Combining hydro-economic and water quality modeling for optimal management of a degraded watershed

Abstract Increase of economic and productivity efficiencies intensifies environmental pressures, too. Agriculture is one of the most common examples of this phenomenon. The sector is lacking proper management, which is especially prominent in Mediterranean areas. To address the situation, a holistic modeling approach, combining hydrological, economic and water quality aspects, is recommended for implementation in a Greek watershed. The broader area is degraded regarding its water availability, quality, and management. The model provides insights into water balance, net profit from agricultural activities, presents water quality data from simulations, and introduces two useful parameters informing the decision-maker's knowledge and understanding: the deficit irrigation water's value and a hydro-economic index which estimates (socio-)economic benefits over environmental balance. A combined demand-management plan is also examined considering the above outputs in investigating the multiple effects of the suggested policy measures. Furthermore, to discuss the optimal approach depending on data availability and scope, we compare two different settings of the proposed model. The results of the study confirmed the continuous quantitative and qualitative water resources' deterioration and economic overexploitation of the watershed. The study reveals the immediate need for management actions, integrated modeling approaches, and provides future recommendations on hydro-economic modeling.

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Effect of Forest Cover on Water Treatment Costs

Water Economics and Policy ◽

10.1142/s2382624x17500060 ◽

2017 ◽

Vol 03 (04) ◽

pp. 1750006 ◽

Cited By ~ 18

Author(s):

Travis Warziniack ◽

Chi Ho Sham ◽

Robert Morgan ◽

Yasha Feferholtz

Keyword(s):

Water Quality ◽

Land Use ◽

Water Treatment ◽

Forest Cover ◽

The United States ◽

Economic Benefits ◽

Treatment Costs ◽

Quality Data ◽

Water Quality Data ◽

The Impact

This paper studies the relationship between forest cover and drinking water chemical treatment costs using land use data and a survey by the American Water Works Association (AWWA). The survey gathers cost and water quality data from 37 treatment plants in forested ecoregions of the United States. We model the effect of forest conversion on the cost of water treatment using a two-step process. First, we examine the effect of changes in land use on water quality through an ecological production function. Second, we examine the effect of changes in water quality on cost of treatment through an economic benefits function. We find a negative relationship between forest cover and turbidity, but no relationship between forest cover and total organic carbon (TOC). Increasing forest cover in a watershed by 1% reduces turbidity by 3%, and increasing development by 1% in a watershed increases turbidity by 3%. The impact of development is more consistent across models than the impact of forest cover. We also find a large impact on turbidity from grazing in the watershed. Our economic benefits function shows a 1% increase in turbidity increases water treatment costs by 0.19%, and 1% increase in TOC increases water treatment costs by 0.46%. TOC has a clearer impact on costs than turbidity, which becomes insignificant when we omit one of our observations with high turbidity.

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Ranking methods to set restoration and remediation priorities on a watershed scale

Water Science & Technology ◽

10.2166/wst.2008.567 ◽

2008 ◽

Vol 58 (10) ◽

pp. 2025-2030 ◽

Cited By ~ 2

Author(s):

William T. Stringfellow

Keyword(s):

Water Quality ◽

Implementation Process ◽

Scientific Data ◽

Quality Data ◽

Quadrant Analysis ◽

Ranking Methods ◽

Water Quality Data ◽

Management Actions ◽

Sources Of Pollution ◽

The Relationship

The establishment of a total maximum daily load (TMDL) is part of management process that results in the institution of watershed-based controls of otherwise unregulated sources of pollution. In California (USA), the implementation of a TMDL is driven forward in a process where watershed stakeholders are expected to cooperate on actions needed to improve ecosystem health. In the TMDL process, methods are needed for synthesizing complex scientific data into actionable management information. Where pollutant load analysis may be misleading or perceived as unfair, non-parametric statistical methods can be applied to flow and water quality data to guide the selection of drainages for remediation. The calculation of normalized rank means (NRMs) for flow and water quality can be used to set priorities for the implementation of TMDL management actions. Drainages can be classified into one of four categories (quadrants) based on the relationship between flow and water quality NRMs. Drainages can be included or excluded from management action based on their quadrant classification. Although there are many possible alternative approaches, this “quadrant analysis” is suggested as a scientifically rigorous methods for identifying priority watersheds in the often contentious, stakeholder driven TMDL implementation process.

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Water Quality Data Availability for Model Calibration Using EPA's BASINS

Proceedings of the Water Environment Federation ◽

10.2175/193864700785149323 ◽

2000 ◽

Vol 2000 (6) ◽

pp. 2179-2201

Author(s):

J. Beebe ◽

D. Barton ◽

R. Whittemore ◽

J. Palumbo

Keyword(s):

Water Quality ◽

Model Calibration ◽

Data Availability ◽

Quality Data ◽

Water Quality Data

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Water quality management in the Crocodile River catchment, Eastern Transvaal, South Africa

Water Science & Technology ◽

10.2166/wst.1995.0603 ◽

1995 ◽

Vol 32 (5-6) ◽

pp. 201-208

Author(s):

P. J. Ashton ◽

F. C. van Zyl ◽

R. G. Heath

Keyword(s):

South Africa ◽

Water Quality ◽

Quality Management ◽

Water Quality Management ◽

Quality Data ◽

Catchment Management ◽

Land Uses ◽

Water Quality Data ◽

River Catchment ◽

Management Actions

The Crocodile River catchment lies in an area which currently has one of the highest rates of sustained economic growth in South Africa and supports a diverse array of land uses. Water quality management is vital to resource management strategies for the catchment. A Geographic Information System (GIS) was used to display specific catchment characteristics and land uses, supplemented with integrative overlays depicting land-use impacts on surface water resources and the consequences of management actions on downstream water quality. The water quality requirements of each water user group were integrated to optimise the selection of rational management solutions for particular water quality problems. Time-series water quality data and cause-effect relationships were used to evaluate different water supply scenarios. The GIS facilitated the collation, processing and interpretation of the enormous quantity of spatially orientated information required for integrated catchment management.

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The role of citizen science as a tool of public information in water quality management in the Brantas catchment, Indonesia

10.5194/egusphere-egu21-9302 ◽

2021 ◽

Author(s):

Reza Pramana ◽

Schuyler Houser ◽

Daru Rini ◽

Maurits Ertsen

Keyword(s):

Water Quality ◽

Quality Management ◽

Citizen Science ◽

Water Resource ◽

Water Resource Management ◽

Water Quality Management ◽

Data Availability ◽

Quality Data ◽

Water Quality Data ◽

Data Set

Water quality in the rivers and tributaries of the Brantas catchment (about 12.000 km2) is deteriorating due to various reasons, including rapid economic development, insufficient domestic water treatment and waste management, and industrial pollution. Various parameters measured by agencies involved in water resource development and management and environmental management consistently demonstrate exceedance of the local water quality standards. Between the different agencies, water quality data are available &#8211; intermittently from 2009 until 2019 at 104 locations, but generally on a monthly basis. Still, opportunities to improve data availability are apparent, both to increase the amount and representability of the data sets. The opportunity to expand available data via citizen science is simultaneously an opportunity to provide education on water stewardship and empower citizens to participate in water quality management. We plan to involve people from eight communities living close to the river and researchers from two local universities in a citizen-science campaign. The community members would sample weekly at 10 locations, from upstream to downstream of the catchment. We will use probes and test strips to measure the temperature, electrical conductivity, pH, nitrate, phosphate, ammonia, iron, and dissolved oxygen. The results will potentially be combined with the data from government agencies to construct an integrated water quality data set to improve decision making and the quality of community engagement in water resource management.

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INDEKS KUALITAS AIR RAWA LEBAK DELING UNTUK BUDIDAYA PERIKANAN ALAMI

Jurnal Akuakultur Rawa Indonesia ◽

10.36706/jari.v6i2.7156 ◽

2018 ◽

Vol 6 (2) ◽

pp. 123-128

Author(s):

Irkhamiawan Ma’ruf ◽

Rahmad Kurniawan ◽

Khusnul Khotimah

Keyword(s):

Water Quality ◽

Fisheries Management ◽

Economic Benefits ◽

Quality Analysis ◽

Quality Data ◽

Water Quality Data ◽

Temperature Parameter ◽

Vegetation Water ◽

The One ◽

Quality Measurements

ABSTRACTAs a common properti, fisheries management in swamps need to be made to provides economic benefits for the parties on the one side (especially the community), and the sustainability of the ecosystem itself on the other side. Current conditions need to be obtained to formulate swamp resource management in a sustainable manner by reducing fishing activities with aquaculture activities. Aquaculture, besides providing greater income, can also control fishing activities and reduce pressure on the swamp ecosystem. The study was conducted in Rawa Deling, Deling Village, Pangkalan Lampam Sub-District, OKI District. Water quality measurements are carried out for 5 months, from March 2018 to July 2018 in 4 stations with differences depth and vegetation. Water quality analysis is carried out to get an overview of the swamp condition. Water quality data will determine the feasibility and treatment needed for aquaculture. The results of water quality measurements showed that temperature parameter values ranging from 28.1 - 32.2 oC, depths of 0.7 - 5 m, brightness of 20 - 50 cm, TDS 17 - 35 mgL-1, pH 4.1 - 5, DO 1 , 7 - 4.1 mgL-1, phosphate <0.060 - <0.090 mgL-1, total nitrogen 12.50 - 38.90 mgL-1, ammonia 0.68 - 0.93 mgL-1. Measuring water quality shows the potential for deling swamps to be developed in an effort to increase fish stocks and aquaculture activities.Keywords : lebak lebung swamps, sustainable fisheries management, swamp water quality

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Water Quality Modeling of Mahabad Dam Watershed–Reservoir System under Climate Change Conditions, Using SWAT and System Dynamics

Water ◽

10.3390/w11020394 ◽

2019 ◽

Vol 11 (2) ◽

pp. 394 ◽

Cited By ~ 9

Author(s):

Mohammad Nazari-Sharabian ◽

Masoud Taheriyoun ◽

Sajjad Ahmad ◽

Moses Karakouzian ◽

Azadeh Ahmadi

Keyword(s):

Climate Change ◽

Water Quality ◽

System Dynamics ◽

Water Conservation ◽

Assessment Tool ◽

Swat Model ◽

Water Quality Modeling ◽

Quality Data ◽

Livestock Farming ◽

Water Quality Data

The total phosphorus (TP) concentration, as the primary limiting eutrophication factor in the Mahabad Dam reservoir in Iran, was studied, considering the combined impacts of climate change, as well as the scenarios on changes in upstream TP loadings and downstream dam water allocations. Downscaled daily projected climate data were obtained from the Beijing Normal University Earth System Model (BNU-ESM) under moderate (RCP4.5) and extreme (RCP8.5) scenarios. These data were used as inputs of a calibrated Soil and Water Assessment Tool (SWAT) model of the watershed in order to determine the effects of climate change on runoff yields in the watershed from 2020 to 2050. The SWAT model was calibrated/validated using the SUFI-2 algorithm in the SWAT Calibration Uncertainties Program (SWAT-CUP). Moreover, to model TP concentration in the reservoir and to investigate the effects of upstream/downstream scenarios, along with forecasted climate-induced changes in streamflow and evaporation rates, the System Dynamics (SD) model was implemented. The scenarios covered a combination of changes in population, agricultural and livestock farming activities, industrialization, water conservation, and pollution control. Relative to the year 2011 in which the water quality data were available, the SD results showed the highest TP concentrations in the reservoir under scenarios in which the inflow to the reservoir had decreased, while the upstream TP loadings and downstream dam water allocations had increased (+29.9%). On the other hand, the lowest TP concentration was observed under scenarios in which upstream TP loadings and dam water allocations had decreased (−18.5%).

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GRQA: Global River Water Quality Archive

10.5194/egusphere-egu21-3865 ◽

2021 ◽

Author(s):

Holger Virro ◽

Giuseppe Amatulli ◽

Alexander Kmoch ◽

Longzhu Shen ◽

Evelyn Uuemaa

Keyword(s):

Water Quality ◽

River Water ◽

Large Scale ◽

Hydrological Modeling ◽

Water Quality Modeling ◽

River Water Quality ◽

Quality Data ◽

Observation Data ◽

Water Quality Data ◽

Physically Based

Recent advances in implementing machine learning (ML) methods in hydrology have given rise to a new, data-driven approach to hydrological modeling. Comparison of physically based and ML approaches has shown that ML methods can achieve a similar accuracy to the physically based ones and outperform them when describing nonlinear relationships. Global ML models have been already successfully applied for modeling hydrological phenomena such as discharge.However, a major problem related to large-scale&#160; water quality modeling has been the lack of available observation data with a good spatiotemporal coverage. This has affected the reproducibility of previous studies and the potential improvement of existing models. In addition to the observation data itself, insufficient or poor quality metadata has also discouraged researchers to integrate the already available datasets. Therefore, improving both, the availability, and quality of open water quality data would increase the potential to implement predictive modeling on a global scale.We aim to address the aforementioned issues by presenting the new Global River Water Quality Archive (GRQA) by integrating data from five existing global and regional sources:<ul><li>Canadian Environmental Sustainability Indicators program (CESI)</li> <li>Global Freshwater Quality Database (GEMStat)</li> <li>GLObal RIver Chemistry database (GLORICH)</li> <li>European Environment Agency (Waterbase)</li> <li>USGS Water Quality Portal (WQP)</li> </ul>The resulting dataset contains a total of over 14 million observations for 41 different forms of some of the most important water quality parameters, focusing on nutrients, carbon, oxygen and sediments. Supplementary metadata and statistics are provided with the observation time series to improve the usability of the dataset. We report on developing a harmonized schema and reproducible workflow that can be adapted to integrate and harmonize further data sources. We conclude our study with a call for action to extend this dataset and hope that the provided reproducible method of data integration and metadata provenance shall lead as an example.

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Water quality modeling for determination of suitability of water for shrimp farming in tidal rivers

Water Quality Research Journal ◽

10.2166/wqrj.2018.006 ◽

2018 ◽

Vol 54 (1) ◽

pp. 34-46

Author(s):

Navid Dolatabadi Farahani ◽

Hamid Taheri Shahraiyni ◽

Reza Sheikhi

Keyword(s):

Water Quality ◽

Water Channels ◽

Water Quality Modeling ◽

Shrimp Farming ◽

Quality Data ◽

Quality Model ◽

Water Quality Data ◽

Shrimp Culture ◽

Standard Values

Abstract In this study, the water quality of the Bahmanshir River and its water channels where Choebdeh Shrimp Farms (the largest shrimp culture complex in Iran) are located were simulated using MIKE11 software. First, an integrated hydraulic and salinity model of the river and its water channels was developed. Then, Manning and dispersion coefficients of the river were calibrated and validated. The most important parameters in the water quality model were determined by sensitivity analysis and these parameters were calibrated using in situ measured water quality data. The errors of salinity, temperature, nitrate, ammonia and dissolved oxygen (DO) models in the verification step were 7.9, 1.2, 0.34, 0.79 and 12%, respectively. Then, two scenarios were applied to the river and the effects of these scenarios on the water quality of the river and its channels were evaluated. The results demonstrated that the site selection of the shrimp culture complex had been performed well because different scenarios could not affect the water quality in the channels. Finally, the water quality in the channels was compared with the standard values of shrimp survival parameters. All of the parameters in the channels were in the range of standard values except DO, which was slightly under the standard value.

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Innovation Through Collaboration

Water e-Journal ◽

10.21139/wej.2020.018 ◽

2020 ◽

pp. 1-10

Author(s):

Lynne Powell ◽

HanShe Lim ◽

Iain Brown ◽

Tao Huang ◽

Niels C. Munksgaard ◽

...

Keyword(s):

Water Quality ◽

Real Time ◽

Quality Data ◽

Water Quality Data ◽

Management Actions ◽

Urban Catchments ◽

First Time ◽

Industry Community

With little data available on the quality of stormwater discharging from urban catchments to the Great Barrier Reef (GBR), the driver for the Smart Catchments: Saltwater Creek project was “If we don’t monitor, we can’t manage”. To do this, near real-time high-frequency discharge and water quality data are needed. A second driver was to make available, for the first time in a GBR catchment, near real-time water quality data for Council’s management actions but also for the community from an education perspective to engage them in water quality issues. Working collaboratively with industry, community, educators and scientists, the project, led by Cairns Regional Council, fulfils a commitment to the Reef 2050 Long-Term Sustainability Plan. This paper presents a more holistic and effective approach to monitor and manage water quality runoff from urban catchments.

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