Grid Based Services and Tools for Hydrological Model Processing and Visualization

Author(s):  
Victor Bacu ◽  
Danut Mihon ◽  
Teodor Stefanut ◽  
Denisa Rodila ◽  
Dorian Gorgan ◽  
...  
2021 ◽  
Author(s):  
Ponnambalam Rameshwaran ◽  
Ali Rudd ◽  
Vicky Bell ◽  
Matt Brown ◽  
Helen Davies ◽  
...  

<p>Despite Britain’s often-rainy maritime climate, anthropogenic water demands have a significant impact on river flows, particularly during dry summers. In future years, projected population growth and climate change are likely to increase the demand for water and lead to greater pressures on available freshwater resources.</p><p>Across England, abstraction (from groundwater, surface water or tidal sources) and discharge data along with ‘Hands off Flow’ conditions are available for thousands of individual locations; each with a licence for use, an amount, an indication of when abstraction can take place, and the actual amount of water abstracted (generally less than the licence amount). Here we demonstrate how these data can be used in combination to incorporate anthropogenic artificial influences into a grid-based hydrological model. Model simulations of both high and low river flows are generally improved when abstractions and discharges are included, though for some catchments model performance decreases. The new approach provides a methodological baseline for further work investigating the impact of anthropogenic water use and projected climate change on future river flows.</p>


2020 ◽  
Vol 588 ◽  
pp. 124990 ◽  
Author(s):  
Meihong Ma ◽  
Lei Wen ◽  
Sijia Hao ◽  
Gang Zhao ◽  
Minpei Zhou ◽  
...  

2015 ◽  
Vol 12 (3) ◽  
pp. 3169-3203 ◽  
Author(s):  
O. Rakovec ◽  
A. H. Weerts ◽  
J. Sumihar ◽  
R. Uijlenhoet

Abstract. This study investigates the suitability of the Asynchronous Ensemble Kalman Filter (AEnKF) and a partitioned updating scheme for hydrological forecasting. The AEnKF requires forward integration of the model for the analysis and enables assimilation of current and past observations simultaneously at a single analysis step. The results of discharge assimilation into a grid-based hydrological model for the Upper Ourthe catchment in the Belgian Ardennes show that including past predictions and observations in the data assimilation method improves the model forecasts. Additionally, we show that elimination of the strongly non-linear relation between the soil moisture storage and assimilated discharge observations from the model update becomes beneficial for improved operational forecasting, which is evaluated using several validation measures.


2001 ◽  
Vol 45 ◽  
pp. 127-132 ◽  
Author(s):  
Y. TACHIKAWA ◽  
T. KAWAKAMI ◽  
Y. ICHIKAWA ◽  
M. SHIIBA ◽  
K. TAKARA

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