This study evaluates MODIS snow cover characteristics for large number of snowmelt runoff events in 145 catchments from 9 countries in Europe. The analysis is based on open discharge daily time series from the Global Runoff Data Center database and daily MODIS snow cover data. Runoff events are identified by a base flow separation approach. The MODIS snow cover characteristics are derived from Terra 500 m observations (MOD10A1 dataset, V005) in the period 2000–2015 and include snow cover area, cloud coverage, regional snowline elevation (RSLE) and its changes during the snowmelt runoff events. The snowmelt events are identified by using estimated RSLE changes during a runoff event. The results indicate that in the majority of catchments there are between 3 and 6 snowmelt runoff events per year. The mean duration between the start and peak of snowmelt runoff events is about 3 days and the proportion of snowmelt events in all runoff events tends to increase with the maximum elevation of catchments. Clouds limit the estimation of snow cover area and RSLE, particularly for dates of runoff peaks. In most of the catchments, the median of cloud coverage during runoff peaks is larger than 80%. The mean minimum RSLE, which represents the conditions at the beginning of snowmelt events, is situated approximately at the mean catchment elevation. It means that snowmelt events do not start only during maximum snow cover conditions, but also after this maximum. The mean RSLE during snowmelt peaks is on average 170 m lower than at the start of the snowmelt events, but there is a large regional variability.
Flooding remains the most widely distributed natural hazard in Europe, leading to significant economic and social impact. Earth observation data is presently capable of making fundamental contributions towards reducing the detrimental effects of extreme floods. Technological advance makes development of online services able to process high volumes of satellite data without the need of dedicated desktop software licenses possible. The main objective of the case study is to present and evaluate a methodology for mapping of flooded areas based on MODIS satellite images derived indices and using state-of-the-art geospatial web services. The methodology and the developed platform were tested with data for the historical flood event that affected the Danube floodplain in 2006 in Romania. The results proved that, despite the relative coarse resolution, MODIS data is very useful for mapping the development flooded area in large plain floods. Moreover it was shown, that the possibility to adapt and combine the existing global algorithms for flood detection to fit the local conditions is extremely important to obtain accurate results.
Predicting snow cover dynamics and relevant streamflow due to snowmelt is a challenging issue in mountainous basins. Spatio-temporal variations of snow extent can be analyzed using probabilistic snow cover maps derived from satellite images within a relatively long period. In this study, Probabilistic Snow Depletion Curves (P-SDCs) and Probabilistic Snow Lines (P-SLs) are acquired from Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-filtered daily snow cover images. Analyses of P-SDCs show a strong correlation with average daily runoff (R2 = 0.90) and temperature (R2 = 0.96). On the other hand, the challenge lies in developing noteworthy methods to use P-SDCs in streamflow estimations. Therefore, the main objective is to explore the feasibility of producing probabilistic runoff forecasts with P-SDC forcing in a snow dominated basin.
Upper Euphrates Basin in Turkey has large snow extent and high snowmelt contribution during spring and summer periods. The melting characteristics are defined by P-SDCs using MODIS imagery for 2001–2012. The value of snow probability maps on ensemble runoff predictions is shown with Snowmelt Runoff Model (SRM) during 2013–2015 where the estimated runoff values indicate good consistency (NSE: 0.47–0.93) with forecasts based on the derived P-SDCs. Therefore, the probabilistic approach distinguishes the snow cover characteristics for a region and promotes a useful methodology on the application of probabilistic runoff predictions especially for snow dominated areas.
Mean annual recharge in the Danube-Tisza sand plateau region of Hungary over the 2000-2008 period was estimated at a 1-km spatial resolution as the difference of mean annual precipitation (P) and evapotranspiration (ET). The ET rates were derived from linear transformations of the MODIS daytime land surface temperature (Ts) values with the help of ancillary atmospheric data (air temperature, humidity, and sunshine duration). The groundwater under the sand plateau receives about 75 ± 50 mm of recharge annually (the plus/minus value is the associated error, resulting from an assumed 5% error in both the P and ET values), which is about 14 ± 9 % of the regional mean annual P value of 550 mm. The largest continuous region with elevated recharge rates (about 180 ± 50 mm a-1 or 30 ± 8 % of P) occur in the south-western part of the plateau due to more abundant precipitation (around 580 mm a-1), while recharge is the smallest (about 40 ± 40 mm a-1 or 7 ± 7 % of P) under forested areas. Typically, lakes, wetlands, river valleys, and certain afforested areas in the north-central part of the region act as discharge areas for groundwater. and Priemerný ročný úhrn doplňovania podzemných vôd plošiny zloženej z pieskov medzi riekami Dunaj a Tisa s rozlíšením 1 km, pre roky 2000-2008 bol určený ako rozdiel medzi priemerným ročným úhrnom zrážok (P) a evapotranspiráciou (ET). ET bolo určené z lineárnej transformácie teploty povrchu počas dňa (Ts) získanej systémom MODIS pomocou údajov o vlastnostiach atmosféry (teplota vzduchu, vlhkosť vzduchu a trvanie slnečného svitu). Podzemná voda pod pieskovým masívom dostáva ročne asi 75 ± 50 mm vody (znamienka plus/mínus znamenajú chybu, vyplývajúcu z predpokladanej 5% chyby hodnôt P a ET), ktorá je asi 14 ± 9 % regionálnej priemernej ročnej hodnoty P, ktorá je 550 mm. Najväčšia spojitá oblasť so zvýšeným doplňovaním podzemnej vody (približne 180 ± 50 mm za rok alebo 30 ± 8 % P) sa nachádza v juhozápadnej časti plató a je dôsledkom vyššieho ročného úhrnu zrážok (okolo 580 mm), doplňovanie je nižšie v zalesnených oblastiach (okolo 40 ± 40 mm, alebo 7 ± 7 % P). Jazerá, mokrade, rieky a niektoré zalesnené oblasti v strednej a severnej časti tejto oblasti drénujú podzemné vody.
Spatial and temporal variability of snow line (SL) elevation, snow cover area (SCA) and depletion (SCD) in winters 2001-2014 is investigated in ten main Slovak river basins (the Western Carpathians). Daily satellite snow cover maps from MODIS Terra (MOD10A1, V005) and Aqua (MYD10A1, V005) with resolution 500 m are used. The results indicate three groups of basins with similar variability in the SL elevation. The first includes basins with maximum elevations above 1500 m a.s.l. (Poprad, Upper Váh, Hron, Hornád). Winter median SL is equal or close to minimum basin elevation in snow rich winters in these basins. Even in snow poor winters is SL close to the basin mean. Second group consists of mid-altitude basins with maximum elevation around 1000 m a.s.l. (Slaná, Ipeľ, Nitra, Bodrog). Median SL varies between 150 and 550 m a.s.l. in January and February, which represents approximately 40–80% snow coverage. Median SL is near the maximum basin elevation during the snow poor winters. This means that basins are in such winters snow free approximately 50% of days in January and February. The third group includes the Rudava/Myjava and Lower Váh/Danube. These basins have their maximum altitude less than 700 m a.s.l. and only a small part of these basins is covered with snow even during the snow rich winters. The evaluation of SCA shows that snow cover typically starts in December and last to February. In the highest basins (Poprad, Upper Váh), the snow season sometimes tends to start earlier (November) and lasts to March/April. The median of SCA is, however, less than 10% in these months. The median SCA of entire winter season is above 70% in the highest basins (Poprad, Upper Váh, Hron), ranges between 30-60% in the mid-altitude basins (Hornád, Slaná, Ipeľ, Nitra, Bodrog) and is less than 1% in the Myjava/Rudava and Lower Váh/Danube basins. However, there is a considerable variability in seasonal coverage between the years. Our results indicate that there is no significant trend in mean SCA in the period 2001-2014, but periods with larger and smaller SCA exist. Winters in the period 2002-2006 have noticeably larger mean SCA than those in the period 2007-2012. Snow depletion curves (SDC) do not have a simple evolution in most winters. The snowmelt tends to start between early February and the end of March. The snowmelt lasts between 8 and 15 days on average in lowland and high mountain basins, respectively. Interestingly, the variability in SDC between the winters is much larger than between the basins.