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Flood Hazard Assessment in Data-Scarce Basins: Use of alternative data and modelling techniques
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences. Centre for Natural Disaster Science (CNDS).ORCID iD: 0000-0002-9943-6140
2017 (English)Doctoral thesis, comprehensive summary (Other academic)Alternative title
Riskbedömning av översvämning i avrinningsområden med dålig datatillgång : Användning av alternativa data och modelleringsverktyg (Swedish)
Abstract [en]

Flooding is of great concern world-wide, causing damage to infrastructure, property and loss of life. Low-income countries, in particular, can be negatively affected by flood events due to their inherent vulnerabilities. Moreover, data to perform studies for flood risk management in low-income regions are often scarce or lacking sufficient quality.

This thesis proposes new methodologies and explores the use of unconventional sources of information in flood hazard assessment in areas where the quantity or sufficient quality of traditional hydrometrical data are lacking. 

One method was developed to account for errors in spatially averaged rainfall, from a sparse rain-gauge network, used as input to a rainfall-runoff model. A spatially-averaged and event-dependent rainfall depth multiplier led to improvements of the hydrographs at calibration. And by using a distribution of the multiplier, identified from previous events in the catchment, improvement in predictions could also be obtained.

A second method explored the possibility of reproducing an unmeasured extreme flood event using a combination of models, post-event data, precipitation and an uncertainty-analysis framework. This combination allowed the identification of likelihood-associated parameter sets from which the flood hazard map for the extreme event could be obtained.

A third and fourth study made at the regional scale explored the value of catchment similarities, and the effects of climate on the hydrological response of catchments.

Flood frequency curves were estimated for 36 basins, assumed ungauged, using regional information of short flow records, and local information about the frequency of the storm. In the second regional study, hydro-climatic information provided great value to constrain predictions of series of daily flow from a hydrological model.

Previously described methods, used in combination with unconventional information within an uncertainty analysis, proven to be useful for flood hazard assessment at basins with data limitations. The explored data included: post-event measurements of an extreme flood event, hydro-climate regional information and local precipitation data. The methods presented in this thesis are expected to support development of hydrological studies underpinning flood-risk reduction in data-poor areas.

Abstract [sv]

Extremt höga vattenflöden ställer till stora problem i hela världen. De skadar infrastruktur och egendom och orsakar död. Framför allt kan låg- och medelinkomstländer vara väldigt sårbara för extrema flöden. I dessa länder saknas dessutom ofta data som behövs för att kunna bedöma översvämningsrisker, eller så finns bara data av dålig kvalitet.

Denna avhandling föreslår nya metoder som använder okonventionella informationskällor vid bedömning av översvämningsrisker i områden där traditionella hydrologiska data saknas eller har otillräcklig kvalitet.

En metod utvecklades för att ta hänsyn till fel i rumslig medelnederbörd beräknad från ett glest nät av nederbördsmätare att användas som indata i en nederbörds-avrinningsmodell. Användning av en multiplikator för medelvärdesbildad nederbörd, i tid och rum, för enskilda högflödestillfällen ledde till förbättrad modellkalibrering. Genom att använda multiplikatorfördelningar, identifierade från tidigare högflödestillfällen i avrinningsområdet, kunde också prognoser förbättras.

En andra metod använde sig av möjligheten att reproducera ett extremt högflöde inom ramen för en osäkerhetsanalys med hjälp av en kombination av modeller, nederbördsdata och data som uppmätts i efterhand. Denna kombination gjorde det möjligt att identifiera parametervärdesuppsättningar med hophörande sannolikheter ur vilka det gick att erhålla en översvämningskarta för det höga flödet.

En tredje och fjärde studie i regional skala utforskade värdet av likheter mellan avrinningsområden och hur områdenas hydrologiska gensvar beror av klimatet.

Kurvan för kumulativa högflödesfrekvenser (flood frequency curve, FFC) kunde skattas med hjälp av lokal nederbördsinformation och regional information om korta tidsserier av vattenföring från 36 avrinningsområden som antogs sakna vattenföringsdata. I den andra regionala studien visade sig hydroklimatisk information av värde för att avgränsa godtagbara prognoser för daglig vattenföring från en hydrologisk modell.

Tidigare beskrivna metoder, använda tillsammans med okonventionell information inom ramen för en osäkerhetsanalys, visade sig vara användbara för att bedöma översvämningsrisker i avrinningsområden med databegränsningar. Bland utforskade data fanns: mätningar i efterhand av ett extremt högflöde, hydroklimatisk regional information och lokala nederbördsmätningar. Metoderna i denna avhandling förväntas kunna stödja utvecklingen av hydrologiska studier av höga flöden och översvämningar i områden med bristande datatillgång.

Abstract [es]

Las inundaciones ocasionan daños a la infraestructura, propiedad y pérdida de vidas a nivel mundial. Los países en desarrollo son los más vulnerables a inundaciones, la calidad y cantidad de datos hidro-climatológicos disponibles en los mismos dificulta el desarrollo de estudios para la evaluación de riesgo a esta amenaza. Esta tesis propone métodos en la que se hace uso de fuentes de información no-convencionales para la evaluación de riesgo por inundación en regiones con datos escasos o limitados.

Un método considera el error asociado a la precipitación promedio sobre cuencas en modelos lluvia-escorrentía como un factor multiplicador del histograma del evento. El uso de la precipitación promedio junto con una distribución probabilística del factor multiplicador como datos de entrada a un modelo de lluvia-escorrentía mejoraron los hidrogramas durante los periodos de calibración y predicción.

Un segundo método exploró la posibilidad de reproducir un evento extremo de inundación usando una combinación de modelos hidrológicos e hidráulico, un análisis de incertidumbre, datos hidrométricos recopilados después del evento y datos de precipitación registrados durante-el-evento. Dicha combinación permitió la identificación de los parámetros de los modelos y la elaboración un mapa de amenaza por inundaciones para dicho evento.

Adicionalmente, se estimaron curvas de frecuencia de inundaciones para 36 cuencas, asumidas no aforadas, mediante un método de regionalización que usa registros de caudal de corta duración disponibles en la región. Dichas curvas fueron extendidas haciendo uso de información local sobre la frecuencia de las tormentas. Se encontró que la información hidro-climatológica tiene un gran valor para reducir el rango de incertidumbre de las simulaciones de caudal diaria de un modelo hidrológico.

Los métodos anteriores se usaron en combinación con información no-convencional dentro de un análisis de incertidumbre y han probado su utilidad para la evaluación de riesgo por inundaciones en cuencas con registros escasos o limitados. Los datos utilizados en esta tesis incluyen datos hidrométricos recopilados pasado el evento, registros hidro-climatológicos regionales y precipitación local. Se espera que los métodos presentados aquí contribuyan al desarrollo de estudios hidrológicos importantes para la reducción del riesgo por inundaciones en regiones con déficit de registros hidro-climatológicos.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2017. , p. 64
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1489
Keywords [en]
Central America, floods, data scarcity, data quality, uncertainty analysis, regionalisation, flood frequency analysis, GLUE, hydraulic modelling, rainfall-runoff modeling, TOPMODEL, LISFLOOD-FP, GRADEX, index-flood, Muskingum-Cunge-Todini flow routing
Keywords [sv]
Mellanamerika, högflöde, datakvalitet, osäkerhetsanalys, regionalisering, frekvensanalys av högflöden, GLUE, hydraulisk modellering, nederbörds-avrinningsmodeller, TOPMODEL, LISFLOOD-FP, GRADEX, indexflöde, Muskingum-Cunge-Todini flödessvarstid
Keywords [es]
Central América, inundaciones, escasez de datos, calidad de los datos, análisis de incertidumbre, regionalización, análisis de frequencia de inundación, GLUE, modelación hidraulica, modelo de lluvia-escorrentía, TOPMODEL, LISFLOOD-FP, GRADEX, índice de inundación, Muskingum-Cunge-Todini rutina de propagación de flujo
National Category
Oceanography, Hydrology and Water Resources
Identifiers
URN: urn:nbn:se:uu:diva-317332ISBN: 978-91-554-9848-1 (print)OAI: oai:DiVA.org:uu-317332DiVA, id: diva2:1081316
Public defence
2017-05-05, Axel Hambergsalen, Earth Sciences Centre, Villavägen 16, Uppsala, 10:00 (English)
Opponent
Supervisors
Funder
Sida - Swedish International Development Cooperation AgencyAvailable from: 2017-04-10 Created: 2017-03-13 Last updated: 2018-01-13
List of papers
1. Can climate variability information constrain a hydrologicalmodel for an ungauged Costa Rican catchment?
Open this publication in new window or tab >>Can climate variability information constrain a hydrologicalmodel for an ungauged Costa Rican catchment?
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(English)In: Hydrological Processes, ISSN 0885-6087, E-ISSN 1099-1085Article in journal (Other academic) Submitted
Place, publisher, year, edition, pages
John Wiley & Sons
Keywords
Uncertainty, ungauged basins, climate variability, hydrological model, Central America, process constraints
National Category
Oceanography, Hydrology and Water Resources
Identifiers
urn:nbn:se:uu:diva-317262 (URN)
Available from: 2017-03-12 Created: 2017-03-12 Last updated: 2018-01-13
2. Regionalized flood frequency analysis: the index-flood and the GRADEX methods combination
Open this publication in new window or tab >>Regionalized flood frequency analysis: the index-flood and the GRADEX methods combination
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2017 (English)Manuscript (preprint) (Other academic)
National Category
Oceanography, Hydrology and Water Resources
Identifiers
urn:nbn:se:uu:diva-317082 (URN)
Available from: 2017-03-09 Created: 2017-03-09 Last updated: 2018-01-13
3. Reproducing an extreme flood with uncertain post-event information
Open this publication in new window or tab >>Reproducing an extreme flood with uncertain post-event information
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2017 (English)In: Hydrology and Earth System Sciences Discussions, ISSN 1812-2108, E-ISSN 1812-2116, Vol. 21, no 7, p. 3597-3618Article in journal (Refereed) Published
Abstract [en]

Studies for the prevention and mitigation of floods require information on discharge and extent of inundation, commonly unavailable or uncertain, especially during extreme events. This study was initiated by the devastating flood in Tegucigalpa, the capital of Honduras, when Hurricane Mitch struck the city. In this study we hypothesized that it is possible to estimate, in a trustworthy way considering large data uncertainties, this extreme 1998 flood discharge and the extent of the inundations that followed from a combination of models and post-event measured data. Postevent data collected in 2000 and 2001 were used to estimate discharge peaks, times of peak, and high-water marks. These data were used in combination with rain data from two gauges to drive and constrain a combination of well-known modelling tools: TOPMODEL, Muskingum-Cunge-Todini routing, and the LISFLOOD-FP hydraulic model. Simulations were performed within the generalized likelihood uncertainty estimation (GLUE) uncertainty-analysis framework. The model combination predicted peak discharge, times of peaks, and more than 90% of the observed highwater marks within the uncertainty bounds of the evaluation data. This allowed an inundation likelihood map to be produced. Observed high-water marks could not be reproduced at a few locations on the floodplain. Identifications of these locations are useful to improve model set-up, model structure, or post-event data-estimation methods. Rainfall data were of central importance in simulating the times of peak and results would be improved by a better spatial assessment of rainfall, e. g. from radar data or a denser rain-gauge net-work. Our study demonstrated that it was possible, considering the uncertainty in the post-event data, to reasonably reproduce the extreme Mitch flood in Tegucigalpa in spite of no hydrometric gauging during the event. The method proposed here can be part of a Bayesian framework in which more events can be added into the analysis as they become available.

National Category
Oceanography, Hydrology and Water Resources
Identifiers
urn:nbn:se:uu:diva-317261 (URN)10.5194/hess-21-3597-2017 (DOI)000405652200001 ()
Funder
Sida - Swedish International Development Cooperation Agency, 54100006Swedish National Infrastructure for Computing (SNIC), p2011010
Available from: 2017-03-12 Created: 2017-03-12 Last updated: 2018-01-13Bibliographically approved
4. Event and model dependent rainfall adjustments to improve discharge predictions
Open this publication in new window or tab >>Event and model dependent rainfall adjustments to improve discharge predictions
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2017 (English)In: Hydrological Sciences Journal, ISSN 0262-6667, E-ISSN 2150-3435, Vol. 62, no 2, p. 232-245Article in journal (Refereed) Published
Abstract [en]

Most conceptual rainfall–runoff models use as input spatially averaged rainfall fields which are typically associated with significant errors that affect the model outcome. In this study, it was hypothesised that a simple spatially and temporally averaged event-dependent rainfall multiplier can account for errors in the rainfall input. The potentials and limitations of this lumped multiplier approach were explored by evaluating the effects of multipliers on the accuracy and precision of the predictive distributions. Parameter sets found to be behavioural across a range of different flood events were assumed to be a good representation of the catchment dynamics and were used to identify rainfall multipliers for each of the individual events. An effect of the parameter sets on identified multipliers was found; however, it was small compared to the differences between events. Accounting for event-dependent multipliers improved the reliability of the predictions. At the cost of a small decrease in precision, the distribution of identified multipliers for past events can be used to account for possible rainfall errors when predicting future events. By using behavioural parameter sets to identify rainfall multipliers, the method offers a simple and computationally efficient way to address rainfall errors in hydrological modelling.

Keywords
rainfall multiplier, rainfall input error, reliability of the predictions, precision of predictions, Topmodel, floods
National Category
Earth and Related Environmental Sciences
Research subject
Earth Science with specialization in Environmental Analysis
Identifiers
urn:nbn:se:uu:diva-291537 (URN)10.1080/02626667.2016.1183775 (DOI)000392602000006 ()
Funder
Sida - Swedish International Development Cooperation Agency, 54100006Swedish National Infrastructure for Computing (SNIC), p2011010
Available from: 2016-05-03 Created: 2016-05-03 Last updated: 2018-09-03Bibliographically approved

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