scholarly journals Sensitivity Analysis of Parameters in Water Quality Models and Water Environment Management

2012 ◽  
Vol 03 (08) ◽  
pp. 863-870 ◽  
Author(s):  
Dongjun Liu ◽  
Zhihong Zou
Keyword(s):  
Water Quality ◽  
Sensitivity Analysis ◽  
Water Environment ◽  
Quality Models ◽  
Environment Management ◽  
Water Quality Models

Effective Global Sensitivity Analysis for High-Dimensional Hydrologic and Water Quality Models

2019 ◽  
Vol 24 (1) ◽  
pp. 04018057 ◽  
Author(s):  
Yogesh Khare ◽  
Christopher J. Martinez ◽  
Rafael Muñoz-Carpena ◽  
Adelbert “Del” Bottcher ◽  
Andrew James
Keyword(s):  
Water Quality ◽  
Sensitivity Analysis ◽  
Global Sensitivity Analysis ◽  
High Dimensional ◽  
Quality Models ◽  
Global Sensitivity ◽  
Water Quality Models

Nutrient Speciation and Refractory Compounds in Water Quality Models

2016 ◽  
Vol 15 (0) ◽  
pp. 9781780408323-9781780408323
Author(s):  
D. L. Clark ◽  
G. Hunt ◽  
M. S. Kasch ◽  
P. J. Lemonds
Keyword(s):  
Water Quality ◽  
Quality Models ◽  
Refractory Compounds ◽  
Water Quality Models

The Use of Water Quality Models in Belgium

1987 ◽  
Vol 19 (7) ◽  
pp. 1197-1202 ◽  
Author(s):  
A. Van Der Beken
Keyword(s):  
Water Quality ◽  
Quality Models ◽  
Water Quality Models

scholarly journals Relative Performance of 1-D Versus 3-D Hydrodynamic, Water-Quality Models for Predicting Water Temperature and Oxygen in a Shallow, Eutrophic, Managed Reservoir

Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 88
Author(s):  
Xiamei Man ◽  
Chengwang Lei ◽  
Cayelan C. Carey ◽  
John C. Little
Keyword(s):  
Water Quality ◽  
Water Temperature ◽  
Water Quality Model ◽  
Relative Performance ◽  
Bubble Plume ◽  
Quality Model ◽  
Quality Models ◽  
Management Interventions ◽  
Water Quality Models ◽  
D Model

Many researchers use one-dimensional (1-D) and three-dimensional (3-D) coupled hydrodynamic and water-quality models to simulate water quality dynamics, but direct comparison of their relative performance is rare. Such comparisons may quantify their relative advantages, which can inform best practices. In this study, we compare two 1-year simulations in a shallow, eutrophic, managed reservoir using a community-developed 1-D model and a 3-D model coupled with the same water-quality model library based on multiple evaluation criteria. In addition, a verified bubble plume model is coupled with the 1-D and 3-D models to simulate the water temperature in four epilimnion mixing periods to further quantify the relative performance of the 1-D and 3-D models. Based on the present investigation, adopting a 1-D water-quality model to calibrate a 3-D model is time-efficient and can produce reasonable results; 3-D models are recommended for simulating thermal stratification and management interventions, whereas 1-D models may be more appropriate for simpler model setups, especially if field data needed for 3-D modeling are lacking.

Hydrologic and Water Quality Models: Use, Calibration, and Validation

2012 ◽  
Vol 55 (4) ◽  
pp. 1241-1247 ◽  
Author(s):  
D. N. Moriasi ◽  
B. N. Wilson ◽  
K. R. Douglas-Mankin ◽  
J. G. Arnold ◽  
P. H. Gowda
Keyword(s):  
Water Quality ◽  
Quality Models ◽  
Calibration And Validation ◽  
Water Quality Models

Water Quality Models for Developing Soil Management Practices

2020 ◽  
pp. 349-382
Author(s):  
J.R. Williams ◽  
J.G. Arnold ◽  
C.A. Jones ◽  
V.W. Benson ◽  
R.H. Griggs
Keyword(s):  
Water Quality ◽  
Management Practices ◽  
Soil Management ◽  
Quality Models ◽  
Water Quality Models

Evolutive techniques applied to water quality models calibration

2009 ◽  
pp. 199-202
Author(s):  
P López-Jiménez ◽  
F Martínez-Solano ◽  
Gonzalo López-Patiño ◽  
Vicente Fuertes-Miquel
Keyword(s):  
Water Quality ◽  
Quality Models ◽  
Water Quality Models

scholarly journals Improving and parameterising nitrogen and phosphorus modelling for application of LUCI in New Zealand

2021 ◽  
Author(s):  
◽  
Martha Trodahl
Keyword(s):  
Water Quality ◽  
New Zealand ◽  
Land Cover ◽  
Land Management ◽  
Stream Water ◽  
Nutrient Loss ◽  
Catchment Scale ◽  
Quality Models ◽  
Export Coefficient ◽  
Water Quality Models

<p>Over the last 50 years freshwater and marine environments have become severely impaired due to contamination from pathogens, heavy metals, sediment, industrial chemicals and nutrients (MEA 2005b). In many countries, including New Zealand, increased nitrogen (N) and phosphorus (P) loading to terrestrial and freshwater environments from diffuse nutrient sources are of particular concern (MEA 2005a; PCE 2015b; Steffen et al. 2015) and many governments now mandate control of diffuse nutrient loss to water. Water quality models are invaluable tools that can assist with decision making around this widespread issue through exploration of the current situation and future scenarios.  Many water quality models exist, functioning at a variety of temporal and spatial scales and varying in detail and complexity. However, few, if any, simultaneously represent sub-field to catchment scale processes and outcomes, both of which are required to fully address water quality issues associated with diffuse nutrient sources. Those that do, likely require extensive time and expertise to operate. Water quality models embedded in the Land Utilisation and Capability Indicator (LUCI), an ecosystem service decision support framework, offer the opportunity to overcome these limitations. Being highly spatially explicit, yet straightforward to use, they can inform and assist individual land owners, catchment managers and other stakeholders with planning, decision making and management of water quality at sub-field to landscape scale.  To model diffuse nutrient losses LUCI, like many catchment scale water quality models, requires some form of estimated nutrient loss, or export coefficient, from land units within the catchment of interest. To be representative export coefficients must consider climate, soil, topography, and land cover and management variables. A number of methods of export coefficient derivation exist, although generally they consider only very limited geo-climatic, land cover and land management variables.  The principal aim of this study is development of algorithms capable of calculating New Zealand site specific N and P export coefficients from detailed geo-climatic, land cover and land management variables, for application in LUCI water quality models. Algorithms for pastoral land cover are developed from a large dataset comprising real pastoral farm input and output data from nutrient budgeting model OVERSEER. Algorithms are extended to land covers other than pasture, albeit in a limited manner. This is achieved through rescaling of the pastoral algorithms to account for relative differences in literature reported N and P losses from pasture and a variety of other New Zealand land covers. Application of the developed algorithms in LUCI water quality models results in positioning of export coefficients at the DEM grid square scale (≤ 15 m x 15 m for New Zealand). In addition, intra-basin configuration is considered in LUCI, at the same grid square scale, as water and nutrient flows are cascaded through the catchment. Application of the export coefficient calculating algorithms are applied to two contrasting New Zealand catchments. Tuapaka catchment, an 85ha agricultural foothill catchment in Manawatu, North Island, and Lake Rotorua catchment, a 502 km2 volcanic, mixed land cover catchment in Bay of Plenty, North Island.  This research is supported by Ravensdown, a farmer owned co-operative, which plans to use LUCI extensively to advise and assist farmers with water quality issues. The ability to model mitigation strategies in LUCI is an important capability. Therefore, this research also includes a review of five particularly important on-farm mitigation strategies, which will later be used by the wider LUCI development team to assist with better parameterisation and improved performance of mitigation options in LUCI.  Application of the developed algorithms at farm to catchment scale in LUCI results in considerably more nuanced, detailed maps and data showing N and P sources and pathways, compared to LUCI’s previously used ‘one export coefficient per land cover’ approach. Although results indicate absolute nutrient loss values are not always ‘correct’ compared to either OVERSEER predictions or in-stream water quality measurements, these differences appear comparable to those seen with similar water quality models. In addition, the issue of representativeness of OVERSEER predictions and in-stream water quality measurements exists.  Nevertheless improvement to absolute predictions is always an aim. This research indicates further improvements to LUCI water quality predictions could result from refinement of both pastoral and other land cover algorithms, and from improved representation of attenuation processes in LUCI, including groundwater representation. However, lack of measured on-land and in-stream N and P loss data is a major challenge to both algorithm refinement and to evaluation of results. In addition, more detailed spatial data would provide more nuanced results from algorithm application.  Although the algorithm application context in this research is LUCI water quality models applied in New Zealand, this does not preclude application of the developed algorithms in other export coefficient based, catchment scale water quality models. Using spatial data pertaining to climate, soil, topographic and land management variables, land units of combined variables can be identified and the algorithms applied, resulting in explicitly positioned export coefficients that can be fed into the catchment scale water quality model of interest. Therefore, developments made here potentially represent a wider contribution to catchment scale modelling using export coefficients.</p>

scholarly journals Assessment of Nakdong River Basin Management: Target Water Quality Achievement and Future Challenges

2020 ◽  
Vol 20 (2) ◽  
pp. 251-263
Author(s):  
Kyeong Hwan Kang ◽  
Junghyeon Kim ◽  
Hyeonjin Jeon ◽  
Kyoungwoo Kim ◽  
Imgyu Byun
Keyword(s):  
Water Quality ◽  
River Basin ◽  
Water Environment ◽  
Quality Data ◽  
Master Plan ◽  
Nakdong River ◽  
Environment Management ◽  
Pollutant Load ◽  
Nakdong River Basin ◽  
Representative Points

In 2006, the Korean Ministry of Environment established <The 1st Water Environment Management Master Plan>. The plan aimed at “Clean Water, Eco River 2015” and guided water quality protection and strengthened water management. This study evaluated the achievement of the target water quality among the 33 mid-level basins in the Nakdong River basin and assessments of the causes of non-achievement of the target water quality by mid-level basins. According to the 2015 water quality data, only 16 of the 33 mid-level basins achieved the target water quality. The low achievement of the target water quality was attributed to the failure to predict the pollutant load at the time of planning, problems with the management of tributaries, implementation of the <Four major river restoration project>, and problems with the representativeness of the water quality representative points. In addition, feasibility studies on the water quality monitoring representative point used in each mid-level basin were also performed; some mid-level basins required improvement or change of the representative points. This study also suggested further research to improve water quality, such as detailed studies of the management of pollutant load, mainstream tributaries, and water quality indicators, for the revision of the current ongoing <The 2nd Water Environment Management Master Plan>.

Sign in / Sign up

Export Citation Format

Share Document