Elevation based correction of snow coverage retrieved from satellite images to improve model calibration

Corbari, Chiara; Ravazzani, Giovanni; Martinelli, J.; Mancini, Marco

doi:10.5194/hess-13-639-2009

Cited by 45 publications

(47 citation statements)

References 26 publications

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“…Lammering and Dwyer, 2000;Ranzi et al, 1999;Corbari et al, 2009) and the controlling effect of topography can be taken into account (Bavay et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of future hydrological cycle under climate change scenarios in a mesoscale Alpine watershed of Italy

Groppelli

Soncini

Bocchiola

et al. 2011

Nat. Hazards Earth Syst. Sci.

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Abstract. We investigate future (2045)(2046)(2047)(2048)(2049)(2050)(2051)(2052)(2053)(2054) hydrological cycle of the snow fed Oglio (≈1800 km 2 ) Alpine watershed in Northern Italy. A Stochastic Space Random Cascade (SSRC) approach is used to downscale future precipitation from three general circulation models, GCMs (PCM, CCSM3, and HadCM3) available within the IPCC's data base and chosen for this purpose based upon previous studies. We then downscale temperature output from the GCMs to obtain temperature fields for the area. We also consider a projected scenario based upon trends locally observed in former studies, LOC scenario. Then, we feed the downscaled fields to a minimal hydrological model to build future hydrological scenarios. We provide projected flow duration curves and selected flow descriptors, giving indication of expected modified (against control run for 1990-1999) regime of low flows and droughts and flood hazard, and thus evaluate modified peak floods regime through indexed flood. We then assess the degree of uncertainty, or spread, of the projected water resources scenarios by feeding the hydrological model with ensembles projections consistent with our deterministic (GCMs + LOC) scenarios, and we evaluate the significance of the projected flow variables against those observed in the control run. The climate scenarios from the adopted GCMs differ greatly from one another with respect to projected precipitation amount and temperature regimes, and so do the projected hydrological scenarios. A relatively good agreement is found upon prospective shrinkage and shorter duration of the seasonal snow cover due to increased temperature patterns, and upon prospective increase of hydrological losses, i.e. evapotranspiration, for the same reason. However, precipitation patterns are less consistent, because HadCM3 and PCM models project noticeably increased precipitation for 2045-2054, whereas CCSM3 provides decreased precipCorrespondence to: D. Bocchiola (daniele.bocchiola@polimi.it) itation patterns therein. The LOC scenario instead displays unchanged precipitation. The ensemble simulations indicate that several projected flow variables under the considered scenarios are significantly different from their control run counterparts, and also that snow cover seems to significantly decrease in duration and depth. The proposed hydrological scenarios eventually provide a what-if analysis, giving a broad view of the possible expected impacts of climate change within the Italian Alps, necessary to trigger the discussion about future adaptation strategies.

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“…Lammering and Dwyer, 2000;Ranzi et al, 1999;Corbari et al, 2009) and the controlling effect of topography can be taken into account (Bavay et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of future hydrological cycle under climate change scenarios in a mesoscale Alpine watershed of Italy

Groppelli

Soncini

Bocchiola

et al. 2011

Nat. Hazards Earth Syst. Sci.

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“…The extreme complexity of processes involved in hydrology of mountainous areas and the great spatial variability of meteorological forcings and river basin characteristics require the use of physically based spatially distributed hydrological models to simulate the transformation of rainfall into runoff [13,14].…”

Section: Introductionmentioning

confidence: 99%

Assessing Climate Impacts on Hydropower Production: The Case of the Toce River Basin

Ravazzani

Valle

Gaudard

et al. 2016

Climate

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Abstract:The aim of the presented study is to assess the impacts of climate change on hydropower production of the Toce Alpine river basin in Italy. For the meteorological forcing of future scenarios, time series were generated by applying a quantile-based error-correction approach to downscale simulations from two regional climate models to point scale. Beside a general temperature increase, climate models simulate an increase of mean annual precipitation distributed over spring, autumn and winter, and a significant decrease in summer. A model of the hydropower system was driven by discharge time series for future scenarios, simulated with a spatially distributed hydrological model, with the simulation goal of defining the reservoirs management rule that maximizes the economic value of the hydropower production. The assessment of hydropower production for future climate till 2050 respect to current climate (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010) showed an increase of production in autumn, winter and spring, and a reduction in June and July. Significant change in the reservoir management policy is expected due to anticipation of the date when the maximum volume of stored water has to be reached and an increase of the reservoir drawdown during August and September to prepare storage capacity for autumn inflows.

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“…Snow percentage at the sub-pixel size is useful for sensitivity analyses of the homogeneity of the snow cover, especially during the melting season, whether it is continuous or not. All data were acquired for pixel sizes of 500 m × 500 m, and the main steps of our methodology can be summarized as (i) the re-projection of all data from sinusoidal to UTM using the SRTM DEM, (ii) radiometric correction of local sun illumination within the DEM (Teillet et al, 1982;Corbari et al, 2009), (iii) snow cover area (SCA) mapping retrieved from the NSIDC classification (Hall et al, 2002), (iv) fractional snow cover mapping …”

Section: Image Processingmentioning

confidence: 99%

Shifting mountain snow patterns in a changing climate from remote sensing retrieval

Dedieu

Lessard-Fontaine

Ravazzani

et al. 2014

Science of The Total Environment

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• MODIS satellite images analysis for snow cover dynamics over 2000-2010 time period.• Application to river basins at medium and large scale (Europe, Central Asia).• Statistical bias as standard deviation values express sensitivity to climate change.• Below 1200 m, a winter time continuous snow-pack is becoming increasingly rare. Observed climate change has already led to a wide range of impacts on environmental systems and society. In this context, many mountain regions seem to be particularly sensitive to a changing climate, through increases in temperature coupled with changes in precipitation regimes that are often larger than the global average (EEA, 2012). In mid-latitude mountains, these driving factors strongly influence the variability of the mountain snow-pack, through a decrease in seasonal reserves and earlier melting of the snow pack. These in turn impact on hydrological systems in different watersheds and, ultimately, have consequences for water management. Snow monitoring from remote sensing provides a unique opportunity to address the question of snow cover regime changes at the regional scale. This study outlines the results retrieved from the MODIS satellite images over a time period of 10 hydrological years (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010) and applied to two case studies of the EU FP7 ACQWA project, namely the upper Rhone and Po in Europe and the headwaters of the Syr Darya in Kyrgyzstan (Central Asia). The satellite data were provided by the MODIS Terra MOD-09 reflectance images (NASA) and MOD-10 snow products (NSIDC). Daily snow maps were retrieved over that decade and the results presented here focus on the temporal and spatial changes in snow cover. This paper highlights the statistical bias observed in some specific regions, expressed by the standard deviation values (STD) of annual snow duration. This bias is linked to the response of snow cover to changes in elevation and can be used as a signal of strong instability in regions sensitive to climate change: with alternations of heavy snowfalls and rapid snow melting processes. The interest of the study is to compare the methodology between the medium scales (Europe) and the large scales (Central Asia) in order to overcome the limits of the applied methodologies and to improve their performances. Results show that the yearly snow cover duration increases by 4-5 days per 100 m elevation during the accumulation period, depending of the watershed, while during the melting season the snow depletion rate is 0.3% per day of surface loss for the upper Rhone catchment, 0.4%/day for the Syr Darya headwater basins, and 0.6%/day for the upper Po, respectively. Then, the annual STD maps of snow cover indicate higher values (more than 45 days difference compared to the mean values) for (i) the Po foothill region at medium elevation (SE orientation) and (ii) the Kyrgyzstan high plateaux (permafrost areas). These observations cover only a timeperiod of 10 years, but exhibit a signal under current climate that is alread...

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Elevation based correction of snow coverage retrieved from satellite images to improve model calibration

Cited by 45 publications

References 26 publications

Evaluation of future hydrological cycle under climate change scenarios in a mesoscale Alpine watershed of Italy

Evaluation of future hydrological cycle under climate change scenarios in a mesoscale Alpine watershed of Italy

Assessing Climate Impacts on Hydropower Production: The Case of the Toce River Basin

Shifting mountain snow patterns in a changing climate from remote sensing retrieval

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