About the training
The SERVIR-HKH Initiative, a joint initiative of ICIMOD, USAID and NASA, is working on developing information services using Earth Observation (EO) and climate modelling technology. EO technologies have tremendous potential to support the implementation of long-term and large-scale research and development programmes and resolve data and information gaps in the agriculture sector, which include status and changes in land use, agricultural production, and resilience for food security, among many other aspects.
As a part of this initiative, International Centre for Integrated Mountain Development (ICIMOD) is working in collaboration with the United States Department of Agriculture-Agriculture Research Service (ARS) team and Ministry of Agriculture and Livestock Development (MoALD) Agriculture GIS Unit and the United Nations World Food Programme (WFP) to develop a web-based crop monitoring and forecasting system for Nepal to produce in-season monthly crop condition and yield outlooks for rice.
In connection with rice yield estimation, we are organizing a series of field orientation and data collection events from 21–25 August 2024. This events, in collaboration with Ministry of Agriculture and Livestock Development (MoALD), United States Department of Agriculture (USDA), and WFP, will focus on gathering comprehensive field data at different stages of rice phenology for Environmental Policy Integrated Climate (EPIC) agroecosystem modelling. This data is essential for predicting rice crop yields and water use. During this period, we will specifically conduct fieldwork for biomass information collection during the rice panicle formation stage. The panicle formation stage is a critical growth period where the potential yield is largely determined. Assessing biomass at this stage helps understand how well the crop has developed and if it is on track to achieve optimal yields.
Objectives
The training aims to provide agriculture professionals from MoALD with better understanding of:
- Field data collection techniques and the use of field data collection through mobile application
- Collect the biomass information in different stages of rice phenology
- Collect information on crop management practices in the Mahottari district
Expected outcomes
- Develop a comprehensive understanding of the EPIC model and relevant application
- Quantify dry and wet biomass of the rice in three rice growing stages (panicle formation, flowering and maturity)
- Gather detailed crop management information, such as transplanting dates, harvest time, irrigation, water availability and fertiliser information
Expected participants
A total 10 MoALD officials will be participating in this training.
Resource persons
MoALD
- Chet Bahadur Roka, Senior Statistics Officer
- Richa Shah, Agro Economist
ICIMOD
- Sravan Shrestha, Senior Associate – Remote Sensing and Geoinformation
- Sarthak Shrestha, Remote Sensing and Geoinformation Associate
WFP
- Man Kshetri, GIS Analyst
Background
The UN Sustainable Development Goal 2 (Zero hunger) aims to end hunger, achieve food security and improved nutrition, and promote sustainable agriculture. The Hindu-Kush Himalayan (HKH) region is highly vulnerable to climate-related disasters (e.g.
floods, droughts); often leading to low agriculture production and food scarcity, which affects rural livelihoods. Furthermore, climate-driven risks of extreme weather events are expected to continue increasing in the near future and increasing the risk of food insecurity. It is thus crucial to have the ability to produce accurate sub-seasonal-to-seasonal (S2S) forecasts to drive crop forecasts, and to provide reliable within-season crop conditions and yield outlooks with actionable lead-time. Such forecasts and outlooks offer early warnings on the impacts of extreme events and help stakeholders at all levels make sound decisions that can improve risk management and enhance policymaking, and interventions.
The Government of Nepal (GoN) recognises the prevailing situation of food insecurity across the country and attaches high importance to ensuring food security for all. However, there is a need to build upon significant capacity in food security planning, monitoring and evaluation within the GoN to enable it to provide reliable and timely information to support planning and policy decision-making processes. ICIMOD in collaboration with MoALD Nepal, WFP and USDA-ARS is developing a satellite-based agriculture monitoring and forecasting (SAMF) framework to provide within-season monthly crop conditions and yield outlooks at sub-district level for rice production systems with acceptable accuracy. This framework uses satellite remote-sensing-derived crop variables (e.g., leaf area index), rice maps, and downscaled and bias-corrected S2S forecasts in the crop model Environmental Policy Integrated Climate (EPIC), to simulate crop condition and crop yields periodically during the growing season.
