Mapping Land Surface Drought in Water-Scarce Arid Environments Using Satellite-Based TVDI Analysis

A A Alazba, Amr Mossad, Hatim M. E. Geli, Ahmed El-Shafei, Ahmed Elkatoury (), Mahmoud Ezzeldin, Nasser Alrdyan and Farid Radwan
Additional contact information
A A Alazba: Alamoudi Water Research, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia
Amr Mossad: Department of Agricultural Engineering, Faculty of Agriculture, Ain Shams University, Hadaek Shoubra, P.O. Box 68, Cairo 11241, Egypt
Hatim M. E. Geli: New Mexico Water Resources Research Institute, Department of Animal and Range Sciences, New Mexico State University, Las Cruces, NM 88003, USA
Ahmed El-Shafei: Department of Agricultural Engineering, College of Food & Agriculture Sciences, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia
Ahmed Elkatoury: Alamoudi Water Research, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia
Mahmoud Ezzeldin: Alamoudi Water Research, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia
Nasser Alrdyan: Alamoudi Water Research, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia
Farid Radwan: Alamoudi Water Research, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia

Land, 2025, vol. 14, issue 6, 1-28

Abstract: Drought, a natural phenomenon intricately intertwined with the broader canvas of climate change, exacts a heavy toll by ushering in acute terrestrial water scarcity. Its ramifications reverberate most acutely within the agricultural heartlands, particularly those nestled in arid regions. To address this pressing issue, this study harnesses the temperature vegetation dryness index (TVDI) as a robust drought indicator, enabling a granular estimation of land water content trends. This endeavor unfolds through the sophisticated integration of geographic information systems (GISs) and remote sensing technologies (RSTs). The methodology bedrock lies in the judicious utilization of 72 high-resolution satellite images captured by the Landsat 7 and 8 platforms. These images serve as the foundational building blocks for computing TVDI values, a key metric that encapsulates the dynamic interplay between the normalized difference vegetation index (NDVI) and the land surface temperature (LST). The findings resonate with significance, unveiling a conspicuous and statistically significant uptick in the TVDI time series. This shift, observed at a confidence level of 0.05 (Z S = 1.648), raises a crucial alarm. Remarkably, this notable surge in the TVDI exists in tandem with relatively insignificant upticks in short-term precipitation rates and LST, at statistically comparable significance levels. The implications are both pivotal and starkly clear: this profound upswing in the TVDI within agricultural domains harbors tangible environmental threats, particularly to groundwater resources, which form the lifeblood of these regions. The call to action resounds strongly, imploring judicious water management practices and a conscientious reduction in water withdrawal from reservoirs. These measures, embraced in unison, represent the imperative steps needed to defuse the looming crisis.

Keywords: drought monitoring; arid climates; TVDI; NDVI; LST; RSTs; GISs (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2073-445X/14/6/1302/pdf (application/pdf)
https://www.mdpi.com/2073-445X/14/6/1302/ (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:jlands:v:14:y:2025:i:6:p:1302-:d:1681975

Access Statistics for this article

Land is currently edited by Ms. Carol Ma

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