Drought assessment based on the long-term stability of temperature and precipitation in Ardabil DareRood basin

Document Type : Complete scientific research article


1 Ph.D. student of Climate Hazards, University of Mohaghegh Ardebili, Ardabil, Iran.

2 Assistant Professor, Department of Geography, University of Mohaghegh Ardabil, Iran

3 Associate Professor of Geomorphology, University of Mohaghegh Ardebili, Ardabil, Iran.

4 Associate Professor at the Department of Natural Resources, University of Mohaghegh Ardebili, Ardabil, Iran

5 Professor of Climatology, Faculty of Geography and Planning, Tabriz University, Tabriz, Iran


Background and objectives: One of the most important natural hazards that is affecting a large number of people, due to extensive damage, is drought. Drought is also a phenomenon directly related to the issue of water scarcity and because of its reversibility, it can affect the various aspects of human life and the environment. The drought affects almost all the determinants of the hydrological cycle from the onset of precipitation and then the surface water flow and eventually storage in groundwater. Therefore, in this research, due to the results of the stable process of precipitation and temperature in the Ardabil DareRood basin, SPI Index which relies on precipitation, with the RDI index which combines the parameters of potential evapotranspiration and precipitation, were compared and evaluated in different time intervals.
Materials and methods: In this study, in order to identify drought and wet periods, it was used from monthly precipitation data, Minimum and maximum monthly temperature for seven synoptic stations, for a 30 years (1985-2014) in the Ardabil DareRood basin in the northwest of Iran. In order to identify the trend in the precipitation and temperature series in this research was used Man-Kendall (MK) and Sen's slope (Sen) models. Also, to assess the long-term stability of the trend in the time series was used the LOWESS curve (at a significant level of 5%). Also using Aridity index, four stations in the arid area and three stations in the semi-arid region were established. In order to calculate the RDI index, the values of potential evapotranspiration were use. The amount of PET in the RDI index using monthly temperature values, and was obtained by the Hargreaves method. Finally, SPI and RDI indices were compared in 3, 6, 9, and 12-month scales.
Results: The results of the LOWESS curve showed that the annual temperature at all stations follows an incremental scenario. While the precipitation behaves differently and often is decreasing. The results also showed that SPI and RDI indices are very similar in different time scales, and R2 is in most cases greater than 0.90. The extreme drought the observed in SPI and RDI models is related to the Ardabil station in 2010-2011 on a 3-month scale, whose values were respectively -3/11 and -3/09. Also, the results showed that the RDI index that Extreme and severe wet values it’s larger than SPI. Eventually, both indices are many similarities with each other but because of RDI's use of PET, It can be used more widely for arid and semi-arid regions of Iran
Conclusion: this research, two SPI and RDI indices were used to compare the drought events in the DarehRood Ardabil basin of the northwest of Iran.Due to the dry and semi-arid climate of most regions of Iran, It is very probable that the amount of precipitation is zero in some seasons. Therefore precipitation-based indices such as SPI may have less efficiency than RDI index, which, in addition to rainfall, uses potential evapotranspiration (PET) in their formulation. Considering the importance of PET parameter in agriculture and water resources management in Iran, It is necessary to examine the RDI index in other regions of Iran, such as the northwest and mountainous regions of Iran and its results can be compared with other indicators such as the important and highly applicable SPI indicator.


1.Ahmad, L., Parvaze, S., Majid, M., and Kanth, R.H. 2016. Analysis of Historical Rainfall Data for Drought Investigation Using Standard Precipitation Index (SPI) Under Temperate Conditions of Srinagar Kashmir. Pak. J. Meteorol. 13: 25. 29-38.
2.Cleveland, W.S. 1979. Robust locally weighted regression and smoothing scatterplots. J. Amer. Statist. Assoc.
74: 829-836.
3.Dastorani, M.T., Massah Bavan, A.R., Poormohammadi, S., and Rahimian, M.H. 2011. Assessment of potential climate change impacts on drought indicators (Case study: Yazd station, Central Iran). Desert. 16: 2. 159-167.
4.Edwards, D.C., and McKee, T.B. 1997. Characteristics of 20th century drought in the United States at multiple time scales. Climatology Rep. 97-2, Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado. 585p.
5.Feng, G., Cobb, S., Abdo, Z., Fisher, D.K., Ouyang, Y., Adeli, A., and Jenkins, J.N. 2016. Trend analysis and forecast of precipitation, reference evapotranspiration and rainfall deficit in the Blackland Prairie of Eastern Mississippi. J. Appl. Meteorol. Climatol. 55: 1425-1439.
6.Gąsiorek, E., and Musiał, E. 2015. Evaluation of the Precision of Standardized Precipitation Index (SPI) Based on Years 1954-1995 in Łódź. J. Ecol. Engin. 16: 4.
7.Hargreaves, G.H., and Samani, Z.A. 1985. Reference crop evapotranspiration from temperature. Applied Engineering in Agriculture. 1: 2. 96-99.
8.Hayes, M.J., Wilhelmi, O.V., and Knutson, C.L. 2004. Reducing drought risk: bridging theory and practice. Natural Hazards Review. 5: 2.106-113.
9.Helsel, D.R., and Hirsch, R.M. 1992. Statistical Methods in Water Resources. Elsevier, Amsterdam.
10.Kendall, M.G. 1975. Rank Correlation Methods, Charles Griffin, London.
11.Khalili, D., Farnoud, T., Jamshidi, H., Kamgar-Haghighi, A.A., and Zand-Parsa, S. 2011. Comparability analyses of the SPI and RDI meteorological drought indices in different climatic zones. Water Resources Management. 25: 6. 1737-1757.
12.Khan, M.I., Liu, D., Fu, Q., Dong, S., Liaqat, U.W., Faiz, M.A., and Hu, Y. and Saddique, Q., 2016. Recent climate trends and drought behavioral assessment based on precipitation and temperature data series in the Songhua River basin of China. Water resources management. 30: 13. 4839-4859.
13.Kogan, F.N. 2000. Contribution of remote sensing to drought early warning. Early Warning Systems for Drought Preparedness and Drought Management, Proceedings of an expert group meeting held on Warning Systems for Drought Preparedness and Drought Management. Edited by D.A. Wilhite, M.V.K. Sivakumar, and D.A. Wood. Lisbon, Portugal, Pp: 75-87.
14.Kousari, M.R., Dastorani, M.T., Niazi, Y., Soheili, E., Hayatzadeh, M., and Chezgi, J. 2014. Trend Detection of Drought in Arid and Semi-Arid Regions of Iran Based on Implementation of Reconnaissance Drought Index (RDI) and Application of Non-Parametrical Statistical Method. Water Resour Manage. 28: 1857-1872.
15.Lloyd‐Hughes, B., and Saunder, M.A. 2002. A drought climatology for Europe. Inter. J. Climatol. 22: 13. 1571-1592.
16.Mann, H.B. 1945. Nonparametric tests against trend. Econometrica. 13: 245-259.
17.McKee, T.B., Doesken, N.J., and Kleist, J. 1993. January. The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology (Vol. 17, No. 22, pp. 179-183). Boston, MA: American Meteorological Society.
18.Merabti, A., Martins, D.S., Meddi, M., and Pereira, L.S. 2018. Spatial and time variability of drought based on SPI and RDI with various time scales. Water Resources Management. 32: 1087.
19.Neelakanth, J.K., Balakrishnan, P., Muthuchamy, I., and Tamilmanai, D. 2017. Assessment of drought using standardized precipitation index (SPI) for Koppal district, Karnataka, India. Environment and Ecology. 35: 3. 1665-1668.
20.Rahmat, S., Jayasuriya, N., and Bhuiyan, M. 2015. Assessing droughts using meteorological drought indices in Victoria, Australia. Hydrology Research. 46: 3. 463-476.
21.Rahmat, S.N. 2015. Methodology for development of drought severity-duration-frequency (SDF) Curves. Ph.D. Thesis, School of Civil, Environmental and Chemical Engineering, RMIT University, Melbourne, Australia.
22.Rossi, G., Vega, T., Bonaccorso, B., Eds. 2007. Methods and tools for drought analysis and management
(Vol. 62). Springer Science & Business Media.
23.Safiolea, E., Tsakiris, V., Vangelis, H., Verbeiren, B., and Huysmans, M. 2015. Analysing drought characteristics in recharging areas of Belgian aquifers. European Water. 50: 59-72.
24.Shishutosh Barua, S.M.A.S.C.E., Ng, A.W.M., and Perera, B.J.C. 2010. Comparative evaluation of drought indexes: case study on the Yarra River catchment in Australia. J. Water Resour. Plan. Manage. 137: 2. 215-226.
25.Surendran, U., Kumar, V., Ramasubramoniam, S., and Raja, P. 2017. Development of drought indices for semi-arid region using drought indices calculator (DrinC)–A case study from Madurai District, a semi-arid region in India. Water Resources Management. 11: 13. 3593-3605.
26.Taxak, A.K., Murumkar, A.R., and Arya, D.S. 2014. Long term spatial and temporal rainfall trends and homogeneity analysis in Wainganga basin, Central India. Weather and Climate Extremes. 4: 50-61.
27.Tigkas, D., and Tsakiris, G. 2015. Early estimation of drought impacts on rainfed wheat yield in Mediterranean climate. Environmental Processes. 2: 1. 97-114.
28.Tigkas, D., Vangelis, H., and Tsakiris, G. 2012. Drought and climate change impact on streamflow in small watersheds. Science of the Total Environment. 440: 33-41.
29.Tigkas, D., Vangelis, H., and Tsakiris, G. 2013. The RDI as a composite climatic index. European Water. 41: 17-22.
30.Tigkas, D., Vangelis, H., and Tsakiris, G. 2016. Introducing a modified reconnaissance drought index (RDIe) incorporating effective precipitation. Procedia Engineering. 162: 332-339.
31.Tsakiris, G. 2017. Drought risk assessment and management. Water Resources Management. 31: 10. 3083-3095.
32.Tsakiris, G., Nalbantis, I., Vangelis, H., Verbeiren, B., Huysmans, M., Tychon, B., Jacquemin, I., Canters, F., Vanderhaegen, S., Engelen, G., Poelmans, L., De, Becker, P., and Batelaan, O. 2013. A system- based paradigm of drought analysis for operational management. Water Resources Management. 27: 10. 5281-5297.
33.Tsakiris, G., Pangalou, D., and Vangelis, H., 2007. Regional Drought Assessment Based on the Reconnaissance Drought Index (RDI). Water Resources Management, 21: 5. 821-833.
34.Tsakiris, G., and Vangelis, H. 2005. Establishing a drought index incorporating evapotranspiration. European Water. 9: 10. 3-11.
35.Ueangsawat, K., Nilsamranchit, S., and Jintrawet, A. 2016. Comparison of estimation methods for Daily reference evapotranspiration under Limited Climate data in Upper Northern Thailand. Environ. Natur. Resour. J. 14:2. 10-23. DOI: 10.14456/ennrj.2016.9.
36.Wilhite, DA. 1993. The enigma of drought. Drought Assessment, Management and Planning: Theory and Case Studies. Kluwer Academic Publishers, Boston, Ma, Pp: 3-15.
37.Yue, S., and Wang, C.Y. 2004. The mann-kendall test modified by effective sample size to detect trend in serially Correlated hydrological series. Water Resource Management. 18: 201-218.
38.Yue, S., Pilon, P., Phinney, B., and Cavadias, G.S. 2002. The influence of autocorrelation on the ability to detect trend in hydrological series. Hydrological Processes. 16: 1807-1829.
39.Zarch, M.A.A., Malekinezhad, H., Mobin, M.H., Dastorani, M.T., and Kousari, M.R. 2011. Drought monitoring by reconnaissance drought index (RDI) in Iran. Water resources management. 25: 13. 3485.
40.Zarei, A.R., Moghimi, M.M., and Mahmoudi, M.R. 2016. Analysis of changes in spatial pattern of drought using RDI index in south of Iran. Water resources management. 30: 11. 3723-3743.
41.Zehtabian, G., Karimi, K., Mirdashtvan, M., and Khosravi, H. 2013. Comparability Analyses of the SPI and RDI Meteorological Drought Indices in South Khorasan Province in Iran. Inter. J. Adv. Biol. Biom. Res. 1: 9. 981-992.