MODULE 8 LECTURE NOTES 5 REMOTE SENSING APPLICATIONS IN DROUGHT ASSESSMENT

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1 MODULE 8 LECTURE NOTES 5 REMOTE SENSING APPLICATIONS IN DROUGHT ASSESSMENT 1. Introduction Drought is a phenomenon of long-term moisture deficiency. It may be meteorological, agricultural or hydrologic drought. Meteorological drought indicates deficiency in precipitation, whereas agricultural drought indicates scarcity in plant water availability leading to a reduction in crop yield. Hydrologic drought is defined using a combination of factors such as stream flow, groundwater availability and reservoir storage. Remote sensing methods have been used for monitoring both agricultural and meteorological droughts. This lecture gives a brief introduction to the application of remote sensing methods for drought monitoring, particularly agricultural drought monitoring. The lecture also gives the details of the National Agricultural Drought Assessment and Monitoring System (NADAMS) initiated by the National remote Sensing Agency (NRSA), India. 2. Remote sensing applications in drought assessment Remote sensing applications in drought assessment involve monitoring of both the meteorological conditions and the agronomic condition. 2.1 Meteorological condition Remote sensing techniques have been used very effectively to estimate the rainfall and the solar radiation, which are some of the essential informations for drought forecasting and monitoring. Remote sensing estimation of rainfall is based on the differentiation of precipitating clouds from the non-precipitating clouds. Optical remote sensing techniques and microwave (both passive and active) have been used for this. Solar radiation is a major determinant of plant growth and evapotranspiration. Remote sensing techniques are being used to measure the solar insolation through the measurement of energy reflected back from the area. D Nagesh Kumar, IISc, Bangalore 1 M8L5

2 2.2 Agronomic condition Remote sensing data have been widely used to monitor the crop health condition. Remote sensing derived indices such as NDVI are generally used for this. In addition, the day-time and night-time thermal data have been used to find the thermal inertia of the system and hence to interpret the moisture stress condition. Another major application of remote sensing is in the estimation of soil moisture condition in the fields. 3. National Agricultural Drought Assessment and Monitoring System (NADAMS) National Agricultural Drought Assessment and Monitoring System (NADAMS) was initiated in 1989 by the National Remote Sensing Agency (NRSA) under the Remote Sensing Application Mission (RSAM) Drought Monitoring program. The project covers 14 states of the country, which are agriculturally important and vulnerable to drought. The states covered under NADAMS are Andhra Pradesh, Bihar, Chhattisgarh, Gujarat, Haryana, Jharkhand, Karnataka, Maharashtra, Madhya Pradesh, Orissa, Rajasthan, Tamil Nadu, Uttaranchal and Uttar Pradesh (Fig. 1). Fig. 1 States covered under the NADAMS D Nagesh Kumar, IISc, Bangalore 2 M8L5

3 NADAMS provides near real-time information on the prevalence, severity level and persistence of agricultural drought at national/ state / district level during the kharif season. Initial objectives of the program were to provide periodic drought monitoring at district level, during the kharif season (June-October). With the advancement of technology, the objectives have been modified, and currently the mission provides drought monitoring at district level for the entire country. In addition, river basin-wise and crop-wise comprehensive drought monitoring is also achieved under the mission. The details of the NADAMS shown in this lecture are mainly from the work done by Dr. A.T. Jayaseelan, and his colleagues in NRSA, Hyderabad. 3.1 under NADAMS Fig. 2 shows the conceptualization of various droughts in the NADAMS. Accordingly, agricultural drought is assessed by measuring the crop biophysical parameters and in turn the vegetation index and yield condition through remote sensing. Fig. 2 Conceptualization of drought in NADAMS D Nagesh Kumar, IISc, Bangalore 3 M8L5

4 In the NADAMS, vegetation indices (e.g., NDVI) derived from the remote sensing data have been used to assess the drought severity. NDVI is also used to derive other relevant parameters such as GNDVI (weighted average vegetation index over entire geographical area of each district), MNDVI (weighted average vegetation index over vegetation area of each district), VA (vegetation area) and Cl (the residual cloud cover). in any reporting period is based on comparison of district NDVI profile till then to the seasonal profiles of the normal year. For example, Fig. 3 shows the NDVI profile for the Sikar District in Rajastan. Fig.3. Typical NDVI profile for the Sikar District in Rajastan Profile anomalies are interpreted in terms of moisture stress conditions and relative severity level. The relative drought severity level (normal, mild, moderate and severe) is assessed on the basis of criteria such as delay in vegetation growth (1 fortnight, 2 fortnights, 3-4 fortnights and more than 4 fortnights) and the VI anomaly, compared to normal year in percentage: up to 10% low, % low, 25-50% low and more than 50% low. methodology of the NADAMS consists of two components or two segments: ground segment and space segment. D Nagesh Kumar, IISc, Bangalore 4 M8L5

5 Ground segment The ground segment consists of collection and aggregation of the ground based information pertaining to the land use conditions, crop particulars such as cropping pattern, crop duration, yield, irrigated and rainfed area identification. It also consists of the derivation of the correlation between the vegetation indices and the crop yield. Fig.4 shows the schematic representation of the ground segment of the NADAMS. Fig.4. Schematic representation of the ground segment of the NADAMS drought assessment program Space segment The space segment consists of generation of the NDVI images, district level statistics extraction, drought assessment integrating the satellite and ground segment information etc. Fig.5 shows the schematic representation of the space segment of the NADAMS. D Nagesh Kumar, IISc, Bangalore 5 M8L5

6 Fig.5. Schematic representation of the space segment of the NADAMS drought assessment program Remote sensing data used in NADAMS In view of the whole country coverage and the periodic reporting of every fortnight, NADAMS uses National Oceanic and Atmospheric Administration (NOAA) Satellite's Advanced Very High Resolution Radiometer (AVHRR) data that has 1.1 km spatial resolution at nadir and everyday revisit capability. The AVHRR data is used for the drought monitoring in the 10 states marked in Fig.1. The remaining 4 states are monitored by AWiFS and WiFS data. D Nagesh Kumar, IISc, Bangalore 6 M8L5

7 Detailed drought analysis at sub-district level is achieved for four states (Andhra Pradesh, Karnataka, Haryana and Maharashtra) by using moderate resolution Advanced Wide Field Sensor (AWiFS) of Resourcesat 1 (IRS P6), and WiFS of IRS 1C and 1D data. The raw satellite data are collected from the respective organizations and the basic corrections viz., geometric correction, radiometric corrections and panoramic corrections are made. Further the data is used to extract the vegetation indices as well as the land surface temperature. The NOAA AVHRR data processing method with the sequence of steps on radiometric and geometric correction, cloud masking and time composition algorithm was developed by Jeyaseelan and Malleswara Rao (1987). Fig.6 shows the steps involved in the satellite image processing in the NADAMS. Fig. 6. Schematic representation of the algorithm used for estimating drought statistics from remote sensing data D Nagesh Kumar, IISc, Bangalore 7 M8L5

8 Fig. 8 shows a sample VI image showing the color coded, final maximum value composite for entire India, in September Fig.7 Color coded NDVI image generated using remote sensing images Once the parameters are extracted from the satellite images, the administrative boundaries are overlaid over these images in a GIS framework as shown in Fig This helps to extract the details for each administrative block and hence to derive the respective statistics. D Nagesh Kumar, IISc, Bangalore 8 M8L5

9 Fig. 8 Karnataka state maps with district boundaries Fig. 9. Karnataka state administrative boundaries overlaid over the Color coded Maximum value composite of NDVI D Nagesh Kumar, IISc, Bangalore 9 M8L5

10 National level monitoring NADAMS uses AVHRR data at 1.1 km spatial resolution to monitor the drought scenario in the 14 states shown in Fig.1. For these states, using the satellite remote sensing data NADAMS provide the following information. Agricultural vegetation condition images at state / district levels Products on drought related parameters- rainfall, crop areas etc. Agricultural drought assessment maps For each state, district level analyses are provided, as well as the summary report for the entire state. These drought reports are disseminated fortnightly / monthly through post, and DMS-VP network. Biweekly bulletin contains vegetation index image, greenness comparison map and drought assessment report and progressive drought status at district level for every state. Based on the district level analysis, first cut drought alert is sent to the Central and State Govt. Departments related with agriculture and revenue including district level officers through telephone in 3-4 days. In addition, the printed bulletin is sent in 10 days. Monthly bulletins contain district wise agricultural background, consolidated reports on rain and agricultural operation, satellite based assessment on current vegetation development, early warning on subsequent period condition, and expected reduction in yield from major crops. These bulletins are sent to the Central and State Govt. Departments related with agriculture and relief. This information, provided in terms of bulletin in a periodic and time effective manner, will help the resource managers in optimally allocating the financial and other resources to where and when they are most needed. Fig. 11 shows the NDVI maps of Maharashtra in 2001, and the drought condition estimated based on the NDVI. Tables 1 and 2 show the sample drought reports generated by NADAMS for Haryana state in D Nagesh Kumar, IISc, Bangalore 10 M8L5

11 Fig. 10 NDVI maps of Maharashtra and the drought severity map D Nagesh Kumar, IISc, Bangalore 11 M8L5

12 Table 1. District-wise drought assessment and early warning for Haryana as on 30/09/2001 D Nagesh Kumar, IISc, Bangalore 12 M8L5

13 Table 2. Progressive drought status report of Haryana state up to 31/10//2001 The current NDVI is compared with the corresponding period of normal NDVI * Cloud cover is more than 20% of the geographical area Caution: The comparative condition need to be viewed with caution if there is significant residual cloud cover D Nagesh Kumar, IISc, Bangalore 13 M8L5

14 Regional monitoring Detailed drought analysis at sub-district level is achieved for four states (Andhra Pradesh, Karnataka, Haryana and Maharashtra) by using moderate resolution IRS AWiFS, and WiFS data. Fig.12 shows the monthly composite NDVI image of agricultural area, India in September 2003, generated from the IRS WiFS data. No Data Fig.11. IRS WiFS monthly composite NDVI image of agricultural area, India, Sep D Nagesh Kumar, IISc, Bangalore 14 M8L5

15 At the regional level, NADAMS provides the following information for the kharif season. Information by end of August o Table showing sub-district cropped area till the end of July and August and crop condition assessment o Maps of cropped area and condition assessment for each district Information by end of September o Table showing sub-district cropped area till the end of September, crop condition assessment and early warning Information by end of October o Table showing Mandal wise cropped area, crop condition assessment and early warning on expected yield. For each state, NADAMS generates monthly report at Mandal / Taluk (sub-district) level. Crop condition is estimated using the NDVI estimated from the satellite imagery. Similarly, crop moisture status is estimated using the index NDWI (Normalized Difference Water Index) from satellite images. NWDI = (NIR SWIR) / (NIR + SWIR) For example, Fig. 13and 14 show the crop condition and crop moisture status, respectively in Maharashtra in September 2006, derived using the NDVI and the NDWI from the AWiFS data. D Nagesh Kumar, IISc, Bangalore 15 M8L5

16 Fig. 12. Crop condition status in Sept 2006 based on NDVI Fig. 13. Crop Moisture status in Sept 2006 based on NDWI D Nagesh Kumar, IISc, Bangalore 16 M8L5

17 Principal users of the NADAMS drought monitoring reports Central Agencies o Dept. of Agriculture and Cooperation o Planning commission o India Meteorological Department State Agencies o State Relief Department o State Agricultural Department o State remote sensing application centers District report o District Collectors(District administration) Applications of the NADAMS drought bulletins The drought warnings and the drought monitoring reports generated by the NADAMS have been used as inputs to review the agricultural situations by the agriculture departments. They have also been used as inputs for developing contingency plans, for estimating relief claims and for relief management. Satellite Remote Sensing and GIS can play a very important role in Agricultural Drought Assessment and its mitigation Bibliography / Further reading 1. Jeyaseelan, A.T. and Malleswara Rao, T.Ch. (1987). NOAA AVHRR data processing method for vegetation index generation in the vax-11 system. A technical report, water resources division, NRSA, Hyderabad, India. 2. Nagesh Kumar D and Reshmidevi TV (2013). Remote sensing applications in water resources J. Indian Institute of Sci., 93(2), D Nagesh Kumar, IISc, Bangalore 17 M8L5