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- Quesada Montano, Beatriz, et al.
(författare)
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Can climate variability information constrain a hydrological model for an ungauged Costa Rican catchment?
- 2018
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Ingår i: Hydrological Processes. - : WILEY. - 0885-6087 .- 1099-1085. ; 32:6, s. 830-846
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Tidskriftsartikel (refereegranskat)abstract
- Long-term hydrological data are key to understanding catchment behaviour and for decision making within water management and planning. Given the lack of observed data in many regions worldwide, such as Central America, hydrological models are an alternative for reproducing historical streamflow series. Additional types of informationto locally observed dischargecan be used to constrain model parameter uncertainty for ungauged catchments. Given the strong influence that climatic large-scale processes exert on streamflow variability in the Central American region, we explored the use of climate variability knowledge as process constraints to constrain the simulated discharge uncertainty for a Costa Rican catchment, assumed to be ungauged. To reduce model uncertainty, we first rejected parameter relationships that disagreed with our understanding of the system. Then, based on this reduced parameter space, we applied the climate-based process constraints at long-term, inter-annual, and intra-annual timescales. In the first step, we reduced the initial number of parameters by 52%, and then, we further reduced the number of parameters by 3% with the climate constraints. Finally, we compared the climate-based constraints with a constraint based on global maps of low-flow statistics. This latter constraint proved to be more restrictive than those based on climate variability (further reducing the number of parameters by 66% compared with 3%). Even so, the climate-based constraints rejected inconsistent model simulations that were not rejected by the low-flow statistics constraint. When taken all together, the constraints produced constrained simulation uncertainty bands, and the median simulated discharge followed the observed time series to a similar level as an optimized model. All the constraints were found useful in constraining model uncertainty for anassumed to beungauged basin. This shows that our method is promising for modelling long-term flow data for ungauged catchments on the Pacific side of Central America and that similar methods can be developed for ungauged basins in other regions where climate variability exerts a strong control on streamflow variability.
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| 2. |
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| 3. |
- Quesada Montano, Beatriz, et al.
(författare)
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Characterising droughts in Central America with uncertain hydro-meteorological data
- 2019
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Ingår i: Journal of Theoretical and Applied Climatology. - : Springer Science and Business Media LLC. - 0177-798X .- 1434-4483. ; 137:3-4, s. 2125-2138
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Tidskriftsartikel (refereegranskat)abstract
- Central America is frequently affected by droughts that cause significant socio-economic and environmental problems. Drought characterisation, monitoring and forecasting are potentially useful to support water resource management. Drought indices are designed for these purposes, but their ability to characterise droughts depends on the characteristics of the regional climate and the quality of the available data. Local comprehensive and high-quality observational networks of meteorological and hydrological data are not available, which limits the choice of drought indices and makes it important to assess available datasets. This study evaluated which combinations of drought index and meteorological dataset were most suitable for characterising droughts in the region. We evaluated the standardised precipitation index (SPI), a modified version of the deciles index (DI), the standardised precipitation evapotranspiration index (SPEI) and the effective drought index (EDI). These were calculated using precipitation data from the Climate Hazards Group Infra-Red Precipitation with Station (CHIRPS), the CRN073 dataset, the Climate Research Unit (CRU), ECMWF Reanalysis (ERA-Interim) and a regional station dataset, and temperature from the CRU and ERA-Interim datasets. The gridded meteorological precipitation datasets were compared to assess how well they captured key features of the regional climate. The performance of all the drought indices calculated with all the meteorological datasets was then evaluated against a drought index calculated using river discharge data. Results showed that the selection of database was more important than the selection of drought index and that the best combinations were the EDI and DI calculated with CHIRPS and CRN073. Results also highlighted the importance of including indices like SPEI for drought assessment in Central America.
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| 4. |
- Quesada-Montano, Beatriz, 1984-
(författare)
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Hydro-Climatic Variability and Change in Central America : Supporting Risk Reduction Through Improved Analyses and Data
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Floods and droughts are frequent in Central America and cause large social, economic and environmental impacts. A crucial step in disaster risk reduction is to have a good understanding of the causing mechanisms of extreme events and their spatio-temporal characteristics. For this, a key aspect is access to a dense network of long and good-quality hydro-meteorological data. Unfortunately, such ideal data are sparse or non-existent in Central America. In addition, the existing methods for hydro-climatic studies need to be revised and/or improved to find the most suitable for the region’s climate, geography and hydro-climatic data situation. This work has the ultimate goal to support the reduction of risks associated with hydro-climatic-induced disasters in Central America. This was sought by developing ways to reduce data-related uncertainties and by improving the available methods to study and understand hydro-climatic variability processes. In terms of data-uncertainty reduction, this thesis includes the development of a high resolution air temperature dataset and a methodology to reduce uncertainties in a hydrological model at ungauged basins. The dataset was able to capture the spatial patterns with a detail not available with existing datasets. The methodology significantly reduced uncertainties in an assumed-to-be ungauged catchment. In terms of methodological improvements, this thesis includes an assessment of the most suitable combination of (available) meteorological datasets and drought indices to characterise droughts in Central America. In addition, a methodology was developed to analyse drought propagation in a tropical catchment, in an automated, objective way. Results from the assessment and the drought propagation analysis contributed with improving the understanding of drought patterns and generating processes in the region. Finally, a methodology was proposed for assessing changes in both hydrological extremes in a consistent way. This contrasts with most commonly used frameworks that study each extreme individually. The method provides important characteristics (frequency, duration and magnitude), information that can be useful for decisions within risk reduction and water management. The results presented in this thesis are a contribution, in terms of hydro-climatic data and assessment methods, for supporting risk reduction of disasters related with hydro-climatic extremes in Central America.
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