Iran-Water Resources Research

Iran-Water Resources Research

Developing the Drought Index in Natural and Engineering Sub-basins (Case Study: Zayandehrood Basin)

Document Type : Original Article

Authors
1 Assistant Professor, Civil Engineering Department, Faculty of Engineering, University of Kashan, Kashan, Iran.
2 Professor, Department of Civil Engineering, Isfahan University of Technology, Isfahan, Iran.
Abstract
Due to the climate change, we nowadays are witnessing extreme water resources events such as droughts and floods in all parts of the world. Historically, dams are used for water storage, electricity production, and agricultural and industrial uses, which, along their advantages, causes environmental damage. Dams divide basins into engineering and natural basins, and so one of the goals of this research is to explain the differences and performance of these two types of basins in terms of water resources and drought indicators. To this end, this research reviewed and evaluated the existing indicators and provide an integrated index including the influencing factors of drought. Due to the strategic location of the Zayanderood basin in the central plateau of Iran, this basin is selected for the case study. The imbalance between resources and consumption, especially in recent years, is considered as the main factor aggravating drought. Integrated drought index includes various factors in terms of meteorological and hydrological factors, and the index is validated using agricultural factors and variables. The results showed that in natural watersheds, a comprehensive estimate of the drought situation can be obtained by using changes in rainfall or evaporation, although drought estimation using the bivariate index shows better results and performance. In the engineering basins, the bivariate index has a better performance than the indices based solely on rainfall or evaporation and creates a greater correlation with the validation index based on the agricultural drought index.
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Abedi-Koupai J (2011) Zoning of drought in Isfahan province and strategies to reduce the effect of water scarcity. Drought, Zayandehrood, solutions and challenges. Isfahan Governorate Crisis Management Department (In Persian)
Hao Z, AghaKouchak, A (2013) Multivariate Standardized Drought Index: A parametric multi-index model. Advances in Water Resources 57:12–18
Huang S, Chang J, Leng G, Huang Q (2015) Integrated index for drought assessment based on variable fuzzy set theory: A case study in the Yellow River basin, China. Journal of Hydrology 527:608–618
Jing LP, Michael LN, Huang JZ (2007) An entropy weighting k-means algorithm for subspace clustering of high-dimensional sparse data. IEEE Trans. Knowledge Data Eng 19(8):1026–1040
Karamouz M, Rasouli K, Nazif S (2009) Development of a hybrid index for drought prediction. Journal of Hydrologic Engineering 14:617-627
Karamouz M, Araghinejad Sh (2011) Advanced hydrology. Amirkabir University Press, 464p (In Persian)
Karamouz M, Ahmadi A, Fallahi M (2012) System engineering. Amirkabir University Press, 544p (In Persian)
Khoshoei Esfahani M, Safavi HR, Zamani AR (2016) Design of drought monitoring system based on integrated index in Zayanderood River Basin -Iran. Journal of Water and Soil Science, Isfahan University of Technology, 10.18869/acadpub.jstnar.20.75.27 (In Persian)
Liu XW (2007) Parameterized defuzzification with maximum entropy weighting function another view of the weighting function expectation method. Math Computer Modell 45(1–2):177–188
Liu L, Hong Y, Bednarczyk CN, Yong B, Shafer MA, Riley R, Hocker JE (2012) Hydro-climatological drought analyses and projections using meteorological and hydrological drought indices: A case study in Blue River Basin, Oklahoma.  Journal of Water Resources Management 26:2761–2779
Mckee TB, Doesken NJ, Kleist J (1993) The relationship of drought frequency and duration to time scales. Preprints 8th Conference on Applied Climatology, 179-184
Meng QS (1989) Information theory [M]. Xi’An Jiaotong University Press, Xi’An, pp. 19–36
Palmer WC (1965) Meteorological drought. U. S. Weather Bureau, Washington D.C, Research Paper, 45
Pandey RP, Pandey A, Galkate RV, Byun RH, Mal BC (2010) Integrating hydro-meteorological and physiographic factors for assessment of vulnerability to drought.  Journal of Water Resources Management 24:4199-4217
Pandey S, Pandey AC, Nathawat MS, Kumar M, Mahanti NC (2012) Drought hazard assessment using geoinformatics over parts of Chotanagpur plateau region, Jharkhand, India. Natural Hazards 63:279–303
Qiu WH (2002) Management decision and applied entropy. China Machine Press, Beijing, pp. 193–196
Rajsekhar D, Singh VP, Mishra AK (2014) Multivariate drought index: An information theory based approach for integrated drought assessment. Journal of Hydrology 526:164-182
Rouse JW, Hass RH, Deering DW, Shehell JA (1974) Monitoring the vernal advancement and retrogradation (Green wave effect) of natural vegetation. Final Rep, Rsc: 1978-4, Remote Sensing Center, Texas A & M University, College Station
Safavi HR, Khoshoei Esfahani M, Zamani AR (2014) Integrated index for assessment of vulnerability to drought, case study: Zayandehrood River Basin, Iran. Journal of Water Resources Management 28:1671–1688
Safavi HR, Raghibi V, Mazdiyasni O, Mortazavi-Naeini M (2018) A new hybrid drought-monitoring framework based on nonparametric standardized indicators. Hydrology Research 49(1):222–236
Shafer BA, Dezman LE (1982) Development of a Surface Water Supply Index (SWSI) to assess the severity of drought conditions in snowpack runoff areas. Proceeding of the Western Snow Conference, 164-175
Smith VA, Maidment DR (2008) Texas integrated drought information system. A Prototype of the Trinity River Basin. University of Texas at Austin
Waseem M, Ajmal M, Kim TW (2015) Development of a new composite drought index for multivariate drought assessment. Journal of Hydrology 527:30–37
Zou ZH, Yun Y, Sun JN (2006) Entropy method for determination of weight of evaluating in fuzzy synthetic evaluation for water quality assessment indicators. Journal of Environmental Science 18(5):1020–1023

  • Receive Date 18 January 2023
  • Revise Date 11 June 2023
  • Accept Date 27 June 2023