quality assurance checklist (quack) - reporting · (fowler et al., 2007; chen et al., 2011; forbes...

Version: 2.0

Copernicus Climate Change Service – Global Impacts

Quality Assurance Checklist (QUACK) - reporting

What is QUACK:

This tool is developed for the showcases of in C3S_422_Lot1_SMHI to promote high quality in each showcase

For a set of quality indicators it offers you structured questions in combination with guidance material

How to apply QUACK*:

For each quality indicator you will find assessment questions. Please state if they apply for your showcase.

For each assessment question; you will find supporting material under: http://climateservice-global.eu/quality-assurance/

Give a short description about how you treated the quality indicators

Wherever possible – provide any documents, links, scripts, etc. that support your performance

Note: Please save the file name as: Organization_Country_QUACK_reporting (e.g SMHI_Sweden_QUACK_reporting.docx)

*in case you have any questions contact: [email protected]

http://climateservice-global.eu/quality-assurance/

Copernicus Climate Change Service - C3S_422_Lot1_SMHI

Version: 2.0

reporting Version: 2.0

Showcase name: Health, Food and Water Security in South Africa

Short description of a showcase: The 3rd highest risk facing the water utility - Umgeni Water - responsible for supplying potable water to consumers within the uMngeni catchment, including those in the greater Durban-Pietermaritzburg area in South Africa, is the potential impact of a changing climate on both the quantity and quality of the water resource. This case study will focus on improving the understanding of the potential changes in water quality in the uMngeni catchment under a future climate.

Organization: University of KwaZulu-Natal (UKZN), South Africa

Reporter name & email: Michele Toucher ([email protected]) Last updated and Place: 17/01/2019, South Africa


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Dimension: Input data

Criterion: Scientific & methodological quality

Quality indicator

Applied

Short description

Supporting documents

Comments

Yes

No

Transparency

Are all data sources referenced? Please provide which category (observation, simulation, etc) of data you used and the source.

Example: Forcing data: Precipitation , Station data, 1 h, 24 stations, national weather service

Simulation: GCM data, 50 km resolution; ensemble of five models; RCP 4.5 and 8.5, provided by C3S_422_Lot1_SMHI

Yes

Observed data for hydrological model configuration is referenced - Daily rainfall – Lynch 2004 - Temperature – Schulze and Maharaj 2004 - Land use – National Land Cover 2000 - Soils – South African Climatology and Agrohydrology Atlas - All other parameters and variables from ACRU User Manual – Schulze 1995 To create future climate projections, Climate Impact Indicators produced within the C3S_422_Lot1_SMHI contract and available in the CDS catalogue were used and are referenced to this.

Lynch, S. D.: The Development of a Raster Database of Annual, Monthly and Daily Rainfall for Southern Africa, Water Research Commission, South Africa, Rep. 1156/1/04, 2004. Schulze, R. E. and Maharaj, M.: Development of a Database of Gridded Daily Temperatures for Southern Africa, Water Research Commission, South Africa, Rep. 1156/2/04, 83 pp, 2004. National Land Cover (NLC): Produced by CSIR and ARC


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consortium, South Africa, 2000. Schulze, R. E., Maharaj, M., Warburton, M. L., Gers, C. J., Horan, M. J. C., Kunz, R. P. and Clark, D. J.: Electronic data accompanying the South African Atlas of Climatology and Agrohydrology, Water Research Commission, South Africa, Rep. 1489/1/08, 2008. Schulze, R.E. (Ed.): Hydrology and Agrohydrology: A Text to Accompany the ACRU 3.00 Agrohydrological Modelling System. Water Research Commission, South Africa, 552 pp, 1995.

Do the metadata follow international standards?

Yes

No No the historical data used in the study does not have accompanying metadata which meets international standards. However, it is the most widely used and accepted sources of historical data for South Africa. The CII’s available in the CDS catalogue have metadata that follows international standards.

The historical data has detailed reports (references given above).


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Appropriateness

Are the used data appropriate for the case study in terms of spatial and temporal scale?

Yes Distributed model designed for catchment links and flows running at a daily rainfall to give daily runoff and other variables.

Schulze, R.E. (Ed.): Hydrology and Agrohydrology: A Text to Accompany the ACRU 3.00 Agrohydrological Modelling System. Water Research Commission, South Africa, 552 pp, 1995. Smithers, J. C. and Schulze, R. E.: ACRU Agrohydrological Modelling System: User Manual Version 4.00, School of Bioresources Engineering and Environmental Hydrology, University of KwaZulu-Natal, South Africa, 2004.

Completeness

Is the technical consistency checked (no outliers, no gaps in time series, etc.)?

Yes The historical climate data used has been extensively error checked by Lynch (2004) and Schulze and Maharaj (2004).

Lynch, S. D.: The Development of a Raster Database of Annual, Monthly and Daily Rainfall for Southern Africa, Water Research Commission, South Africa, Rep. 1156/1/04, 2004.


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Schulze, R. E. and Maharaj, M.: Development of a Database of Gridded Daily Temperatures for Southern Africa, Water Research Commission, South Africa, Rep. 1156/2/04, 83 pp, 2004.

Do you have all available data sets considered?

Yes The best available historical data sets were considered. The CII from all 19 GCMs for both the RCP 4.5 and RCP 8.5 scenarios were considered. The time horizon was limited to 2011 – 2040 due to the interests of the client.


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Dimension: Processing


Quality indicator

Applied

Short description


Comments

Yes

No

Transparency

Are the processing steps (i.e. scripts) well documented and reproducible?

Yes Those completed are documented. The ACRU model is freely available and can be downloaded from http://cwrr.ukzn.ac.za/resources/acru The ACRU user manual details the specifics needed for model configuration. The model configuration for the uMngeni catchment is available on request and thus the outputs can be reproduced.

http://cwrr.ukzn.ac.za/resources/acru Schulze, R.E. (Ed.): Hydrology and Agrohydrology: A Text to Accompany the ACRU 3.00 Agrohydrological Modelling System. Water Research Commission, South Africa, 552 pp, 1995. Smithers, J. C. and Schulze, R. E.: ACRU Agrohydrological Modelling System:

http://cwrr.ukzn.ac.za/resources/acru




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User Manual Version 4.00, School of Bioresources Engineering and Environmental Hydrology, University of KwaZulu-Natal, South Africa, 2004.

Are the applied methods well documented and follow scientific standards (i.e. peer reviewed)?

Yes The applied methods for configuring the model and running it adhered to the user manual.


Appropriateness

Are the used methods, for instance bias-adjustment, appropriate for the case study?

Yes The use of a distributed hydrological model designed for catchment links and flows running at a daily rainfall to give daily runoff and other variables was the most appropriate method to determine changes in water quality. The decision was taken to employ the commonly used “change factor” method (Fowler et al., 2007; Chen et al., 2011; Forbes et al., 2011) of statistical downscaling to derive the future climate files for input to the ACRU model from

Chen, J, Brissette, FP and Leconte, R. 2011. Uncertainty of downscaling method in quantifying the impact of climate change on hydrology. Journal of Hydrology 401(3-4):190-202. Forbes, KA, Kienzle, SW, Coburn, CA, Byrne, JM and Rasmussen, J.




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the available GCM information as the change factor method of downscaling is the most widely used method for impact analysis (Chen et al., 2011).

2011. Simulating the hydrological response to predicted climate change on a watershed in southern Alberta, Canada. Climatic Change 105(3-4):555-576. Fowler, HJ, Blenkinsop, S and Tebaldi, C. 2007. Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling. International Journal of Climatology 27(12):1547-1578.

Accuracy/Robustness

Are the uncertainties assessed systematically in a standard manner?

The full set of GCM outputs were used as input to the hydrological model. The RCP 8.5 scenarios results are included in the showcase. The median and the range between the 25th and 75th percentile are displayed to provide an indication of the uncertainties.


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Is the case study based on different global or regional climate model simulations? In case that not all simulations of an ensemble are used, is the selection well explained and justified?

Yes Global climate model simulations. All available GCM outputs available in the CDS catalogue were used.

Is the showcase using climate emission scenarios i.e. a low, medium and high scenario? (Please specify the name of scenarios used in the showcase).

Both the RCP 4.5 and RCP 8.5 emissions scenarios were used for all available GCM outputs, however, only the RCP 8.5 emissions scenarios are included in the showcase.

Validation

Is validation possible for the showcase? Is there a procedure in place for a validation against independent data?

Yes

As this is initially run using a historical data set, the model results are compared to the gauged observed runoff to ensure robustness.

Reflectivity

Is the scientific consistency among multiple data sets and

Yes

The climate changes have been compared to Archer et al. (2018) which presents regional results of climate change impacts for southern Africa.

Archer, E., Engelbrecht, F., Hänsler, A., Landman, W., Tadross, M. & Helmschrot, J.


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their findings well documented? (i.e. comparing your results to the existing peer reviewed studies in the region)

(2018) Seasonal prediction and regional climate projections for southern Africa. In: Climate change and adaptive land management in southern Africa – assessments, changes, challenges, and solutions (ed. by Revermann, R., Krewenka, K.M., Schmiedel, U., Olwoch, J.M., Helmschrot, J. & Jürgens, N.), pp. 14–21, Biodiversity & Ecology, 6, Klaus Hess Publishers, Göttingen & Windhoek. (14) Seasonal prediction and regional climate projections for southern Africa.


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Criterion: Practical Relevance

Suitability for target group

Is the relevance for the client assured?

Yes Having recently struggled through a nationwide severe drought, short term management has been the focus of Umgeni Water recently. The philosophy of Umgeni Water, therefore, is to continue planning based on the historical and projected demand information but to “keep an eye” on climate change so that mitigation measures can be included as soon as it becomes apparent that the information is well informed from an improved GCM science and more certainty at the catchment and local scale. Thus, the information produced will assist Umgeni Water to “keep an eye” on the progression of climate change science.


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Dimension: Output


Quality indicator

Applied

Short description


Comments

Yes

No

Transparency

Are the produced results provided with metadata?

Yes Metadata with the links to the ACRU resources are provided.

Are the limits of provided information disclosed?

Yes As this is initially run using a historical data set, the model results are compared to the gauged observed runoff to ensure robustness

Consistency

About the visualization of your output: Do the graphics and tables of the presentation match the captions and explanations?

Yes The results shown in the graphics reflect the text in the captions.


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Reliability

Is the confidence of the data presented (e.g. the spread of the whole ensemble)?

Yes All available GCM scenarios were used as input to the ACRU model and the outputs are available for all.

Criterion: Practical Relevance

Lucidity/Clarity

Is the presentation of your output clear and does It follow visualization standards?

Yes

Given the vast quantity of outputs produced it was difficult to present them all, thus the key indicators were included to ensure clarity of the outputs.

Do the pictures, and maps used match the explanation i.e. story?

Yes The graphs included illustrate the changes in the key parameters and the infographic on water quality illustrated the likely impacts.

Rights of Use

Are the rights of dissemination clarified (i.e. open access)?

Yes All the graphs produced are open

access http://climateservice-

global.eu/ukzn.

http://climateservice-global.eu/ukzn



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Usability

Is the output intuitively presented and freely accessible?

Yes The graphs produced are available through the showcase

http://climateservice-global.eu/ukzn. We do not have the resources to host the time series data.

Criterion: Review Process Review by third party

Are the results of the showcases reviewed externally or internally? To what level the review process was taken.

Yes The ACRU model configuration has been used for other projects where it is has been reviewed by external reference groups.

E.g. WRC funded project – K5/2205: Development and assessment of an integrated water resources accounting methodology for South Africa (http://www.wrc.org.za/mdocs-posts/2205/)


http://www.wrc.org.za/mdocs-posts/2205/

http://www.wrc.org.za/mdocs-posts/2205/


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Dimension: Outcome

Criterion: Satisfaction

Quality indicator

Applied

Short description


Comments

Yes

No

Usefulness

Does the product help for problem solving of your client?

No It is unlikely that it will be used for problem solving by the client given the uncertainties that still exist in the GCM projections of future rainfall. However, it further adds to the clients knowledge around climate change. As noted above, the uMngeni catchment has recently struggled through a severe drought. Short term management has been the focus of Umgeni Water. The philosophy of Umgeni Water, is to continue planning based on the historical and projected demand information but to “keep an eye” on climate change so that mitigation measures can be included as soon as it becomes apparent that the information is well informed from an improved GCM science and more certainty at the catchment and local scale. Thus, the information produced will assist Umgeni Water to “keep an eye” on the progression of climate change science.

quality assurance checklist (quack) - reporting · (fowler et al., 2007; chen et al., 2011; forbes...

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