The Hindu Kush Himalaya (HKH) contains the largest reservoir of ice and snow outside the Earth’s polar ice sheets. There are few direct measurements of the snow water equivalent (SWE) – the volume of water stored in ice and seasonal snow. This makes predicting snow and ice melt and their contribution to runoff challenging. Even in retrospect, understanding the previous year's snow water supply is difficult. For many regions in the HKH, seasonal snow and ice melt are a significant part of water supply, and accurate knowledge of the state of the snowpack early in the spring can provide awareness of summer and fall droughts.
Spaceborne remote sensing from optical and passive microwave sensors can inform our understanding of snow, ice, and the processes acting on these critical resources. This training will inform participants on ways to use passive microwave and optical remote sensing, and energy balance and climate models to improve our understanding of water supplies stored as ice and seasonal snow.
There is no specific technique for estimating SWE everywhere, hence, this training will provide participants with the necessary tools to determine the best approach for their region of interest. Participants will understand the benefits and limitations of various methods for SWE estimation.
The training will also cover a wide range of topics: fundamentals of snow science, snow remote sensing, SWE reconstruction, snow covered area analysis and historical contextualization, data visualization, and machine learning for water supply forecasting from seasonal snow through lectures and hands-on exercises. A mix of operational and research grade products and techniques will be presented in hands-on exercises. We will use in situ data, satellite remote sensing measurement, energy balance modeling, climate models, and machine learning in example watersheds in the HKH region to go through various techniques for data exploration and information extraction for water supply management.
ICIMOD and Cold World Consulting (CWC) will be conducting this training, within the framework of ICIMOD’s SERVIR Hindu Kush Himalaya (SERVIR-HKH) initiative, and as part of the institutional capacity building efforts with the NASA SERVIR Applied Sciences Team.
This training aims to provide theoretical and practical knowledge to professionals from Afghanistan, Bhutan, and Nepal in using remote sensing and model data and its applications in SWE estimation and prediction.
Upon completion of the training, participants will have better understanding of the concepts and general applications of remote sensing and model data for estimating SWE, enabling them to use the knowledge professionally.
A total of 22 professionals from HKH countries including Afghanistan, Bhutan, and Nepal with backgrounds in remote sensing and Geographic Information Systems (GIS) will be participating in the training.
Participants’ skill level
The training is designed for water professionals with little to no background in computer science. The hands-on exercises are designed to enable participants with varying levels of technical backgrounds to extract meaningful information. A basic understanding of hydrology, snow, and physics is recommended.
Virtual training structure
Due to COVID-19, the training will be conducted virtually. The training will be a mix of recorded and live sessions. There will be 4 live sessions. Prior to each session, there will be a set of recorded lectures of approximately 1 hour for the students to watch. Each live session will begin with an interactive question and answer period, followed by discussion on the lecture material. The rest of the live sessions will be devoted to hands-on exercises with lab exercises run on Python Jupyter Notebooks.
Resource persons and facilitators
- Cold World Consulting
- NASA SERVIR Science Coordination Office
26–28 April 2021, 3–6 May 2021 (Mondays and Wednesdays, Afghanistan Time UTC+04:30)
- Day 1 – Monday, 26 April 2021
Morning session (S1): Introduction to snow science
Training overview and introduction of the participants
Live Q&A for recorded video lectures
- An introduction to snow hydrology
- Optical and passive microwave remote sensing of snow
- Visualize operational SWE products using Jupyter Notebooks
Rajesh Bahadur Thapa, ICIMOD
Karl Rittger, CWC
Timbo Stillinger, CWC
- Day 2 – Wednesday, 28 April 2021
- Day 3: 7 April 2021
- Day 4: 8 April 2021