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Development of Index to Assess Drought Conditions Using Geospatial Data a Case Study Of Jaisalmer District, Rajasthan, India

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Warianty tytułu
PL
Opracowanie wskaźnika oceniającego stopień suszy z wykorzystaniem danych georeferencyjnych na przykładzie okręgu Jaisalmer w Radżastanie (Indie)
Języki publikacji
EN
Abstrakty
EN
The Jaisalmer district of Rajasthan province of India was known to suffer with frequent drought due to poor and delayed monsoon, abnormally high summer-temperature and insufficient water resources. However flood-like situation prevails in the drought prone Jaisalmer district of Rajasthan as torrential rains are seen to affect the region in the recent years. In the present study, detailed analysis of meteorological, hydrological and satellite data of the Jaisalmer district has been carried out for the years 2006−2008. Standardized Precipitation Index (SPI), Consecutive Dry Days (CDD) and Effective Drought Index (EDI) have been used to quantify the precipitation deficit. Standardized Water-Level Index (SWI) has been developed to assess ground-water recharge-deficit. Vegetative drought indices like Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Vegetation Health Index (VHI), Normalized Difference Vegetation Index (NDVI) and Modified Soil-Adjusted Vegetation Index 2 have been calculated. We also introduce two new indices Soil based Vegetation Condition Index (SVCI) and Composite Drought Index (CDI) specifically for regions like Jaisalmer where aridity in soil and affects vegetation and water-level.
PL
Okręg Jaisalmer w indyjskiej prowincji Radżasthan znany był z częstych susz, spowodowanych słabymi i pojawiającymi się zbyt późno opadami monsunowymi, wyjątkowo wysokimi temperaturami w lecie i niewystarczającą ilością zasobów wodnych. Jednakże ostatnio, w podatnym na suszę okręgu Jaisalmer w Radżasthanie, częstsze jest zagrożenie ze strony powodzi, spowodowanych ulewnymi deszczami. W niniejszej pracy przedstawiono szczegółową analizę danych meteorologicznych, hydrologicznych i satelitarnych z okręgu Jaisalmer, zgromadzonych w latach 2006−2008. Aby ilościowo opisać deficyt opadów, użyto następujących wskaźników: standaryzowany wskaźnik opadów (Standardized Precipitation Index – SPI), ciągły wskaźnik dni suchych (Consecutive Dry Days – CDD) oraz efektywny wskaźnik suszy (Effective Drought Index – EDI). Aby ocenić deficyt wód grunto wych, opracowano standaryzowany wskaźnik poziomu wód (Standardized Water-Level Index – SWI). Obliczono wskaźniki suszy wegetacyjnej takie jak: wskaźnik stanu wegetacji (Vegetation Condition Index – VCI), wskaźnik stanu temperatury (Temperature Condition Index – TCI), wskaźnik zdrowia wegetacji (Vegetation Health Index – VHI), znormalizowany różnicowy wskaźnik wegetacji (Normalized Difference Vegetation Index – NDVI) oraz zmodyfikowany wskaźnik wegetacji z uwzględnieniem poprawki na glebę – wskaźnik wegetacji 2 (Vegetation Index 2). Wprowadzono również dwa nowe wskaźniki: oparty na glebie wskaźnik stanu wegetacji (Soil based Vegetation Condition Index – SVCI) i złożony wskaźnik suszy (Composite Drought Index – CDI), uwzględniając specyfikę dla regionów takich jak Jaisalmer, gdzie suchość w glebie ma wpływ na wegetację i poziom wód.
Rocznik
Tom
Strony
29--39
Opis fizyczny
Bibliogr. 37 poz., rys.
Twórcy
autor
  • Lab for Spatial Informatics, International Institute of Information Technology, Gachibowli, Hyderabad – 500032
autor
  • Lab for Spatial Informatics, International Institute of Information Technology, Gachibowli, Hyderabad – 500032
  • Lab for Spatial Informatics, International Institute of Information Technology, Gachibowli, Hyderabad – 500032
Bibliografia
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  • [5] Dracup JA (1991) Drought Monitoring, Stochastic Hydrology and Hydraulics 5 (4): 261–266
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  • [8] McVicar TR, Jupp DLB (1998). The Current and Potential Operational Uses of Remote Sensing to Aid Decisions on Drought Exceptional Circumstances in Australia: a Review, Agr. Systems (57): 399–468
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  • [16] Thiruvengadachari S, Gopalkrishna HR (1993) An integrated PC environment for assessment of drought. International Journal of Remote Sensing (14):3201–3208
  • [17] Tian G (1993) Estimation of Evapotranspiration and Soil moisture and Drought Monitoring using Remote Sensing in North China Plain. In Space and Environment, Special Plenary Session. In International Astronautical Federation, 44th IAF Congress Graz, Austria, pp. 23–31
  • [18] Johnson GE, Achutuni VR, Thiruvengadachari S, Kogan FN (1993) The role of NOAA satellite data in drought early warning and monitoring: Selected case studies. Chapter 3. In Drought assessment, management, and planning: Theory and case studies, ed D. A. Wilhite, 31–48. New York, NY: Kluwer Academic Publishers
  • [19] Bhuiyan C (2004) Various drought indices for monitoring drought condition in Aravalli terrain of India. Proceedings of the XXth ISPRS Conference, Istanbul, 12–23 July 2004, pp. 907–912
  • [20] Tian G, Jupp DLB, Qin Y, McVicar TR, Li F (1998) Monitoring Soil Moisture and Drought Using AVHRR Satellite Data II: Applications. CSIRO Earth Observation Centre, Canberra, ACT
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  • [28] Gosh TK (1997) Investigation of Drought Through Digital Analysis of Satellite Data and Geographical Information Systems, Theor. Appl. Climatol . (58): 105–11
  • [29] McKee TB, Doesken NJ, Kleist J (1993) The Relationship of Drought Frequency and Duration to Time Scales, Proc. 8th Conf. on Appl. Clim ., 17–22 Jan. 1993, Anaheim, CA, 179–18
  • [30] Shafer BA, Dezman LE (1982). Development of a Surface Water Supply Index (SWSI) to assess the severity of drought conditions in snowpack runoff areas. In: Proceedings of the Western Snow Conference, Fort Collins, CO, pp. 164âA˘ S¸ 175.
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  • [32] Byun HR, Wilhite DA (1999). Objective quantification of drought severity and duration. J. Climate (12): 2747–2756.
  • [33] Tucker CJ (1979) Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment (8) :127–150
  • [34] Teillet PM, Staenz K, Willams DJ (1997) Effects of spectral, spatial, and radiometric characteristics on remote sensing vegetation indices of forested regions. Remote Sensing of Environment (61): 139–1
  • [35] Baret F, Guyot G (1991) Potentials and limits of vegetation indices for LAI and APAR assessment. Remote Sensing of Environment (35):161–173
  • [36] Thenkabail PS, Gamage MSDN, Smakhtin VU (2004) The Use of Remote Sensing Data for Drought Assessment and Monitoring in Southwest Asia, Research Report, International Water Management Institute (85): 1–25
  • [37] Kogan FN (1990) Remote sensing of weather impacts on vegetation in non-homogeneous areas. Int. J. Remote Sensing, 11(8): 1405-1419
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-037e1821-dbab-4c0d-9915-fb2020bbc72a
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