Hydroclimatic Aspects of the 2011 Assiniboine River Basin Flood

2015 ◽  
Vol 16 (3) ◽  
pp. 1250-1272 ◽  
Author(s):  
Julian Brimelow ◽  
Kit Szeto ◽  
Barrie Bonsal ◽  
John Hanesiak ◽  
Bohdan Kochtubajda ◽  
...  
Keyword(s):  
River Basin ◽  
Large Scale ◽  
Snow Water Equivalent ◽  
Early Summer ◽  
Spring Precipitation ◽  
Cumulative Impact ◽  
Socioeconomic Impacts ◽  
Cold Temperatures ◽  
Extreme Flood ◽  
Precipitation Events

Abstract In the spring and early summer of 2011, the Assiniboine River basin in Canada experienced an extreme flood that was unprecedented in terms of duration and severity. The flood had significant socioeconomic impacts and caused over $1 billion (Canadian dollars) in damage. Contrary to what one might expect for such an extreme flood, individual precipitation events before and during the 2011 flood were not extreme; instead, it was the cumulative impact and timing of precipitation events going back to the summer of 2010 that played a key role in the 2011 flood. The summer and fall of 2010 were exceptionally wet, resulting in above-normal soil moisture levels at the time of freeze-up. This was followed by record high snow water equivalent values in March and April 2011. Cold temperatures in March delayed the spring melt, resulting in the above-average spring freshet occurring close to the onset of heavy rains in May and June. The large-scale atmospheric flow during May and June 2011 favored increased cyclone activity in the region, which produced an anomalously large number of heavy rainfall events over the basin. All of these factors combined generated extreme flooding. Japanese 55-year Reanalysis Project (JRA-55) data are used to quantify the relative importance of snowmelt and spring precipitation in contributing to the unprecedented flood and to demonstrate how the 2011 flood was unique compared to previous floods. This study can be used to validate and improve flood forecasting techniques over this important basin; the findings also raise important questions regarding floods in a changing climate over basins that experience pluvial and nival flooding.

scholarly journals Cloud obstruction and snow cover in Alpine areas from MODIS products

2014 ◽  
Vol 18 (11) ◽  
pp. 4579-4600 ◽  
Author(s):  
P. Da Ronco ◽  
C. De Michele
Keyword(s):  
Snow Cover ◽  
River Basin ◽  
Cloud Cover ◽  
Large Scale ◽  
Snow Water Equivalent ◽  
Practical Interest ◽  
Computational Effort ◽  
Po River ◽  
Average Value ◽  
Po River Basin

Abstract. Snow cover maps provide information of great practical interest for hydrologic purposes: when combined with point values of snow water equivalent (SWE), they enable estimation of the regional snow resource. In this context, Earth observation satellites are an interesting tool for evaluating large scale snow distribution and extension. MODIS (MODerate resolution Imaging Spectroradiometer on board Terra and Aqua satellites) daily Snow Covered Area product has been widely tested and proved to be appropriate for hydrologic applications. However, within a daily map the presence of cloud cover can hide the ground, thus obstructing snow detection. Here, we consider MODIS binary products for daily snow mapping over the Po River basin. Ten years (2003–2012) of MOD10A1 and MYD10A1 snow maps have been analysed and processed with the support of a 500 m resolution Digital Elevation Model (DEM). We first investigate the issue of cloud obstruction, highlighting its dependence on altitude and season. Snow maps seem to suffer the influence of overcast conditions mainly in mountain and during the melting period. Thus, cloud cover highly influences those areas where snow detection is regarded with more interest. In spring, the average percentages of area lying beneath clouds are in the order of 70%, for altitudes over 1000 m a.s.l. Then, starting from previous studies, we propose a cloud removal procedure and we apply it to a wide area, characterized by high geomorphological heterogeneity such as the Po River basin. In conceiving the new procedure, our first target was to preserve the daily temporal resolution of the product. Regional snow and land lines were estimated for detecting snow cover dependence on elevation. In cases when there was not enough information on the same day within the cloud-free areas, we used temporal filters with the aim of reproducing the micro-cycles which characterize the transition altitudes, where snow does not stand continually over the entire winter. In the validation stage, the proposed procedure was compared against others, showing improvements in the performance for our case study. The accuracy is assessed by applying the procedure to clear-sky maps masked with additional cloud cover. The average value is higher than 95% considering 40 days chosen over all seasons. The procedure also has advantages in terms of input data and computational effort requirements.

Physiographic controls on pre-event hydrological states and hydrological response to extreme precipitation in the Alzette River Basin, Luxembourg

2021 ◽  
Author(s):  
Carol Tamez Melendez ◽  
Judith Meyer ◽  
Audrey Douinot ◽  
Günter Blöschl ◽  
Laurent Pfister
Keyword(s):  
River Basin ◽  
Large Scale ◽  
Flash Flood ◽  
Potential Evapotranspiration ◽  
Convective Precipitation ◽  
Hydrological Response ◽  
Local Character ◽  
Area Of Interest ◽  
Oceanic Climate ◽  
Precipitation Events

<p>Flash flood events have caused massive damage on multiple occasions between 2016 and 2018 in several catchments in eastern Luxembourg. This region is very well known for being exposed to large-scale winter floods, commonly triggered by long-lasting advective precipitation events related to westerly atmospheric fluxes. However, flash floods - a truly exceptional phenomenon in this region - are have solely occurred in summer in response to intense convective precipitation events. Thus, because of the rare occurrence and local character of this type of events, the mechanisms eventually controlling a flash flood-type response of a catchment remains poorly understood.  </p><p>Here, we focus on four main objectives: i) the role that physiographic characteristics play on the spatial variability of pre-event hydrological states (as expressed via storage) across a set of 41 nested catchments located in the Sûre River basin (4,240 km<sup>2</sup>), Luxembourg, ii) the hydrological response to precipitation controlled by those pre-event hydrological states, iii) the responsivity (resistance) and elasticity (resilience) of the catchments to global change, and iv) the relation between water yields and the offsets from Budyko curve and its related energy limits.</p><p>The area of interest is not only characterised by a homogenous temperate oceanic climate but also by heterogeneous physiographical conditions and land use, which makes it ideal for this study. We used 8 years’ worth hydrological data (precipitation, discharge and potential evapotranspiration) to calculate the increments of the water balance and determine the maximum storage capacity and storage deficits. Second, we used the relationship between storage deficit and discharge to estimate total storage at a hypothetical nearly zero flow condition. Third, we compared the pre-hydrological states and event runoff ratios (Q/P) to the catchments’ physiographical conditions in order to link catchment’s sensitivity to storage metrics. We then assessed the responsivity and elasticity to climate and anthropogenic variations – as expressed through the PET/P and AET/P deviations from the Budyko curve and energy limits– for each individual catchment. Finally, we investigated the catchment’s area control on responsivity, elasticity, water yields and Budyko’s elements across our set of 41 nested catchments.</p>

scholarly journals Influence of snow water equivalent on droughts and their prediction in the USA

2018 ◽  
Author(s):  
Daniel Abel ◽  
Felix Pollinger ◽  
Heiko Paeth
Keyword(s):  
Sierra Nevada ◽  
Large Scale ◽  
Snow Water Equivalent ◽  
Southern Oscillation ◽  
Original Data ◽  
The United States ◽  
Early Summer ◽  
Drought Severity ◽  
Southern Us ◽  
Snow Water

Abstract. Droughts can result in enormous impacts for environment, societies, and economy. In arid or semiarid regions with bordering high mountains, snow is the major source of water supply due to its role as natural water storage. The goal of this study is to examine the influence of snow water equivalent (SWE) on droughts in the United States and find large-scale climatic predictors for SWE and drought. For this, a Maximum Covariance Analysis (MCA), also known as Singular Value Decomposition, is performed with snow data from the ERA–Interim reanalysis and the self-calibrating Palmer Drought Severity Index (sc–PDSI) as drought index. Furthermore, the relationship of resulting principal components and original data with atmospheric patterns is investigated. The leading mode shows the spatial connection between SWE and drought via downstream water/moisture transport. Especially the Rocky Mountains in Colorado (CR) play a key role for the central and western South, but the Sierra Nevada and even the Appalachian Mountains are relevant, too. The temperature and precipitation based sc–PDSI is able to capture this link because increased soil moisture results in higher evapotranspiration with lower sensible heat and vice versa. A time shifted MCA indicates a prediction skill for drought conditions in spring and early summer for the downstream regions of CR on the basis of SWE in March. Furthermore, the phase of the El Niño–Southern Oscillation is a good predictor for drought in the southern US and SWE around Colorado. The influence of the North Atlantic Oscillation and Pacific North American Pattern is not that clear.

scholarly journals Assessment of a multiresolution snow reanalysis framework: a multidecadal reanalysis case over the upper Yampa River basin, Colorado

2018 ◽  
Vol 22 (7) ◽  
pp. 3575-3587 ◽  
Author(s):  
Elisabeth Baldo ◽  
Steven A. Margulis
Keyword(s):  
Data Assimilation ◽  
River Basin ◽  
Large Scale ◽  
Snow Water Equivalent ◽  
Low Complexity ◽  
Snow Accumulation ◽  
Computationally Efficient ◽  
Snow Cover Area ◽  
Mountain Ranges ◽  
Snow Water

Abstract. A multiresolution (MR) approach was successfully implemented in the context of a data assimilation (DA) framework to efficiently estimate snow water equivalent (SWE) over a large head water catchment in the Colorado River basin (CRB), while decreasing computational constraints by 60 %. A total of 31 years of fractional snow cover area (fSCA) images derived from Landsat TM, ETM+, and OLI sensor measurements were assimilated to generate two SWE reanalysis datasets, a baseline case at a uniform 90 m spatial resolution and another using the MR approach. A comparison of the two showed negligible differences in terms of snow accumulation, melt, and timing for the posterior estimates (in terms of both ensemble median and coefficient of variation). The MR approach underestimated the baseline peak SWE by less than 2 % and underestimated day of peak and duration of the accumulation season by a day on average. The largest differences were, by construct, limited primarily to areas of low complexity, where shallow snowpacks tend to exist. The MR approach should allow for more computationally efficient implementations of snow data assimilation applications over large-scale mountain ranges, with accuracies similar to those that would be obtained using ∼ 100 m simulations. Such uniform resolution applications are generally infeasible due to the computationally expensive nature of ensemble-based DA frameworks.

scholarly journals Extreme Flood Impact on Estuarine and Coastal Biogeochemistry: the 2013 Elbe Flood

2016 ◽  
Author(s):  
Yoana G. Voynova ◽  
Holger Brix ◽  
Wilhelm Petersen ◽  
Sieglinde Weigelt-Krenz ◽  
Mirco Scharfe
Keyword(s):  
Dissolved Oxygen ◽  
German Bight ◽  
Large Scale ◽  
Monitoring Network ◽  
Oxygen Depletion ◽  
Early Summer ◽  
Elbe Estuary ◽  
Atmospheric Conditions ◽  
Arctic Seas ◽  
Extreme Flood

Abstract. Within the context of predicted and observed increase in droughts and floods with climate change, large summer floods are likely to become more frequent. These extreme events can alter typical biogeochemical patterns in coastal systems. The extreme Elbe River flood in June, 2013 not only caused major damages in several European countries, but also generated large scale biogeochemical changes in the Elbe Estuary and the adjacent German Bight. Due to a number of well documented and unusual atmospheric conditions, the early summer of 2013 in Central and Eastern Europe was colder and wetter than usual, with saturated soils, and higher than average cumulative precipitation. Additional precipitation at the end of May, and beginning of June, 2013, caused widespread floods within the Danube and Elbe Rivers, as well as billions of euros in damages. The floods generated the largest summer discharge on record within the last 140 years. The high-frequency monitoring network in the German Bight available within the Coastal Observing System for Northern and Arctic Seas (COSYNA) captured the flood influence on the German Bight. Monitoring data from a FerryBox station in the Elbe Estuary (Cuxhaven) and from a FerryBox platform aboard the M/V Funny Girl Ferry (traveling between Büsum and Helgoland) documented the salinity changes on the German Bight, which persisted for about 2 months after the peak discharge. The flood generated a large influx of nutrients, dissolved and particulate organic carbon on the coast. These conditions subsequently led to the onset of a chlorophyll bloom within the German Bight, observed by dissolved oxygen supersaturation, and higher than usual pH in surface coastal waters. The prolonged stratification also led to widespread bottom water dissolved oxygen depletion, unusual for the south eastern German Bight in the summer.

scholarly journals Assessment of a multi-resolution snow reanalysis framework: a multi-decadal reanalysis case over the Upper Yampa River Basin, Colorado

2017 ◽  
Author(s):  
Elisabeth Baldo ◽  
Steven A. Margulis
Keyword(s):  
Data Assimilation ◽  
River Basin ◽  
Large Scale ◽  
Snow Water Equivalent ◽  
Low Complexity ◽  
Snow Accumulation ◽  
Computationally Efficient ◽  
Snow Cover Area ◽  
Mountain Ranges ◽  
Snow Water

Abstract. A multi-resolution (MR) approach was successfully implemented in the context of a data assimilation (DA) framework to efficiently estimate snow water equivalent (SWE) over a large headwater catchment in the Colorado River Basin (CRB), while decreasing computational constraints by 60 %. Thirty-one years of fractional snow cover area (fSCA) images derived from Landsat TM, ETM+ and OLI sensors measurements were assimilated to generate two SWE reanalysis datasets, a baseline case at a uniform 90 m spatial resolution and another using the MR approach. A comparison of the two showed negligible differences in terms of snow accumulation, melt and timing for the posterior estimates (in terms of both ensemble median and standard deviation). The MR approach underestimated the baseline peak SWE by less than 2 %, and day of peak and duration of the accumulation season by a day on average. The largest differences were, by construct, limited primarily to areas of low complexity, where shallow snowpacks tend to exist. The MR approach should allow for more computationally efficient implementations of snow data assimilation applications over large-scale mountain ranges with accuracies similar to those that would be obtained using ~ 100 m simulations. Such uniform resolution applications are generally infeasible due to the computationally expensive nature of ensemble-based DA frameworks.

scholarly journals Hydroclimatology of the Missouri River Basin

2018 ◽  
Vol 19 (1) ◽  
pp. 161-182 ◽  
Author(s):  
Erika K. Wise ◽  
Connie A. Woodhouse ◽  
Gregory J. McCabe ◽  
Gregory T. Pederson ◽  
Jeannine-Marie St-Jacques
Keyword(s):  
River Basin ◽  
Missouri River ◽  
Winter Precipitation ◽  
Meridional Flow ◽  
Early Summer ◽  
Hydroelectric Power ◽  
Spring Precipitation ◽  
The Pacific ◽  
Droughts And Floods ◽  
Instrumental Period

Abstract Despite the importance of the Missouri River for navigation, recreation, habitat, hydroelectric power, and agriculture, relatively little is known about the basic hydroclimatology of the Missouri River basin (MRB). This is of particular concern given the droughts and floods that have occurred over the past several decades and the potential future exacerbation of these extremes by climate change. Here, observed and modeled hydroclimatic data and estimated natural flow records in the MRB are used to 1) assess the major source regions of MRB flow, 2) describe the climatic controls on streamflow in the upper and lower basins , and 3) investigate trends over the instrumental period. Analyses indicate that 72% of MRB runoff is generated by the headwaters in the upper basin and by the lowest portion of the basin near the mouth. Spring precipitation and temperature and winter precipitation impacted by changes in zonal versus meridional flow from the Pacific Ocean play key roles in surface water supply variability in the upper basin. Lower basin flow is significantly correlated with precipitation in late spring and early summer, indicative of Atlantic-influenced circulation variability affecting the flow of moisture from the Gulf of Mexico. Although increases in precipitation in the lower basin are currently overriding the effects of warming temperatures on total MRB flow, the upper basin’s long-term trend toward decreasing flows, reduction in snow versus rain fraction, and warming spring temperatures suggest that the upper basin may less often provide important flow supplements to the lower basin in the future.

scholarly journals Seasonal Rainfall Forecasts for the Yangtze River Basin in the Extreme Summer of 2020

2021 ◽  
Author(s):  
Philip E. Bett ◽  
Gill M. Martin ◽  
Nick Dunstone ◽  
Adam A. Scaife ◽  
Hazel E. Thornton ◽  
...  
Keyword(s):  
Linear Regression ◽  
River Basin ◽  
Yangtze River ◽  
Asian Summer Monsoon ◽  
Yangtze River Basin ◽  
Early Summer ◽  
Lead Times ◽  
Seasonal Forecasts ◽  
June July ◽  
The Impact

AbstractSeasonal forecasts for Yangtze River basin rainfall in June, May–June–July (MJJ), and June–July–August (JJA) 2020 are presented, based on the Met Office GloSea5 system. The three-month forecasts are based on dynamical predictions of an East Asian Summer Monsoon (EASM) index, which is transformed into regional-mean rainfall through linear regression. The June rainfall forecasts for the middle/lower Yangtze River basin are based on linear regression of precipitation. The forecasts verify well in terms of giving strong, consistent predictions of above-average rainfall at lead times of at least three months. However, the Yangtze region was subject to exceptionally heavy rainfall throughout the summer period, leading to observed values that lie outside the 95% prediction intervals of the three-month forecasts. The forecasts presented here are consistent with other studies of the 2020 EASM rainfall, whereby the enhanced mei-yu front in early summer is skillfully forecast, but the impact of midlatitude drivers enhancing the rainfall in later summer is not captured. This case study demonstrates both the utility of probabilistic seasonal forecasts for the Yangtze region and the potential limitations in anticipating complex extreme events driven by a combination of coincident factors.

scholarly journals Using the Global Hydrodynamic Model and GRACE Follow-On Data to Access the 2020 Catastrophic Flood in Yangtze River Basin

2021 ◽  
Vol 13 (15) ◽  
pp. 3023
Author(s):  
Jinghua Xiong ◽  
Shenglian Guo ◽  
Jiabo Yin ◽  
Lei Gu ◽  
Feng Xiong
Keyword(s):  
River Basin ◽  
Hydrodynamic Model ◽  
Yangtze River ◽  
Large Scale ◽  
Yangtze River Basin ◽  
The Yangtze River ◽  
Ecosystem Monitoring ◽  
Catastrophic Flood ◽  
Basin Scale ◽  
The Yangtze River Basin

Flooding is one of the most widespread and frequent weather-related hazards that has devastating impacts on the society and ecosystem. Monitoring flooding is a vital issue for water resources management, socioeconomic sustainable development, and maintaining life safety. By integrating multiple precipitation, evapotranspiration, and GRACE-Follow On (GRAFO) terrestrial water storage anomaly (TWSA) datasets, this study uses the water balance principle coupled with the CaMa-Flood hydrodynamic model to access the spatiotemporal discharge variations in the Yangtze River basin during the 2020 catastrophic flood. The results show that: (1) TWSA bias dominates the overall uncertainty in runoff at the basin scale, which is spatially governed by uncertainty in TWSA and precipitation; (2) spatially, a field significance at the 5% level is discovered for the correlations between GRAFO-based runoff and GLDAS results. The GRAFO-derived discharge series has a high correlation coefficient with either in situ observations and hydrological simulations for the Yangtze River basin, at the 0.01 significance level; (3) the GRAFO-derived discharge observes the flood peaks in July and August and the recession process in October 2020. Our developed approach provides an alternative way of monitoring large-scale extreme hydrological events with the latest GRAFO release and CaMa-Flood model.

scholarly journals Assessing Climatic Drivers of Spring Mean and Annual Maximum Flows in Western Canadian River Basins

Water ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 1617
Author(s):  
Yonas B. Dibike ◽  
Rajesh R. Shrestha ◽  
Colin Johnson ◽  
Barrie Bonsal ◽  
Paulin Coulibaly
Keyword(s):  
Snow Water Equivalent ◽  
Climate Model ◽  
Regional Climate ◽  
River Basins ◽  
Snow Accumulation ◽  
Spatial Variations ◽  
Annual Maximum ◽  
Spring Precipitation ◽  
Average Maximum ◽  
Maximum Flows

Flows originating from cold and mountainous watersheds are highly dependent on temperature and precipitation patterns, and the resulting snow accumulation and melt conditions, affecting the magnitude and timing of annual peak flows. This study applied a multiple linear regression (MLR) modelling framework to investigate spatial variations and relative importance of hydroclimatic drivers of annual maximum flows (AMF) and mean spring flows (MAMJflow) in 25 river basins across western Canada. The results show that basin average maximum snow water equivalent (SWEmax), April 1st SWE and spring precipitation (MAMJprc) are the most important predictors of both AMF and MAMJflow, with the proportion of explained variance averaging 51.7%, 44.0% and 33.5%, respectively. The MLR models’ abilities to project future changes in AMF and MAMJflow in response to changes to the hydroclimatic controls are also examined using the Canadian Regional Climate Model (CanRCM4) output for RCP 4.5 and RCP8.5 scenarios. The results show considerable spatial variations depending on individual watershed characteristics with projected changes in AMF ranging from −69% to +126% and those of MAMJflow ranging from −48% to +81% by the end of this century. In general, the study demonstrates that the MLR framework is a useful approach for assessing the spatial variation in hydroclimatic controls of annual maximum and mean spring flows in the western Canadian river basins. However, there is a need to exercise caution in applying MLR models for projecting changes in future flows, especially for regulated basins.

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