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

Muhammad Shehzad Ashraf, Muhammad Shahid, Muhammad Waseem, Muhammad Azam and Khalil Ur Rahman ()
Additional contact information
Muhammad Shehzad Ashraf: Centre of Excellence in Water Resources Engineering, University of Engineering & Technology, GT-Road, Lahore 54890, Pakistan
Muhammad Shahid: Department of Civil Engineering, University of Engineering & Technology, Lahore 54890, Pakistan
Muhammad Waseem: Centre of Excellence in Water Resources Engineering, University of Engineering & Technology, GT-Road, Lahore 54890, Pakistan
Muhammad Azam: Faculty of Agricultural Engineering and Technology, PMAS Arid Agriculture University, Rawalpindi 46000, Pakistan
Khalil Ur Rahman: State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China

Sustainability, 2023, vol. 15, issue 11, 1-20

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.

Keywords: hydrological drought; Upper Indus River Basin; trend; Mann–Kendall (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/11/9065/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/11/9065/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:11:p:9065-:d:1163437

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().