Dynamic drought risk assessment using crop model and remote sensing techniques

International Symposium on Earth Observation for One Belt and One Road

地球科学;政治学;社会学;经济学

Sun, H.^1,2 ; Su, Z.^1,2 ; Lv, J.^1,2 ; Li, L.^3 ; Wang, Y.^1,2

Research Centre on Flood and Drought Disaster Reduction, Ministry of Water Resources of China, Beijing

100038, China^1

China Institute of Water Resources and Hydropower Research, Beijing

100038, China^2

College of Life Science and Technology, Beijing Normal University, Beijing

100875, China^3

关键词: Agricultural drought;    Leaf Area Index;    Liaoning Province;    Moderate resolution imaging spectroradiometer datum;    Remote sensing techniques;    Scenario-based methods;    Static evaluation;    Water shortages;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/57/1/012012/pdf
DOI  :  10.1088/1755-1315/57/1/012012

来源: IOP

【 摘 要 】

Drought risk assessment is of great significance to reduce the loss of agricultural drought and ensure food security. The normally drought risk assessment method is to evaluate its exposure to the hazard and the vulnerability to extended periods of water shortage for a specific region, which is a static evaluation method. The Dynamic Drought Risk Assessment (DDRA) is to estimate the drought risk according to the crop growth and water stress conditions in real time. In this study, a DDRA method using crop model and remote sensing techniques was proposed. The crop model we employed is DeNitrification and DeComposition (DNDC) model. The drought risk was quantified by the yield losses predicted by the crop model in a scenario-based method. The crop model was re-calibrated to improve the performance by the Leaf Area Index (LAI) retrieved from MODerate Resolution Imaging Spectroradiometer (MODIS) data. And the in-situ station-based crop model was extended to assess the regional drought risk by integrating crop planted mapping. The crop planted area was extracted with extended CPPI method from MODIS data. This study was implemented and validated on maize crop in Liaoning province, China.