Special Issue "Hydrological Modeling: Beyond Runoff Calibration"

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A special issue of Hydrology (ISSN 2306-5338).

Deadline for manuscript submissions: closed (30 September 2015)

Special Issue Editor

Guest Editor
Dr. Luca Brocca (Website)

Research Institute for Geo-Hydrological Protection, National Research Council, Via della Madonna Alta 126, I-06128 Perugia, Italy
Phone: +39 0755014418
Interests: use of remote sensing observations for hydrological applications; use of soil moisture observations for landslide prediction, erosion, numerical weather prediction; hydrologic and hydraulic modelling; real time flood forecasting; flooding risk analysis; flood frequency assessment (under climate change); optimization and management of hydro-meteorological networks

Special Issue Information

Dear Colleagues,

In the scientific literature, a plethora of hydrological models can be found with different levels of complexity. These models all share one general issue: the difficulty of verifying their reliability when they are applied to study basins with different climates, soils, and land uses. However, the increased availability of new hydrological observations, from in situ and satellite sensors (e.g., data concerning soil moisture, tracers, isotopes, energy fluxes, etc.) allows for unprecedented new opportunities. In fact, most studies still use only runoff data, sometimes over only a limited time period, for calibrating and validating hydrological models. Moreover, these models are built primarily to simulate only runoff. Due to the well-known issue of equifinality, we expect considerable uncertainties from these models’ predictions.

This Special Issue on "Hydrological Modeling: Beyond Runoff Calibration" aims to present a new generation of modeling studies that incorporate and use new hydrological information, provided through experimental hydrologists, so as to foster a constructive dialogue between modelers and experimentalists. Hopefully, other variables, beyond discharge, will be used for controls. This aim does not suggest that new structures or kinds of models should be developed. However, these models should be able to efficiently use newly available information. Utilizing such information effectively will reduce the uncertainties of applying existing models for (real time) flood forecasting and will allow building more robust models that are able to face the new challenges of making predictions under climate change. These benefits will augment the abilities of a wide range of disciplines in which water is an essential agent.

Reviews, recent advances, future trends, and case studies of general interest that address the development and application of these "new generation" hydrological models are welcome. Possible examples are: (1) models that are able to efficiently use and assimilate remote sensing observations (e.g., soil moisture), (2) simplified models that are applied in scarcely gauged catchments, and (3) new flexible models that are able to improve our understanding of river basin hydrological behavior. Some relevant questions that may be addressed by this Special Issue are: (1) Do our models make robust predictions of hydrological cycle components under climate change scenarios? (2) Can we integrate different data sources into our hydrological models for improving their predictions? (3) Do we trust hydrological models enough to apply them in ungauged basins? Finally, an overarching question might be: Can we give reliable hydrological predictions without model calibration?

Dr. Luca Brocca
Guest Editor

Submission

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Hydrology is an international peer-reviewed Open Access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. For the first couple of issues the Article Processing Charge (APC) will be waived for well-prepared manuscripts. English correction and/or formatting fees of 250 CHF (Swiss Francs) will be charged in certain cases for those articles accepted for publication that require extensive additional formatting and/or English corrections.

Keywords

  • hydrological modeling
  • distributed models
  • experimental hydrology
  • remote sensing
  • climate change
  • ungauged basins
  • soil moisture, runoff

Published Papers (6 papers)

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Research

Open AccessArticle Postprocessing of Medium Range Hydrological Ensemble Forecasts Making Use of Reforecasts
Hydrology 2016, 3(2), 21; doi:10.3390/hydrology3020021
Received: 17 December 2015 / Revised: 19 May 2016 / Accepted: 23 May 2016 / Published: 31 May 2016
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Abstract
A hydrological ensemble prediction system is running operationally at the Royal Meteorological Institute of Belgium (RMI) for ten catchments in the Meuse basin. It makes use of the conceptual semi-distributed hydrological model SCHEME and the European Centre for Medium Range Weather Forecasts [...] Read more.
A hydrological ensemble prediction system is running operationally at the Royal Meteorological Institute of Belgium (RMI) for ten catchments in the Meuse basin. It makes use of the conceptual semi-distributed hydrological model SCHEME and the European Centre for Medium Range Weather Forecasts (ECMWF) ensemble prediction system (ENS). An ensemble of 51 discharge forecasts is generated daily. We investigate the improvements attained through postprocessing the discharge forecasts, using the archived ECMWF reforecasts for precipitation and other necessary meteorological variables. We use the 5-member reforecasts that have been produced since 2012, when the horizontal resolution of ENS was increased to the N320 resolution (≈30 km over Belgium). The reforecasts were issued weekly, going back 20 years, and we use a calibration window of five weeks. We use these as input to create a set of hydrological reforecasts. The implemented calibration method is an adaption of the variance inflation method. The parameters of the calibration are estimated based on the hydrological reforecasts and the observed discharge. The postprocessed forecasts are verified based on a two-and-a-half year period of data, using archived 51 member ENS forecasts. The skill is evaluated using summary scores of the ensemble mean and probabilistic scores: the Brier Score and the Continuous Ranked Probability Score (CRPS). We find that the variance inflation method gives a significant improvement in probabilistic discharge forecasts. The Brier score, which measures probabilistic skill for forecasts of discharge threshold exceedance, is improved for the entire forecast range during the hydrological summer period, and the first three days during hydrological winter. The CRPS is also significantly improved during summer, but not during winter. We conclude that it is valuable to apply the postprocessing method during hydrological summer. During winter, the method is also useful for forecasting exceedance probabilities of higher thresholds, but not for lead times beyond five days. Finally, we also note the presence of some large outliers in the postprocessed discharge forecasts, arising from the fact that the postprocessing is performed on the logarithmically transformed discharges. We suggest some ways to deal with this in the future for our operational setting. Full article
(This article belongs to the Special Issue Hydrological Modeling: Beyond Runoff Calibration)
Open AccessArticle Flash Flood Prediction by Coupling KINEROS2 and HEC-RAS Models for Tropical Regions of Northern Vietnam
Hydrology 2015, 2(4), 242-265; doi:10.3390/hydrology2040242
Received: 27 August 2015 / Revised: 2 November 2015 / Accepted: 11 November 2015 / Published: 17 November 2015
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Abstract
Northern Vietnam is a region prone to heavy flash flooding events. These often have devastating effects on the environment, cause economic damage and, in the worst case scenario, cost human lives. As their frequency and severity are likely to increase in the [...] Read more.
Northern Vietnam is a region prone to heavy flash flooding events. These often have devastating effects on the environment, cause economic damage and, in the worst case scenario, cost human lives. As their frequency and severity are likely to increase in the future, procedures have to be established to cope with this threat. As the prediction of potential flash floods represents one crucial element in this circumstance, we will present an approach that combines the two models KINEROS2 and HEC-RAS in order to accurately predict their occurrence. We used a documented event on 23 June 2011 in the Nam Khat and the larger adjacent Nam Kim watershed to calibrate the coupled model approach. Afterward, we evaluated the performance of the coupled models in predicting flow velocity (FV), water levels (WL), discharge (Q) and streamflow power (P) during the 3–5 days following the event, using two different precipitation datasets from the global spectral model (GSM) and the high resolution model (HRM). Our results show that the estimated Q and WL closely matched observed data with a Nash–Sutcliffe simulation efficiency coefficient (NSE) of around 0.93 and a coefficient of determination (R2) at above 0.96. The resulting analyses reveal strong relationships between river geometry and FV, WL and P. Although there were some minor errors in forecast results, the model-predicted Q and WL corresponded well to the gauged data. Full article
(This article belongs to the Special Issue Hydrological Modeling: Beyond Runoff Calibration)
Open AccessArticle Impacts of Forest Fires and Climate Variability on the Hydrology of an Alpine Medium Sized Catchment in the Canadian Rocky Mountains
Hydrology 2015, 2(1), 23-47; doi:10.3390/hydrology2010023
Received: 21 August 2014 / Revised: 4 January 2015 / Accepted: 27 January 2015 / Published: 5 February 2015
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Abstract
This study investigates the hydrology of Castle River in the southern Canadian Rocky Mountains. Temperature and precipitation data are analyzed regarding a climate trend between 1960 and 2010 and a general warming is identified. Observed streamflow has been declining in reaction to [...] Read more.
This study investigates the hydrology of Castle River in the southern Canadian Rocky Mountains. Temperature and precipitation data are analyzed regarding a climate trend between 1960 and 2010 and a general warming is identified. Observed streamflow has been declining in reaction to a decreasing snow cover and increasing evapotranspiration. To simulate the hydrological processes in the watershed, the physically based hydrological model WaSiM (Water Balance Simulation Model) is applied. Calibration and validation provide very accurate results and also the observed declining runoff trend can be reproduced with a slightly differing inclination. Besides climate change induced runoff variations, the impact of a vast wildfire in 2003 is analyzed. To determine burned areas a remote sensing method of differenced burn ratios is applied using Landsat data. The results show good agreement compared to observed fire perimeter areas. The impacts of the wildfires are evident in observed runoff data. They also result in a distinct decrease in model efficiency if not considered via an adapted model parameterization, taking into account the modified land cover characteristics for the burned area. Results in this study reveal (i) the necessity to establish specific land cover classes for burned areas; (ii) the relevance of climate and land cover change on the hydrological response of the Castle River watershed; and (iii) the sensitivity of the hydrological model to accurately simulate the hydrological behavior under varying boundary conditions. By these means, the presented methodological approach is considered robust to implement a scenario simulations framework for projecting the impacts of future climate and land cover change in the vulnerable region of Alberta’s Rocky Mountains. Full article
(This article belongs to the Special Issue Hydrological Modeling: Beyond Runoff Calibration)
Open AccessArticle The Use of H-SAF Soil Moisture Products for Operational Hydrology: Flood Modelling over Italy
Hydrology 2015, 2(1), 2-22; doi:10.3390/hydrology2010002
Received: 2 September 2014 / Accepted: 26 December 2014 / Published: 13 January 2015
Cited by 3 | PDF Full-text (2128 KB) | HTML Full-text | XML Full-text
Abstract
The ever-increasing availability of new remote sensing and land surface model datasets opens new opportunities for hydrologists to improve flood forecasting systems. The current study investigates the performance of two operational soil moisture (SM) products provided by the “EUMETSATSatellite Application Facility in [...] Read more.
The ever-increasing availability of new remote sensing and land surface model datasets opens new opportunities for hydrologists to improve flood forecasting systems. The current study investigates the performance of two operational soil moisture (SM) products provided by the “EUMETSATSatellite Application Facility in Support of Operational Hydrology and Water Management” (H-SAF, http://hsaf.meteoam.it/) within a recently-developed hydrological model called the “simplified continuous rainfall-runoff model” (SCRRM) and the possibility of using such a model at an operational level. The model uses SM datasets derived from external sources (i.e., remote sensing and land surface models) as input for calculating the initial wetness conditions of the catchment prior to the flood event. Hydro-meteorological data from 35 Italian catchments ranging from 800 to 7400 km2 were used for the analysis for a total of 593 flood events. The results show that H-SAF operational products used within SCRRM satisfactorily reproduce the selected flood events, providing a median Nash–Sutcliffe efficiency index equal to 0.64 (SM-OBS-1) and 0.60 (SM-DAS-2), respectively. Given the results obtained along with the parsimony, the simplicity and independence of the model from continuously-recorded rainfall and evapotranspiration data, the study suggests that: (i) SM-OBS-1 and SM-DAS-2 contain useful information for flood modelling, which can be exploited in flood forecasting; and (ii) SCRRM is expected to be beneficial as a component of real-time flood forecasting systems in regions characterized by low data availability, where a continuous modelling approach can be problematic. Full article
(This article belongs to the Special Issue Hydrological Modeling: Beyond Runoff Calibration)
Open AccessArticle Remote Sensing and Ground-Based Weather Forcing Data Analysis for Streamflow Simulation
Hydrology 2014, 1(1), 89-111; doi:10.3390/hydrology1010089
Received: 23 July 2014 / Revised: 20 October 2014 / Accepted: 24 October 2014 / Published: 31 October 2014
Cited by 1 | PDF Full-text (52629 KB) | HTML Full-text | XML Full-text
Abstract
Hydrological simulation, based on weather inputs and the physical characterization of the watershed, is a suitable approach to predict the corresponding streamflow. This work, carried out on four different watersheds, analyzed the impacts of using three different meteorological data inputs in the [...] Read more.
Hydrological simulation, based on weather inputs and the physical characterization of the watershed, is a suitable approach to predict the corresponding streamflow. This work, carried out on four different watersheds, analyzed the impacts of using three different meteorological data inputs in the same model to compare the model’s accuracy when simulated and observed streamflow are compared. Meteorological data from the Daily Global Historical Climatology Network (GHCN-D), National Land Data Assimilation Systems (NLDAS) and the National Operation Hydrological Remote Sensing Center’s Interactive Snow Information (NOHRSC-ISI) were used as an input into the Soil and Water Assessment Tool (SWAT) hydrological model and compared as three different scenarios on each watershed. The results showed that meteorological data from an assimilation system like NLDAS achieved better results than simulations performed with ground-based meteorological data, such as GHCN-D. However, further work needs to be done to improve both the datasets and model capabilities, in order to better predict streamflow. Full article
(This article belongs to the Special Issue Hydrological Modeling: Beyond Runoff Calibration)
Figures

Open AccessArticle From Catchment to National Scale Rainfall-Runoff Modelling: Demonstration of a Hydrological Modelling Framework
Hydrology 2014, 1(1), 63-88; doi:10.3390/hydrology1010063
Received: 19 June 2014 / Revised: 17 July 2014 / Accepted: 26 July 2014 / Published: 5 August 2014
Cited by 2 | PDF Full-text (1723 KB) | HTML Full-text | XML Full-text
Abstract
The increasing availability of digital databases (e.g., of climatology, topography, soils and land use) has enabled research into the generalisation of hydrological model parameter values from physical properties and the development of grid-based models. A hydrological modelling framework (HMF) is being developed [...] Read more.
The increasing availability of digital databases (e.g., of climatology, topography, soils and land use) has enabled research into the generalisation of hydrological model parameter values from physical properties and the development of grid-based models. A hydrological modelling framework (HMF) is being developed to exploit this generalisation and provide a flexible gridded infrastructure, operational over regional, national or larger scales at a range of spatial and temporal resolutions. The capability of the framework is demonstrated through adaptation of an existing semi-distributed catchment-based rainfall-runoff model, CLASSIC, for which a generalised methodology exists to determine parameter values. The main change required was to ensure consistency of parameter values between the runoff procedure in CLASSIC and flow routing in the HMF. Assessment is by comparison of modelled and observed flow at grid points in Britain corresponding to gauging stations, both for catchments previously modelled and for new locations, for a range of catchment areas and physical properties and for four spatial resolutions (10, 5, 2.5 and 1 km). Good model performance is achieved for 90% of catchments tested, with a 5 km resolution proving adequate for catchments larger than 500 km2. Applications are outlined for which the framework could be used to test alternative modelling approaches or undertake consistent studies across the range of resolutions. Full article
(This article belongs to the Special Issue Hydrological Modeling: Beyond Runoff Calibration)

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