Review of recent advances in index flood estimation

International audienceIndex flood estimation for regional flood frequency analysis needs to be based on the information available. The most appropriate method depends on the specific application and its choice requires a problem-oriented analysis. This paper presents a simple theoretical framework to deal with index flood estimation for a specific river site. The methodological approaches available for the purpose are reviewed. For each, the information required is specified and the reliability of the estimate, particularly desirable in risk analysis and management, is discussed. Where flood observations are lacking, indirect estimation must be undertaken using scenarios including those commonly met in hydrological practice; generally, these depend on the amount and type of information available. For each scenario, the methodologies are outlined, in order of the expected degree of complexity. After a guided analysis, an investigator can adopt the method providing the best tradeoff between effort in collecting and handling data and the resultant reliability which can be expected. Keywords: direct and indirect methods, index flood estimation, reliability, scenarios

Regional evaluation of three day snow depth for avalanche hazard mapping in Switzerland

The distribution of the maximum annual three day snow fall depth <i>H<sub>72</sub></i>, used for avalanche hazard mapping according to the Swiss procedure (<i>Sp</i>), is investigated for a network of 124 stations in the Alpine part of Switzerland, using a data set dating back to 1931. Stationarity in time is investigated, showing in practice no significant trend for the considered period. Building on previous studies about climatology of Switzerland and using an iterative approach based on statistical tests for regional homogeneity and scaling of <i>H<sub>72</sub></i> with altitude, seven homogenous regions are identified. A regional approach based on the index value is then developed to estimate the <i>T</i>-years return period quantiles of <i>H<sub>72</sub></i> at each single site <i>i</i>, <i>H<sub>72i</sub>(T)</i>. The index value is the single site sample average μ<sub><i>H<sub>72i</sub></i></sub>. The dimensionless values of <i>H<sup>*</sup><sub>72i</sub>=H<sub>72i</sub> / μ<sub>H<sub>72i</sub></sub></i> are grouped in one sample for each region and their frequency of occurrence is accommodated by a General Extreme Value, GEV, probability distribution, including Gumbel. The proposed distributions, valid in each site of the homogeneous regions, can be used to assess the <i>T</i>-years return period quantiles of <i>H<sup>*</sup><sub>72i</sub></i>. It is shown that the value of <i>H<sub>72i</sub>(T)</i> estimated with the regional approach is more accurate than that calculated by single site distribution fitting, particularly for high return periods. A sampling strategy based on accuracy is also suggested to estimate the single site index value, i.e. the sample average μ<sub><i>H<sub>72i</sub></i></sub>, critical for the evaluation of the distribution of <i>H<sub>72i</sub></i>. The proposed regional approach is valuable because it gives more accurate snow depth input to dynamics models than the present procedure based on single site analysis, so decreasing uncertainty in hazard mapping procedure

Prediction of future hydrological regimes in poorly gauged high altitude basins: the case study of the upper Indus, Pakistan

In the mountain regions of the Hindu Kush, Karakoram and Himalaya (HKH) the "third polar ice cap" of our planet, glaciers play the role of "water towers" by providing significant amount of melt water, especially in the dry season, essential for agriculture, drinking purposes, and hydropower production. Recently, most glaciers in the HKH have been retreating and losing mass, mainly due to significant regional warming, thus calling for assessment of future water resources availability for populations down slope. However, hydrology of these high altitude catchments is poorly studied and little understood. Most such catchments are poorly gauged, thus posing major issues in flow prediction therein, and representing in fact typical grounds of application of PUB concepts, where simple and portable hydrological modeling based upon scarce data amount is necessary for water budget estimation, and prediction under climate change conditions. In this preliminarily study, future (2060) hydrological flows in a particular watershed (Shigar river at Shigar, ca. 7000 km<sup>2</sup>), nested within the upper Indus basin and fed by seasonal melt from major glaciers, are investigated. <br><br> The study is carried out under the umbrella of the SHARE-Paprika project, aiming at evaluating the impact of climate change upon hydrology of the upper Indus river. We set up a minimal hydrological model, tuned against a short series of observed ground climatic data from a number of stations in the area, in situ measured ice ablation data, and remotely sensed snow cover data. The future, locally adjusted, precipitation and temperature fields for the reference decade 2050–2059 from <i>CCSM3</i> model, available within the IPCC's panel, are then fed to the hydrological model. We adopt four different glaciers' cover scenarios, to test sensitivity to decreased glacierized areas. The projected flow duration curves, and some selected flow descriptors are evaluated. The uncertainty of the results is then addressed, and use of the model for nearby catchments discussed. The proposed approach is valuable as a tool to investigate the hydrology of poorly gauged high altitude areas, and to project forward their hydrological behavior pending climate change

2008-2011 snow covered area (SCA) variability over 18 watersheds of the central Chile through MODIS data

Snowmelt contributes largely to water budget of several Chilean mountain watersheds. To describe snow covered area (SCA) variability within 18 watersheds in Central Chile during 2008\u20132011 we used MODIS data (i.e. MOD10A2-V5 maximum snow cover extent in eight-day periods). The study area was divided into three different zones (Northern, Central, and Southern), due to its large extent (~205,000 km2), and according to former studies performed by the Direcc\uedon General de Aguas (DGA) of the Chilean Government covering the time window 2000\u20132007. After georeferencing our data to the WGS84 Datum (UTM Projection, zone 19S), the scenes were cropped to fit the study area. We selected and set a threshold for cloud coverage (<30%) in order to discard the images with too cloud cover, so losing only 2% of the sample. Hypsographic and aspect analyses were performed using the SRTM3 elevation model. We found largest values of SCA during 2008\u20132011 in the Central Zone, while the topographic and climatic features (i.e. lower altitudes in the South, and a drier climate in the North) limit snow deposition elsewhere. Similarly, snow line is higher in the Northern zone (due to the presence of the plateau), and lower moving southwards. In the North the minimum SCA is reached sooner than elsewhere, lasting for a longer period (November to March). West side showed the maximum of SCA in all zones throughout the study period. The present work extends in time the dataset of SCA in the Central Chile, adding information for statistic assessment, and trend analysis of snow cover in this area

Physics-Based Mixed-Mode Reverse Recovery Modeling And Optimization Of Si PiN And MPS Fast Recovery Diodes

The paper presents the results of the application of physics-based mixed-mode simulations to the analysis and optimization of the reverse recovery for Si-based fast recovery diodes (FREDs) using Platinum (Pt) lifetime killing. The trap model parameters are extracted from Deep Level Transient Spectroscopy (DLTS) characterization. The model is validated against experimental characterization carried out on the current International Rectifier (IR) FRED PiN technology. Improved designs, using emitter control efficiency and merged PiN-Schottky structures, are analyzed. Comparison between simulated and measured results are presente

Hydrology and potential climate changes in the Rio Maipo (Chile)

Glaciers of the central Andes have recently been retreating in response to global warming, with large consequences on the hydrological regime. We assessed here potential climate change impacts until 2100 upon the hydrologic regime of the largely snow-ice melt driven Maipo River basin (closed at El Manzano, ca. 4800 km2), watering 7 M people in the metropolitan region of Santiago de Chile. First, a weather-driven hydrological model including simplified glaciers\u2019 cover dynamics was set up and validated, to depict the hydrological regime of this area. In situ data from recent glaciological expeditions, ice thickness estimates, historical weather and hydrological data, and remote sensing data including precipitation from the Tropical Rainfall Measuring Mission (TRMM), and snow cover and temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used for model set up. We subsequently forced the model with projections of temperatures and precipitations (plus downscaling) until 2100 from the GCM model ECHAM6, according to 3 different radiative concentration pathways (RCPs 2.6, 4.5, 8.5) adopted by the IPCC in its AR5. We investigated yearly and seasonal trends of precipitation, temperature and hydrological fluxes until 2100 under the different scenarios, in projection period (PR, 2014-2100), and we compared them against historically observed trends in control period (CP, 1980-2013). The results show potential significant increasing trends in temperature until 2100, consistently with observed historical trends, unless for Spring (OND). Precipitation varies more uncertainly, with no historically significant changes, and only few scenarios projecting significant variations. In the PR period, yearly flow decreases, significantly under RCP8.5 (-0.31 m3s-1). Flow decrease is expected especially in Summer (JFM) under RCP8.5 (-0.55 m3s-1). Fall (AMJ) flows would decrease slightly, while winter (JAS) flows are projected to increase, and significantly under RCP4.5 (+0.22 m3s-1), as due to sustained melting therein. Spring (OND) flows also would decrease largely under RCP8.5, down to -0.67 m3s-1, due to increased evapotranspiration for high temperatures

Application of a stochastic weather generator to assess climate change impacts in a semi-arid climate: The Upper Indus Basin

Assessing local climate change impacts requires downscaling from Global Climate Model simulations. Here, a stochastic rainfall model (RainSim) combined with a rainfall conditioned weather generator (CRU WG) have been successfully applied in a semi-arid mountain climate, for part of the Upper Indus Basin (UIB), for point stations at a daily time-step to explore climate change impacts. Validation of the simulated time-series against observations (1961–1990) demonstrated the models’ skill in reproducing climatological means of core variables with monthly RMSE of <2.0 mm for precipitation and ⩽0.4 °C for mean temperature and daily temperature range. This level of performance is impressive given complexity of climate processes operating in this mountainous context at the boundary between monsoonal and mid-latitude (westerly) weather systems. Of equal importance the model captures well the observed interannual variability as quantified by the first and last decile of 30-year climatic periods. Differences between a control (1961–1990) and future (2071–2100) regional climate model (RCM) time-slice experiment were then used to provide change factors which could be applied within the rainfall and weather models to produce perturbed ‘future’ weather time-series. These project year-round increases in precipitation (maximum seasonal mean change:+27%, annual mean change: +18%) with increased intensity in the wettest months (February, March, April) and year-round increases in mean temperature (annual mean +4.8 °C). Climatic constraints on the productivity of natural resource-dependent systems were also assessed using relevant indices from the European Climate Assessment (ECA) and indicate potential future risk to water resources and local agriculture. However, the uniformity of projected temperature increases is in stark contrast to recent seasonally asymmetrical trends in observations, so an alternative scenario of extrapolated trends was also explored. We conclude that interannual variability in climate will continue to have the dominant impact on water resources management whichever trajectory is followed. This demonstrates the need for sophisticated downscaling methods which can evaluate changes in variability and sequencing of events to explore climate change impacts in this region

A simple model to evaluate ice melt over the ablation area of glaciers in the Central Karakoram National Park, Pakistan

This study provides an estimate of fresh water derived from ice melt for the ablation areas of glaciers in the Central Karakoram National Park (CKNP), Pakistan. In the CKNP there are ~700 glaciers, covering ~4600 km2, with widespread debris cover (518 km2). To assess meltwater volume we applied a distributed model able to describe both debris-covered and debris-free ice ablation. The model was calibrated using data collected in the field in the CKNP area and validated by comparison with ablation data collected in the field, independent of the data used in building the model. During 23 July\u20139 August 2011, the mean model-estimated ablation in the CKNP was 0.024 m w.e./ d in debris covered areas and 0.037 m w.e./ d in debris-free areas. We found a mean error of +0.01 m w.e. (corresponding to 2%) and a root-mean-square error equal to 0.09 m w.e. (17%). According to our model, the ablation areas of all the glaciers in the CKNP produced a water volume of 1.963 km3 during the study period. Finally, we performed several sensitivity tests for assessing the impact of the input data variations

Distributed global debris thickness estimates reveal debris significantly impacts glacier mass balance

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