Modeller subjectivity and calibration impacts on hydrological model applications: An event-based comparison for a road-adjacent catchment in south-east Norway

Kalantari, Zahra; Lyon, Steve W.; Jansson, Per‐Erik; Stolte, Jannes; French, Helen K.; Folkeson, Lennart; Sassner, Mona

doi:10.1016/j.scitotenv.2014.09.030

Cited by 18 publications

(15 citation statements)

References 27 publications

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“…, ; Hessel, van den Bosch, & Vigiak, ; Hessel & Jetten, ; Kalantari et al . , ; Sheikh, van Loon, Hessel, & Jetten, ). The theory and structure of LISEM were previously described (Baartman et al .…”

Section: Methodsmentioning

confidence: 99%

“…, ; Cuomo et al ., ; Hessel et al . , ; Kalantari et al ., ) and (b) a calibration with additional constraints on expected temporal evolution of K sat1 and n for the successive events (TCS).…”

Section: Methodsmentioning

confidence: 99%

“…The estimation of soil moisture, K sat , and n requires external information (Berthet, Andreassian, Perrin, & Javelle, 2009;Tramblay et al, 2010) or a calibration step for each rainfall-runoff event (Baartman, Jetten, Ritsema, & de Vente, 2012;Cuomo, Della Sala, & Novita, 2015;Kalantari et al, 2015), which may jeopardize the predictive capacity of the model. In a landscape with many land uses, calibration steps may also hamper the selection of a unique set of spatial parameters that best describe the catchment dynamics and may lead to "equifinality" as a result of over-parameterisation (Beven, 2006;Kirchner, 2006).…”

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confidence: 99%

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Improving runoff prediction using agronomical information in a cropped, loess covered catchment

Lefrancq

Dijk²,

Jetten

et al. 2017

Hydrol. Process.

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Predicting runoff hot spots and hot‐moments within a headwater crop‐catchment is of the utmost importance to reduce adverse effects on aquatic ecosystems by adapting land use management to control runoff. Reliable predictions of runoff patterns during a crop growing season remain challenging. This is mainly due to the large spatial and temporal variations of topsoil hydraulic properties controlled by complex interactions between weather, growing vegetation, and cropping operations. This interaction can significantly modify runoff patterns and few process‐based models can integrate this evolution of topsoil properties during a crop growing season at the catchment scale. Therefore, the purpose of this study was to better constrain the event‐based hydrological model Limburg Soil Erosion Model by incorporating temporal constraints for input topsoil properties during a crop growing season (LISEM). The results of the temporal constraint strategy (TCS) were compared with a classical event per event calibration strategy (EES) using multi‐scale runoff information (from plot to catchment). The EES and TCS approaches were applied in a loess catchment of 47 ha located 30 km northeast of Strasbourg (Alsace, France). A slight decrease of the Nash–Sutcliffe efficiency criterion on runoff discharge for TCS compared to EES was counterbalanced by a clear improvement of the spatial runoff patterns within the catchment. This study showed that limited agronomical and climatic information added during the calibration step improved the spatial runoff predictions of an event‐based model. Reliable prediction of runoff source, connectivity, and dynamics can then be derived and discussed with stakeholders to identify runoff hot spots and hot‐moments for subsequent land use and crop management modifications.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Improving runoff prediction using agronomical information in a cropped, loess covered catchment

Lefrancq

Dijk²,

Jetten

et al. 2017

Hydrol. Process.

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“…Hydrodynamical models have many application areas: land use analysis (Kalantari, Lyon, et al, ), climate change analysis (Kalantari, Lyon, et al, ; Kalantari, Briel, et al, ), and flood prediction and rainfall–runoff modeling (Kalantari et al, ; Kalantari, Ferreira, Walsh, Ferreira, & Destouni, ). There are several different software packages that can be used for hydrodynamical modeling.…”

Section: A Sociohydrological Systems Modelmentioning

confidence: 99%

Sociohydrology modeling for complex urban environments in support of integrated land and water resource management practices

et al. 2018

Self Cite

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This paper argues that a systems' thinking and explicit modeling approach is needed to address noted weaknesses (in terms of practicality and usefulness) in integrated water resource management. A process of coupling complex regional land use, economy, and water system interactions in integrated modeling is demonstrated with proof‐of‐concept applications to two urban cases (Chicago and Stockholm). In this uniquely coupled systems model, urban land use scenarios are considered a complex urban system represented by dynamic systems models of land use, economics, and water with a focus on urban environments that include drivers and system feedbacks with implications focused on urban water systems. The integrated model results reveal that the physical availability of land for economic activities (forecasted via a bottom‐up land use change model) and their locations differ sharply from top‐down sectoral‐based economic forecasts. This shows that both human systems (economic and land use planning) and natural systems (land use limitations and associated water implications) need to be considered in order to accurately account for system(s) impacts. For example, flood zone regulations divert land use to other locations, whereas land cover changes can greatly affect the water infiltration characteristics of land surfaces and thereby alter hydrological outcomes. Our results indicate that modeling social and natural processes using a systems approach can provide a more comprehensive understanding of coupled causal mechanisms, impacts, and feedbacks in applications of integrated water resource management.

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“…However, the process of calibration is difficult and subjective [1]. This is partly as a result of modeling errors stemming from different sources such as: correctness and adequacy of the input data [2,3], the model's lack of accounting of relevant physical processes in the watershed [4,5], and also the experience of the modeler in manual calibration [6,7].…”

Section: Introductionmentioning

confidence: 99%

Assessing the Uncertainty of Multiple Input Datasets in the Prediction of Water Resource Components

Kamali

Abbaspour

Yang

2017

Water

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A large number of local and global databases for soil, land use, crops, and climate are now available from different sources, which often differ, even when addressing the same spatial and temporal resolutions. As the correct database is unknown, their impact on estimating water resource components (WRC) has mostly been ignored. Here, we study the uncertainty stemming from the use of multiple databases and their impacts on WRC estimates such as blue water and soil water for the Karkheh River Basin (KRB) in Iran. Four climate databases and two land use maps were used to build multiple configurations of the KRB model using the soil and water assessment tool (SWAT), which were similarly calibrated against monthly river discharges. We classified the configurations based on their calibration performances and estimated WRC for each one. The results showed significant differences in WRC estimates, even in models of the same class i.e., with similar performance after calibration. We concluded that a non-negligible level of uncertainty stems from the availability of different sources of input data. As the use of any one database among several produces questionable outputs, it is prudent for modelers to pay more attention to the selection of input data.

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Modeller subjectivity and calibration impacts on hydrological model applications: An event-based comparison for a road-adjacent catchment in south-east Norway

Cited by 18 publications

References 27 publications

Improving runoff prediction using agronomical information in a cropped, loess covered catchment

Improving runoff prediction using agronomical information in a cropped, loess covered catchment

Sociohydrology modeling for complex urban environments in support of integrated land and water resource management practices

Assessing the Uncertainty of Multiple Input Datasets in the Prediction of Water Resource Components

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