Spatiotemporal Analysis of Drought and Agriculture Standardized Residual Yield Series Nexuses across Punjab, Pakistan

Waseem, Muhammad; Jaffry, Ali Hasan; Azam, Muhammad; Ahmad, Ijaz; Abbas, Adnan; Lee, Jae-Eun

doi:10.3390/w14030496

Cited by 21 publications

(7 citation statements)

References 26 publications

(30 reference statements)

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“…These investigations, however, are primarily focused on agricultural drought, the temporal and geographical distribution of precipitation. Furthermore, these studies did not expressly address drought trends, whereas our emphasis is on drought trends analysis (Waseem et al, 2022;Ullah et al, 2023;Rahman et al, 2023). This study used SPI and SPEI values obtained across seven various time frames from 1981 to 2020 across 12 strategically selected meteorological stations to undertake an exhaustive investigation of drought trends in Punjab Province, Pakistan.…”

Section: Discussionmentioning

confidence: 99%

Analysing Spatiotemporal Drought Patterns in Punjab Province, Pakistan, Utilizing SPI and SPEI

Hussain,

Suliman

2023

Preprint

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The Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) are applied in this study to examine drought features at different Punjab Province stations. We examine drought occurrence through drought frequency, concentrating on spatial and temporal scales and considering different geomorphologies. A modified Mann-Kendall test and multiple linear regression are used to examine monthly data from 12 weather stations collected between 1980 and 2020. Stations at high elevations have very variable precipitation, which can lead to periodic droughts. Surprisingly, SPEI shows more drought sensitivity than SPI. The severity of the drought has decreased recently, especially after the 1998–2002 peak period. Correlation analysis demonstrates a substantial link between SPI and SPEI at high elevation stations, with Murree displaying the strongest correlation (0.9334) on a one-month time frame, and Bahawalpur exhibiting a comparably lower correlation (0.6824). Positive trends in SPI and SPEI values are revealed by Mann-Kendall trend tests, which are most prominent at higher elevations and on the northern side of Punjab. On a one-month time scale, the Mianwali station has the strongest trend in SPEI (0.1497), whereas Bahawalnagar has negligible trends in both SPI (0.0214) and SPEI (0.0459). At high elevation sites, the frequency of drought is constantly high, and SPEI routinely detects greater drought at low elevations. Similar drought frequencies are shown by both indexes for the northern region of Punjab. The results of a multiple linear regression model demonstrate the significant impact of meteorological variables on monthly mean precipitation, which advances our knowledge of Punjab's spatiotemporal drought dynamics and provides important information for planning for resilience and water resource management.

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Section: Discussionmentioning

confidence: 99%

Analysing Spatiotemporal Drought Patterns in Punjab Province, Pakistan, Utilizing SPI and SPEI

Hussain,

Suliman

2023

Preprint

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“…The ERA5 dataset, which has a horizontal spatial resolution of 30 km, combines extensive past climate observations into global‐scale approximations using advanced modelling techniques and data integration methods (Ali et al, 2022; Mistry et al, 2022). Due to the lack of long‐term observational data from various weather stations across Pakistan, the ERA5 dataset was chosen for this region due to its higher resolution and availability over an extended period (Rebi et al, 2023; Waseem et al, 2022; Zittis et al, 2016). Compared to other products, this ERA5 reanalysis product performed well in reproducing climate variables such as precipitation and temperature in the region (Ali et al, 2022; Waseem et al, 2022).…”

Section: Datasetsmentioning

confidence: 99%

“…Due to the lack of long‐term observational data from various weather stations across Pakistan, the ERA5 dataset was chosen for this region due to its higher resolution and availability over an extended period (Rebi et al, 2023; Waseem et al, 2022; Zittis et al, 2016). Compared to other products, this ERA5 reanalysis product performed well in reproducing climate variables such as precipitation and temperature in the region (Ali et al, 2022; Waseem et al, 2022). The data was accessed via the website https://cds.climate.copernicus.eu/#!/home.…”

Section: Datasetsmentioning

confidence: 99%

A novel approach for evaluation of CMIP6 GCMs in simulating temperature and precipitation extremes of Pakistan

Ali,

Hamed,

Muhammad

et al. 2024

Intl Journal of Climatology

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The study used a hybrid approach to evaluate the performance of 20 global climate models (GCMs) from CMIP6 in reproducing 20 extreme temperature and precipitation indices over Pakistan. This study first analysed the future simulations of extremes and discarded the GCMs whose projections fell outside the 95% confidence interval. The remaining GCMs' performance was evaluated using the Kling Gupta Efficiency‐based criteria. The changes in extreme climatic events in Pakistan were projected using the multi‐model ensemble (MME) median of the selected GCMs for four shared socioeconomic pathways (SSPs) in two future periods, 2020–2059 and 2060–2099. Four GCMs' showed inconsistency in projecting future climatic extremes and were discarded initially. The past performance of the remaining GCMs revealed EC‐Earth3‐Veg‐LR, GFDL‐ESM4, MRI‐ESM2‐0 and NOR‐ESM2‐MM to be effective in reproducing extreme indices for the historical period. The MME median of the selected GCMs showed a gradual increase in most of the temperature and precipitation extreme indices in the future periods for all SSPs across the country. Specifically, it showed a higher increase in daily maximum temperature (TXx) by 4.5–5°C, daily minimum temperature (TNn) by more than 4.5°C, consecutive days with a temperature higher than the 95th percentile (WSDI) by >160 days, one‐day maximum rainfall by 9–15 mm and days with precipitation above the 95th percentile by >50 mm in northern high‐elevated areas during 2060–2099 for SSP585. Similarly, a higher increase in TXx by 4.5–5°C, TNn by >4.5°C, WSDI by 140 days and tropical nights by 40–60 days was also found in the western arid region during 2060–2099 for SSP585. The study highlights that northern high‐elevated and western arid regions are at a higher risk of extreme temperatures and precipitation due to climate change.

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“…Roushangar et al [24] identified the spatio-temporal variation of drought frequency, duration, severity, and peak in Iran during the 1951-2016 period based on SPI with timescales of 3, 6, and 12 months. Waseem et al [25] analyzed the spatio-temporal variation of drought frequency and severity in Punjab, Pakistan during 2001-2019 using SPI-12.…”

Section: Spatio-temporal Analysis Of Drought In the North-eastern Coa...mentioning

confidence: 99%

“…There are several drought characteristics, hence the spatio-temporal variation analysis of drought is considered more reliable when more drought characteristics are used. To analyze the spatial variation of drought, the above studies used data collected from many ground stations [16] [18] [21] [24] [25] or satellite data [20] or both ground stations and satellite data [17] [23]. The results of spatio-temporal analysis of drought help constitute the scientific basis to analyze the impact of drought on crop production [21] [25], suggesting a cropping pattern for the drought-affected regions and implementing effective drought mitigation measures and water resource planning in drought areas [18].…”

Section: Spatio-temporal Analysis Of Drought In the North-eastern Coa...mentioning

confidence: 99%

Spatio-Temporal Analysis of Drought in the North-Eastern Coastal Region of Vietnam Using the Standardized Precipitation Index (SPI)

Tuan¹,

Hiếu²,

Bang³

et al. 2023

ACS

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Spatio-temporal analysis of drought provides valuable information for drought management and damage mitigation. In this study, the Standardized Precipitation Index at the time scale of 6 months (SPI-6) is selected to reflect drought conditions in the North-Eastern coastal region of Vietnam. The drought events and their characteristics from 1981 to 2019 are detected at 9 meteorological stations and 10 Chirps rainfall stations. The spatio-temporal variation of drought in the study region is analyzed on the basis of the number, duration, severity, intensity, and peak of the detected drought events at the 19 stations. The results show that from 1981 to 2019 the drought events mainly occurred with 1-season duration and moderate intensity and peak. The number, duration, severity, and peak of the drought events were the greatest in the period 2001-2010 and were the smallest in the period 2011-2019. Among the 19 stations, the drought duration tends to decrease at 11 stations, increase at 7 stations, and has a slight variant at 1 station; the drought severity tends to decrease at 14 stations, increase at 4 stations, and has not a significant trend at 1 station; the drought intensity tends to decrease at 17 stations, increase at 1 station, and has a slight variant at 1 station; and the drought peak tends to decrease at 18 stations and increase at 1 station.

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Spatiotemporal Analysis of Drought and Agriculture Standardized Residual Yield Series Nexuses across Punjab, Pakistan

Cited by 21 publications

References 26 publications

Analysing Spatiotemporal Drought Patterns in Punjab Province, Pakistan, Utilizing SPI and SPEI

Analysing Spatiotemporal Drought Patterns in Punjab Province, Pakistan, Utilizing SPI and SPEI

A novel approach for evaluation of CMIP6 GCMs in simulating temperature and precipitation extremes of Pakistan

Spatio-Temporal Analysis of Drought in the North-Eastern Coastal Region of Vietnam Using the Standardized Precipitation Index (SPI)

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