A spatiotemporal analysis of extreme agrometeorological events during selected growth stages of maize (Zea mays L.) from 1960 to 2017 in Northeast China

Zhang, Fangliang; Yang, Xiaoguang; Sun, Shuang; Gao, Jiqing; Liu, Zhijuan; Liu, Tao

doi:10.1007/s00704-020-03465-0

Cited by 14 publications

(13 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The CWDI can be calculated as follows:

{CWDI}_{i} = \{\begin{matrix} \frac{{ET}_{normalc} - P_{i}}{{ET}_{c}} \times 100 % {ET}_{normalc} > P_{i} \\ 0 {ET}_{normalc} \leq P_{i} \end{matrix}

where CWDI i is the 10 day crop water deficit index, ET c is the 10 day accumulated crop water demand (in millimeters), and P i is the 10 day total precipitation (in millimeters). The crop water demand (ET c ) can be calculated as the potential reference evapotranspiration with the Food and Agriculture Organization (FAO) Penman method 12,29 …”

Section: Methodsmentioning

confidence: 99%

“…Therefore, the CWDI can be regarded as a cumulative value to reflect the actual water deficit degree. When studying the crop water deficit during a certain 10 day period, it is often necessary to consider the impact of the previous four 10‐day water deficits on the current 10 day period, which can be determined as follows:

{CWDI}_{i} = a \cdot {CWDI}_{i} + b \cdot {CWDI}_{i - 1} + c \cdot {CWDI}_{i - 2} + d \cdot {CWDI}_{i - 3} + e \cdot {CWDI}_{i - 4}

where CWDI i is the crop cumulative water deficit index in time units (10 days), CWDI i , CWDI i −1 , CWDI i −2 , CWDI i −3 and CWDI i −4 are the crop water deficit index values in the i , i − 1, i − 2, i − 3, and i − 4 time units, respectively, a , b , c , d , and e are the cumulative weight coefficients of the corresponding time units, and the values are 0.3, 0.25, 0.2, 0.15 and 0.1, respectively 12,30,31 …”

Section: Methodsmentioning

confidence: 99%

“…The planted area and production of maize in northeast China account for 30% of the national total amount 11 . It has been shown that the main extreme agrometeorological event in northeast China is chilling damage before the 21st century, while drought is the main one after the 21st century 12 . With warming temperatures, the frequency of heat waves in northeast China has significantly increased, such as the Northeast Asian heat wave in 2018 13 .…”

Section: Introductionmentioning

confidence: 99%

“…Previous studies have focused on individual climate extremes on annual or seasonal timescales, including chilling damage, 22 drought, 23‐25 extremely low‐temperature events, 26 and gales 12 in northeast China. The spatial‐temporal variation of high temperature, drought, high temperature and drought combined conditions is insufficient.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Spatial‐temporal patterns of high‐temperature and drought during the maize growing season under current and future climate changes in northeast China

Zhao

Zhang

et al. 2023

J Sci Food Agric

Self Cite

View full text Add to dashboard Cite

Background Under the background of global warming, the intensity and frequency of extreme meteorological events in the maize growing season in northeast China are increasing. In order to clarify the occurrence characteristics of extreme meteorological events in northeast China, this study focused on three extreme agrometeorological events, i.e., high temperatures, drought, and the compound events of high‐temperature and drought during the maize growing season (May–September), impacting maize production. Results Based on historical (1981–2017) and future (2021–2060) climate data, we analyzed the spatial‐temporal patterns of these three events with different intensities in northeast China. The results indicated that slight high‐temperatures and moderate and severe droughts occurred more frequently in the study area during the historical period. The frequency of the different grades of the compound events of high‐temperature and drought will exhibit an increasing trend in the future, as will the frequency of the compound events of high‐temperature and drought. This is particularly evident in the northwest of the study area. Conclusion The compound events of high‐temperature and drought mainly occurred in late July and early August, encompassing the flowering stage of maize varieties. It is important to identify the area and time of major extreme weather events to implement the necessary preventive measures. © 2023 Society of Chemical Industry.

show abstract

“…The CWDI can be calculated as follows:

{CWDI}_{i} = \{\begin{matrix} \frac{{ET}_{normalc} - P_{i}}{{ET}_{c}} \times 100 % {ET}_{normalc} > P_{i} \\ 0 {ET}_{normalc} \leq P_{i} \end{matrix}

Section: Methodsmentioning

confidence: 99%

{CWDI}_{i} = a \cdot {CWDI}_{i} + b \cdot {CWDI}_{i - 1} + c \cdot {CWDI}_{i - 2} + d \cdot {CWDI}_{i - 3} + e \cdot {CWDI}_{i - 4}

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Spatial‐temporal patterns of high‐temperature and drought during the maize growing season under current and future climate changes in northeast China

Zhao

Zhang

et al. 2023

J Sci Food Agric

Self Cite

View full text Add to dashboard Cite

show abstract

“…Worldwide, among the weather phenomena that most affect the agricultural sector are precipitation variability [1][2][3][4][5], intense meteorological droughts [6][7][8][9][10], and hot extremes (HEs) [11][12][13]. The importance of studying HEs and meteorological droughts jointly is that HE events can be predicted from knowledge of previous meteorological droughts, mainly due to the fact that dry events can increase the number of hot days in the summer [14].…”

Section: Introductionmentioning

confidence: 99%

Hot Extremes and Climatological Drought Indicators in the Transitional Semiarid-Subtropical Region of Sinaloa, Northwest Mexico

Cárdenas¹,

Ruacho²,

Montoya³

et al. 2022

Pol. J. Environ. Stud.

View full text Add to dashboard Cite

The main goal of this study was to explore the historical and recent spatial concurrence between the frequency (F), duration (D) and intensity (I) of hot extremes (HEs) and the frequency and evolution of meteorological drought in the region of Sinaloa. Based on the values of daily maximum temperature (Tmax) and precipitation obtained from CLImate COMputing for the interval April-October of a historical period and a recent period , the HE and the standardized precipitation index (SPI) were calculated on one-month (SPI-1) and four-month (SPI-4) timescales. Spearman rank correlation coefficients (Sr) were used to obtain the significant concurrences (SCs) between HEs and SPI-1, and HEs and SPI-4. El Quelite weather station showed the highest historical SCs between HEs and SPI-1 (−0.66≤Sr≤−0.57). Jaina is the only station that showed SCs with all four indicators of HEs and SPI-4 (−0.47≤Sr≤−0.34). In this study, the concurrence between HEs and SPI-1, and HEs and SPI-4 was determined for the first time. These are phenomena that can decrease the crop yield, particularly for rainfed crops such as maize, sesame and sorghum in the region commonly known as "the breadbasket of Mexico".

show abstract

Process-based dynamic identification indicators of soybean chilling damage and analysis of the corresponding spatiotemporal characteristics in Northeast China

Wang

Gao

et al. 2023

Int J Biometeorol

View full text Add to dashboard Cite

A spatiotemporal analysis of extreme agrometeorological events during selected growth stages of maize (Zea mays L.) from 1960 to 2017 in Northeast China

Cited by 14 publications

References 27 publications

Spatial‐temporal patterns of high‐temperature and drought during the maize growing season under current and future climate changes in northeast China

Spatial‐temporal patterns of high‐temperature and drought during the maize growing season under current and future climate changes in northeast China

Hot Extremes and Climatological Drought Indicators in the Transitional Semiarid-Subtropical Region of Sinaloa, Northwest Mexico

Process-based dynamic identification indicators of soybean chilling damage and analysis of the corresponding spatiotemporal characteristics in Northeast China

Contact Info

Product

Resources

About