Effects of Hydrogel Amendment to Different Soils on Plant Available Water and Survival of Trees under Drought Conditions

The effect of super absorbent polyacrylate (SAP) hydrogel amendment to different soil types on plant available water (PAW), evapotranspiration and survival of Eucalyptus grandis, Eucalyptus citriodora, Pinus caribaea, Araucaria cunninghamii, Melia volkensii, Grevillea robusta, Azadirachta indica, Maesopsis eminii and Terminalia superba was investigated. The seedlings were potted in 3 kg size polythene bags filled with sand, loam, silt loam, sandy loam and clay soils, amended at 0 (control), 0.2 and 0.4% w/w hydrogel. The tree seedlings were allowed to grow normally with routine uniform watering in a glass house set up for a period of eight weeks, after which they were subjected to drought conditions by not watering any further. The 0.4% hydrogel amendment significantly (p < 0.05) increased the PAW by a factor of about three in sand, two fold in silt loam and one fold in sandy loam, loam and clay soils compared to the control. Similarly, the addition of either 0.2 or 0.4% hydrogel to the five soil types resulted in prolonged tree survival compared to the controls. Araucaria cunninghammi survived longest at 153 days, while Maesopsis eminii survived least (95 days) in sand amended at 0.4% after subjection to desiccation. Evapotranspiration was reduced in eight of the nine tree species grown in sandy loam, loam, silt loam and clay soils amended at 0.4% hydrogel. It is probable that soil amendment with SAP decreased the hydraulic soil conductivity that might reduce plant transpiration and soil evaporation.     

Constraints to effective adoption of innovative livestock production technologies in the Rift Valley (Kenya)

We surveyed small-scale farmers in the Kenyan Rift Valley province (Narok and Nakuru districts) to describe constraints to, and changes in, livestock production and to assess the extent to which farmers have adopted new technologies promoted by extension services. In the arid areas of southern Narok, farmers' main constraints were drought and disease. Farmers in Nakuru district, situated in the fertile highlands of the Rift Valley, were also affected by disease but also lacked markets and capital. Although 83% of the farmers had regular contact with extension services that provided advice on new technologies and livestock production innovations, only about half of the respondents implemented the proposed changes. Many of those who did change (38%) improved pasture/nutrition/manure management and relatively few (16%) improved their animal breeding practices. Results of a multinomial logit model revealed that, apart from the significant differences between the two districts, the nature of the advice and the expected outcomes had the strongest influence on the probability of successfully implementing changes to livestock production. The results further suggest that adoption of new technologies is limited by lack of knowledge, inadequate support and a failure to target local needs and conditions and empower livestock keepers.     

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.     

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...     

GEV干旱指数及其在气象干旱预测和监测中的应用和检验

介绍了一种新的基于广义极值分布(Generalized Extreme Value,GEV)的干旱指数的构建过程及其原理。并利用1951—2010年中国地区160个气象台站的逐月降水资料,选择6个代表台站,检验1951—2010年60年间预测的干旱和实际干旱事件发生的吻合程度;利用2009—2010年资料检验GEV指数和实际发生的干旱事件在月尺度上的监测效果。结果表明,利用GEV方法定义的干旱指数能较好地监测干旱事件的发生和发展,与目前广泛使用的Ci指数监测结果较为一致。同时这种指数也能用于某一地区干旱事件的预测和干旱等级的划分。对干旱业务监测和预测有重要的参考意义。但该指数对站点疏密有一定的依赖性,站点稀疏的区域存在着一些误差。     

Monitoring global land surface drought based on a hybrid evapotranspiration model

The latent heat of evapotranspiration (ET) plays an important role in the assessment of drought severity as one sensitive indicator of land drought status. A simple and accurate method of estimating global ET for the monitoring of global land surface droughts from remote sensing data is essential. The objective of this research is to develop a hybrid ET model by introducing empirical coefficients based on a simple linear two-source land ET model, and to then use this model to calculate the Evaporative Drought Index (EDI) based on the actual estimated ET and the potential ET in order to characterize global surface drought conditions. This is done using the Global Energy and Water Cycle Experiment (GEWEX) Surface Radiation Budget (SRB) products, AVHRR-NDVI products from the Global Inventory Modeling and Mapping Studies (GIMMS) group, and National Centers for Environmental Prediction Reanalysis-2 (NCEP-2) datasets. We randomly divided 22 flux towers into two groups and performed a series of cross-validations using ground measurements collected from the corresponding flux towers. The validation results from the second group of flux towers using the data from the first group for calibration show that the daily bias varies from −6.72 W/m² to 12.95 W/m² and the average monthly bias is −1.73 W/m². Similarly, the validation results of the first group of flux towers using data from second group for calibration show that the daily bias varies from −12.91 W/m² to 10.26 W/m² and the average monthly bias is −3.59 W/m². To evaluate the reliability of the hybrid ET model on a global scale, we compared the estimated ET from the GEWEX, AVHRR-GIMMS-NDVI, and NECP-2 datasets with the latent heat flux from the Global Soil Wetness Project-2 (GSWP-2) datasets. We found both of them to be in good agreement, which further supports the validity of our model's global ET estimation. Significantly, the patterns of monthly EDI anomalies have a good spatial and temporal correlation with the Palmer Drought Severity Index (PDSI) anomalies from January 1984 to December 2002, which indicates that the method can be used to accurately monitor long-term global land surface drought.