ALBERT

Beschreibung: In this work 10 algorithms for estimating downwelling longwave atmospheric radiation (L↓) and 1 for upwelling longwave radiation (L↑) are integrated into the JGrass-NewAge modelling system. The algorithms are tested against energy flux measurements available for 24 sites in North America to assess their reliability. These new JGrass-NewAge model components are used (i) to evaluate the performances of simplified models (SMs) of L↓, as presented in literature formulations, and (ii) to determine by automatic calibration the site-specific parameter sets for L↓ in SMs. For locations where calibration is not possible because of a lack of measured data, we perform a multiple regression using on-site variables, i.e. mean annual air temperature, relative humidity, precipitation, and altitude. The regressions are verified through a leave-one-out cross validation, which also gathers information about the possible errors of estimation. Most of the SMs, when executed with parameters derived from the multiple regressions, give enhanced performances compared to the corresponding literature formulation. A sensitivity analysis is carried out for each SM to understand how small variations of a given parameter influence SM performance. Regarding the L↓ simulations, the Brunt (1932) and Idso (1981) SMs, in their literature formulations, provide the best performances in many of the sites. The site-specific parameter calibration improves SM performances compared to their literature formulations. Specifically, the root mean square error (RMSE) is almost halved and the Kling–Gupta efficiency is improved at all sites. Also in this case, Brunt (1932) and Idso (1981) SMs provided the best performances. The L↑ SM is tested by using three different temperatures (surface soil temperature, air temperature at 2 m elevation, and soil temperature at 4 cm depth) and model performances are then assessed. Results show that the best performances are achieved using the surface soil temperature and the air temperature.

Beschreibung: Rainfall-induced shallow landslides can lead to loss of life and significant damage to private and public properties, transportation systems, etc. Predicting locations that might be susceptible to shallow landslides is a complex task and involves many disciplines: hydrology, geotechnical science, geology, hydrogeology, geomorphology, and statistics. Two main approaches are commonly used: statistical or physically based models. Reliable model applications involve automatic parameter calibration, objective quantification of the quality of susceptibility maps, and model sensitivity analyses. This paper presents a methodology to systemically and objectively calibrate, verify, and compare different models and model performance indicators in order to identify and select the models whose behavior is the most reliable for particular case studies.The procedure was implemented in a package of models for landslide susceptibility analysis and integrated in the NewAge-JGrass hydrological model. The package includes three simplified physically based models for landslide susceptibility analysis (M1, M2, and M3) and a component for model verification. It computes eight goodness-of-fit indices by comparing pixel-by-pixel model results and measurement data. The integration of the package in NewAge-JGrass uses other components, such as geographic information system tools, to manage input–output processes, and automatic calibration algorithms to estimate model parameters. The system was applied for a case study in Calabria (Italy) along the Salerno–Reggio Calabria highway, between Cosenza and Altilia. The area is extensively subject to rainfall-induced shallow landslides mainly because of its complex geology and climatology. The analysis was carried out considering all the combinations of the eight optimized indices and the three models. Parameter calibration, verification, and model performance assessment were performed by a comparison with a detailed landslide inventory map for the area. The results showed that the index distance to perfect classification in the receiver operating characteristic plane (D2PC) coupled with the model M3 is the best modeling solution for our test case.

Beschreibung: This work presents a software package for the interpolation of climatological variables, such as temperature and precipitation, using kriging techniques. The purposes of the paper are (1) to present a geostatistical software that is easy to use and easy to plug in to a hydrological model; (2) to provide a practical example of an accurately designed software from the perspective of reproducible research; and (3) to demonstrate the goodness of the results of the software and so have a reliable alternative to other, more traditional tools. A total of 11 types of theoretical semivariograms and four types of kriging were implemented and gathered into Object Modeling System-compliant components. The package provides real-time optimization for semivariogram and kriging parameters. The software was tested using a year's worth of hourly temperature readings and a rain storm event (11 h) recorded in 2008 and retrieved from 97 meteorological stations in the Isarco River basin, Italy. For both the variables, good interpolation results were obtained and then compared to the results from the R package gstat.

Beschreibung: This work presents a package for the interpolation of climatological variables, such as temperature and precipitation, using Kriging techniques. The purposes of the study are (1) to present a geostatistical software easy to use and easy to plug-in in a hydrological model, (2) to show a practical example of an accurately designed software in the perspective of reproducible research, (3) to show the goodness of the software applications, in order to have a reliable alternative to other traditionally used tools. Ten 5 types of theoretical semivariograms and four types of Kriging were implemented and gathered into ObjectModelling System compliant components. The package provides real time optimization for semivariogram and kriging parameters. The software was tested using temperature and rainfall data retrieved from 97 meteorological stations in the Isarco River basin, Italy. For both variables, good interpolation results were obtained and then compared to the results from the R package, gstat.

Beschreibung: Hydrological extremes, floods and droughts, cause significant economic damages and pose risks to lives worldwide. In an increasing hydro-climatic risk context as a result of climate change, this work identifies future hot-spots across Great Britain expected to be impacted by an increase in both floods and droughts. First, flood and drought hazards were defined and selected in a consistent and parallel approach with a threshold method. Then, a nation-wide systematic and robust statistical framework was developed to quantify changes in frequency, magnitude, and duration, and assess time of year for both droughts and floods, and the uncertainty associated with climate model projections. This approach was applied to a spatially-coherent statistical database of daily river flows (Future Flows Hydrology) across Great Britain to assess changes between the baseline (1961–1990) and the 2080s (2069–2098). The results showed that hydro-hazard hot-spots are likely to develop along the west coast of England and Wales and across northeast Scotland, mainly during the winter (floods) and autumn (droughts) seasons, with a higher increase in drought hazard in terms of magnitude and duration. These results suggest a need for adapting water management policies in light of climate change impact, not only on the magnitude, but also on the timing of hydro-hazard events, and future policy should account for both extremes together, alongside their potential future evolution. This novel, consistent, method is transferable to new hydro-climatic projection databases.

Beschreibung: The Upper Blue Nile basin is one of the most data-scarce regions in developing countries, and hence the hydrological information required for informed decision making in water resource management is limited. The hydrological complexity of the basin, tied with the lack of hydrometeorological data, means that most hydrological studies in the region are either restricted to small subbasins where there are relatively better hydrometeorological data available, or on the whole-basin scale but at very coarse timescales and spatial resolutions. In this study we develop a methodology that can improve the state of the art by using available, but sparse, hydrometeorological data and satellite products to obtain the estimates of all the components of the hydrological cycle (precipitation, evapotranspiration, discharge, and storage). To obtain the water-budget closure, we use the JGrass-NewAge system and various remote sensing products. The satellite product SM2R-CCI is used for obtaining the rainfall inputs, SAF EUMETSAT for cloud cover fraction for proper net radiation estimation, GLEAM for comparison with NewAge-estimated evapotranspiration, and GRACE gravimetry data for comparison of the total water storage amounts available in the whole basin. Results are obtained at daily time steps for the period 1994–2009 (16 years), and they can be used as a reference for any water resource development activities in the region. The overall water-budget analysis shows that precipitation of the basin is 1360 ± 230 mm per year. Evapotranspiration accounts for 56 % of the annual water budget, runoff is 33 %, storage varies from −10 to +17 % of the water budget.

Beschreibung: In an increasing hydro-climatic risk context as a result of climate change, this work aims to identify future hydro-hazard hot-spots as a result of climate change across Great Britain. First, flood and drought hazards were defined and selected in a consistent and parallel approach with a threshold method. Then, a nation-wide systematic and robust statistical framework was developed to quantify changes in frequency, magnitude, and duration, and assess time of year for both droughts and floods, and the uncertainty associated with climate model projections. This approach was applied to a spatially coherent statistical database of daily river flows (Future Flows Hydrology) across Great Britain to assess changes between the baseline (1961–1990) and the 2080s (2069–2098). The results showed that hydro-hazard hot-spots are likely to develop along the western coast of England and Wales and across north-eastern Scotland, mainly during the winter (floods) and autumn (droughts) seasons, with a higher increase in drought hazard in terms of magnitude and duration. These results suggest a need for adapting water management policies in light of climate change impact, not only on the magnitude, but also on the timing of hydro-hazard events, and future policy should account for both extremes together, alongside their potential future evolution.