DOI: 10.1007/s11069-020-03872-6
论文题名: Quantification of agricultural drought over Indian region: a multivariate phenology-based approach
作者: Das P.K. ; Das R. ; Das D.K. ; Midya S.K. ; Bandyopadhyay S. ; Raj U.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2020
卷: 101, 期: 1 起始页码: 255
结束页码: 274
语种: 英语
中文关键词: Agricultural drought
; Integrated normalized difference vegetation index
; Length of crop growing period
; Multivariate phenology derived agricultural drought index
; Multivariate standardized drought index
英文关键词: drought
; growing season
; multivariate analysis
; NDVI
; phenology
; quantitative analysis
; India
英文摘要: The objective, accurate and rapid quantification of agricultural drought is the key component of effective drought planning and management mechanism. The present study proposed a new index, i.e. multivariate phenology-based agricultural drought index (MADI), for quantification of the agricultural drought using long-term (1982–2015) crop phenological parameters. The 15-day global inventory modelling and mapping studies time-series normalized difference vegetation index (NDVI) data (~ 8 km) were interpolated at daily scale and smoothened using Savitzky and Golay filtering technique. Different crop phenological parameters, i.e. start of season, end of season, length of the growing period (lgp), integrated NDVI (iNDVI), etc., were estimated using a combination of threshold and derivative approaches for individual pixels during kharif season. Based on the time of occurrence, the agricultural droughts may lead to delay in crop sowing, reduction in cropped area and/or decreased production. Hence, the lgp and iNDVI were selected among all phenological parameters for their capability to represent alterations in crop duration and crop production, respectively. The long-term lgp and iNDVI of individual pixel were detrended and transformed into standardized lgp (Slgp) and standardized iNDVI (SiNDVI) to eliminate the existing trends developed due to technological improvements during study period and existing heterogeneity of Indian agricultural system, respectively. The MADI was calculated by fitting Slgp and SiNDVI into joint probability distribution, where the best joint distribution family along with associated parameters was selected based on the goodness-of-fit for individual pixel. The values of MADI vary between − 4 and + 4, where the negative and positive values represent drought and non-drought conditions, respectively. The efficacy of the proposed index was tested over the Indian region by comparing with the multivariate standardized drought index, which considers the impacts of both meteorological and soil moisture drought using copula approach. © 2020, Springer Nature B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/168449
Appears in Collections: 气候变化与战略
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作者单位: Regional Remote Sensing Centre-East, NRSC, Kolkata, India; TERI School of Advanced Studies, New Delhi, India; Agricultural Chemistry and Soil Science, University of Calcutta, Kolkata, India; Department of Atmospheric Sciences, University of Calcutta, Kolkata, India; Regional Centres, NRSC, Hyderabad, India
Recommended Citation:
Das P.K.,Das R.,Das D.K.,et al. Quantification of agricultural drought over Indian region: a multivariate phenology-based approach[J]. Natural Hazards,2020-01-01,101(1)