Assessing spatiotemporal variation of drought and its impact on maize yield in Northeast China

Guo, Enliang; Liu, Xingpeng; Zhang, Jiquan; Wang, Yongfang; Wang, Cailin; Wang, Rui; Li, Danjun

doi:10.1016/j.jhydrol.2017.07.060

Cited by 106 publications

(51 citation statements)

References 30 publications

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“…Following Guo et al . (), the composite meteorological drought index was used to analyse the spatial variation of drought (Figure ). As discussed above, Figure shows that drought exerted a huge influence on the agricultural area in the three years.…”

Section: Resultsmentioning

confidence: 99%

“…The modified methods can generate more accurate results in months with a large number of ET 0 values By collecting information from the National Library of China, the drought events that occurred in the past 50 years were also investigated: there were also three major drought disasters in northeast China (Table 8). Following Guo et al (2017), the composite meteorological drought index was used to analyse the spatial variation of drought (Figure 7). As discussed above, Figure 7 shows that drought exerted a huge influence on the agricultural area in the three years.…”

Section: Modification Of Optimal Methodsmentioning

confidence: 99%

“…These plains produce more than 40% of the grain output of China (Liang et al ., ). Moreover, drought disasters significantly affected the productivity of crops in northeast China (Zheng et al ., ; Guo et al ., ). Therefore, an optimal equation other than the P‐M method in northeastern China needs to be found.…”

Section: Introductionmentioning

confidence: 99%

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Performance of 12 reference evapotranspiration estimation methods compared with the Penman–Monteith method and the potential influences in northeast China

Song

Lü

Xiao

et al. 2018

Meteorological Applications

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Reference evapotranspiration (ET0) is an important factor for agricultural activity and water management. Its estimation methods have significant regional differences. The Penman–Monteith (P‐M) method, which is recommended by the Food and Agriculture Organization (FAO), has been widely accepted, but it requires a large amount of data. This study analysed the performance of 12 ET0 estimation methods in different sub‐regions and periods by comparing them with the FAO P‐M method. Northeastern China was divided into eight sub‐regions according to their terrains and climates. Meteorological data obtained from 126 stations in these sub‐regions between the 1950s and 2014 were used to calculate the ET0 values. The performances were identified via four indices: root mean squared error, mean absolute error, average ratio and Spearman's correlation co‐efficient. The optimal method for agricultural areas was then modified by using linear regression analysis. The results are as follows: the Valiantzas2, Romanenko2 and H‐Makkink methods are recommended as alternative methods during the crop‐growing period, whereas the Turc and Hargreaves–Samani methods can generate significant biases. The Valiantzas2 and H‐Makkink methods are the optimal ones for estimating ET0 values in agricultural areas. Based on the outputs from the FAO P‐M method, ET0 values are most sensitive to temperature, accounting for 59.5%. Other methods that provide similar results can be considered as alternatives. Finally, the modified equation can provide the most accurate results, but drought events also affect the accuracy of the modified method.

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Section: Resultsmentioning

confidence: 99%

Section: Modification Of Optimal Methodsmentioning

confidence: 99%

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Performance of 12 reference evapotranspiration estimation methods compared with the Penman–Monteith method and the potential influences in northeast China

Song

Lü

Xiao

et al. 2018

Meteorological Applications

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“…To study the effect of drought on crop yield, it is necessary to obtain the climate yield. By identifying the long-term trend of yield unit area and using the appropriate de-trend method, the influence of climate on crop yield unit area can be obtained, i.e., the climate yield can be obtained [34].…”

Section: Calculation Of Climate Yield and Drought Assessment Indicatorsmentioning

confidence: 99%

Effect of Climate Change on Maize Yield in the Growing Season: A Case Study of the Songliao Plain Maize Belt

Guna

Zhang

Tong

et al. 2019

Water

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Based on the 1965–2017 climate data of 18 meteorological stations in the Songliao Plain maize belt, the Coupled Model Intercomparision Project (CMIP5) data, and the 1998–2017 maize yield data, the drought change characteristics in the study area were analyzed by using the standardized precipitation evapotranspiration index (SPEI) and the Mann–Kendall mutation test; furthermore, the relationship between meteorological factors, drought index, and maize climate yield was determined. Finally, the maize climate yields under 1.5 °C and 2.0 °C global warming scenarios were predicted. The results revealed that: (1) from 1965 to 2017, the study area experienced increasing temperature, decreasing precipitation, and intensifying drought trends; (2) the yield of the study area showed a downward trend from 1998 to 2017. Furthermore, the climate yield was negatively correlated with temperature, positively correlated with precipitation, and positively correlated with SPEI-1 and SPEI-3; and (3) under the 1.5 °C and the 2.0 °C global warming scenarios, the temperature and the precipitation increased in the maize growing season. Furthermore, under the studied global warming scenarios, the yield changes predicted by multiple regression were −7.7% and −15.9%, respectively, and the yield changes predicted by one-variable regression were −12.2% and −21.8%, respectively.

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“…基于 SPI 的蒙古高原干旱时空演变特征研究郭恩亮 1,2 ,包玉龙 1,2,3 ,布仁 1,2,* ,包玉海 1,3 ,来全 1,2,3 ,咏梅 1,2,3 ,王永芳 4 1 内蒙古师范大学地理科学学院，内蒙古呼和浩特，010022，中国…”

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Assessing Spatiotemporal Characteristics of Drought based on SPI in Mongolia Plateau

Guo¹,

Bao²,

Bu³

et al. 2018

Proceedings of the 8th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC 2018)

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Assessing spatiotemporal variation of drought and its impact on maize yield in Northeast China

Cited by 106 publications

References 30 publications

Performance of 12 reference evapotranspiration estimation methods compared with the Penman–Monteith method and the potential influences in northeast China

Performance of 12 reference evapotranspiration estimation methods compared with the Penman–Monteith method and the potential influences in northeast China

Effect of Climate Change on Maize Yield in the Growing Season: A Case Study of the Songliao Plain Maize Belt

Assessing Spatiotemporal Characteristics of Drought based on SPI in Mongolia Plateau

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