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Disinformative and Uncertain Data in Global Hydrology: Challenges for Modelling and Regionalisation
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL.
2014 (English)Doctoral thesis, comprehensive summary (Other academic)Alternative title
Desinformativa och osäkra data i global hydrologi : Utmaningar för modellering och regionalisering (Swedish)
Abstract [en]

Water is essential for human well-being and healthy ecosystems, but population growth and changes in climate and land-use are putting increased stress on water resources in many regions. To ensure water security, knowledge about the spatiotemporal distribution of these resources is of great importance. However, estimates of global water resources are constrained by limitations in availability and quality of data. This thesis explores the quality of both observational and modelled data, gives an overview of models used for large-scale hydrological modelling, and explores the possibilities to deal with the scarcity of data by prediction of flow-duration curves.

The evaluation of the quality of observational data for large-scale hydrological modelling was based on both hydrographic data, and model forcing and evaluation data for basins worldwide. The results showed that a GIS polygon dataset outperformed all gridded hydrographic products analysed in terms of representation of basin areas. Through a screening methodology based on the long-term water-balance equation it was shown that as many as 8–43% of the basins analysed displayed inconsistencies between forcing (precipitation and potential evaporation) and evaluation (discharge) data depending on how datasets were combined. These data could prove disinformative in hydrological model inference and analysis.

The quality of key hydrological variables from a numerical weather prediction model was assessed by benchmarking against observational datasets and by analysis of the internal land-surface water budgets of several different model setups. Long-term imbalances were found between precipitation and evaporation on the global scale and between precipitation, evaporation and runoff on both cell and basin scales. These imbalances were mainly attributed to the data assimilation system in which soil moisture is used as a nudge factor to improve weather forecasts.

Regionalisation, i.e. transfer of information from data-rich areas to data-sparse areas, is a necessity in hydrology because of a lack of observed data in many areas. In this thesis, the possibility to predict flow-duration curves in ungauged basins was explored by testing several different methodologies including machine learning. The results were mixed, with some well predicted curves, but many predicted curves exhibited large biases and several methods resulted in unrealistic curves.

Abstract [sv]

Vatten är en förutsättning för människors och ekosystems hälsa, men befolkningsökning och förändringar av klimat och markanvändning förväntas öka trycket på vattenresurserna i många regioner i världen. För att kunna säkerställa en god tillgång till vatten krävs kunskap om hur dessa resurser varierar i tid och rum. Tillförlitligheten hos skattningar av globala vattenresurser begränsas dock både av begränsad tillgänglighet av och kvalitet hos observerade data. Denna avhandling utforskar kvaliteten av såväl observations- som modellbaserade data, ger en överblick över modeller som används för storskalig hydrologisk modellering och utforskar möjligheterna att förutsäga varaktighetskurvor som ett sätt att hantera bristen på data i många områden.

Utvärderingen av observationsbaserade datas kvalitet baserades på hydrografiska data och driv- och utvärderingsdata för storskaliga hydrologiska modeller. Resultaten visade att en uppsättning data över hydrografin baserad på GIS-polygoner representerade avrinningsområdesareorna bättre än alla de som byggde på rutor. En metod baserad på långtidsvattenbalansen identifierade att kombinationen av drivdata (nederbörd och potentiell avdunstning) och utvärderingsdata (vattenföring) var fysiskt orimlig för så många som 8–43 % av de analyserade avrinningsområdena beroende på hur olika datauppsättningar kombinerades. Sådana data kan vara desinformativa för slutsatser som dras av resultat från hydrologiska modeller och analyser.

Kvaliteten hos hydrologiskt viktiga variabler från en numerisk väderprognosmodell utvärderades dels genom jämförelser med observationsdata och dels genom analys av landytans vattenbudget för ett flertal olika modellvarianter. Resultaten visade obalanser mellan långtidsvärden av nederbörd och avdunstning i global skala och mellan långtidsvärden av nederbörd, avdunstning och avrinning i både modellrute- och avrinningsområdesskala. Dessa obalanser skulle till stor del kunna förklaras av den data assimilering som görs, i vilken markvattenlagret används som en justeringsfaktor för att förbättra väderprognoserna.

Regionalisering, som innebär en överföring av information från områden med god tillgång på mätdata till områden med otillräcklig tillgång, är i många fall nödvändig för hydrologisk analys på grund av att mätdata saknas i många områden. I denna avhandling utforskades möjligheten att förutsäga varaktighetskurvor för avrinningsområden utan vattenföringsdata genom flera metoder inklusive maskininlärning. Resultaten var blandade med en del kurvor som förutsas väl, och andra kurvor som visade stora systematiska avvikelser. Flera metoder resulterade i orealistiska kurvor (ickemonotona eller med negativa värden).

 

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2014. , 79 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1211
Keyword [en]
Data uncertainty, Discharge, Disinformative data, Evaporation, Flow-duration curve, Global hydrology, Neural networks, Numerical weather prediction, Precipitation, Quality control, Regionalisation, Ungauged basins, Water balance
Keyword [sv]
Avdunstning, avrinningsområden utan vattenföringsdata, dataosäkerhet, desinformativa data, global hydrologi, kvalitetskontroll, nederbörd, neurala nät, numerisk vädermodell, regionalisering, varaktighetskurva, vattenbalans, vattenföring
National Category
Oceanography, Hydrology, Water Resources
Research subject
Hydrology
Identifiers
URN: urn:nbn:se:uu:diva-236864ISBN: 978-91-554-9121-5 (print)OAI: oai:DiVA.org:uu-236864DiVA: diva2:766354
Public defence
2015-01-23, Hambergsalen, Villavägen 16, Uppsala, 10:00 (English)
Opponent
Supervisors
Available from: 2014-12-22 Created: 2014-11-24 Last updated: 2015-02-03
List of papers
1. Smiling in the rain: Seven reasons to be positive about uncertainty in hydrological modelling
Open this publication in new window or tab >>Smiling in the rain: Seven reasons to be positive about uncertainty in hydrological modelling
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2013 (English)In: Hydrological Processes, ISSN 0885-6087, E-ISSN 1099-1085, Vol. 27, no 7, 1117-1122 p.Article in journal (Refereed) Published
Keyword
uncertainty, hydrological modelling, models, data, education, decision, support
National Category
Natural Sciences Oceanography, Hydrology, Water Resources
Research subject
Hydrology
Identifiers
urn:nbn:se:uu:diva-189022 (URN)10.1002/hyp.9625 (DOI)000316568000013 ()
Available from: 2012-12-21 Created: 2012-12-21 Last updated: 2017-12-06
2. Disinformative data in large-scale hydrological modelling
Open this publication in new window or tab >>Disinformative data in large-scale hydrological modelling
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2013 (English)In: Hydrology and Earth System Sciences, ISSN 1027-5606, E-ISSN 1607-7938, Vol. 17, no 7, 2845-2857 p.Article in journal (Refereed) Published
Abstract [en]

Large-scale hydrological modelling has become an important tool for the study of global and regional water resources, climate impacts, and water-resources management. However, modelling efforts over large spatial domains are fraught with problems of data scarcity, uncertainties and inconsistencies between model forcing and evaluation data. Model-independent methods to screen and analyse data for such problems are needed. This study aimed at identifying data inconsistencies in global datasets using a pre-modelling analysis, inconsistencies that can be disinformative for subsequent modelling. The consistency between (i) basin areas for different hydrographic datasets, and (ii) between climate data (precipitation and potential evaporation) and discharge data, was examined in terms of how well basin areas were represented in the flow networks and the possibility of water-balance closure. It was found that (i) most basins could be well represented in both gridded basin delineations and polygon-based ones, but some basins exhibited large area discrepancies between flow-network datasets and archived basin areas, (ii) basins exhibiting too-high runoff coefficients were abundant in areas where precipitation data were likely affected by snow undercatch, and (iii) the occurrence of basins exhibiting losses exceeding the potential-evaporation limit was strongly dependent on the potential-evaporation data, both in terms of numbers and geographical distribution. Some inconsistencies may be resolved by considering subgrid variability in climate data, surface-dependent potential-evaporation estimates, etc., but further studies are needed to determine the reasons for the inconsistencies found. Our results emphasise the need for pre-modelling data analysis to identify dataset inconsistencies as an important first step in any large-scale study. Applying data-screening methods before modelling should also increase our chances to draw robust conclusions from subsequent model simulations.

National Category
Natural Sciences
Identifiers
urn:nbn:se:uu:diva-206677 (URN)10.5194/hess-17-2845-2013 (DOI)000322376000031 ()
Available from: 2013-09-03 Created: 2013-09-02 Last updated: 2017-12-06Bibliographically approved
3. Technical review of large-scale hydrological models for implementation in operational flood forecasting schemes on continental level
Open this publication in new window or tab >>Technical review of large-scale hydrological models for implementation in operational flood forecasting schemes on continental level
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(English)Article in journal (Other academic) Submitted
National Category
Oceanography, Hydrology, Water Resources
Identifiers
urn:nbn:se:uu:diva-236863 (URN)
Available from: 2014-11-24 Created: 2014-11-24 Last updated: 2015-02-03
4. Imbalanced land-surface water budgets in a numerical weather prediction system
Open this publication in new window or tab >>Imbalanced land-surface water budgets in a numerical weather prediction system
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(English)Article in journal (Other academic) Submitted
National Category
Natural Sciences Oceanography, Hydrology, Water Resources
Identifiers
urn:nbn:se:uu:diva-236860 (URN)
Available from: 2014-11-24 Created: 2014-11-24 Last updated: 2015-02-03
5. Regionalisation of flow-duration curves on global scale – assessment of methods
Open this publication in new window or tab >>Regionalisation of flow-duration curves on global scale – assessment of methods
(English)Manuscript (preprint) (Other academic)
National Category
Oceanography, Hydrology, Water Resources
Identifiers
urn:nbn:se:uu:diva-236866 (URN)
Available from: 2014-11-26 Created: 2014-11-24 Last updated: 2015-02-03

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