Accelerated eutrophication, which is harmful and difficult to repair, is one of the most obvious and pervasive water pollution problems in the world. In the past three decades, the management of eutrophication has undergone a transformation from simple directed algal killing, reducing endogenous nutrient concentration to multiple technologies for the restoration of lake ecosystems. This article describes the development and revolution of three remediation methods in application, namely physical, chemical, and biological methods, and it outlines their possible improvements and future directions. Physical and chemical methods have obvious and quick effects to purify water in the short term and are more suitable for small-scale lakes. However, these two methods cannot fundamentally solve the eutrophic water phenomenon due to costly and incomplete removal results. Without a sound treatment system, the chemical method easily produces secondary pollution and residues and is usually used for emergency situations. The biological method is cost-effective and sustainable, but needs a long-term period. A combination of these three management techniques can be used to synthesize short-term and long-term management strategies that control current cyanobacterial blooms and restore the ecosystem. In addition, the development and application of new technologies, such as big data and machine learning, are promising approaches.

The northern high latitudes have warmed by about 0.8°C since the early 1970s, but not all areas have warmed uniformly [Hansen et al., 1999]. There is warming in most of Eurasia, but the warming rate in the United States is smaller than in most of the world, and a slight cooling is observed in the eastern United States over the past 50 years. These changes beg the question, can we detect the biotic response to temperature changes? Here we present results from analyses of a recently developed satellite‐sensed normalized difference vegetation index (NDVI) data set for the period July 1981 to December 1999: (1) About 61% of the total vegetated area between 40°N and 70°N in Eurasia shows a persistent increase in growing season NDVI over a broad contiguous swath of land from central Europe through Siberia to the Aldan plateau, where almost 58% (7.3×106 km2) is forests and woodlands; North America, in comparison, shows a fragmented pattern of change in smaller areas notable only in the forests of the southeast and grasslands of the upper Midwest, (2) A larger increase in growing season NDVI magnitude (12% versus 8%) and a longer active growing season (18 versus 12 days) brought about by an early spring and delayed autumn are observed in Eurasia relative to North America, (3) NDVI decreases are observed in parts of Alaska, boreal Canada, and northeastern Asia, possibly due to temperature‐induced drought as these regions experienced pronounced warming without a concurrent increase in rainfall [Barber et al., 2000]. We argue that these changes in NDVI reflect changes in biological activity. Statistical analyses indicate that there is a statistically meaningful relation between changes in NDVI and land surface temperature for vegetated areas between 40°N and 70°N. That is, the temporal changes and continental differences in NDVI are consistent with ground‐based measurements of temperature, an important determinant of biological activity. Together, these results suggest a photosynthetically vigorous Eurasia relative to North America during the past 2 decades, possibly driven by temperature and precipitation patterns. Our results are in broad agreement with a recent comparative analysis of 1980s and 1990s boreal and temperate forest inventory data [United Nations, 2000].

全球大幅度变暖,水循环加快,增强降水和蒸发.中国西北部从19世纪小冰期结束以来100a左右处于波动性变暖变干过程中.1987年起新疆以天山西部为主地区,出现了气候转向暖湿的强劲信号,降水量、冰川消融量和径流量连续多年增加,导致湖泊水位显著上升、洪水灾害猛烈增加、植被改善、沙尘暴减少.新疆其他地区以及祁连山中西段的降水和径流也有增加趋势.这样气候转型前景如何,是仅为年代际波动还是可发展为世纪性趋势,是只限于天山西部还是可能扩及整个西北以至华北.从引用现有区域气候模式预测,对径流变化模式预测和相似古气候情景的讨论,认为转向暖湿的趋势可以肯定,但目前尚不能确切预测转型扩大在时间上与空间上变化的速度和程度.

气候是植被变化的主要驱动因子， 研究全球增暖背景下中国区域植被变化及其对气候的响应对于国家开展重大生态恢复评估和未来植被保护政策制定具有重要意义。利用2000 -2016年MODIS植被指数（Normalized Difference Vegetation Index， NDVI）数据集， 运用统计分析方法， 从平均态、 线性趋势、 时间序列、 相关性等方面系统分析了2000年以来中国区域植被变化及其对气候变化的响应。结果表明： 中国区域NDVI在平均态上呈现从东南向西北递减的空间分布， 受降水生长季的影响， 东部地区植被指数明显较大； 我国大部分地区NDVI呈现增加的趋势， 其中湿润半湿润地区NDVI增长幅度为0.037·（10a）^-1， 而在干旱半干旱地区变化较小［0.013·（10a）^-1］。NDVI的变化与气候驱动因素的相关性存在一定的区域差异， 其中： NDVI与气温变化在东南沿海、 东北东部以及青藏高原北部等地区呈现出显著正相关， 而在青藏高原南部等地区呈现微弱的负相关； 除青藏高原、 塔里木盆地和东北北部等地区外， NDVI与降水量在全国大多数地区呈正相关。从全国平均来看， 温度和降水变化对NDVI的贡献分别为7.5%和9.1%， 其中温度对NDVI变化的贡献主要体现在湿润半湿润地区（9.3%）， 而降水的贡献则在干旱半干旱地区（12.2%）。植被变化对气候要素驱动的响应也呈现出明显的区域差异性， 在我国东南沿海、 云贵高原东部、 四川盆地等南方地区以及黄河中下游、 东北东部等部分地区， NDVI变化对气温的敏感性最强； 而在中国北方干旱半干旱大部分地区， NDVI变化则是对降水驱动具有很显著的响应特征。总体而言， 气温是驱动南方地区植被变化的主导因子， 而降水则调控着北方地区植被生长变化。

为了研究张掖市气候变化与植被覆盖关系，选择张掖市1982—2015年逐月NASA GIMMS归一化植被指数(NDVI)与气温、降水资料，运用统计学方法和Pearson相关系数法，分析了NDVI与气温、降水的年、季节变化趋势以及NDVI与气候因子气温、降水的相关性。结果表明：年、各季节NDVI呈增长趋势，夏季增长最快；年、各季节气温呈上升趋势，夏季上升最快；年降水量呈增长趋势，春、夏季降水量呈减少趋势，秋、冬季降水量呈增加趋势，秋季增多最大。年和春、夏、秋三季气温与年NDVI显著相关，相关系数通过了?=0.01的显著性水平检验，冬季气温与NDVI呈弱负相关。年、各季节降水量与NDVI相关性都不显著。植被生长对气候变化存在滞后效应，春、夏、秋三季气温与下一季NDVI的相关性显著，冬季相关性不显著。各季节降水量与下一季NDVI相关性不显著。

植被覆盖度是衡量地表植被长势和评价区域生态系统健康程度的重要指标，研究石羊河流域植被覆盖度的时空变化，对研究内陆干旱地区陆地生态系统环境变化具有重要意义。利用EOS/MODIS卫星数据，借鉴景观生态空间分布格局分析方法，从植被覆盖度面积变化和类型转换趋势方面分析2000—2014年石羊河流域植被的空间分布变化与格局演变。结果表明，2000—2014年石羊河流域内以低覆盖植被为主，其中极低覆盖植被年际波动最大，中高覆盖植被年际波动最小。在2001年、2004年、2009年和2013年前后，石羊河流域出现了4次植被生态退化过程。4种土地生态类型的植被覆盖度在年际变化中均呈增加趋势，其中耕地植被生态恢复明显，未利用土地生态恢复比较缓慢。15年石羊河流域内生态向恢复的方向发展。前期与后期的各植被覆盖等级的面积转移途径与幅度基本相似，后期的生态变化程度比前期更加剧烈。植被覆盖变化多集中在人类活动较多的区域。植被生态变化以稳定和轻微恢复为主。各土地生态类型中，耕地植被覆盖度空间变化最大。水资源的空间分布和利用不均是导致植被覆盖变化的空间分布不均的主要因素，中游平原区生态恢复较好，下游民勤绿洲在2010年后的生态退化明显。

地表植被与大气的相互作用过程是地球科学领域的研究重点和热点。本文基于SPOT VGT-NDVI数据和气象站点的气温和降水资料,采用时滞相关分析法,研究了1998年-2011年我国华东及其周边地区四季NDVI对气温和降水的时空响应特征。结果表明,在整个研究区,气温对NDVI的影响大于降水,NDVI与气温在夏季和秋季相关性较高,与降水在秋季和春季相关性较高,冬季NDVI与气温和降水相关性都最低。NDVI对气温响应的滞后期在春季和秋季较短,对降水响应的滞后期在冬季较短,夏季NDVI对气温和降水响应的滞后期都较长。在冬季、春季和秋季,NDVI对气温和降水最大相关系数的空间分布在研究区的南北部差异不明显,在夏季则具有较明显的南北差异。NDVI对气温变化响应的滞后期在春季、夏季和秋季具有较明显的南北差异,对降水变化响应的滞后期除在夏季具有一定的南北差异外,在其他季节空间分布规律性不显著。