scholarly journals On constraining a lumped hydrological model with both piezometry and streamflow: results of a large sample evaluation

2021 ◽  
Author(s):  
Antoine Pelletier ◽  
Vazken Andréassian
Keyword(s):  
Groundwater Level ◽  
Model Calibration ◽  
Additional Data ◽  
Hydrological Model ◽  
Model Performance ◽  
Rainfall Runoff ◽  
Calibration Process ◽  
Level Data ◽  
Streamflow Simulation

Abstract. The role of aquifers in the seasonal and multiyear dynamics of streamflow is undisputed: in many temperate catchments, aquifers store water during the wet periods and release it all year long, making a major contribution to low flows. The complexity of groundwater modelling has long prevented surface hydrological modellers from including groundwater level data, especially in lumped rainfall–runoff models. In this article, we investigate whether using groundwater level data in the daily GR6J model, through a composite calibration framework, can improve the performance of streamflow simulation. We tested the new calibration process on 107 French catchments. Our results show that these additional data are superfluous for streamflow simulation, since for catchments, model performance is not significantly improved. However, parameter stability is ameliorated and the model shows a surprising ability to simulate groundwater level with a satisfying performance, in a wide variety of hydrogeological and hydroclimatic contexts. Finally, we make several recommendations regarding the model calibration process to be used in a given situation.

scholarly journals Information content of stream level class data for hydrological model calibration

2017 ◽  
Vol 21 (9) ◽  
pp. 4895-4905 ◽  
Author(s):  
H. J. Ilja van Meerveld ◽  
Marc J. P. Vis ◽  
Jan Seibert
Keyword(s):  
Time Series ◽  
Citizen Science ◽  
Model Calibration ◽  
Hydrological Model ◽  
Model Performance ◽  
Added Value ◽  
Distributed Data ◽  
Vertical Resolution ◽  
Level Data ◽  
Spatially Distributed

Abstract. Citizen science can provide spatially distributed data over large areas, including hydrological data. Stream levels are easier to measure than streamflow and are likely also observed more easily by citizen scientists than streamflow. However, the challenge with crowd based stream level data is that observations are taken at irregular time intervals and with a limited vertical resolution. The latter is especially the case at sites where no staff gauge is available and relative stream levels are observed based on (in)visible features in the stream, such as rocks. In order to assess the potential value of crowd based stream level observations for model calibration, we pretended that stream level observations were available at a limited vertical resolution by transferring streamflow data to stream level classes. A bucket-type hydrological model was calibrated with these hypothetical stream level class data and subsequently evaluated on the observed streamflow records. Our results indicate that stream level data can result in good streamflow simulations, even with a reduced vertical resolution of the observations. Time series of only two stream level classes, e.g. above or below a rock in the stream, were already informative, especially when the class boundary was chosen towards the highest stream levels. There was some added value in using up to five stream level classes, but there was hardly any improvement in model performance when using more level classes. These results are encouraging for citizen science projects and provide a basis for designing observation systems that collect data that are as informative as possible for deriving model based streamflow time series for previously ungauged basins.

scholarly journals Information content of stream level class data for hydrological model calibration

2017 ◽  
Author(s):  
Ilja van Meerveld ◽  
Marc Vis ◽  
Jan Seibert
Keyword(s):  
Time Series ◽  
Citizen Science ◽  
Model Calibration ◽  
Hydrological Model ◽  
Model Performance ◽  
Added Value ◽  
Data Sets ◽  
Distributed Data ◽  
Vertical Resolution ◽  
Level Data

Abstract. Citizen science can provide spatially distributed data over large areas, including hydrological data. Stream levels are easier to measure than streamflow and can be observed more easily by citizen scientists. However, the challenge with crowd-based stream level data is that observations are taken at irregular time intervals and with a limited vertical resolution. The latter is especially the case at sites where no staff gauge is available and relative stream levels are observed based on (in)visible features in the stream, such as rocks. In order to assess the potential value of crowd-based stream level observations for model calibration, we pretended that stream level observations were available at a limited vertical resolution by transferring streamflow data into stream level classes. A bucket-type hydrological model was calibrated with these hypothetical data sets and subsequently evaluated on the observed streamflow records. Our results indicate that stream level data can result in good streamflow simulations, even with a reduced vertical resolution of the observations. Time series of only two stream level classes, e.g. above or below a rock in the stream, were already informative, especially when the class boundary was chosen towards the highest stream levels. There was some added value in using up to five stream level classes but there was hardly any improvement in model performance when using more level classes. These results are encouraging for citizen science projects and provide a basis for designing observation systems that collect data that are as informative as possible for deriving model-based streamflow time series for previously ungauged basins.

scholarly journals Sensitivity and Performance Analyses of the Distributed Hydrology–Soil–Vegetation Model Using Geomorphons for Landform Mapping

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2032
Author(s):  
Pâmela A. Melo ◽  
Lívia A. Alvarenga ◽  
Javier Tomasella ◽  
Carlos R. Mello ◽  
Minella A. Martins ◽  
...  
Keyword(s):  
Complex Terrain ◽  
Overland Flow ◽  
Hydrological Model ◽  
Model Performance ◽  
Soil Parameters ◽  
Vegetation Model ◽  
Landform Classification ◽  
Physically Based ◽  
And Performance ◽  
Streamflow Simulation

Landform classification is important for representing soil physical properties varying continuously across the landscape and for understanding many hydrological processes in watersheds. Considering it, this study aims to use a geomorphology map (Geomorphons) as an input to a physically based hydrological model (Distributed Hydrology Soil Vegetation Model (DHSVM)) in a mountainous headwater watershed. A sensitivity analysis of five soil parameters was evaluated for streamflow simulation in each Geomorphons feature. As infiltration and saturation excess overland flow are important mechanisms for streamflow generation in complex terrain watersheds, the model’s input soil parameters were most sensitive in the “slope”, “hollow”, and “valley” features. Thus, the simulated streamflow was compared with observed data for calibration and validation. The model performance was satisfactory and equivalent to previous simulations in the same watershed using pedological survey and moisture zone maps. Therefore, the results from this study indicate that a geomorphologically based map is applicable and representative for spatially distributing hydrological parameters in the DHSVM.

scholarly journals SHETRAN and HEC HMS Model Evaluation for Runoff and Soil Moisture Simulation in the Jičinka River Catchment (Czech Republic)

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 872
Author(s):  
Vesna Đukić ◽  
Ranka Erić
Keyword(s):  
Soil Moisture ◽  
Czech Republic ◽  
Hydrological Model ◽  
Flash Flood ◽  
Model Performance ◽  
Rainfall Runoff ◽  
The Czech Republic ◽  
River Catchment ◽  
Hydrological Variable ◽  
Model Structures

Due to the improvement of computation power, in recent decades considerable progress has been made in the development of complex hydrological models. On the other hand, simple conceptual models have also been advanced. Previous studies on rainfall–runoff models have shown that model performance depends very much on the model structure. The purpose of this study is to determine whether the use of a complex hydrological model leads to more accurate results or not and to analyze whether some model structures are more efficient than others. Different configurations of the two models of different complexity, the Système Hydrologique Européen TRANsport (SHETRAN) and Hydrologic Modeling System (HEC-HMS), were compared and evaluated in simulating flash flood runoff for the small (75.9 km2) Jičinka River catchment in the Czech Republic. The two models were compared with respect to runoff simulations at the catchment outlet and soil moisture simulations within the catchment. The results indicate that the more complex SHETRAN model outperforms the simpler HEC HMS model in case of runoff, but not for soil moisture. It can be concluded that the models with higher complexity do not necessarily provide better model performance, and that the reliability of hydrological model simulations can vary depending on the hydrological variable under consideration.

Roles of clay layers in rainfall-runoff processes in a serpentinite headwater catchment

2020 ◽  
Author(s):  
Takahiko Yoshino ◽  
Shin'ya Katsura
Keyword(s):  
Water Flow ◽  
Groundwater Level ◽  
Mineral Soil ◽  
High Water ◽  
Organic Soil ◽  
Rainfall Runoff ◽  
Soil Layers ◽  
Clay Layers ◽  
Headwater Catchment

<p>Rainfall-runoff processes in a headwater catchment have been typically explained by water flow in permeable soil layers (comprised of organic soil layers and mineral soil layers produced by weathering of bedrock) overlying less permeable layers (i.e., bedrock). In a catchment where mineral soils are characterized by clayey materials (e.g., mudstone, slate, and serpentine catchment), it is possible that mineral soil layers function substantially as less permeable layers because of a low permeability of clayey materials. However, roles of clay layers in rainfall-runoff processes in such a headwater catchment are not fully understood. In this study, we conducted detailed hydrological, hydrochemical, and thermal observations in a serpentinite headwater catchment (2.12 ha) in Hokkaido, Northern Japan, where mineral soil layers consisting of thick clay layers (thickness: approximately 1.5 m) produced by weathering of the serpentinite bedrock underlies organic soil layers (thickness: approximately 0.4 m). Saturated hydraulic conductivity (Ks) and water retention curve of these two layers were also measured in a laboratory. The observation results demonstrated that groundwater was formed perennially in the organic soil layers and clay layers. The groundwater level within the organic soil layers and specific discharge of the catchment showed rapid and flashy change in response to rainfall. In contrast, the groundwater level within the clay layers showed slow and small change. Temperature of the groundwater and stream water suggested that water from the depth of the organic soil layers contributed to streamflow. The electric conductivity (EC) of the groundwater in the clay layers was very high, ranging from 321 to 380 µS cmˉ¹. On the other hand, the EC of soil water (unsaturated water stored in the organic soil layers) was relatively low, ranging from 98 to 214 µS cmˉ¹. Hydrograph separation using EC showed that contribution of water emerging from the clay layers to the total streamflow ranged from 31 to 76% in low to high flow periods. Temporal variation in the total head, measured using tensiometers installed at four depths at the ridge of the catchment, indicated that in wet periods when the groundwater level in the organic soil layers was high, water flow from the organic soil layers to the clay layers occurred, whereas, in dry periods, water flow from the clay layers into the organic soil layers occurred. The laboratory measurements showed that the organic soil layers had high Ks (10ˉ² cm sˉ¹) and low water-holding capacity, whereas the clay layers had low Ks (10ˉ⁴ cm sˉ¹) and high water-holding capacity. It can be concluded from these results that clay layers play two roles: (1) forming perched groundwater table and lateral flow on the clay layers (the role of less permeable layers) and (2) supplying water into the organic soil layers in the dry periods (the role of water supplier).</p>

Multi-objective calibration of a distributed eco-hydrological model using several remotely sensed information

2020 ◽  
Author(s):  
Félix Francés ◽  
Carlos Echeverría ◽  
Maria Gonzalez-Sanchis ◽  
Fernando Rivas
Keyword(s):  
Remote Sensing ◽  
Model Calibration ◽  
Hydrological Model ◽  
Model Performance ◽  
Temporal Information ◽  
Temporal Data ◽  
Hydrological Models ◽  
Validation Period ◽  
Spatio Temporal ◽  
Calibration Approach

<p>Calibration of eco-hydrological models is difficult to carry on, even more if observed data sets are scarce. It is known that calibration using traditional trial-and-error approach depends strongly of the knowledge and the subjectivity of the hydrologist, and automatic calibration has a strong dependency of the objective-function and the initial values established to initialize the process.</p><p>The traditional calibration approach mainly focuses on the temporal variation of the discharge at the catchment outlet point, representing an integrated catchment response and provides thus only limited insight on the lumped behaviour of the catchment. It has been long demonstrated the limited capabilities of such an approach when models are validated at interior points of a river basin. The development of distributed eco-hydrological models and the burst of spatio-temporal data provided by remote sensing appear as key alternative to overcome those limitations. Indeed, remote sensing imagery provides not only temporal information but also valuable information on spatial patterns, which can facilitate a spatial-pattern-oriented model calibration.</p><p>However, there is still a lack of how to effectively handle spatio-temporal data when included in model calibration and how to evaluate the accuracy of the simulated spatial patterns. Moreover, it is still unclear whether including spatio-temporal data improves model performance in face to an unavoidable more complex and time-demanding calibration procedure. To elucidate in this sense, we performed three different multiobjective calibration configurations: (1) including only temporal information of discharges at the catchment outlet (2) including both temporal and spatio-temporal information and (3) only including spatio-temporal information. In the three approaches, we calibrated the same distributed eco-hydrological model (TETIS) in the same study area: Carraixet Basin, and used the same multi-objective algorithm: MOSCEM-UA. The spatio-temporal information obtained from satellite has been the surface soil moisture (from SMOS-BEC) and the leaf area index (from MODIS).</p><p>Even though the performance of the first calibration approach (only temporal information included) was slightly better than the others, all calibration approaches provided satisfactory and similar results within the calibration period. To put these results into test, we also validated the model performance by using historical data that was not used to calibrate the model (validation period). Within the validation period, the second calibration approach obtained better performance than the others, pointing out the higher reliability of the obtained parameter values when including spatio-temporal data (in this case, in combination with temporal data) in the model calibration. It is also reliable to mention that the approaches considering only spatio-temporal information provided interesting results in terms of discharges, considering that this variable was not used at all for calibration purposes.</p>

scholarly journals Calibration of hydrological model parameters for ungauged catchments

2007 ◽  
Vol 11 (2) ◽  
pp. 703-710 ◽  
Author(s):  
A. Bárdossy
Keyword(s):  
Hydrological Model ◽  
Model Performance ◽  
Model Parameters ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Ungauged Catchments ◽  
Rainfall Runoff Model ◽  
Climate Statistics ◽  
Runoff Model ◽  
German Part

Abstract. The parameters of hydrological models for catchments with few or no discharge records can be estimated using regional information. One can assume that catchments with similar characteristics show a similar hydrological behaviour and thus can be modeled using similar model parameters. Therefore a regionalisation of the hydrological model parameters on the basis of catchment characteristics is plausible. However, due to the non-uniqueness of the rainfall-runoff model parameters (equifinality), a workflow of regional parameter estimation by model calibration and a subsequent fit of a regional function is not appropriate. In this paper a different approach for the transfer of entire parameter sets from one catchment to another is discussed. Parameter sets are considered as tranferable if the corresponding model performance (defined as the Nash-Sutclife efficiency) on the donor catchment is good and the regional statistics: means and variances of annual discharges estimated from catchment properties and annual climate statistics for the recipient catchment are well reproduced by the model. The methodology is applied to a set of 16 catchments in the German part of the Rhine catchments. Results show that the parameters transfered according to the above criteria perform well on the target catchments.

scholarly journals Integrating remote sensing-derived evapotranspiration and ground-monitored discharge data for the improvement of hydrological modelling: A case study of the Sekong River Basin

2021 ◽  
Author(s):  
Raksmey Ang ◽  
S. Shrestha ◽  
Salvatore Virdis ◽  
Saurav KC
Keyword(s):  
Remote Sensing ◽  
Model Calibration ◽  
Hydrological Model ◽  
Hydrologic Model ◽  
Physically Based Model ◽  
Physically Based ◽  
Streamflow Data ◽  
The Impact ◽  
Streamflow Simulation ◽  
Calibration Approach

This study analyses the efficiency of integrating remotely sensed evapotranspiration into the process of hydrological model calibration. A joint calibration approach, employing both remote sensing-derived evapotranspiration and ground-monitored streamflow data was compared with a conventional ground-monitored streamflow calibration approach through physically-based hydrological, Soil and Water Assessment Tool (SWAT) model setups. The efficacy of the two calibration schemes was investigated in two modelling setups: 1) a physically-based model with only the outlet gauge available for calibration, and 2) a physically-based model with multiple gauges available for calibration. Joint calibration was found to enhance the skill of hydrological models in streamflow simulation compared to ground-monitored streamflow-only calibration at the unsaturated zone in the upstream area, where essential information on evapotranspiration is also required. Additionally, the use of remote sensing-derived evapotranspiration can significantly improve high flow compared to low flow simulation. A more consistent model performance improvement, obtained from using remote sensing-derived evapotranspiration data was found at gauged sites not used in the calibration, due to additional information on spatial evapotranspiration in internal locations being enhanced into a process-based model. Eventually, satellite-based evapotranspiration with fine resolution was found to be competent for calibrating and validating the hydrological model for streamflow simulation in the absence of measured streamflow data for model calibration. Furthermore, the impact of using evapotranspiration for hydrologic model calibration tended to be stronger at the upstream and tributary sub-basins than at downstream sub-basins.

Use of Radar Quantitative Precipitation Estimates (QPEs) for Improved Hydrological Model Calibration and Flood Forecasting

2021 ◽  
Author(s):  
Dayal Wijayarathne ◽  
Paulin Coulibaly ◽  
Sudesh Boodoo ◽  
David Sills
Keyword(s):  
Real Time ◽  
Model Calibration ◽  
Hydrological Model ◽  
Flood Forecasting ◽  
Hydrological Models ◽  
Radar Rainfall ◽  
Precipitation Estimates ◽  
Quantitative Precipitation Estimates ◽  
Streamflow Simulation ◽  
Rainfall Estimates

AbstractFlood forecasting is essential to minimize the impacts and costs of floods, especially in urbanized watersheds. Radar rainfall estimates are becoming increasingly popular in flood forecasting because they provide the much-needed real-time spatially distributed precipitation information. The current study evaluates the use of radar Quantitative Precipitation Estimates (QPEs) in hydrological model calibration for streamflow simulation and flood mapping in an urban setting. Firstly, S-band and C-band radar QPEs were integrated into event-based hydrological models to improve the calibration of model parameters. Then, rain gauge and radar precipitation estimates’ performances were compared for hydrological modeling in an urban watershed to assess radar QPE's effects on streamflow simulation accuracy. Finally, flood extent maps were produced using coupled hydrological-hydraulic models integrated within the Hydrologic Engineering Center- Real-Time Simulation (HEC-RTS) framework. It is shown that the bias correction of radar QPEs can enhance the hydrological model calibration. The radar-gauge merging obtained a KGE, MPFC, NSE, and VE improvement of about + 0.42, + 0.12, + 0.78, and − 0.23, respectively for S-band and + 0.64, + 0.36, + 1.12, and − 0.34, respectively for C-band radar QPEs. Merged radar QPEs are also helpful in running hydrological models calibrated using gauge data. The HEC-RTS framework can be used to produce flood forecast maps using the bias-corrected radar QPEs. Therefore, radar rainfall estimates could be efficiently used to forecast floods in urbanized areas for effective flood management and mitigation. Canadian flood forecasting systems could be efficiently updated by integrating bias-corrected radar QPEs to simulate streamflow and produce flood inundation maps.

scholarly journals Multi-variable SWAT model calibration with remotely sensed evapotranspiration and observed flow

RBRH ◽  
2017 ◽  
Vol 22 (0) ◽  
Author(s):  
Ana Clara Lazzari Franco ◽  
Nadia Bernardi Bonumá
Keyword(s):  
Model Calibration ◽  
Hydrological Model ◽  
Swat Model ◽  
Model Performance ◽  
Low Flow ◽  
Single Variable ◽  
Daily Step ◽  
Streamflow Prediction ◽  
Negro River ◽  
Monthly Streamflow

ABSTRACT Although intrinsic, uncertainty for hydrological model estimation is not always reported. The aim of this study is to evaluate the use of satellite-based evapotranspiration on SWAT model calibration, regarding uncertainty and model performance in streamflow simulation. The SWAT model was calibrated in a monthly step and validated in monthly (streamflow and evapotranspiration) and daily steps (streamflow only). The validation and calibration period covers the years from 2006 to 2009 and the study area is the upper Negro river basin, situated in Santa Catarina and Paraná. SWAT-CUP was used to calibrate and validate the model, using SUFI-2 with KGE (Kling-Gupta Efficiency) as objective function. Different calibration strategies were evaluated, considering single-variable and multi-variable calibration, using streamflow and evapotranspiration. Compared to conventional single-variable calibration (streamflow only), multi-variable calibration (streamflow and evapotranspiration, simultaneously) produce better streamflow performance, especially for low flow periods and daily step validation. Despite that, no evidence of reduction of streamflow prediction uncertainty was observed. SWAT model calibration using solely evapotranspiration still requires further studies.

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