Simulation of maize drought degree in Xi'an City based on cusp catastrophe model

Drought generally has significant impacts on crops.It is essential to quantitatively evaluate the relationship between crop production and drought degree to provide technical support for drought disaster prevention.In this study,a drought degree index that can reflect the changes in precipitation,evapotranspiration,and soil moisture was developed on the basis of crop yield reduction rate.Four drought scenarios were set up to simulate the effects of meteorological drought on drought degree of crops at different growth stages.A cusp catastrophe model was constructed to analyze the mutation characteristics of the drought degree of maize at different growth stages under different meteorological drought conditions.Xi'an City in China was selected as the study area,and summer maize was selected as the research crop.Precipitation and crop yield data from 1951 to 2010 were used as the fundamental data to investigate drought degree mutation of summer maize.The results show that,under the meteorological drought conditions at the emergence-jointing stage,drought degree may change abruptly,and soil moisture content at the sowingemergence,jointing-tasseling,and tasseling-mature stages should be kept higher than 39%.

Analysis on Agricultural Drought Degree in Crop Growth Season in Recent 50 Years in Xinmin,Liaoning Province

By means of the analysis methods of linear regression,climate tendency rate,integral humidity index and dry-wet index,precipitation,agricultural water demand and drought degree were analyzed systematically.The results showed that precipitation tendency rate in crop growing season was-19.983 mm/10 a in recent 50 years,and precipitation reduced by around 100 mm.60%-70% years had basically satisfactory precipitation and the satisfaction degree of natural precipitation towards agricultural water demand decreased by 23%.Due to precipitation decrease,climatic type changed from semi-humid and relative drought to moderate drought.The average water deficit was 56 mm in growth season and 36% years were affected by drought.Spring drought was the most serious with the probability of 64%,followed by autumn drought with the probability of 58%,and summer drought was the lightest with the probability of 24%.The drought probability from planting to seedling emergence in May was 70%,which had the greatest effect on agriculture production.

Precipitation Change and Agricultural Drought and Flood Degrees during Crop Growth Season in Binzhou City

[Objective]The research aimed to analyze precipitation change and agricultural drought and flood degrees during crop growth season in Binzhou.[Method]Based on monthly rainfall and average temperature data at Binzhou meteorological observatory during March-November of1981-2010,by using linear regression,climatic tendency rate and dry-wet coefficient,precipitation change and agricultural drought and flood degrees during crop growth season of the past 30 years in Binzhou were analyzed from natural precipitation tendency change and satisfaction degree of agricultural water demand during crop growth season.[Result]In the past 30 years,precipitation during growth season in Binzhou presented increasing tendency.Spring,summer and autumn precipitation all increased somewhat,especially summer precipitation.Monthly average rainfall distribution was very uneven,and rainfall in July and August was more.In the past 30 years,average dry-wet coefficient K value during crop growth season in Binzhou was 0.60,it overall belonged to moderate drought climate type,and occurrence frequency of drought was 97%.It belonged to serious drought climate type in spring and autumn and light drought climate type in summer.Dry-wet coefficient presented rising tendency,illustrating that climate was developing toward wet direction.Seen from mean over the years,except humid in July,it was over light drought in other months.[Conclusion]Climate was overall arid during crop growth season in Binzhou,but precipitation somewhat increased in the past 30 years.Therefore,we suggested that artificial rainfall work should be enhanced.

Estimation of meteorological drought indices based on AgMERRA precipitation data and station-observed precipitation data

Meteorological drought is a natural hazard that can occur under all climatic regimes. Monitoring the drought is a vital and important part of predicting and analyzing drought impacts. Because no single index can represent all facets of meteorological drought, we took a multi-index approach for drought monitoring in this study. We assessed the ability of eight precipitation-based drought indices（SPI（Standardized Precipitation Index）, PNI（Percent of Normal Index）, DI（Deciles index）, EDI（Effective drought index）, CZI（China-Z index）, MCZI（Modified CZI）, RAI（Rainfall Anomaly Index）, and ZSI（Z-score Index）） calculated from the station-observed precipitation data and the Ag MERRA gridded precipitation data to assess historical drought events during the period 1987–2010 for the Kashafrood Basin of Iran. We also presented the Degree of Dryness Index（DDI） for comparing the intensities of different drought categories in each year of the study period（1987–2010）. In general, the correlations among drought indices calculated from the Ag MERRA precipitation data were higher than those derived from the station-observed precipitation data. All indices indicated the most severe droughts for the study period occurred in 2001 and 2008. Regardless of data input source, SPI, PNI, and DI were highly inter-correlated（R^2=0.99）. Furthermore, the higher correlations（R^2=0.99） were also found between CZI and MCZI, and between ZSI and RAI. All indices were able to track drought intensity, but EDI and RAI showed higher DDI values compared with the other indices. Based on the strong correlation among drought indices derived from the Ag MERRA precipitation data and from the station-observed precipitation data, we suggest that the Ag MERRA precipitation data can be accepted to fill the gaps existed in the station-observed precipitation data in future studies in Iran. In addition, if tested by station-observed precipitation data, the Ag MERRA precipitation data may be used for the data-lacking areas.