|ZHANG, X. - Beijing Normal University|
|ZHAO, X. - Beijing Normal University|
|LIU, S. - Beijing Normal University|
|ZHOU, T. - Beijing Normal University|
|PONCE CAMPOS, G.E. - University Of Arizona|
Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/10/2014
Publication Date: 6/6/2014
Citation: Zhang, X., Moran, M.S., Zhao, X., Liu, S., Zhou, T., Ponce Campos, G. 2014. Impact of prolonged drought on rainfall use efficiency using MODIS data across China in the early 21st century. Remote Sensing of Environment. 150:188-197. https://doi.org/10.1016/j.rse.2014.05.003.
Interpretive Summary: Many regions are suffering from severe and frequent droughts, but their impacts on the grasslands and forests around the world are still uncertain. In this study, we investigated the impacts of the prolonged drought during the early 21st century on four ecosystems in China including forests, savannas and grasslands. Our results indicate that the water use of plants in all thes ecosystems is affected by not only the current drought conditions, but also the drought conditions of the previous year. Based on these results, we developed and validated a simulation model to predict the effect of drought on vegetation growth. This model is particularly useful for understanding the impact of prolonged drought on our extensive forests and grasslands. It will help managers plan for the impact of predicted climate change on valuable natural resources, especially if prolonged drought continues in the future.
Technical Abstract: Frequency and severity of droughts are projected to increase in many regions, and their effects on temporal dynamics of the terrestrial carbon cycle remain uncertain. Ecosystem net primary productivity (NPP) is a key component of the carbon cycle, and rainfall use efficiency (RUE=NPP/precipitation) is an important measure of ecosystem stability and resilience. Here we investigated the temporal patterns of NPP and RUE and their key driving climate factors, during the early 21st century drought for four biomes in China: Needleleaf forest, Broadleaf forest, Woody savannas, and Grassland. Our results confirmed recent findings that the impact of current-year precipitation on NPP was confounded by an array of biotic and abiotic factors. Whereas, the RUE responded strongly to variations in current- and previous-year drought for all four biomes and the four biomes combined. We found that a dry year preceded by a wet year resulted in the highest RUE, and conversely, a wet year preceded by a dry year resulted in the lowest RUE. This was attributed to the legacy effect of precipitation changes in both wet and dry years, and to the resilience of the biomes in the dry years. Based on these results, we developed and validated a model of RUE based on the Palmer Drought Severity Index (PDSI) of both current and previous years which works well for these four biomes and all biomes combined. This model is particularly useful for understanding the impact of prolonged drought at the landscape scale because it is based on accessible satellite data and available meteorological data and the results have been tested across four major biomes.