Projection of hydrothermal condition in Central Asia under four SSP-RCP scenarios

Hydrothermal condition is mismatched in arid and semi-arid regions, particularly in Central Asia (including Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan, and Turkmenistan), resulting many environmental limitations. In this study, we projected hydrothermal condition in Central Asia based on bias-corrected multi-model ensembles (MMEs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under four Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) scenarios (SSP126 (SSP1-RCP2.6), SSP245 (SSP2-RCP4.5), SSP460 (SSP4-RCP6.0), and SSP585 (SSP5-RCP8.5)) during 2015-2100. The bias correction and spatial disaggregation, water-thermal product index, and sensitivity analysis were used in this study. The results showed that the hydrothermal condition is mismatched in the central and southern deserts, whereas the region of Pamir Mountains and Tianshan Mountains as well as the northern plains of Kazakhstan showed a matched hydrothermal condition. Compared with the historical period, the matched degree of hydrothermal condition improves during 2046-2075, but degenerates during 2015-2044 and 2076-2100. The change of hydrothermal condition is sensitive to precipitation in the northern regions and the maximum temperatures in the southern regions. The result suggests that the optimal scenario in Central Asia is SSP126 scenario, while SSP585 scenario brings further hydrothermal contradictions. This study provides scientific information for the development and sustainable utilization of hydrothermal resources in arid and semi-arid regions under climate change.     

Impact of climate change on the streamflow in the glacierized Chu River Basin,Central Asia

Catchments dominated by meltwater runoff are sensitive to climate change as changes in precipitation and temperature inevitably affect the characteristics of glaciermelt/snowmelt, hydrologic circle and water resources. This study simulated the impact of climate change on the runoff generation and streamflow of Chu River Basin(CRB), a glacierized basin in Central Asia using the enhanced Soil and Water Assessment Tool(SWAT). The model was calibrated and validated using the measured monthly streamflow data from three discharge gauge stations in CRB for the period 1961–1985 and was subsequently driven by downscaled future climate projections of five Global Circulation Models(GCMs) in Coupled Model Inter-comparison Project Phase 5(CMIP5) under three radiative forcing scenarios(RCP2.6, RCP4.5 and RCP8.5). In this study, the period 1966–1995 was used as the baseline period, while 2016–2045 and 2066–2095 as the near-future and far-future period, respectively. As projected, the climate would become warmer and drier under all scenarios in the future, and the future climate would be characterized by larger seasonal and annual variations under higher RCP. A general decreasing trend was identified in the average annual runoff in glacier(–26.6% to –1.0%), snow(–21.4% to +1.1%) and streamflow(–27.7% to –6.6%) for most of the future scenario periods. The projected maximum streamflow in each of the two future scenarios occurred one month earlier than that in the baseline period because of the reduced streamflow in summer months. Results of this study are expected to arouse the serious concern about water resource availability in the headwater region of CRB under the continuously warming climate. Changes in simulated hydrologic outputs underscored the significance of lowering the uncertainties in temperature and precipitation projection.     

Climate change impacts on the streamflow of Zarrineh River,Iran

Zarrineh River is located in the northwest of Iran, providing more than 40% of the total inflow into the Lake Urmia that is one of the largest saltwater lakes on the earth. Lake Urmia is a highly endangered ecosystem on the brink of desiccation. This paper studied the impacts of climate change on the streamflow of Zarrineh River. The streamflow was simulated and projected for the period 1992-2050 through seven CMIP5 (coupled model intercomparison project phase 5) data series (namely, BCC-CSM1-1, BNU-ESM, CSIRO-Mk3-6-0, GFDL-ESM2G, IPSL-CM5A-LR, MIROC-ESM and MIROC-ESM-CHEM) under RCP2.6 (RCP, representative concentration pathways) and RCP8.5. The model data series were statistically downscaled and bias corrected using an artificial neural network (ANN) technique and a Gamma based quantile mapping bias correction method. The best model (CSIRO-Mk3-6-0) was chosen by the TOPSIS (technique for order of preference by similarity to ideal solution) method from seven CMIP5 models based on statistical indices. For simulation of streamflow, a rainfall-runoff model, the hydrologiska byrans vattenavdelning (HBV-Light) model, was utilized. Results on hydro-climatological changes in Zarrineh River basin showed that the mean daily precipitation is expected to decrease from 0.94 and 0.96 mm in 2015 to 0.65 and 0.68 mm in 2050 under RCP2.6 and RCP8.5, respectively. In the case of temperature, the numbers change from 12.33°C and 12.37°C in 2015 to 14.28°C and 14.32°C in 2050. Corresponding to these climate scenarios, this study projected a decrease of the annual streamflow of Zarrineh River by half from 2015 to 2050 as the results of climatic changes will lead to a decrease in the annual streamflow of Zarrineh River from 59.49 m³/s in 2015 to 22.61 and 23.19 m³/s in 2050. The finding is of important meaning for water resources planning purposes, management programs and strategies of the Lake's endangered ecosystem.     

21世纪开都-孔雀河流域未来气候变化情景预估

利用Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections (DCHP)提供的31个 CMIP5降尺度数据和CRU逐月气温、降水格点数据集,通过评估PLS(偏最小二乘回归)、RR（岭回归）和EE（等权平均）3种多模式集合平均预估模型对历史气候变化的模拟能力,确定最优集合方法,进而预估开都-孔雀河流域21世纪气候变化情景。结果表明：① 所建立的PLS模型对流域的气温和降水具有较好的模拟能力,尤其对气温的模拟, r值均达到了0.64以上,明显优于降水（0.19~0.36）,但存在空间异质性;② 21世纪开都-孔雀河流域各子区气温呈显著增加趋势,且RCP8.5情景下的增温速率〔0.58~0.67 ℃·（10a）-1〕是RCP4.5情景下〔0.25~0.31 ℃·（10a）-1〕的2倍以上,21世纪中叶是2种情景产生明显差异的开始。整个流域增温速率由西北山区向东南荒漠区逐渐增大;③ 未来降水在不同排放情景下变化速率的分布状况略有不同,但均呈显著增加趋势,且RCP8.5情景下的增加速率〔1.22%~1.54%·（10a）-1〕总体上高于RCP4.5〔0.80%~1.32%·（10a）-1〕。     

Impacts of climate change on wheat anthesis and fusarium ear blight in the UK

Climate change will affect both growth of agricultural crops and diseases that attack them but there has been little work to study how its impacts on crop growth influence impacts on disease epidemics. This paper investigates how impacts of climate change on wheat anthesis date will influence impacts on fusarium ear blight in UK mainland arable areas. A wheat growth model was used for projections of anthesis dates, and a weather-based model was developed for use in projections of incidence of fusarium ear blight in the UK. Daily weather data, generated for 14 sites in arable areas of the UK for a baseline (1960–1990) scenario and for high and low CO₂ emissions in the 2020s and 2050s, were used to project wheat anthesis dates and fusarium ear blight incidence for each site for each climate change scenario. Incidence of fusarium ear blight was related to rainfall during anthesis and temperature during the preceding 6 weeks. It was projected that, with climate change, wheat anthesis dates will be earlier and fusarium ear blight epidemics will be more severe, especially in southern England, by the 2050s. These projections, made by combining crop and disease models for different climate change scenarios, suggest that improved control of fusarium ear blight should be a high priority in industry and government strategies for adaptation to climate change to ensure food security.     

Mapping the current and future distributions of Onosma species endemic to Iran

Climate change may cause shifts in the natural range of species especially for those that are geographically restricted and/or endemic species. In this study, the spatial distribution of five endemic and threatened species belonging to the genus Onosma (including O. asperrima, O. bisotunensis, O. kotschyi, O. platyphylla, and O. straussii) was investigated under present and future climate change scenarios: RCP2.6 (RCP, representative concentration pathway; optimistic scenario) and RCP8.5 (pessimistic scenario) for the years 2050 and 2080 in Iran. Analysis was conducted using the maximum entropy (MaxEnt) model to provide a basis for the protection and conservation of these species. Seven environmental variables including aspect, depth of soil, silt content, slope, annual precipitation, minimum temperature of the coldest month, and annual temperature range were used as main predictors in this study. The model output for the potential habitat suitability of the studied species showed acceptable performance for all species (i.e., the area under the curve (AUC)>0.800). According to the models generated by MaxEnt, the potential current patterns of the species were consistent with the observed areas of distributions. The projected climate maps under optimistic and pessimistic scenarios (RCP2.6 and RCP8.5, respectively) of 2050 and 2080 resulted in reductions and expansions as well as positive range changes for all species in comparison to their current predicted distributions. Among all species, O. bisotunensis showed the most significant and highest increase under the pessimistic scenario of 2050 and 2080. Finally, the results of this study revealed that the studied plant species have shown an acute adaptability to environmental changes. The results can provide useful information to managers to apply appropriate strategies for the management and conservation of these valuable Iranian medicinal and threatened plant species in the future.     

基于MaxEnt预测未来气候条件下钻叶紫菀在中国的潜在适生区

钻叶紫菀Symphyotrichum subulatum是一级恶性入侵植物,其传播速度快,繁殖能力强,严重影响本地草本植物多样性。本研究利用生态位模型MaxEnt和地理信息系统软件ArcGIS,根据收集的钻叶紫菀分布点和环境变量,预测目前气候条件和未来气候变化情景下钻叶紫菀在中国的潜在适生区,并推测环境变量对钻叶紫菀适生区的影响。结果表明,钻叶紫菀的潜在适生区主要位于亚热带湿润型气候大区的低海拔区域,其中高适生区的分布范围为21°～40°N,主要位于广东、福建、江西、江苏、湖南、湖北、四川东南地区和安徽东北地区等。影响钻叶紫菀潜在适生区分布的关键环境变量为最干旱月份降水量、最湿润月份降水量、10月平均温度、3月最高温度、8月最低温度和6月太阳辐射量。在未来气候变化情景SSP126、SSP245、SSP370和SSP585条件下,钻叶紫菀的低、中和高适生区面积占比将分别增加3.54%、4.80%、5.73%和3.29%。整体而言,未来气候变化有利于钻叶紫菀适生区的扩张。到21世纪中叶,钻叶紫菀的高适生区呈现向高海拔地区和中高纬度(具体为由南向北和西北方向)扩张的趋势。钻叶紫菀适生区分布范...     

基于MaxEnt模型预测外来入侵植物刺果瓜在中国的潜在地理分布

为明确外来入侵植物刺果瓜 Sicyos angulatus在我国的潜在地理分布,基于MaxEnt模型、ArcGIS软件及全球分布数据,在历史气候条件及未来气候条件下 （低强迫情景SSP126和高强迫情景SSP585）预测刺果瓜在中国的潜在地理分布。结果显示, MaxEnt模型的曲线下面积（area undercurve, AUC）值为0.977,表明模型具有较高的可靠性;气温季节性变化、最热月的最高温、最干月降水量和最湿季节的降水量是影响刺果瓜在中国潜在地理分布的4个关键环境变量;历史气候条件下刺果瓜主要发生在中国东部、中部和西部,适生区总面积占中国陆地总面积的23.29%;未来气候条件下,刺果瓜在中国的适生区范围有所减少, SSP126和SSP585情景下刺果瓜在中国的适生区总面积分别为186.10×10⁴ km²和162.68×10⁴ km²,分别占中国陆地总面积的19.35%和16.91%,但还是主要覆盖黄淮海平原夏播玉米区和南方丘陵玉米区等产区,质心由南向北移动。     

基于水足迹的民勤县农作物耗水当量与气候响应评估

在阐述水足迹、水资源压力指数的基础上,计算了1991—2013年民勤县8种主要农作物(玉米、小麦、棉花、葵花、苹果、瓜类、蔬菜)蓝水需水量、总耗水当量和单位作物耗水当量,研究了这些作物在23年内总耗水当量和单位耗水当量的时间序列变化规律,并对比三种经济技术耗水分离模型,分离出4种典型作物(小麦、玉米、棉花、瓜类)单位气候耗水当量,最后选择逐步回归分析法探讨了作物气候耗水当量与相关气候因子之间的关系。结果表明:(1)民勤总耗水当量逐年增加,粮食作物总耗水当量变化最大,蔬菜、油料作物(葵花)次之,单位作物耗水当量在震荡中逐年递减;(2)HP滤波法为最优气候耗水当量分离模型,单位作物气候耗水当量趋势性不明显,序列期内震荡显著,且不同作物差异较大;(3)显著影响单位作物气候耗水当量的主要气候因子为5、6月份总降水量和7月份相对湿度,与生长期内气温要素相关性不强。可见,不同作物耗水变化的气候响应模式差异较大,整体受降水和温度的影响显著,但对全球气候变暖大趋势的响应机制尚不明确。     

未来气候变化对东北地区玉米单产影响的模拟研究

东北地区是我国具有战略意义的商品粮基地,研究气候变化对东北地区玉米产量的影响具有重要意义。采用区域气候模式与作物生长WOFOST模型相结合的方法,模拟了基准气候(BS,1961-1990年)和B2情景下2011-2050年东北地区的玉米单产,初步预测了未来气候情景下玉米单产的变化状况。结果表明:WOFOST作物模型能较好的模拟东北地区的玉米产量,模型检验结果表明,该模型对玉米产量的模拟在70%～80%年份里的模拟精确度在80%以上。模拟结果显示:未来10-20年内,东北地区北部大部地区玉米具有增产潜力,但就北地区整体而言,总体增产幅度较小。2030s和2040s东北地区大部受气候因素影响表现为减产。未来40年,受气候变化影响东北地区玉米单产总体表现为减产,减产幅度为9.5%。由于目前的研究结果存在未考虑农业生产的适应措施等局限性,可能会高估气候变化的负面影响。     

Economic losses from reduced freshwater under future climate scenarios: An example from the Urumqi River,Tianshan Mountains

As important freshwater resources in alpine basins, glaciers and snow cover tend to decline due to climate warming, thus affecting the amount of water available downstream and even regional economic development. However, impact assessments of the economic losses caused by reductions in freshwater supply are quite limited. This study aims to project changes in glacier meltwater and snowmelt of the Urumqi River in the Tianshan Mountains under future climate change scenarios (RCP2.6 (RCP, Representative Concentration Pathway), RCP4.5, and RCP8.5) by applying a hydrological model and estimate the economic losses from future meltwater reduction for industrial, agricultural, service, and domestic water uses combined with the present value method for the 2030s, 2050s, 2070s, and 2090s. The results indicate that total annual glacier meltwater and snowmelt will decrease by 65.6% and 74.5% under the RCP4.5 and RCP8.5 scenarios by the 2090s relative to the baseline period (1980-2010), respectively. Compared to the RCP2.6 scenario, the projected economic loss values of total water use from reduced glacier meltwater and snowmelt under the RCP8.5 scenario will increase by 435.10×10⁶ and 537.20×10⁶ CNY in the 2050s and 2090s, respectively, and the cumulative economic loss value for 2099 is approximately 2124.00×10⁶ CNY. We also find that the industrial and agricultural sectors would likely face the largest and smallest economic losses, respectively. The economic loss value of snowmelt in different sectorial sectors is greater than that of glacier meltwater. These findings highlight the need for climate mitigation actions, industrial transformation, and rational water allocation to be considered in decision-making in the Tianshan Mountains in the future.     

基于MaxEnt模型预测气候变化下飞扬草在中国的潜在地理分布

为明确入侵杂草飞扬草Euphorbia hirta Linn.在中国的潜在地理分布，基于MaxEnt模型结合ArcGIS地理信息系统软件，对飞扬草在历史气候及未来气候2个情景下的潜在适生区进行预测，并采用刀切法分析各环境因子对飞扬草适生区的影响。结果显示，在飞扬草潜在地理分布变化过程中，影响最大的环境因子是最湿季度降水量，其次是最暖季度平均温度。历史气候条件下，飞扬草在中国的总适生区面积占全国陆地总面积的32.45%，其中高适生区占13.57%，中适生区占10.06%，低适生区占8.82%。未来气候条件下，预测结果表明2050年飞扬草的潜在适生区将进一步扩张，其中在高强迫SSP585情景下飞扬草的总适生区面积大于低强迫SSP126情景下的总适生区面积，而SSP126情景下的高适生区面积则大于SSP585情景下的高适生区面积。表明飞扬草在中国的潜在适生区分布范围较广，可能在未来进一步扩散至全国，建议相关部门加强监控，防止飞扬草进一步入侵和扩散。     

Downy mildew outbreaks on grapevine under climate change: elaboration and application of an empirical‐statistical model*

The global climate is changing. Much research has already been carried out to assess the potential impacts of climate change on plant physiology. However, effects on plant disease have not yet been deeply studied. In this paper, an empirical disease model for primary infection of downy mildew on grapevine was elaborated and used to project future disease dynamics under climate change. The disease model was run under the outputs of the General Circulation Model (GCM) and future scenarios of downy mildew primary outbreaks were generated at several sites all over the word for three future dates: 2030, 2050, 2080. Results suggested a potential general advance of first disease outbreaks, both in the Northern and Southern Hemispheres, for all three future decades considered. The advance is predicted to be from about a minimum of one day in South Africa in 2030 to a maximum of 28 days in Chile and China in 2080. The advance in the outbreak time could lead to more severe infections, due to the polycyclic nature of the pathogen. Therefore, changes in the timing and frequency of fungicide treatments could be expected in the future, with a possible increase in the costs of disease management.     

基于CMIP5的中国区域气溶胶变化及其对降水的影响

基于第5次国际耦合模式比较计划(CMIP5)提供的气溶胶光学厚度(AOD)数据和气溶胶单因子历史试验降水数据,采用线性趋势分析、相关分析、经验正交分解(EOF)方法,从时间和空间维度上分析了自工业革命以来中国AOD的变化及其对降水的影响。1860-2000年,中国区域的AOD整体呈显著增加的趋势(P<0.001),AOD的增加趋势以胡焕庸线为界呈现出"东高西低"的空间分布格局,并在1945年以后AOD的增加趋势〔0.3807·(100a)^-1〕显著大于1945年以前的趋势〔0.0290·(100a)^-1〕。在气溶胶单因子驱动试验中,中国有89.1%区域的降水呈显著减少的趋势(P<0.001),其中东南部、四川盆地以及青藏高原东南部是降水减少最明显的区域,西北地区降水减少趋势较弱,并在1962年以后降水的减少趋势〔118.04mm·(100a)^-1〕显著大于1962年以前的趋势〔26.67mm·(100a)^-1〕。气溶胶主要通过抑制弱降水显著降低了降水事件发生的频率与降水强度,降低速率分别为3.160d·(100a)^-1、0.1624mm·d^-1·(100a)^-1。研究工业革命以来气溶胶对降水的气候效应,为更好的应对区域气候变化问题提供科学依据。     

Scenario simulation of water retention services under land use/cover and climate changes: a case study of the Loess Plateau,China

Comprehensive assessments of ecosystem services in environments under the influences of human activities and climate change are critical for sustainable regional ecosystem management. Therefore, integrated interdisciplinary modelling has become a major focus of ecosystem service assessment. In this study, we established a model that integrates land use/cover change (LUCC), climate change, and water retention services to evaluate the spatial and temporal variations of water retention services in the Loess Plateau of China in the historical period (2000-2015) and in the future (2020-2050). An improved Markov-Cellular Automata (Markov-CA) model was used to simulate land use/land cover patterns, and ArcGIS 10.2 software was used to simulate and assess water retention services from 2000 to 2050 under six combined scenarios, including three land use/land cover scenarios (historical scenario (HS), ecological protection scenario (EPS), and urban expansion scenario (UES)) and two climate change scenarios (RCP4.5 and RCP8.5, where RCP is the representative concentration pathway). LUCCs in the historical period (2000-2015) and in the future (2020-2050) are dominated by transformations among agricultural land, urban land and grassland. Urban land under UES increased significantly by 0.63×10³ km²/a, which was higher than the increase of urban land under HS and EPS. In the Loess Plateau, water yield decreased by 17.20×10⁶ mm and water retention increased by 0.09×10⁶ mm in the historical period (2000-2015), especially in the Interior drainage zone and its surrounding areas. In the future (2020-2050), the pixel means of water yield is higher under RCP4.5 scenario (96.63 mm) than under RCP8.5 scenario (95.46 mm), and the pixel means of water retention is higher under RCP4.5 scenario (1.95 mm) than under RCP8.5 scenario (1.38 mm). RCP4.5-EPS shows the highest total water retention capacity on the plateau scale among the six combined scenarios, with the value of 1.27×10⁶ mm. Ecological restoration projects in the Loess Plateau have enhanced soil and water retention. However, more attention needs to be paid not only to the simultaneous increase in water retention services and evapotranspiration but also to the type and layout of restored vegetation. Furthermore, urbanization needs to be controlled to prevent uncontrollable LUCCs and climate change. Our findings provide reference data for the regional water and land resources management and the sustainable development of socio-ecological systems in the Loess Plateau under LUCC and climate change scenarios.     

气候变化下栎枯萎病菌在中国的潜在适生区预测

为降低未来气候变化下栎树枯萎病暴发的风险，基于现有的栎枯萎病菌Bretziella fagacearum分布数据，筛选影响其分布的关键环境变量，利用优化后的MaxEnt模型预测当前气候条件和未来气候条件（低强迫情景SSP126和高强迫情景SSP585）下其在中国的潜在适生区。结果显示，最暖月最高温度、最干季度平均温度、年降水量、最干月降水量是影响栎枯萎病菌分布的关键环境变量；优化后MaxEnt模型的受试者工作特征曲线下面积值高于0.90，表明该模型预测结果可靠。当前气候条件下栎树枯萎病菌的适生区面积约为1.39×10⁶ km²，占中国陆地总面积的14.48%，高适生区主要分布在湖南省北部、浙江省中南部、湖北省东南部、江西省西部和新疆维吾尔自治区北部。未来气候条件（低强迫情景SSP126和高强迫情景SSP585）下栎树枯萎病菌适生区面积均呈增加趋势，尤其高适生区的气候异常程度最高，造成其面积增加。此外，高适生区的质心均有由湖南省向北迁移的趋势。     

不同气候情景下中国东北与华北作物产量变化趋势模拟

采用意大利ICTP中心的区域气候模式RegCM3输出的多情景加权平均值简称REA情景和英国Hadley中心的区域气候模式PRECIS输出的A2和B2情景,结合WOFOST作物生长模拟模型,模拟研究了未来40 a(2011—2050年)气候变化对我国华北东北农作物产量的影响。模拟结果表明:从40 a平均结果来看,对于东北玉米区,三种气候情景资料下可能减产区域主要是东北三省的偏西南地区,其中减产高值区主要集中在吉林省的西部地区白城、通榆等地。对于华北冬麦区,REA情景下可能减产区主要是河北省的东部和山东省的东部,其中减产高值区主要集中在京津及其以东地区;A2和B2情景下可能减产区主要是河北省的中部和东部、山东省的东部以及河南省的南部偏南地区,其中减产高值区主要集中在天津及其以东地区和山东省的东部沿海地区。     

气候变化对新疆意大利蝗潜在分布的影响

意大利蝗Calliptamus italicus(L.)是新疆草原主要优势蝗虫之一,每年给新疆畜牧业经济带来严重损失,气候变化对其潜在分布影响的预测对其科学防治有重要意义。本研究采用意大利蝗的分布数据和生物气候数据,结合MaxEnt模型和ArcGIS软件,预测了BCC_CSM1.1气候模式下政府间气候变化专门委员会第五次工作报告(IPCC AR5)采用的RCP2.6、RCP4.5和RCP8.5三种气候情景在2021-2040年(2030s)、2041-2060年(2050s)和2061-2080年(2070s)的意大利蝗新疆潜在适生区分布范围。结果表明:在BCC_CSM1.1的各情景下,意大利蝗适生区在北疆及天山一带分布格局基本保持不变,但高度适生区面积都有所增加,其中在天山和阿尔泰山地区,意大利蝗中、高度适生区范围将向更高海拔区域蔓延,在北疆阿勒泰地区高度适生区明显增加。极端水分条件和水热条件对意大利蝗在新疆潜在分布发挥主要作用,其中4月、10月、3月和11月降水量对意大利蝗在新疆潜在分布影响最大,因其直接影响土壤相对含水量和土壤温度,从而决定意大利蝗卵的存活量。     

Simulating hydrological responses to climate change using dynamic and statistical downscaling methods: a case study in the Kaidu River Basin,Xinjiang, China

Climate change may affect water resources by altering various processes in natural ecosystems. Dynamic and statistical downscaling methods are commonly used to assess the impacts of climate change on water resources. Objectively, both methods have their own advantages and disadvantages. In the present study, we assessed the impacts of climate change on water resources during the future periods (2020-2029 and 2040-2049) in the upper reaches of the Kaidu River Basin, Xinjiang, China, and discussed the uncertainties in the research processes by integrating dynamic and statistical downscaling methods (regional climate models (RCMs) and general circulation modes (GCMs)) and utilizing these outputs. The reference period for this study is 1990-1999. The climate change trend is represented by three bias-corrected RCMs (i.e., Hadley Centre Global Environmental Model version 3 regional climate model (HadGEM3-RA), Regional Climate Model version 4 (RegCM4), and Seoul National University Meso-scale Model version 5 (SUN-MM5)) and an ensemble of GCMs on the basis of delta change method under two future scenarios (RCP4.5 and RCP8.5). We applied the hydrological SWAT (Soil and Water Assessment Tool) model which uses the RCMs/GCMs outputs as input to analyze the impacts of climate change on the stream flow and peak flow of the upper reaches of the Kaidu River Basin. The simulation of climate factors under future scenarios indicates that both temperature and precipitation in the study area will increase in the future compared with the reference period, with the largest increase of annual mean temperature and largest percentage increase of mean annual precipitation being of 2.4°C and 38.4%, respectively. Based on the results from bias correction of climate model outputs, we conclude that the accuracy of RCM (regional climate model) simulation is much better for temperature than for precipitation. The percentage increase in precipitation simulated by the three RCMs is generally higher than that simulated by the ensemble of GCMs. As for the changes in seasonal precipitation, RCMs exhibit a large percentage increase in seasonal precipitation in the wet season, while the ensemble of GCMs shows a large percentage increase in the dry season. Most of the hydrological simulations indicate that the total stream flow will decrease in the future due to the increase of evaporation, and the maximum percentage decrease can reach up to 22.3%. The possibility of peak flow increasing in the future is expected to higher than 99%. These results indicate that less water is likely to be available in the upper reaches of the Kaidu River Basin in the future, and that the temporal distribution of flow may become more concentrated.     

Ecological determinants and risk areas of Striga hermonthica infestation in western Kenya under changing climate

Striga hermonthica (Del.) Benth is a parasitic weed that is damaging major cereal crops in sub-Saharan Africa (SSA). Although Striga is recognised as an agricultural scourge, there is limited information available indicating the extent of its growth and spread as impacted by the changing climate in Kenya. This study investigated the impact of current climate conditions and projected future (2050) climate change on the infestation of Striga hermonthica in the western Kenya region. Specifically, the study aimed to predict Striga hermonthica habitat suitability in five counties in the western Kenya region through using the maximum entropy (MaxEnt) model and bioclimatic, soil, topographic and land use, and land cover (LULC) variables. Striga hermonthica geolocations were collected and collated and ecological niche models were developed to determine the habitat suitability. The results showed that approximately 1767 km² (10% of the total study area) is currently highly suitable for Striga hermonthica occurrence. The future projections showed a range between 2106 km² (19% of the total study area) and 2712 km² (53% of the total study area) at the minimum carbon (RCP 2.6) and the maximum carbon emission scenarios (RCP 8.5) respectively. Elevation, annual precipitation, LULC, temperature seasonality and soil type were determined to be the most influential ecological predictor variables for Striga hermonthica establishment. The study revealed the importance of using climate, soil, topographic and LULC variables when evaluating agricultural production constraints such as Striga's prevalence. The methodology used in this study should be tested in other Striga affected areas.