Integrated Drought Index (IDI) for Drought Monitoring and Assessment in India

Drought monitoring and declaration in India are challenging due to the requirement of multiple drought indices representing meteorological, hydrological, and agricultural droughts that are often not available in near real‐time. In addition, the current drought monitoring efforts do not consider grou...

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Veröffentlicht in:Water resources research 2020-02, Vol.56 (2), p.n/a
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description Drought monitoring and declaration in India are challenging due to the requirement of multiple drought indices representing meteorological, hydrological, and agricultural droughts that are often not available in near real‐time. In addition, the current drought monitoring efforts do not consider groundwater storage variability. To overcome this, we develop an Integrated Drought Index (IDI) that combines the response of meteorological, hydrological, and agricultural droughts and accounts for groundwater storage. We use the Gaussian copula to integrate the 12‐month Standardized Precipitation Index (SPI), 4‐month Standardized Runoff Index (SRI), 1‐month Standardized Soil moisture Index (SSI), and 1‐month Standardized Groundwater Index (SGI) to develop IDI. Hydrologic variables (total runoff, soil moisture, and groundwater) required in IDI were simulated using the Variable Infiltration Capacity (VIC) with SIMple Groundwater Model (VIC‐SIMGM). We evaluated IDI against the Drought Severity Index (DSI), terrestrial and groundwater storage anomalies from the Gravity Recovery and Climate Experiment (GRACE) satellites, groundwater well, and streamflow anomalies. Moreover, we identify the three major droughts with the highest severity (based on IDI) that occurred in 1965, 1987, and 2002 in the Sabarmati river basin. The three most severe droughts occurred in 1966, 1979, and 2010 in the Brahmani basin. Notwithstanding the large intermodel uncertainty, which arises primarily from precipitation projections, the drought frequency based on IDI is projected to decline in Sabarmati while it increases in Brahmani basin under the warming climate. Our results show that IDI can be effectively used for drought monitoring and assessment under retrospective and future climate in India. Key Points Developed an Integrated Drought Index based on meteorological, hydrological, and agricultural droughts IDI uses SPI, SRI, SSI, and SGI by incorporating the response of precipitation, runoff, soil moisture, and groundwater IDI performs well against the Drought Severity Index (DSI) and groundwater well and streamflow observations
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In addition, the current drought monitoring efforts do not consider groundwater storage variability. To overcome this, we develop an Integrated Drought Index (IDI) that combines the response of meteorological, hydrological, and agricultural droughts and accounts for groundwater storage. We use the Gaussian copula to integrate the 12‐month Standardized Precipitation Index (SPI), 4‐month Standardized Runoff Index (SRI), 1‐month Standardized Soil moisture Index (SSI), and 1‐month Standardized Groundwater Index (SGI) to develop IDI. Hydrologic variables (total runoff, soil moisture, and groundwater) required in IDI were simulated using the Variable Infiltration Capacity (VIC) with SIMple Groundwater Model (VIC‐SIMGM). We evaluated IDI against the Drought Severity Index (DSI), terrestrial and groundwater storage anomalies from the Gravity Recovery and Climate Experiment (GRACE) satellites, groundwater well, and streamflow anomalies. Moreover, we identify the three major droughts with the highest severity (based on IDI) that occurred in 1965, 1987, and 2002 in the Sabarmati river basin. The three most severe droughts occurred in 1966, 1979, and 2010 in the Brahmani basin. Notwithstanding the large intermodel uncertainty, which arises primarily from precipitation projections, the drought frequency based on IDI is projected to decline in Sabarmati while it increases in Brahmani basin under the warming climate. Our results show that IDI can be effectively used for drought monitoring and assessment under retrospective and future climate in India. Key Points Developed an Integrated Drought Index based on meteorological, hydrological, and agricultural droughts IDI uses SPI, SRI, SSI, and SGI by incorporating the response of precipitation, runoff, soil moisture, and groundwater IDI performs well against the Drought Severity Index (DSI) and groundwater well and streamflow observations</description><identifier>ISSN: 0043-1397</identifier><identifier>EISSN: 1944-7973</identifier><identifier>DOI: 10.1029/2019WR026284</identifier><language>eng</language><publisher>Washington: John Wiley &amp; Sons, Inc</publisher><subject>Agricultural drought ; Anomalies ; Climate ; Climate change ; Computer simulation ; Drought ; Drought index ; Drought monitoring ; Environmental monitoring ; Future climates ; Global warming ; GRACE (experiment) ; Gravity ; Groundwater ; Groundwater runoff ; Groundwater storage ; Hydrologic drought ; Hydrological drought ; Hydrology ; Infiltration capacity ; Integrated Drought Index ; Meteorological drought ; Moisture index ; Precipitation ; River basins ; Rivers ; Runoff ; Soil ; Soil moisture ; Soils ; Standardized precipitation index ; Stream discharge ; Stream flow ; VIC ; Water wells</subject><ispartof>Water resources research, 2020-02, Vol.56 (2), p.n/a</ispartof><rights>2019. 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Moreover, we identify the three major droughts with the highest severity (based on IDI) that occurred in 1965, 1987, and 2002 in the Sabarmati river basin. The three most severe droughts occurred in 1966, 1979, and 2010 in the Brahmani basin. Notwithstanding the large intermodel uncertainty, which arises primarily from precipitation projections, the drought frequency based on IDI is projected to decline in Sabarmati while it increases in Brahmani basin under the warming climate. Our results show that IDI can be effectively used for drought monitoring and assessment under retrospective and future climate in India. 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In addition, the current drought monitoring efforts do not consider groundwater storage variability. To overcome this, we develop an Integrated Drought Index (IDI) that combines the response of meteorological, hydrological, and agricultural droughts and accounts for groundwater storage. We use the Gaussian copula to integrate the 12‐month Standardized Precipitation Index (SPI), 4‐month Standardized Runoff Index (SRI), 1‐month Standardized Soil moisture Index (SSI), and 1‐month Standardized Groundwater Index (SGI) to develop IDI. Hydrologic variables (total runoff, soil moisture, and groundwater) required in IDI were simulated using the Variable Infiltration Capacity (VIC) with SIMple Groundwater Model (VIC‐SIMGM). We evaluated IDI against the Drought Severity Index (DSI), terrestrial and groundwater storage anomalies from the Gravity Recovery and Climate Experiment (GRACE) satellites, groundwater well, and streamflow anomalies. Moreover, we identify the three major droughts with the highest severity (based on IDI) that occurred in 1965, 1987, and 2002 in the Sabarmati river basin. The three most severe droughts occurred in 1966, 1979, and 2010 in the Brahmani basin. Notwithstanding the large intermodel uncertainty, which arises primarily from precipitation projections, the drought frequency based on IDI is projected to decline in Sabarmati while it increases in Brahmani basin under the warming climate. Our results show that IDI can be effectively used for drought monitoring and assessment under retrospective and future climate in India. Key Points Developed an Integrated Drought Index based on meteorological, hydrological, and agricultural droughts IDI uses SPI, SRI, SSI, and SGI by incorporating the response of precipitation, runoff, soil moisture, and groundwater IDI performs well against the Drought Severity Index (DSI) and groundwater well and streamflow observations</abstract><cop>Washington</cop><pub>John Wiley &amp; Sons, Inc</pub><doi>10.1029/2019WR026284</doi><tpages>22</tpages><orcidid>https://orcid.org/0000-0001-8461-4162</orcidid><orcidid>https://orcid.org/0000-0002-3046-6296</orcidid></addata></record>
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subjects Agricultural drought
Anomalies
Climate
Climate change
Computer simulation
Drought
Drought index
Drought monitoring
Environmental monitoring
Future climates
Global warming
GRACE (experiment)
Gravity
Groundwater
Groundwater runoff
Groundwater storage
Hydrologic drought
Hydrological drought
Hydrology
Infiltration capacity
Integrated Drought Index
Meteorological drought
Moisture index
Precipitation
River basins
Rivers
Runoff
Soil
Soil moisture
Soils
Standardized precipitation index
Stream discharge
Stream flow
VIC
Water wells
title Integrated Drought Index (IDI) for Drought Monitoring and Assessment in India
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