郝增超副教授
电话：
E-mail：haozc@bnu.edu.cn
研究方向：水文学及水资源
个人履历
教育经历：
2001.9-2005.7 中国农业大学，学士
2005.9-2007.7 清华大学，硕士
2007.9-2012.5 德州农工大学，博士

工作经历：
2012.6-2013.12 加州大学欧文分校，博士后
2014.1-2014.09 俄克拉何马大学，博士后
2014.10- 北京师范大学，讲师

科学研究
主要研究领域：
干旱监测、预报与风险分析
气候变化与极值
流域水文模拟
代表性研究项目：
集合干旱预报方法及其在华北地区的应用（国家自然科学基金），2017-2019 (主持)
代表性论文：
Hao, Z., Y. Xia, L. Luo, et al. (2017). Toward a categorical drought prediction system based on U.S. Drought Monitor (USDM) and climate forecast. Journal of Hydrology, 551: 300–305.
Hao, Z., X. Yuan, Y. Xia (2017). An overview of drought monitoring and prediction systems at regional and global scales. Bulletin of the American Meteorological Society, in press.
Hao, Z., F. Hao, V. P. Singh, et al. (2017). An integrated drought package for drought monitoring, prediction and analysis to aid drought modeling and assessment. Environmental modeling & software, 91: 199-209
Hao, Z., F. Hao, V. P. Singh, et al. (2016). Probabilistic prediction of hydrologic drought using a conditional probability approach based on the meta-Gaussian model. Journal of Hydrology, 542：772–780
Hao, Z., F. Hao, V. P. Singh, et al. (2016). A theoretical drought classification method for the multivariate drought index based on distribution properties of standardized drought indices. Advances in Water Resources, 92:240–247
Hao, Z., F. Hao and V. P. Singh (2016). A general framework for the multivariate multi-index drought prediction based on multivariate Ensemble Streamflow Predictions (ESP). Journal of Hydrology, 539: 1-10.
Hao, Z., F. Hao, Y. Xia et al. (2016). A statistical method for categorical drought prediction based on NLDAS-2. Journal of Applied Meteorology and Climatology,55(4): 1049-1061
Hao, Z., and V.P. Singh. (2015). Review of dependence modeling in hydrology and water resources. Progress in Physical Geography，40(4): 549-578.
Hao, Z., Y. Hong, Y. Xia et al. (2015). Probabilistic drought characterization in the categorical form using ordinal regression Model. Journal of Hydrology, 535: 331–339.
Hao, Z. and V. P. Singh (2015). Drought characterization from a multivariate perspective: A review, Journal of Hydrology, 527: 668–678.
Hao, Z. and V. P. Singh (2015). Integrating entropy and copula theories for hydrologic modeling and analysis, Entropy, 17, 2253-2280.
Hao, Z. et al. (2014). Global integrated drought monitoring and prediction system. Scientific Data. 1:140001 doi: 10.1038/sdata.2014.1
Hao, Z. and A. AghaKouchak (2014). A nonparametric multivariate multi-index drought monitoring framework, Journal of Hydrometeorology, 15, 89–101.
Hao, Z. et al (2013). Changes in concurrent monthly precipitation and temperature extremes, Environmental Research Letter, 8, 034014.
Hao, Z. and V. P. Singh (2013), Modeling multi-site streamflow dependence with maximum entropy copula, Water Resources Research, 49.
Hao, Z. and A. AghaKouchak (2013), Multivariate Standardized Drought Index: a multi-index approach for drought analysis, Advances in Water Resources, 57, 12–18.
Hao, Z., and V. P. Singh (2013), Entropy-based method for extreme rainfall analysis in Texas, Journal of Geophysical Research: Atmospheres, 118.
Hao, Z. and V. P. Singh (2013), Entropy based method for drought analysis, Journal of Hydrologic Engineering, 18(7):780–786.
Hao, Z. and V. P. Singh (2011), Single-site monthly streamflow simulation using entropy theory, Water Resources Research, 47, W09528.
郝增超，尚松浩.基于栖息地模拟的河道生态需水量多目标评价方法及其应用［Ｊ］.水利学报, 2008, 39(5): 557-561

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