Located in the central part of western China, Qinghai Province is one of the poorest provinces in China. Dari County, the case study area, is located in the south-eastern part of Qinghai-Tibetan High Plateau. Due to Dari’s special geographical location with an average altitude ranging from 3500 to 4000 meters above the sea level, extensive pastoral production systems play an overwhelming role in the local economy. However, the harsh climate determines a high-risk environment and the mainly Tibetan herders are living under difficult and poor conditions with very weak risk prevention and avoiding capacities and capabilities.This report documents the in-depth situation assessment on Pastoral Risk Management and Poverty Alleviation, in Dari County. It identifies the current risks and poverty evidences existing in the county and it compares perceptions, and recomendations of different stakeholders to improve current pastoral risks management approaches and practice.

The global climate maps presented here are based on data for mean monthly values of temperature, precipitation and cloudiness prepared in 1991 by R. Leemans and W. Cramer and published by the International Institute for Applied Systems Analysis (IIASA). The IIASA data correspond to an imaginary "net" covering the Earth's surface with a mesh size of 0.5 degrees. This is equivalent to about 60 km - an area of about 3,600 sq. km - at the equator.

This FAO Guidelines examines issues specific to those sectors, and suggest the processes, information requirements, policy directions, planning tools and possible interventions that are necessary for ICAM (Integrated coastal area management and agriculture).

Crop forecasting is the art of predicting crop yields (tons/ha) and production before the harvest actually takes place, typically a couple of months in advance. Several techniques can be used. What is described here is the approach used by FAO in national food security systems. Crop forecasting relies on computer programmes that describe the plant-environment interactions in quantitative terms. Such programmes are called "models", and they attempt to simulate plant-weather-soil interactions. They need, therefore, information and data on the most important factors that affect crop yields - the model inputs. After passing "through" the model, the inputs are converted to a number of outputs, such as maps of crop conditions and yields.