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- Westerberg, Ida, 1979-
(författare)
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Observational Uncertainties in Water-Resources Modelling in Central America : Methods for Uncertainty Estimation and Model Evaluation
- 2011
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Knowledge about spatial and temporal variability of hydrological processes is central for sustainable water-resources management, and such knowledge is created from observational data. Hydrologic models are necessary for prediction for time periods and areas lacking data, but are affected by observational uncertainties. Methods for estimating and accounting for such uncertainties in water-resources modelling are of high importance, especially in regions such as Central America. Observational uncertainties were addressed in three ways in this thesis; quality control, quantitative estimation and development of model-evaluation techniques that addressed unquantifiable uncertainties. A first step in any modelling study should be the quality control and concurrent analysis of the representativeness of the observational data. In the characterisation of the precipitation regime in the Choluteca River basin in Honduras, four different quality problems were identified and 22% of the daily data had to be rejected. The monitoring network was found to be insufficient for a comprehensive characterisation of the high spatiotemporal variability of the precipitation regime. Quantitative estimations of data uncertainties can be made when sufficient information is available. Discharge-data uncertainties were estimated with a fuzzy regression for time-variable rating curves and from official rating curves for 35 stations in Honduras. The uncertainties were largest for low flows, as a result of measurement uncertainties and natural variability. A method for calibration with flow-duration curves was developed which enabled calibration to the whole flow range, accounting for discharge uncertainty and calibration with non-overlapping time periods for model input and evaluation data. The method compared favourably to traditional calibration in a test using two models applied in basins with different runoff-generation processes. A post-hoc analysis made it possible to identify potential model-structure errors and periods of disinformative data. Flow-duration curves were regionalised and used for calibration of a Central-American water-balance model. The initial model uncertainty for the ungauged basins was reduced by 70%. Non-representative precipitation data were found to be the main obstacle to comprehensive regional water-resources modelling in Central America. These methods bridged several problems related to observational uncertainties in water-balance modelling. Estimates of prediction uncertainty are an important basis for all types of decisions related to water-resources management.
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| 2. |
- Westerberg, Ida, 1979-, et al.
(författare)
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Reply to Discussion of "Perceptual models of uncertainty for socio-hydrological systems : a flood risk change example"(*)
- 2018
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Ingår i: Hydrological Sciences Journal. - : Informa UK Limited. - 0262-6667 .- 2150-3435. ; 63:13-14, s. 2001-2003
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Ertsen discusses the representation of reality and uncertainty in our paper, raising three critical points. In response to the first, we agree that discussion of different interpretations of the concept of uncertainty is important when developing perceptual models - making different uncertainty interpretations explicit was a key motivation behind our method. Secondly, we do not, as Ertsen suggests, deny anyone who is not a "certified" scientist to have relevant knowledge. The elicitation of diverse views by discussing perceptual models is a basis for open discussion and decision making. Thirdly, Ertsen suggests that it is not useful to treat socio-hydrological systems as if they exist. We argue that we act as "pragmatic realists" in most practical applications by treating socio-hydrological systems as an external reality that can be known. But the uncertainty that arises from our knowledge limitations needs to be recognized, as it may impact on practical decision making and associated costs.
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