Field measurements in river embankments: validation and management with spatial database and webGIS

This study focuses on the development of a system with a spatial database and a webGIS able to store, validate and display the data to assist the decision makers in managing early warning systems for river embankment failure. In order to obtain precise results, it is essential to have a tool with ability of managing a large number of data for checking their reliability and for locating them in the space. In this paper, special emphasis was given in the development of procedures to assess the reliability of the measures. For this purpose, the database includes all the information needed to describe the instrument performance, such as the sand pack size and casing diameter of open-standpipe piezometers for evaluating their time lag, and the calibration curves of transducers with the possibility of their updating. The position of the non-functioning instruments is identified through the analysis of the electrical signal and spatial displays, while the analyses of the redundancy and coherence of measures is used for detecting doubtful data. Database and webGIS were applied to the monitoring data of an embankment of the Adige River in Northern Italy. The database and webGIS system has proved to be a suitable and effective tool for the management and validation of real-time data and periodical field measurements.     

The investment climate for climate investment: Joint Implementation in transition countries

Transition countries are expected to become important players in the emerging market for greenhouse gas emission reductions, as they can cut emissions at a relatively low cost. However, the attractiveness of the region as a supplier of emission reductions will not only depend on its cost advantage. It will also depend on the business climate offered to carbon investors—factors like a well-functioning legal and regulatory system, economic and political stability and the capacity to process emission reduction projects efficiently. This paper looks at the carbon investment climate in the transition countries eligible for Joint Implementation (JI)—Russia, Ukraine, Croatia and the EU accession countries. It concludes that JI investors will face a clear trade-off between the scope for cheap JI on the one hand, and the quality of the business environment and JI institutions on the other. The countries with the highest potential for cheap emission reductions also tend to be the countries with the most difficult business climate and the least institutional capacity for JI. The most attractive JI locations may be median countries with a reasonable JI potential and an acceptable business climate, such as Bulgaria, Romania and the Slovak Republic.     

Effects of atmospheric river landfalls on the cold season precipitation in California

Effects of atmospheric river (AR) landfalls in the California coast on the cold-season precipitation in California are examined for the cold seasons of 10 water years (WYs) 2001–2010 using observed data and regional modeling in conjunction with AR-landfall inventory based on visual inspections of precipitable water vapor (PWV) from remote sensing and reanalysis. The PWV in the SSM/I and SSMIS retrievals and the ERA-Interim reanalysis shows 95 AR-landfall days in the California coast that are almost evenly split between the northern and southern coasts across 37.5N. The CPC/NCEP gridded daily precipitation analysis shows that 10–30% of the cold-season precipitation totals in California have occurred during these AR landfalls. The analysis also reveals that the percentage of precipitation and the precipitation intensity during AR landfalls in California are characterized by strong north-to-south gradient. This north–south contrast in the AR precipitation is reversed for the non-AR precipitation in the coastal range. The frequency of AR landfalls and the cold-season precipitation totals in the Sierra Nevada region are only marginally correlated. Instead, AR landfalls are closely related with the occurrence of heavy precipitation events. The freezing-level altitudes are systematically higher for AR wet days than non-AR wet days indicating warmer low-troposphere during AR storms. Cold season simulations for the 10 WYs 2001–2010 show that the Weather Research and Forecast (WRF) model can reasonably simulate important features in both the seasonal and AR precipitation totals. The daily pattern correlation coefficients between the simulated and ERA-Interim upper-air fields exceed 0.9 for most of the period. This suggests that the simulated temporal variations in the atmospheric circulation agree reasonably with the reanalysis over seasonal time scales, characteristics critical for reliable simulations of regional scale hydrologic cycle. The simulated seasonal and AR precipitation totals also agree reasonably with the CPC/NCEP precipitation analysis. The most notable model errors include the overestimation (underestimation) of the season-total and AR precipitation in the northern (southern) California region. The differences in the freezing-level altitudes during the AR- and non-AR wet days in the simulation agree with those from the ERA-Interim reanalysis. The freezing level altitudes are systematically overestimated in the simulations, suggesting warm biases in the low troposphere. Overall, WRF appears to perform reasonably in simulating the key features in the cold season precipitation related with AR landfalls, an important capability for assessing the impact of global climate variations and change on future hydrology in California.     

Regional Stress Fields under Tibet from 3D Global Flow Simulation

Tibetan area is the most active continental collision zone on earth.Several major earth-quakes occurred around the boundaries of Tibetan plateau and caused massive damages and casualties.The dynamics of this area is not well understood due to the complex structure of Tibet and its sur-rounding area.In this study,a 3D global flow simulation with only viscous rheology is applied to studying the stress distribution in this area,and the interaction between Tibet and its surrounding areas is investigated.Finally...     

A cloud mask methodology for high resolution remote sensing data combining information from high and medium resolution optical sensors

This study presents a novel cloud masking approach for high resolution remote sensing images in the context of land cover mapping. As an advantage to traditional methods, the approach does not rely on thermal bands and it is applicable to images from most high resolution earth observation remote sensing sensors. The methodology couples pixel-based seed identification and object-based region growing. The seed identification stage relies on pixel value comparison between high resolution images and cloud free composites at lower spatial resolution from almost simultaneously acquired dates. The methodology was tested taking SPOT4-HRVIR, SPOT5-HRG and IRS-LISS III as high resolution images and cloud free MODIS composites as reference images. The selected scenes included a wide range of cloud types and surface features. The resulting cloud masks were evaluated through visual comparison. They were also compared with ad-hoc independently generated cloud masks and with the automatic cloud cover assessment algorithm (ACCA). In general the results showed an agreement in detected clouds higher than 95% for clouds larger than 50 ha. The approach produced consistent results identifying and mapping clouds of different type and size over various land surfaces including natural vegetation, agriculture land, built-up areas, water bodies and snow.