Using targeted short-term field investigations to calibrate and evaluate the structure of a hydrological model

Hughes, D.A.; Gush, Mark B; Tanner, Jane; Dye, P. J.

doi:10.1002/hyp.9807

Cited by 5 publications

(5 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some authors assumed that a short and intensive field campaign could be carried out in the catchment of interest to collect data for model calibration. They tested the value of combining runoff data and additional data such as groundwater dynamics (Freer et al, 2004;Juston et al, 2009;Seibert and McDonnell, 2013), soil moisture (Hughes et al, 2014) or hydro-chemical tracers (Uhlenbrook and Sieber 2005) for model calibration.…”

Section: Introductionmentioning

confidence: 99%

Prediction of hydrographs and flow-duration curves in almost ungauged catchments: Which runoff measurements are most informative for model calibration?

Pool

Viviroli

Seibert

2017

Journal of Hydrology

View full text Add to dashboard Cite

Applications of runoff models usually rely on long and continuous runoff time series for model calibra-tion. However, many catchments around the world are ungauged and estimating runoff for these catch-ments is challenging. One approach is to perform a few runoff measurements in a previously fully ungauged catchment and to constrain a runoff model by these measurements. In this study we investigated the value of such individual runoff measurements when taken at strategic points in time for applying a bucket-type runoff model (HBV) in ungauged catchments. Based on the assumption that a limited number of runoff measurements can be taken, we sought the optimal sampling strategy (i.e. when to measure the streamflow) to obtain the most informative data for constraining the runoff model. We used twenty gauged catchments across the eastern US, made the assumption that these catchments were ungauged, and applied different runoff sampling strategies. All tested strategies consisted of twelve runoff measurements within one year and ranged from simply using monthly flow maxima to a more complex selection of observation times. In each case the twelve runoff measurements were used to select 100 best parameter sets using a Monte Carlo calibration approach. Runoff simulations using these 'informed' parameter sets were then evaluated for an independent validation period in terms of the Nash-Sutcliffe efficiency of the hydrograph and the mean absolute relative error of the flow-duration curve. Model performance measures were normalized by relating them to an upper and a lower benchmark representing a well-informed and an uninformed model calibration. The hydrographs were best simulated with strategies including high runoff magnitudes as opposed to the flow-duration curves that were generally better estimated with strategies that captured low and mean flows. The choice of a sampling strategy covering the full range of runoff magnitudes enabled hydrograph and flow-duration curve simulations close to a well-informed model calibration. The differences among such strategies covering the full range of runoff magnitudes were small indicating that the exact choice of a strategy might be less crucial. Our study cor-roborates the information value of a small number of strategically selected runoff measurements for sim-ulating runoff with a bucket-type runoff model in almost ungauged catchments.

show abstract

Section: Introductionmentioning

confidence: 99%

Prediction of hydrographs and flow-duration curves in almost ungauged catchments: Which runoff measurements are most informative for model calibration?

Pool

Viviroli

Seibert

2017

Journal of Hydrology

View full text Add to dashboard Cite

show abstract

“…Hughes et al . [] made weekly flow measurements on a small stream in South Africa over an 18 month period and investigated how these data can help better constrain the parameters of the Pitman hydrological model. Temnerud et al .…”

Section: Introductionmentioning

confidence: 99%

“…One can mention a few examples of such situations reported in the literature. Hughes et al [2014] made weekly flow measurements on a small stream in South Africa over an 18 month period and investigated how these data can help better constrain the parameters of the Pitman hydrological model. Temnerud et al [2007] carried out point flow measurements at 66 sites within a 78 km 2 catchment in northern Sweden during a low-flow period to investigate the role of spatial patterns in water quality issues.…”

mentioning

confidence: 99%

How should a rainfall‐runoff model be parameterized in an almost ungauged catchment? A methodology tested on 609 catchments

Serna

Lebecherel

Perrin

et al. 2016

Water Resources Research

View full text Add to dashboard Cite

This paper examines catchments that are almost ungauged, i.e., catchments for which only a small number of point flow measurements are available. In these catchments, hydrologists may still need to simulate continuous streamflow time series using a rainfall‐runoff model, and the methodology presented here allows using few point measurements for model parameterization. The method combines regional information (parameter sets of neighboring gauged stations) and local information (contributed by the point measurements) within a framework where the relative weight of each source of information is made dependent on the number of point measurements available. This approach is tested with two different hydrological models on a set of 609 catchments in France. The results show that on average a few flow measurements can significantly improve the simulation efficiency, and that 10 measurements can reduce the performance gap between the gauged and ungauged situations by more than 50%. The added value of regional information progressively decreases until being almost insignificant when sufficient flow measurements are available. Model parameters tend to come closer to the values obtained by calibration in fully gauged conditions as the number of point flow measurements increases.

show abstract

“…In short, improvement of Q and E simulation capacity appears in most catchments. These improvements have spatial variability (between catchments) and model variability (between models), which are caused by distinct model structures and model parameters (Hughes et al., 2014; Jayathilake & Smith, 2020). The consistent improvement and more balanced performance of simulating Q and E prove the rationality of integrating GCR.…”

Section: Discussionmentioning

confidence: 99%

Improving the Applicability of Lumped Hydrological Models by Integrating the Generalized Complementary Relationship

Lei,

Cheng,

Zhang

et al. 2024

Water Resources Research

View full text Add to dashboard Cite

Lumped hydrological models (LHMs) are indispensable for water resource planning and environmental studies due to simple structures and robust performances. LHMs commonly focus on runoff processes with crude representations for other hydrological processes, such as evapotranspiration (E). Therefore, these models may yield unrealistic water balance partitioning. The challenge is to enhance the LHMs performance while retaining simplicity. The generalized complementary relationship (GCR) is a simple and robust method for estimating E. This study attempted to incorporate GCR into four widely used LHMs (Australian water balance model, GR2M, SIMHYD, and TANK) to test whether the integrated models (GCR‐LHMs) can improve runoff simulation at little cost to the model structure and data requirement. Original LHMs and integrated GCR‐LHMs were tested in 2112 catchments over various climatic conditions. Results show that the GCR‐LHMs outperform original LHMs in most catchments (77.7 ± 5.0%). In addition, the number of catchments that GCR‐LHMs have qualified performance (i.e., Kling‐Gupta coefficient [KGE] more than 0.5) increased by 10.7 ± 3.6% compared with LHMs. The performance of original and integrated models is dependent on the aridity index and normalized vegetation index. However, the improvement in model performance is less catchment characteristics dependent. These results indicate that incorporating GCR into the LHMs improves the model performance under different climatic and vegetation conditions and justifies the integration. GCR integration with LHMs can improve runoff estimation ability (with higher KGE and R‐Square) while retaining model simplicity and readily available input. These findings are valuable for improving the applicability and accuracy of LHMs.

show abstract

Using targeted short-term field investigations to calibrate and evaluate the structure of a hydrological model

Cited by 5 publications

References 33 publications

Prediction of hydrographs and flow-duration curves in almost ungauged catchments: Which runoff measurements are most informative for model calibration?

Prediction of hydrographs and flow-duration curves in almost ungauged catchments: Which runoff measurements are most informative for model calibration?

How should a rainfall‐runoff model be parameterized in an almost ungauged catchment? A methodology tested on 609 catchments

Improving the Applicability of Lumped Hydrological Models by Integrating the Generalized Complementary Relationship

Contact Info

Product

Resources

About