Water Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot 010018, China; Inner Mongolia Water Resource Protection and Utilization Key Laboratory, Hohhot 010018, China.
Water Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot 010018, China; Inner Mongolia Water Resource Protection and Utilization Key Laboratory, Hohhot 010018, China.
Sci Total Environ. 2020 Jan 10;699:134278. doi: 10.1016/j.scitotenv.2019.134278. Epub 2019 Sep 4.
The aim of this paper is to propose a new non-stationarity hydrological drought index, which incorporates the climate-driven and human-induced non-stationarities in streamflow. For this purpose, significant teleconnection indices have been selected by correlation analysis to represent large-scale climate variability, and human-induced indices have been calculated using the Soil and Water Assessment Tool (SWAT) to indicate varying anthropogenic forcing. Whereafter, a non-stationary probability model fitted to streamflow series has been developed using the climate-driven and human-induced indices as covariates. Base on the non-stationary model, we present a variation of the classical Standardized Streamflow Index (SSI), named Non-stationary Standardized Streamflow Index (NSSI). Focusing on the streamflow records of Luanhe River basin from 1958 to 2011, a comparison of performance between NSSI and SSI has been conducted to demonstrate the capability of the NSSI. Finally temporal-spatial patterns of drought during the last 40 years over the basin have been estimated by using the NSSI. The results show that the non-stationary model describes the variability of streamflow better than a stationary one, and the covariates selected with Akaike information criterion (AIC) provide insights into non-stationary behaviors. Since the NSSI effectively accounts for the non-stationarities of streamflow associated with climate changes and human activities, it provides more reasonable and satisfactory results than the SSI. Additionally, it is indicated that serious long-term droughts generally appeared more frequently in the southeast of Luanhe River basin, and an obvious aggravating tendency of drought was observed in this area during 1971-2011. The presented NSSI enables hydrological droughts to be better characterized in a non-stationary context, thus providing valuable references for the improvement of drought index and the drought related policy-making.
本文旨在提出一种新的非平稳水文干旱指数，该指数综合考虑了气候驱动和人类活动引起的径流动态变化。为此，通过相关分析选择了具有显著遥相关关系的指数来表示大尺度气候变异性，并用土壤和水评估工具（SWAT）计算了人类活动指数，以指示不同的人为强迫。随后，利用气候驱动和人为驱动指数作为协变量，建立了适用于径流序列的非平稳概率模型。在此基础上，提出了经典标准化径流指数（SSI）的一种变体，称为非平稳标准化径流指数（NSSI）。以 1958 年至 2011 年滦河流域的径流记录为例，对 NSSI 和 SSI 的性能进行了比较，以验证 NSSI 的性能。最后，利用 NSSI 估算了流域过去 40 年的干旱时空分布。结果表明，非平稳模型比平稳模型更能描述径流动态变化，而基于赤池信息量准则（AIC）选择的协变量则可以深入了解非平稳行为。由于 NSSI 有效地考虑了气候变化和人类活动引起的径流非平稳性，因此它提供了比 SSI 更合理和令人满意的结果。此外，研究表明，严重的长期干旱一般更频繁地出现在滦河流域的东南部，并且在 1971 年至 2011 年期间，该地区的干旱情况明显加剧。提出的 NSSI 能够在非平稳背景下更好地描述水文干旱，为干旱指数的改进和干旱相关政策的制定提供了有价值的参考。
