Effect of riparian land use on environmental conditions and riparian vegetation in the east African highland streams

Agricultural land use is expanding and at an accelerated rate. In Ethiopia, most of this expansion has occurred in highland areas and involve deforestation of natural riparian vegetation. However, the impacts on the water quality of streams are poorly understood, especially with regard to the influence of land use patterns on highland streams. In this study, we investigated the effects of land use modifications on the water quality and riparian condition of highland streams and examined whether the preservation of riparian vegetation would help mitigate the negative impacts of intensive agriculture practices. Our results show significant differences in the water quality of streams with different land use. Several parameters commonly used to indicate water quality, such as the concentrations of orthophosphate, turbidity, and suspended solids were significantly higher in the agricultural streams than in the forest stream. The preservation of riparian vegetation in the surrounding highland streams was associated with overall better riparian condition, floristic quality, and water quality such as lower turbidity, total suspended solids, orthophosphate, and higher dissolved oxygen. We conclude, that increases in vegetation cover improved riparian condition and water quality relative to other non-vegetated areas. Therefore, we strongly recommend the preservation of riparian vegetation in tropical highland streams surrounded by intensive agriculture. More studies on the effects of best management practices in areas dominated by agriculture can greatly improve our capacity to prevent the degradation of water quality in tropical highland streams of Africa.     

软土动力特性动三轴试验研究

许多学者对软土在动力作用下的变形特性进行了大量的研究,并提出了相应的经验公式,但其经验公式参数较多且试验复杂,不易被一般工程技术人员掌握运用。本文采用天津滨海地区软土为研究对象,进行钻探取样、波速测试、室内静力学和动三轴试验,获取该地区软土的静、动力学参数,并利用相对简单的模型对残余应变和软化指数随振次的变化规律采用最小二乘法进行拟合,取得很好的效果。成果表明,利用简单的模型对软土的动力特性进行区域性研究是可行的。该成果可为今后软土动力特性和软土震陷计算方法研究提供参考和基础性资料。     

Characteristics and Analysis of the Seismic Damage from the MS7.0 Jiuzhaigou Earthquake in the Area between Songpan and Jiuzhaigou

This paper expounds the features of the buildings and analyzes the seismic disaster characteristics of the Jiuzhaigou M_S7. 0 earthquake in the area between Songpan and Jiuzhaigou. New buildings (especially the frame structure) had good anti-seismic performance,but brick-wood structures and brick-concrete structures sustained large amounts of damage in the earthquake. By computing the seismic damage index,we found that the seismic damage index of the frame structure was far less than that of civil structures and brick-wood structures. The seismic damage index of frame structures were all zero in the Ⅵ area,and increased rapidly with the increase of intensity,but the increasing range was reduced. We also discussed how to evaluate the intensity in areas where there was a lack of buildings or there was only one structure type,which can be referenced in future field work.     

Modelling soil moisture in a high‐latitude landscape using LiDAR and soil data

Soil moisture has a pronounced effect on earth surface processes. Global soil moisture is strongly driven by climate, whereas at finer scales, the role of non‐climatic drivers becomes more important. We provide insights into the significance of soil and land surface properties in landscape‐scale soil moisture variation by utilizing high‐resolution light detection and ranging (LiDAR) data and extensive field investigations. The data consist of 1200 study plots located in a high‐latitude landscape of mountain tundra in north‐western Finland. We measured the plots three times during growing season 2016 with a hand‐held time‐domain reflectometry sensor. To model soil moisture and its temporal variation, we used four statistical modelling methods: generalized linear models, generalized additive models, boosted regression trees, and random forests. The model fit of the soil moisture models were R² = 0.60 and root mean square error (RMSE) 8.04 VWC% on average, while the temporal variation models showed a lower fit of R² = 0.25 and RMSE 13.11 CV%. The predictive performances for the former were R² = 0.47 and RMSE 9.34 VWC%, and for the latter R² = 0.01 and RMSE 15.29 CV%. Results were similar across the modelling methods, demonstrating a consistent pattern. Soil moisture and its temporal variation showed strong heterogeneity over short distances; therefore, soil moisture modelling benefits from high‐resolution predictors, such as LiDAR based variables. In the soil moisture models, the strongest predictor was SAGA (System for Automated Geoscientific Analyses) wetness index (SWI), based on a 1 m² digital terrain model derived from LiDAR data, which outperformed soil predictors. Thus, our study supports the use of LiDAR based SWI in explaining fine‐scale soil moisture variation. In the temporal variation models, the strongest predictor was the field‐quantified organic layer depth variable. Our results show that spatial soil moisture predictions can be based on soil and land surface properties, yet the temporal models require further investigation. Copyright © 2017 John Wiley & Sons, Ltd.     

Extracting water-related features using reflectance data and principal component analysis of Landsat images

This study aimed to map water features using a Landsat image rather than traditional land cover. We involved the original bands, spectral indices and principal components (PCs) of a principal component analysis (PCA) as input data, and performed random forest (RF) and support vector machine (SVM) classification with water, saturated soil and non-water categories. The aim was to compare the efficiency of the results based on various input data. Original bands provided 93% overall accuracy (OA) and bands 4–5–7 were the most informative in this analysis. Except for MNDWI (modified normalized differenced water index, with 98% OA), the performance of all water indices was between 60 and 70% (OA). The PCA-based approach conducted on the original bands resulted in the most accurate identification of all classes (with only 1% error in the case of water bodies). We therefore show that both water bodies and saturated soils can be identified successfully using this approach.     

青海东南部农村民居结构特点及抗震能力分析

我国农村民居的抗震能力具有显著的地域特点。本文基于现场调研结果总结了青海东南部黄河流域农村民居的结构特点,并对其抗震能力进行了评估。庄廓院是调研区内的典型农村民居,本文对调研区内庄廓院的木构架房屋进行研究,提出庄廓土墙围护木构架房屋的震害等级分类标准,根据实际震害资料和类比的方法确定了当地土墙围护木构架结构的震害矩阵和震害指数与峰值加速度的关系曲线。与云南鲁甸农村的土木结构房屋比较,青海庄廓院民居具有更高的抗震能力;与未设防的砖混结构比较,这种土墙围护的木构架结构在高烈度区造成人员伤亡的风险更低。     

旅游活动对鼎湖山生物圈保护区植被的影响

以鼎湖山生物圈保护区为例,采用敏感水平、群落景观重要值、物种多样性信息指数、阴生种比例、伴人植物比例和旅游影响系数等指标,对旅游活动与植被环境的关系和景区管理水平进行了分析评价。研究表明:(1)旅游影响系数与植被环境质量评价指标之间、植被环境质量各项评价指标之间、旅游影响系数内部各因子之间均存在不同程度的相关性。敏感水平值越大,群落景观重要值、阴生种比例值越小,物种多样性信息指数、伴人植物比例、旅游影响系数值越大;旅游影响系数越大,敏感水平、物种多样性信息指数、伴人植物比例越大,群落景观重要值、阴生种比例越小;旅游影响系数与其各影响因子均呈正相关,即旅游影响系数越大,枯枝落叶层越薄、草本层盖度越小、幼苗量越小、折枝数量越多、垃圾量越大。研究结果与鼎湖山旅游发展的实践基本相符,客观上揭示了旅游活动对植被影响的规律和特点;(2)根据旅游影响系数分级标准,鼎湖山景区质量管理水平总体可定为中上水平,但个别地段存在环境隐患,有必要进一步提高管理水平。     

大气散射对采用归一化植被指数进行赤潮遥感监测的影响研究

1　引言近年来赤潮灾害在我国海域频繁发生,对沿海环境、经济和人民生产生活都造成一定的影响,因此对赤潮进行实时监测并业务化运行就显得尤其重要.赤潮遥感监测是目前常用手段之一,在实践中取得了一定的效果,但到目前为止还没有一种成熟的算法能用于业务化监测赤潮的发生.很多研究人员借鉴归一化植被指数(NDVI)阈值法、海表温度(SST)异常等来判断赤潮的发生,但归一化植被指数阈值法经常会出现误判或无法区分正常与异常水体的情况.该阈值范围由先验知识得到,没有定量的理论依据.归一化植被指数是陆地遥感中用以表征地表植物覆盖程度和健…     

近岸海水质量量化方法及分类评价

近岸海域是陆地、海洋和大气之间各种过程相互作用最活跃的界面[1],沿海100km以内区域聚积着约60%的世界人口[2],其环境质量强烈受人类活动影响.对近岸海域进行水质环境管理,应依据海水物理、化学和生物学性质对海水进行分类评价[3,4].