03. July 2026

“Afghanistan’s water future depends on snow that is already shrinking. My hope is that this research makes clear we need to act" Abdul Haseeb Azizi successfully defends his thesis on "Water and Snow Storage Dynamics in Afghanistan"

Abdul Haseeb Azizi successfully defends his thesis on "Water and Snow Storage Dynamics in Afghanistan"

ZEF researcher Abdul Haseeb Azizi (ZEF ECOL) obtained his doctoral degree (Dr.-Ing) for his doctoral thesis on "Water and Snow Storage Dynamics in Afghanistan: Coupling Ground Observations, Remote Sensing, Machine Learning, and Hydrological Modeling". His degree was granted by the Faculty of Agriculture, Nutritional Sciences and Engineering University of Bonn, Germany. 

Supervision and tutoring

Abdul Haseeb's primary supervisor was Prof. Dr.-Ing. Jürgen Kusche (University of Bonn), his co-supervisor was Prof. Dr. Christian Borgemeister (ZEF, University of Bonn). His tutors were Dr.-Ing. Bernhard Tischbein (ZEF, University of Bonn) and Dr.-Ing. Fazlullah Akhtar (ZEF, University of Bonn), who also gave scientific guidance and support throughout the PhD journey.

Defense Abdul Haseeb Azizi
Defense Abdul Haseeb Azizi © ZEF
Download all images in original size The impression in connection with the service is free, while the image specified author is mentioned.
Please fill out this field using the example format provided in the placeholder.
The phone number will be handled in accordance with GDPR.

What was Abdul Haseeb's research about?

In Afghanistan, approximately 70 to 80 percent of all freshwater comes from snow-melt. Without that snow, rivers run dry, crops fail, and millions of people go without safe drinking water. Yet Afghanistan has almost no functioning stations to measure how much snow falls, how fast glaciers are shrinking, or how quickly groundwater is being pumped out of the ground. Decades of conflict destroyed much of the monitoring network — leaving decision-makers largely blind to an accelerating crisis.

For his doctoral research, Abdul Haseeb combined satellite observations, machine learning, and climate modelling to build the first comprehensive, country-wide picture of how Afghanistan’s water is changing across all five major river basins — covering the period from 1979 to 2024.

Main research findings

  • Using gravity satellite data (e.g., GRACE) combined with machine learning to fill data gaps revealed that Afghanistan is losing water storage at a rate of 2.46 gigatons per year. 

  • The two main contributors are glacier retreat and groundwater depletion. Together, they account for 85.8% of Terrestrial Water Storage loss.  In the Helmand Basin, groundwater alone is declining by over one gigaton per year, mainly due to intensive irrigation.

  • Snow is disappearing quickly. Peak snowmelt now occurs about 35 days earlier than in the 1980s, and the total volume of snowmelt has fallen by about 25 percent. In the worst-affected basins, such as the Helmand basin, the decline is even steeper. Projections suggest that snowmelt could decrease by more than 70 percent by the end of this century under high-emissions scenarios.

  • Snowmelt in Afghanistan is projected to decline substantially due to climate change. On average, a 1°C increase in temperature reduces annual snowmelt by about 11%. The greatest impacts are expected in the Helmand, Harirud-Murghab, and Northern basins, where snowmelt would reduce by 17-18%.

  • The crisis is uneven. The Helmand and Harirud-Murghab basins are the most at risk and the most densely populated agricultural zones. Basins with the largest populations face the sharpest water losses.
Graph from doctoral thesis of Abdul Haseeb Azizi
Graph from doctoral thesis of Abdul Haseeb Azizi - Relative contributions of different water storage components to the terrestrial water storage decline in Afghanistan during 2003-2022, based on GRACE satellite observations combined with machine learning reconstruction. © Abdul Haseeb Azizi
Defense Abdul Haseeb Azizi Group
Defense Abdul Haseeb Azizi Group © ZEF

“Afghanistan’s water future depends on snow that is already shrinking. My hope is that this research gives scientists, water managers, and policymakers a clearer picture of what is being lost — and how little time there is to act. It is essential to move water management from crisis response to forecast-guided, flexible and basin-specific adaptation for water and food security.

This research matters because it gives Afghanistan — and the international agencies working there — the scientific evidence needed to adapt. The methods are also designed to work in any data-scarce mountain country facing the same pressures: shrinking snowpacks, depleting aquifers, and a growing gap between water supply and demand."

This research was funded by the German Academic Exchange Service (DAAD).

"I am deeply grateful to DAAD for the opportunity, to my supervisors for their guidance, to my mentors Dr. Tischbein and Dr. Akhtar for their unwavering support.” (Abdul Haseeb Azizi)

Machine learning-based estimation of fractional snow cover in the Hindukush Mountains using MODIS and Landsat data. Journal of Hydrology, 638, 131579 (2024). https://doi.org/10.1016/j.jhydrol.2024.131579

Assessing long-term water storage dynamics in Afghanistan: An integrated approach using machine learning, hydrological models, and remote sensing. Journal of Environmental Management, 370, 122901 (2024). https://doi.org/10.1016/j.jenvman.2024.122901