Assessment of Variability in Hydrological Droughts Using the Improved Innovative Trend Analysis Method

Author:

Ashraf Muhammad Shehzad12,Shahid Muhammad3ORCID,Waseem Muhammad1ORCID,Azam Muhammad4ORCID,Rahman Khalil Ur5ORCID

Affiliation:

1. Centre of Excellence in Water Resources Engineering, University of Engineering & Technology, GT-Road, Lahore 54890, Pakistan

2. Department of Civil Engineering, University of Central Punjab, Lahore 54590, Pakistan

3. Department of Civil Engineering, University of Engineering & Technology, Lahore 54890, Pakistan

4. Faculty of Agricultural Engineering and Technology, PMAS Arid Agriculture University, Rawalpindi 46000, Pakistan

5. State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China

Abstract

The use of hydro-climatological time series to identify patterns is essential for comprehending climate change and extreme events such as drought. Hence, in this study, hydrological drought variability based on the standard drought index (SDI) using DrinC was investigated at ten (10) hydrological stations in the Upper Indus River Basin (UIRB) of Pakistan on a monthly timescale for a period of 1961–2018. Moreover, the applicability of the improved innovative trend analysis by Sen Slope method (referred hereafter as the IITA) method was evaluated in comparison with innovative trend analysis (ITA) and Mann–Kendall (MK). The findings demonstrated a significant decreasing trend in the hydrological drought from October to March; on the other hand, from April through September, a significant increasing trend was observed. In addition to that, the consistency of the outcomes across the three trend analysis methods was also observed in most of the cases, with some discrepancies in trend direction, such as at Kharmong station. Conclusively, consistency of results in all three trend analysis methods showed that the IITA method is reliable and effective due to its capability to investigate the trends in low, median, and high values of hydrometeorological timeseries with graphical representation. A degree-day or energy-based model can be used to extend the temporal range and link the effects of hydrological droughts to temperature, precipitation, and snow cover on a sub-basin scale.

Funder

Shuimu Scholar Program of Tsinghua University

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction

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