Hydrogeomorphology
fatemeh menbari; Amjad Maleki; nayyeri hadi
Abstract
Morphometric analysis of a drainage basins and river network plays an vital role in understanding the hydrogeological behavior of the drainage basin . Therefore, the current research was conducted with the aim of modeling flood and its relationship with morphometric variables using multivariate regression. ...
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Morphometric analysis of a drainage basins and river network plays an vital role in understanding the hydrogeological behavior of the drainage basin . Therefore, the current research was conducted with the aim of modeling flood and its relationship with morphometric variables using multivariate regression. The research method is based on the destruction of morphometric parameters and statistical analysis, including correlation coefficient and linear regression analysis. In this regard, first, the studied basins have been selected using ARC GIS 10.5 software, and the limits of each one has been determined. Then, their morphometric characteristics have been extracted. The Flood discharge has also been reconstructed in return periods of 2 to 500 years using easy-fit software. For modeling, first, the linear relationship between each morphometric variable as an independent variable with flood discharge as a dependent variable was investigated. After ensuring the linear relationship between variables and flood discharge, correlation between each variable and flood discharge was calculated. The variables with the highest correlation were watershed area, basin length, and surface flow length. Using multivariate regression, modeling was used for independent variables and flood discharge. The results show that as the return period increases, the relationship between independent variables and flood discharge increases, So that the correlation of the area with the return period of 25 years is 0.609 and with the return period of 200 years is 0.677.also, the proposed models have more validity for flood prediction using multivariate regression analysis in return periods above 25 to 500 years.
Amin Navidtalab; Ghasem Askari; Farahnaz Ahmadpour; Maryam Tahmasebi
Abstract
1-IntroductionOne of the most important issues, facing the human society and environment, is water resources management. Regarding the drought, this issue turns to a serious challenge for decision makers, and affect the the people more than other natural hazards (Hagman, 1984). Normally, drought occurs ...
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1-IntroductionOne of the most important issues, facing the human society and environment, is water resources management. Regarding the drought, this issue turns to a serious challenge for decision makers, and affect the the people more than other natural hazards (Hagman, 1984). Normally, drought occurs in all climatic conditions (Dai, 2010). Through the current research, we try to investigate drought in Lurestan Province using Percent of Normal precipitation Index (PNI) which evaluates meteorological drought (Hayes, 2006; Zargar et al., 2011). Lurestan Province located in the western Iran, and has an area of about 29,308 Km2. Geographically, it sits between northern latitudes of 32֯ 38' 39" and 34֯ 24' 17" and between eastern longitudes of 46֯ 52' 14" and 50֯ 01' 59". Climatic differences has led to the emergence of three conspicuous climates: (1) mountainous cold climate in the northern and eastern parts, (2) temperate climate in central parts, and (3) warm climate in the south and southeastern parts.2-MethodologyThe meteorological drought intensity is evaluated through different methods including Standardized Precipitation Index (SPI), Percent of Normal Index (PNI), Deciles Index (DI), Effective Drought Index (EDI), China-Z (CZI), Modified China-Z (MCZI), Rainfall Anomaly Index (RAI), Z-Score Index (ZSI), Palmer Drought Severity Index (PDSI), (Willeke et al., 1994; Byun and Wilhite, 1999; Hayes, 2006; Salehnia et al., 2017). To evaluate drought, a period of thirty-year (1988 – 2017) data were adopted from nine synoptic weather stations including Khorramabad, Borujerd, Aligudarz, Aleshtar, Noorabad, Poldokhtar, Kohdasht, Azna, and Dorud. For calculating PNI, the following equation has been applied (equ.1): PNI=P/P ̅ *100 (1)where PNI stands for Percent of Normal precipitation Index, P for annual precipitation (mm), P ̅ for average precipitation of the thirty-year period. PNI (%) ≤110 represents Moderately to Extremely wet climate, 80-110 Normal, 55-80 Moderately dry, 40-55 Very dry, and 40≥ Extremely dry (Morid et al., 2006).3-Resultsand DiscussionConsidering 67 years recorded data for Khorramabad, 32 years for Aligudarz, and 30 years for borujerd, these stations are considered as milestones to reconstruct the data for stations with lack of data for the thirty-year period of study. For other stations, 13 to 17 years of data were reconstructed (Table 1). To find the best reference station for incomplete stations, geographic and climatic resemblance with the stations of complete thirty-year period data was considered. Temperature, precipitation, De Martonne aridity index, and climatic classification by Iran Meteorological Organization (IMO) were evaluated for all stations to find similarities.Table (1): Reconstructed years of data for each station based on geographic and climatic resemblance with the stations of complete thirty-year period data. De Martonne classificat-ionIMO classificationAvail-able yearsReconstr-ucted yearsStation21.3Semi-aridModerately wet, warm summer, moderately cold winter670Khorramabad17.8Semi-aridModerately wet, temperate summer, very cold winter1713Azna18.4Semi-aridModerately wet, temperate summer, very cold winter320Aligudarz7.55Dry or AridModerately wet, warm summer, cold winter1713Dorud18.4Semi-aridModerately wet, warm summer, moderately cold winter300Borujerd18.6Semi-aridModerately wet, temperate summer, cold winter2010Aleshtar19.5Semi-aridModerately wet, temperate summer, very cold winter1713Noorabad14.8Semi-arid to AridModerately wet, warm summer, cold winter2010Kuhdasht10.9Dry or AridModerately wet, very warm summer, moderately cold winter1911Poldokhtar 4-ConclusionNone of stations show Extreme drought. Severe drought is observed in 6 stations with little percentages (3.3-6.6%). Weak droughts has been recorded between 6.6 to 30% in all stations (Table 2). Therefore, dried 80% of springs and rivers in Lurestan could not be solely resulted from meteorological drought in Lurestan. The role of water management in creating this crisis should not be neglected.Table (2): Percentage of different intensities of drought in the studied stationsModerately to Extremely dryNormalModerately dryVery dryExtermely dryStation23.343.3303.30Khorramabad3040236.60Azna26.643.323.36.60Aligudarz2066.36.66.60Dorud30502000Borujerd36.646.616.600Aleshtar36.636.626.600Noorabad33.340206.60Kuhdasht26.65016.66.60Poldokhtar Keywords: Meteorological drought, Drought intensity, drought prediction, Lurestan5- References Byun, H. R., Wilhite, D. A. 1999. Objective quantification of drought severity and duration. Journal of Climate, 12(9): 2747–2756.Dai, A. (2011), Drought under global warming: a review. WIREs Clim Change, 2: 45-65. doi:10.1002/wcc.81De Martonne, E. (1926). Aerisme, et índices d’aridite. Comptesrendus de L’Academie des Sciences, 182: 1395– 1398.Hagman, G. (1984). Prevention Better than Cure: Report on Human and Natural Disasters in the Third World, Stockholm: Swedish Red Cross.Hayes MJ. Drought indices. What Is Drought? Lincoln, Nebraska: National Drought Mitigation Center, 2006. Available at: http://drought.unl.edu/whatis/indices.htm. Salehnia, N., Alizadeh, A., Sanaeinejad, H., Bannayan, M., Zarrin, A., & Hoogenboom, G. (2017). Estimation of meteorological drought indices based on AgMERRA precipitation data and station-observed precipitation data. Journal of Arid Land, 9(6): 797-809.Willeke, G., Hosking, J. R. M., Wallis, J. R. (1994). The national drought atlas. In: Institute for Water Resources Report 94-NDS-4. U.S Army Corp of Engineers, CD-ROM. Norfolk, VA.Zargar, A., Sadiq, R., Naser, B., & Khan, F. I. (2011). A review of drought indices. Environmental Reviews, 19(NA): 333-349.
