Crop sap flow is a critical indicator of crop water demand, and predicting its variation trend is essential for adjusting agricultural planting structure and managing water resource in hyper-arid areas. Presently, research on crop sap flow in hyper-arid areas faces limitations due to inadequate meteorological data and restricted monitoring duration, leading to imprecise assessments of environmental impacts on future crop sap flow. Consequently, this hinders effective irrigation scheduling and oasis sustainable development policy. This study analyzed the sap flow changes characteristics of two economic crops (red jujube and walnut) at different time scales in the oasis in the south of Tarim Basin from 2017 to 2021 and the relationship between four environmental factors (solar radiation, temperature, relative humidity and vapor pressure deficit) and the sap flow of red jujube and walnut. By using the Random Forest (RF) model and the future climate data, the sap flow of the two economic crops from 2020 to 2100 was predicted. The results showed that: (1) walnut had a longer daily peak sap flow duration compared to red jujube, whereas red jujube showed a longer monthly peak sap flow duration; (2) in hyper-arid areas, the moisture and temperature directly influenced crop sap flow, while other environmental factor affected these two factors; (3) with the temperature increases, the water demand of red jujube and walnut in Cele Oasis will exceed local water resources carrying capacity. To achieve sustainable development of oasis, it is vital to consider future climatic changes in planning the expansion and crop structure.

Glacial and snow meltwater from high mountains plays a critical role in the regulation of river discharge and impacts the irrigation of croplands in arid regions. In this study, the variable infiltration capacity (VIC)-glacier hydrological model combined with a crop yield model (CROPR model) was used to investigate the significance of meltwater to irrigation and cotton yield in the Yarkant River basin of arid Northwest China. The results indicated that the annual meltwater followed an increasing trend at a rate of 0.5 mm/10 a during 1960–2017. The warm–dry to warm–wet climate during recent decades has been driving the increasing annual total discharge and meltwater and the decreasing total irrigation, irrigation from meltwater and contribution of meltwater to cotton yield. The effect of precipitation on irrigation from meltwater and the contribution of meltwater to cotton production were greater than those of temperature. Increasing precipitation decreased the impact of meltwater on irrigation and cotton production. This study is helpful for the scientific management of cryospheric water resources and addressing the risk of water shortages in the arid region of Northwest China.

Drip irrigation is an effective method to utilize waste saline-sodic land with a high water table. For reasonable and sustainable utilization of saline-sodic soil under such conditions, spatiotemporal changes in total nitrogen (TN), total phosphorus (TP), and soil organic matter (SOM) were investigated during the utilization process. The soil was sampled from newly built raised beds before planting (0 y) and beds in three adjacent plots had been planted with Lycium barbarum L. for one (1 y), two (2 y), and three years (3 y), respectively, at the end of the growing season. Soil samples were obtained at four horizontal distances from the drip line (0, 10, 20, and 30 cm) and four vertical soil depths (0–10, 10–20, 20–30, and 30–40 cm). The results showed that the average TN and TP of the soil profile increased with the planting year and were approximately 0.68 and 1.81 g·kg−1 in the soils of 3 y, approximately 84.9 and 42.4% higher than that of 0 y, respectively. SOM decreased in the first growing season and then continuously increased in the following planting years, reaching 8.26 g·kg−1 in the soils of 3 y, which was approximately 38.2% higher than that of 0 y. TN, TP, and SOM contents were high in soils around the drip line and decreased with distance from the drip line. In both horizontal and vertical directions, TN, TP, and SOM varied slightly in soils of 0, 1, and 2 y, while in soils of 3 y, TN and SOM decreased with increased distance in both horizontal and vertical directions and TP decreased obviously only within 10 cm in both directions. This indicated that the contents and distributions of soil nutrients in such saline-sodic soils could be improved with planting year under drip irrigation with local saline groundwater and especially around the drip line as the soil around the dripper was quickly ameliorated.

Crop yields are related to N fertilizer management, and also depend on local precipitation. Varying precipitation levels with long-term meteorological data have not been considered to optimize nitrogen (N) strategies in previous studies on the Loess Plateau of China. In this study, Root Zone Water Quality Model 2 (RZWQM2) was calibrated and validated using data from multi-year experiments and used to assess and optimize N management strategies for winter wheat cultivation. Results showed that the basal dressing fertilizer with 120 kg N ha-1 together with the topdressing of 67–77 kg N ha-1 was recommended in regions with 443 mm average annual precipitation. For those with 364 mm and 290 mm average annual precipitation, the basal dressing fertilizer with 90 kg N ha-1 together with the topdressing of 67–77 kg N ha-1 and the basal dressing with 90 kg N ha-1 together with the topdressing fertilizer of 13–23 kg N ha-1 were recommended, respectively. Compared with farmers' practice (i.e., the single basal dressing), although decreasing the total rate by 12–18 kg N ha-1, the optimized N strategies (i.e., the basal fertilizer together with one-time topdressing) can effectively promote grain N uptake, nitrogen harvest index, and agronomic efficiency of N. It also maintained similar grain yield, evapotranspiration, and crop water productivity. The minimum precipitation threshold was around 300 mm, where the topdressing N fertilizer had little influence on grain yield, evapotranspiration, and grain N uptake. Additionally, the largest advantage of optimized N strategies was saving N fertilizer and reducing the environment footprint of wheat production. However, the crop production under the optimized N strategies was more sensitive to the precipitation variation than that under farmers' practice. Thus, if climate continues to change following historical data, greater harvest fluctuations are expected under optimized N strategies. To cope with the evolving climate change, optimized N strategies should be integrated with other management measures for smallholder farming households on the Loess Plateau.

Drip irrigation with saline water is frequently adopted to realize the sustainable utilization of saline–sodic soil with high water tables, and soil enzyme activities can be used to indicate changes in soil quality. In the current study, spatiotemporal changes in soil urease enzyme (URE), alkaline phosphatase (ALP) and invertase (INV) activities were investigated during consecutive growing seasons. Soil in beds was sampled before planting (0 y) and one, two, three and four years after the growing season (1 y, 2 y, 3 y, 4 y), and these samples were distributed at four horizontal distances from the drip line (0, 10, 20 and 30 cm) and four vertical soil depths (0–10, 10–20, 20–30 and 30–40 cm). The results showed that a distribution pattern of URE and ALP activities formed during the first growing season, while the distribution of INV activity formed until the third growing season. All three soil enzyme activities in the upper soil layers and positions close to the drip line were more greatly affected by planting year. The average URE activity of the soil profile decreased slightly during the first year and increased by about 220% and decreased by 20% after reclamation for two and three years, and finally, it increased to 4.9 μg NH4+·g−1·h−1 at the end of the fourth growing season. ALP activity remained stable during the first two years and rapidly increased in the following years; in particular, in the fourth year, it reached 32.7 μg ph(OH)·g−1·h−1. INV activity increased continually with the number of years after planting and reached 1009.0 μg glu·g−1·h−1 at the fourth season’s end. An analysis of variance indicated that URE, ALP and INV activities varied insignificantly among the time points of 0 y, 1 y, 2 y and 3 y (p < 0.05), while they were significantly higher for 4 y than for 0 y and 1 y. In addition, all three enzyme activities of the soil profile had an exponentially increasing trend with the number of years after planting. These results indicated the soil quality in saline–sodic soils could be improved with time under drip irrigation with local saline groundwater, especially around the drip line.

Improving cotton (Gossypium hirsutum L.) yield and water use efficiency (WUE) under future climate scenarios by optimizing irrigation regimes is crucial in hyper-arid areas. Assuming a current baseline atmospheric carbon dioxide concentration (CO2atm) of 380 ppm (baseline, BL0/380), the Root Zone Water Quality Model (RZWQM2) was used to evaluate the effects of four climate change scenarios—S1.5/380 (∆Tair°=1.5 °C,∆CO2atm=0), S2.0/380 (∆Tair°=2.0 °C,∆CO2atm=0), S1.5/490 (∆Tair°=1.5 °C,∆CO2atm=+110 ppm) and S2.0/650 (∆Tair°=2.0 °C,∆CO2atm=+270 ppm) on soil water content (θ), soil temperature (Tsoil°), aboveground biomass, cotton yield and WUE under full irrigation. Cotton yield and irrigation water use efficiency (IWUE) under 10 different irrigation management strategies were analysed for economic benefits. Under the S1.5/380 and S2.0/380 scenarios, the average simulated aboveground biomass of cotton (vs. BL0/380) declined by 11% and 16%, whereas under S1.5/490 and S2.0/650 scenarios it increased by 12% and 30%, respectively. The simulated average seed cotton yield (vs. BL0/380) increased by 9.0% and 20.3% under the S1.5/490 and S2.0/650 scenarios, but decreased by 10.5% and 15.3% under the S1.5/380 and S2.0/380 scenarios, respectively. Owing to greater cotton yield and lesser transpiration, a 9.0% and 24.2% increase (vs. BL0/380) in cotton WUE occurred under the S1.5/490 and S2.0/650 scenarios, respectively. The highest net income ($3741 ha−1) and net water yield ($1.14 m−3) of cotton under climate change occurred when irrigated at 650 mm and 500 mm per growing season, respectively. These results suggested that deficit irrigation can be adopted in irrigated cotton fields to address the agricultural water crisis expected under climate change.

Understanding the impacts of future climate change and long-term agronomic practices on environmental quality and agricultural productivity is critical to the development of sustainable agronomic management approaches. Given these requirements, the present study's objective was to evaluate the potential impacts of climate change and long-term conservation practices on greenhouse gas (GHG) emissions and crop growth. To project potential future (2065-2084) climatic conditions for a field under a long-term maize cropping system situated in Nebraska (USA), 12 different combinations of regional climate models x global climate models (RCMs-GCMs) were generated under representative concentration pathway 8.5 (RCP8.5) and a heightened atmospheric carbon dioxide concentration ([CO2]atm = 714.1 ppm). Then, employing a well-calibrated instance of the Root Zone Water Quality Model (RZWQM2), the effects of four long-term conservation practices were simulated under the 12 RCMs-GCMs. Compared to other climatic factors (e.g., shortwave radiation, wind run, and relative humidity), temperature, precipitation, and [CO2]atm played more important roles for future carbon dioxide (CO2) and nitrous oxide (N2O) emissions, global warming potential (GWP), soil organic carbon (SOC), crop yield, and total crop biomass. The sum of their relative contributions to GHG emissions and crop growth exceeded 83.9 % across all treatments. Under future climatic conditions, CO2 and N2O emissions increased significantly - 19.4 % +/- 5.8 % and 26.6 % +/- 8.9 %, respectively - compared to those under historical baseline conditions. Likewise, the GWP increased by 19.8 +/- 5.8 %. Although rising [CO2]atm afforded limited benefits in terms of crop photosynthesis rates, rising future temperatures shortened crop growth cycles, resulting in a net decrease of 9.1 % +/- 1.9 % in maize yield and 4.2 % +/- 1.6 % in total biomass. SOC saw a net increase of 4.8 % +/- 0.4 % under the future (vs. baseline) climate. Compared to residue removal with no-till treatment, annual CO2 and N2O emissions in the long-term maize cropping system were predicted to increase by 26.8 % and 27.9 % between 2065 and 2084 under residue retention with tillage treatment, respectively. Whereas crop yield and biomass were not significantly affected by residue or tillage management practices. The simulation method provided valuable evidence for management decisions to assess the synergistic effects of climate change and long-term agronomic practices on the environment and agricultural productivity. Further investigation is needed on the effects of other climate RCPs and agronomic management for sustainable agricultural production.

Deficit irrigation (DI) is a widely recognized water-saving irrigation method, but it is difficult to precisely quantify optimum DI levels in tomato production. In this study, the Root Zone Water Quality-Simultaneous Heat and Water (RZ-SHAW) model was used to evaluate the potential effects of different DI levels on tomato growth in a drip-irrigated field. Combinations of five DI scenarios were tested in greenhouse field experiments under plastic film mulching according to the percentage of crop evapotranspiration (ET), i.e., ET50, ET75, ET100, ET125, and ET150. The model was calibrated by using the ET100 scenario, and validated with four other scenarios. The simulation results showed that the predictions of tomato growth parameters and soil water were in good agreement with the observed data. The relative root mean square error (RRMSE), the percent bias (PBIAS), index of agreement (IoA) and coefficient of determination (R2) for leaf area index (LAI), plant height and soil volumetric water content (VWC) along the soil layers were <23.5%, within ±16.7%, >0.72 and >0.56, respectively. The relative errors (REs) of simulated biomass and yield were 3.5–8.7% and 7.0–14.0%, respectively. There was a positive correlation between plant water stress factor (PWSF) and DI levels (p < 0.01). The calibrated model was subsequently run with 45 different DI scenarios from ET0 to ET225 to explore optimal DI management for maximizing water productivity (WP) and yield. It was found that the maximum WP and yield occurred in ET95 and ET200, with values of 28.3 kg/(ha·mm) and 7304 kg/ha, respectively. The RZ-SHAW demonstrated its capacity to evaluate the effects of DI management on tomato growth under plastic film mulching. The parameterized model can be used to optimize DI management for improving WP and yield based on the water stress-based method.

[目的]探究气候变化对极端干旱区棉花生长和产量的影响.[方法]利用2018年新疆策勒绿洲棉田数据对根区水质模型(Root Zone Water Quality Model-version2,RZWQM2)进行率定和验证;基于验证后的模型模拟了1960—2019年气候变化对棉花生育期、产量和灌溉水利用效率(IWUE)的影响;利用相关分析探究了关键气候要素与棉花生育期和产量的相关性.[结果]RZWQM2模型能够较好地模拟极端干旱区绿洲棉田各土层含水量(除0.15～0.25 m外)、棉花生长和产量,平均一致性指数(IOA)>0.75.棉花的出苗期、花期、吐絮期和成熟期均推迟,平均每10年推迟时间约为1.1、2.1、3.5、3.5 d;棉花产量和IWUE均呈下降趋势,每10年下降幅度分别为45.95 kg/hm2和0.13 kg/(mm·hm2).气温和太阳辐射量对棉花生长有显著影响,其中最低气温是影响棉花生育期的主导因子,最高气温对棉花产量有一定负面影响;太阳辐射量则是引起产量变化的主导因子.[结论]研究结果可为绿洲农业应对气候变化的影响提供一定的科学指导.

Snow and glaciers provide water to the densely populated downstream area of the Tarim River Basin, which is an important irrigated agricultural area in China. Cotton is an important cash crop, and meltwater is an important irrigation water source for cotton in this region. In this study, the spatiotemporal dependence of cotton yield on mountain meltwater resources in the subbasins of the Tarim River basin was quantified by the variable infiltration capacity (VIC) hydrologic model with the degree-day and CROPR models during 1960–2017. The results showed that the changes in meltwater in all subbasins had a significantly increasing trend. Meltwater contributions to cotton irrigation and yield varied spatiotemporally. Along the area south of the Tian Shan Mountains, the meltwater contribution to irrigation showed a decreasing trend from west to east, and the highest contribution of meltwater to cotton yield occurred in the Weigan River basin, followed by the Aksu River basin and Kaidu River basin. Along the northern Karakoram Mountains, the meltwater contributions to cotton irrigation and yield first decreased and then increased from west to east. In the whole basin, 48.6% of total irrigation withdrawals originated from mountain snow and glacial meltwater and contributed an additional 55.9% to total cotton production during the study period. The results provide important agricultural information for locations where shifts in water availability and demand are projected as a result of socioeconomic growth.

The drip fertigation technique is a modern, efficient irrigation method to alleviate water scarcity and fertilizer surpluses in crop production, while the precise quantification of water and fertilizer inputs is difficult for drip fertigation systems. A field experiment of maize (Zea mays L.) in a solar greenhouse was conducted to meet different combinations of four irrigation rates (I125, I100, I75 and I50) and three nitrogen (N) fertilizer rates (N125, N100 and N75) under surface drip fertigation (SDF) systems. The Root Zone Water Quality Model (RZWQM2) was used to assess the response of soil volumetric water content (VWC), leaf area index (LAI), plant height and maize yield to different SDF managements. The model was calibrated by the I100N100 scenario and validated by the remaining five scenarios (i.e., I125N100, I75N100, I50N100, I100N125 and I100N75). The predictions of VWC, LAI and plant height were satisfactory, with relative root mean square errors (RRMSE) < 9.8%, the percent errors (PBIAS) within ±6%, indexes of agreement (IoA) > 0.85 and determination of coefficients (R2) > 0.71, and the relative errors (RE) of simulated yields were in the range of 1.5–7.2%. The simulation results showed that both irrigation and fertilization had multiple effects on water and N stresses. The calibrated model was subsequently used to explore the optimal SDF scenarios for maximizing yield, water use efficiency (WUE) or nitrogen use efficiency (NUE). Among the SDF managements of 21 irrigation rates × 31 N fertilizer rates, the optimal SDF scenarios were I120N130 for max yield (10516 kg/ha), I50N70 for max WUE (47.3 kg/(ha·mm)) and I125N75 for max NUE (30.2 kg/kg), respectively. The results demonstrated that the RZWQM2 was a promising tool for evaluating the effects of SDF management and achieving optimal water and N inputs.

Understanding the variation and magnitude of crop coefficient (K-c) is important to accurate determine crop evapotranspiration (ETc) and optimal irrigation scheduling. Sensible heat advection is expected to increase Kc by providing additional energy, while its effect on K-c over paddy field is rarely featured. A three-year experiment was conducted over a paddy field to develop local K-c using the eddy covariance technique (EC) in the Poyang River basin, southern China. The local K-c curve, the characteristics of advection and its contribution to K-c were investigated. The three-year average local K-c values during the initial, mid-season and late-season stages were 1.12, 1.29 and 1.13 for the early rice and 1.11, 1.39 and 1.02 for the late rice, respectively. The advection was more likely to occur during the late rice season than the early rice season. The three-year average advective days were 8.0 d for the early rice season and 29.7 d for the late rice season, respectively. The contribution of advection to daily K-c ranged from 0.6% to 13.2% for the early rice season and 1.1% to 37.7% for the late rice season, respectively. The upwind city was found to be a possible energy source for advection. The occurrence of advection was closely related to air temperature gradients (Delta T) between the city and paddy field and wind speed (u(2)). Our study indicated advection also existed in the humid paddy field and had considerable effects on Kc. These results are helpful for decision-makers to quantify crop water consumption and improve irrigation water efficiency.

Sustaining cotton (Gossypium hirsutum L.) production under limited water availability and climate change in an extremely arid oasis is a key challenge for the stakeholders. This study was conducted to quantify the climate change impacts on cotton phenology and seed yield under full (638 mm) and deficit (478 mm) irrigation regimes in an extremely arid oasis in China. The Root Zone Water Quality (RZWQM2) model with the integration of six global circulation models (GCMs) under two representative concentration pathways (RCP 4.5 and 8.5) was used to determine the potential impacts of climate change on cotton for future periods (2022–2047, 2048–2073, and 2073–2099) compared to baseline (1975–2000). The results revealed that number of days to anthesis and maturity was expected to be reduced under RCP 4.5 and RCP 8.5 with full and deficit irrigation for future periods compared to baseline. However, this reduction was maximum under RCP 8.5 for 2074–2099 with full irrigation treatment. Seed cotton yield was also expected to decrease by 13–18

Irrigated cotton (Gossypium hirsutum L.) is produced mainly in Northwest China, where groundwater is heavily used. To alleviate water scarcity and increase regional economic benefits, a four-year (2016–2019) field experiment was conducted in Qira Oasis, Xingjiang Province, to evaluate irrigation water use efficiency (IWUE) in cotton production using the Root Zone Water Quality Model (RZWQM2), that was calibrated and validated using volumetric soil water content (θ), soil temperature (Tsoil°) and plant transpiration (T), along with cotton growth and yield data collected from full and deficit irrigation experimental plots managed with a newly developed Decision Support System for Irrigation Scheduling (DSSIS). In the validation phase, RZWQM2 adequately simulated (S) topsoil θ and Tsoil°, as well as cotton growth (average index of agreement (IOA) > 0.76). Relative root mean squared error (RRMSE) and percent bias (PBIAS) of cotton seed yield were 8% and 2.5%, respectively, during calibration, and 20% and −10.3% during validation. The cotton crop’s (M) T was well S (−18% < PBIAS < 14% and IOA > 0.95) for both full and deficit irrigation fields. The validated RZWQM2 model was subsequently run with seven irrigation scenarios with 850 to 350 mm water (Irr850, Irr750, Irr700, Irr650, Irr550, Irr450, and Irr350) and long-term (1990–2019) weather data to determine the best IWUE. Simulation results showed that the Irr650 treatment generated the greatest cotton seed yield (4.09 Mg ha−1) and net income (US $3165 ha−1), while the Irr550 treatment achieved the greatest IWUE (6.53 kg ha−1 mm−1) and net water production (0.94 $ m−3). These results provided farmers guidelines to adopt deficit irrigation strategies.

Reference evapotranspiration (ET 0 ) is important for agricultural production and the hydrological cycle. Knowledge of ET 0 can aid the appropriate allocation of irrigation water in arid regions. This study analyzed the trends in ET 0 over different timescales in the Tarim River basin (TRB), Central Asia. ET 0 was calculated by the Penman-Monteith method using data from 1960–2017 from 30 meteorological stations located in the TRB. The Mann-Kendall (MK) test with trend-free prewhitening and Sen’s slope estimator were applied to detect trends in ET 0 variation. The results showed that the mean ET 0 decreased at a rate of 0.49 mm·10 a -1 on an annual timescale. The mean ET 0 exhibited a decreasing trend in summer and increasing trends in other seasons. The effects of climatic factors on ET 0 were assessed by sensitivity analysis and contribution rate analysis. Maximum temperature (T max ), relative humidity (RH) and wind speed (WS) showed important effects on ET 0 . However, WS, which decreased, was the key element that induced changes in ET 0 in the TRB. This work provides an important baseline for the management of agricultural water resources and scientific planning in agriculture.

Optimizing irrigation scheduling through a Decision Support System has shown promise to improve crop yield and water productivity in irrigated agriculture in an arid climate. The effects of an irrigation scheduling method on cotton (Gossypium hirsutum L.) yield and water productivity were investigated in Qira Oasis, China from 2016-2018. The Decision Support System for Irrigation Scheduling (DSSIS) was based on forecasted rainfall and water stress index simulated by the Root Zone Water Quality Model (RZWQM2). A field experiment was conducted to test the viability of the DSSIS in 2016. The design of the experiment was a randomized complete that included two factors and two levels for each factor: (i) irrigation scheduling method-DSSIS-based (DSS) and soil moisture sensor-based (SMS), and (ii) irrigation level-full irrigation (FI) and deficit irrigation (DI, 75 % of FI). Implementation of the DSS led to significant increases in seed cotton yield [1.05 Mg ha(-1) (32 %)] and water productivity [1.64 kg ha(-1) mm(-1) (20 %)] compared to the SMS. Compared to DI, FI significantly increased cotton yield [0.69 Mg ha(-1) (20 %)] but had no significant effect on water productivity. In general, the higher water productivity under DSS (vs. SMS) was attributed to the reduced water stress and increased seed cotton yield. While the DSS-FI treatment provided the greatest seed cotton yield (4.55 Mg ha(-1)) and net income (US $3427 ha(-1)), the highest water productivity (10.09 kg ha(-1) mm(-1)) was achieved under the DSS-DI treatment. Water use under DSS-DI treatment significantly decreased by 51 mm (10 %) and 23 mm (5 %), respectively, compared to DSS-FI and SMS-FI treatments. Therefore, our results demonstrated that the DSS with deficit irrigation could maintain cotton yield and improve water productivity under an arid desert climate.

Assessing the potential impacts of climate change on cotton (Gossypium hirsutum L.) yield and water demand is crucial in allocating water resources. In this study, cotton yield and water requirement under future climate scenarios was evaluated in Qira oasis, China. Six general circulation models (GCMs), under moderate and high representative concentration pathway (RCP) scenarios (4.5 and 8.5) and elevated CO2 (eCO(2)) concentration (218-502ppm), were used to project climate for near (2041-2060) and far future (2061-2080) periods. With current management practices, the impacts of climate change on cotton yield and water requirement were simulated using the Root Zone Water Quality Model (RZWQM2), which was calibrated with experimental data (2007-2014) in a previous study. For the study region, the GCMs predicted an increase of 2.38 degrees C and 3.24 degrees C in temperature and 3.5% and 5.3% mm in precipitation during the growing seasons (April-October) for 2041-2060 and 2061-2080, respectively. For 2041-2060, seed cotton yield was projected to increase by 0.24Mg ha(-1) (5.6%) under RCP4.5 and 0.19Mg ha(-1) (4.5%) under RCP8.5 comparing to the baseline yield of 4.23Mg ha(-1); however, for 2061-2080, the model predicted a 0.32Mg ha -1 (7.6%) yield increase under RCP4.5 but a 0.28Mg ha(-1) (6.5%) decrease under RCP8.5. The increased cotton yield was mainly attributable to the fertilization effect of eCO(2) dominating the detrimental effects of shorter growing seasons (8.0-9.5 days). Alleviated low temperature stress also slightly promoted cotton yield. Averaged across the RCP4.5 and RCP8.5 scenarios, simulated cropping season water requirement for the 2041-2060 and 2061-2080 were 728mm and 706mm, respectively, an decrease by 7.5% and 10.3% relative to the present day baseline (786mm), respectively. This decrease was attributed to shorter growing seasons and eCO(2). These results suggest that the region's agricultural water crisis may be alleviated in the future.