thornthwaite, 1948). Accordingly, several drought indices have been proposed that incorporate ET into their calculation including the PDSI, Crop Water Stress Index (CWSI; Jackson et al., 1981), Supply–Demand Drought Index (SDDI; Rind et al., 1990), Water Deficit Index (WDI; Moran et al., 1994), Reconnaissance Drought Index (RDI; Tsakiris & Vangelis, 2005), Evaporative Drought Index (EDI; Yao et al., 2010), Standardized Precipitation Evapotranspiration Index (SPEI; Vicente‐Serrano et al., 2010), Evaporative Stress Index (ESI; M. C. Anderson et al., 2016), Drought Severity Index (DSI; Mu et al., 2013), Green Water Scarcity Index (GWSI; Núñez et al., 2013), Green Water Stress Index (GrWSI; Wada, 2013), Standardized Palmer Drought Index (SPDI; Ma et al., 2014), Multivariate Drought Index (MDI; Rajsekhar et al., 2015), effective Reconnaissance Drought Index (eRDI; Tigkas et al., 2017), Normalized Ecosystem Drought Index (NEDI; Chang et al., 2018), and Aggregate Drought Index (ADI; S. Wang et al., 2018).

Schematic illustration of three-month Standardized Precipitation Evapotranspiration Index (SPEI) with 1° spatial resolution.

      (Source: The Standardized Precipitation Evapotranspiration Index (SPEI), http://spei.csic.es/map/maps.html)

      1.2.5. Snow

Schematic illustration of Evaporative Stress Index (ESI) derived from observations of land surface temperatures and leaf area index from the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra and Aqua satellites and the Visible Infrared Imaging Radiometer Suite (VIIRS) of the Suomi National Polar-orbiting Partnership (NPP).