青藏高原植被覆盖变化及其与气候变化的关系

近几十年来,全球气候变化对青藏高原植被覆盖产生了重要影响。基于青藏高原1981—2005年遥感影像及同期气象数据,结合生态学模型,分析了青藏高原植被覆盖度变化趋势及其与气候变化的关系。结果显示,25 a间,青藏高原温度升高、降水量增加,植被覆盖度呈"整体升高、局部退化"趋势;地表植被改善区主要位于植被低覆盖区,退化区主要位于高覆盖区;从不同植被类型看,除针叶林、阔叶林受采伐影响覆盖度下降外,其他植被覆盖度均不同程度的上升;植被覆盖度变化与同期降水量变化、温度变化均呈正相关,且具有明显的区域差异。     

A review of continental scale hydrological models and their suitability for drought forecasting in (sub-Saharan) Africa

The aim of this review is to provide a basis for selecting a suitable hydrological model, or combination of models, for hydrological drought forecasting in Africa at different temporal and spatial scales; for example short and medium range (1–10 days or monthly) forecasts at medium to large river basin scales or seasonal forecasts at the Pan-African scale. Several global hydrological models are currently available with different levels of complexity and data requirements. However, most of these models are likely to fail to properly represent the water balance components that are particularly relevant in arid and semi-arid basins in sub-Saharan Africa. This review critically looks at weaknesses and strengths in the representation of different hydrological processes and fluxes of each model. The major criteria used for assessing the suitability of the models are (1) the representation of the processes that are most relevant for simulating drought conditions, such as interception, evaporation, surface water-groundwater interactions in wetland areas and flood plains and soil moisture dynamics; (2) the capability of the model to be downscaled from a continental scale to a large river basin scale model; and (3) the applicability of the model to be used operationally for drought early warning, given the data availability of the region. This review provides a framework for selecting models for hydrological drought forecasting, conditional on spatial scale, data availability and end-user forecast requirements. Among 16 well known hydrological and land surface models selected for this review, PCR-GLOBWB, GWAVA, HTESSEL, LISFLOOD and SWAT show higher potential and suitability for hydrological drought forecasting in Africa based on the criteria used in this evaluation.     

On the identification of ENSO-induced rainfall and runoff variability: a comparison of methods and indices

Abstract

It is known that the El Niño Southern Oscillation (ENSO) phenomenon induces marked climate variability across many parts of the world. However, in seeking useful relationships between ENSO and climate, several indices are available. In addition to the choice of index, previous studies assessing ENSO effects have employed a range of different methods to classify periods as El Niño, La Niña or Neutral. It is therefore clear that significant subjectivity exists in the adoption of ENSO classification schemes. In this study, several ENSO classification methods are applied to a range of ENSO indices. Each method-index combination is investigated to determine which provides the strongest relationship with rainfall and runoff in the Williams River catchment, New South Wales, Australia. The results demonstrate substantial differences between the methods and indices. The Multivariate ENSO Index (or MEI) is found to provide the best classification irrespective of method. The potential for forecasting ENSO-related effects on rainfall, runoff and river abstractions is then investigated. A “rise rule” to account for dynamic ENSO trends is also assessed. Strong relationships were found to exist with runoff (rainfall) up to nine (eight) months in advance of the Summer/autumn period. Implications for improved forecasting of potential river abstractions are apparent.     

Combined analysis of precipitation and water deficit for drought hazard assessment

Abstract

The combined analysis of precipitation and water scarcity was done with the use of the Standardized Precipitation Index (SPI) and the Standardized Runoff Index (SRI), developed as a monthly, two-variable SPI-SRI indicator to identify different classes of hydrometeorological conditions. Stochastic analysis of a long-term time series (1966–2005) of monthly SPI-SRI indicator values was performed using a first-order Markov chain model. This provided characteristics of regional features of drought formation, evolution and persistence, as well as tools for statistical long-term drought hazard prediction. The study was carried out on two subbasins of the Odra River (Poland) of different orography and land use: the mountainous Nysa K?odzka basin and the lowland, agricultural Prosna basin. Classification obtained with the SPI-SRI indicator was compared with the output from the NIZOWKA model that provided identification of hydrological drought events including drought duration and deficit volume. Severe and long-duration droughts corresponded to SPI-SRI Class 3 (dry meteorological and dry hydrological), while severe but short-term droughts (lasting less than 30 days) corresponded to SPI-SRI Class 4 (wet meteorological and dry hydrological). The results confirm that, in Poland, meteorologically dry conditions often shift to hydrologically dry conditions within the same month, droughts rarely last longer than 2 months and two separate drought events can be observed within the same year.     

Landslide susceptibility assessment using three bivariate models considering the new topo-hydrological factor: HAND

Abstract

The main objective of this study is to assess the relative contribution of the state-of-the-art topo-hydrological factor, known as height above the nearest drainage (HAND), to landslide susceptibility modellling using three novel statistical models: weights-of-evidence (WofE), index of entropy and certainty factor. In total, 12 landslide conditioning factors that affect the landslide incidence were used as input to the models in the Ziarat Watershed, Golestan Province, Iran. Landslide inventory was randomly divided into a ratio of 70:30 for training and validating the results of the models. The optimum combination of conditioning factors was identified using the principal components analysis (PCA) method. The results demonstrated that HAND is the defining factor among hydrological and topographical factors in the study area. Additionally, the WofE model had the highest prediction capability (AUPRC = 74.31%). Therefore, HAND was found to be a promising factor for landslide susceptibility mapping.     

升温1.5℃和2.0℃情景下中亚地区干旱耕地暴露度研究

基于CMIP5中的5个全球气候模式统计降尺度的降水、最高和最低气温等数据,利用标准降水蒸发指数（SPEI）和强度-面积-持续时间（IAD）方法识别全球升温1.5℃与2.0℃情景下中亚地区干旱事件,结合30 m分辨率土地利用数据,探讨中亚干旱事件的演变及耕地暴露度变化。结果表明：相比基准期（1986—2005年),中亚地区的降水和潜在蒸发量均有所增加;全球升温1.5℃与2.0℃情景下,中亚地区的干旱事件频次、强度和面积均将增加,其中重旱和极旱事件的频次和影响面积大幅上升,而中旱事件的频次和影响面积持续下降;1986—2005年中亚地区年均干旱耕地暴露度约11.5万km2,全球升温1.5℃和2.0℃情景下,干旱耕地暴露度将分别上升到17.9万km2和28.6万km2,且暴露在极旱下的耕地面积增加最明显。全球升温1.5℃与2.0℃情景下,增加的干旱事件将会严重威胁当地农业生产和粮食安全,中亚地区需对干旱事件采取长期的减缓与适应措施。     

新疆天山山区干旱灾害综合风险评估与区划

以自然灾害风险四因子理论为基础,综合考虑研究区自然及社会经济情况,建立适合天山山区干旱灾害风险概念框架和指标体系,结合GIS技术进行了该地区干旱灾害风险评估与区划。结果表明：致灾因子危险性较高的区域是伊犁河谷及天山北坡一带,东疆地区和南疆西部危险性较低;承灾体脆弱性较高的区域为伊犁河谷和博州地区,吐鲁番、哈密及克州属于低脆弱区;孕灾环境敏感性较高地区主要分布在天山北坡的精河至吐鲁番一线、阿克苏地区西部、巴州北部等地,伊犁河谷、巴州北部、哈密市北部、南疆西部山区属低敏感区;防灾减灾能力整体表现为中东部高于西部区域;新疆天山山区干旱综合风险整体呈现出中部高、两端低的趋势,即中部的天山南北两侧干旱风险高于南疆西部和东疆地区。构建的评估模型总体反映了研究区旱灾综合风险水平,可为新疆天山草原灾害风险管理、应对气候变化、抗旱减灾行动提供参考。     

Identifying future climate change and drought detection using CanESM2 in the upper Siem Reap River,Cambodia

Cambodia is one of the most vulnerable countries to climate change impacts such as floods and droughts. Study of future climate change and drought conditions in the upper Siem Reap River catchment is vital because this river plays a crucial role in maintaining the Angkor Temple Complex and livelihood of the local population since 12th century. The resolution of climate data from Global Circulation Models (GCM) is too coarse to employ effectively at the watershed scale, and therefore downscaling of the dataset is required. Artificial neural network (ANN) and Statistical Downscaling Model (SDSM) models were applied in this study to downscale precipitation and temperatures from three Representative Concentration Pathways (RCP 2.6, RCP 4.5 and RCP 8.5 scenarios) from Global Climate Model data of the Canadian Earth System Model (CanESM2) on a daily and monthly basis. The Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were adopted to develop criteria for dry and wet conditions in the catchment. Trend detection of climate parameters and drought indices were assessed using the Mann-Kendall test. It was observed that the ANN and SDSM models performed well in downscaling monthly precipitation and temperature, as well as daily temperature, but not daily precipitation. Every scenario indicated that there would be significant warming and decreasing precipitation which contribute to mild drought. The results of this study provide valuable information for decision makers since climate change may potentially impact future water supply of the Angkor Temple Complex (a World Heritage Site).     

The Modification of Palmer Drought Severity Index in the Research of Drought in Huaihe Area

Palmer指数是目前研究区域干旱时应用最广泛的指数之一,但由于其空间适用性比较强,所以在应用已修正的Palmer指数描述淮河流域干旱等级和持续时间时和实际情况有较大差异,因此有必要做进一步订正。利用淮河流域开封、信阳、巢湖站1961—2009年逐日降水和气温等常规观测资料,根据1965年Palmer指数原理,在2004、2006年几次修正的基础上对Palmer指数进行修正。淮河流域和美国Kansas、Iowa周边区域均属亚热带季风气候,但在用Palmer指数研究2个区域的旱涝时,其前期旱涝对后期的影响程度存在一定的差异,在淮河流域前期旱涝的影响要小些,因此,在修正Palmer指数过程中加入一个修正系数,用以改善其敏感度。结果表明,修正后的Palmer指数在反映淮河流域的干旱强度和持续时间等方面都得到了很好的改进,可以用于淮河流域干旱的监测和预警。     

Palmer干旱指数在淮河流域的修正及应用

Palmer指数是目前研究区域干旱时应用最广泛的指数之一,但由于其空间适用性比较强,所以在应用已修正的Palmer指数描述淮河流域干旱等级和持续时间时和实际情况有较大差异,因此有必要做进一步订正。利用淮河流域开封、信阳、巢湖站1961—2009年逐日降水和气温等常规观测资料,根据1965年Palmer指数原理,在200...