Agriculture, Ecosystems and Environment

Agriculture, Ecosystems and Environment 127 (2008) 107 118 Contents lists available at ScienceDirect Agriculture, Ecosystems and Environment journal homepage: www.elsevier.com/locate/agee Climate-induced changes in crop water balance during 1960 2001 in Northwest China Yanzhao Yang, Zhiming Feng, He Qing Huang *, Yaoming Lin Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Anwai, Beijing, 100101, China ARTICLE INFO ABSTRACT Article history: Received 30 March 2007 Received in revised form 10 March 2008 Accepted 13 March 2008 Available online 25 April 2008 Keywords: Climate change Agriculture Water Crops GIS Spatial distribution Sustainable development Northwest China Climate change affects regional agricultural development, but a quantitative assessment of large-scale impacts remains difficult. Northwest China has experienced considerable climate change during the last 40 years, and this study uses GIS technology to evaluate the impacts of that change on the agricultural water balance. Results show that over the last 40 years the climate has transitioned from a warm-dry to a warm-wet pattern in the northwestern area of Northwest China, while exhibiting a pattern of increasing aridity in other parts of the region since the 1980s. Through analysis of the spatio-temporal distribution of agricultural water balance using water cycle models that include climatic, crop and cropland layers, we found that the climate warming in the northwestern area of the region has led to a notable reduction in the agricultural water deficit. This reduction, however, still cannot significantly alleviate the water deficit. Finally, we argue that to make agricultural development sustainable in this area, both hard and soft approaches are needed to bring about efficient use of the limited water resources. ß 2008 Elsevier B.V. All rights reserved. 1. Introduction In the last several decades, climate warming has been observed at local to regional and global scales (e.g., Voortman, 1998; Boyles and Raman, 2003; Du et al., 2004; Macdonald et al., 2005). The recent report of IPCC (2007) presents a detailed evaluation of longterm worldwide observations on climate change and a sound physical analysis of the potential trend of the change. It concludes that it is very likely that the global climate is going to get warmer in the near future. In Northwest China, observations have shown that water level of lakes has been rising, and surface area expanding since 1987. These observations are much different than the normal trend of the regional climate becoming warmer and drier, leading Shi et al. (2002) to hypothesize that they signal a climatic shift from a warm-dry to a warm-humid pattern in the region. This climate change in Northwest China, nevertheless, is spatially and temporally heterogeneous. Qian and Zhu (2001) examined the variations of surface air temperature and atmospheric precipitation across China from 1880 to 1998 and attributed the recent climate warming in Northwest China to both the evolution of the monsoon system in East Asia and intensified human activity. Based on meteorological observations, * Corresponding author. Tel.: +86 10 64888992; fax: +86 10 64888992. E-mail address: huanghq@igsnrr.ac.cn (H.Q. Huang). Li et al. (2003) found that the emergence of a climatic transition from a warm-dry to a warm-wet pattern is only limited to the western area of Northwest China, while it remains very dry with no significant increase in precipitation in the central and eastern areas. Recently, Shi et al. (2007) made a very detailed investigation of meteorological data and found that the regional climate change falls into three categories: notable change, slight change and no change. Using a meteorological model, they also simulated the future climate of Northwest China and predicted that the annual temperature and precipitation in the region will increase 2.0 8C and 19%, respectively. China, like many other parts of the world, has experienced continual population growth, rapid economic development and an increased awareness of ecological needs over the last several decades. These changes have made already scarce freshwater resources an even more important factor exerting significant restrictions on local to regional and even global socio-economic development and environmental conservation. It has been estimated that some 26 countries, with a total population of 230 million, experience water scarcity and 67% of the future population of the world may experience some impact from water stress (Batchelor, 1999; Wallace, 2000). Agriculture is the largest use of freshwater by humans, accounting for around three quarters of global water consumption by humans (Bennett, 2000; Qadir et al., 2003; Sophocleous, 2004). It is estimated that agriculture will remain the largest use of freshwater for satisfying the demands of 0167-8809/$ see front matter ß 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.agee.2008.03.007

108 Y. Yang et al. / Agriculture, Ecosystems and Environment 127 (2008) 107 118 the growing human population, economic development and ecosystem conservation in the future (Batchelor, 1999; Zhu, 1997). Evaluation of agricultural water resources has thus become a very important issue for identifying effective adaptation measures for regional agricultural development under the effect of global warming. With the emergence of global warming, sustainable socioeconomic development has become an even more urgent issue for research, especially in the water-scarce area of Northwest China. Due to the complex spatio-temporal distribution of temperature, precipitation, evaporation, soil characteristics and other factors in such a large area, this study deploys GIS techniques to evaluate regional climate change and its impacts on the agricultural water balance. With the growing availability and sophistication of GIS, the use of GIS techniques has become increasingly common in both natural and social sciences. In regional water resources research, GIS is now widely used as a spatial analysis and presentation tool, facilitating the quantitative characterization and visualization of spatial variables and relationships. Taking advantage of the powerful data integration and spatial analysis capability, this study utilizes ArcGIS to interpolate data and to investigate and visualize the spatial distribution of water balance in Northwest China in term of the natural water cycling process. Climatic, crop, and cropland water balance models were developed to reflect this process. Based on data collected from satellite images and field investigation, we present a detailed analysis of spatio-temporal variations in climate change in Northwest China and quantify the impacts of the change on the spatio-temporal distribution of agricultural water balance with three models. In conclusion, we suggest effective approaches for achieving sustainable agricultural development in the region. 2. Study area Northwest China consists of the provinces of Shaanxi, Gansu, and Qinghai, and the autonomous regions of Ningxia and Xinjiang. It includes 356 counties with an area of 3.1 million km 2, 32.44% of Fig. 2. Changes of population and agricultural factors in Northwest China during 1960 2006 (data source: NBSC, 2007). China s total area (NBSC, 2007). Among them, the economy of 313 counties is predominantly agricultural. Over the last several decades, regional GDP has increased by 118.3 times, from 9.38 billion yuan in 1960 to 1.12 trillion yuan in 2006, accompanied by an increase in population from 43.4 million in 1960 to 94.6 million in 2006. In comparison with other regions in China, the economy in most of Northwest China is still relatively undeveloped and the ecological environment is highly vulnerable (Figs. 1 and 2). Located in the center of the Eurasian continent, this region has a typical arid and semi-arid continental inland climate, characterized mainly by low and irregular precipitation, high evaporation, and pronounced periods of drought. The mean annual precipitation in the region ranges from 10 to 1200 mm, and progressively decreases in volume from mountainous areas to the lower areas of drainage basins (Fig. 3). The mean annual evaporation in the region ranges from 800 to 3200 mm (Fig. 3). Renewable water resources available in the region are around 2200 m 3 per person per year, approximately the same as the living standard used in western and industrialized countries (2000 m 3 )(Song et al., 2005; Bouwer, 2000). However, in the provinces of Shaanxi and Gansu and the autonomous region of Ningxia, the amount of per-capita water resources available was Fig. 1. Location of Northwest China and the spatial distribution of 13 agro-ecological zones.

Y. Yang et al. / Agriculture, Ecosystems and Environment 127 (2008) 107 118 109 Fig. 3. Spatial distribution of major climatic factors in Northwest China ((A) mean annual temperature, (B) annual precipitation, (C) annual evaporation).

110 Y. Yang et al. / Agriculture, Ecosystems and Environment 127 (2008) 107 118 only 900, 800 and 190 m 3 per year on average, respectively, during 1995 2005. This means that of the 94.63 million residents in the region, 69.1 million or 73% of them experience water scarcity. The regional economy is primarily agricultural. In 2006, agricultural land area totaled 154.8 million ha, accounting for 49.74% of the region s area (MLRC, 2006). This includes 14.4 million ha of cultivated land, 110.9 million ha of pasture, 25.5 million ha of woodland, and 1.3 million ha of fruit orchard, accounting for 9.32%, 71.63%, 16.49%, and 0.85% of agricultural land, respectively. The major crops cultivated in the region are wheat (spring and winter wheat), maize (spring and summer maize), cotton, potato, oil-seed rape, vegetables, soybean, rice, sugar beet, and flax, of which wheat and maize constitute a large proportion. In 2006, the sown area of wheat and maize accounted for 24.23% and 17.22% of the total sown area. In contrast, the sown area of cotton, potato, oil-seed rape, vegetables, soybean, rice, sugar beet and flax accounted respectively for only 10.64%, 8.83%, 7.34%, 7.07%, 5.99%, 2.22%, 0.74% and 0.19%. Due to the predominance of agriculture, water usage in agricultural sector is the highest of all human uses. Agricultural water consumption amounted to 64.5 trillion m 3 in 2005, accounting for 84.95% of all human water use in the region. The amount of irrigation water was 58.2 trillion m 3, or 90.21% of total agricultural water usage (MWRC, 2005). Although there are extensive irrigation systems in Northwest China, water usage is notoriously inefficient. It is estimated that annual average water usage is about 11,130 m 3 /ha in the region, much higher than the national average irrigation use of 6000 m 3 /ha. In some parts, particularly in the autonomous region of Ningxia, the annual irrigation water usage is 22,215 m 3 /ha, although more than half of this water is lost to leakage before reaching farmers fields. Water resources have been viewed as common resources and people often dispute about the apportioning of water. One of the main disputes is over water distribution among the upper, middle and lower reaches of rivers. For example, the lower reach basin of Heihe River has been affected by intensive water utilization in the middle reach to such an extent that the downstream annual runoff was reduced from 1.19 trillion m 3 in the 1950s to 0.69 trillion m 3 in the 1990s (Wang and Cheng, 2000). As a result, a large amount of cultivated land in the lower reach could not be appropriately irrigated. In places such as the Heihe River and Shiyanghe River drainage basins, the ratios of used water resources/usable water resources have reached 112% and 154%, respectively. This implies that the used quantity of water resources significantly exceeds the amount of renewable water resources. This over-exploitation of water resources significantly affects the groundwater table in the middle and lower reaches of the two rivers. It has also been observed that irrational irrigation in oases has resulted in a series of environmental disasters including soil salinization, desertification, lake contraction and drying, and a significant drop in the groundwater table (Wang et al., 2002; Song et al., 2004). These problems are caused not only by natural factors such as the uneven spatial and temporal distribution of precipitation, but also by a lack of knowledge on large-scale water balance issues and the resulting mismanagement. To solve these problems, it is necessary to gain a more detailed understanding of the variations in agricultural-use water over space and time in the region, especially with the emergence of a regional gradual warming trend. 3. Water balance models 3.1. Levels of water cycle Water cycling in agro-ecosystems is a complex process but can be broadly characterized by a continuum of atmosphere plant soil. The major factors affecting water balance in this cycle are precipitation, evaporation, evapotranspiration, and soil water. These factors are closely related to climate conditions and to quantify the impacts of climate change on agricultural water balance, this study examines three levels of water balance inherent in the natural water cycling process. The first level of water balance reflects regional wetness and dryness and is determined through analysis of the spatio-temporal interactions between precipitation and crop evapotranspiration, and is termed the climatic water balance. The second level of water balance is determined through examining the difference between the water demand of crops and rainfall for various crop growth periods, and is termed the crop water balance. The third level of water balance concerns the combined effects of crops water requirement on rainfall and soil water in cropland and is thus labeled the cropland water balance. 3.2. Climatic water balance model Climatic water balance has been assessed by meteorologists and geographers with numerous models (Zhao et al., 2000; Wang et al., 1998). In line with previous studies, this study applies the following climatic water balance model: CL i ¼ P i ET 0;i (1) where CL i is the climatic water balance in month i, i is the month of year, P i represents the precipitation in month i, and ET 0 denotes the monthly reference crop evapotranspiration. Based on the monthly weather data generated for grid cells of 1km1 km size, this study uses the Penman Monteith method recommended by FAO (Allen et al., 1998) to calculate the reference crop evapotranspiration in the following form: ET 0 ¼ 0:408DðR n GÞþr 900 Tþ273 U 2ðe s e a Þ (2) D þ rð1 þ 0:34U 2 Þ where ET 0 is the reference level of crop evapotranspiration (mm day 1 ), R n represents the net radiation at the crop surface (MJ m 2 day 1 ), G denotes the density of soil heat flux (MJ m 2 day 1 ), r is the psychrometric constant (kpa 8C 1 ), T is the mean air temperature at 2 m height (8C), U 2 represents the wind speed at 2 m height (ms 1 ), e s is the saturation vapour pressure (kpa), e a denotes the actual vapour pressure (kpa), e s e a represents the saturation vapour pressure deficit (kpa), and D denotes the slope of vapour pressure curve (kpa 8C 1 ). Due to the lack of directly measured data, the net radiation R n and the density of soil heat flux G are estimated using the empirical formulations presented in the FAO Irrigation and Drainage Paper 56 for a long time-step (month) (Allen et al., 1998). 3.3. Crop water balance model The crop water balance accounts for the difference between precipitation and water requirements of crops during crop growth periods. From studies by Zhao (1996) and Li et al. (2004), this type of water balance model can be written as: CR ij ¼ P ij ET c;ij (3) where CR ij is the crop water balance for crop j in month i (mm), P ij represents the precipitation for crop j during month i (mm), ET c is the monthly crop evapotranspiration (mm), i is the month of year, and j is the type of crops. The crop evapotranspiration (ET c ) is the amount of ET for a specific crop, and can be calculated with the crop coefficient approach (Allen et al., 1998; Fan and Cai, 2002). This approach can

Y. Yang et al. / Agriculture, Ecosystems and Environment 127 (2008) 107 118 111 be written as: ET c ¼ K c ET 0 (4) where ET 0 is the reference crop evapotranspiration (mm) and K c is a crop-related coefficient. 3.4. Cropland water balance model Because soil in cropland has a capacity for storing and supplying a certain amount of water to crops, determination of the water balance status of cropland is made by applying a complex model that takes into account the combined effects of spatio-temporal changes in precipitation, soil water content and crop type. This model first examines whether precipitation alone can satisfy the water demand of each crop (ET c ) based on the following condition: BL t ¼ P t ET c (5) where BL t is the excessive precipitation for the crop at time t. When precipitation alone satisfies the water demand of a crop, or BL t > 0, the status of water balance can be determined from:if BL t +ST t 1 > ST max : Q st ¼ BL t þ ST t 1 ST max ; DEF t ¼ 0; ST t ¼ ST max (6) else if BL t +ST t 1 ST max : Q st ¼ 0; DEF t ¼ 0; ST t ¼ BL t þ ST t 1 (7) where ST t 1,ST t,st max, Q st and DEF t are the soil water content at time t 1 and t, the maximum soil water content, the runoff at time t, and the cropland water deficit, respectively. When precipitation alone cannot satisfy the water demand of the crop, or BL t < 0, the soil content ST t is normally determined based on the empirical relationship between potential soil evaporation and soil water content. This study illustrates the relationship with an empirical curve developed for each agroecological zone based on studies by Lin (1997) and Lin et al. (2000). With the determination of the difference in the soil water content at the t 1 and t time-steps, or DST t =ST t 1 ST t directly from the curve, the status of water deficiency (DEF) can be calculated from the following model:if DST t (ET c P t ) 0: DEF t ¼ 0; Q st ¼ 0 (8) else if DST t (ET c P t ) < 0: DEF t ¼ ðet c P t DST t Þ; Q st ¼ 0 (9) This water balance model has previously been applied to investigate the status of cropland water balance in North China. In most cases, it produces satisfactory water balance simulations with errors generally less than 10% (Lin, 1997; Lin et al., 2000). Using this model, this study estimates the monthly cropland water balance for 12 major crops (spring and winter wheat, spring and summer maize, cotton, potato, oil-seed rape, vegetables, soybean, rice, sugar beet, and flax) in the 313 agricultural counties of Northwest China over the period of 1960 2001. 4. Data collection To apply the above three water balance models, four basic data types are required: monthly weather data, crop phenology data, soil properties, and regional cultivation and social data. In Northwest China, there are 129 meteorological stations governed by the Meteorological Administration of China (MAC). The available observations of monthly weather data and soil properties recorded at these stations during 1960 2001 were collected from MAC. The weather database includes monthly values of maximum air temperature, minimum air temperature, relative air humidity, wind speed, and irradiation. All of these weather data were assigned to grid cells of 1 km 1 km size by interpolation using the ordinary Kriging method, inverse distance weighting, and gradient distance weighting. Before interpolation, the raw data were analyzed to investigate the degree of correlation of each factor with altitude. If the correlation was found to be significant, the data were then corrected based on a reference altitude. Otherwise, a direct interpolation was performed. Of the available methods, we chose the one that produces a minimum meansquare error for each factor. The soil database includes soil types, surface texture (upper 100 cm of the soil), soil moisture (upper 100 cm of the soil and in 10 layers), and soil bulk density for each of the 129 meteorological stations. Using the ordinary Kriging method, soil water content and water holding capacity were derived for each grid cell of 1 km 1 km size. The agricultural calendars for each crop were obtained through personal interviews with experts and local farmers. The questionnaire data were used to calculate the average sowing and harvesting dates for each crop type. Because many similar characteristics are displayed in an agricultural zone in terms of climate, geographic conditions and agricultural calendar, the sowing and harvesting dates for all crops were assumed to be the same in each zone. Of various methodologies for classification of agro-ecological zones, this study applies the method proposed by Chen (2001), which has been widely applied in China. According to this, Northwest China can be classified into 13 agro-ecological zones (Fig. 1). Table 1 Variations of temperature and precipitation in 13 agro-ecological zones during 1960 2001 Climate factor Period I1 I2 I3 I4 II1 II2 III1 III2 III3 III4 III5 IV1 V1 Maximum temperature (8C) 60s 13.0 16.5 17.4 13.6 10.1 9.8 11.7 13.2 14.3 15.3 17.9 15.5 17.22 70s 12.9 16.1 17.3 13.6 10.1 9.9 11.6 13.2 14.4 15.5 18.0 15.5 17.29 80s 13.0 16.2 17.4 13.7 10.0 10.0 11.7 13.2 14.5 15.4 17.7 15.6 16.93 90s 13.6 16.8 17.8 14.4 10.7 10.3 12.4 14.0 15.4 16.3 18.7 16.3 17.80 Average 13.1 16.4 17.5 13.9 10.3 10.0 11.9 13.4 14.7 15.7 18.1 15.8 17.34 Minimum temperature (8C) 60s 0.2 2.0 3.4 1.1 5.0 5.6 2.7 0.8 1.3 3.8 8.0 2.0 6.62 70s 0.1 1.9 3.6 0.9 4.5 5.0 2.3 0.9 1.4 4.0 8.1 2.2 6.81 80s 0.6 2.7 3.9 0.6 4.1 4.7 2.0 1.1 1.4 4.0 8.2 2.6 6.83 90s 1.2 3.4 4.4 0.2 3.7 4.5 1.7 1.6 2.2 4.6 8.8 3.4 7.20 Average 0.4 2.6 3.9 0.6 4.3 4.9 2.1 1.1 1.6 4.2 8.3 2.6 6.89 Precipitation (mm) 60s 178.5 81.6 75.5 175.8 351.2 231.6 370.7 467.9 415.4 570.6 665.8 238.3 754.14 70s 181.3 87.0 73.5 188.0 348.2 233.5 387.3 456.2 382.4 525.5 627.9 241.4 705.06 80s 197.5 91.1 81.5 183.5 360.7 246.9 379.1 439.4 371.5 543.0 684.1 214.2 794.27 90s 212.9 99.7 89.4 177.7 328.4 232.6 367.0 424.7 365.5 488.8 563.8 230.3 660.22 Average 194.3 90.7 80.7 181.4 346.0 236.2 375.9 444.9 381.2 527.9 630.3 230.7 723.72

112 Y. Yang et al. / Agriculture, Ecosystems and Environment 127 (2008) 107 118 Fig. 4. Variation of temperature and precipitation in 13 agro-ecological zones during 1960 2001 ((A) maximum temperature, (B) minimum temperature, (C) precipitation). The cultivated areas for 12 major crop types in the 313 agricultural counties of Northwest China were collected from the National Bureau of Statistics of China (NBSC) (NBSC, 2005). Regional cultivation methods and soil water use efficiency data were obtained from local farmers and experts. 5. Evaluation of the impacts of climate change with GIS 5.1. Trends of climate change Table 1 and Fig. 4 present the variation in major meteorological factors in the 13 agro-ecological zones of Northwest China during the period of 1960 2001. These factors include maximum and minimum temperature and precipitation, with values for each zone representing the averages from all grid cells in the zone. As seen in Table 1, the maximum temperature in the 1990s was higher than average in all 13 agro-ecological zones, increasing by 0.27 to 0.63 8C, while in the other decades it was generally lower than average. Although the minimum temperature in all 13 ecological zones in the 1990s was higher than average, increasing 0.30 0.82 8C, a pattern of increasing minimum temperature actually has occurred in most ecological zones since the 1980s. It is most likely that climate warming in Northwest China emerged in the 1980s, although it was not well recognized until the 1990s. The variation in precipitation over the last 40 years exhibits a complex pattern over the 13 agro-ecological zones. As is evident in Table 1 and Fig. 4, precipitation increased considerably in the agroecological zones of I1, I2 and I3 (the whole area of Xinjiang) in the 1990s, about 19 mm more than the average and about 34 mm more than the 1960s average in Zone I1. In the other agroecological zones, precipitation was higher in both the 1960s and 1980s but lower in the 1970s and 1990s, with the lowest precipitation levels evident in the 1990s. These results demonstrate that the climate has transitioned from a warm-dry to a warm-wet pattern in the northwestern area of Northwest China. In other parts of the region, there was no significant increase in precipitation but a noticeable increase in temperature since the 1980s, implying that these areas have been gradually getting drier. 5.2. Spatial distribution of water balance in natural water cycle process Using the collected data and Eqs. (1) and (2), the annual and monthly climatic water balances were calculated for each 1-km grid cell. Because the collected data show that daily maximum and minimum air temperatures and the wind speed at 2 m height, U 2, in the region vary respectively in the ranges of 36 32 8C and 0.1 5.8 ms 1, the psychrometric constant r is calculated to range from 0.036 to 0.068 kpa 8C 1. Thus, we calculated using the Penman Monteith method that the daily and monthly values of the reference crop evapotranspiration ET 0 vary within the ranges of 0.1 9.7 and 4.3 301.6 mm, respectively, with higher values of ET 0 during summer periods (Fig. 5(B)). To reflect the spatial variation of climatic water balance in the different agro-ecological zones over the last 40 years, the calculated water balances for grid cells in each agro-ecological zone were averaged and presented in Fig. 6. It can be noted that the surplus annual climatic water balances mainly occurred in Zone V1 and a small area of Zone III5, while the highest water deficit was exhibited in Zones I1, I2 and I3. The spatial distribution of water deficit shows a pattern of increasing from southeast to northwest.

Y. Yang et al. / Agriculture, Ecosystems and Environment 127 (2008) 107 118 113 Fig. 5. Spatial distribution of monthly reference crop evapotranspiration ((A) November, (B) July). The bar charts in Fig. 6 show the spatial distribution of monthly climatic water balance in each agro-ecological zone, using 41-year (1960 2001) averages. It can be seen from these bar charts that the water deficits in northern agro-ecological zones (Zones I1, I2, I3, I4, IV1 and III3) are generally very high, particularly during the summer periods (Fig. 6). In calculating the crop water balance, we used 12 major crops planted in the region. Since K c in Eq. (4) varies predominantly based on specific crop characteristics and only to a limited extent due to climate, we obtained the monthly values of K c for each crop in the different agricultural zones from local experiments and previous studies (GWR, 1999). We found that the value of K c ranges from 0.25 to 1.3 in the different crop growth periods, with much higher values during the tasseling and grain-filling periods and lower values in the initial growth and maturity stages of most crops. Of the 12 crops studied, the values of K c for rice is the highest, greater than 1 in most areas, while the average values of K c for potato over the whole growth period are the lowest, in the range of 0.7 0.9. Of the 12 crop types, spring wheat is the most widespread crop in Northwest China, and its annual water balance is calculated from Eqs. (3) and (4) for each grid cell of 1 km 1 km size. The spatial distribution of the average annual water balance for spring wheat over the last 40 years is presented in Fig. 7. It is evident that water deficit is a major characteristic of spring wheat in Northwest China. The water balance of spring wheat exhibits the same pattern of spatial variation as the climatic water balance, with a water deficit tending to increase from southeast to northwest. The bar charts in Fig. 7 illustrate the average crop water balance for the 12 major crops in each agro-ecological zone. In most agroecological zones, particularly in Zones I1, I2, I3, I4, IV1, and III3, the water deficits of rice, cotton, sugar beet, and vegetables are higher

114 Y. Yang et al. / Agriculture, Ecosystems and Environment 127 (2008) 107 118 Fig. 6. Spatial distribution of annual and monthly (bar charts) climatic water balance in 13 agro-ecological zones, 1960 2001 average. than those of the other crops, and the water deficit of potato is the lowest. Using Eqs. (5) (9) to compute cropland water balance, we analyzed the collected data on soil bulk density, soil field water capacity and withering soil humidity, finding that ST max takes a value between 197 and 312 mm in the 13 agro-ecological zones when the soil depth is 1 m. Because the collected census data on cultivated areas for each crop are by county, the spatial distribution of annual cropland water balance for spring wheat in Northwest China is calculated at the county level. Using the sown area of spring wheat as a weighting factor, the average cropland water balance of spring wheat from all the counties in each eco-agricultural zone is presented in Fig. 8. In general, precipitation and soil water cannot meet the water demand of Fig. 7. Spatial distribution of crop water balance for spring wheat and for 12 crop types (bar charts) in 13 agro-ecological zones, 1960 2001 average (RI, SW, WW, PM,UM, PO, SO, CO, RA, FL, SU, and VE represent rice, spring wheat, winter wheat, spring maize, summer maize, potato, soybean, cotton, oil-seed rape, flax, sugar beet, and vegetables, respectively; The background is the crop water balance for spring wheat on cultivated land at 1 km 1 km scale in 13 agricultural zones; The location of cultivated land is derived from China s 1:1,000,000 land classification map extracted from remote sensing imagery by Liu et al. (2005)).

Y. Yang et al. / Agriculture, Ecosystems and Environment 127 (2008) 107 118 115 Fig. 8. Spatial distribution of cropland water balance for spring wheat and 12 crop types (bar charts) in 13 agro-ecological zones, 1960 2001 average (The meanings of RI, SW, WW, PM, UM, PO, SO, CO, RA, FL, SU, and VE are the same as in Fig. 7 and the background is the cropland water balance for spring wheat at the county level calculated based on cropland water balance at 1 km 1 km scale). spring wheat, and the water deficit tends to increase from southeast to northwest and from hilly areas to plains. In most areas, the cropland water balance for spring wheat is a deficit, with the water deficit of spring wheat in Turfan County in East Xinjiang (Zone I2) the highest of all counties at around 670 mm. Nevertheless, the water balance of spring wheat in the prefectures of Hanzhong and Ankang in South Shaanxi (Zone V1) is a surplus, and soil water and precipitation there are approximately sufficient for meeting water requirements. The bar charts presented for each agro-ecological zone in Fig. 8 show the cropland water balances for 12 crop types averaged from all counties in a zone, with sown area of crops as a weighting factor. In most agro-ecological zones, the water deficits of economic crops such as cotton, sugar beet and rice are generally higher, while the water deficit of potato is considerably lower. The water deficit of cotton amounts to about 809 mm, the highest of all 12 crop types, while the water deficit of potato is the lowest, around 67 mm (Table 2). Water demand and climatic conditions at different growth stages vary considerably, and consequently affect water balance. Table 2 shows the average cropland water balance for the 12 crop types in the region at various growth stages. For most crops, the water deficit is generally lower in the initial growth and maturity stages, but much higher in the tasseling and grain-filling periods. For example, the cropland water deficit of spring wheat during May and July reached 103 and 89 mm, respectively, while only 17 mm in the initial growth stage and 48 mm in the maturity period. 5.3. Impacts of climate change on water balance Table 3 and Fig. 9 present the variation in climatic, crop and cropland water balances for the 13 agro-ecological zones over the last four decades. In the western area (Zones I1, I2 and I3), which consists mainly of the autonomous region of Xinjiang, the water deficits based on the climatic, crop and cropland models all show a similar trend of decreasing over time. In the 1960s, the average climatic water deficit of Beijiang hilly area (Zone I1), Dongjiang basin (Zone I2) and Nanjiang hilly area (Zone I3) were 921, 1207 and 1034 mm, respectively, which is 6%, 7% and 5% higher than the 41-year average. In the 1990s, the climatic water deficits in these three zones declined to 823, 1055, and 929 mm, respectively, a Table 2 Cropland water balance at different growth periods of 12 main crops (mm) Crop January February March April May June July August September October November December Growing period Spring wheat 17 48 103 89 48 305 Winter wheat 1 1 3 13 41 48 54 15 5 2 1 184 Spring maize 5 11 35 53 45 7 156 Summer maize 90 48 62 49 0 249 Rice 72 117 126 112 79 5 511 Potato 2 5 14 22 17 7 67 Soybean 18 13 23 40 32 29 155 Cotton 35 134 180 189 157 74 40 809 Oil-seed rape 2 1 9 32 40 65 68 47 8 10 14 7 303 Flax 9 12 69 119 107 7 323 Sugar beet 17 112 154 144 94 521 Vegetables 11 17 33 53 73 84 61 54 38 27 16 12 479

116 Y. Yang et al. / Agriculture, Ecosystems and Environment 127 (2008) 107 118 Table 3 Water balance in natural water cycle process during 1960 2001 (mm) Water balance Period I1 I2 I3 I4 II1 II2 III1 III2 III3 III4 III5 IV1 V1 Climatic water balance 60s 921 1207 1034 832 364 267 427 314 517 277 190 753 1 70s 909 1155 1037 852 387 277 418 343 572 344 235 768 66 80s 851 1121 970 810 351 260 399 327 551 274 104 789 85 90s 823 1055 929 810 395 264 408 364 591 378 286 835 89 Average 871 1127 987 825 376 267 412 339 562 323 208 790 22 Cv 0.10 0.10 0.07 0.06 0.14 0.09 0.17 0.27 0.19 0.37 0.73 0.12 6.28 Crop water balance 60s 615 775 657 491 175 96 229 167 311 164 115 455 24 70s 606 743 663 491 188 105 220 184 346 206 138 458 16 80s 566 721 617 464 160 92 205 163 317 146 33 469 102 90s 542 674 590 474 197 104 218 197 349 227 164 490 28 Average 579 723 629 479 183 100 217 179 338 189 117 470 13 Cv 0.10 0.07 0.07 0.08 0.22 0.19 0.25 0.39 0.24 0.47 0.92 0.14 5.58 Cropland water balance 60s 604 774 655 485 160 89 196 129 279 123 64 439 45 70s 595 742 662 488 176 100 198 160 320 170 94 450 10 80s 554 721 617 462 152 90 183 137 300 122 13 465 111 90s 526 674 589 472 182 95 194 168 333 193 119 488 1 Average 566 723 627 476 169 94 193 150 311 155 75 463 39 Cv 0.10 0.07 0.07 0.07 0.17 0.13 0.20 0.32 0.20 0.43 0.90 0.13 2.10 decrease of 11%, 13% and 10% compared to their deficits in the 1960s. Similar percentages of increase and decrease are also evident in crop and cropland water deficits. This is essentially consistent with variations in precipitation in the three zones as shown in Table 1. These results demonstrate that although the climate has transitioned from a warm-dry to a warm-wet pattern in the northwestern area of Northwest China, it has only alleviated the water deficit problem to a very limited degree. For the central and eastern areas of Northwest China, Table 1 shows that precipitation in the 1990s was lower than the 41-year average, and water deficiency in the water cycle was consequently higher. In the 1970s, the climate in these areas was slightly drier than in the 1960s, and the water deficits tended to be higher than average, as shown in Table 3 and Fig. 9. During the last 40 years, the highest precipitation levels and lowest water deficit appeared in the eastern areas in the 1980s. In the 1990s, the water deficit in the eastern region increased considerably, and became the highest for most of Northwest China. In the hilly area around Sichuan Basin (Zone V1), which is located in the southeastern part of Northwest China, the cropland water balance became a deficit in the 1990s, Fig. 9. Water balance in natural water cycle during 1960 2001 ((A) climatic water balance, (B) crop water balance, (C) cropland water balance).

Y. Yang et al. / Agriculture, Ecosystems and Environment 127 (2008) 107 118 117 while in Fenwei Valley (Zone III5), the cropland water deficit in the 1990s reached 119 mm, which is 1.58 times the overall average. In the southern Qinghai Plateau and eastern Qinghai hilly areas (Zones II2 and III1), the climatic, crop and cropland water deficits in the 1990s were close to their overall averages, while in the Yinchuan Plain (Zone IV1), the water deficit has increased over the last 40 years. Overall, climate warming trends have made water deficits much more serious in the central and eastern parts of Northwest China. 6. Approaches for sustainable agricultural development As seen in Table 2, economic crops such as cotton, sugar beet and vegetables need more water than the other types of crops. This casts doubt on whether sustainable agricultural development can be achieved in the northwestern area of the region because the sown area of these economic crops has been increasing significantly in recent years (Table 2). In Xinjiang, for example, the sown area of cotton in 1960 was only 0.16 million ha, but it increased to 1.27 million ha by 2006. The main cause for this increase was the rapid development of a marketoriented economy, which enables farmers to pursue higher economic returns through increased cultivation of economic crops. As a result, the limited water resources in the area have been used irrationally, causing more and more conflicts among communities located in different reaches of drainage systems. The highly vulnerable regional ecosystems have also been moving towards a collapsing point (Wang et al., 2002; Song et al., 2004). To resolve these problems, soft approaches for raising public awareness on the long-term importance of ecological conservation and water resource protection for the goal of achieving sustainable development are necessary. However these soft approaches, which focus on the long term, are not sufficient to solve the water deficit problem in an area with a serious scarcity of freshwater resources and a rapidly growing economy. Because in this area most farmers still regard water resources as common resources which are freely available, it is urgent to clarify the legal aspects of water rights and adopt economic measures of commercializing water resources and pricing water usage. An effective management system should be responsible for allocating water resources for each industry, department, enterprise, irrigation area, and perhaps even each household. Only by adopting these stringent regulatory approaches can water usage between upstream and downstream or rural and urban areas, and trade-offs between economic and ecological benefits, be reasonably balanced and the continual expansion of economic crop cultivation be effectively curbed. As practiced in the drainage basin of the Yellow River, a combination of hard approaches for effectively controlling limited water resources with soft approaches to raise public awareness of ecological conservation and water resources protection is the most effective means for areas with serious water scarcity to achieve sustainable development (Su, 2005). 7. Conclusion This study shows that during 1960 2001 the climate in Northwest China has transitioned from a warm-dry to a warmwet pattern in the northwestern area of the region, while becoming drier with no significant increase in precipitation in the central and eastern areas. Due to this change in climate, the average water deficit during the last 40 years is about 6% lower than the average water deficit in the 1960s. In the 1990s, the water deficit in the northwestern area of Northwest China decreased about 11% compared to the water deficit in the 1960s. Despite this significant decrease, the water deficit is still substantial, suggesting that the climatic transition from a warm-dry to a warm-wet pattern in this area can alleviate the water deficit problem to only a very limited degree. In contrast, the significant climate warming in the central and eastern areas of Northwest China, particularly in the 1990s, caused an increase in the water deficit because there was no significant increase in precipitation. Furthermore, this study found that economic crops such as cotton, sugar beet and vegetables require more water than the other types of crops planted in the region. 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