Monthly soil erosion monitoring based on remotely sensed biophysical parameters: a case study in Strymonas river basin towards a functional pan-European service

Abstract

Currently, many soil erosion studies at local, regional, national or continental scale use models based on the USLE-family approaches. Applications of these models pay little attention to seasonal changes, despite evidence in the literature which suggests that erosion risk may change rapidly according to intra-annual rainfall figures and vegetation phenology. This paper emphasises the aspect of seasonality in soil erosion mapping by using month-step rainfall erosivity data and biophysical time series data derived from remote-sensing. The latter, together with other existing pan-European geo-databases sets the basis for a functional pan-European service for soil erosion monitoring at a scale of 1:500,000. This potential service has led to the establishment of a new modelling approach (called the G2 model) based on the inheritance of USLE-family models. The G2 model proposes innovative techniques for the estimation of vegetation and protection factors. The model has been applied in a 14,500 km² study area in SE Europe covering a major part of the basin of the cross-border river, Strymonas. Model results were verified with erosion and sedimentation figures from previous research. The study confirmed that monthly erosion mapping would identify the critical months and would allow erosion figures to be linked to specific land uses.     

Uncertainty analysis of soil erosion modelling using different resolution of open-source DEMs

The Digital Elevation Model (DEM) is one of the important parameters of soil erosion assessment and notable uncertainties are found in using different resolutions of the DEM. Revised Universal Soil Loss Equation model has been applied to analyze the effect of open-source DEMs with different resolution and accuracy on the uncertainties of soil erosion modelling in a part of the Narmada river basin in Madhya Pradesh in central India. Selected open-source DEMs are GTOPO30 (1 km), SRTM (30 and 90 m), CARTOSAT (30 m) and ASTER (30 m), used for estimating erosion rate. Results with better accuracy are achieved with the high-resolution DEMs (30 m) with higher vertical accuracy than the coarse resolution DEMs with lower accuracy. This study has presented potential uncertainties introduced by the open-source DEMs in soil erosion modelling for better understanding of appropriate selection and acceptable errors for researchers.     

Estimation of hourly and daily evapotranspiration and soil moisture using downscaled LST over various urban surfaces

Surface moisture is important to link land surface temperature (LST) to people’s thermal comfort. In urban areas, the surface roughness from buildings and urban trees impacts wind speed, and consequently surface moisture. To find the role of surface roughness in surface moisture estimation, we developed methods to estimate daily and hourly evapotranspiration (ET) and soil moisture, based on a case study of Indianapolis, Indiana, USA. In order to capture the spatial and temporal variations of LST, hourly and daily LST was produced by downscaling techniques. Given the heterogeneity in urban areas, fractions of vegetation, soil, and impervious surfaces were calculated. To describe the urban morphology, surface roughness parameters were calculated from digital elevation model (DEM), digital surface model (DSM), and Terrestrial Light Detection and Ranging (LiDAR). Two source energy balance (TSEB) model was employed to generate ET, and the temperature vegetation index (TVX) method was used to calculate soil moisture. Stable hourly soil moisture fluctuated from 15% to 20%, and daily soil moisture increased due to precipitation and decreased due to seasonal temperature change. ET over soil, vegetation, and impervious surface in the urban areas yielded different patterns in response to precipitation. The surface roughness from high-rise has bigger influence on ET in central urban areas.     

基于GIS的县域土壤重金属生态风险评价

为研究经济快速发展区农田土壤中重金属的含量及污染状况,本文以浙江省慈溪市为研究对象,研究土壤中铜、汞、镉、铅、砷、铬、锌七种重金属含量特征,并采用潜在生态危害指数法对其进行评价,并绘制生态风险危害指数分级图。结果表明:土壤中除汞元素含量较高外,其他各元素含量仅稍高于当地土壤背景值。七种元素的单因子污染指数Cfi值均属于中等的污染参数,综合污染指数Cd上限值已处于高污染指数的范围,但平均值为属于中等污染水平。从潜在生态风险评价结果来看,七种元素的单项潜在生态风险参数Eri的值也只有汞达到了强生态危害,七种元素综合潜在生态危害指数RI刚刚达到中等生态危害水平,说明该区农田土壤尚处于较低的生态风险状态。生态危害指数插值结果表明,慈溪市重金属元素的高风险区分布在中南部人类活动较为活跃、城乡工业较发达的区域,在今后的土地利用中,应高度重视人类活动对土壤重金属污染的影响。     

智能全站仪在大型压力容器焊接变形监测中的应用

在大型压力容器的部件焊接过程中,由于预热、焊接等工艺流程会导致各部件产生变形,从而引起部件之间的位置关系产生变化。为保证压力容器成品满足设计要求,必须在制造过程中实施变形监测,依据变形数据适当调整焊接工艺流程,控制变形量。提出采用智能全站仪配以自动变形监测软件对大型压力容器焊接变形进行实时监测,并应用于生产实践中,监测结果表明该方法自动化程度高、实时性好,能同时给出位置和姿态变形数据。     

用ERS风散射计数据估算土壤水分方法的研究

欧空局ERS1/2卫星上的风散射计(WSC),分辨率是50km,4天内能覆盖全球超过80%的范围,并可在多角度下对地物目标进行观测。本文研究利用该散射计数据估算土壤水分的方法。首先,利用基于ERS散射计数据建立的全球C波段雷达后向散射系数数据库,根据传统的几何光学模型(GOM),反演得到与土壤含水量密切相关的法线方向Fresnel反射率,并与两个采样点(安多和那曲)上的实测降雨量及土壤水分相对比,证明了ERS散射计数据与土壤水分的高相关性;第二步,以水云模型为基础,结合AIEM模型,发展了一种简化模型来估算土壤水分绝对值,分别利用气象站实测点数据和同时期的Basist湿度指数(BWI)进行验证,表明反演结果能较好反映土壤水分的空间分布状况。     

共享存储中一种基于流量均衡的队列门限控制算法

提出了使用流量压力均衡作为设置每队列门限的主要依据,让系统的各个端口分担大体相同的流量压力。各个端口的门限控制使得公共存储空间既能够保持在平均意义下的平衡,又能实现突发时段的调剂。模拟结果显示,该算法的效率大大高于传统的动态门限算法。     

MODIS数据在广西生态环境监测及评价中的应用方法

利用MODIS数据广西遥感影像,用监督分类法做出了地物覆盖分类图,用主成分分析法做出了土壤侵蚀强度图和生态环境质量综合评价指数图。     

基于多源遥感数据的生态系统保育土壤价值评估——以河北省北部四地市为例

为了给合理地利用土地资源和科学地进行环境保护提供依据,利用多源遥感影像数据,结合气象数据、土壤属性数据与DEM,对河北北部地区生态系统的土壤保持量进行了评估,并参考《森林生态系统服务功能评估规范》,对生态系统保护土壤肥力的价值与固土价值进行了评估.结果表明,研究区2008年度生态系统的土壤保持总量达到7.55亿t,对应...     

柔性版印刷网点扩大与变形的研究与控制

从柔版印刷传递过程入手,分析印刷压力、加网线数、印版硬度等影响网点增大的几个主要因素,通过实验得到它们之间的影响曲线,最终提出控制柔版网点增大的控制方法,有利于实际生产中提高柔性版印刷品的质量。