scholarly journals Validation of the STRIVE model for coupling ecological processes and surface water flow

2010 ◽  
Vol 13 (4) ◽  
pp. 741-759
Author(s):  
L. De Doncker ◽  
P. Troch ◽  
R. Verhoeven ◽  
K. Buis ◽  
P. Meire
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Water Flow ◽  
Research Question ◽  
Quality Parameters ◽  
Water Levels ◽  
Ecological Processes ◽  
Vegetation Growth ◽  
Surface Water Flow ◽  
Quality Aspects

The 1D model package STRIVE is verified for simulating the interaction between ecological processes and surface water flow. The model is general and can be adapted and further developed according to the research question. The hydraulic module, based on the Saint-Venant equations, is the core part. The presence of macrophytes influences the water quality and the discharge due to the flow resistance of the river, expressed by Manning's coefficient, and allows an ecological description of the river processes. Based on the advection–dispersion equation, water quality parameters are incorporated and modelled. Calculation of the water quantity parameters, coupled with water quality and inherent validation and sensitivity analysis, is the main goal of this research. An important study area is the River Aa near Poederlee (Belgium), a lowland river with a wealth of vegetation growth, where discharge and vegetation measurements are carried out on a regular basis. The developed STRIVE model shows good and accurate calculation results. The work highlights the possibility of STRIVE to model flow processes, water quality aspects and ecological interaction combined and separately. Coupling of discharges, water levels, amount of biomass and tracer values provides a powerful prediction modelling tool for the ecological behaviour of lowland rivers.

Assessement of Water Quality Parameters in Some Potential Pollutant Areas from Romania

2018 ◽  
Vol 69 (8) ◽  
pp. 2045-2049
Author(s):  
Catalina Gabriela Gheorghe ◽  
Andreea Bondarev ◽  
Ion Onutu
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Surface Water Quality ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Quality Data ◽  
Chemical Parameters ◽  
Water Quality Data ◽  
Pollutant Sources ◽  
Water Quality Forecasting

Monitoring of environmental factors allows the achievement of some important objectives regarding water quality, forecasting, warning and intervention. The aim of this paper is to investigate water quality parameters in some potential pollutant sources from northern, southern and east-southern areas of Romania. Surface water quality data for some selected chemical parameters were collected and analyzed at different points from March to May 2017.

Comparison of surface water flow simulation over structured and unstructured grids

2021 ◽  
Author(s):  
Nivedhitha Ajithkumar ◽  
Prabhakar Alok Verma ◽  
Frank B. Osei ◽  
Hari Shankar
Keyword(s):  
Surface Water ◽  
Water Flow ◽  
Unstructured Grids ◽  
Flow Simulation ◽  
Surface Water Flow

scholarly journals Multivariate Monitoring of Surface Water Quality: Physico-Chemical, Microbiological and 3D Fluorescence Characterization

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1673
Author(s):  
Claude Daou ◽  
Mervat El Hoz ◽  
Amine Kassouf ◽  
Bernard Legube
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Anthropogenic Activities ◽  
Surface Water Quality ◽  
Principal Component ◽  
Specific Weight ◽  
Quality Parameters ◽  
Primary Objective ◽  
Fluorescence Excitation ◽  
Fluorescence Characteristics

The primary objective of this study is to explore a water quality database on two Mediterranean rivers (the Kadisha-Abou Ali and El Jaouz rivers—located in north Lebanon), considering their physicochemical, microbiological and fluorescence characteristics. Principal Component Analysis (PCA) was applied to the matrix gathering physicochemical and microbiological data while the Common Components and Specific Weight Analysis (CCSWA) or ComDim was used for fluorescence excitation-emission matrices (EEMs). This approach provided complementary and valuable information regarding water quality in such complex ecosystem. As highlighted by the PCA and ComDim scores, the Kadisha-Abou Ali River is highly influenced by anthropogenic activities because its watershed districts are intensively populated. This influence reveals the implication of organic and bacteriological parameters. To the contrary, the El Jaouz watershed is less inhabited and is characterized by mineral parameters, which determines its water quality. This work highlighted the relationship between fluorescence EEMs and major water quality parameters, enabling the selection of reliable water quality indicators for the studied rivers. The proposed methodology can surely be generalized to the monitoring of surface water quality in other rivers. Each customized water quality fingerprint should constantly be inspected in order to account for any emerging pollution.

scholarly journals A Spatial Analysis to Define Data Requirements for Hydrological and Water Quality Models in Data-Limited Regions

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 267 ◽  
Author(s):  
Ersilia D’Ambrosio ◽  
Anna De Girolamo ◽  
Marinella Spanò ◽  
Vera Corbelli ◽  
Gennaro Capasso ◽  
...  
Keyword(s):  
Water Quality ◽  
Spatial Analysis ◽  
Surface Water ◽  
Source Parameters ◽  
Quality Parameters ◽  
Point Sources ◽  
Water Quality Parameters ◽  
Limited Area ◽  
Climatic Data ◽  
Basin Scale

The objective of the present work is a spatial analysis aimed at supporting hydrological and water quality model applications in the Canale d’Aiedda basin (Puglia, Italy), a data-limited area. The basin is part of the sensitive environmental area of Taranto that requires remediation of the soil, subsoil, surface water, and groundwater. A monitoring plan was defined to record the streamflow and water quality parameters needed for calibrating and validating models, and a database archived in a GIS environment was built, which includes climatic data, soil hydraulic parameters, groundwater data, surface water quality parameters, point-source parameters, and information on agricultural practices. Based on a one-year monitoring of activities, the average annual loads of N-NO3 and P-PO4 delivered to the Mar Piccolo amounted to about 42 t year−1, and 2 t year−1, respectively. Knowledge uncertainty in monthly load estimation was found to be up to 25% for N-NO3 and 40% for P-PO4. The contributions of point sources in terms of N-NO3 and P-PO4 were estimated at 45% and 77%, respectively. This study defines a procedure for supporting modelling activities at the basin scale for data-limited regions.

Flow and Radionuclide Transport From Rock to Surface Systems: Characterization and Modelling of Potential Repository Sites in Sweden

2007 ◽  
Author(s):  
Kent Werner ◽  
Emma Bosson ◽  
Sten Berglund
Keyword(s):  
Surface Water ◽  
Groundwater Flow ◽  
Water Flow ◽  
Exit Point ◽  
Flow Paths ◽  
Near Surface ◽  
Mike She ◽  
Mike 11 ◽  
Surface Water Flow ◽  
Safety Assessments

The safety assessments of potential geological repositories for spent nuclear fuel in Sweden are supported by modelling of groundwater flow in rock, to predict locations (exit points) where radionuclides from the deep repository may enter land, surface waters and associated ecosystems above the rock. This modelling includes detailed rock descriptions, but simplifies the upper part of the flow domain, including representations of meteorological processes and interactions with hydrological objects at the surface. Using the Laxemar candidate site as example, this paper investigates some potentially important consequences of these simplifications. Specifically, it compares particle tracking results obtained by a deep-rock groundwater flow model (CONNECTFLOW) and by MIKE SHE-MIKE 11, which contains detailed descriptions of near-surface/surface water flow. Overall, the models predict similar exit point patterns, occurring as clusters along streams in valleys, at a lake, and in sea bays. However, on a detailed level there are some prediction differences, which may be of importance for biosphere-focused safety assessments. CONNECTFLOW essentially predicts flow paths through the repository that follow fractures and deformation zones, outcropping in valleys. In comparison, MIKE SHE-MIKE 11 provides more detailed information on near-surface water flow paths, including the associated exit points and inputs to assessments of radionuclide retention.

scholarly journals Impacts of hurricanes on surface water flow within a wetland

2010 ◽  
Vol 392 (3-4) ◽  
pp. 164-173 ◽  
Author(s):  
Yang Deng ◽  
Helena M. Solo-Gabriele ◽  
Michael Laas ◽  
Lynn Leonard ◽  
Daniel L. Childers ◽  
...  
Keyword(s):  
Surface Water ◽  
Water Flow ◽  
Surface Water Flow

The Influence of Land Roughness to Irrigation Efficiency Based on SIRMOD Model of Border Irrigation of Wheat

2014 ◽  
Vol 955-959 ◽  
pp. 3640-3644
Author(s):  
He Xiang Zheng ◽  
Xue Song Cao ◽  
Jia Bin Wu ◽  
Jian Cheng Zhang
Keyword(s):  
Surface Roughness ◽  
Surface Water ◽  
Water Flow ◽  
Water Movement ◽  
Field Trials ◽  
Measured Data ◽  
Irrigation Efficiency ◽  
Movement Process ◽  
Surface Water Flow

Land roughness is an important parameter of border irrigation in the surface water flow movement, it affects of the water movement process and affects irrigation efficiency, so it’s necessary combined with field surface other parameters to study irrigation field roughness to the irrigation efficiency. Agreement is good between simulated by SIRMOD model and measured values​​ through field trials the measured data of water flow advance and regression process, and indicating with SIRMOD model can simulate border irrigation process. Four kinds of typical field surface roughness of irrigation simulation by SIRMOD model and analysis of the results obtained: land roughness difference of water flow advance and regression process influence significantly, the water flow advance and regression process is better with the small land roughness, and the curve of water flow advance and regression becomes uneven, so irrigation efficiency significant reduction with the field surface roughness increases.

Estimating surface water flow speeds using time–frequency methods

2010 ◽  
Vol 4 (4) ◽  
pp. 406 ◽  
Author(s):  
P.R. Kersten ◽  
R.W. Jansen ◽  
T.L. Ainsworth ◽  
J.V. Toporkov ◽  
M.A. Sletten
Keyword(s):  
Surface Water ◽  
Water Flow ◽  
Time Frequency ◽  
Surface Water Flow ◽  
Flow Speeds
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