Team Telangana State Remote Sensing Applications Centre (TRAC)
Sri K. Ramakrishna Rao, IAS Director General (FAC) Principal Secretary (Finance and Planning) Government of Telangana
Dr. G. Sreenivasa Reddy Addl. Director General
Dr. M. Kavitha Scientist 'SC'
Sri. A. Kamalakar Reddy Senior Technical Officer
Sri. N. Narender Technical Officer
Acknowledgement
We take this opportunity to express our sincere thanks to Directorate of Economics and Statistics, Telangana State Developing Planning Society, and India Meteorological Department for providing rainfall data. We also express our gratitude to Department of Agriculture and Irrigation Department for sharing progress of crop sowings and reservoir water levels data respectively for integrated seasonal condition monitoring of the state.
HIGHLIGHTS INTEGRATED SEASONAL CONDITION MONITORING SYSTEM (ISMS) - TELANGANA Cumulative Report up to 15th September, 2018 Seasonal condition is categorised as “Normal” in 238 Mandals as on date 15th September 2018 Seasonal condition is categorised as “Mild” in 186 Mandals as on date 15th September 2018 Seasonal condition is categorised as “Moderate” in 80 Mandals as on date 15th September 2018 Seasonal condition is categorised as “Severe” in 80 Mandals as on date 15th September 2018
Seasonal Condition up to 1st fortnight of September, 2018 Rainfall from 1st June to 15th September 2018
Rainfall 01st June to 15th September, 2018
237 Mandals out of 584 (40.6%) of state received Deficient rainfall. 52 Mandals (8.9%) of the state received Excess rainfall. 6 Mandals (1%) of the state received Large Deficient rainfall. 1 Mandals (0.2%) of the state received Large Excess rainfall.
288 Mandals (49.3%) have received Normal rainfall respectively.
Seasonal condition of Telangana upto1st fortnight of September 2018
CONTENTS
S. No. Description Page No
1 Background and Rationale 1 2 1. Data used, Indicators and Methodology 3 3 Present status up to 1st fortnight of September 2018 7 3.1 Rainfall data 7 3.2 Reservoir Water Levels 10 3.3 Crop Sowing Progress 11 3.4 Vegetation Index 14 3.5 Surface Wetness Indicators 17 3.6 Drought situation of Mandals 20 3.7 Dry Spell 28 3.8 District Wise NDVI / NDWI / VCI Status 30 4 References 31
List of Tables
Page Table No. Description No
1 Classification of agricultural situation 3 2 Data source and indicators 3 3 Rainfall status as on 15th September 2018 8 4 Reservoir water levels 10 5 District Wise Crop Sowing Area - Up to the week ending 29-08-2018 12 6 Mandals under Mild, Moderate and Severe category based on ISMS criteria 21 7 District wise NDVI / NDWI / VCI Status 30
List of Figures
Pa Figure Description ge. No. No 1 Location of Automatic Weather Stations 2
2 Flow chart of drought assessment methodology 6 3 Deviation of rainfall in percent w.r.t. normal from June 01st to September 15th, 2018 9 4 District wise deviation from normal crop sown area as on date 29-08-2018 11 5 District wise deviation (graph) from normal crop sown area as on date 29-08-2018 13 6 NDVI - MODIS: First Fortnight of September 2018 14 7 NDVI - MODIS, Fortnightly agricultural situation from September 2018, 2017 and 2016 15 8 NDVI deviation (MODIS - 250m), First Fortnight of September 2018 w.r.t. 2013 16 9 NDWI - MODIS: First Fortnight of September 2018 17 10 NDWI - MODIS, Fortnightly agricultural situation from September 2018, 2017 and 2016 18 11 NDWI deviation (MODIS - 250m), First Fortnight of September 2018 w.r.t. 2013 19 12 Mandal wise drought assessment based on ISMS criterion 20 14 Dry spells from June 01st to September 15th, 2018 28 15 Dry spells With Rainfall Status from June 01st to September 15th, 2018 29
ANNEXURE
S. No Description Page. No
I District wise maps showing Mild, Moderate and Severe Mandals 32
1. Background and Rationale Drought is a complex natural hazard. It is defined as any deficiency of water to satisfy the normal need to agriculture, livestock, industry, or human population. Drought assessment and monitoring is essential for the agricultural sector to take appropriate mitigation measures. Drought indices derived from satellite data play a major role in assessing the health and condition of the crops/vegetation.
National Agricultural Drought Assessment and Monitoring System (NADAMS) project of National Remote Sensing Centre (NRSC), Indian Space Research Organization (ISRO) established a remote sensing based drought assessment protocol utilizing the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI). The Government of India has established Mahalanobis National Crop Forecast Centre (MNCFC) under Department of Agriculture and Cooperation, New Delhi for carrying out drought assessment at national level.
The Department of Agriculture and Cooperation, Government of India published a drought manual in 2016 which suggested parameters like rainfall deficiency, area under sowing, NDVI, Moisture Adequacy Index (MAI) and some other indictors to declare drought. The Government of Telangana (GoTS) recommended that drought declaration should include three indices with at least one index from each of the following two groups;
Group 1 Rainfall deviation Dry spell MAI Group 2 NDVI Area reduction under major crop (s) Supplementary indicators These indicators are very important to provide information on drought impact on other sectors. Depletion in ground water level Fodder shortage Drinking water shortage
An extensive weather observation network of 855 Automatic Weather Stations (AWS) is established in Telangana. Telangana State Development Planning Society (TSDPS) monitors the data and maintains the networks. Figure 1 showing the location of AWS stations in Telangana.
Integrated Seasonal Condition Monitoring System (First Fortnight of September, 2018) 1
Figure 1: Location of automatic weather stations
Telangana State Remote Sensing Applications Centre (TRAC) has established a protocol Integrated Seasonal Condition Monitoring System (ISMS). The objectives of the ISMS are
Concurrent monitoring of seasonal conditions using remote sensing, extensive weather network data and continuous ground truth. Develop an early warning (monitoring and forecasting) of drought using suite of indicators, which will help to increase drought preparedness, and identify and implement appropriate Disaster Risk Reduction (DRR) measures. Early warning to the Districts/Mandals.
ISMS uses the rainfall data provided by Directorate of Economics & Statistics (DE&S), weekly progress of crop area sowings, groundwater level and its fluctuation, command and non- command area, water releases data, reservoir levels in addition to the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) based methodology of MNCFC. This output is verified through ground truth, additionally in context of the state specific drought declaration criteria. The agricultural situation is classified in three to four categories as per the NRSC i.e. Normal, Watch, Alert for June to August and Normal, Mild, Moderate and Severe for September to October. The details of the classification of agricultural situation are given in Table 1.
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Table. 1. Classification of agricultural situation
Duration Condition Description Normal Agricultural situation is normal Progress of agricultural situation is slow Watch Ample scope for recovery No external intervention needed July - August Very slow progress of agricultural situation Need for intervention. Alert Develop and implement contingency plans to minimise loss Mild Crops have suffered stress slightly drought September - Moderate Considerable loss in production. October drought Take measures to alleviate suffering Severe High risk significant reduction in crop yield Management measures to provide relief
2. Data used, Indicators and Methodology 2.1. Data used Details of data used under project are discussed in Table 2. Table. 2. Data source and indicators
Data source Product Indicators MODIS (250/500m) Surface reflectance NDVI & NDWI AWiFS Surface reflectance NDVI & NDWI Daily rainfall Rainfall deviation AWS/ DES Crop sown area Dry spells Crop cutting experiments Crop yield Agriculture District wise sown areas Weekly sowing progress Department, GoTS deviation from normal Irrigation Reservoir levels/ Water Command area Mandals Department, GoTS release data under canal irrigation
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2.2. Indicators and Index
2.2.1. Rainfall data In Telangana, South-West Monsoon is crucial for agriculture sector. ISMS uses integrated (AWS+DES+IMD) Mandal wise rainfall data provided by Directorate of Economics & Statistics (DES). This data is used for computation of meteorological drought situation and to derive the mandal wise spatial distribution of rainfall in the state.
2.2.2. Reservoir water levels and water release - major and medium project A scheme having Culturable Command Area (CCA) up to 2,000 hectares individually is classified as minor irrigation scheme. A scheme having CCA more than 2,000 hectares and up to 10,000 hectares individually is a medium irrigation scheme. A scheme having CCA more than 10,000 hectares is major irrigation scheme. In Telangana, water is released during Kharif season to major and medium command areas.
2.2.3. Crop sowing progress Weekly crop sowing progress reports are taken from 'Season and Crop Coverage Report- Kharif 2018' of Commissioner of Agriculture, Telangana. The report includes current status of Weather condition, Water level, Crop sowing and Agricultural Operations.
2.2.4. Vegetation index The crop/vegetation reflects high energy in the near infrared band due its canopy geometry and health of the standing crops/vegetation and absorbs high in the red band due to its biomass and photosynthesis. Uses of these contrast characteristics of vegetation in near infrared and red bands indicate both the health and condition of the crops/vegetation. Normalised Difference Vegetation Index (NDVI) is widely used for operational drought assessment because of its simplicity in calculation, easy to interpret and its ability to partially compensate for the effects of atmosphere, illumination geometry etc., (Malingreau 1986, Tucker and Chowdhary 1987, Kogan 1995). NDVI is derived by the difference of these measurements and divided by their sum.
The vegetation index is generated from each of the available satellite data irrespective of the cloud cover present. To minimize the cloud, monthly time composite vegetation index is generated.
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2.2.5. Surface wetness indicator Shortwave Infrared (SWIR) band is sensitive to moisture available in soil as well as in crop canopy. In the beginning of the cropping season, soil background is dominant hence SWIR is sensitive to soil moisture in the top 1-2 cm. As the crop progresses, SWIR becomes sensitive to leaf moisture content. SWIR band provides only surface wetness information. When the crop is grown-up, SWIR response is only from canopy and not from the underlying soil. NDWI using SWIR can complement NDVI for drought assessment particularly in the beginning of the cropping season. NDWI is derived as under;
Higher values of NDWI signify more surface wetness. The wetness index is generated from each of the available satellite data irrespective of the cloud cover present. To minimize the cloud, monthly time composite wetness index is generated.
2.2.6. Vegetation condition index Kogan (1995) developed Vegetation Condition Index (VCI) using the range of NDVI as under,
The current drought assessment expressed as percentage of deviation of NDVI and NDWI based on 10 year NDVI and NDWI index values. The minimum and maximum value of NDVI and NDWI, the VCI discriminated between the weather components.
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2.3 Methodology
Satellite Data
MODIS AWiFS
NDVI & NDWI NDVI & NDWI
Deviation w.r.t. VCI Normal year
% Rainfall Dev. Command and Non command areas
Dry Spell
June Normal June Normal
to watch to Watch Aug Alert Aug Alert
Normal Normal Sept Sept Mild Mild to to Moderate Moderate Oct Oct Severe Severe
Sampling Plan based on: Water Release Meteorological drought Command/Non Ground Composite
command area Truth Fortnightly Report Drought Prone border Reservoir Level line areas
voir level Weekly Sowing Progress
Figure 2: Flow chart of drought assessment methodology
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The methodology to assess and monitor the agricultural conditions and situation in the state at district and Mandal level uses IRS Resourcesat-2 AWiFS data. Indian Remote Sensing satellite (IRS) Resourcesat-2 having Advanced Wide Imaging Field Sensor (AWiFS) payload collects data in two spectral bands 0.62-0.68 µm (red) and 0.77-0.86 µm (near infrared) with spatial resolution of 56 m and ground swath of 740 km with a revisit period of 5 days. Along with this MODIS 250/500 m satellite data provide spectra, radiometric and spatial resolutions products for better monitoring of the agriculture. The combination of AWiFS and MODIS is useful to increase the frequency of images. The different activities carried out through ISMS commence with acquisition of MODIS (250 m) and AWiFS (56 m) satellite data. The satellite data being processed and NDVI and NDWI indices are developed. Based on these indices deviation with respect to normal year (2013) is calculated and Mandal wise statistics are derived. The agricultural situation is assessed incorporating rainfall deviation, command and non command areas, dry spell, drought prone border line areas, crop sown area progress and ground truth along with satellite derived indices. The flow chart of methodology is shown in Figure 2.
3. Present status up to 1st fortnight of September 2018
3.1. Rainfall data The status of rainfall as on 15th September 2018 is shown in Table.3.
. 1 Mandal (0.2%) of the state received Large Excess (+60% and above) rainfall. . 52 Mandals (8.9%) of the state received Excess (+20% to +59%) rainfall. . 288 Mandals (49.3%) have received Normal (+19% to -19%) rainfall. . 237 Mandals out of 584 (40.6%) of state received Deficient (-20% to -59%) rainfall. . 6 Mandals (1%) of the state received Large Deficient (-60% to -99%) rainfall.
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Table. 3. Rainfall status as on 15th September 2018
Large Large S. No District Name Excess Normal Deficient Total Excess Deficient 1 Adilabad 9 9 18 2 Bhadradri Kothagudem 11 10 2 23 3 Hyderabad 6 10 16 4 Jagtial 3 15 18 5 Jangaon 1 4 8 13 6 Jayashankar Bhupalpally 1 1 18 20 7 Jogulamba Gadwal 3 9 12 8 Kamareddy 11 11 22 9 Karimnagar 2 13 1 16 10 Khammam 3 18 21 11 Kumurambheem Asifabad 2 13 15 12 Mahabubabad 11 5 16 13 Mahabubnagar 3 16 7 26 14 Mancherial 17 1 18 15 Medak 1 19 20 16 Medchal Malkajgiri 5 9 14 17 Nagarkurnool 5 15 20 18 Nalgonda 1 8 19 3 31 19 Nirmal 1 12 6 19 20 Nizamabad 2 22 3 27 21 Peddapalli 8 6 14 22 Rajanna Sircilla 8 5 13 23 Rangareddy 3 6 18 27 24 Sangareddy 1 23 2 26 25 Siddipet 5 17 22 26 Suryapet 15 8 23 27 Vikarabad 1 5 12 18 28 Wanaparthy 3 11 14 29 Warangal Rural 9 6 15 30 Warangal Urban 1 10 11 31 Yadadri Bhuvanagiri 3 12 1 16 Total 1 52 288 237 6 584
SOURCE: DE&S
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The % deviation of Actual & Normal rainfall received up to 15th September 2018 is shown in Fig. 3 respectively.
Figure 3: Deviation of rainfall in percent w.r.t. normal from June 01st to September 15th, 2018
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3.2. Reservoir water levels All the major reservoirs are holding 1195 TMC as on 15-09-2018, and as on date last year the level had stood at 707 TMC. The details of water levels of all major reservoirs as on 15-09-2018 are furnished hereunder in Table.4. Table.4. Reservoir Water Levels PARTICULARS OF MAJOR RESERVOIRS AS ON 15/September /2018 THIS YEAR LAST YEAR Gross As on FRL Capacity As on 15 / September / 2018 15 / September / Sl No Reservoir Name Time 2017 Gross Gross Level Inflow Outflow Level (feet) (TMC) Storage Storage (in feet) (TMC) (Cusecs) (Cusecs) (in feet) (TMC) Krishna Basin 1 Almatti 09:49 1705 129.721 1704.66 127.83 0 2336 1704.72 128.19 2 Jurala 09:11 1045 9.657 1044.88 9.583 9780 9537 1044.95 9.624 3 Nagarjunasagar 09:13 590 312.045 586.1 300.84 0 21244 500.9 116.734 4 Narayanapur 09:50 1615 37.646 1612.43 34.12 88 11503 1614.9 37.56 5 Srisailam 09:12 885 215.807 877.3 174.7 3561 36681 833.7 53.56 6 Tungabhadra 09:10 1633 100.86 1631.52 95.24 2724 11271 1624.94 72.72 7 Ujjaini 09:09 1630 117.24 1630 117.24 741 1448 1630 117.24 Godavari Basin 8 Jaikwad 09:15 1522 102.732 1510.48 61.34 0 1086 1519 90.7 9 Kaddam 08:31 700 7.6 697.93 7.07 594 1026 698.8 7.29 10 Lower Manair Dam 08:30 920 24.074 892.05 6.76 1228 2628 893.3 7.252 11 Nizam sagar 09:16 1405 17.803 1383.84 2.14 0 837 1387.34 3.07 12 Singur 09:15 1717.93 29.91 1696.34 7.24 0 155 1712.93 22.1 13 Sri Ram Sagar 08:29 1091 90.313 1085.4 68.113 0 6269 1075.6 41.2 Source: Irrigation Department, Hyderabad
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3.3. Crop Sowing Progress For the weekend of 29th August, 2018 all districts of the state are showing more than 25 % negative deviation w.r.t. season normal sowings. The total area sown in the state is 3382763 ha as against the normal sown area of 4329057 ha as on date. The details are shown in Figure 4 and the deviation graph is shown in 5.
Figure 4: District wise deviation from normal crop sown area as on date 29-08-2018
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Table 5: District Wise Crop Sowing Area - Up to the week ending 29-08-2018
S. No District Name Normal (ha) Actual (ha) Deviation% 1 Medak 95843 65221 -31.95 2 Khammam 232315 180428 -22.33 3 Suryapet 152413 121648 -20.19 4 Wanaparthy 79546 65286 -17.93 5 Jayashankar Bhupalpally 139511 115158 -17.46 6 Warangal Rural 158812 131106 -17.45 7 Rangareddy 164236 137713 -16.15 8 Vikarabad 171824 145079 -15.57 9 Jogulamba Gadwal 127449 107946 -15.30 10 Sangareddy 221614 194474 -12.25 11 Jagtial 120602 107860 -10.57 12 Nalgonda 314398 284609 -9.47 13 Karimnagar 113839 103944 -8.69 14 Medchal Malkajgiri 6885 6293 -8.60 15 Jangaon 115388 106384 -7.80 16 Bhadradri Kothagudem 125063 115896 -7.33 17 Kumarambheem Asifabad 126015 117091 -7.08 18 Siddipet 202772 189933 -6.33 19 Nagarkurnool 217191 204368 -5.90 20 Rajanna Sircilla 78986 75519 -4.39 21 Mahabubabad 121322 117345 -3.28 22 Yadadri Bhuvanagiri 114608 111494 -2.72 23 Hyderabad 0 0 0.00 24 Adilabad 192626 194098 0.76 25 Nizamabad 172448 174331 1.09 26 Peddapalle 86491 87983 1.73 27 Nirmal 150337 154837 2.99 28 Kamareddy 146770 151653 3.33 29 Mahabubnagar 242508 252353 4.06 30 Mancherial 82187 86435 5.17 31 Warangal Urban 55058 58411 6.09 Total 4329057 3382763
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Figure5: District wise deviation (graph) from normal crop sown area as on date 29-08-2018
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3.4. Vegetation index The Normalized Difference of Vegetation Index (NDVI) for 1st fortnight of September 2018 is shown in the figures and also compared with 2017 and 2016. The year 2013 is treated as a normal year. Mandal wise NDVI, monthly agricultural situation for the year 2018, 2017 and 2016, deviation of NDVI w.r.t. 2013 are shown in the Figures 6, 7, and 8 respectively. As per NDVI deviation w.r.t normal moderate stress is observed in Jogulamba Gadwal, Nagarkurnool, Nalgonda, Mahabubnagar, Rangareddy and Wanaparthy Districts.
Figure 6: NDVI - MODIS: First Fortnight of September 2018
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Figure 7: NDVI - MODIS, Fortnightly agricultural situation from September 2018, 2017 and 2016
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Figure 8: NDVI deviation (MODIS - 250m), First Fortnight of September 2018 w.r.t. 2013
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3.5. Surface wetness indicator The map indicates status of moisture availability in soil as well as in crop canopy for 1st fortnight of September 2018. The year 2013 is treated as a normal year. Mandal wise Normalized Difference Water Index (NDWI) situation from the year 2018, 2017 & 2016, Fortnightly agricultural situation deviation of NDWI w.r.t. 2013 are shown in the Figures 9, 10, and 11 respectively. As per NDWI deviation w.r.t normal moderate stress is observed in Jogulamba Gadwal, Nagarkurnool, Nalgonda, Mahabubnagar, Rangareddy, Vikarabad, Wanaparthy and Yadadri Bhuvanagiri Districts.
Figure 9: NDWI - MODIS: First Fortnight of September 2018
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Figure 10: NDWI - MODIS, Fortnightly agricultural situation from September 2018, 2017 and 2016
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Figure 11: NDWI deviation (MODIS - 250m), First Fortnight of September 2018 w.r.t. 2013
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3.6. Drought situation of Mandals 3.6.1 Composite criteria The drought situation in the state is assessed using different indicators viz., NDVI, NDWI and rainfall deviation of mandals. Compositing all indicators, mandals were categorised into Normal, Mild, Moderate and Severe. Mandal-wise analysis for the 1st fortnight of September 2018 indicated “Normal” agricultural situation in 238 Mandals. The agricultural situation is categorized as “Mild” in 186, "Moderate" in 80 and "Severe" in 80 Mandals. The Mandals under Normal, Mild, Moderate and Severe categories are given in the Table.6. and their spatial distribution is shown in Figure 12.
Figure 12: Mandal wise drought assessment based on ISMS criterion
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Table.6. Mandals under Mild, Moderate and Severe category based on ISMS criteria
District Mild Moderate Severe Adilabad Boath Tamsi Neradigonda Ichoda Mavala Sirikonda Bhadradri Kothagudem Annapureddipalle Cherla NIL Aswapuram Dummugudem Bhadrachalam Karakagudem Chandrugonda Manuguru Chunchupally Pinapaka Laxmidevipalli Mulakalapalle Palawancha Jagtial Kathlapur NIL NIL Jangaon Bachannapeta NIL Palakurthi Chilpur Tharigoppula Devaruppala Zaffergadh Ganpur stn Gundala Lingalaghanpur Narmetta Jayashankar Bhupalpally Bhupalpalle Mahadevpur Malharrao Chityal Mangapet Mutharam Mahadevpur Kataram Palmela Mogullapalle Venkatapuram Tekumatla Jogulamba Gadwal Aiza Dharur Kaloor Timmanadoddi Gadwal Ghattu Maldakal
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Manopad Waddepalle Rajoli Undavelli Kamareddy Domakonda Banswada NIL Kamareddy Bibipet Lingampet Yellareddy Machareddy Naga Reddipet Nizamsagar Pedda Kodapgal Pitlam Ramareddy Karimnagar Ellandakunta NIL NIL Jammikunta Karimnagar Khammam Chinthakani Bonakal Madhira Mudigonda Enkuru Yerrupalem Kamepalle Singareni Komaram Bheem Asifabad Chintalamanepally Lingapur Penchikalpet Jainoor Sirpur U Sirpur T Kagaznagar Tiryani Kouthala Mahabubabad Dornakal Kesamudram Peddavangara Garla Kuravi Mahabubabad Narsimhulapet Nellikudur
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Mahabubnagar Addakal Chinna ChinthaKunta Balanagar Bhoothpur Devarkadara Hanwada Gandeed Krishna Makthal Jadcherla Maganoor Musapet Koilkonda Mahabubnagar Urban Kosgi Mahabubnagar Rural Marikal Midjil Narva Nawabpet Rajapur Mancherial Bellampalle NIL Hajipur Bhimaram Mancherial Chennur Naspur Dandepalle Jaipur Jannaram Kannepalli Nennal Medak Alladurg Manoharabad Tekmal Chilipched Kowdipalle Kulcharam Narsapur Narsingi Nizampet Papannapet Ramayampet Shankarampet A Shivampet
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Medchal Malkajgiri NIL Medchel NIL Medipally Shamirpet Nagarkurnool Amrabad Achampet Balmoor Kollapur Bijinapalle Charakonda NagarKurnool Kodair Kalwakurthy Urkonda Lingal Padra Peddakothapalle Vangoor Tadoor Veldanda Telkapalle Thimmajipeta Uppunuthala Nalgonda Chityala Gurrampode Adavi devula palli Kangal Tirumalagiri Sagar Anumula Haliya Kattangoor Chandampet Kethepalle Chandur Munugode Chinthapalle Nakrekal Damaracherla Nalgonda Devarakonda Narketpalle Gundlapalle Nidamanur Kondamallapally Pedda Adiserlapalle Marriguda Miryalaguda Nampalle Neredugommu Peddavura Thripuraram Nirmal Dastuarabad Narsapur G Kaddampeddur Dilawarpur Khanpur Laxmanchanda Mamda Nirmal
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Nirmal Rural Pembi Nizamabad Armur Jakranpalle Balkonda Mendora Mupkal Kammarpalle Navipet Nizamabad North Makloor Nizamabad Rural Nizamabad South Ranjal Rudrur Vailpur Peddapalli Manthani Ramagundam NIL Mutharam Manthani Rajanna Sircilla Ellanthakunta NIL NIL Gambhiraopeta Mustabad Sirsilla Vemulawada Yellareddypeta Rangareddy Amangal Abdullapurmet Farooqnagar Chevella Balapur Gandipet Kadthal Ibrahimpatnam Hayathnagar Manchal Keshampeta Kandukur Nandigam Moinabad Kothur Shankarpalle Saroornagar Madgul Shabad Maheshwaram Talakondapalle Yacharam Sangareddy Andhole Jharasangam Ameenapur Hathanoora Kandi Jinnaram Kalher Manoor Kohir Munipalli Naykal Kondapur Narayankhed Watpalle Mogdampalle
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Patancheruvu Nagalgidda Pulkal Sadasivpet Ramachandrapuram Zahirabad Sangareddy Sirgapoor Siddipet Anthakkapeta Bejjanki NIL Cheriyal Dubbak Chinnakodur Komaravelly Gajwel Mulug Jagadevpur Thoguta Maddur Wargal Markook Mirdoddi Nanganur Rayapole Siddipet_Rural Siddipet_Urban Suryapet Ananthagiri NIL Chilkur Chinthala palem Chivvemla Garidepalle Kodad Jajireddigudem Mellachervu Munagala Nagaram Neredcherla Thirumalagiri Vikarabad Bantwaram Basheerabad Kotepally Bomraspeta Kodangal Marpalle Dharur Kulkacharla Mominpet Doma Nawabpet Vikarabad Peddemul Pargi
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Pudur Yelal Tandur Wanaparthy Amarchinta Gopalpeta NIL Atmakur Peddamandadi Ghanpur Revelly Kothakota Madanapur Pangal Srirangapur Veepangandla Wanaparthy Warangal Rural Atmakur NIL Sangem Chennaraopeta Duggondi Nekkonda Raiparthy Warangal Urban Khilla Warangal NIL Inole Velair Yadadri Bhuvanagiri Alair Mootakondur Addagudur Bhongiri Mothkur Atmakur M Bibinagar Narayanapur Choutuppal Bommalaramaram Pochampalle Yadagirigutta Ramannapeta Turkapalle M Valigonda
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3.7. Dry Spell In State 319 Mandals experienced dry spells up to first Fortnight of September, 2018. The distribution of the Mandals under dry spell category is shown in Figure:13. Mandals with both deficient rainfall and dry spell situation in the state are shown in Figure:14.
Figure 13: Dry spells from June 01st to September 15th, 2018
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st th Figure 14: Dry spells with Rainfall Status from June 01 to September 15 , 2018
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3.8. District Wise NDVI / NDWI / VCI Status NDVI/NDWI/VCI status as on 15-09-2018, Telangana S.No. District NDVI Average VCI NDWI Average VCI VCI Value NDVI (NDVI) Value NDWI (NDWI) Condition 1 Adilabad 0.67 0.66 70.48 0.52 0.52 62.86 Normal 2 Bhadradri-Kothagudem 0.54 0.54 65.54 0.38 0.44 42.69 Normal 3 Hyderabad 0.18 0.28 30.14 0.13 0.16 36.11 Normal 4 Jagtial 0.96 0.63 88.65 0.79 0.51 91.89 Normal 5 Jangaon 0.36 0.61 8.88 0.27 0.44 38.65 Moderate 6 Jayashankar-Bhupalpally 0.50 0.49 60.46 0.37 0.41 44.55 Normal 7 Jogulamba-Gadwal 0.43 0.37 71.50 0.23 0.21 53.61 Normal 8 Kamareddy 0.68 0.63 82.03 0.55 0.50 80.88 Normal 9 Karimnagar 0.64 0.60 76.47 0.51 0.48 70.04 Normal 10 Khammam 0.60 0.59 62.11 0.44 0.46 47.76 Normal 11 Komaram Bheem-Asifabad 0.53 0.55 55.31 0.42 0.45 50.11 Mild 12 Mahabubabad 0.59 0.62 42.99 0.44 0.47 28.98 Mild 13 Mahabubnagar 0.54 0.46 82.49 0.33 0.31 63.06 Normal 14 Mancherial 0.52 0.50 67.92 0.42 0.40 70.74 Normal 15 Medak 0.64 0.64 61.48 0.49 0.50 52.70 Normal 16 Medchal-Malkajgiri 0.44 0.49 40.58 0.29 0.34 31.29 Mild 17 Nagarkurnool 0.48 0.46 62.90 0.26 0.29 44.67 Normal 18 Nalgonda 0.53 0.54 51.09 0.35 0.37 45.98 Mild 19 Nirmal 0.61 0.57 79.49 0.51 0.46 79.77 Normal 20 Nizamabad 0.64 0.62 73.02 0.53 0.49 76.98 Normal 21 Peddapalli 0.59 0.56 70.46 0.49 0.45 74.39 Normal 22 Rajanna-Siricilla 0.61 0.61 61.71 0.46 0.47 52.87 Normal 23 Rangareddy 0.45 0.51 45.76 0.31 0.36 39.32 Mild 24 Sangareddy 0.55 0.57 63.52 0.44 0.44 62.65 Normal 25 Siddipet 0.59 0.63 39.47 0.43 0.47 38.52 Moderate 26 Suryapet 0.58 0.58 52.29 0.48 0.45 67.60 Normal 27 Vikarabad 0.54 0.52 73.30 0.40 0.40 69.85 Normal 28 Wanaparthy 0.47 0.47 61.30 0.31 0.33 45.73 Normal 29 Warangal Rural 0.62 0.64 42.58 0.49 0.50 47.92 Mild 30 Warangal Urban 0.60 0.61 41.85 0.47 0.46 52.39 Mild 31 Yadadri-Bhongir 0.57 0.59 47.43 0.39 0.41 44.58 Mild
Table.7 District wise NDVI / NDWI / VCI Status
*Normalized Difference Vegetative Index (NDVI) Value - Current year NDVI *Normalized Difference Wetness Index (NDWI) Value - Current year NDWI *Average NDVI - Average of previous 16 years NDVI *Average NDWI - Average of previous 16 years NDWI *VCI (NDVI) - Vegetation Condition Index based on NDVI *VCI (NDWI) - Vegetation Condition Index based on NDWI *NDVI/NDWI Condition - VCI>=60 (Normal), VCI>=40 (Mild), VCI>=20 (Moderate), VCI<20 (Severe)
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References Department of Agriculture and Cooperation, 2009, Manual for Drought Management, Ministry of Agriculture, Govt. of India, New Delhi.
http://drought.unl.edu/portals/0/docs/international/GovtIndiaDroughtManual.pdf
Department of Agriculture, 2017, Season and Crop Coverage Report, Kharif - 2017, Govt. of Telangana
Kogan FN, 1995, Droughts of late 1980s in the USA as derived from NOAA polar orbiting satellite data, Bulletin of American Meteorological Society, 76: 655-668
Malingreau JP, 1986, Global vegetation dynamics: Satellite observations over Asia, International Journal of Remote Sensing, 7: 1121-1146.
Tucker CJ and Chowdhary BJ, 1987, Satellite remote sensing of drought conditions, Remote Sensing of Environment, 23: 243-251
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ANNEXURE I
District Wise Maps Showing Mild, Moderate and Severe Mandals
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