Integrated Monitoring of Hydro–Meteorological Droughts in Kasilian's Basin (Mazandaran Province)

Authors

1 M.Sc. Graduated, Department of Irrigation and Reclamation Engineering, Natural Resources and Agricultural Campus, University of Tehran, Karaj, Iran

2 Assistant Professor, Department of Irrigation and Reclamation Engineering, Natural Resources and Agricultural Campus, University of Tehran, Karaj, Iran

3 Associate Professor, Department of Irrigation and Reclamation Engineering, Natural Resources and Agricultural Campus, University of Tehran, Karaj, Iran

Abstract

Drought is a temporary status of water deficit with respect to its long term average condition. Combined Drought Indices (CDIs) are new tools to evaluate general status of drought in a region. In this study, we focus on the integrated monitoring of meteorological droughts (based on temperature and precipitation data) and hydrological droughts (only based on streamflow data) in the Kasilian's basin. The main goal of the investigation is to present a combined drought index called Hydro–Meteorological Drought Index (HMDI) using Principal Component Analysis (PCA) in the basin. PCA is a multivariate technique to reduce dimensionality of data in a number of principal components. The Standardized Precipitation Index (SPI) and the Standardized Precipitation–Evapotranspiration Index (SPEI) were applied to monitor meteorological droughts and the Streamflow Drought Index (SDI) for monitoring hydrological droughts. The data were gathered from the meteorological and hydrometric stations located in Kasilian's basin for the period 1349–50 to 1391–92 as the water year. The station Derzikola (in the upstream) was selected for meteorological analysis and two stations Valikbon and Shirgah were employed to analyze hydrologic drought conditions in the upstream and downstream of the basin, respectively. The preliminary controls on the quality of available data were accomplished using some statistical tests for randomness, normality, adequacy of record length, outliers and temporal trend. Employing 49 probability distributions showed that Wakeby is the best fit distribution for precipitation and streamflow data and General Extreme Value for the difference series of precipitation minus evapotranspiration. The meteorological (SPI and SPEI) and hydrological (SDI) drought indices were calculated at four time windows including 3, 6, 9 and 12 months (each of which starts from the month Octobr). In the next stage, for calculation of hydro–meteorological droughts, using PCA technique, two combined drought indices including SPI–SDI and SPEI–SDI were built. The combined indices, which are the standardized form of the first principal component (PC1), was individually calculated at upstream (for hydrometric station of Valikbon) and downstream (for hydrometric station of Shirgah) of the basin. PC1s were able to explain 74.3–87.9% of variabilities in data. The PC1 of the combination SPEI–SDI explained more variability than the SPI–SDI, both in upstream and in downstream of the basin. This may be related to the high correlation of SPEI and SDI series. The results showed that, for identification of dry years, SPEI–SDI is more successful than SPI–SDI at the upstream station. Therefore, combination of two indices with high correlation made satisfactory results in detecting overall status of droughts in the basin of interest. On the other hand, both combined drought indices have no differences in monitoring droughts at the downstream station. Also, during continuing dry periods, combined indices indicated drought status one month earlier in comparison with single indices. Accordance of the classified series of SPI and SPEI with combined drought indices was higher at larger time scales than smaller ones. This may be due to smoother series of single drought indices at larger time scales as well as high correlation level between indices employed in constructing HMDI.

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References

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Journal of the Earth and Space Physics
Volume 44, Issue 2
July 2018
Pages 463-477

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