It will now be possible to monitor drought at 5-km resolution on near real-time basis. The dataset and drought indicators for south Asia have been made available from 1980 onwards. The database will be updated once every week.
Now, near real-time monitoring of drought at a 5-km resolution that will help policy makers and others in water management at a district and sub-basin levels is possible, thanks to the precipitation and temperature datasets developed and made freely available online by researchers at the Indian Institute of Technology (IIT), Gandhinagar. The dataset and drought indicators available from 1980 to April 2017, and to be updated on a weekly basis, covers the entire south Asian region. Besides drought, the dataset can also be used for monitoring heat and cold waves in South Asia.
“We don’t know whether a particular region is in drought as we don’t have real-time rainfall and temperature data at appropriate scale. IMD [Indian Meteorology Department] provides daily rainfall data mainly during the monsoon season. There’s no real-time information at high-resolution about drought after the monsoon season,” says Prof. Vimal Mishra from the Civil Engineering department at IIT Gandhinagar and one of the two researchers who developed the dataset.
Also, IMD’s drought information is based only on rainfall data and does not incorporate the role of air temperature. But higher temperature after the monsoon season can cause drought-like situation due to increased evotranspiration loses.
This motivated the team to provide information in near real-time on whether a region of interest is under drought and what fraction of a district or sub-basin is under drought. The emphasis was to develop a dataset at a finer resolution (5 km) as the data provided by IMD and other agencies is coarse (resolution of 25 km).
How the dataset was prepared
The researchers used CHIRPS global rainfall data which are available at 5 km resolution and corrected the data for bias and errors. “The corrected data compares well with the IMD data once we aggregate our data to the IMD scale,” says Prof. Mishra.
The precipitation dataset at a finer resolution of 5 km over the entire south Asian region was evaluated against a standard rainfall database (APHRODITE) that is available for the entire South Asia and satellite-based (Modis) information (Normalized Difference Vegetation Index). Earlier studies have shown that the Aphrodite database matches the IMD rainfall data quite well. The results were published in the journal Scientific Data.
“The drought indices — standardized precipitation index and standardized precipitation evapotranspiration index — were estimated using the bias-corrected, high-resolution data and evaluated against satellite-based drought products. The validation gives us the confidence that our dataset can indicate the severity and areal extent of drought at a district and sub-basin level in south Asia,” says Saran Aadhar the Civil Engineering department at IIT Gandhinagar and the first author of the paper.
Putting the drought system to test
The researchers used the drought indices to assess severity and areal extent of drought in 2015 for a four-month period of June to September. The indices indicate that a large area of India, Pakistan and Nepal experienced severe and extreme drought in 2015.
They further demonstrated the utility by estimating the extent of 2015 drought in four districts of Uttar Pradesh by using the indices for a one-year period. They found two districts did not have drought while the other two had 40-50% area under drought. They tested the dataset for the 2015 Chennai flood and evaluated the heat wave of May 2015 and cold wave of January 2016 as well.
“The developed dataset and drought indicators performed well over the south Asian region. Apart from IMD, this is an additional effort to provide more real-time information on drought that can be used for decision-making,” says Prof. Mishra. “Our group will update the database once every week.”
The team proposes to provide a five-day precipitation data as the possibility of errors and inconsistency increases in the case of daily precipitation data.
Along with the precipitation data, the team will also provide maximum and minimum temperature data at district and sub-basin level.