scholarly journals Drought assessment for kharif rice using standardized precipitation index (SPI) and vegetation condition index (VCI)

2021 ◽  
Vol 21 (2) ◽  
pp. 182-187
Author(s):  
DEEPA B. KAMBLE ◽  
SHWETA GAUTAM ◽  
HIMANI BISHT ◽  
SHRADDHA RAWAT ◽  
ARNAB KUNDU
Keyword(s):  
Standardized Precipitation Index ◽  
Condition Index ◽  
Precipitation Index ◽  
Agricultural Drought ◽  
Productivity Index ◽  
Weather Data ◽  
Multiple Regression Equation ◽  
Drought Assessment ◽  
Vegetation Condition ◽  
Vegetation Condition Index

The monthly weather data for 31 years from 1985-2015 was used to analyze the extent of meteorological drought using standardized precipitation index (SPI) over Allahabad, Kanpur and Lucknow. MODIS NDVI data from 2000-2015 was used for monitoring of agricultural drought through NDVI based vegetation condition index (VCI) for all the three districts. The monthly SPI and VCI values from July to October were correlated with productivity index (PI) of kharif rice.Both the indices (SPI and VCI) were positively correlated with PI for all the districts. In Allahabad SPI and VCI during September month showed a significant correlation (0.70**& 0.61*) while in Kanpur VCI during October and SPI of July and August were significantly correlated with PI of kharif Rice. The multiple regression equation developed for predicting kharif rice PI in Allahabad, Kanpur and Lucknow districts explained 69 to 76 per cent variabilityin PI. 

scholarly journals DROUGHT MONITORING OVER PADDY FIELD AREA IN INDRAMAYU DISTRICT, WEST JAVA USING REMOTELY SENSED INDICES

2010 ◽  
Vol 5 (1) ◽  
Author(s):  
Parwati ◽  
Miao Jungang ◽  
Orbita Roswintiarti
Keyword(s):  
Soil Moisture ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Condition Index ◽  
Dry Season ◽  
Precipitation Index ◽  
Agricultural Drought ◽  
Drought Monitoring ◽  
West Java ◽  
Vegetation Health

In this research, several meteorological and agricultural drought indices based on remote sensing data are built for drought monitoring over paddy area in Indramayu District, West Java, Indonesia. The meteorological drought index of Standardized Precipitation Index (SPI) is developed from monthly Outgoing Long Wave Radiation (OLR) data from 1980 to 2005. The SPI represents the deficient of precipitation. Meanwhile, the agricultural drought of Vegetation Health Index (VHI) was developed from daily Moderate-resolution ImagingSpectroradiometer (MODIS) data during dry season (May-August) 2003-2006. The VHI was designed to monitoring vegetation health, soil moisture, and thermal conditions. The result shows that the agricultural drought occurate in Indramayu District, especially in the northern and southern part during the dry season in 2003 and 2004. It is found that there is a strong correlation between VHI and soil moisture measured in the field (r=0.84). Key words:Agricultural drought, Meteorological drought, Standardized Precipitation Index, Temperature Condition Index, Vegetation Condition Index.

scholarly journals Daily standardized precipitation index with multiple time scale for monitoring water deficit across the mainland China from 1961 to 2018

2021 ◽  
Author(s):  
Qianfeng Wang ◽  
Rongrong Zhang ◽  
Yanping Qu ◽  
Jingyu Zeng ◽  
Xiaoping Wu ◽  
...  
Keyword(s):  
Standardized Precipitation Index ◽  
Social Economy ◽  
Mainland China ◽  
Precipitation Index ◽  
Agricultural Drought ◽  
Multiple Time ◽  
Data Set ◽  
Drought Assessment ◽  
Multi Scale ◽  
The Standardized Precipitation Index

Abstract. With the increasing shortage of water resources, drought has become one of the hot issues in the world. The standardized precipitation index (SPI) is one of the widely used drought assessment indicators because of its simple and effective calculation method, but it can only assess drought events more than one month. We developed a new multi-scale daily SPI dataset to make up for the shortcomings of the commonly used SPI and meet the needs of drought types at different time scales. Taking three typical stations in Henan, Yunnan and Fujian Province as examples, the drought events identified by SPI with different scales were consistent with the historical drought events recorded. Meanwhile, we took the 3-month scale SPI of soil and agricultural drought as an example, and analyzed the characteristics of drought events in 484 stations in Chinese mainland. The results showed that most of the drought events the mainland China did not increase significantly, and some parts of the northwestern Xinjiang and Northeast China showed signs of gradual relief. In short, our daily SPI data set is freely available to the public on the website https://doi.org/10.6084/m9.figshare.14135144, and can effectively capture drought events of different scales. It can also meet the needs of drought research in different fields such as meteorology, hydrology, agriculture, social economy, etc.

scholarly journals GEOSPATIAL APPROACH TO CATEGORIZE AND COMPARE THE AGRO-CLIMATOLOGICAL DROUGHTS OVER MARATHWADA REGION OF MAHARASHTRA, INDIA

2018 ◽  
Vol IV-5 ◽  
pp. 279-285
Author(s):  
S. Kulkarni ◽  
S. Gedam
Keyword(s):  
Management Strategies ◽  
Standardized Precipitation Index ◽  
Interdisciplinary Approach ◽  
Condition Index ◽  
Agricultural Drought ◽  
Drought Severity ◽  
Severe Drought ◽  
Vegetation Condition Index ◽  
Rainfall Trends ◽  
Drought Mitigation

<p><strong>Abstract.</strong> The present study mainly focuses on the comparison and quantification of meteorological droughts with agricultural droughts to understand their relationship to the occurrences and intensities of droughts. This study is based on analysis of the changing agro-climatological drought conditions from the year 2001 to 2017, over the districts of Marathwada, which are known to be the most drought-prone regions of the Maharashtra, India. To quantify the drought severity, Standardized Precipitation Index (SPI) from TRMM and Vegetation Condition Index (VCI) from MODIS datasets have been derived and compared. This study indicated that the years 2002, 2009, 2014 and 2015 were the most severe drought periods over Marathwada. Parts of Nanded, Aurangabad and Latur districts were the highest drought-affected areas from last 17 years, where the frequency of agricultural drought incidence was more than eight years. Over the districts of Hingoli and Parbhani, decreasing rainfall trends plus highly negative values of SPI (&amp;leq;<span class="thinspace"></span>&amp;minus;1.5) in the month of July shows a major concern for agricultural activities. Positive correlation-ship (41%) was noticed between SPI and VCI during the study period, but it was not statistically significant. In the year 2015, which was one of the intense drought years, it is noted that the agricultural drought was the most influencing drought type covering about 53% of the affected area. This study thus can help in identification of drought types and their intensities with spatial extent through an area specific interdisciplinary approach which in turn will help to develop region-specific drought mitigation and management strategies.</p>

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