Dynamic assessment and prediction of drought impacts on yields

Person in Charge: Yu Chaoqin

1. The published paper:

“Dynamic assessment of the impact of drought on agricultural yield and scale-dependent return periods over large geographic regions”, http://www.sciencedirect.com/science/article/pii/S1364815214002278#

2. Introduction

Dynamic assessment and prediction of large-scale drought impacts on agricultural yields can provide essential information for supporting drought management, but remain a scientific and technical challenge. The difficulties root in how to deal with the uncertainty of future drought development, how to quantify the impacts of water stress on the ultimate yields before harvest, and how to perform reasonable evaluation over very large geographic regions under varying environmental conditions.

In 2008, a scenario-based approach to quantify the uncertainty of dynamic drought impacts on yields was initially figured out during a Skype meeting between Chaoqing Yu and Changsheng Li. And they applied this approach with the DNDC model in Liaoning Province, China, for evaluating dynamic drought impacts on yields. With the development of dynamic assessment methodology, software tools, and agricultural databases, the team applied this approach to predict the corn yield losses in the USA drought in 2012; and the predicted national yield at the end of October (120bushel/acre) was highly close to the harvested yield (120bushel/acre) released by the USDA in February, 2013. In 2013, the team started to build agricultural model for China and predicted the rice losses in the southern China in 2013; and the results were sent to the Office of State Flood Control and Drought Relief Headquarters and other departments. In 2014, the predictions of yield losses in China and the USA are daily updated by the team, the predicted results for China were also sent to the relevant drought management offices.