气候变化背景下中国南方地区季节性干旱特征与适应Ⅵ.防旱避灾种植模式优化布局

南方地区是我国重要的农业种植区,季节性干旱严重影响该地区的农业生产.本文基于南方地区不同干旱分区中选取的13个典型地区1981-2007年气象资料和作物生育期、产量等资料,依据各地逐年降水量将其分为干旱年、正常年和丰水年3种不同降水年型,利用作物水分临界期需水量与降水量的耦合度、气象产量、单位面积产值以及全生育期的水分利用效率和降水量5个指标,对典型地区种植模式的综合效益进行评价,得到南方不同区域不同降水年型下的优化种植模式.结果表明: 半干旱区在干旱年型下,宜采取2种抗旱种植模式：马铃-玉米-甘薯和冬小麦-中稻-甘薯.半湿润区在干旱年型下,种植模式以冬小麦-中稻-甘薯最优,油菜-中稻-甘薯次之.在温润区(即典型的季节性干旱区),江南地区在3种年型下均以马铃薯-双季稻最优;西南地区宜搭配抗旱作物进行三熟制种植,如冬小麦-中稻-甘薯、冬小麦-玉米-甘薯、马铃薯-双季稻等.从最大程度利用水热资源角度考虑,三熟种植模式最优,以水旱轮作为主,丰水年型宜搭配水稻.     

Climate science and famine early warning

Food security assessment in sub-Saharan Africa requires simultaneous consideration of multiple socio-economic and environmental variables. Early identification of populations at risk enables timely and appropriate action. Since large and widely dispersed populations depend on rainfed agriculture and pastoralism, climate monitoring and forecasting are important inputs to food security analysis. Satellite rainfall estimates (RFE) fill in gaps in station observations, and serve as input to drought index maps and crop water balance models. Gridded rainfall time-series give historical context, and provide a basis for quantitative interpretation of seasonal precipitation forecasts. RFE are also used to characterize flood hazards, in both simple indices and stream flow models. In the future, many African countries are likely to see negative impacts on subsistence agriculture due to the effects of global warming. Increased climate variability is forecast, with more frequent extreme events. Ethiopia requires special attention. Already facing a food security emergency, troubling persistent dryness has been observed in some areas, associated with a positive trend in Indian Ocean sea surface temperatures. Increased African capacity for rainfall observation, forecasting, data management and modelling applications is urgently needed. Managing climate change and increased climate variability require these fundamental technical capacities if creative coping strategies are to be devised.     

Development and assessment of a coupled crop–climate model

It is well established that crop production is inherently vulnerable to variations in the weather and climate. More recently the influence of vegetation on the state of the atmosphere has been recognized. The seasonal growth of crops can influence the atmosphere and have local impacts on the weather, which in turn affects the rate of seasonal crop growth and development. Considering the coupled nature of the crop–climate system, and the fact that a significant proportion of land is devoted to the cultivation of crops, important interactions may be missed when studying crops and the climate system in isolation, particularly in the context of land use and climate change.
To represent the two-way interactions between seasonal crop growth and atmospheric variability, we integrate a crop model developed specifically to operate at large spatial scales (General Large Area Model for annual crops) into the land surface component of a global climate model (GCM; HadAM3). In the new coupled crop–climate model, the simulated environment (atmosphere and soil states) influences growth and development of the crop, while simultaneously the temporal variations in crop leaf area and height across its growing season alter the characteristics of the land surface that are important determinants of surface fluxes of heat and moisture, as well as other aspects of the land-surface hydrological cycle. The coupled model realistically simulates the seasonal growth of a summer annual crop in response to the GCM's simulated weather and climate. The model also reproduces the observed relationship between seasonal rainfall and crop yield. The integration of a large-scale single crop model into a GCM, as described here, represents a first step towards the development of fully coupled crop and climate models. Future development priorities and challenges related to coupling crop and climate models are discussed.     

Influence of seasonal weather and climate variability on crop yields in Scotland

The climatic sensitivity of four important agriculture crops (wheat, barley, oats, potatoes) in a northern temperate bioclimatic region is investigated using national-level yield data for 1963–2005. The climate variables include monthly and annual meteorological data, derived bioclimatic metrics, and the North Atlantic Oscillation index. Statistical analysis shows that significant relationships between yield and climate vary depending on the crop type and month but highlight the influence of precipitation (negative correlation) and sunshine duration (positive correlation) rather than temperature. Soil moisture deficit is shown to be a particular useful indicator of yield with drier summers providing the best yields for Scotland as a whole. It is also tentatively inferred that the sensitivity of these crops, particularly wheat and barley, to soil moisture deficits has increased in recent years. This suggests that improved crop yields are optimised for dry sunny years despite the continued prevalence of considerable inter-annual variability in seasonal weather.     

Phenotypic flexibility in basal metabolic rate is associated with rainfall variability among populations of rufous-collared sparrow

Phenotypic flexibility in metabolic rates allows organisms to reversibly adjust their energy flow to meet challenges imposed by a variable environment. In turn, the food habits hypothesis (FHH) predicts that species or populations adjust their basal metabolic rate (BMR) according to the diet attributes such as food abundance or predictability. Desert ecosystems represent a temporally heterogeneous environment because of low rain pulse predictability, which is also associated with temporal variation in food resources. In the present study, we investigated the relationship between the magnitude of BMR flexibility in response to dietary acclimation and the inter-annual rainfall variability in three populations of rufous-collared sparrows. Specifically we addressed the question of whether birds from a desert environment are more flexible in BMR than those from non-desert habitats. We found a positive trend between BMR flexibility and the inter-annual rainfall variability. In fact, dietary treatments had a significant effect only in desert birds, a result that also supported the FHH. Our study confirms the existence of phenotypic variation in response to environmental conditions among populations, and also highlights the importance of considering the circumstances in which phenotypic flexibility evolves and the specific environmental cues that induce their expression.     

Inter-annual Variability of Soil Respiration in Wet Shrublands: Do Plants Modulate Its Sensitivity to Climate?

Understanding the response of soil respiration to climate variability is critical to formulate realistic predictions of future carbon (C) fluxes under different climate change scenarios. There is growing evidence that the influence of long-term climate variability in C fluxes from terrestrial ecosystems is modulated by adjustments in the aboveground–belowground links. Here, we studied the inter-annual variability in soil respiration from a wet shrubland going through successional change in North Wales (UK) during 13 years. We hypothesised that the decline in plant productivity observed over a decade would result in a decrease in the apparent sensitivity of soil respiration to soil temperature, and that rainfall variability would explain a significant fraction of the inter-annual variability in plant productivity, and consequently, in soil respiration, due to excess-water constraining nutrient availability for plants. As hypothesised, there were parallel decreases between plant productivity and annual and summer CO₂ emissions over the 13-year period. Soil temperatures did not follow a similar trend, which resulted in a decline in the apparent sensitivity of soil respiration to soil temperature (apparent Q₁₀ values decreased from 9.4 to 2.8). Contrary to our second hypothesis, summer maximum air temperature rather than rainfall was the climate variable with the greatest influence on aboveground biomass and annual cumulative respiration. Since summer air temperature and rainfall were positively associated, the greatest annual respiration values were recorded during years of high rainfall. The results suggest that adjustments in plant productivity might have a critical role in determining the long-term-sensitivity of soil respiration to changing climate conditions.     

6种温带森林凋落量年际及年内动态

森林凋落物量及其组分因生态系统结构特征和环境变化而表现出明显的时间动态,从而影响森林生态系统物质循环和生态服务功能。连续6年观测帽儿山地区6种温带森林凋落物量及组份的时间动态、温度和降雨量等气象因子,旨在深入了解该地区森林生态系统的物质循环过程及调控因子。结果表明:6种森林的年落凋落量差异显著,平均值依次为:蒙古栎林(4.60 t/hm~2)﹥杂木林(4.21 t/hm~2)﹥硬阔叶林(4.03 t/hm~2)﹥红松林(3.95 t/hm~2)﹥杨桦林(3.89 t/hm~2)﹥落叶松林(3.85 t/hm~2)。各森林年凋落量的年际变化表现为"升高-降低"交替波动模式,但总体上呈上升趋势。凋落物各组份的年际变化不同,枝凋落量变化较为稳定;叶凋落量与凋落总量一致,升高-降低波动明显;繁殖器官及其他凋落量随林龄增加而增加。各森林凋落物量的年内变化呈单峰曲线波动,最大值出现时间因林型而异。枝凋落量在年内表现为双峰曲线模式波动;叶凋落量年内呈单峰曲线模式波动,并与凋落总量年内动态一致;繁殖器官与其他凋落量年内动态波动平缓,无明显凋落峰值。降雨量显著影响年凋落物量(P0.05),分别解释了凋落总量、叶凋落量90%、87%变化。平均温度、积温和总降雨量显著影响凋落量年内动态,总降雨量的影响作用最为突出。因此,除林分自身的生物学特性外,降雨是影响该温带森林凋落量年内、年际动态的重要因素。     

Variability in the performance of the spectrogram correlation detector for North-east Pacific blue whale calls

Spectrogram correlation has been used successfully for automatic detection of baleen whale calls. However, applying this method consistently to long time series can be challenging. To illustrate the potential challenges of the automatic detection process, recordings collected in the Southern California Bight between 2007 and 2012 were used for detection of North-east Pacific blue whale (Balaenoptera musculus) B calls. The effects of the following factors were investigated: blue whale B call frequency shift and appropriate kernel modification, seasonal variability in call abundance, analyst variability and noise. Due to intra- and inter-annual changes in the call frequency of blue whale B calls, seasonal and annual adjustments to the call detection kernel were needed. To account for seasonal variability in call production, evaluation of the detector against ground truth data was performed at multiple times during the year. Analyst variability did not affect overall long-term trends in detection, but it had an impact on the total number of detections, as well as call rate estimation. Noise, particularly from shipping, was negatively correlated with detections at hourly time scales. A detailed analysis of variability in the performance of spectrogram correlation detectors should be performed when applying this method to long-term acoustic data-sets.     

Analysis of candidate gene expression patterns of adult male <Emphasis Type="Italic">Macrobrachium rosenbergii</Emphasis> morphotypes in response to a social dominance hierarchy

Because phytoplankton communities exhibit seasonal patterns driven by changes in physical factors, grazing pressure, and nutrient limitations, climate change, in combination with local phosphorus management policies are expected to impact phytoplankton annual dynamic. We used long-term monitoring data from Lake Geneva (from 1974 to 2010) to test if changes in phytoplankton seasonal succession across years is related to re-oligotrophication, inter-annual variability in thermal conditions, and Daphnia sp. density. We used a Bayesian method to identify species assemblages and wavelet analysis to detect transient dynamics in seasonal periodicity. A decrease in phosphorus concentrations appeared to play a major role in the inter-annual replacement of species assemblages. Furthermore, some species assemblages exhibited a change in their seasonal periodicity that was most likely induced by changes in Daphnia sp. density. Finally, we demonstrated that flexibility in the pattern of phytoplankton seasonal successions played a stabilizing role at the community level. The results suggest that phenology and inter-annual changes in seasonal dynamics of phytoplankton assemblages are important components to consider for explaining long-term variability in phytoplankton community.     

Analysis of water- and nitrogen-use efficiency of wheat in a Mediterranean climate

Water-use efficiency (WUE [g grain yield m^–2 mm^–1 ET]) and nitrogen-use efficiency (NUE [ g grain yield g^–1 N_applied]) are important measures that can affect the productivity of crops in different environmental systems. However, measurement and interpretation of WUE and NUE in the field are often hampered by the high degree of complexity of these systems due to season-to-season variability in rainfall, the variation in crop responses to soil types and to agronomic management. To be able to guide agronomic practice, experimentally-derived measurements of WUE and NUE need to be extrapolated across time and space through appropriate modelling. To illustrate this approach, the Agricultural Production Systems Simulator (APSIM), which has been rigorously tested for wheat (Triticum aestivum L.) in a Mediterranean environment, was used to estimate and analyse the WUE and NUE of wheat crops in the Mediterranean-climatic region of the central Western Australian agricultural zone. The APSIM model was run for three locations (average annual rainfall of 461 mm [high rainfall zone], 386 mm [medium] and 310 mm [low]) and two soil types that had contrasting plant-available water-holding capacities in the rooting zone (sand: 55 mm, clay soil: 109 mm). Simulations were carried out with historical weather records (82–87 years) assuming current crop management and cultivars. The modelling analyses highlighted the inherently high degree of seasonal variability in yield, WUE and NUE of wheat, depending on soil type, N fertiliser input, rainfall amount and, in particular, rainfall distribution. The clay soil tended to be more productive in terms of grain yield, WUE and NUE in the high and medium rainfall zones, but less productive in most years in the low rainfall zone. The sandy soil was less productive in the high rainfall zone due to the high nitrate leaching potential of this soil type, but more productive than the clay in the low rainfall zone due to poorer pre-anthesis growth and less water use, less water loss by soil evaporation and relatively more water use in the post-anthesis phase. When a wheat crop was sown early on clay soil in the low rainfall zone, it yielded as high as in the other rainfall zones in seasons when rainfall was above average or there was a good store of water in the soil prior to sowing. The simulations confirmed findings from a limited number of field experiments and extended these findings both qualitatively and quantitatively across soil types, rainfall regions and crop management options. Furthermore, by using long-term historical weather records, the simulations extended the findings across the wide range of climatic scenarios experienced in mediterranean-climatic regions.     

Inter-annual,seasonal and spatial variability in nutrient limitation of phytoplankton production in a river impoundment

We characterize seasonal and spatial patterns in phytoplankton abundance, production and nutrient limitation in a mesotrophic river impoundment located in the southeastern United States to assess variation arising from inter-annual differences in watershed inputs. Short-term (48 h) in situ nutrient addition experiments were conducted between May and October at three sites located along the longitudinal axis of the lake. Nutrient limitation was detected in 12 of the 18 experiments conducted over 2 years. Phytoplankton responded to additions of phosphorus alone although highest chlorophyll concentrations were observed in enclosures receiving combined (P and N) additions. Growth responses were greatest at downstream sites and in late summer suggesting that those populations experience more severe nutrient limitation. Interannual variation in nutrient limitation and primary production corresponded to differences in the timing of hydrologic inputs. Above average rainfall and discharge in late-summer (July–October) of 1996 coincided with higher in-lake nutrient concentrations, increased production, and minimal nutrient limitation. During the same period in 1995, discharge was lower, nutrient concentrations were lower, and nutrient limitation of phytoplankton production was more pronounced. Our results suggest that nutrient limitation is common in this river impoundment but that modest inter-annual variability in the timing of hydrologic inputs can substantially influence seasonal and spatial patterns.     

A growing season climatic index to simulate gross primary productivity and carbon budget in a Tibetan alpine meadow

Accurate estimation of gross primary production (GPP) of ecosystem is needed to evaluate terrestrial carbon cycle at various spatial and temporal scales. Eddy covariance (EC) technique provides continuous measurements of net ecosystem CO₂ exchange (NEE) and can be used to separate GPP from NEE in real time series. However, seasonal and inter-annual variation and consequently ecosystem carbon budget is still very difficult to simulate from climatic and environment. To address this limitation, we develop a growing season indicator (GSI) based on low temperature and soil water stress to model and predict intra and inter-annual dynamic of gross primary productivity (GPP). Validation of this new index was conducted using continuous six-year consective EC measurement from 2004 to 2009 at a Tibetan alpine meadow. Simulated GPP agreed well with the observed GPP in terms of seasonal and inter-annual variation. The six-year correlation coefficients on seasonal scale between GSI and scalar GPP derived from EC reached more than 0.85 no matter in dry years or wet years. In addition, the temporal GPP estimation derived from GSI model was quite similar to those from observed values by EC measurement. Moreover, accumulated GSI values can predict annual variability of net ecosystem production (NEP). Higher yearly accumulated GSI corresponded to more annual NEP. When cumulative GSI arrived up to 92, the target ecosystem was a carbon sink. This is probably a threshold which Tibetan alpine meadow changes from carbon source to carbon sink. It is indicated that the GSI model is a simple, alternative approach to estimating GPP and has the potential to simulate spatial GPP in a larger scale. However, the performance of GSI model in other vegetation types or regions still needs a further verification.     

灌溉水稻生长发育和潜力产量的模拟模型

本文提出的HDRICE模型是灌溉水稻生长的生理生态模型,它由相互衍接的水稻形态发育、干物质积累和叶面积发育三模块组成。形态发育模块用以模拟逐日温度和日长对水稻发育的影响,其参数可反映水稻品种的基本营养性、感温性和感光性;干物质积累模块用以模拟冠层CO_2同化、作物的维持呼吸和生长呼吸及干物质分配等过程;叶面积发育模块用以模拟叶面积指数的动态。本文还讨论了模型的输入参数和模型检验。模型可应用于模拟水稻的生长发育,预测水稻品种潜在产量及为取得潜在产量所必需的群体数量指标。     

From GCM grid cell to agricultural plot: scale issues affecting modelling of climate impact

General circulation models (GCM) are increasingly capable of making relevant predictions of seasonal and long-term climate variability, thus improving prospects of predicting impact on crop yields. This is particularly important for semi-arid West Africa where climate variability and drought threaten food security. Translating GCM outputs into attainable crop yields is difficult because GCM grid boxes are of larger scale than the processes governing yield, involving partitioning of rain among runoff, evaporation, transpiration, drainage and storage at plot scale. This study analyses the bias introduced to crop simulation when climatic data is aggregated spatially or in time, resulting in loss of relevant variation. A detailed case study was conducted using historical weather data for Senegal, applied to the crop model SARRA-H (version for millet). The study was then extended to a 10 degrees N-17 degrees N climatic gradient and a 31 year climate sequence to evaluate yield sensitivity to the variability of solar radiation and rainfall. Finally, a down-scaling model called LGO (Lebel-Guillot-Onibon), generating local rain patterns from grid cell means, was used to restore the variability lost by aggregation. Results indicate that forcing the crop model with spatially aggregated rainfall causes yield overestimations of 10-50% in dry latitudes, but nearly none in humid zones, due to a biased fraction of rainfall available for crop transpiration. Aggregation of solar radiation data caused significant bias in wetter zones where radiation was limiting yield. Where climatic gradients are steep, these two situations can occur within the same GCM grid cell. Disaggregation of grid cell means into a pattern of virtual synoptic stations having high-resolution rainfall distribution removed much of the bias caused by aggregation and gave realistic simulations of yield. It is concluded that coupling of GCM outputs with plot level crop models can cause large systematic errors due to scale incompatibility. These errors can be avoided by transforming GCM outputs, especially rainfall, to simulate the variability found at plot level.     

冬作季节土地管理对水稻土CH_4排放季节变化的影响

通过温室盆栽试验对水稻土CH4 排放的季节变化及冬作季节土地管理的影响进行了研究 .结果表明 ,冬作季节种植紫云英、淹水休闲及干燥休闲但泡水前施用稻草处理泡水后 3 0dCH4 排放量分别高达 13 3d观测期总排放量的 67.5 %、3 5 .5 %及 3 3 .3 % ,且在泡水后第 13天及水稻移栽后第 7、40、91天分别出现 4个CH4 排放高峰 ;而种植小麦和干燥休闲但冬作前施用稻草处理泡水后 5 5dCH4 排放量才占观测期总排放量的 6.74%和 0 .2 7% ,随后至水稻收获CH4 排放通量也不高 .冬作季节土地管理引起的水稻生长期土壤Eh季节变化的差异是造成CH4 排放通量季节变化差异的主要原因     

冬作季节土地管理对水稻土CH4排放季节变化的影响

通过温室盆栽试验对水稻土ＣＨ４排放的生节变化及冬作季节土地管理的影响进行了研究,结果表明,冬作季节种植紫云英、淹水休闲及干燥休闲但泡水前施用稻草处理泡水后３０ｄＣＨ４排放量分别高达１３３ｄ观测期总排放量的６７５％、３５．５％及３３．３％,且在泡水后第１３天及水稻移栽后第７、４０、９１天分别出现４个ＣＨ４排放高峰;而种植小麦和干燥休闲但冬作前施用稻草处理泡水后５５ｄＣＨ４排放量才占观测期总排放量的６     

Modelling Seasonal and Inter-annual Variations in Carbon and Water Fluxes in an Arid-Zone <Emphasis Type="Italic">Acacia</Emphasis> Savanna Woodland, 1981–2012

Changes in climatic characteristics such as seasonal and inter-annual variability may affect ecosystem structure and function, hence alter carbon and water budgets of ecosystems. Studies of modelling combined with field experiments can provide essential information to investigate interactions between carbon and water cycles and climate. Here we present a first attempt to investigate the long-term climate controls on seasonal patterns and inter-annual variations in water and carbon exchanges in an arid-zone savanna-woodland ecosystem using a detailed mechanistic soil–plant–atmosphere model (SPA), driven by leaf area index (LAI) simulated by an ecohydrological model (WAVES) and observed climate data during 1981–2012. The SPA was tested against almost 3 years of eddy covariance flux measurements in terms of gross primary productivity (GPP) and evapotranspiration (ET). The model was able to explain 80 and 71% of the variability of observed daily GPP and ET, respectively. Long-term simulations showed that carbon accumulation rates and ET ranged from 20.6 g C m^?2 mon^?1 in the late dry season to 45.8 g C m^?2 mon^?1 in the late wet season, respectively, primarily driven by seasonal variations in LAI and soil moisture. Large climate variations resulted in large seasonal variation in ecosystem water-use efficiency (eWUE). Simulated annual GPP varied between 146.4 and 604.7 g C m^?2 y^?1. Variations in annual ET coincided with that of GPP, ranging from 110.2 to 625.8 mm y^?1. Annual variations in GPP and ET were driven by the annual variations in precipitation and vapour pressure deficit (VPD) but not temperature. The linear coupling of simulated annual GPP and ET resulted in eWUE having relatively small year-to-year variation.     

A spatiotemporal assessment of field residues of rice,maize, and wheat at provincial and county levels in China

China has a huge resource potential for biomass‐based renewable energy development, but the resources of field residues are still not effectively used. Rice, maize, and wheat made up 89% of staple crop production in China in 2009. A comprehensive assessment of field residues of these three crops is necessary for the development of biomass‐based industries. This research was based on multiyear county‐level data of crop production, area and yield, as well as the crop phenology information from agrometeorological stations. Spatial and temporal analyses were conducted to quantify the spatial patterns, seasonal variations, and temporal trends of the three major field residues. The mean amount of field residue of rice, maize, and wheat was 470.8 Mt/year from 2002 to 2009. Rice residue topped the field residues at 188.5 Mt/year, followed by maize (152.6 Mt/year) and wheat (129.8 Mt/year). The resource supply of field residues varied temporally throughout the season, where peak months are May, June, September, and October. The resources of all three field residues increased from 2002 to 2009, topped by maize residues at a rate of 10.0 Mt/year. Spatially, high production counties had the fast growth rate and a strong positive spatial autocorrelation. The results showed that the intersection area of East and South Central regions has a spatially concentrated residue density and a stable supply for 5 months. The region can be considered as a suitable region for bioenergy development. A better understanding of spatial and temporal distribution of crop residues could facilitate strategic and tactical bioenergy planning.     

Current Status of Cereal Root Diseases in Western Australia Under Intensive Cereal Production and Their Comparison with the Historical Survey Conducted During 1976–1982

Two separate surveys of root diseases of cereals in the Western Australian (WA) cereal belt were conducted: the first conducted annually for wheat and barley during 1976–1982 and the second for wheat during 2005–2007. For the 1976–1982 survey, the cereal belt was divided into 15 zones based on the location and rainfall. Sampling was representative of the actual cropping area, with both wheat and barley sampling sites selected by zone as a percentage of total sites. Over 31 000 plants were assessed from a total of 996 fields. Average take‐all incidence ranged from 3% in the northern low rainfall zone to 57% in the southern high rainfall zone. Other root diseases assessed included rhizoctonia root rot, fusarium crown rot and subcrown internode discolouration. During the 2005–2007 survey, around 20 000 plants from a total of 210 fields being intensively cropped with cereals were surveyed for take‐all, rhizoctonia root rot, fusarium crown rot, common root rot, root lesion nematode and cereal cyst nematode. The 2005–2007 survey results indicated that root and crown diseases prevailed in paddocks frequently cropped with cereals and occurred at damaging levels across all WA cropping districts surveyed. The more recent root disease survey identified that the fungal diseases rhizoctonia root rot and fusarium crown rot and the root lesion nematode were the most serious impediments to intensive cereal production, particularly in the southern region of WA. Comparing the 2005–2007 results with the previous survey of 1976–1982, the relative importance of take‐all appears to have declined over the past 30 years.     

Much Improved Irrigation Use Efficiency in an Intensive Wheat-Maize Double Cropping System in the North China Plain

Crop yield and water use efficiency （WUE） in a wheat-maize double cropping system are influenced by short and uneven rainfalls in the North China Plain （NCP）, A 2-year experiment was conducted to investigate the effects of irrigation on soil water balance, crop yield and WUE to improve irrigation use efficiency in the cropping system, Soil water depletion （~SWS） by crop generally decreased with the increase of irrigation and rainfall, while ASWS for the whole rotation was relatively stable among these irrigation treatments, High irrigations in wheat season increased initial soil moisture and ASWS for subsequent maize especially in the drought season, Initial soil water influenced mainly by the irrigation and rainfall in the previous crop season, is essential to high yield in such cropping systems, Grain yield decreased prior to evapotranspiraUon （ET） when ET reached about 300mm for wheat, while maize showed various WUEs with similar seasonal ET, For whole rotation, WUE declined when ET exceeded about 650 mm, These results indicate great potential for improving irrigation use efficiency in such wheat-maize cropping system in the NCP, Based on the present results, reasonable irrigation schedules according to different annual rainfall conditions are presented for such a cropping system.