Impact of uncertainty description on assimilating hydraulic head in the MIKE SHE distributed hydrological model

Zhang, Donghua; Madsen, Henrik; Ridler, Marc; Refsgaard, Jens Christian; Jensen, Karsten H.

doi:10.1016/j.advwatres.2015.07.018

Cited by 31 publications

(23 citation statements)

References 35 publications

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“…At quadrat scale, the results of correlation analysis between impervious percentages and However, pattern indices alone may not be sufficient to display the whole city landscape changes, so we introduced the impervious percentage and carried out the research at different scales to obtain the quantitative relationships among landscape indices, impervious percentages and water balance components. Previous studies indicated that the urban green spaces, as a measure to reduce surface runoff and alleviate the negative effects on the hydrology in the process of urbanization, have attracted more attention [19]. In addition, for Beijing, the role of urban wetlands has gradually received great attention from urban planners and managers.…”

Section: Discussionmentioning

confidence: 99%

WetSpass-Based Study of the Effects of Urbanization on the Water Balance Components at Regional and Quadrat Scales in Beijing, China

Zhang

Liu

Cheng

et al. 2017

Water

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Abstract:China is the largest country in terms of population and its booming urbanization has exerted negative effects on ground-surface hydrological processes at different spatial scales, land-use types, and water balance, such as surface runoff, groundwater recharge, and evapotranspiration. However, it is not yet well understood as to how the modifications of the spatial patterns of landscapes affect the water balance on a regional scale. In this study, the water and energy transfer among soil, plants, and atmosphere (WetSpass) model was applied to evaluate the urbanization effects on the water balance on a regional scale by using Beijing as the case city for this current study. The relationships among impervious surfaces, landscape pattern indices, and water balance components were also quantified. Results indicated built-up land in 2012 was 673 km 2 larger than it in 2000, mostly converted from croplands. WetSpass model also indicated the variation rates of annual average surface runoff, evapotranspiration and groundwater recharge were 7%, 0.4% and −2% in the whole Beijing area, while they reached 52%, 6% and −24% in the urban area of Beijing from 2000 to 2012, respectively. At a city scale, four districts-Dongcheng, Xicheng, Chaoyang, and Haidian-were characterized by higher impervious percentage, as reflected by lower groundwater recharge and higher surface runoff than other districts. At quadrat scale, however, groundwater recharge (surface runoff) was negatively (positively) correlated with impervious percentages. For landscape indices, the Aggregation Index was positively correlated with surface runoff and negatively correlated with groundwater recharge while Patch Density Index, Splitting Index, Patch Richness Density Index, and Shannon's Diversity Index presented opposite relationships. The results of this study can help to develop human knowledge about the impacts of urbanization on hydrological cycles on a regional scale.

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Section: Discussionmentioning

confidence: 99%

WetSpass-Based Study of the Effects of Urbanization on the Water Balance Components at Regional and Quadrat Scales in Beijing, China

Zhang

Liu

Cheng

et al. 2017

Water

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“…In general, the framework could also be applied to synthetic perturbations of each ME (defined by a priori statistical distribution). However, the choice of these distributions can strongly affect the outcome and the respective conclusions (Baroni et al, ; Haghnegahdar & Razavi, ; Zhang et al, ). For this reason, we decided to demonstrate the method using practically implementable features as MEs (e.g., better rainfall data).…”

Section: Introductionmentioning

confidence: 99%

What Did Really Improve Our Mesoscale Hydrological Model? A Multidimensional Analysis Based on Real Observations

Francke

Baroni

Brosinsky

et al. 2018

Water Resources Research

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Modelers can improve a model by addressing the causes for the model errors (data errors and structural errors). This leads to implementing model enhancements (MEs), for example, meteorological data based on more monitoring stations, improved calibration data, and/or modifications in process formulations. However, deciding on which MEs to implement remains a matter of expert knowledge. After implementing multiple MEs, any improvement in model performance is not easily attributed, especially when considering different objectives or aspects of this improvement (e.g., better dynamics vs. reduced bias). We present an approach for comparing the effect of multiple MEs based on real observations and considering multiple objectives (MMEMO). A stepwise selection approach and structured plots help to address the multidimensionality of the problem. Tailored analyses allow a differentiated view on the effect of MEs and their interactions. MMEMO is applied to a case study employing the mesoscale hydro‐sedimentological model WASA‐SED for the Mediterranean‐mountainous Isábena catchment, northeast Spain. The investigated seven MEs show diverse effects: some MEs (e.g., rainfall data) cause improvements for most objectives, while other MEs (e.g., land use data) only affect a few objectives or even decrease model performance. Interaction of MEs was observed for roughly half of the MEs, confirming the need to address them in the analysis. Calibration and increasing the temporal resolution showed by far stronger impact than any of the other MEs. The proposed framework can be adopted in other studies to analyze the effect of MEs and, thus, facilitate the identification and implementation of the most promising MEs for comparable cases.

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“…The Karup catchment is a well-studied catchment in terms of model parameterization and model calibration (Refsgaard, 1997;Madsen, 2003;Zhang et al, 2015). A relatively simple model with a fast computation time was developed for this catchment to test and verify various DA methods.…”

Section: Study Areasmentioning

confidence: 99%

Multivariate hydrological data assimilation of soil moisture and groundwater head

Zhang

Madsen

Ridler

et al. 2016

Hydrol. Earth Syst. Sci.

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Abstract. Observed groundwater head and soil moisture profiles are assimilated into an integrated hydrological model. The study uses the ensemble transform Kalman filter (ETKF) data assimilation method with the MIKE SHE hydrological model code. The method was firstly tested on synthetic data in a catchment of less complexity (the Karup catchment in Denmark), and later implemented using data from real observations in a larger and more complex catchment (the Ahlergaarde catchment in Denmark). In the Karup model, several experiments were designed with respect to different observation types, ensemble sizes and localization schemes, to investigate the assimilation performance. The results showed the necessity of using localization, especially when assimilating both groundwater head and soil moisture. The proposed scheme with both distance localization and variable localization was shown to be more robust and provide better results. Using the same assimilation scheme in the Ahlergaarde model, groundwater head and soil moisture were successfully assimilated into the model. The hydrological model with assimilation showed an overall improved performance compared to the model without assimilation.

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Impact of uncertainty description on assimilating hydraulic head in the MIKE SHE distributed hydrological model

Cited by 31 publications

References 35 publications

WetSpass-Based Study of the Effects of Urbanization on the Water Balance Components at Regional and Quadrat Scales in Beijing, China

WetSpass-Based Study of the Effects of Urbanization on the Water Balance Components at Regional and Quadrat Scales in Beijing, China

What Did Really Improve Our Mesoscale Hydrological Model? A Multidimensional Analysis Based on Real Observations

Multivariate hydrological data assimilation of soil moisture and groundwater head

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