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Special Issue "Study for Ungauged Catchments—Data, Models and Uncertainties"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: 31 October 2019.

Special Issue Editors

Guest Editor
Dr. Jong Ahn Chun

APEC Climate Center; Busan 48058, South Korea
Website | E-Mail
Phone: +82-51-745-3957
Interests: hydrological and water quality modelling; uncertainty in model predictions; surface hydrology; flow and solute transport modelling
Guest Editor
Dr. Daeha Kim

APEC Climate Center; Busan 48058, South Korea
E-Mail
Phone: +82-51-745-3983
Interests: hydrologic prediction in ungauged basins; modelling with remote sensing datasets; uncertainty analysis of hydrological model parameters; integrated river basin modelling

Special Issue Information

Dear Colleagues,

An operational system for flood forecasts and simulations has been widely used to minimize catastrophic impacts on humans, infrastructure, and agricultural systems across the globe. Rainfall-runoff models are often employed in flood forecasting systems and applied for assessing the associated risks and impacts. Hence, accurate and reliable runoff predictions by the rainfall-runoff models should be a core component for flood risk management. However, since most catchments around the world still remain ungauged, identifying parameters of the rainfall-runoff models is still a challenge that may lead to substantial uncertainty in runoff predictions. The lack of local hydrologic observations has been always an issue for hydrologic modelers and analyzers to identify parameters of hydrological models.

In this Special Issue of Water, we welcome original and innovative research papers focusing on modelling hydrological processes addressing the ungauged catchment problem associated with uncertainties of hydrological models and their parameters. We expect that this Special Issue will contribute to the improvement of prediction skills and to a reduction in the uncertainty in flood forecasting by advancing our knowledge and understanding of hydrological processes.

Dr. Jong Ahn Chun
Dr. Daeha Kim
Guest Editors

Manuscript Submission Information

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. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short 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 thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • rainfall-runoff modeling
  • flood forecasting
  • uncertainty of hydrological models
  • parameter identification
  • predictions in ungauged catchments

Published Papers (5 papers)

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Research

Open AccessArticle
Small-Scale Rainfall Variability Impacts Analyzed by Fully-Distributed Model Using C-Band and X-Band Radar Data
Water 2019, 11(6), 1273; https://doi.org/10.3390/w11061273
Received: 7 May 2019 / Revised: 2 June 2019 / Accepted: 13 June 2019 / Published: 18 June 2019
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Abstract
Recent studies have highlighted the need for high resolution rainfall measurements for better modelling of urban and peri-urban catchment responses. In this work, we used a fully-distributed model called “Multi-Hydro” to study small-scale rainfall variability and its hydrological impacts. The catchment modelled is [...] Read more.
Recent studies have highlighted the need for high resolution rainfall measurements for better modelling of urban and peri-urban catchment responses. In this work, we used a fully-distributed model called “Multi-Hydro” to study small-scale rainfall variability and its hydrological impacts. The catchment modelled is a semi-urban area located in the southwest region of Paris, an area that has been previously partially validated. At this time, we make some changes to the model, henceforth using its drainage system globally, and we investigate the influence of small-scale rainfall variability by modelling three rainfall events with two different rainfall data inputs: the C-band radar data provided by Météo-France at a 1 km × 1 km × 5 min resolution, and the new X-band radar (recently installed at Ecole des Ponts, France) data at a resolution of 250 m × 250 m × 3.41 min, thereby presenting the gains of better resolution (with the help of Universal Multifractals). Finally, we compare the Multi-Hydro hydrological results with those obtained using an operational semi-distributed model called “Optim Sim” over the same area to revalidate Multi-Hydro modelling, and discuss the model’s limitations and the impacts of data quality and resolution, observing the difficulties associated with semi-distributed models when accounting the spatial variability of weather radar data. This work concludes that it may be useful in future to improve rainfall data acquisition, aiming for better spatio-temporal resolution (now achieved by the weather dual-polarized X-band radars) and data quality when considering small-scale rainfall variability, and to merge deterministic, fully-distributed and stochastic models into a hybrid model which would be capable of taking this small-scale rainfall variability into account. Full article
(This article belongs to the Special Issue Study for Ungauged Catchments—Data, Models and Uncertainties)
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Open AccessArticle
Assessment of Agricultural Drought Considering the Hydrological Cycle and Crop Phenology in the Korean Peninsula
Water 2019, 11(5), 1105; https://doi.org/10.3390/w11051105
Received: 7 April 2019 / Revised: 21 May 2019 / Accepted: 23 May 2019 / Published: 27 May 2019
Cited by 1 | PDF Full-text (7128 KB) | HTML Full-text | XML Full-text
Abstract
Hydrological changes attributable to global warming increase the severity and frequency of droughts, which in turn affect agriculture. Hence, we proposed the Standardized Agricultural Drought Index (SADI), which is a new drought index specialized for agriculture and crops, and evaluated current and expected [...] Read more.
Hydrological changes attributable to global warming increase the severity and frequency of droughts, which in turn affect agriculture. Hence, we proposed the Standardized Agricultural Drought Index (SADI), which is a new drought index specialized for agriculture and crops, and evaluated current and expected droughts in the Korean Peninsula. The SADI applies crop phenology to the hydrological cycle, which is a basic element that assesses drought. The SADI of rice and maize was calculated using representative hydrological variables (precipitation, evapotranspiration, and runoff) of the crop growing season. In order to evaluate the effectiveness of SADI, the three-month Standardized Precipitation Index, which is a representative drought index, and rainfed crop yield were estimated together. The performance evaluation of SADI showed that the correlation between rainfed crop yield and SADI was very high compared with that of existing drought index. The results of the assessment of drought over the past three decades provided a good indication of a major drought period and differentiated the results for crops and regions. The results of two future scenarios showed common drought risks in the western plains of North Korea. Successfully validated SADIs could be effectively applied to agricultural drought assessments in light of future climate change, and would be a good example of the water-food nexus approach. Full article
(This article belongs to the Special Issue Study for Ungauged Catchments—Data, Models and Uncertainties)
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Open AccessArticle
Evaluation of Future Flood Risk According to RCP Scenarios Using a Regional Flood Frequency Analysis for Ungauged Watersheds
Water 2019, 11(5), 992; https://doi.org/10.3390/w11050992
Received: 24 March 2019 / Revised: 30 April 2019 / Accepted: 7 May 2019 / Published: 11 May 2019
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Abstract
According to the accepted climate change scenarios, the future rainfall in the Korean peninsula is expected to increase by 3–10%. The expected increase in rainfall leads to an increase of runoff that is directly linked to the stability of existing and newly installed [...] Read more.
According to the accepted climate change scenarios, the future rainfall in the Korean peninsula is expected to increase by 3–10%. The expected increase in rainfall leads to an increase of runoff that is directly linked to the stability of existing and newly installed hydraulic structures. It is necessary to accurately estimate the future frequency and severity of floods, considering increasing rainfall according to different climate change scenarios. After collecting observed flood data over twenty years in 12 watersheds, we developed a regional frequency analysis (RFA) for ungauged watersheds by adjusting flood quantiles calculated by a design rainfall-runoff analysis (DRRA) using natural flow data as an index flood. The proposed RFA was applied to estimate design floods and flood risks in 113 medium-sized basins in South Korea according to representative concentration pathway (RCP) scenarios. Regarding the future of the Korean peninsula, compared with the present, the flood risks were expected to increase by 24.85% and 20.28% on average for the RCP 8.5 and 4.5 scenarios, respectively. Full article
(This article belongs to the Special Issue Study for Ungauged Catchments—Data, Models and Uncertainties)
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Open AccessArticle
Quantification of Stream Drying Phenomena Using Grid-Based Hydrological Modeling via Long-Term Data Mining throughout South Korea including Ungauged Areas
Water 2019, 11(3), 477; https://doi.org/10.3390/w11030477
Received: 28 January 2019 / Revised: 28 February 2019 / Accepted: 3 March 2019 / Published: 7 March 2019
Cited by 1 | PDF Full-text (50352 KB) | HTML Full-text | XML Full-text
Abstract
The Drying Stream Assessment Tool and Water Flow Tracking (DrySAT-WFT) were modified to simulate the hydrological components of water loss databases (DBs) affecting stream drying phenomena. In this study, the phenomenon is defined based on a method using the 10-day minimum flow (reference [...] Read more.
The Drying Stream Assessment Tool and Water Flow Tracking (DrySAT-WFT) were modified to simulate the hydrological components of water loss databases (DBs) affecting stream drying phenomena. In this study, the phenomenon is defined based on a method using the 10-day minimum flow (reference Q355). Prior to identifying the method using reference Q355, the DrySAT-WFT model was calibrated and verified for its performance with the total runoff (TQ), evapotranspiration (ET), and soil moisture (SM) at 12 streamflow locations, 3 ET locations, and 58 SM locations. The average R2 for TQ in 2005 to 2015 were 0.66 to 0.84, which demonstrates good performance. Moreover, Nash Sutcliffe model efficiency (NSE) values were 0.52 to 0.72, which are also good. After verifying the DrySAT-WFT model for hydrologic components, in order to apply the method, this study defined the drying progress which was analyzed by the stream drying index (SDI) as decision criteria. In this study, the criteria for the estimation of SDI were calculated as reference Q355 coming from the 10-day minimum flow considering only weather changes from 1976 to 2015. Then, SDI grades were determined by counting the number of days below a reference Q355 from TQ considering all water loss databases (DBs) such as weather changes, groundwater uses, forest heights, soil depths, land use, and road network. On the other hand, SDI represents how many days below the reference Q355 increased when all water loss DBs were applied, in comparison to when only weather changes were applied. The DrySAT-WFT model simulated the hydrological components of the water balance based on each water loss DB, including the application of all DBs. As a result, the change ratios for TQ were measured: −4.8% for groundwater use (GWU), −1.3% for forest height (FH), −0.3% for road network (RN), −0.1% for land use (LU) and −0.1% for soil depth (SD). Overall, TQ values decreased by -8.4%. The change ratios for ET were measured: −2.0% for GWU, +10.5% for FH, +5.6% for RN, −1.8% for LU and +0.3% for SD. Overall, the ET values increased by +14.7%. In addition, based on all water loss DBs, the SDI was evaluated for all watersheds, which intensified recently (2006–2015). Under weather DB conditions, the average SDI was measured as 2.0 for all watersheds. Stream drying processes remained limited, requiring only monitoring. Given baseline conditions, stream drying intensified to grades of 3.1 (1976–1985), 3.2 (1986–1995), 3.3 (1996–2005) and 3.5 (2006–2015) by all water loss DBs. Full article
(This article belongs to the Special Issue Study for Ungauged Catchments—Data, Models and Uncertainties)
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Open AccessArticle
Modelling Snowmelt in Ungauged Catchments
Water 2019, 11(2), 301; https://doi.org/10.3390/w11020301
Received: 20 December 2018 / Revised: 23 January 2019 / Accepted: 29 January 2019 / Published: 11 February 2019
PDF Full-text (2342 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Temperature-based snowmelt models are simple to implement and tend to give good results in gauged basins. The situation is, however, different in ungauged basins, as the lack of discharge data precludes the calibration of the snowmelt parameters. The main objective of this study [...] Read more.
Temperature-based snowmelt models are simple to implement and tend to give good results in gauged basins. The situation is, however, different in ungauged basins, as the lack of discharge data precludes the calibration of the snowmelt parameters. The main objective of this study was therefore to assess alternative approaches. This study compares the performance of two temperature-based snowmelt models (with and without an additional radiation term) and two energy-balance models with different data requirements in 312 catchments in the US. It considers the impact of: (i) the meteorological forcing, by using two gridded datasets (Livneh and MERRA-2), (ii) different approaches for calibrating the snowmelt parameters (an a priori approach and one based on Snow Data Assimilation System (SNODAS), a remote sensing-based product) and (iii) the parameterization and structure of the hydrological model used for transforming the snowmelt signal into streamflow at the basin outlet. The results show that energy-balance-based approaches achieve the best results, closely followed by the temperature-based model including a radiation term and calibrated with SNODAS data. It is also seen that data availability and quality influence the ranking of the snowmelt models. Full article
(This article belongs to the Special Issue Study for Ungauged Catchments—Data, Models and Uncertainties)
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