The U.S. Geological Survey (USGS) was due to give in-person surface-water training in 2020 to Afghanistan's Ministry of Energy and Water (MEW), now the National Water Affairs Regulation Authority (NWARA). The COVID-19 pandemic halted travel, so the USGS built a virtual training series instead: prerecorded and live presentations over 4 weeks in August 2021.
The training stopped after the second week when the Afghan Government collapsed. But the prerecorded presentations and materials had already been delivered, so participants can still watch and share them — and the USGS can reuse or adapt them for nongovernmental organisations involved in humanitarian water relief in Afghanistan, or for other international training.
Background
Since 2004 the USGS has helped rebuild Afghanistan's ability to monitor its water resources, working with scientists in several government agencies, including the MEW, NWARA and the Ministry of Agriculture, Irrigation, and Livestock. It has compiled and recovered Afghan hydrologic data and trained people in collecting water-resource data. This work helped Afghan scientists develop the data networks needed to understand and manage water resources that may affect current and future supplies.
Why record the training
The aim was to deliver surface-water training efficiently. Because the presentations were recorded and sent ahead, trainees could watch them on their own schedule, or where internet access was limited — a real advantage given the large time difference between the United States and Afghanistan. Unrecorded training is hard to recall later without detailed notes; recordings let participants translate, pause and replay.
How it worked
The learning objective was to understand how to collect useful, meaningful surface-water data as a basis for understanding hydrologic processes and managing water. Each week had three parts:
- a 1-hour live introduction to the week's topic;
- materials sent weekly: prerecorded presentations, videos and exercises;
- a 2-hour live summary at the end of the week, closing with questions and answers.
Each topic was designed to take a week, but the course was self-guided, so participants could go at their own pace.
| Week | Topic | Objectives |
|---|---|---|
| 1 | Streamflow gaging | why stage (water elevation) data matter — the basis for most derived variables, such as streamflow, and for hydrologic forecasting, from models to flood forecasts; typical field methods and streamgage operation; analysing recorded and derived data |
| 2 | Fluvial sediment sampling | why accurate sediment data matter; collecting different kinds of sediment data; designing a study that includes sediment sampling |
| 3 | Bathymetry | what bathymetry is and how it is used; collecting, processing and quality-checking bathymetry data accurately; examples of useful bathymetry products |
| 4 | Streamflow and sediment modelling | analysing sediment data; kinds of surface-water models; running a surface-water model with practical examples |
Advantages
The virtual format saved money: delivered electronically, it needed no travel. In-person training remains useful, but this approach could deliver introductory material in future so that time together is spent on more targeted training or joint work. More general trainings can also serve more than one audience or purpose, and can be shared with local, national and international communities.
Sources
Based on "Virtual Training Prepared for the Former Afghanistan Ministry of Energy and Water—Streamgaging, Fluvial Sediment Sampling, Bathymetry, and Streamflow and Sediment Modeling," by Joel T. Groten, Joshua F. Valder, Brenda K. Densmore, Logan W. Neal, Justin Krahulik and Thomas J. Mack, U.S. Geological Survey Fact Sheet 2022–3014, published by the U.S. Geological Survey; rewritten in hubnx's own words.
- The fact sheet cites Mack and others (2014), USGS Fact Sheet 2014–3068, on USGS water-resources work in Afghanistan from 2004 to 2014.
- The fact sheet's screenshot of a live session, which shows participants' video images, is not reproduced.
Licence: CC0 1.0 (public domain) · Adapted from pubs.usgs.gov
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