Modeling multivariate standardized drought index based on the drought information from precipitation and runoff: a case study of Hare watershed of Southern Ethiopian Rift Valley Basin

被引：26

作者：

Yisehak, Biniyam ^{[1
]}

Zenebe, Amanuel ^{[2
]}

机构：

[1] Mekelle Univ, Inst Climate & Soc, POB 231, Mekelle, Tigray, Ethiopia

[2] Mekelle Univ, Land Resource Management & Environm Protect, Mekelle, Tigray, Ethiopia

来源：

MODELING EARTH SYSTEMS AND ENVIRONMENT | 2021年 / 7卷 / 02期

关键词：

Standardized precipitation index; Standardized runoff index; Multivariate standardized drought index; Joint probability distribution; Drought characteristics;

D O I：

10.1007/s40808-020-00923-6

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Drought is below-normal availability of rainfall, runoff, and or soil moisture for a prolonged period in a given region. Modeling drought index using multiple variables is important for future hydrological drought monitoring and sustainable water resource management. This study aimed to model multivariate standardized drought index (MSDI) based on the drought information from precipitation and runoff. Long year (1980-2014) monthly observed precipitation and runoff data were used to analyzed standardized precipitation index (SPI) and standardized runoff index (SRI) respectively. The best-fit copula family was selected to construct the joint probability distribution (JPD) of the SPI and SRI, and MSDI was developed. SPI, SRI, and MSDI at 6 and 12-month drought time scales were analyzed to characterize hydrological drought properties. The correlation among three drought indices (SPI, SRI, and MSDI) were analyzed using the Pearson correlation method. The goodness-of-fit test result showed that the Clayton copula was found the best-fitted copula function in describing JPD the two drought indices. The MSDI showed that the drought onset most likely similar to the SPI. Moreover, MSDI showed the maximum duration of drought occurred with varying severities about 26-28-months, while the duration of drought is extensive, but the frequency of drought less relative to SPI and SRI. The developed model, MSDI had a high correlation with SPI and SRI (R > 0.7 and R-2>0.5,p similar to 0.0) compared to the correlation between SPI and SRI. Therefore, modeling hydrological drought using multiple variables is better than estimated with a single variable.

引用

页码：1005 / 1017

页数：13

共 45 条

[1]

Abramowitz M., Stegun I.A., Handbook of Mathematical Functions: With Formulas, Graphs, and Mathematical Tables 55 (Courier Corporation). 3Rd Ed, (1965)

[2]

Aho K., Derryberry D., Peterson T., Model selection for ecologists: the worldviews of AIC and BIC, Ecology, 95, pp. 631-636, (2014)

[3]

Akaike H., A new look at the statistical model identification. Sel. Pap.s Hirotugu Akaike, pp. 215-222, (1974)

[4]

Belayneh A., Adamowski J., Khalil B., Ozga-Zielinski B., Long-term SPI drought forecasting in the Awash River Basin in Ethiopia using wavelet neural network and wavelet support vector regression models, J Hydrol, 508, pp. 418-429, (2014)

[5]

Bisht D.S., Sridhar V., Mishra A., Chatterjee C., Raghuwanshi N.S., Drought characterization over India under projected climate scenario, Int J Climatol, 39, pp. 1889-1911, (2019)

[6]

Dai A., Zhao T., Chen J., Climate change and drought: a precipitation and evaporation perspective, Curr Clim Chang Rep, 4, pp. 301-312, (2018)

[7]

Dash S.S., Sahoo B., Raghuwanshi N.S., A SWAT-Copula based approach for monitoring and assessment of drought propagation in an irrigation command, Ecol Eng, 127, pp. 417-430, (2019)

[8]

Edossa D.C., Babel M.S., Das G.A., Drought analysis in the Awash river basin, Ethiopia, Water Resour Manag, 24, pp. 1441-1460, (2010)

[9]

Edwards D.C., Characteristics of 20th Century drought in the United States at multiple time scales, Air Force Inst of Tech Wright-Patterson AFB OH, (1997)

[10]

Division F and AO of the UNL and WD. The soil and terrain database for Northeastern Africa: crop production system zones of the IGAD subregion, (1998)

← 1 2 3 4 5 →