Investigating Drought and Flood Evolution Based on Remote Sensing Data Products over the Punjab Region in Pakistan

Author:

Ullah Rahat123,Khan Jahangir45,Ullah Irfan6,Khan Faheem7ORCID,Lee Youngmoon8ORCID

Affiliation:

1. Jiangsu Key Laboratory for Optoelectronic Detection of Atmosphere and Ocean, Nanjing University of Information Science & Technology, Nanjing 210044, China

2. Institute of Optics and Electronics, Nanjing University of Information Science & Technology, Nanjing 210044, China

3. Jiangsu International Joint Laboratory on Meteorological Photonics and Optoelectronic Detection, Nanjing University of Information Science & Technology, Nanjing 210044, China

4. Key Lab of Remote Sensing for Agri-Hazards, Ministry of Agriculture, College of Information & Electrical Engineering, China Agricultural University, Beijing 100083, China

5. Department of Computer Science & IT, Sarhad University of Science & Information Technology, Peshawar 25120, Pakistan

6. College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China

7. Department of Computer Engineering, Gachon University, Seongnam-si 13120, Republic of Korea

8. Department of Robotics, Hanyang University, Ansan 15588, Republic of Korea

Abstract

Over the last five decades, Pakistan experienced its worst drought from 1998 to 2002 and its worst flood in 2010. This study determined the record-breaking impacts of the droughts (1998–2002) and the flood (2010) and analyzed the given 12-year period, especially the follow-on period when the winter wheat crop was grown. We identified the drought, flood, and warm and cold edges over the plain of Punjab Pakistan based on a 12-year time series (2003–2014), using the vegetation temperature condition index (VTCI) approach based on Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data products. During the year 2010, the Global Flood Monitoring System (GFMS) model applied to the real-time Tropical Rainfall Measuring Mission (TRMM) rainfall incorporated data products into the TRMM Multi-Satellite Precipitation Analysis (TMPA) for the flood detection/intensity, stream flow, and daily accumulative precipitation, and presented the plain provisions to wetlands. This study exhibits drought severity, warm and cold edges, and flood levels using the VTCI drought-monitoring approach, which utilizes a combination of the normalized difference vegetation index (NDVI) with land surface temperature (LST) data products. It was found that during the years 2003–2014, the VTCI had a positive correlation coefficient (r) with the cumulative precipitation (r = 0.60) on the day of the year (D-073) in the winter. In the year 2010, at D-201, there was no proportionality (nonlinear), and at D-217, a negative correlation was established. This revealed the time, duration, and intensity of the flood at D-201 and D-217, and described the heavy rainfall, stream flow, and flood events. At D-233 and D-281 during 2010, a significant positive correlation was noticed in normal conditions (r = 0.95 in D-233 and r = 0.97 in D-281 during the fall of 2010), which showed the flood events and normality. Notably, our results suggest that VTCI can be used for drought and wet conditions in both rain-fed and irrigated regions. The results are consistent with anomalies in the GFMS model using the spatial and temporal observations of the MODIS, TRMM, and TMPA satellites, which describe the dry and wet conditions, as well as flood runoff stream flow and flood detection/intensity, in the region of Punjab during 2010. It should be noted that the flood (2010) affected the area, and the production of the winter wheat crop has consistently declined from 19.041 to 17.7389 million tons.

Funder

National Natural Science Foundation of China

Hanyang University

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

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