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Northwest A&F University (2021)

Agricultural Drought Prediction Model in China Based on Meteorological Drought and High Temperature


Titre : Agricultural Drought Prediction Model in China Based on Meteorological Drought and High Temperature

Auteur : 吴海江

Grade : Master 2021

Université : Northwest A&F University

Résumé partiel
With the intensification of global climate change and the rapidly increasing population,the demand for food and water resource will do further expand.Food and water security mostly are affected by agricultural droughts.The agriculture drought(soil moisture deficit)is influenced by precipitation deficit(meteorological drought)and high temperatures.Thus,the development of efficient and reliable methods for agricultural drought prediction by considering these factors is crucial to crop yield security,water resources allocation,and drought mitigation deployment.The diversity temporal scales of Standardized Soil Moisture Index(SSI)are applied to monitor agricultural drought and may result in inconsistent drought situations.The Joint Standardized Soil Moisture Index(JSSI),which is used to assess the comprehensive situation of agricultural drought,is constructed by combing the SSI(calculated by GLDAS-Noah root zone soil moisture)over 1-,3-,6-,9-,and 12-month timescales based on Kendall Copula.The6-month timescale Standardized Precipitation Index(SPI)and 3-month timescale Standardized Temperature Index(STI)are utilized to depict meteorological drought and high temperatures,respectively.Accordingly,the Standardized Compound Events Indicator(SCEI)and Standardized Dry or Hot Events Index(SDHEI)are constructed based on SPI and STI.The joint and conditional probability of agricultural drought is analyzed under the conditions of meteorological drought and high temperature with different severity in China from June to August.For the 1–3-month lead,the meta-Gaussian(MG)model and Pair Copula Constructions(PCC)model is proposed under considering two cases as predictors:1)antecedent SPI(SPIt–i ;t denotes the target month,and i indicates the lead time)combined persistence JSSI(JSSIt–i),and 2)previous SPI,antecedent STI(STIt–i),and JSSI persistence.The leave-one-out cross validation(LOOCV)is adopted to predict the agricultural drought in summer season of each year over China.The prediction performance of these two agricultural drought prediction models under the two cases in different climate regions of China is compared.The main results listed below :(1)The JSSI is capable of capturing both emerging and prolonged agricultural drought in a timely manner,which can reflect the comprehensive agricultural drought situation.

Mots clés : agricultural drought ;drought prediction ;meta-Gaussian model ;Pair Copula Constructions model ;China;

Présentation (CNKI)

Page publiée le 27 octobre 2021