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Journal of Geographical Sciences >

2016 , Vol. 26 >Issue 6: 643 - 657

DOI: https://doi.org/10.1007/s11442-016-1290-3

Research Articles

Spatio-temporal changes in agricultural hydrothermal conditions in China from 1951 to 2010

  • CUI Yaoping ,
  • NING Xiaoju ,
  • QIN Yaochen , * ,
  • LI Xu ,
  • CHEN Youmin
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  • College of Environment and Planning, Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions, Henan Collaborative Innovation Center for Coordinating Industrialization, Urbanization and Modernization in Center Economic Zone, Henan University, Kaifeng 475004, Henan, China

*Corresponding author: Qin Yaochen (1959-), Professor, specialized in a regional model on sustainable development and geographic information science. E-mail:

Author: Cui Yaoping (1984-) specialized in land use and climate change, E-mail: ; Ning Xiaoju (1987-) specialized in sustainable development, E-mail: . Both of the authors had the same contributions to the paper.

Received date: 2015-12-29

  Accepted date: 2016-02-01

  Online published: 2016-06-15

Supported by

National Basic Program of China (973 Program), No.2012CB955800

National Natural Science Foundation of China, No.41171438, No.41401504

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Journal of Geographical Sciences, All Rights Reserved
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Abstract

Based on the daily observation data of 824 meteorological stations during 1951- 2010 released by the National Meteorological Information Center, this paper evaluated the changes in the heat and moisture conditions of crop growth. An average value of ten years was used to analyze the spatio-temporal variation in the agricultural hydrothermal conditions within a 1 km2 grid. Next, the inter-annual changing trend was simulated by regression analysis of the agricultural hydrothermal conditions. The results showed that the contour lines for temperature and accumulated temperatures (the daily mean temperature ≥0°C) increased significantly in most parts of China, and that the temperature contour lines had all moved northwards over the past 60 years. At the same time, the annual precipitation showed a decreasing trend, though more than half of the meteorological stations did not pass the significance test. However, the mean temperatures in the hottest month and the coldest month exhibited a decreasing trend from 1951 to 2010. In addition, the 0°C contour line gradually moved from the Qinling Mountains and Huaihe River Basin to the Yellow River Basin. All these changes would have a significant impact on the distribution of crops and farming systems. Although the mechanisms influencing the interactive temperature and precipitation changes on crops were complex and hard to distinguish, the fact remained that these changes would directly cause corresponding changes in crop characteristics.

Key words： temperature; precipitation; accumulated temperature; agricultural condition; China

Cite this article

CUI Yaoping , NING Xiaoju , QIN Yaochen , LI Xu , CHEN Youmin . Spatio-temporal changes in agricultural hydrothermal conditions in China from 1951 to 2010[J]. Journal of Geographical Sciences, 2016 , 26(6) : 643 -657 . DOI: 10.1007/s11442-016-1290-3

1 Introduction

Global warming and precipitation change lead to various oscillations of natural systems, ecosystems, human health and other aspects. Especially, agricultural production systems, which evidently rely on climatic resources, show an obvious frangibility and vulnerability (Burton et al., 2002; Ragab and Prudhomme, 2002; Fernanda and Maria, 2009; Alam et al., 2013). Climatic factors determine potential agricultural productivity. Global warming will continue to increase the heat stress on major crops worldwide, which, coupled with the instability caused by precipitation, can cause a threat to current crop production (Ramirez-Villegas et al., 2013). Edmar et al. (2013) found that crop areas will evidently change in 2071-2100, whereby the area changes for corn and wheat crops would be more intense than those for rice and soybean crops within the context of changes in heat stress associated with A1B emission scenarios. However, certain studies have shown that rice planting may face greater risk in the future (Ramirez-Villegas et al., 2013). For certain specific areas, studies have revealed that agricultural planting regions at 40°-60°N would face more risk in the future. At the same time, high-latitude agricultural regions, such as those in northern Europe and Canada, would benefit (Olesen and Bindi, 2002; Falloon and Betts, 2010; Smitha et al., 2013).
An analysis of the changes in agricultural conditions is indispensable for exploring agricultural adaptability to climate change in China. Therefore, many studies have focused on this topic. The annual average temperature in China has increased by 0.4-0.5°C per century under the background of global change (Ding et al., 2003), and precipitation has also been shown to exhibit obvious regional characteristics (Piao et al., 2010). From 1960 to 2013, precipitation in most parts of China tended to be normal or stable, which was beneficial to human activities (Liu et al., 2015). Specifically, the climate presented a warming trend in southern China and the Hanjiang basin (Li et al., 2010; Chen et al., 2006). A drought trend then developed in southern China while a moisture trend occurred in the southeast region (Ren et al., 2014). Moreover, in some provinces of northern China, such as Shandong province, the number of precipitation days showed a significantly decreasing trend (Dong et al., 2014). In northwest China, the warming trend in winter was more intense than in summer. In addition, the east and west parts of northwest China showed a warm-wet trend and warm-dry trend, respectively (Liu et al., 2005). On the one hand, such temperature and precipitation changes would have a profound impact on China’s agricultural production. Firstly, the increasing accumulated temperature—over 10°C in some southern provinces—caused an expansion of the boundaries of tropical crop planting towards high-altitude areas (Dai et al., 2014). In addition, the increasing precipitation in the growing season of rice has led to an improved growth pattern in the main rice-growing regions of China (Ma et al., 2012). Moreover, Tao et al. (2012) thought that climate change changed the phenology of wheat in China. The interaction between the decreasing negative accumulated temperature and mean temperature in the coldest month and the increasing annual extreme minimum temperature has enlarged the growth areas of winter wheat (Qian et al., 2014). Some studies have found that the rising winter temperature has led to the northern boundary of winter wheat being extended significantly—by 70 km over the past 50 years (Hu et al., 2014). Furthermore, the increasing light and heat resources in the northwest region have been shown to increase the light/temperature production potential of cotton (Mamat et al., 2014). On the other hand, the change in temperature and precipitation may lead to more negative consequences for agricultural production. Han et al. considered that the drought disaster in southwest China over the past 60 years had been mainly caused by rising temperatures (Han et al., 2014). Xiong et al. (2013) found that many climatic factors, such as the average temperature, daily temperature and radiation, had significantly changed in the period of rice growth from 1981 to 2007. Additionally, the increasing maximum temperature would lead to a corresponding increase in heat damage in rice production. In terms of northern regions, some studies have found that the drought trend was aggravated in Huang-Huai-Hai Plain in China from 1991 to 2011, and that the climate suitability of summer maize also declined (Xu et al., 2014a, 2014b).
Obviously, under the background of global climate change, the climatic conditions will change correspondingly in China. But what are the specific characteristics of different periods in different regions? To answer this question, this study selected the climate indicators closely related to agricultural production so as to analyze the spatio-temporal changes in agricultural climate conditions based on the daily meteorological observation data over a 60-year period and to compare the changing trend in water and heat resources required for crop growth.

2 Data and methods

2.1 Climatic factors

This study considers how temperature and precipitation directly affect crop growth. Therefore, five climatic factors were chosen to analyze spatio-temporal changes in agricultural hydrothermal conditions. The annual mean temperature was used to reflect the general changing trend in temperature, and the mean temperature in the hottest month and mean temperature in the coldest month were used to reflect changes in extreme temperature in this study. Also, the mean temperature in the hottest month was used to represent the requirements of high temperature in agricultural production. We defined accumulated temperature as the sum by which the actual air temperature rises above a given threshold value and the number of days during which this increase is maintained. The accumulated temperature over 0°C was used to represent the change in heat resources within a defined period of field-farming activity. The mean temperature in the coldest month was used to reflect the effect of climate change on winter crop conditions. Lastly, the annual precipitation was used to represent the variety of water sources required for crop growth. All of the above mentioned climatic factors jointly determine the climatic conditions for crop growth.

2.2 Data and process

In this study, daily observation data from 1951 to 2010 from 824 meteorological stations were collected. In accordance with the introductory documentation of the China Meteorological Data Sharing Service System, we used SQL language to calculate the annual mean temperature, the mean temperature in the hottest month, the mean temperature in the coldest month, and the annual precipitation. Finally, based on the rule that the accumulated temperature onset and offset are defined according to consecutive days (more than 5 days), the accumulated temperature over 0°C was recorded.
According to the previous research, we found that the spatial interpolation for temperature based on a DEM (digital elevation model) can simulate the spatial distribution of temperature effectively (He et al., 2005; Ji and Yu, 2010; Li et al., 2014). Here, the study uses the DEM as a co-variable and employs the ordinary Kriging method to interpolate the temperature and precipitation data. The final Kriging interpolation outputs were 1 km*1 km grid data.
In the actual processing, climatic factors were divided into six averaged data groups using ArcGIS 10.3 software: namely 1950s, 1960s, 1970s, 1980s, 1990s and 2000s. Referring to Wei’s research (Wei, 2007), a linear regression method was used to estimate the linear tendency of different climatic factors. Also, the F-test was used to determine the significance level (with an F value of 0.1).

3 Results and analysis

3.1 Interpolation accuracy

According to the results of Kriging interpolation models used in previous studies (Ji and Yu, 2010), the spherical model was used to interpolate. The mean error of prediction and the standard root mean square error were used to perform the entire cross-examination. The values of the mean error and the standard root mean square error were close to 0 and 1 respectively, indicating improved interpolation accuracy (Tang and Yang, 2012). The results showed that the interpolation accuracy achieved in the 1950s provided the lowest level of accuracy because observation stations in the 1950s were relatively rare among the six averaged data groups. In terms of the different interpolation accuracies of the climatic factors, the error mean of prediction and the standard root mean square error of the mean temperature in the coldest month were, respectively, close to 0 and 1, indicating a significantly high level of interpolation accuracy. In terms of the other climatic factors—accumulated temperature over 0°C and annual precipitation—although the standard root mean square error of the two factors was close to 1, the mean error deviated from 0 relatively (Table 1). The insensitive relationship between the two climatic factors and the DEM may have led to these results. Moreover, it was difficult to estimate the complex spatial relationships between the two climatic factors and other environmental elements, such as vegetation and slope, using the interpolation model.
Table 1 Cross-examination accuracy of interpolation methods
Climatic factor Examination 1950s 1960s 1970s 1980s 1990s 2000s
Annual mean
temperature		 Mean error of prediction 0.025 0.027 0.023 0.023 0.028 0.027
Standard root mean square error 1.864 1.284 1.382 1.433 1.376 1.405
Mean temperature in the hottest month Mean error of prediction 0.016 0.021 0.019 0.020 0.016 0.017
Standard root mean square error 1.293 1.486 1.378 1.505 1.225 1.306
Mean temperature in the coldest month Mean error of prediction 0.023 0.026 0.021 0.026 0.036 0.036
Standard root mean square error 1.283 0.938 0.095 0.982 1.088 1.085
Accumulated temperature over 0°C Mean error of prediction 4.586 5.184 4.589 4.692 3.896 4.104
Standard root mean square error 1.92 1.298 1.37 1.412 1.372 1.421
Annual precipitation Mean error of prediction 3.679 1.726 0.704 2.4 2.008 2.07
Standard root mean square error 1.834 1.44 1.406 1.496 1.341 1.268

3.2 Temporal variation in agricultural climatic factors

By comparing the decadal mean values of the six data groups separately, the fluctuant values of all climatic factors were obtained (Figure 1). The decadal mean values for the annual mean temperature, mean temperature in the coldest month and accumulated temperature over 0°C from the 1950s to 1970s were all lower than the average value for all 60 years. However, for the remaining decades (1980 to 2000), the decadal mean values for the three climatic factors showed an increasing tendency to be higher than the average value for all 60 years, especially for the mean values of accumulated temperature over 0°C. The letter U characteristics were found for the mean temperature in the hottest month. The annual precipitation showed a typical fluctuation trend along with time, and no significant change patterns have been found. The statistical characteristics relating to the agricultural climatic factors provided key information among temporal variations (Table 2). Based on the consideration of heat and water supply for crops, we found that the variation coefficient of accumulated temperature over 0°C and the annual precipitation were relatively stable at 0.4 and 0.6-0.7, respectively, indicating that the fluctuation frequency of the two climatic factors was relatively stable throughout the study period.
Figure 1 Decadal changes in agricultural climatic factors in China
Table 2 The statistical characteristics of agricultural climatic factors
Climatic factors Statistical factors 1950s 1960s 1970s 1980s 1990s 2000s
Annual mean
temperature		 Standard deviation 6.7 6.7 6.7 6.6 6.5 6.5
Coefficient of variation 0.6 0.6 0.6 0.6 0.5 0.5
Mean temperature
in the hottest month		 Standard deviation 4.9 5.1 5.1 5.0 4.9 4.8
Coefficient of variation 0.2 0.2 0.2 0.2 0.2 0.2
Mean temperature
in the coldest month		 Standard deviation 10.6 10.1 10.2 10.2 10.1 10.1
Coefficient of variation -3.1 -2.7 -3.3 -3.9 -4.7 -5.2
Accumulated
temperature over 0°C		 Standard deviation 1798 1795 1825 1814 1824 1831
Coefficient of variation 0.4 0.4 0.4 0.4 0.4 0.4
Annual precipitation Standard deviation 545.5 527 550 541 572.3 529
Coefficient of variation 0.6 0.6 0.6 0.6 0.7 0.6

3.3 Spatio-temporal variation in temperature

(1) Annual mean temperature
Based on the spatial distribution of annual mean temperature (Figure 2), the 20°C contour lines in certain southern regions extended northwards. The 15°C contour line had moved from the Huaihe River Basin to the Yellow River Basin, while the regions of the 10°C contour line remained relatively stable. In the northeast region, the areas of frozen soil zones with an annual mean temperature below 0°C markedly diminished. In the Qinghai-Tibet Plateau, although the areas of frozen soil zones with an annual mean temperature below 0°C increased initially then decreased, the final results showed that the areas within the Qinghai-Tibet Plateau have diminished over the past 60 years. At the same time, some patches with an annual mean temperature of 5-10°C were found within the Qaidam Basin. Generally, the contour lines of increasing annual mean temperature were repositioned towards north, and the areas of increasing temperature expanded during the study period.
Figure 2 Spatial interpolation results of mean temperature in China from 1951 to 2010
Comparing the temperature change of the earlier decadal data with the later decadal data, the analysis results illustrated that different change patterns were apparent in different regions. Therein, in the 1960s (Figure 3a), the decadal annual mean temperature in most parts of China decreased by 0-2.5°C, while the areas with an increasing temperature trend mainly involved northern Xinjiang and eastern Inner Mongolia. In the 1970s (Figure 3b), the temperature in most areas (86.5% of China as a whole) showed an increasing trend. In the 1980s (Figure 3c), 72.3% of the entire area exhibited an increasing trend, while the regions with a decreasing trend mainly involved the Sichuan Basin, Guanzhong plain and Huang-Huai-Hai Plain. In the 1990s (Figure 3d), almost all areas in China (98%) showed an increasing trend. In the 2000s (Figure 3e), there was a reduction in areas showing an increasing trend, with a whole-area rate of 70.7%, mainly involving regions within northern China. The statistical characteristics of regression analysis and the significance test also showed that the trend value b was increased in almost all meteorological observation stations, and more than 86.0% of observation stations passed the significance test (Table 3).
Figure 3 Spatial changing trend of mean temperature in China over the past 60 years
Table 3 The statistical characteristics of regression analysis and significance test
Percentage / % Regression coefficients b>0 and f (significance) Regression coefficients b>0 and f (non significance) Regression coefficients b<0 and f (significance) Regression coefficients b<0 and f (non significance)
Annual mean
temperature		 85.94 0.86 10.15 3.06
Mean temperature in the hottest month 34.19 10.17 31.86 23.77
Mean temperature in the coldest month 81.94 0.12 16.09 1.84
Accumulated temperature over 0°C 86.32 0.49 11.11 2.08
Annual precipitation 6.72 10.87 35.53 46.89
(2) Accumulated temperature over 0°C
Based on spatial changes of the six accumulated data groups, the results (Figure 4) showed that the 8000°C contour lines of accumulated temperature over 0°C had extended into southern China. The 6000°C contour lines of accumulated temperature over 0°C had gradually moved from south to north and crossed the Yangtze River. In the western regions of Inner Mongolia, the areas with 4000-6000°C of accumulated temperature over 0°C had become considerably more widespread over the past 60 years. Some regions in the Qinghai-Tibet Plateau had changed from 2000°C of accumulated temperature over 0°C to 2000-4000°C.
Figure 4 Spatial interpolation results of the accumulated temperatures over 0°C in China from 1951 to 2010
The main change range of accumulated temperature over 0°C was from 0°C to 250°C (Figure 5). From the 1960s to the 1980s, the regions with increasing or decreasing trends occupied a huge total area of China. After 1990, the accumulated temperature over 0°C showed a significant pattern—namely, almost all regions exhibited an increasing trend. In the 1960s and 1970s, 58.7% and 44.7% of areas, respectively, showed an increasing trend. In the 1980s, 63.4% of areas showed an increasing trend—exceeding 60% for the first time. In the 1990s and 2000s, more than 95.0% of areas showed an increasing trend. All changes in spatial distributions for different decades are shown in Figure 5. The statistical characteristic results of regression analysis and significance tests showed that the trend value b was more than 0 in almost all meteorological observation stations, and only 0.5% of observation stations did not pass the significance test (Table 3).
(3) Mean temperature in the hottest month and the coldest month
The patterns of temperature change were revealed not only by annual mean temperature and accumulated temperature, but also by the mean temperature in the hottest and coldest month.
Figure 5 Spatial changing trend of the accumulated temperatures over 0°C in China from 1951 to 2010
Figure 6 illustrates that the mean temperature in the hottest month showed a decreasing trend in the earlier three decades, while the mean temperature in the hottest month showed an increasing trend in the latter three decades for most parts of China. Therein, from the 1950s to the 1970s the regions that showed a decreasing trend were located in the Qinghai-Tibet Plateau and arid and semi-arid regions of northwest China. Similar to the accumulated temperature over 0°C, from the 1980s onward the area rate with increasing trend of mean temperature in the hottest month reached more than 60.0% of the whole of China. In the 1990s, the area rate was 86.2%, and the northern regions across the Yangtze River basically maintained the increasing trend. Based on the 60-year observation data, we also performed regression analysis. The linear trend results showed that 34.2% of the meteorological observation stations passed the significance test of increasing trend, while 31.9% of the meteorological observation stations passed the significance test of decreasing trend (Table 3).
To fully analyze the problem, the mean temperature in the coldest month was used to check the spatio-temporal change situation (Figure 7). In the 1960s, the area rate with increasing trend was less than 50.0%, while the area rate reached 80.3% in the 1970s. And from the 1980s to the 1990s, the area rate with increasing trend continued to maintain a relatively high level. In the 2000s, the area rate dropped to 58.5%. Figure 7 also illustrates the four different classes of values, which showed that the contour lines of mean temperature in the coldest month moved gradually northwards. In particular, the 0°C contour lines were found to be gradually approaching the Yellow River Basin from the Qinling Mountains and Huaihe River region. In that period, the regions with a decreasing trend were mainly distributed on the Northeast China Plain around Bohai Bay and in certain arid and semi-arid regions of northern China. Although there were some regions with a decreasing trend in China in every decade, the areas with an increasing trend were always larger than the areas with a decreasing trend except for the first decade (the 1950s). The values of regression coefficients b of 694 observation stations were greater than 0 and passed the significance test. Moreover, the analysis results showed that, in terms of spatial distribution, the mean temperature in the coldest month was different to the mean temperature in the hottest month in some regions of China (Table 3).
Figure 6 Spatial changing trend of mean temperature in the hottest month in China from 1951 to 2010
Figure 7 Spatial changing trend of mean temperature in the coldest month in China from 1951 to 2010

3.4 Spatio-temporal changes in precipitation

Precipitation is an important factor in agriculture. In this study, the spatial pattern of annual mean precipitation was mapped using the non-equal interval classification method (Figure 8). The northern borders of 200 mm contour lines of precipitation always varied along with the changes in the study period. The eastern borders of 400 mm contour lines of precipitation were found to have varied with time, while the southern borders remained stable, over the past 60 years. The borders of the 800 mm contour lines of precipitation also remained stable. The basic pattern of precipitation was stable, which led to a stable pattern of planting.
Figure 8 Spatial interpolation results of annual precipitation in China from 1951 to 2010
The spatial changes in precipitation over the six decades were analyzed by calculating the difference in results between one decade and the next (e.g. results for the 1960s minus results for the 1950s; results for the 2000s minus results for the 1990s; and so on) (Figure 9). The results showed that the maximum change areas occurred in southern China. In the 1950s-1960s and 1960s-1970s, the annual mean precipitation showed both an increasing trend and decreasing trend. In the 1970s-1980s, the precipitation showed a decreasing trend in southern regions—in particular, the precipitation decreased by 100-800 mm in the Yunnan-Guizhou Plateau. In the 1980s-1990s, the annual mean precipitation showed an obviously increasing trend, while a relatively decreasing trend occurred in the 1990s-2000s. The past 60 years have witnessed both increasing trends and decreasing trends in northeast China, north China, arid regions of northwest China, and the Qinghai-Tibet Plateau. The results of linear trend regression analysis showed that the trend values b in most observation stations were less than 0. But the results of the significance test revealed that 67.8% of the observation stations did not pass the significance test (Table 3). Therefore, there have been no obvious patterns of change in precipitation over the past 60 years. The change in precipitation was found to be more complex than the change in temperature factors.
Figure 9 Spatial changing trend of annual precipitation in China over the past 60 years

4 Discussion

Almost all the agricultural heat resources—except the mean temperature in the hottest month—showed increasing trends over the past 60 years. By contrast, the agricultural water resource showed no significant pattern. It is likely that the impact of changes in agricultural water and heat conditions on agricultural production would vary owing to the different geographical locations, crop characteristics, and agronomic management systems. In the northeast region, increasing temperature significantly raised local heat resources, which would provide very suitable conditions for crop growth (Li et al., 2011). Overall, the heat resources showed an increasing trend in the northwest region, while an increasing trend of annual precipitation in the northwest region did not pass the significance test. However, these results may not be consistent with those found in other studies (Liu et al., 2005; Deng et al., 2010; Shi et al., 2002). Although higher temperatures can also accelerate field evapotranspiration, heat resources aid vegetation growth (Mamat et al., 2014). The increasing mean temperature in the coldest month may significantly reduce the ill-effects of low temperature on overwintering crops in northern China. Hu et al. found that winter wheat production increased along with increasing temperature in winter in northern China (Hu et al., 2014). Yet the decreasing mean temperature in the hottest month reduced the heat supply for thermophilic crops, and reduced the climatic suitability (Xu et al., 2014b). Most temperature factors continued to increase in southern regions. Temperature changes always shortened the growth season and reduced the amount of time available for accumulating nutrients. All these factors may influence crop quality and confer agricultural production risks (Yang et al., 2010). The heat resources showed an increasing trend, too, in the Qinghai-Tibet Plateau. In particular, the increasing accumulated temperature over 0°C made the region suitable for crop growth. Zhang et al. studied the plant density in the Yarlung Zangbo River Valley and found that warming temperatures expanded the areas of local vegetation growth (Zhang et al., 2013).
The aim of this study was to analyze the spatio-temporal changes in the hydrothermal conditions of agriculture over the past 60 years and discuss the effects of climate change on agricultural production. One main focus was an analysis of the spatio-temporal changes that have occurred in China. Previous studies have focused mainly on the impact of climate on agricultural production (Liu et al., 2005; Chen et al., 2006; Wei, 2007; Li et al., 2010; Tang and Yang, 2012; Hu et al., 2014; Qian et al., 2014; Xu et al., 2014b). Because of the limited range of the available analysis scales and methods, it was sometimes difficult to achieve consistent results. Based on a uniform standard, this study could provide more comprehensive analysis results. Another focus of the study was an analysis of the regional differences in climatic changes. Many previous researches have revealed that there is an increasing trend toward rising temperatures throughout China (Liu et al., 2005; Chen et al., 2006; Li et al., 2010; Dai et al., 2014; Hu et al., 2014; Qian et al., 2014). However, this study found that some heat factors may show a decreasing trend in some regions; for example, the mean temperature in the hottest month was reduced in most parts of two important agricultural regions: the Yellow River Basin and the Yangtze River Basin. At the same time, we also found that precipitation showed no significant change within the study period. Further research is needed to better understand the conclusion of “warm and humid” or “warm dry” conditions in certain regions (Liu et al., 2005; Li et al., 2010; Ren et al., 2014).

5 Conclusions

Based on the daily observation data from 824 meteorological stations in China, the paper analyzed the spatio-temporal changes in temperature and precipitation. The results showed the following:
(1) The 10°C contour lines moved towards high latitude in most northern regions and the low temperature areas rapidly diminished in the Qinghai-Tibet Plateau. The changing trend of annual mean temperature was significant and passed the 0.1 significance level test for the past 60 years. Similar to the changes in 10°C contour lines, the contour lines of accumulated temperature over 0°C moved towards high latitude since the 1960s, and the rising trend of accumulated temperature over 0°C passed the significance test for most conditions.
(2) The mean temperature in the hottest month showed two different trends in space, namely the coexistence of rising and falling trends. Therein, the areas with a significantly rising trend were mainly distributed in northeast China, the Inner Mongolia Plateau and southeast China, while the areas with a falling trend were distributed only in the middle and lower reaches of the Yellow River and the Yangtze River basins. The contour lines of mean temperature in the coldest month moved gradually northwards. In particular, the 0°C contour lines were close to the Yellow River Basin from the Qinling Mountains and Huaihe River region. The trend values of mean temperature in the coldest month were also positive for most parts of China.
(3) Although annual precipitation showed a decreasing trend in most areas, more than half of the observed stations did not pass the significance test. The 400 mm and 800 mm precipitation contour lines were the key rainfall factors for agricultural pattern, and the two key factors essentially remained stable, implying that stable boundaries existed between animal husbandry and planting, and between dryland farming and water farming. However, the precipitation contour lines of 200 mm and 1600 mm varied significantly in both northern and southern China.
During the period of whole crop growth, the influence of spatial distribution of temperature and precipitation on regional agriculture continued to vary owing to differences in regions and crop types. Future studies should explore the biological characteristics of one specific crop with its corresponding requirement for heat and water resources during the growth period. Then, we can quantitatively assess the effect of heat and water resources on crops and take measures to avoid certain harmful situations linked to specific climatic conditions.

The authors have declared that no competing interests exist.

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Dai S P, Li H L, Luo H X.et al., 2014. The spatio-temporal change of active accumulated temperature ≥10°C in southern China from 1960 to 2011.Acta Geographica Sinica, 69(5): 650-660. (in Chinese)The spatial and temporal variation of active accumulated temperature ≥10℃(AAT10) was analyzed by using the linear trend line method, cumulative anomaly method and multiple linear regression interpolation method based on the daily meteorological observation data from 104 meteorological stations in Southern China and surrounding 39 meteorological stations during 1960-2011. The result shows that: (1) From time scale point of view, the climatic trend of AAT10 increased with an average of 7.54oC/10a in Southern China since 1960. The area of AAT10<6000℃decreased from 1960 to 2011, and the area of 6000℃<AAT10<8000℃ decreased from 1960 to 1979 and increased from 1980 to 2011, and the area of AAT10>8000℃ increased from 1960 to 2011. (2) From spatial scale point of view, the AAT10 in Southern China was reduced with increasing latitude and increasing altitude. The area of 5000℃<AAT10<8000℃ occupied 70% of the study area, followed by that of 4000℃<AAT10<5000℃; and the areas of AAT10<4000℃ and AAT10>8000℃ were the least. The climate trend rate at 99% of the meteorological stations of the AAT10 was greater than zero, suggesting that the AAT10 increased significantly in the central Yunnan province, southern Guangdong province and Hainan Island. (3) Comparison of period I (1960-1989) and period II (1980-2011) with the change of climatic zones indicates that the North Tropical Zone, South Subtropical Zone and Central Subtropical Zone gradually expanded, and North Subtropical Zone and Temperate Zone showed a decreasing trend. The change of climatic zones expanded to high altitude and latitude. (4) The increase of AAT10 is conducive to the production of tropical crops planted, which will increase the planting area suitable for tropical crops, and expand the planting boundaries to high latitude and high altitude.

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Deng Z Y, Zhang Q, Ning H F.et al., 2010. Influence of climate warming and drying on crop eco-climate adaptability in northwestern China.Journal of Desert Research, 30(3): 633-639. (in Chinese)<FONT face=Verdana>Responding to climate warming and drying in northwestern China, the heat index, water index, and growth index of some summer crops (winter and spring wheat), autumn crops (corn, potato, millet and prosomillet) and economic crops (cotton, flax, rape, and wine grape) all show changes more or less. The influence of climate warming on crop heat eco-adaptability is significant, and the heat index for current crops displays an increase of 100~200 ℃ compared with that in 1980s. The crop water eco-adaptability also had an obvionus sensitivity to the climate drying and warming, showing an increase of 50~80 mm in comparison to that in 1980s. Generally, there are both positive and negative impacts on crop eco-adaptability, namely positive effects on irrigated crops and negative effects on rainfed crops. It is necessary to adapt a modern agricultural development mechanism for irrigated crops and to establish a system adaptable to arid climate changes for rainfed crops.</FONT>

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Ding Y H, Zhang J, Xu Y et al., 2003. Climatic System Change and Forecast. Beijing: China Meteorological Press, 32-35. (in Chinese)

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Dong X G, Gu W Z, Meng X X.et al., 2014. Change features of precipitation events in Shandong Province from 1961 to 2010.Acta Geographica Sinica, 69(5): 661-671. (in Chinese)Based on daily precipitation data of 121 weather stations in Shandong Province from 1961 to 2010, this paper analyzed the features of precipitation days and intensity including climate characteristics, trends, contribution rate, variation field, abrupt change and periodicity. The results indicated that with a significant drop of days, both annual precipitation days and intensity showed an obvious decadal oscillation. Annual precipitation days and intensity presented evident zonal distribution and gradually decreased from southeast to northwest. Precipitation intensity of heavy rainfall in various places were more uniform, meanwhile days and intensity of extreme rainfall were more and higher in mountain area of southern Shandong than in the northern part. There were 116 stations showing a decreasing trend of annual rainfall days and 80 stations presenting an increase of intensity. Furthermore, days of heavy rainfall decreased and intensity of extreme rainfall had become higher apparently. Heavy and extreme rainfall days on a small proportion, however contributed significantly to the annual precipitation. Since the 21st century, the days and precipitation percentage of heavy rainfall and extreme rainfall had an increasing trend. The average rainfall days and variation coefficient changed greatly in the mid-1960s, 1990s and early 21st century. Variation coefficient of different precipitation events showed similar decadal changes, while that of the same precipitation event in different decadal differentiated evidently. The average rainfall days and heavy rainfall intensity mutated in 1977 and 2005 respectively. Heavy rainfall and extreme rainfall days had variation major periods of 5 years and 11 years respectively, while precipitation intensity of different grades had periods of 13 years and 21 years respectively.

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Edmar I T, Guenther F, Harrij V V.et al., 2013. Global hot-spots of heat stress on agricultural crops due to climate change.Agriculture and Forest Meteorology, 170: 206-215.The productivity of important agricultural crops is drastically reduced when they experience short episodes of high temperatures during the reproductive period. Crop heat stress was acknowledged in the IPCC 4th Assessment Report as an important threat to global food supply. We produce a first spatial assessment of heat stress risk at a global level for four key crops, wheat, maize, rice and soybean, using the FAO/IIASA Global Agro-Ecological Zones Model (GAEZ). A high risk of yield damage was found for continental lands at high latitudes, particularly in the Northern Hemisphere between 40 and 60°N. Central and Eastern Asia, Central North America and the Northern part of the Indian subcontinent have large suitable cropping areas under heat stress risk. Globally, this ranged from less than 502Mha of suitable lands for maize for the baseline climate (1971–2000) to more than 12002Mha for wetland rice for a future climate change condition (2071–2100) assuming the A1B emission scenario. For most crops and regions, the intensity, frequency and relative damage due to heat stress increased from the baseline to the A1B scenario. However for wheat and rice crops, GAEZ selection of different crop types and sowing dates in response to A1B seasonal climate caused a reduction in heat stress impacts in some regions, which suggests that adaptive measures considering these management options may partially mitigate heat stress at local level. Our results indicate that temperate and sub-tropical agricultural areas might bear substantial crop yield losses due to extreme temperature episodes and they highlight the need to develop adaptation strategies and agricultural policies able to mitigate heat stress impacts on global food supply.

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Falloon P, Betts R, 2010. Climate impacts on European agriculture and water management in the context of adaptation and mitigation: The importance of an integrated approach.Science of the Total Environment, 408: 5667-5687.

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Fernanda M S, Maria L F, 2009. Climate change and its marginalizing effect on agriculture.Ecological Economics, 68: 896-904.The agriculture of some areas considered marginal in the EU agricultural context is being questioned due to its low productivity and growing dependence on economic aid programs Common Agricultural Policy (CAP). This study shows that climate change increases these areas marginalisation of since worsens crop growth conditions. The influence of climate change on the agricultural sector is analyzed using the Multicriteria Decision Paradigm with information provided by the Erosion-Productivity Impact Calculator (EPIC) and a General Circulation Model (GCM) as inputs for multicriteria mathematical programming models. The results obtained show climate change effects on the crop portfolio. Further results suggest that climate change effects are not only economics and environmental, reducing the suitable area for crops, but also social as it causes loss of jobs in the agricultural sector.

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Han L Y, Zhang Q, Yao Y B.et al., 2014. Characteristics and origins of drought disasters in Southwest China in nearly 60 years.Acta Geographica Sinica, 69(5): 632-639. (in Chinese)Drought is a meteorological disaster that causes huge losses to agricultural yields every year. This paper analyzed drought trends based on statistical disaster data, which included drought-induced areas, drought-affected areas, and lost harvests under the effects of global warming. The results showed that droughts are becoming more critical and frequent in China. The agricultural effects of drought for drought-induced areas, drought-affected areas, lost harvest areas and comprehensive loss rate increased in the last 60 years in each province of Southwest China. It is important to examine the spatial and temporal changes in the agricultural effects of drought in guiding disaster mitigation work. This paper analyzed the drought conditions in large farming areas of Southwest China, which were frequently hit by serious droughts. Total drought area ranked first in Sichuan Province, second in Guizhou Province, and third in Yunnan Province. The average annual comprehensive loss rate accounted for 3.9% in Southwest China, and increased in recent years. Drought tolerance of all provinces is related to regional climate change effects, such as temperature, precipitation, moisture, and vegetation coverage.

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He H Y, Guo Z H, Xiao W F, 2005. Review on spatial interpolation techniques of rainfall.Chinese Journal of Ecology, 24(10): 1187-1191. (in Chinese)Rainfall spatial distribution is the important information in many fields,such as water resource management,drought and flood disaster prediction,and regional sustainable development,but its interpolation has been a puzzle because there are many affecting elements,such as latitude,longitude,elevation,distance to water bodies,slope,etc.,especially in mountainous regions.It is difficult to build a general rainfall interpolation model for different geographical regions.Several kinds of rainfall interpolation methods were introduced in this paper,including global interpolation methods(trend surface and multiple regression),local interpolation methods(Thiessen polygons,inverse distance weighting,kriging and splines),and mixed methods(combined global and local methods).Their advantages,disadvantages and applicability were discussed.Recently,with the development of applied mathematics and artificial neural networks(ANN),some new methods were put forward in the rainfall interpolation,especially the ANN technique,such as Back-Propagation neural networks(BP network) and Radial Basis Function networks(RBFN).Because of the uncertainty of rainfall,more detailed geographical and topographical characteristics are needed to improve the precision of predicted rainfall.Detailed topographical characteristics could be provided by a large scale DEM(digital elevation model) or DTM(digital terrain model),which plays an important role in rainfall interpolation.Different interpolation methods are required in different space or time scales.Even the same rainfall interpolation might get different results in different regions.The mixed methods,combining the advantages of global and local interpolation methods,are useful for improving the interpolation precision,which would be one of the important research fields in the future.

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Hu S, MO X G, Lin Z H, 2014. The contribution of climate change to the crop phenology and yield in Haihe River Basin.Geographical Research, 33(1): 3-12. (in Chinese)According to the 30 climatic stations with climatic records from 1960 to 2009 in Haihe River Basin, the classical calculation methods of agro-meteorological indicators was adopted to analyze the changes of temperature, precipitation and sunshine duration in the past 50 years. With the aid of VIP crop model, the effect of atmospheric CO2 enrichment, temperature, precipitation and sunshine duration variations on crop yield was study separately. The results show that the north limit of winter wheat moved northward by approximately 70 km in recent 50 years due to the significant temperature rising in winter. Based on the assumption that the irrigation amount and the crop varieties remained same in recent 50years, the wheat yield shows an upward trend(0.2%-3.4%/10 years). Roughly 11%, 0.7%,-0.2% and-6.5% variability of wheat yield can be explained by atmospheric CO2 enrichment, temperature rise, precipitation decline and sunshine duration decrease, respectively. The positive effect introduced by atmospheric CO2 enrichment offsets most negative effect introduced by sunshine duration declining, indicating that atmospheric CO2 enrichment is the main causes of the wheat yield rising. The maize yield shows a downward trend(0.6%~3.8%/ 10 years) in the recent 50 years when the irrigation amount and the maize varieties remained same. Roughly 0.7%,-3.6%,-1.0% and-6.8% variability of maize yield can be explained by atmospheric CO2 enrichment, temperature rise, precipitation decline and sunshine duration decrease, respectively, indicating that the sunshine duration decrease and the temperature rise are the main causes of the maize yield declining. These results can provide scientific supports for the assessment of the impact of climate change on agriculture and its adaptation countermeasures formulation.

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Ji Q, Yu M, 2010. Study on parameters setting of ordinary cokriging interpretation to average annual temperature. Journal of Capital Normal University (Natural Science Edition), 31(4): 81-87. (in Chinese)

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Li Y, Yang X G, Wang W F.et al., 2010. Changes of China agricultural climate resources under the background of climate change I: Spatiotemporal change characteristics of agricultural climate resources in South China.Chinese Journal of Applied Ecology, 21(10): 2605-2614. (in Chinese)<p>By using the 1961-2007 daily weather data from 66 meteorological stations all over South China, this paper studied the spatiotemporal change characteristics of agricultural climate resources, including heat, light, and precipitation, in this region on the scales of whole year and temperaturedefined growth season. In 1961-2007, the mean annual air temperature in this region tended to be&nbsp;increased by 0.20 ℃&middot;（10 a）<sup>-1</sup> and the climatic trend of &ge;10 ℃ accumulated temperature in temperaturedefined growth season increased gradually from north to south, with an average of 98 ℃&middot;d&middot;（10 a）<sup>-1</sup>. Comparied with those in 1961-1980, the areas of the accumulated temperature zone of 6200-7500 ℃&middot;d and&nbsp; 7500-8000 ℃&middot;d&nbsp;&nbsp;in 1981-2007&nbsp; increased by 1.5&times;10<sup>4</sup> and 4.7&times;10.4km<sup>2</sup> respectively. In 1961-2007, the sunshine hours on the scales of whole year and temperature-defined growth season decreased by -57 h&middot;（10 a）<sup>-1</sup> and -38 h&middot;（10 a）<sup>-1</sup> respectively, and the areas with sunshine hour &ge;1800 h on the two scales tended to be decreased, compared with those in 1961-1980. The precipitation on the two scales increased slightly, and the increment varied obviously in different parts of the region. There were 62% and 52% of the stations where the reference crop evapotranspiration on the scales of whole year and temperature-defined growth season was in negative, respectively. In 1981-2007, the high-value area of reference crop evapotranspiration decreased, while the low-value area increased, compared with those in 1961-1980. The mean climatic trend of annual humidity index&nbsp; was 0.01&middot;(10 a)<sup>-1</sup> and 70% of the stations showed an increasing trend. Comparing with that in 1961-1980, the humidity index on the scale&nbsp;of temperature-defined growth season in 1981-2007 was increased by 0.02, with&nbsp;53% of the stations showed positive. On the whole, the change characteristics of climate in South China in 1961-2007 showed a tendency of warming and wetting, which would impact the cropping system, yield, and agricultural structure in the&nbsp;region.</p>

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Li Y C, He Z M, Liu C X, 2014. Review on spatial interpolation methods of temperature data from meteorological stations.Progress in Geography, 33(8): 1019-1028. (in Chinese)Spatial interpolation is an important method for creating spatial representation of temperature in geographic and ecological research and is important for supplying fine resolution temperature data for ecological models. This paper reviews existing spatial interpolation research of meteorological factors and compares a number of interpolation methods, including global interpolators (trend surfaces and regression models), local interpolators (inverse distance weighting, gradient plus inverse distance squares method, PRISM, splines, ANUSPLIN), geostatistical methods (Ordinary Kriging, Co-kriging), and mixed methods (combined global, local, and geostatistical methods). These methods are commonly used for the spatial interpolation of temperature data. The aim of this study is to explore the suitability and inadequacies of these methods in order to provide references for future research involving spatial interpolation of temperature data. It also attempts to explore ways to improve the application of the various methods. The comparison of these methods shows that each method has its own strength in particular applications. There is no universal method suitable for all practical applications. In practice, specific geographical characteristics of the study area must be considered and tests should be done to determine the suitability of specific methods. In order to achieve optimal interpolation result of regional temperature, parameters of the methods should be adapted based on actual geographical conditions. Global interpolation and geostatistical methods can be applied to study global trends. Local interpolation based on distance similarity principle does not apply to global trends simulation. Mixed methods are able to combine advantages of global interpolation, local interpolation, and geostatistics, and improve the simulation accuracy. Mixed methods and PRISM and ANUSPLIN are more suitable for application under complex terrain conditions. In future research, integration of various temperature spatial interpolation methods will improve, and more mixed methods combining global, local, and geostatistical methods will be created. Methods based on the physical distribution characteristics of temperature and combined with GIS technology will be prevalent. In order to improve the simulation accuracy of temperature in microscopic details, introduction of additional factors, such as terrain, will be an important future trend.

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Li Z G, Yang P, Tang H J.et al., 2011. Trend analysis of typical phenophases of major crops under climate change in the three provinces of Northeast China.Scientia Agricultura Sinica, 44(20): 4180-4189. (in Chinese)【Objective】 The objective of this research is to analyze the phenophases (including the stages of seeding, heading and maturity) changes of rice, maize, spring wheat and soybean in three provinces of Northeast China. 【Method】Annual slope change rate (&theta;) was computed to evaluate the temporal trend and the relationship between agroclimate and phenophases. 【Result】Over the past 20 years, the timing of first effective temperature date (T&ge;10℃) was advanced, the first frost date was postponed, the growth period was continually extended and the accumulated temperature (T&ge;10℃) was increased in most area of the three provinces. Under this background, the temporal trend of phenophases of both rice and maize showed an advanced seeding stage (0.04＜&theta;＜0.55 d?a-1 and 0.04＜&theta;＜0.35 d?a-1), a postponed maturity stage (0.09＜&theta;＜0.35 d?a-1 and 0.23＜&theta;＜0.38 d?a-1) and an extended length of growth period (0.31＜&theta;＜1.26 d?a-1 and 0.11＜&theta;＜0.57 d?a-1). By contrast, temporal trend of soybean phenophases was different and characterized by an advanced seeding stage (0.01＜&theta;＜0.61 d?a-1), a maturity stage (0.18＜&theta;＜0.19 d?a-1), and a shortened growth period (0.06＜&theta;＜0.17 d?a-1). As for spring wheat, there was no obvious temporal change for the phenophases.【Conclusion】Climate change resulted in the increase of temperature suitability for crops, which could benefit from an early seeding stage, a late maturity stage and a long growth period.

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Liu D X, Dong A A, Lu D R, 2005. Climatic change of Northwest China and its influence on agricultural production in recent 43 years.Agricultural Research in the Arid Area, 23(2): 195-201. (in Chinese)The paper uses such indexes collected by 171 experiment stations in northwest China between 1961 and 2003 as average monthly temperatures, the highest and lowest monthly temperatures, rainfalls, accumulative temperatures above zero ℃ and ten ℃ and the negative accumulative below zero ℃ to analyze the patterns for the climatic changes of northwest China. The average monthly temperatures, the highest and lowest monthly temperatures, the rainfalls, the accumulative temperatures above zero ℃ and ten ℃ in 1987~2003 remarkably increased compared with those in 1961~1986; Of them the lowest temperature did rise with the highest range and the temperatures in winter increased with a higher range than those in spring. The climatic changes of northwest China resulted from the contributions of the lowest temperatures. Meantime, the negative accumulative temperatures below zero℃ obviously declined, the rainfalls increased in the western part of northwest China and decreased in the eastern of north of China with the divide line moving along yellow river. Northwest China tended to become humid in its western part and warm in its eastern part so that warm-liking crops increased in planting area and overwinter crops moved toward north beyond their planting boundary.

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Liu Y L, Yan J P, Cen M Y, 2015. Comprehensive evaluation of precipitation heterogeneity in China.Acta Geographica Sinica, 70(3): 392-406. (in Chinese)<p>Through comparisons of various methods, the method of precipitation concentration degree (PCD) was used to study precipitation heterogeneity. In addition to PCD, normal distribution functions, cumulative frequencies, and percentiles were used to establish a graded evaluation index of precipitation heterogeneity. A comprehensive evaluation of precipitation heterogeneity and its spatiotemporal variation in China in 1960-2013 were analyzed. Results indicated that: (1) seven categories of precipitation heterogeneity could be identified: high centralization, moderate centralization, mild centralization, normal, mild dispersion, moderate dispersion, and high dispersion; (2) during the study period, the precipitation in more parts of China tended to be normal or dispersed, which is beneficial to human activities.</p>

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Ma X, Wu S H, Li Y E.et al., 2012. Assessing climate change impact on seasonal drought in main rice cropping regions in the south of China.Acta Geographica Sinica, 67(11): 1451-1460. (in Chinese)Impact of climate change on seasonal drought in main rice cropping regions in China is important for adjusting rice planting pattern and improving adaptation ability. By comparing the level and spatial and temporal distribution of available water and seasonal drought during 1981-2030, this paper assesses impact of climate change on seasonal drought in main rice cropping regions in the south of China. The results are shown as follows. (1) The mean available water of early rice and late rice will increase by more than 10% in the growing season, while mean available water of medium rice will keep invariant. Meanwhile, the spatial distribution of available water of early rice and later rice becomes more homogeneous. This means that, due to climate change, available water of main rice cropping regions generally in the growing season will be more abundant, and spatial distribution of available water is more homogeneous, which is conductive to mitigate seasonal drought. (2) The area of seasonal drought of early rice will reduce by 12,500 km<sup>2</sup> medium rice by 80,000 km<sup>2</sup> and especially later rice will decrease by 250,000 km<sup>2</sup> accounting for 20% of the planting area of later rice. This means that, under climate change, the seasonal drought on the whole will tend to weaken, especially seasonal drought of later rice will obviously be weakened. (3) Based on the relationship between available water from hydrologic circulation process and water demands for crop growing season, the Water Supplies and Demands Index (WSDI) is suitable for assessing the impact of climate change on seasonal drought in main rice cropping regions.

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Mamat Y, Ulam M, Sabit M, 2014. Impact of climate warming on cotton production of Ugan-Kuqa River delta oasis.Geographical Research, 33(2): 251-259. (in Chinese)This paper uses average daily temperature data of 1961-2010 obtained from Kuqa,Shaya and Xinhe weather stations to reveal the impact of climate warming on cotton production of Ugan-Kuqa River delta oasis. Results showed that:(1) The temperature of the research area, during recent 50 years, showed an increasing trend, the spring temperature rose by 1.75℃, the summer temperature by 1.65℃, and autumn temperature by 2.05℃; the average minimum and maximum temperature from April to October rose by 2.25℃ and 0.05℃, respectively; the average minimum and maximum temperature from May to September rose by 2.55℃, and 0.3℃, respectively; accumulated temperature( 10℃) rose by 361.1℃.(2) Due to the accelerating spring warming, and slowing fall cooling, cotton sowing advanced eight days, stop growing delayed six days, and growth period extended about 14days; As the average minimum temperature in growth period and 10℃ accumulated temperature had risen, the heat resources of cotton growth period increased, poor climatic conditions was down to the lowest, photosynthetic rate was stronger, light and temperature matching were more coordinated, so that the cotton dry matter accumulation has been effectively increased, which resulted in increasing cotton yield per unit. The cotton light and temperature potential productivity of the research area in recent 50 years increased by18.65%, and the actual production increased by 437.38%.(3) The average cotton light and temperature potential productivity in the study area was4238 kg/hm2, which was 2.45 times of the average actual production. With the development of cotton farming and cultivation technology, the wide application of high-yielding cotton varieties, and the extensive use of water-saving irrigation technologies, levels of cotton light and temperature potential productivity will be higher in the future.

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Olesen J E, Bindi M, 2002. Consequences of climate change for European agricultural productivity, land use and policy.European Journal of Agronomy, 16: 239-262.<h2 class="secHeading" id="section_abstract">Abstract</h2><p id="">This paper reviews the knowledge on effects of climate change on agricultural productivity in Europe and the consequences for policy and research. Warming is expected to lead to a northward expansion of suitable cropping areas and a reduction of the growing period of determinate crops (e.g. cereals), but an increase for indeterminate crops (e.g. root crops). Increasing atmospheric CO<sub>2</sub> concentrations will directly enhance plant productivity and also increase resource use efficiencies.</p><p id="">In northern areas climate change may produce positive effects on agriculture through introduction of new crop species and varieties, higher crop production and expansion of suitable areas for crop cultivation. Disadvantages may be an increase in the need for plant protection, the risk of nutrient leaching and the turnover of soil organic matter. In southern areas the disadvantages will predominate. The possible increase in water shortage and extreme weather events may cause lower harvestable yields, higher yield variability and a reduction in suitable areas for traditional crops. These effects may reinforce the current trends of intensification of agriculture in northern and western Europe and extensification in the Mediterranean and southeastern parts of Europe.</p><p id="">Policy will have to support the adaptation of European agriculture to climate change by encouraging the flexibility of land use, crop production, farming systems etc. In doing so, it is necessary to consider the multifunctional role of agriculture, and to strike a variable balance between economic, environmental and social functions in different European regions. Policy will also need to be concerned with agricultural strategies to mitigate climate change through a reduction in emissions of methane and nitrous oxide, an increase in carbon sequestration in agricultural soils and the growing of energy crops to substitute fossil energy use. The policies to support adaptation and mitigation to climate change will need to be linked closely to the development of agri-environmental schemes in the European Union Common Agricultural Policy.</p><p id="">Research will have further to deal with the effect on secondary factors of agricultural production, on the quality of crop and animal production, of changes in frequency of isolated and extreme weather events on agricultural production, and the interaction with the surrounding natural ecosystems. There is also a need to study combined effects of adaptation and mitigation strategies, and include assessments of the consequences on current efforts in agricultural policy to develop a sustainable agriculture that also preserves environmental and social values in the rural society.</p>

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Piao S L, Ciais P, Huang Y.et al., 2010. The impacts of climate change on water resources and agriculture in China.Nature, 467: 43-51.China is the world's most populous country and a major emitter of greenhouse gases. Consequently, much research has focused on China's influence on climate change but somewhat less has been written about the impact of climate change on China. China experienced explosive economic growth in recent decades, but with only 7% of the world's arable land available to feed 22% of the world's population, China's economy may be vulnerable to climate change itself. We find, however, that notwithstanding the clear warming that has occurred in China in recent decades, current understanding does not allow a clear assessment of the impact of anthropogenic climate change on China's water resources and agriculture and therefore China's ability to feed its people. To reach a more definitive conclusion, future work must improve regional climate simulations-especially of precipitation-and develop a better understanding of the managed and unmanaged responses of crops to changes in climate, diseases, pests and atmospheric constituents.

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Qian J X, Li N, Han P, 2014. Influence of climate warming in winter on the winter wheat cultivable area in Shanxi Province.Acta Geographica Sinica, 69(5): 672-680. (in Chinese)Based on the daily mean temperature data of 70 meteorological stations in Shanxi Province from 1970 to 2012, the negative accumulated temperature in winter, average monthly temperature in January and extreme minimum temperature were computed and their changing trends were analyzed in this paper using linear trend estimation method, and their abrupt change points were observed by means of accumulated variance method and contours of the negative accumulated temperature in winter, average monthly temperature in January and extreme minimum temperature were compared respectively after being divided into two groups according to the abrupt change points. The results showed that the negative accumulated temperature in winter showed a remarkable decrease, and the average monthly temperature in January and extreme minimum temperature did not increase significantly. Changes were found between the two groups, the negative accumulated temperature decreased by 103.4℃, and the average monthly temperature in January and extreme minimum temperature rose by 0.7℃and 0.9℃, respectively. The negative accumulated temperature and extreme minimum temperature played a key role, which are the thresholds that the winter wheat Province could be planted or not. Under climatic warming, the winter wheat cultivable area and the reliable planting area expanded by 2.9&#215;10<sup>6</sup> hm<sup>2</sup> (increased by 52%) and 2.3&#215;10<sup>6</sup> hm<sup>2</sup> (rose by 79%), respectively.

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Ragab R, Prudhomme C, 2002. Climate change and water resources management in arid and semi-arid regions: Prospective and challenges for the 21st century.Biosystems Engineering, 81(1): 3-34.<h2 class="secHeading" id="section_abstract">Abstract</h2><p id="">The overgrowing population and the recent droughts are putting water resources under pressure and calling for new approaches for water planning and management if escalating conflicts are to be avoided and environmental degradation is to be reversed. As countries are using their water resources with growing intensity, poor rainfall increasingly leads to national water crises as water tables fall and reservoirs, wetlands and rivers empty. Global warming could cause further changes, further variability and further uncertainty. The UK Hadley Centre's global climate model was run at a spatial scale of 2&middot;5 by 3&middot;75&deg; (latitude and longitude) grid squares to simulate the global climate according to scenarios of greenhouse gas concentration emission. Runs of the model assuming the emission scenario proposed by the Intergovernmental Panel on Climate Change in 1995 are analysed here for the 2050s time horizon. Outputs provide estimations of climate variables, such as precipitation and temperature, at a monthly time step. Those results, assumed representative of future climatic conditions, are compared to mean monthly values representative of the current climate and expressed in terms of percentage change. The results show that, for the dry season (April&ndash;September), by the 2050s, North Africa and some parts of Egypt, Saudi Arabia, Iran, Syria, Jordan and Israel, are expected to have reduced rainfall amounts of 20&ndash;25% less than the present mean values. This decrease in rainfall is accompanied by a temperature rise in those areas of between 2 and 2&middot;75&deg;C. For the same period, the temperature in the coastal areas of the Mediterranean countries will rise by about 1&middot;5&deg;C. In wintertime, the rainfall will decrease by about 10&ndash;15% but would increase over the Sahara by about 25%. Given the low rainfall rate over the Sahara, the increase by 25% will not bring any significant amount of rain to the region. In wintertime, the temperature in the coastal areas will also increase but by only 1&middot;5&deg;C on average, while inside the region it will increase by 1&middot;75&ndash;2&middot;5&deg;C.</p><p id="">In southern Africa (Angola, Namibia, Mozambique, Zimbabwe, Zambia, Botswana and South Africa), results suggest an increase of the annual average temperature ranging between 1&middot;5 and 2&middot;5&deg;C in the south to between 2&middot;5 and 3&deg;C in the north. The summer range is between 1&middot;75 and 2&middot;25&deg;C in the south, and increases towards the north to between 2&middot;75 and 3&middot;0&deg;C while the winter range is between 1&middot;25 and 2&deg;C in the south, and increases towards the north to between 2&middot;5 and 2&middot;75&deg;C. On the other hand, the annual average will decrease by 10&ndash;15% in the south and by 5&ndash;10% in the north. The annual average decrease is 10%. However, some places will have an increase <em>i.e.</em> by 5&ndash;20% in South Africa in wintertime. In the Taklimakan region (Tarim Basin) west of China, the annual average temperature is shown to increase by 1&middot;75&ndash;2&middot;5&deg;C. Annual average rainfall should increase by 5&ndash;&gt;25% in most of the region but decrease by 5&ndash;10% in some small parts. In summer, an increase by 5&ndash;15% is indicated in most of the region, and an increase by up to 25% or more during the wintertime.</p><p id="">In the Thar Desert (India&ndash;Pakistan&ndash;Afghanistan), estimations suggest that the annual average increase in temperature ranges from 1&middot;75 to 2&middot;5&deg;C, ranging from 1&middot;5 to 2&middot;25&deg;C in winter and from 2 to 2&middot;5&deg;C in summer. Annual average precipitation is shown to decrease by 5&ndash;25% in the region. The winter will have values closer to the annual average but the summer will have more decrease and most of the region will see a decrease closer to 25%.</p><p id="">In the Aral Sea basin (Kazakhstan, Turkmenistan and Uzbekistan), estimates suggest an annual average increase in temperature ranging from 1&middot;75 to 2&middot;25&deg;C, higher in summer (between 2 and 2&middot;75&deg;C) than in winter (between 1&middot;5 and 2&deg;C). Rainfall should increase by 5&ndash;20% annually, in summer increasing by 5&ndash;10% in the north but decreasing by up to 5% in the south, while in wintertime, both south and north should undergo increases of 5&ndash;10% and 20&ndash;25%, respectively.</p><p id="">In Australia, results indicate an increase in the annual average temperature ranges of 1&ndash;1&middot;5&deg;C in the south to 2&middot;5&ndash;2&middot;75&deg;C in the north, slightly higher during the summer than in the winter. The summer range is between 1 and 2&deg;C in the south and increases towards the north to 2&middot;5&ndash;3&middot;0&deg;C while the winter range is between 1 and 1&middot;5&deg;C in the south, and increases towards the north to between 2 and 2&middot;25&deg;C. Rainfall annual average is shown to decrease by 20&ndash;25% in the south and by 5&ndash;10% in the north.</p><p id="">Given the above-mentioned facts, in order to meet the water demands in the next century, some dams and water infrastructure will be built in some countries and a new paradigm by rethinking the water use with the aim of increasing the productive use of water will have to be adopted. Two approaches are needed: increasing the efficiency with which current needs are met and increasing the efficiency with which water is allocated among different uses. In addition, non-conventional sources of water supply such as reclaimed, recycled water and desalinated brackish water or seawater is expected to play an important role.</p>

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Ramirez-Villegas J, Jarvis A, Läderach P, 2013. Empirical approaches for assessing impacts of climate change on agriculture: The EcoCrop model and a case study with grain sorghum.Agricultural and Forest Meteorology, 170: 67-78.

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Ren Z G, Zhang M J, Wang S J.et al., 2014. Changes in precipitation extremes in South China during 1961-2011.Acta Geographica Sinica, 69(5): 640-649. (in Chinese)Based on the daily precipitation from a 0.5&deg; &times; 0.5&deg; gridded dataset and meteorological stations during 1961-2011 released by National Meteorological Information Center, this paper evaluates the reliability of this gridded precipitation dataset in South China. Five precipitation indices recommended by the World Meteorological Organization (WMO) were selected to investigate the changes in precipitation extremes in South China. The results indicate that the limited bias was observed between gridded data interpolated to given stations and the corresponding observed data, and that 50.64% of the stations had bias between -10% and 0. Generally, the correlation coefficients between gridded data and observed data are above 0.80 in most parts of the region. The average of precipitation indices shows a significant spatial difference with drier northwest section and wetter southeast section. The trend magnitudes of maximum 5-day precipitation (RX5day), very wet day precipitation (R95), very heavy precipitation days (R20mm) and simple daily intensity index (SDII) were 0.17 mm&middot;a<sup>-1</sup> 1.14 mm&middot;a<sup>-1</sup> 0.02 d&middot;a<sup>-1</sup> and 0.01 mm&middot;d&middot;a<sup>-1</sup> respectively, while consecutive wet days (CWD) decreased by -0.05 d&middot;a<sup>-1</sup> during 1961-2011. There is spatial disparity in trend magnitudes of precipitation indices, and approximate 60.85%, 75.32% and 75.74% of the grid boxes showed increasing trends for RX5day, SDII and R95, respectively. There were high correlations between precipitation indices and total precipitation, which was statistically significant at the 0.01 level.

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Shi Y F, Shen Y P, Hu R J, 2002. Preliminary study on signal, impact and foreground of climatic shift from warm-dry to warm-humid in Northwest China.Journal of Glaciology and Geocryology, 24(3): 219-226. (in Chinese)A rapid, high amplitude global climatic warming would speed global water cycle and strengthen rainfall and evaporation. Climatic warming and drying course were dominated in past about 100 years since the end of Little Ice Age in Northwest China. The strong signals of climatic shift to warm humid pattern have been appearing in the western part of Chinese Tianshan Mountains and neighborhood regions including Northern Xinjiang since 1987. Precipitation, meltwater of glacier and runoff of rivers increase continuously, and results in lake level rising, flood damaged magnification and intensified, vegetation coverage extending and dust storm weaken in western parts of Northwest China. In the other areas of Xinjiang, and the middle and western section of Qilian Mountains, the precipitations and runoff of rivers have also an increasing tendency. How is the foreground of climatic shift to warn humid conditions, it is just restricted to decadal fluctuation, or possibility to century scale shift trend, and is just limited to western Tianshan or could extend and/or wholly Northwest China down to North China? Using the results of regional climatic model simulation from IPCC and China Assessment Report published, predicting river runoff regime and similar paleoclimate scenarios for the Northwest China are analysed and discussed, and the trend of shifting warm humid climate can be fixed in recent future. However, uncertain of projected results remain, and rating and magnitude of climatic shift extending in temporal and spatial scales can not at present be projected in detail and in being exactitude.

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Smith W N, Grant B B, Desjardins R L.et al., 2013. Assessing the effects of climate change on crop production and GHG emissions in Canada agriculture.Ecosystems and Environment, 179: 139-150.

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Tang G A, Yang X, 2012. ArcGIS: GIS Spatial Analysis Experiment Tutorial. Beijing: Science Press. (in Chinese)

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Tao F L, Zhang S, Zhang Z, 2012. Spatiotemporal changes of wheat phenology in China under the effects of temperature, day length and cultivar thermal characteristics.European Journal of Agronomy, 43: 201-212.

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Wei F Y, 2007. Modern Climate Statistics Diagnosis and Prediction Technology. Beijing: China Meteorological Press. (in Chinese)

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Xiong W, Yang J, Wu W B.et al., 2013. Sensitivity and vulnerability of China’s rice production to observed climate change.Acta Ecologica Sinica, 33(2): 509-518. (in Chinese)

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Xu J W, Ju H, Liu Q.et al., 2014. Variation of drought and regional response to climate change in Huang-Huai-Hai Plain.Acta Ecologica Sinica, 34(2): 460-470. (in Chinese)It is widely recognized that the frequency and intensity of extreme weather events and climate disasters have strongly increased with global warming. The area of influence of climate disasters has also increased,which has had adverse effects on sustainable social and economic development. Drought is a recurring natural phenomenon,and is associated with a deficit of water resources over a large geographic area and long duration. Drought is attracting increased attention from scholars,with a focus on its intensity,duration and areal extent in northern China within the context of global change. Investigation of the variation of drought and regional response to climate change is very important to agricultural production, and can provide a reference fordeveloping appropriate measures to reduce droughts on the Huang-Huai-Hai( 3H) Plain. At present,relevant research is more inclined to study meteorological drought itself, without consideration of drought characteristics in different phases in crop-growing seasons and the climate background of global change. In this paper,we determine drought characteristics in all four seasons and the winter wheat growing season on the 3H Plain,together with the effects of climate change. Based on data of 34 meteorological stations from 1961 to 2011,a relative moisture index was calculated to investigate the spatial pattern and temporal variability of drought characteristics on the 3H Plain. The results show varying degrees of drought in spring,winter and the winter wheat growing season. Drought frequency exceeded 90% over the past 50 years on the plain,with spring and winter the driest seasons. There were high-frequency drought areas in central and northern parts of the plain during spring,winter and the winter wheat growing season. The regional distribution of drought intensity and frequency showed an increasing tendency from south to north. A wet trend was detected on the plain in the winter wheat growing season over the last 50 years. However,the relative moisture index changed since 1978. That is to say,the index had an increasing trend from 1961 to 1980 when the plain was wetter; the index decreased from 1980 to 2011 when it was drier. Overall,although drought eased over the entire analysis period,a serious drought tendency has emerged over the last 20 years. In addition,temporal variability of the relative moisture index was significantly correlated with precipitation,solar radiation and relative humidity. This indicates that drought characteristics of the plain were more sensitive to these three climate variables. This has received increased attention in recent years with respect to addressing climate change. The results of our study indicate an arid trend,with increase of temperature in spring and summer on the 3H Plain. Therefore,relevant agencies should create an early warning system of extreme weather events and natural disasters,toward improvement of future regional agricultural scientific management and decision support systems in agricultural production. These agencies should also adapt to climate change by selecting strongly drought-resistant crop varieties and by adjusting cultivation methods and management measures,especially irrigation measures aimed at spring drought on the 3H Plain.

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Xu L L, Lv H Q, Fang L, 2014. Effect of climate change on the climate suitability of summer maize on the Huang-Huai-Hai Plain. Resources Science, 36(4): 782-787. (in Chinese)Maize is an important food crop and the Huang-Huaihai summer maize region is the largest corn-producing area in China. Based on daily 0.25 脳 0.25 degree grid meteorological data under an A1B climate scenario(1951-2100)extracted from the regional climate model RegCM3 and 1971-2000 daily meteorological data for the Huang-Huaihai region,summer maize climate suitability modeling across the whole growth period was contrasted and combined with temperature,precipitation and sunshine. Our aim was to provide a theoretical basis for the rational development and utilization of climate resources and adjusting the layout of agricultural production. The temporal and spatial variation characteristics of summer maize climate suitability in Huang-Huaihai from 1951-2100 were analyzed. We found that the climate suitability of summer maize from 1951 to 2100 followed a downward trend. During 1951 to 2010,summer maize climate suitability was mostly higher than 0.8 with southern Hebei,eastern Henan and western Shandong increasing slightly. It begins to decline 2011-2040 to 0.65~0.75,and then decreases fiercely to 0.45~0.5 from 2071-2100. The jointing-tasseling and heading-maturity stages were more sensitive to moisture and temperature compared to other growing-stages. From 1951-2100,the temperature and precipitation suitability degree on summer maize jointing-tasseling and heading-maturity stages both declined drastically,while that for the sowing-emergence and emergence-jointing stages changed slightly. The precipitation suitability degree and temperature suitability degree during these two developmental periods were the main drivers of the decline in summer maize climate suitability.

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Yang S B, Shen S H, Zhao X Y.et al., 2010. Impacts of climate changes on rice production in the middle and lower reaches of the Yangtze River.Acta Agronomica Sinica, 36(9): 1519-1528. (in Chinese)Increasing atmospheric greenhouse gas concentration is expected to induce significant climate change over the next century, but the impacts on society remain highly uncertain. This paper aimed to assess the potential impacts of climate change on rice crop (<em>Oryza sativa</em> L.) production in the middle and lower reaches of the Yangtze River, where is one of the most important food production regions in China. Data taken from the PRECIS regional climate model were used as the baseline (1961&ndash;1990) and future (2021&ndash;2050) periods under IPCC SRES A2 and B2 scenario conditions, and were used as input of the rice model ORYZA2000. Simulations were performed with and without considering the enhanced CO<sub>2</sub>-fertilization effects to evaluate the response of rice crop to raised temperature and CO<sub>2</sub> concentration, respectively. The results indicated that the rice growth duration would be shortened and yield would be declined significantly with raising temperature future when CO<sub>2</sub>-fertilization effects was not considered. The rice growth duration would be shortened by 4.5 d and yield would be reduced by 15.2% under A2 scenario in 2021&ndash;2050 periods compared with the baseline weather while they would be 3.4 d shortened and 15% reduced respectively under B2 scenario in the same period. The areas where rice yield reduced more than 20% concentrated on most regions of Anhui, Hubei and Hunan provinces. The significance of the enhanced CO<sub>2</sub>-fertilization effect to rice crop was found under the simulated future elevated CO<sub>2</sub> concentrations (2021-2050) for both A2 and B2 scenarios. But it was still not enough to offset the negative effects of warming for single crop rice and early rice, except for the late rice that the contribution of CO<sub>2</sub>-fertilization effect on rice yield was greater. With considering CO<sub>2</sub>-fertilization effect, the rice yields declined by 5.1% and 5.8% under A2 and B2 scenarios, respectively. The areas with a serious yield reduction decreased and the average yield reduction were lessened remarkably. Meanwhile, the areas with an increase in rice yields were founded in some parts of Jiangxi and Zhejiang provinces, although the yield increase might be less than 10%. In addition, the yield stability, defined as the ratio of standard deviation to average yield at each grid across each province, would be increased in 2021&ndash;2050 periods when CO<sub>2</sub>-fertilization effect was considered, indicating that the CO<sub>2</sub>-fertilization effect may reduce the future yield variability. However, there were still many uncertainties in this study. The possible impact of water stress under future climate was not considered, due to the automatic irrigation pattern selected. The soil parameters used as input to the ORYZA2000 might increase the uncertainties for assessing the impacts of climate change on rice yield. Finally, the overall results were compared with those in other studies, in which CERES-Rice was employed and a good agreement was obtained, indicating that the rice model ORYZA2000 can be well applied in assessing the impact of climate change on rice crop in China.

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Zhang G L, Dong J W, Zhou C P.et al., 2013. Increasing cropping intensity in response to climate warming in Tibetan Plateau, China.Field Crops Research, 142: 36-46.Effects of global warming on agriculture have attracted lots of attention; however, agricultural response to climate change has been hardly documented in alpine regions. The Tibetan Plateau (TP) has a low agricultural portion, but it is an increasing minority, which plays an important role in regional food security due to growing population. The region of Brahmaputra River and its two tributaries in Tibet Autonomous Region (BRIT) is the main alpine agricultural area in the TP. Rapid warming has substantially affected agro-climate resources there and altered cropland pattern as well as cropping intensity. In this study, we explored how climate warming affected cropping intensity in past decades in BRTT. The potentially spatial distributions of single and double cropping systems in different decades (1970s, 19805, 1990s and 2000s) were simulated based on a cropping suitability model, considering climatic, terrain and water factors. The results showed a significant increase of cropping intensity in some regions, in response to climate warming. The area suitable for single cropping increased from 19 110 km(2) in 1970s to 19 980 km(2) in 2000s, expanding from the downstream valleys of Lhasa River and Nyang Qu River of the tributaries of Brahmaputra to upstream valleys. The area suitable for double cropping gradually increased from 9 km(2) in 1970s to 2015 km(2) in 2000s, expanding from the lower reaches of Brahmaputra River in Lhoka Prefecture to the upper ones, as well as the Lhasa River tributaries. The upper limit elevation suitable for single cropping rose vertically from 5001 m above sea level (ASL) to 5032m ASL from 1970s to 2000s, meanwhile that of double cropping rose from 3608 m ASL to 3813 m ASL. Overall, increased cropland area and cropping intensity due to climatic warming could increase food production in BRIT to some extent. Further investigation about potential uncertain effects from warming is still needed for regional agricultural adaption to climate change. (C) 2012 Elsevier B.V. All rights reserved.

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