Long‐Term Cumulative Effects of Intra‐Annual Variability of Unsteady River Discharge on the Progradation of Delta Lobes: A Modeling Perspective

2019 ◽  
Vol 124 (4) ◽  
pp. 960-973 ◽  
Author(s):  
Weilun Gao ◽  
Dongdong Shao ◽  
Zheng Bing Wang ◽  
William Nardin ◽  
Prateek Rajput ◽  
...  
Keyword(s):  
River Discharge ◽  
Cumulative Effects ◽  
Annual Variability

STIV-DIEX INTEGRATED SYSTEM FOR LONG-TERM CONTINUOUS RIVER DISCHARGE MONITORING

2018 ◽  
Vol 74 (4) ◽  
pp. I_667-I_672
Author(s):  
Yuya SUZUKI ◽  
Jin KASHIWADA ◽  
Yasuo NIHEI ◽  
Tomohito FUJII ◽  
Kenji TAIRA ◽  
...  
Keyword(s):  
River Discharge ◽  
Integrated System ◽  
Discharge Monitoring

scholarly journals Long-term changes of river discharge regime in Latvia

2008 ◽  
Vol 39 (2) ◽  
pp. 133-141 ◽  
Author(s):  
Maris Klavins ◽  
Valery Rodinov
Keyword(s):  
Climate Variability ◽  
River Discharge ◽  
Water Resource Management ◽  
Regional Climate ◽  
Hydrological Regime ◽  
High Water ◽  
Regime Changes ◽  
Long Term Changes ◽  
Discharge Regime

The study of changes in river discharge is important for regional climate variability characterization and for development of an efficient water resource management system. The hydrological regime of rivers and their long-term changes in Latvia were investigated. Four major types of river hydrological regimes, which depend on climatic and physicogeographic factors, were characterized. These factors are linked to the changes observed in river discharge. Periodic oscillations of discharge, and low- and high-water flow years are common for the major rivers in Latvia. A main frequency of river discharge regime changes of about 20 and 13 years was estimated for the studied rivers. A significant impact of climate variability on the river discharge regime has been found.

Bedforms, bed material, and bedload transport in a salt-wedge estuary: Fraser River, British Columbia

1989 ◽  
Vol 26 (7) ◽  
pp. 1440-1452 ◽  
Author(s):  
R. A. Kostaschuk ◽  
M. A. Church ◽  
J. L. Luternauer
Keyword(s):  
British Columbia ◽  
River Discharge ◽  
Bedload Transport ◽  
Fraser River ◽  
Seasonal Fluctuations ◽  
Salt Wedge ◽  
Migration Rates ◽  
Material Load ◽  
Bed Material

The lower main channel of the Fraser River, British Columbia, is a sand-bed, salt-wedge estuary in which variations in velocity, discharge, and bedform characteristics are contolled by river discharge and the tides. Bed-material composition remains consistent over the discharge season and in the long term. Changes in bedform height and length follow but lag behind seasonal fluctuations in river discharge. Migration rates of bedforms respond more directly to river discharge and tidal fall than do height and length. Bedform characteristics were utilized to estimate bedload transport in the estuary, and a strong, direct, but very sensitive relationship was found between bed load and river discharge. Annual bedload transport in the estuary is estimated to be of the order of 0.35 Mt in 1986. Bedload transport in the estuary appears to be higher than in reaches upstream, possibly because of an increase in sediment movement along the bed to compensate for a reduction in suspended bed-material load produced by tidal slack water and the salt wedge.

scholarly journals Inter-annual variability of wind climates and wind turbine annual energy production

2018 ◽  
Author(s):  
Sara C. Pryor ◽  
Tristan J. Shepherd ◽  
Rebecca J. Barthelmie
Keyword(s):  
Standard Deviation ◽  
Wind Energy ◽  
Wind Turbine ◽  
Energy Production ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Speeds ◽  
Annual Variability ◽  
Eastern Usa

Abstract. Inter-annual variability (IAV) of expected annual energy production (AEP) from proposed wind farms plays a key role in dictating project financing. IAV in pre-construction projected AEP and the difference in 50th and 90th percentile (P50 and P90) AEP derives in part from variability in wind climates. However, the magnitude of IAV in wind speeds at/close to wind turbine hub-heights is poorly constrained and maybe overestimated by the 6 % standard deviation of annual mean wind speeds that is widely applied within the wind energy industry. Thus there is a need for improved understanding of the long-term wind resource and the inter-annual variability therein in order to generate more robust predictions of the financial value of a wind energy project. Long-term simulations of wind speeds near typical wind turbine hub-heights over the eastern USA indicate median gross capacity factors (computed using 10-minute wind speeds close to wind turbine hub-heights and the power curve of the most common wind turbine deployed in the region) that are in good agreement with values derived from operational wind farms. The IAV of annual mean wind speeds at/near to typical wind turbine hub-heights in these simulations is lower than is implied by assuming a standard deviation of 6 %. Indeed, rather than in 9 in 10 years exhibiting AEP within 0.9 and 1.1 times the long-term mean AEP, results presented herein indicate that over 90 % of the area in the eastern USA that currently has operating wind turbines simulated AEP lies within 0.94 and 1.06 of the long-term average. Further, IAV of estimated AEP is not substantially larger than IAV in mean wind speeds. These results indicate it may be appropriate to reduce the IAV applied to pre-construction AEP estimates to account for variability in wind climates, which would decrease the cost of capital for wind farm developments.

scholarly journals Further evidence of a cumulative effect of social disadvantage on risk of psychosis

2016 ◽  
Vol 47 (5) ◽  
pp. 913-924 ◽  
Author(s):  
S. A. Stilo ◽  
C. Gayer-Anderson ◽  
S. Beards ◽  
K. Hubbard ◽  
A. Onyejiaka ◽  
...  
Keyword(s):  
Local Population ◽  
Control Sample ◽  
Cumulative Effect ◽  
Social Disadvantage ◽  
Psychiatric Services ◽  
Cumulative Effects ◽  
First Episode ◽  
Increased Risk ◽  
First Contact

BackgroundA growing body of evidence suggests that indicators of social disadvantage are associated with an increased risk of psychosis. However, only a few studies have specifically looked at cumulative effects and long-term associations. The aims of this study are: To compare the prevalence of specific indicators of social disadvantage at, and prior to, first contact with psychiatric services in patients suffering their first episode of psychosis and in a control sample. To explore long-term associations, cumulative effects, and direction of effects.MethodWe collected information on social disadvantage from 332 patients and from 301 controls recruited from the local population in South London. Three indicators of social disadvantage in childhood and six indicators of social disadvantage in adulthood were analysed.ResultsAcross all the domains considered, cases were more likely to report social disadvantage than were controls. Compared with controls, cases were approximately two times more likely to have had a parent die and approximately three times more likely to have experienced a long-term separation from one parent before the age of 17 years. Cases were also more likely than controls to report two or more indicators of adult social disadvantage, not only at first contact with psychiatric services [odds ratio (OR) 9.5], but also at onset of psychosis (OR 8.5), 1 year pre-onset (OR 4.5), and 5 years pre-onset (OR 2.9).ConclusionsGreater numbers of indicators of current and long-term exposure are associated with progressively greater odds of psychosis. There is some evidence that social disadvantage tends to cluster and accumulate.

Application of tree rings in understanding long-term variability in river discharge of high Himalayas, India

2022 ◽  
pp. 247-264
Author(s):  
Vikram Singh ◽  
Krishna G. Misra ◽  
Akhilesh K. Yadava ◽  
Ram R. Yadav
Keyword(s):  
Tree Rings ◽  
River Discharge ◽  
High Himalayas

Time Effects of Informal Caregiving on Cognitive Function and Well-Being: Evidence From ELSA

2020 ◽  
Author(s):  
Jing Yuan ◽  
Daniel Grühn
Keyword(s):  
Cognitive Function ◽  
Cumulative Effect ◽  
Well Being ◽  
Informal Caregiving ◽  
Cumulative Effects ◽  
Time Effects ◽  
Socioemotional Functioning ◽  
Lagged Effects ◽  
The Impact

Abstract Background and Objectives As informal caregiving becomes prevalent, its consequences for caregivers’ cognitive and socioemotional functioning gain more importance for society. There are inconsistent findings regarding the direction of the impact of caregiving—whether caregiving maintains or compromises functioning—and the impact of time—whether the effects accumulate or are stable. In this study, we elucidated 3 time effects of caregiving—concurrent, cumulative, and lagged effects—on cognitive and socioemotional functioning. Research Design and Methods We used data from Wave 1 (2002–2003) to Wave 8 (2016–2017) in the English Longitudinal Study of Ageing (ELSA) and latent growth curve models with the time-varying predictor to investigate 3 time effects of caregiving on cognitive function (memory and executive function) and well-being (life satisfaction and quality of life). Results Over and beyond age effects, current caregiving (concurrent effect) was related to worse well-being and better delayed recall. Little robust cumulative effect was found on cognition and well-being. In addition, there were significant and differential lagged effects of caregiving after controlling for concurrent and cumulative effects; that is, caregiving was related to worse well-being and better memory functioning 2–4 years later. Discussion and Implications The differential concurrent and lagged effects of caregiving on cognitive and socioemotional functioning suggest separate mechanisms for different domains of functioning. The nonsignificant cumulative effects but significant lagged effects imply that even one-time caregiving has long-term (2–4 years) consequences for the caregiver’s future functioning, and the mechanism of long-term caregiving effects may be more qualitative than quantitative.

scholarly journals River Discharge Estimation based on Satellite Water Extent and Topography: An Application over the Amazon

2019 ◽  
Vol 20 (9) ◽  
pp. 1851-1866 ◽  
Author(s):  
Dinh Thi Lan Anh ◽  
Filipe Aires
Keyword(s):  
River Discharge ◽  
Amazon Basin ◽  
Water Cycle ◽  
Large River ◽  
Water Volume ◽  
Discharge Estimation ◽  
Three Rivers ◽  
Storage Change

Abstract River discharge (RD) estimates are necessary for many applications, including water management, flood risk, and water cycle studies. Satellite-derived long-term GIEMS-D3 surface water extent (SWE) maps and HydroSHEDS data, at 90-m resolution, are here used to estimate several hydrological quantities at a monthly time scale over a few selected locations within the Amazon basin. Two methods are first presented to derive the water level (WL): the “hypsometric curve” and the “histogram cutoff” approaches at an 18 km × 18 km resolution. The obtained WL values are interpolated over the whole water mask using a bilinear interpolation. The two methods give similar results and validation with altimetry is satisfactory, with a correlation ranging from 0.72 to 0.89 in the seven considered stations over three rivers (i.e., Wingu, Negro, and Solimoes Rivers). River width (RW) and water volume change (WVC) are also estimated. WVC is evaluated with GRACE total water storage change, and correlations range from 0.77 to 0.88. A neural network (NN) statistical model is then used to estimate the RD based on four predictors (SWE, WL, WVC, and RW) and on in situ RD measurements. Results compare well to in situ measurements with a correlation of about 0.97 for the raw data (and 0.84 for the anomalies). The presented methodologies show the potential of historical satellite data (the combination of SWE with topography) to help estimate RD. Our study focuses here on a large river in the Amazon basin at a monthly scale; additional analyses would be required for other rivers, including smaller ones, in different environments, and at higher temporal scale.

scholarly journals Recent trends and variability in river discharge across northern Canada

2016 ◽  
Vol 20 (12) ◽  
pp. 4801-4818 ◽  
Author(s):  
Stephen J. Déry ◽  
Tricia A. Stadnyk ◽  
Matthew K. MacDonald ◽  
Bunu Gauli-Sharma
Keyword(s):  
Arctic Ocean ◽  
River Discharge ◽  
Flow Regulation ◽  
Data Availability ◽  
Labrador Sea ◽  
James Bay ◽  
River Diversion ◽  
Northern Canada ◽  
Annual Variability ◽  
Hydropower Production

Abstract. This study presents an analysis of the observed inter-annual variability and inter-decadal trends in river discharge across northern Canada for 1964–2013. The 42 rivers chosen for this study span a combined gauged area of 5.26  ×  106 km2 and are selected based on data availability and quality, gauged area and record length. Inter-annual variability in river discharge is greatest for the eastern Arctic Ocean (coefficient of variation, CV  =  16 %) due to the Caniapiscau River diversion into the La Grande Rivière system for enhanced hydropower production. Variability is lowest for the study area as a whole (CV  =  7 %). Based on the Mann–Kendall test (MKT), no significant (p > 0.05) trend in annual discharge from 1964 to 2013 is observed in the Bering Sea, western Arctic Ocean, western Hudson and James Bay, and Labrador Sea; for northern Canada as a whole, however, a statistically significant (p < 0.05) decline of 102.8 km3 25 yr−1 in discharge occurs over the first half of the study period followed by a statistically significant (p < 0.05) increase of 208.8 km3 25 yr−1 in the latter half. Increasing (decreasing) trends in river discharge to the eastern Hudson and James Bay (eastern Arctic Ocean) are largely explained by the Caniapiscau diversion to the La Grande Rivière system. Strong regional variations in seasonal trends of river discharge are observed, with overall winter (summer) flows increasing (decreasing, with the exception of the most recent decade) partly due to flow regulation and storage for enhanced hydropower production along the Hudson and James Bay, the eastern Arctic Ocean and Labrador Sea. Flow regulation also suppresses the natural variability of river discharge, particularly during cold seasons.

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