Development and evaluation of Soil Moisture Deficit Index (SMDI) and Evapotranspiration Deficit Index (ETDI) for agricultural drought monitoring. Narasimhan, B. & Srinivasan, R. Agricultural and Forest Meteorology, 133(1):69–88, November, 2005.
Development and evaluation of Soil Moisture Deficit Index (SMDI) and Evapotranspiration Deficit Index (ETDI) for agricultural drought monitoring [link]Paper  doi  abstract   bibtex   
Drought is one of the major natural hazards that bring about billions of dollars in loss to the farming community around the world each year. Drought is most often caused by a departure of precipitation from the normal amount, and agriculture is often the first sector to be affected by the onset of drought due to its dependence on water resources and soil moisture reserves during various stages of crop growth. Currently used drought indices like the Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI) have coarse spatial (7000–100,000km2) and temporal resolution (monthly). Hence, the distributed hydrologic model SWAT was used to simulate soil moisture and evapotranspiration from daily weather data at a high spatial resolution (16km2) using GIS. Using this simulated data the drought indices Soil Moisture Deficit Index (SMDI) and Evapotranspiration Deficit Index (ETDI) were developed based on weekly soil moisture deficit and evapotranspiration deficit, respectively. SMDI was computed at four different levels, using soil water available in the entire soil profile, then soil water available at the top 2ft. (SMDI-2), 4ft. (SMDI-4), and 6ft. (SMDI-6). This was done because the potential of the crop to extract water from depths varies during different stages of the crop growth and also by crop type. ETDI and SMDI-2 had less auto-correlation lag, indicating that they could be used as good indicators of short-term drought. The developed drought indices showed high spatial variability (spatial standard deviation ∼1.00) in the study watersheds, primarily due to high spatial variability of precipitation. The wheat and sorghum crop yields were highly correlated (r\textgreater0.75) with the ETDI and SMDI's during the weeks of critical crop growth stages, indicating that the developed drought indices can be used for monitoring agricultural drought.
@article{narasimhan_development_2005,
	title = {Development and evaluation of {Soil} {Moisture} {Deficit} {Index} ({SMDI}) and {Evapotranspiration} {Deficit} {Index} ({ETDI}) for agricultural drought monitoring},
	volume = {133},
	issn = {0168-1923},
	url = {http://www.sciencedirect.com/science/article/pii/S0168192305001565},
	doi = {10.1016/j.agrformet.2005.07.012},
	abstract = {Drought is one of the major natural hazards that bring about billions of dollars in loss to the farming community around the world each year. Drought is most often caused by a departure of precipitation from the normal amount, and agriculture is often the first sector to be affected by the onset of drought due to its dependence on water resources and soil moisture reserves during various stages of crop growth. Currently used drought indices like the Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI) have coarse spatial (7000–100,000km2) and temporal resolution (monthly). Hence, the distributed hydrologic model SWAT was used to simulate soil moisture and evapotranspiration from daily weather data at a high spatial resolution (16km2) using GIS. Using this simulated data the drought indices Soil Moisture Deficit Index (SMDI) and Evapotranspiration Deficit Index (ETDI) were developed based on weekly soil moisture deficit and evapotranspiration deficit, respectively. SMDI was computed at four different levels, using soil water available in the entire soil profile, then soil water available at the top 2ft. (SMDI-2), 4ft. (SMDI-4), and 6ft. (SMDI-6). This was done because the potential of the crop to extract water from depths varies during different stages of the crop growth and also by crop type. ETDI and SMDI-2 had less auto-correlation lag, indicating that they could be used as good indicators of short-term drought. The developed drought indices showed high spatial variability (spatial standard deviation ∼1.00) in the study watersheds, primarily due to high spatial variability of precipitation. The wheat and sorghum crop yields were highly correlated (r{\textgreater}0.75) with the ETDI and SMDI's during the weeks of critical crop growth stages, indicating that the developed drought indices can be used for monitoring agricultural drought.},
	number = {1},
	urldate = {2018-10-25},
	journal = {Agricultural and Forest Meteorology},
	author = {Narasimhan, B. and Srinivasan, R.},
	month = nov,
	year = {2005},
	keywords = {Crop yield, Drought index, Evapotranspiration, PDSI, SPI, Soil moisture},
	pages = {69--88}
}

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