Data assimilation for improved discharge estimates with the wflow_sbm model: a case study of the Overijsselse Vecht river (The Netherlands)

master thesis

Kristina Koronaci (Author), Matthijs Den Toom (Mentor), Nejc Bezak (Commission member), Simon Rusjan (Commission member), Albrecht Weerts (Co-mentor)

Abstract

Extreme hydrological events have become more frequent, as evidenced by the European floods of July 2021, which affected the southern provinces of the Netherlands. The need for improved discharge predictions to be used in operational water management to avoid potential adverse effects of flooding has encouraged researchers to employ several ways to improve hydrological model estimates, including data assimilation. This thesis explores the data assimilation effects in the discharge predictions of the wflow_sbm distributed hydrological model of the Vecht river basin. Additionally, effects on other hydrological states and fluxes like subsurface flow, saturated water depth, and soil moisture were explored spatially. This work presents a methodology for applying data assimilation in a model where water is routed from the surface and subsurface. In contrast, previous studies used a model in which water is routed only via surface water. Ensemble Kalman Filter is used to update the model’s discharge predictions by assimilating external discharge observations. This methodology also explores how the data assimilation effect is influenced by the uncertainty characterization considered in the assimilation framework and other factors like the length of the assimilation window and the number of assimilation locations. A preliminary study of the rainfall data is performed to determine the uncertainties of the chosen rainfall product. A benchmark simulation scenario is then selected after the review of deterministic and ensemble model predictions. Finally, data assimilation experiments are developed after discussing the characterization of the uncertainty model. The results of the model output analysis indicate that streamflow assimilation typically has a positive effect on improving model discharge estimations. Additionally, the Ensemble Kalman Filter update effectively captures the system’s spatial state dynamics for subsurface states and fluxes, such as saturated water depth, soil moisture, etc. Two alternative experimental setups with different assimilation intervals and numbers of assimilated observations are examined concerning how this effect varies over other flow gauge locations. As demonstrated by both experiments, longer assimilation times give better results, with the assimilation effect significantly improving in the final timesteps of the assimilation frame. Furthermore, it is concluded that assimilation of observations near the outlet and interior gauges will improve discharge predictions, whereas assimilation of observations only near the outlet will only improve discharge predictions at a number of stations, typically those that are closer to the assimilation location and those where the wflow sbm model exhibits the same trend as the assimilation station. An uncertainty factor of 2.5 for the precipitation error and 0.1 for the observation error yielded the best results for both experiments. However, this study has several limitations, including assumptions of a perfect model and initial conditions; the way the precipitation and observations error model was derived. As a result, the model gives unrealistic discharge predictions when compensating for the neglected errors. Additionally, a limited number of experiments due to the extensive computational times, attributed to the combination of the OpenDA tool with the distributed model, and the algorithm choice, does not allow the DA impact on the discharge predictions to be judged accurately. Therefore, the final section of this study provides recommendations for future research, suggesting additional experiments with longer assimilation windows; analysis of the spatial correlation structure of precipitation, the use of more statistically reliable techniques to assess the precipitation uncertainties; consideration of the model parameter and initial conditions uncertainty; etc.

Keywords

civil engineering;master thesis;data assimilation;ensemble Kalman Filter;wflow_sbm model;discharge prediction;uncertainty;Vecht River;OpenDA;

Data

Language:	English
Year of publishing:	2022
Typology:	2.09 - Master's Thesis
Organization:	UL FGG - Faculty of Civil and Geodetic Engineering
Publisher:	[K. Koronaci]
UDC:	556.166+556.536(492)(043.3)
COBISS:	124507139
Views:	87
Downloads:	27
Average score:	0 (0 votes)
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Other data

Secondary language:	Slovenian
Secondary title:	Asimilacija podatkov za izboljšane ocene razrešnice z wflow_sbm modelom: študija primera reke Overijsselse Vecht (Nizozemska)
Secondary abstract:	Ekstremni hidrološki dogodki so postali vse pogostejši, kar dokazujejo evropske poplave julija 2021, ki so prizadele južne nizozemske province. Potreba po izboljšanih napovedih izpustov, ki se uporabljajo pri operativnem upravljanju voda, da bi se izognili morebitnim škodljivim učinkom poplav, je spodbudila raziskovalce k uporabi več načinov za izboljšanje ocen hidroloških modelov, vključno z asimilacijo podatkov. Diplomsko delo raziskuje učinke asimilacije podatkov pri napovedih pretoka porazdeljenega hidrološkega modela wflow_sbm porečja reke Vecht. Poleg tega so bili prostorsko raziskani učinki na druga hidrološka stanja in tokove, kot so podzemni tok, globina nasičene vode in vlažnost tal. To delo predstavlja metodologijo za uporabo asimilacije podatkov v modelu, kjer je voda usmerjena s površine in pod površino. V nasprotju s tem so prejšnje študije uporabile model, v katerem je voda speljana le po površinski vodi. Ensemble Kalmanov filter se uporablja za posodobitev napovedi izpustov modela z asimilacijo zunanjih opazovanj izpustov. Ta metodologija raziskuje tudi, kako na učinek asimilacije podatkov vpliva karakterizacija negotovosti, upoštevana v asimilacijskem okviru, in drugi dejavniki, kot sta dolžina asimilacijskega okna in število asimilacijskih lokacij. Izvede se predhodna študija podatkov o padavinah, da se določijo negotovosti izbranega produkta padavin. Po pregledu napovedi determinističnih in ansambelskih modelov se nato izbere primerjalni simulacijski scenarij. Po razpravi o karakterizaciji modela negotovosti so razviti poskusi asimilacije podatkov. Rezultati analize rezultatov modela kažejo, da ima asimilacija toka običajno pozitiven učinek na izboljšanje ocen pretoka modela. Poleg tega posodobitev filtra Ensemble Kalman učinkovito zajame dinamiko prostorskega stanja sistema za stanja in tokove pod površino, kot so globina nasičene vode, vlažnost tal itd. Dve alternativni eksperimentalni nastavitvi z različnimi intervali asimilacije in številom asimiliranih opazovanj sta preučeni glede tega, kako ta učinek razlikuje glede na druge lokacije merilnika pretoka. Kot sta dokazala oba poskusa, dajejo daljši časi asimilacije boljše rezultate, pri čemer se učinek asimilacije znatno izboljša v končnih časovnih korakih okvira asimilacije. Poleg tega je ugotovljeno, da bo asimilacija opazovanj v bližini izpusta in notranjih merilnikov izboljšala napovedi pretoka, medtem ko bo asimilacija opazovanj samo v bližini iztoka izboljšala le napovedi pretoka na številnih postajah, običajno tistih, ki so bližje lokaciji asimilacije, in tistih kjer model wflow sbm kaže enak trend kot asimilacijska postaja. Faktor negotovosti 2,5 za napako padavin in 0,1 za napako opazovanja je dal najboljše rezultate za oba poskusa. Vendar ima ta študija več omejitev, vključno s predpostavkami o popolnem modelu in začetnih pogojih; način, kako je bil izpeljan model napak padavin in opazovanj. Posledično daje model nerealne napovedi praznjenja pri kompenzaciji zanemarjenih napak. Poleg tega omejeno število poskusov zaradi obsežnih računskih časov, pripisanih kombinaciji orodja OpenDA s porazdeljenim modelom, in izbire algoritma ne omogoča natančne ocene vpliva DA na napovedi praznjenja. Zato zadnji del te študije podaja priporočila za prihodnje raziskave in predlaga dodatne poskuse z daljšimi asimilacijskimi okni; analiza prostorske korelacijske strukture padavin, uporaba statistično zanesljivejših tehnik za ocenjevanje padavinske negotovosti; upoštevanje negotovosti parametrov modela in začetnih pogojev; itd.
Secondary keywords:	gradbeništvo;magistrska dela;VOI;asimilacija podatkov;Ensemble Kalman Filter;model wflow_sbm;napoved pretoka;negotovost;reka Vecht;OpenDA;
Type (COBISS):	Master's thesis/paper
Thesis comment:	Univ. v Ljubljani, Fak. za gradbeništvo in geodezijo
Pages:	X, 72 str., [13] str. pril.
ID:	16671184