基于土地利用方式的巢湖流域氮排放情景模拟

土地利用方式及其转移对区域氮素迁移和水体氮负荷产生重要影响,但量化自然发展、耕地保护和生态保护等多情景下土地利用方式氮排放时空变化特征,揭示流域水体氮负荷对土地利用变化的响应机制仍面临挑战。本研究以巢湖流域为研究区,通过遥感解译多时相土地利用类型数据,借助PLUS和InVEST模型探索不同情景下氮排放对各土地利用类型变化的响应机制。结果表明:(1)2000—2020年期间,巢湖流域建设用地面积的增加(626.14 km²)主要占据的是耕地(减少了775.64 km²),城市化建设成为土地利用方式变化的主要驱动力;(2)PLUS模型多情景预测结果显示:2020—2030年间土地利用变化特征与2000—2020年基本保持一致,但各用地间的转换频率降低;(3)经InVEST模拟,耕地面积缩减而导致氮排放的减少量(340.17 t)大于建设用地等面积增加带来的氮排放增加量(170.11 t),使2000—2020年间巢湖流域土地利用所排放的总氮量呈降低趋势,由2000年的4768.04 t降至2020年的4597.98 t;(4)不同情景下,2030年各土地利用方式的氮排放量较2020年均呈降低趋势。其中,生态保护情景既有效地保障了巢湖流域生态功能又展现出较好的氮减排效果(113.36 t);鉴于此,建议流域管理部门应通过合理规划各用地类型的发展,严格控制建设用地对林草地、水域等生态用地的侵占,以期削减流域水体氮负荷、缓解氮素治理压力。     

太湖流域土地利用变化的水文响应模拟

以城市化快速发展的太湖流域为研究对象,采用1985、1995和2000年TM/ETM土地利用解译资料,应用区域尺度单元格网分布式水文模型,进行长序列水文模拟,定量评估太湖流域土地利用变化及其水文响应特征,为流域用地规划、水资源管理以及灾害防治提供决策参数.研究显示,自1985年到2000年,太湖流域城镇面积扩展了40.38%,增加量占太湖流域总面积的3.88%.在1980-2000年的雨情下,全流域土地利用变化导致产流量平均增加4.11%,约为7.56×108 m3,最高值为11.76%,约为10.0×108 m3.受土地利用变化空间差异影响,产流量增加具有较大区域差异,城镇快速扩展的苏锡常地区和浦东浦西地区,土地利用变化导致产流量平均增加为10.07%和7.03%,最高增量达20%-30%.     

近30年中国沿海围垦土地利用格局及其驱动机制

文章以近30年中国沿海地区围垦土地为研究对象,以1985年为基期,分为1985～1990年、1990～1995年、1995～2000年、2000～2005年、2005～2010年、2010～2016年六个时段,系统剖析了中国沿海围垦土地时空演变特征、格局与驱动机制,模拟分析了三种不同发展情景下的围垦土地利用变化及其社会经济、生态环境综合效应.结果表明:(1)近30年中国沿海地区围垦土地9310.6km2,设施农业用地、工矿用地与空闲地面积较大,分别占总围垦面积的42.1%、14.08%和13.9%;全国沿海土地围垦面积变化可划分为增长速率降低阶段、增长速率提升阶段、增长速率减缓阶段;(2)近30年土地围垦最终流向为耕地、农业设施用地与工矿用地,受政策、经济、人口的驱动影响明显,最终形成土地围垦的恶性循环;(3)在三种不同模拟情景下,生态环境效应下降,社会经济效应逐渐增加,珠江三角洲、长江三角洲和环渤海地区的社会经济效应的增速起点时间具有明显差异,分别为1990年、2000年和2005年.最后,深入探析了围垦土地利用问题产生的根源及成因,提出了实现沿海围垦土地可持续利用和加强沿海地区生态环境保护的对策与建议.     

基于CMIP5模式鄱阳湖流域未来参考作物蒸散量预估

预测未来气候情境下鄱阳湖流域参考作物蒸散量(Reference crop Evapotranspiration,ET0)的时空分布可为流域水资源的优化管理,为科学应对气候变化对农业生产的影响提供基础数据支撑.利用鄱阳湖流域14个气象站点1961-2014年逐日气象数据,采用Penman-Monteith公式计算出历史ET0;基于同期美国环境中心(NCEP)再分析数据及2006-2100年CMIP5中CNRM-CM5模式在RCP4. 5和RCP8. 5情景下的预测数据,经统计降尺度模型(statistical downscaling model,SDSM)模拟和偏差校正,预测流域未来ET0;通过Mann-Kendall检验、普通克里金插值和空间自相关法分析了流域1961-2100年ET0的时空演变特征.结果表明:NCEP再分析资料与流域ET0建立的逐步回归降尺度模型模拟效果较好,CNRMCM5模式降尺度模拟结果经偏差校正后,精度明显提高,适宜流域未来ET0的预估.鄱阳湖流域在基准期1961-2010年ET0整体上呈减小趋势,空间分布上呈南北高、中间低的特点,表现出明显的空间差异性.RCP4.5、RCP8.5情景下未来3个时期鄱阳湖流域ET0较基准期均呈不同程度的增加趋势,其空间分布整体表现为东高西低、局地略有突出;无论是在基准期或是未来情景下的3个时期,ET0均具有较强的空间自相关性.在RCP8.5情景下,鄱阳湖1961-2100年干旱指数呈现出较为明显的上升趋势,流域的干旱状况随时间加剧,2011-2100年间流域绝大部分地区由湿润区转为半湿润区,干旱指数自南向北递减,赣江流域将是鄱阳湖流域未来干旱风险的重点防范区.     

流域土地利用分区空间管制研究与初步实践——以太湖流域为例

流域空间开发和土地利用在推动经济社会发展的同时,对流域生态系统的健康和安全造成了剧烈影响,迫切需要在流域综合管理中充实完善土地利用分区与管制等研究内容,因而成为推动湖泊-流域相互作用研究的重要科学问题之一.本文在回顾相关土地利用分区与管制研究基础上,从流域自然地理单元特殊性和管理目标复杂性出发,探讨了流域水陆系统相互作用机制,分析了流域土地利用分区与空间管制的研究重点与基本思路,提出了流域土地利用分区的技术路线及关键方法,并以太湖流域为例进行了初步的实践探索,提出严格保护区、适度发展区、开发利用区和保留发展区四种类型区及其空间管制要求,符合流域资源环境与经济社会发展实际,为流域可持续开发和保护提供指导.最后,讨论了未来流域土地利用分区空间管制需要进一步研究的重点方向与关键问题.     

未来土地利用变化影响中国区域气候的数值模拟

土地利用/土地覆盖变化(LUCC)是人类影响气候的重要强迫之一.相对于历史时期LUCC对区域气候的影响研究,未来LUCC到底对气候有多大影响不得而知.基于CMIP5推荐的土地覆盖数据,采用区域气候模式Reg CM4,通过当代和反映未来(2050年)土地覆盖状况分布情况下各15年(2036~2050)的数值积分试验,探讨了未来LUCC对中国区域气候的影响.未来中国地区主要是以草地转换成森林为主要特征,LUCC引起温度和降水的变化幅度和范围具有季节性差异,其中夏、秋季区域响应最显著,主要包括中国东北、华北和河套地区,青藏高原东部以及华南等地.进一步分析表明,LUCC对大气环流也具有明显的影响,在未来LUCC影响下,印度半岛经孟加拉湾到南海及华南沿岸一带受到一致的异常西南风控制,热带印度西南季风和南海西南季风均偏强,来自南海和印度洋的异常水汽辐合使得中国南方降水偏多.     

快速城镇化进程中太湖流域产水量变化的时空分布特征

快速城镇化进程中太湖流域下垫面的剧烈变化对流域产水量时空分布产生了深刻影响.在分析太湖流域城镇化进程及土地利用变化的基础上,采用太湖流域模型对3种典型降雨过程（1991、1999和2009年）与5种下垫面（1985、1995、2000、2005和2010年）的组合情景进行模拟,综合分析了城镇化进程中全流域和各水利分区在全年期、汛期、涨水期产水量变化的时空分布特征.结果表明：时程上,太湖流域和所有水利分区的各统计时段产水量增幅伴随城镇化进程推进均呈现增加趋势,2005年后产水量增幅进一步加大,且全年产水量增幅主要集中在汛期;空间上,东、中部城市集聚区的产水量增长率明显高于西部山丘区与太湖湖区,这主要是由于西部山丘区、太湖湖区不透水率增幅较小所致.产水量变化的时空非均匀分布特征为城镇化背景下太湖流域防洪除涝格局演变及流域-区域-城市防洪除涝协调性研究提供了重要的先验认识.     

欧亚大陆植被生态系统潜在分布情景及其对气候变化的响应

欧亚大陆植被生态系统的时空分布特征及未来如何变化是"一带一路"倡议推进过程中亟需研究的关键生态环境问题之一.在对HLZ生态系统模型进行修正、拓展和完善的基础上,结合欧亚大陆气候观测数据(1981～2010年)和CMIP5 RCP26、RCP45和RCP85三种情景数据,实现欧亚大陆植被生态系统潜在分布变化特征及未来情景的模拟,并采用生态系统类型多样性模型和生态系统斑块连通性模型,定量揭示欧亚大陆HLZ生态系统类型多样性的变化情景.模拟结果显示,寒温带潮湿森林、冷温带湿润森林和荒漠是欧亚大陆最主要的植被生态系统类型,占整个欧亚大陆总面积的36.71%;三种情景下,极地/冰原面积减少最多,平均每10年减少26.75×106km~2,亚极地/高山湿润苔原减少最快,平均每10年减少10.49%;其中, RCP85情景下的欧亚大陆植被生态系统的变化速度快于其他两种情景,亚极地/高山湿润苔原减少最快,平均每10年减少10.88%.欧亚大陆HLZ生态系统类型多样性整体呈减少趋势,其中RCP26、RCP45和RCP85三种情景的HLZ生态系统类型多样性在2010～2100年间,平均每10年将分别减少0.09%、0.13%和0.16%;植被生态系统斑块连通性在三种情景下均呈现先增加后减少的趋势;"一带一路"沿线的中国区、蒙俄区、西亚区、中亚区、南亚区、东南亚区和欧洲区的HLZ生态系统时空分布及其变化差异特征显著.     

气候变化对黄土高原黑河流域水资源影响的评估与调控

气候变化将对水资源产生重要影响, 评估其潜在影响可为区域可持续发展提供重要的依据. 本研究的目标是评估2010~2039年气候变化对黄土高原黑河流域水资源的可能影响并进而探讨适应性对策. 基于4种全球环流模式(CCSR/NIES, CGCM2, CSIRO-Mk2和HadCM3)的各3种排放情景(A2, B2和GGa), 使用比例法预估了降水、最高和最低温度的未来变化; 使用SWAT (Soil and Water Assessment Tool)模型模拟气候变化的水文响应; 基于元胞自动机-马尔可夫模型(CA-Markov)建立未来土地利用情景. 结果表明, 与目前气候相比, 全球环流模式预测年均降水变化-2.3%~7.8%, 年均最高和最低温度分别增长0.7~2.2和1.2~2.8℃. 不考虑土地利用变化时, SWAT预测2010~2039年的年均径流变化-19.8%~37.0%, 土壤水分含量变化-5.5%~17.2%, 蒸散量普遍增长0.1%~5.9%. 尽管水文气象变量的变化复杂, 但增长的概率较大; 且水文过程将发生变化, 如冬季径流减少等. 考虑土地利用变化时, 较2000年土地利用, 建立的2015土地利用情景将分别增加土壤水分和径流4.0%和5.7%而减少蒸散0.6%. 这表明调整土地利用模式可以有效调控水资源, 可被用来减缓气候变化的不利影响.     

中国耕地变化驱动力分区研究

耕地变化机制是土地利用/土地覆盖(LUCC)研究的重要问题之一. 文中依据1980年代末和2000年两期土地利用遥感调查数据, 应用地理信息系统(GIS)和遥感技术对全国近期耕地变化与自然、社会经济状况进行综合分区研究. 研究发现, 各地区耕地减少和增加是在地理背景制约下,气候系统和社会经济系统变化共同驱动下发生的. 但引起耕地变化的驱动机制具有显著的区域差异, 在中西部地区自然条件的制约和推动起主导作用, 而在东部较发达地区, 社会经济、政策的驱动起主要作用. 耕地面积减少状况在全国范围内普遍存在, 其主导因素包括：招商引资和对外开放政策背景下的开发区建设、城市化导致的产业结构变化和城镇扩张、人民生活水平提高导致的就业观念的改变、气候变化导致的耕种收益的下降、交通条件的改善等等, 这些因素相互作用、相互依赖, 共同导致了中国近年来耕地大量减少的局面. 耕地增加则主要由于农民集体或个人为增加收入, 并在气候条件允许下, 开垦林地、草地或未利用地. 对LUCC驱动机制的研究建立在耕地变化综合分区的基础上, 不仅考虑区域内部的自然与人文因素, 而且还充分考虑了区域外部自然与人文因素的影响作用, 并以定量化的指标反应了各种不同因素对耕地变化的影响作用水平, 本研究可以为综合地理分区与土地利用变化驱动机制研究领域提供一种新的研究方法和思路.     

天目湖流域丘陵山区典型土地利用类型氮流失特征

天目湖丘陵山区农业综合开发持续推进,大量林地转变为茶园,迫切需要认识茶园扩张对流域氮流失的影响.本研究选取茶园、次生马尾松林和毛竹林开展自然降雨条件下的径流小区实验,分析天目湖丘陵山区典型用地类型径流氮流失规律,为评估丘陵山区综合开发的水环境影响提供实测参数.研究表明:茶园、次生马尾松林和毛竹林地表径流TN浓度分别为11.25、2.83和3.60 mg/L,均以溶解态为主;壤中流TN浓度分别为27.16、3.59和1.06 mg/L,茶园和次生马尾松林均以溶解性无机氮(尤其是硝态氮)为主,毛竹林以溶解性有机氮为主;茶园、次生马尾松林和毛竹林的小区尺度地表径流系数均不到0.03,壤中流是丘陵山区径流的主要来源;茶园开发加剧了丘陵山区的氮素流失,茶园径流TN流失强度高达103.08 kg/(hm²·a),分别是次生马尾松林和毛竹林的7.6和23.2倍,壤中流贡献了流失总量的86.7%~99.7%.防治茶园径流氮流失需重点关注壤中流输出,在减量施肥的基础上,采取坡脚构建毛竹林生态缓冲带/在小流域出口布设塘坝等原位拦截措施,实现流域氮流失综合防控.     

Evaluating the spatial distribution of water balance in a small watershed,Pennsylvania

A conceptual water‐balance model was modified from a point application to be distributed for evaluating the spatial distribution of watershed water balance based on daily precipitation, temperature and other hydrological parameters. The model was calibrated by comparing simulated daily variation in soil moisture with field observed data and results of another model that simulates the vertical soil moisture flow by numerically solving Richards' equation. The impacts of soil and land use on the hydrological components of the water balance, such as evapotranspiration, soil moisture deficit, runoff and subsurface drainage, were evaluated with the calibrated model in this study. Given the same meteorological conditions and land use, the soil moisture deficit, evapotranspiration and surface runoff increase, and subsurface drainage decreases, as the available water capacity of soil increases. Among various land uses, alfalfa produced high soil moisture deficit and evapotranspiration and lower surface runoff and subsurface drainage, whereas soybeans produced an opposite trend. The simulated distribution of various hydrological components shows the combined effect of soil and land use. Simulated hydrological components compare well with observed data. The study demonstrated that the distributed water balance approach is efficient and has advantages over the use of single average value of hydrological variables and the application at a single point in the traditional practice. Copyright © 2000 John Wiley & Sons, Ltd.     

太湖流域LUCC对水文过程的影响

基于1971年枯水年、1989年丰水年、2000年平水年3类典型代表年的逐日降雨量、逐日蒸发量以及不同时期地表覆盖遥感分类数据,以城市化快速发展地表覆盖变化明显的太湖流域为研究区域,利用太湖流域河网水量模型进行了土地利用/覆被变化的水文响应研究,分析了太湖流域1990 2000年与2000 2006年间的土地利用/覆被变化及其对水位过程的影响.不仅有利于对城市化地区水文特征变化规律深入了解,也为典型城市化地区防洪减灾提供科学可靠的依据.研究表明,太湖流域城镇化进程的加快引起了土地利用/覆被变化的主要表现是水田、水域等面积向城镇面积转化,城镇化进程加快,2000 2006年期间的城镇化速度大于1990 2000年间;下垫面的变化对太湖流域水文过程产生了明显的影响,随着城市化进程地表覆盖的变化,水位有整体升高的趋势,并且增幅加大,与城镇化速率变化趋势相一致,城镇化程度高的地方水位上升更为明显;降雨量也是水位过程的影响因素之一.     

Modelling the hydrologic effects of dynamic land‐use change using a distributed hydrologic model and a spatial land‐use allocation model

This study develops a novel approach for modelling and examining the impacts of time–space land‐use changes on hydrological components. The approach uses an empirical land‐use change allocation model (CLUE‐s) and a distributed hydrological model (DHSVM) to examine various land‐use change scenarios in the Wu‐Tu watershed in northern Taiwan. The study also uses a generalized likelihood uncertainty estimation approach to quantify the parameter uncertainty of the distributed hydrological model. The results indicate that various land‐use policies—such as no change, dynamic change and simultaneous change—have different levels of impact on simulating the spatial distributions of hydrological components in the watershed study. Peak flow rates under simultaneous and dynamic land‐use changes are 5·71% and 2·77%, respectively, greater than the rate under the no land‐use change scenario. Using dynamic land‐use changes to assess the effect of land‐use changes on hydrological components is more practical and feasible than using simultaneous land‐use change and no land‐use change scenarios. Furthermore, land‐use change is a spatial dynamic process that can lead to significant changes in the distributions of ground water and soil moisture. The spatial distributions of land‐use changes influence hydrological processes, such as the ground water level of whole areas, particularly in the downstream watershed. Copyright © 2010 John Wiley & Sons, Ltd.     

Simulation of urban expansion based on cellular automata and maximum entropy model

Urban expansion is a hot topic in land use/land cover change(LUCC) researches. In this paper, maximum entropy model and cellular automata(CA) model are coupled into a new CA model(Maxent-CA) for urban expansion. This model can help to obtain transition rules from single-period dataset. Moreover, it can be constructed and calibrated easily with several steps.Firstly, Maxent-CA model was built by using remote sensing data of China in 2000(basic data) and spatial variables(such as population density and Euclidean distance to cities). Secondly, the proposed model was calibrated by analyzing training samples,neighborhood structure and spatial scale. Finally, this model was verified by comparing logistic regression CA model and their simulation results. Experiments showed that suitable sampling ratio(sampling ratio equals the proportion of urban land in the whole region) and von Neumann neighborhood structure will help to yield better results. Spatial structure of simulation results becomes simple as spatial resolution decreases. Besides, simulation accuracy is significantly affected by spatial resolution.Compared to simulation results of logistic regression CA model, Maxent-CA model can avoid clusters phenomenon and obtain better results matching actual situation. It is found that the proposed model performs well in simulating urban expansion of China. It will be helpful for simulating even larger study area in the background of global environment changes.     

Seasonal dynamics of suprapermafrost groundwater and its response to the freeing-thawing processes of soil in the permafrost region of Qinghai-Tibet Plateau

The suprapermafrost groundwater in permafrost region not only is an important component of the water cycle and land surface process, but also is closely associated with the charges of ecological environment in cold region. However, the seasonal dynamics, driving factors, and mechanism of suprapermafrost groundwater are not well understood. Based on observation at slope scale on suprapermafrost groundwater dynamics of typical alpine meadows in the Qinghai-Tibet Plateau, the seasonal dynamics, spatial distribution and driving factors of suprapermafrost groundwater were analyzed. The results showed that there were close relationships between the seasonal dynamics of suprapermafrost groundwater and the freezing-thawing processes of active soil in permafrost region. The seasonal dynamics of suprapermafrost groundwater and its slope distribution pattern were controlled by soil temperature of active layers. The phase and range of the suprapermafrost groundwater dynamics are determined by deep soil(below 60 cm depth) moisture and groundwater recharging sources. The relationship between active soil temperatures and dynamics of suprapermafrost groundwater levels was better described by Boltzmann functions. However, the influencing thresholds of soil temperature on groundwater dynamics varied at different depths of active layers and in different slope positions, which resulted in the significant spatial heterogeneity of suprapermafrost groundwater dynamics in slope scale. Land cover change and global warming certainly altered the dynamics of suprapermafrost groundwater and the hydraulic interaction between groundwater and rivers, and consequently altered the overall hydrologic cycle of watershed scale.     

A GIS-BASED DISTRIBUTED SOIL EROSION MODEL： A CASE STUDY OF TYPICAL WATERSHED, SICHUAN BASIN

Based on the measuring data and Digital Elevation Data (DEM) in a typical watershed--Hemingguan Watershed, Nanbu County, Sichuan Province of China, a GIS-based distributed soil erosion model was developed particularly for the purple soil type. It takes 20 m × 20 m grid as calculating unit and operates at 10-minute time interval. The required input data to the model include DEM, soil, land use, and time-series of precipitation and evaporation loss. The model enables one to estimate runoff, erosion and sediment yield for each grid cell and route the flow along its flow path to the watershed outlet. Furthermore, the model is capable of calculating the total runoff; erosion and sediment yield for the entire watershed by recursion algorithm. The validation of the model demonstrated that it could quantitatively simulate the spatial distribution of hydrological variables in a watershed, such as runoff, vegetation entrapment, soil erosion, the degree of soil and water loss. Moreover, it can evaluate the effect of land use change on the runoff generation and soil erosion with an accuracy of 80% and 75% respectively. The application of this model to a neighboring watershed with similar conditions indicates that this distributed model could be extended to other similar regions in China.     

不同尺度流域地表径流氮、磷浓度比较

选择太湖上游为研究对象,采集了1-400 km2不同尺度小流域产出径流TN、TP浓度实测数据,结合前期开展的地表坡面流人工暴雨实验监测结果,开展不同尺度流域水质监测对水体面源污染产出浓度估算影响的比较研究,探讨流域尺度之间入渗、汇流以及伴随的流域生态系统营养盐调节机制的差异．结果表明,流域监测尺度对土地利用面源污染产出浓度估算有较大影响．地表坡面流由于未经过流域汇流过程伴随的下渗滤过与吸附等过程,产出径流TN、TP浓度一般高于小流域．小流域林地生态系统具有较强的入渗机制、接近自然的生态沟谷汇流网络,对面源污染TN、TP有较强的削减作用．农业生态系统较弱的入渗机制、人工沟渠汇流网络对面源污染TN、TP的削减作用较弱．现代农业造成流域面源污染增加不仅仅是因为人类农业活动对流域局部土体及养分的改变,农业生态系统改变流域自然生态系统整体水文过程及营养盐调节机制也是面源污染增加的重要因素之一,恢复小尺度的生态沟谷网络系统对削减流域面源污染具有重要的意义．     

A contrast of two typical LUCC processes and their driving forces in oases of arid areas: A case study of Sangong River Watershed at the northern foot of Tianshan Mountains

Aerial photographs taken in 1978 and 1987, Landsat TM images in 1998 as well as soil, hydrology and socio-economic data for the oases in Sangong River Watershed were processed by Remote Sensing (RS) and Geographic Information System (GIS). There are two typical agricultural land uses in oases, Farm-based Land Use with large-scale intensified agricultural activities (FLU) and Household Responsibility-based Land Use with small-scale activities (HRLU). The Index Model of Land Use/Land Cover Change (LUCC), Weighted Index Sum (WIS) and logistic stepwise regression model were established to contrast the two typical LUCC processes and their driving forces. The land use patterns were dominated by cropland and grassland for the entire region, and cropland, residential and industrial land were increasing stably. In the HRLU areas, woodland and grassland declined dramatically, but in the FLU areas, grassland decreased only by 12.0%, whereas woodland increased by 13.7%. LUCC was stronger in the earlier stage (1978–1987) than in the later stage (1987–1998) for the entire region. LUCC was more intense in the HRLU areas than in the FLU areas during the entire period (1978–1998). Policy was a key factor in the land use change, and water resources were a precondition in land use. Under the control of policy and water resources, the main human driving factors included population and economy, and the main natural restrictions were soil fertility and groundwater depth. Human driving factors controlled the land change in the HRLU areas, but natural restriction factors dominated in the FLU areas. In the mean time, intensification of LUCC in the region had some spatiotemporal implications with a fluctuation of impact factors.     

A contrast of two typical LUCC processes and their driving forces in oases of arid areas: A case study of Sangong River Watershed at the northern foot of Tianshan Mountains

Aerial photographs taken in 1978 and 1987, Landsat TM images in 1998 as well as soil, hydrology and socio-economic data for the oases in Sangong River Watershed were processed by Remote Sensing (RS) and Geographic Information System (GIS). There are two typical agricultural land uses in oases,Farm-based Land Use with large-scale intensified agricultural activities (FLU) and Household Responsibility-based Land Use with small-scale activities (HRLU). The Index Model of Land Use/Land Cover Change (LUCC), Weighted Index Sum (WIS) and logistic stepwise regression model were established to contrast the two typical LUCC processes and their driving forces. The land use patterns were dominated by cropland and grassland for the entire region, and cropland, residential and industrial land were increasing stably. In the HRLU areas, woodland and grassland declined dramatically, but in the FLU areas, grassland decreased only by 12.0%, whereas woodland increased by 13.7%. LUCC was stronger in the earlier stage (1978-1987) than in the later stage (1987-1998) for the entire region. LUCC was more intense in the HRLU areas than in the FLU areas during the entire period (1978-1998). Policy was a key factor in the land use change, and water resources were a precondition in land use. Under the control of policy and water resources,the main human driving factors included population and economy, and the main natural restrictions were soil fertility and groundwater depth. Human driving factors controlled the land change in the HRLU areas, but natural restriction factors dominated in the FLU areas. In the mean time,intensification of LUCC in the region had some spatiotemporal implications with a fluctuation of impact factors.