Drought Monitoring by India Meteorological Department (IMD)
India Meteorological Department (IMD) monitors the incidence, spread, intensification and cessation of drought (near realtime basis) on a weekly time scale over the country based on Aridity Anomaly Index. It also issues Weekly Drought Outlook, based on this index, which indicates the impending drought scenario in the country in the subsequent week.
Based on aridity anomaly index, weekly Aridity Anomaly Reports and maps for the Southwest Monsoon Season for the whole country and for the Northeast Monsoon Season for the five meteorological sub‑divisions, viz. coastal Andhra Pradesh, Rayalaseema, south Interior Karnataka, Tamil Nadu & Pondicherry and Kerala, are prepared and sent to HQrs and various agricultural authorities of State and Central Govts., and Research Institutes on operational basis for their use in Agricultural Planning purposes. The maps are also uploaded in the departmental website. These Aridity Anomaly maps/reports help to assess the moisture stress experienced by growing plants and to monitor agricultural drought situation in the country.
A brief note on “Aridity Anomaly Technique”
Aridity is the Thornthwaite’s concept to describe water deficiency experienced by plants. Thornthwaite gave the following formula for computing aridity index (AI):
PE – AE
AI = ------------- X 100
PE
PE denotes the water need of the plants (which is called potential evapotranspiration). AE denotes the actual evapotranspiration and (PE-AE) denotes the water deficit. PE is computed by Penman’s equation. AE is obtained from the water balance procedure which takes into account the water holding capacity of the soil at the place.
According to this procedure, rainfall is first utilized by the plants for evapotranspiration purpose. When the evapotranspirative demands of the plants are fully met (as given by PE) the excess amount of rainfall percolates and recharge the soil. This soil moisture recharge continues till the soil reaches its field capacity. Any excess amount of rainfall after the evapotranspirative demands are fully met and the soil is recharged completely is considered as water surplus and goes as surface or deep drainage runoff. When the rainfall is less than the evapotranspirative demands, the plant extracts moisture from the soil till the soil is dessicated of its moisture. During the periods of deficient rainfall, soil loses moisture as per the empirical law (Thornthwaite):
S=fc X exp APME/fc
Where S = moisture remaining in the soil as storage. APME is accumulated potential water loss (sum of negative (P-PE) values), fc is field capacity and P is precipitation.
The Aridity Index is worked out on weekly/biweekly basis. It refers to the water stress suffered by a growing plant due to shortage of available moisture (both rainfall and soil moisture). An anomaly from a normal value would thus signify the water shortage from a long term climatic value.
Normal values of this index for successive weeks during the monsoon are worked out for stations representing different agroclimatic zones of the country. Every week the actual aridity at the place is computed from the weekly total rainfall and antecedent soil moisture conditions. The difference between the actual aridity for the week and the normal aridity (Actual-Normal) i.e. the anomaly is obtained.
A negative or a zero value of this anomaly would imply that as compared to the normal, the place had experienced less arid/drought conditions; a positive value would indicate that the place had experienced more arid/drought conditions than the normal. The positive values of the anomalies have been classified into three different classes as follows:
Anomaly of Aridity Index Agricultural Drought Intensity
1 – 25 Mild
26 – 50 Moderate
> 50 Severe
Aridity Anomaly Map gives information about the moisture stress experienced by growing plant. This analysis would indicate qualitatively retardation in the plants growth and so poor yields. Indirectly, this may also be helpful for irrigation scheduling, the amount and the time at which the water is badly needed by the plant.
Monitoring Meteorological Drought using Standardized Precipitation Index (SPI)
Computation of SPI was done at a monthly time scale. The computation was carried out based on the two parameter gamma distribution function. The rainfall data were transformed into log normal values followed by computation of u statistics, shape and scale parameters of the gamma distribution. The resulting parameters were then used to find the incomplete gamma cumulative probability of an observed precipitation event. The incomplete gamma cumulative probability was then converted to gamma probabilities after including the occurrences of zero precipitation events. The gamma probabilities were transformed into standardized normal distribution using equi-probability transformation techniques (Abramowitz and Stegun, 1965). |
