To generate awareness about the technological developments and maximize the use of the web-based application, we are conducting hands-on training for relevant staff at the Department of Forests and Soil Conservation (DoFSC), and division forest offices in districts that experience a high risk of forest fires in Nepal.
We invite partners, stakeholders, and alumni to the public launch event of the Regional Land Cover Monitoring System (RLCMS) for the Hindu Kush Himalaya (HKH) region, where we will be showcasing the web-based RLCMS and releasing the annual land cover data (2000–2018).
The rapid penetration of Earth observation (EO) and geospatial information technology (GIT) across various disciplines has enabled their widespread adoption in planning sectors, resource management, and sustainable development. However, EO and GIT concepts are still rudimentary or nonexistent in school curriculums across the HKH region.
The Hindu Kush Himalayan region is extremely susceptible to periodic monsoon floods. Early warning systems with the ability to predict floods in advance can benefit tens of millions of people living in the region. Two web-based flood forecasting tools (ECMWF-SPT and HIWAT-SPT) are therefore developed and deployed jointly by SERVIR-HKH and NASA-AST to provide early warning to Bangladesh, Bhutan, and Nepal. ECMWF-SPT provides ensemble forecast up to 15-day lead time, whereas HIWAT-SPT provides deterministic forecast up to 3-day lead time covering almost 100% of the rivers. Hydrological models in conjunction with forecast validation contribute not only to advancing the processes of a forecasting system, but also objectively assess the joint distribution of forecasts and observations in quantifying forecast accuracy. The validation of forecast products has emerged as a priority need to evaluate the worth of the predictive information in terms of quality and consistency. This paper describes the effort made in developing the hydrological forecast systems, the current state of the flood forecast services, and the performance of the forecast evaluation. Both tools are validated using a selection of appropriate metrics in measurement in both probabilistic and deterministic space. The numerical metrics are further complemented by graphical representations of scores and probabilities. It was found that the models had a good performance in capturing high flood events. The evaluation across multiple locations indicates that the model performance and forecast goodness are variable on spatiotemporal scale. The resulting information is used to support good decision-making in risk and resource management.
Experts working within the SERVIR-HKH Initiative at ICIMOD investigated the 2018 Panjshir flood using remotely sensed imagery...
Interactive visualisation of the highest mountain peaks of the world that are above 8,000 meter from sea level.
This map story lists glacial lakes of Nepal that have been categorized as potentially dangerous based on...
This story map describes how farmers are demoralized by the problems that they are facing in the field.
SERVIR connects space to village by helping developing countries use satellite data to address challenges in food security, water resources, weather and climate, land use, and natural disasters. A partnership of National Aeronautics and Space Administration (NASA), United States Agency for International Development (USAID), and leading technical organizations, SERVIR develops innovative solutions to improve livelihoods and foster self-reliance in Asia, Africa, and the Americas. Read More
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