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Soil Degradation: Global Assessment
Published in Brian D. Fath, Sven E. Jørgensen, Megan Cole, Managing Soils and Terrestrial Systems, 2020
Ahmet Çilek, Suha Berberoğlu, Erhan Akça, Cenk Dönmez, Mehmet Akif Erdoğan, Burçak Kapur, Selim Kapur
The global aridity index map was gathered from the -Consultative Group for International Agricultural Research – Consortium for Spatial Information (CGIAR-CSI). Aridity is expressed as a function of precipitation, potential evapo-transpiration (PET), and temperature, and is classified according to the climatic zones proposed by the UNEP.[10] The Aridity Index is used to quantify the precipitation deficit over atmospheric water demand. The Aridity Index map was derived using MODIS images with 1 km spatial resolution. The climate data sets were obtained from the WorldClim data set,[11] and the map was estimated with the following equation: Aridity Index (AI)= MAP/MAE,
Drought Management for Landscape and Rural Security
Published in Saeid Eslamian, Faezeh Eslamian, Handbook of Drought and Water Scarcity, 2017
Sandra Reinstädtler, Shafi Noor Islam, Saeid Eslamian
In context of drying land and being extremely important for further discussion the definition of aridity should be mentioned: aridity is equal than a deficit of humidity. So, precipitation is lower than the evaporation in arid areas. The aridity grade gives information for the predestination possibility of drought or degradation. Degeneracy and magnitude of water scarcity are the depending parameters. The aridity grade, and with it the possibility for drought or degradation, is measurable over the aridity index (AI) [86]. The AI is a numerical indicator composed of precipitation divided by (active and passive) evaporation for estimating the grade of aridity [86]. AI quantitatively—and since the twentieth century also empirically—defines the degree of dryness of the climate at a given location. With some specific sort of AI index it is also possible to describe a species distribution. For example, determining the degree of aridity with an AI higher than 1.0 within monthly metering means to obtain the aridity in this perimeter of monitoring. Next to AI the medium annual precipitation and the medium annual evaporation are important for evaluating dry lands, arid regions, or areas [86]. In order to estimate the grade of affinity for a drought-prone area, these forms of metering are helping in assessing drought. But these indices are limited in using only climatic data. They are excluding the use of soil data [14] but it must be acknowledged that these indices are limited to using only climatic data and not soil data [14].
Drought and Remote Sensing
Published in George P. Petropoulos, Tanvir Islam, Remote Sensing of Hydrometeorological Hazards, 2017
Table 1.1 presents an indicative list of available and commonly used meteorological drought indices in different classes (Farago et al., 1989; Dalezios et al., 2017a). A brief description of the classes of meteorological drought indices is as follows: Indices of atmospheric drought: Low humidity is considered as the standard signal of dry spell. Indeed, atmospheric drought is usually described by the water vapor saturation deficit (Selyaninov, 1958).Indices of precipitation anomaly: Several existing precipitation anomaly indices are listed in Table 1.1, such as the Precipitation Index, the Relative Precipitation Sum, the Relative Anomaly, the Standardized Anomaly Index, and the Average Standard Anomaly (WMO, 1975).Aridity indices: The aridity index is based on the evapotranspiration/precipitation ratio (Budyko, 1952). There are several types of aridity indices, some of which are listed in Table 1.1, such as Lang’s Rainfall Index, de Martone Aridity Index, Ped’s Drought Index (PDI1) (1975), Selyaninov’s Hydrothermal Coefficient (1958), Thornthwaite Index (1948), Potential Water Deficit, Potential Evaporation Ratio, Aridity Index: Moisture Available Index, Relative Evaporation, Surface Energy Balance, and Bowen Ratio (Skvortsov, 1950).Recursive drought indices: There are several recursive drought indices consisting of the family of PDSI, which are listed in Table 1.1. Such indices are Fooley Anomaly Index (FAI) (Fensham and Holman, 1999), BMDI, the family of PDSI (Palmer, 1965), SPI (McKee et al., 1993), Surface Water Supply Index (SWSI), Reclamation Drought Index (RDI), Palmer Drought Index (PDI), Crop Moisture Index (CMI), KBDI, EDI, and RDI (Tsakiris and Vagelis, 2005).
Estimation of the effects of climate change and human activities on runoff in different time scales in the Beichuan River Basin, China
Published in Human and Ecological Risk Assessment: An International Journal, 2020
Wang Xianbang, He Kangning, Li Ying, Wang Hui
Where is the aridity index (equal to the potential evapotranspiration divided by the precipitation) and is the plant-available water coefficient, which is a comprehensive parameter related to the underlying surface of the vegetation and soil and reflects the availability of soil moisture to different types of vegetation. The recommended value of is 2.0 for woodland and 0.5 for grassland and arable land (McNulty et al. 2002; Zhang et al. 2001). In this study, according to the annual precipitation, the potential evapotranspiration, and the runoff in the basin, the corresponding value can be reversed (Zhang et al. 2001).
Analysis of spatio-temporal variation of hydroclimatic variables of the Krishna river basin under future scenarios
Published in International Journal of River Basin Management, 2022
Chanapathi Tirupathi, Thatikonda. Shashidhar
Aridity Index (AI) is a measure of the dryness of the climate or water deficit present at a given location (Stadler, 1998) and it is a ratio of Rainfall (R) to Potential Evapotranspiration (PET). In this study, AI is estimated as a ratio of the long-term mean rainfall of each sub-basin to the simulated long-term mean PET of that sub-basin. It is one of the important indicators to represent the desertification process, and the values below 0.5 indicate arid and semi-arid regions, whereas the values between 0.5 to 0.65 indicate dry sub-humid regions and the values more than 0.65 humid and hyper humid regions (Colantoni et al., 2015).
Drought monitoring in Ceyhan Basin, Turkey
Published in Journal of Applied Water Engineering and Research, 2021
The Aridity Index (AI) performs the drought condition and achieves the percentage ratio between water deficit and water need. where PET and AET are the potential evapotranspiration and the actual evapotranspiration, respectively (Middleton and Thomas 1997). AI identifies the drought occurrence indicator by the degree of dryness of the climate in any region (Table 3).