International Journal of Civil Engineering and Technology (IJCIET) Volume 7, Issue 6, NovemberDecember 2016, pp. 714 719, Article ID: IJCIET_07_06_079 Available online at http://www.iaeme.com/ijciet/issues.asp?jtype=ijciet&vtype=7&itype=6 ISSN Print: 09766308 and ISSN Online: 09766316 IAEME Publication DROUGHT ANALYSIS IN THE SEONATH RIVER BASIN USING RECONNAISSANCE DROUGHT INDEX AND STANDARDISED PRECIPITATION INDEX Mani Kant Verma, Dr. M. K. Verma, Dr. L K Yadu, Dr. Meena Murmu Civil Engineering Department, NIT Raipur, Chhattisgarh, India ABSTRACT Drought is a climatic situation, characterized by the less availability of moisture. About 33% land area of India come s under the drought prone zone. Seonath river basin (major source of surface water in Chhattisgarh state, India) was taken as a study area for drought analysis. The present work characterizes the frequency of drought by analyzing Reconnaissance Drought Index (RDI) and Standardized precipitation index (SPI) of Seonath basin (Chhattisgarh). Rainfall data of the thirty three rain gauge stations (year 19802013) were taken as the input data for SPI, Rainfall and Temperature data (year 19842013) for RDI. Key words: DrinC (Drought indices calculator), Standardized Precipitation index (SPI), Reconnaissance Drought Index (RDI). Cite this Article: Mani Kant Verma, Dr. M. K. Verma, Dr. L K Yadu, Dr. Meena Murmu. Drought Analysis in the Seonath River Basin using Reconnaissance Drought Index and Standardised Precipitation Index. International Journal of Civil Engineering and Technology, 7(6), 2016, pp. 714 719. http://www.iaeme.com/ijciet/issues.asp?jtype=ijciet&vtype=7&itype=6 1. INTRODUCTION The Drought is one of the major natural hazard which affects several sectors such as economy, environment and social impact. The effect of drought is raised due to the disbalance of the hydrological cycle. Using these words, we can create the simplest definition of drought that it is a situation when water is scarce and insufficient in quantity to meet the demand. Now days due to climate change issues droughts are occurring very frequently worldwide and in some regions it became a very severe hazard. In India around 68% area is drought susceptible. If a region receives rainfall less than 750 mm in a year, then it is chronically drought prone area. The major drought years in India were 1877, 1899, 1918, 1972, 1987, 2002, 2009 [1,2]. The potential of DrinC software is also highlighted for arid & semiarid region in some literatures [3]. For arid land, drought characteristics is explained and their consequences on water resources management [4]. Drought is an event which correlates two terms i.e., Demand and Supply. RDI method and its potential are explained for calculating the drought index at Bhavnagar district [5]. For arid and semiarid regions RDI is being considered as a potential drought index calculator [6]. http://www.iaeme.com/ijciet/index.asp 714 editor@iaeme.com
Mani Kant Verma, Dr. M. K. Verma, Dr. L K Yadu, Dr. Meena Murmu In this paper SPI and RDI method is used for the drought index over Seonath river basin. Seonath basin is main source of water in Chhattisgarh state. Therefore, drought analysis in Seonath basin (Chhattisgarh) is the objective of this paper. DrinC is used for the study along with Microsoft Excel. 2. STUDY AREA & DATA USED Seonath basin receives about 1150 millimeters of mean annual rainfall, mostly in the monsoon season. Overall climate of the area is subhumid tropical. Major crops grown in the area are paddy and maize in the Kharif season and, gram and mustard in the Rabi season. Therefore, this study is needed to improve the agriculture production. The daily rainfall data of 33 Meteorological Stations over entire Seonath river basin for a period of 1980 to 2012 (33 years) were collected from State Data Centre, Department of Water Resources, Raipur. Figure 1 Thiessen Polygon Map of Seonath River Basin (Thiessen Polygon Map) Table 1 Location of Rain Gauge Station use for SPI calculation S.no. Station Name District Longitude Latitude 1 Ambagarh Chowki Rajnadgaon 80.74861111 20.77777778 2 Balod Durg 81.23333333 20.73333333 3 Bemtara Durg 81.54861111 21.72916667 4 Bilaspur Bilaspur 82.15 22.08333333 5 Bodla Kabirdham 81.22333333 22.18166667 6 Chilhati Korba 82.30833333 21.79166667 7 Chirapani Kabirdham 81.19583333 22.20833333 8 Chuikhadan Rajnadgaon 81.01666667 21.53333333 9 Dongargaon Rajnadgaon 80.8625 20.975 10 Dongargarh Rajnadgaon 80.76666667 21.18333333 11 Doundi Lohara Durg 81.05833333 20.79166667 12 Durg Durg 81.28333333 21.21666667 13 Gandai Kabirdham 81.11666667 21.66666667 14 Ghonga Bilaspur 81.96666667 22.3 15 Gondly Durg 81.13333333 20.75 http://www.iaeme.com/ijciet/index.asp 715 editor@iaeme.com
Drought Analysis in the Seonath River Basin using Reconnaissance Drought Index and Standardised Precipitation Index 16 Kawardha Kabirdham 81.23333333 22.01666667 17 Kendiri Raipur 81.73333333 21.1 18 Kharkhara Durg 81.03333333 20.96666667 19 Khuria Bilaspur 81.59888889 22.3875 20 Khutaghat Bilaspur 82.20833333 22.3 21 Kota Bilaspur 82.03333333 22.26666667 22 Madiyan Rajnadgaon 80.61666667 21.13333333 23 Mungeli Bilaspur 81.68333333 22.06666667 24 Nawagarh_Durg Durg 81.60583333 21.90611111 25 Newara Raipur 81.83333333 21.55 26 Pandaria Bilaspur 81.41666667 22.21666667 27 Pindrawan Raipur 81.85 21.4 28 Patherdih Raipur 81.666 21.4555 29 Raipur Raipur 81.63333333 21.25 30 Semartal Bilaspur 82.16666667 22.18333333 31 Dhamtari Dhamtari 81.55222222 20.82194444 32 Jondhra Raipur 81.8333 22.11 33 Kotni Dhamtari 81.51 21.86 3. METHODOLOGY In this study, SPI and RDI have been used for analysis of the drought over Seonath river basin (major source of surface water in Chhattisgarh state, India). For the assessment of drought; precipitation and potential evapotranspiration data of the basin were used. Wet and dry periods have been compared using SPI and RDI. In this study Drought Index (DI) was calculated using DrinC & Microsoft Excel software. The SPI and RDI were calculated for 12 months basis. In India, generally a monsoon season is between June to September or June to October and sometime it happens till October and November. SPI/RDI value calculated by using monthly rainfall & PET values for year 1980 to 2013. In this paper DrinC is used for drought analysis. As an input, series of daily rainfall data of 33 Meteorological Stations over entire river basin for a period of 1980 to 2013 (34 years) is used in the study. The procedure used for drought analysis by SPI and RDI is discussed below. 3.1. Standardized Precipitation Index (SPI) The SPI and its characteristics is explained by McKee et al. (1993) for drought monitoring and analysis [7]. The input data for SPI calculation is precipitation record at any location and the dataset is fitted on gamma probability density function. SPI is normalized by keeping mean value 0 and standard deviation value unity that is beneficial to identify wet and dry periods equally. For any observed precipitation data, probability is calculated from the gamma function and this is used to estimate the precipitation deviation by SPI normalized. Positive values of SPI shows greater precipitation and negative values shows lesser precipitation than average precipitation. = Where, P i = Precitation value, = average precipitation and, S = standard deviation. The drought event ends when the SPI becomes positive. The ranges of SPI values for different classification of drought conditions are given in table 2 [7]. (1) http://www.iaeme.com/ijciet/index.asp 716 editor@iaeme.com
Mani Kant Verma, Dr. M. K. Verma, Dr. L K Yadu, Dr. Meena Murmu Table 2 Classification of drought conditions according to the SPI values 3.2. Reconnaissance Drought Index (RDI) In this work RDI is used for drought index in addition of SPI. For this standardized form of RDI is used and is a precise technique to characterize a drought event for arid regions [3,5,6]. The RDI is based on two inputs such as cumulative precipitation (based on observed precipitation) and potential evapotranspiration (PET, calculated by Thornthwaite formula). The RDI is calculated in a similar way as explained for SPI index. 4. RESULTS AND DISCUSSION The series result of SPI groups such as Extremely wet, Very wet, Moderately wet, Near normal, Moderately dry, Severely dry and Extremely dry are shown in Figures 2 and 3. From result it can be observed that the actual climate tendency in characterized by increasing of normal and wet periods. According to SPI 12month indicator, only 94% of the last 33 years are characterized by light and medium drought, the doughtiest period being the one between 200809. SPI Extremely wet Very wet Moderately wet Near normal Moderately dry Severely dry Extremely dry 0% 3% 0% 3% 0% 0% 94% Figure 2 Frequency of drought periods (SPI 12month) 2.00 spi 1.00 0.00 1.00 spi 2.00 Figure 3 12month SPI values for Seonath basin http://www.iaeme.com/ijciet/index.asp 717 editor@iaeme.com
Drought Analysis in the Seonath River Basin using Reconnaissance Drought Index and Standardised Precipitation Index The result of RDI 12 is shown in Figures 4 and 5. From these graphs it is observed that the actual climate tendency in characterized by increasing of normal and wet periods. According to RDI 12month indicator, only 93% of the last 33 years are characterized by light and medium drought, the doughtiest period being the one between 200809. RDI Extremely wet Very wet Moderately wet Near normal Moderately dry Severely dry Extremely dry 3% 0% 0% 0% 0% 4% 93% Figure 4 Frequency of drought periods (RDI 12month) 1.50 1.00 0.50 0.00 0.50 1.00 1.50 2.00 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 RDI 1998 1999 2000 200 1 2002 200 3 2004 200 5 2006 200 7 2008 2009 2010 2011 2012 2013 RDI Figure 5 12month RDI values for Seonath basin 5. CONCLUSION The result shows from the above analysis that mainly Semertal, Raipur, Bilaspur, Durg, Kendri are drought prone region. The year 200809 was the doughtiest year for the Seonath basin. Data driven models, can be effective in forecasting drought in the Seonath River Basin. This software also use as a shortterm drought indicator that is closely linked with agricultural drought, is forecast well, and these forecasts can find great application in the Seonath River Basin as a whole given the importance of agriculture in the region. The forecasts for SPI 12 and RDI are even better and can be utilized as longterm planning tools for water resource managers within the country. REFERENCES [1] Drought in India, Poorest Areas Civil Society (PACS) Programme, 2008. [2] http://www.tropmet.res.in/~kolli/mol/monsoon/historical/air.html [3] Tigkas D, Vangelis H, Tsakiris G. DrinC: software for drought analysis based on drought indices. Earth Science Informatics. 2015 Sep 1;8(3):697709. http://www.iaeme.com/ijciet/index.asp 718 editor@iaeme.com
Mani Kant Verma, Dr. M. K. Verma, Dr. L K Yadu, Dr. Meena Murmu [4] Maliva RG, Missimer TM. Arid lands water evaluation and management. Springer Science & Business Media; 2012 Jun 9. [5] Shah R, Manekar VL, Christian RA, Mistry NJ. Estimation of Reconnaissance Drought Index (RDI) for Bhavnagar District, Gujarat, India. World Academy of Science, Engineering and Technology, International Journal of Environmental, Chemical, Ecological, Geological and Geophysical Engineering. 2013 Jul 22;7(7):50710. [6] Vangelis H, Tigkas D, Tsakiris G. The effect of PET method on Reconnaissance Drought Index (RDI) calculation. Journal of Arid Environments. 2013 Jan 31; 88:13040. [7] McKee TB, Doesken NJ, Kleist J. The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology 1993 Jan 17 (Vol. 17, No. 22, pp. 179183). Boston, MA: American Meteorological Society. [8] Ali Jassim Mohammed Salih and Dr. Omran Issa Mohammed, Estimating Reference Evapotranspiration for Middle Euphrates Area Using Artificial Neural Networks (ANNs). International Journal of Civil Engineering and Technology (IJCIET), 7(6), 2016, pp.215 226 [9] Prof. G. Bogayya Naidu, Prof. K. V. SivaKumar Babu and Prof. V. Srinivasulu. Evaluation of Reference Evapotranspiration Estimation Methods and Development of Crop Coefficient Models. International Journal of Civil Engineering and Technology (IJCIET), 6 (11), 2015, pp. 71 75. http://www.iaeme.com/ijciet/index.asp 719 editor@iaeme.com