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Study for Ungauged Catchments—Data, Models and Uncertainties
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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: closed (30 June 2020) | Viewed by 62565

Special Issue Editors

Dr. Jong Ahn Chun

E-Mail Website
Guest Editor
Climate Research Department, APEC Climate Center, Busan, Korea
Interests: hydrological and water quality modelling; uncertainty in model predictions; surface hydrology; flow and solute transport modelling
Special Issues, Collections and Topics in MDPI journals
Dr. Daeha Kim

E-Mail
Guest Editor
APEC Climate Center; Busan 48058, South Korea
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

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Keywords

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

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Published Papers (15 papers)

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Research

11 pages, 4275 KiB  
Article
Analysis of the Relative Importance of Model Parameters in Watersheds with Different Hydrological Regimes
by Yelena Medina and Enrique Muñoz
Water 2020, 12(9), 2376; https://doi.org/10.3390/w12092376 - 25 Aug 2020
Cited by 12 | Viewed by 3288
Abstract
Depending on the purpose of the study, aggregated hydrological models are preferred over distributed models because they provide acceptable results in terms of precision and are easy to run, especially in data scarcity scenarios. To obtain acceptable results in terms of hydrological process [...] Read more.
Depending on the purpose of the study, aggregated hydrological models are preferred over distributed models because they provide acceptable results in terms of precision and are easy to run, especially in data scarcity scenarios. To obtain acceptable results in terms of hydrological process representativeness, it is necessary to understand and assess the models. In this study, the relative importance of the parameters of the Hydrologiska Byråns Vattenbalansavdelning (HBV) model is analyzed using sensitivity analysis to detect if the simulated processes represent the predominant hydrological processes at watershed scale. As a case study, four watersheds with different hydrological regimes (glacial and pluvial) and therefore different dominant processes are analyzed. The results show that in the case of the rivers with a glacial regime, the model performance depends highly on the snow module parameters, while in the case of the rivers with a pluvial regime, the model is sensitive to the soil and evapotranspiration modules. The results are directly related to the hydrological regime, which indicates that the HBV model, complemented by sensitivity analysis, is capable of both detecting and representing hydrological processes at watershed scale. Full article
(This article belongs to the Special Issue Study for Ungauged Catchments—Data, Models and Uncertainties)
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15 pages, 5236 KiB  
Article
Flood Vulnerability Assessment for Prioritizing and Evaluating Rehabilitation of Ungauged Reservoirs Considering Climate Change
by Sang-Min Jun, Moon-Seong Kang, Soonho Hwang, Jihoon Park and Jung-Hun Song
Water 2020, 12(7), 1901; https://doi.org/10.3390/w12071901 - 3 Jul 2020
Cited by 11 | Viewed by 3448
Abstract
The objective of this research was to apply the flood vulnerability assessment to ungauged reservoirs for prioritizing and evaluating the reservoir rehabilitation according to climate change. The flood vulnerability index (FVI) can quantitatively compare the flood vulnerabilities of the analysis targets and can [...] Read more.
The objective of this research was to apply the flood vulnerability assessment to ungauged reservoirs for prioritizing and evaluating the reservoir rehabilitation according to climate change. The flood vulnerability index (FVI) can quantitatively compare the flood vulnerabilities of the analysis targets and can be used for the relative comparison of hydraulic structures to determine the reinforcement priority. In this study, we proposed a simple FVI that contained exposure and adaptive capacity of the hydraulic structure. We selected ten dam heightening reservoirs in Korea and constructed data for flood vulnerability assessment. The FVI was calculated before and after the dam heightening to analyze the priority and effect of reservoir rehabilitation under climate change. Flood vulnerability indices were estimated for four periods (1995s: 1981–2010, 2025s: 2011–2040, 2055s: 2041–2070, 2085s: 2071–2100) and before/after the dam heightening project. As a result, flood vulnerability indices decreased after the dam heightening project for all reservoirs, and the indices have increasing tendencies in the future. The indices developed in this study can be useful to determine the priority and to evaluate the effect of rehabilitation for hydraulic structures. Full article
(This article belongs to the Special Issue Study for Ungauged Catchments—Data, Models and Uncertainties)
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20 pages, 4983 KiB  
Article
An Alternative for Estimating the Design Flood Interval of Agricultural Reservoirs under Climate Change Using a Non-Parametric Resampling Technique
by Jihoon Park, Syewoon Hwang, Jung-Hun Song and Moon-Seong Kang
Water 2020, 12(7), 1894; https://doi.org/10.3390/w12071894 - 2 Jul 2020
Cited by 1 | Viewed by 2317
Abstract
Agricultural reservoirs play such a central role in supplying water to rural areas that it is essential to properly estimate the design flood for agricultural reservoirs under climate change. The objective of this study was to estimate the inflow design flood interval using [...] Read more.
Agricultural reservoirs play such a central role in supplying water to rural areas that it is essential to properly estimate the design flood for agricultural reservoirs under climate change. The objective of this study was to estimate the inflow design flood interval using a non-parametric resampling technique for agricultural reservoirs under climate change. This study suggested an alternative method to point estimation using insufficient past data by providing the interval of the inflow design flood under the representative concentration pathway. To estimate the interval of the inflow design flood, we employed the bootstrap technique, which estimated the confidence interval corresponding to the 95% confidence level. This study covered a spatial range of 30 agricultural reservoirs in South Korea and a temporal range of past and three future representative periods: the base period (2015s: 1986–2015) and future periods (2040s: 2011–2040, 2070s: 2041–2070, 2100s: 2071–2100). We analyzed the results of a 200-year return period and 24-hour duration as a representative case. For the 97.5th bias-corrected and accelerated percentile value, the overall inflow design floods were larger than the base period value (2015s) with the safety factor applied. The northern and midwestern regions of South Korea showed relatively greater changes than the southeastern region. Some agricultural reservoirs showed a decrease in the design flood during the 2040s but generally increased after the 2070s. Through the non-parametric resampling technique, the interval estimation was provided considering the uncertainty of the inflow design flood. By presenting the results for three periods, we can provide policymakers with information to select according to the target period. The findings may provide an essential step in replacing a safety factor used for determining the design flood of agricultural reservoirs with the confidence interval calculated in accordance with statistical characteristics. Full article
(This article belongs to the Special Issue Study for Ungauged Catchments—Data, Models and Uncertainties)
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22 pages, 9195 KiB  
Article
Does Future Climate Bring Greater Streamflow Simulated by the HSPF Model to South Korea?
by Jihoon Park, Euntae Jung, Imgook Jung and Jaepil Cho
Water 2020, 12(7), 1884; https://doi.org/10.3390/w12071884 - 1 Jul 2020
Cited by 7 | Viewed by 3409
Abstract
Evaluating the impact of climate change on water resources is necessary for improving water resource management and adaptation measures at the watershed level. This study evaluates the impact of climate change on streamflow in South Korea using downscaled climate change information based on [...] Read more.
Evaluating the impact of climate change on water resources is necessary for improving water resource management and adaptation measures at the watershed level. This study evaluates the impact of climate change on streamflow in South Korea using downscaled climate change information based on the global climate model (GCM) and hydrological simulation program–FORTRAN model. Representative concentration pathway (RCP) scenarios 4.5 and 8.5 W/m2 were employed in this study. During the distant future (2071–2099), the flow increased by 15.11% and 24.40% for RCP scenarios 4.5 and 8.5 W/m2, respectively. The flow is highly dependent on precipitation and evapotranspiration. Both precipitation and evapotranspiration increased, but the relative change of precipitation was greater than the relative change of evapotranspiration. For this reason, the flow would show a significant increase. Additionally, for RCP 8.5 W/m2, the variability of the flow according to the GCM also increased because the variability of precipitation increased. Moreover, for RCP 8.5 W/m2, the summer and autumn flow increased significantly, and the winter flow decreased in both scenarios. The variability in autumn and winter was so great that the occurrence of extreme flow could intensify further. These projections indicated the possibility of future flooding and drought in summer and winter. Regionally, the flow was expected to show a significant increase in the southeastern region. The findings presented for South Korea could be used as primary data in establishing national climate change adaptation measures. Full article
(This article belongs to the Special Issue Study for Ungauged Catchments—Data, Models and Uncertainties)
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24 pages, 3288 KiB  
Article
Assessing the Resilience of Agricultural Reservoirs in Ungauged Catchments under Climate Change Using a Ratio Correction Factors-Based Calibration and Run Theory
by Sang-Hyun Lee, Sungtae Shin, Jin-Yong Choi, Jihoon Park and Seung-Hwan Yoo
Water 2020, 12(6), 1618; https://doi.org/10.3390/w12061618 - 6 Jun 2020
Cited by 5 | Viewed by 2938
Abstract
This study applied ratio correction factor (RCF) optimization to calibrate the daily storage of agricultural reservoirs located in ungauged catchments that lack stream flow data. Using Run theory, we then assessed the impacts of climate change on the resilience of agricultural reservoir operations [...] Read more.
This study applied ratio correction factor (RCF) optimization to calibrate the daily storage of agricultural reservoirs located in ungauged catchments that lack stream flow data. Using Run theory, we then assessed the impacts of climate change on the resilience of agricultural reservoir operations during reservoir drought conditions. First, we optimized the RCFs of inflow and outflow in three agricultural reservoirs in Korea using limited measurement data from 2008 to 2017; the results showed high performance regarding the simulation of daily reservoir storage. Second, we simulated daily storage volume in reservoirs from 2018 to 2099, using future climate change data, and analyzed the duration and intensity of reservoir drought conditions, which indicated that the storage capacity is under the critical value. Without calibration, the correlation between the simulated and measured reservoir water volumes was very low, but the correlation increased after calibration of the simulated water volumes. A linear relationship between the simulated and measured volumes was observed with a correlation coefficient value of 0.9, indicating that the simulated reservoir values after calibration closely match the measured values. In addition, the maximum intensity of reservoir drought in the Kicheon reservoir was determined to be 486,000 m3 before calibration but 506,000 m3 after calibration. The duration results showed that long-term reservoir drought conditions will be observed more often in the future owing to climate change, and this could be a negative factor affecting the resilience of reservoir operations. Full article
(This article belongs to the Special Issue Study for Ungauged Catchments—Data, Models and Uncertainties)
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14 pages, 5746 KiB  
Article
Uncertainty in Irrigation Return Flow Estimation: Comparing Conceptual and Physically-Based Parameterization Approaches
by Jung-Hun Song, Younggu Her, Soonho Hwang and Moon-Seong Kang
Water 2020, 12(4), 1125; https://doi.org/10.3390/w12041125 - 15 Apr 2020
Cited by 7 | Viewed by 3559
Abstract
Irrigation return flow (RF) is a critical component of the water cycle in an agricultural watershed, influencing the flow regime of downstream river. As such, it should be accurately quantified when developing water resources management plans and practices. Although many studies have proposed [...] Read more.
Irrigation return flow (RF) is a critical component of the water cycle in an agricultural watershed, influencing the flow regime of downstream river. As such, it should be accurately quantified when developing water resources management plans and practices. Although many studies have proposed ways to quantify RF, uncertainty in RF estimates has not been determined to improve reliability and credibility. This study examines how conceptual (CON) and physically-based (PHY) parameterization approaches affect RF uncertainty. Results showed that PHY had a smaller amount of RF uncertainty compared to CON, as parameters of the PHY approach could be regulated based on their physical meanings. This study also found that the application of constraints created based on the relationship between the conceptual parameter and physical characteristics of irrigated plots could effectively reduce RF uncertainty made using the CON approach. This study demonstrates the benefits of the physically-based parameterization approach and the application of constraints on conceptual parameters to RF estimation. Full article
(This article belongs to the Special Issue Study for Ungauged Catchments—Data, Models and Uncertainties)
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27 pages, 19403 KiB  
Article
Spatial Diagnosis of Rain Gauges’ Distribution and Flood Impacts: Case Study in Itaperuna, Rio de Janeiro—Brazil
by Priscila Celebrini de Oliveira Campos and Igor Paz
Water 2020, 12(4), 1120; https://doi.org/10.3390/w12041120 - 14 Apr 2020
Cited by 7 | Viewed by 5430
Abstract
The global increase of urban areas highlights the need to improve their adaptation to extreme weather events, in particular heavy rainfall. This study analyzes the impacts of in-situ rain gauges’ distribution (by applying the fractal dimension concept) associated with a spatial diagnosis of [...] Read more.
The global increase of urban areas highlights the need to improve their adaptation to extreme weather events, in particular heavy rainfall. This study analyzes the impacts of in-situ rain gauges’ distribution (by applying the fractal dimension concept) associated with a spatial diagnosis of flood occurrences in the municipality of Itaperuna, Rio de Janeiro–Brazil, performing an investigation of flood susceptibility maps based on transitory (considering precipitation) and on permanent factors (natural flood susceptibility). The fractal analysis results pointed out that the rain gauges’ distribution presented a scaling break behavior with a low fractal dimension ( 0.416 ) at the small-scale range, highlighting the incapacity of the local instrumentation to capture the spatial rainfall variability. Thereafter, the cross-tabulation method was used to validate both predictive maps with recorded data of the major January 2020 event, which indicated that the transitory factors’ flood map presented an unsatisfactory Probability of Detection of floods ( P O D = 0.552 ) when compared to the permanent factors’ map ( P O D = 0.944 ) . These issues allowed to consider the hydrological uncertainties associated with the sparse gauge network distribution and its impacts on the use of flood susceptibility maps. Such methodology enables the evaluation of other municipalities and regions, constituting essential information in aid of territorial management. Full article
(This article belongs to the Special Issue Study for Ungauged Catchments—Data, Models and Uncertainties)
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21 pages, 3437 KiB  
Article
Enhancing Physical Similarity Approach to Predict Runoff in Ungauged Watersheds in Sub-Tropical Regions
by Santiago Narbondo, Angela Gorgoglione, Magdalena Crisci and Christian Chreties
Water 2020, 12(2), 528; https://doi.org/10.3390/w12020528 - 13 Feb 2020
Cited by 42 | Viewed by 4675
Abstract
Regionalization techniques have been comprehensively discussed as the solution for runoff predictions in ungauged basins (PUB). Several types of regionalization approach have been proposed during the years. Among these, the physical similarity one was demonstrated to be one of the most robust. However, [...] Read more.
Regionalization techniques have been comprehensively discussed as the solution for runoff predictions in ungauged basins (PUB). Several types of regionalization approach have been proposed during the years. Among these, the physical similarity one was demonstrated to be one of the most robust. However, this method cannot be applied in large regions characterized by highly variable climatic conditions, such as sub-tropical areas. Therefore, this study aims to develop a new regionalization approach based on an enhanced concept of physical similarity to improve the runoff prediction of ungauged basins at country scale, under highly variable-weather conditions. A clustering method assured that watersheds with different hydrologic and physical characteristics were considered. The novelty of the proposed approach is based on the relationships found between rainfall-runoff model parameters and watershed-physiographic factors. These relationships were successively exported and validated at the ungauged basins. From the overall results, it can be concluded that the runoff prediction in the ungauged basins was very satisfactory. Therefore, the proposed approach can be adopted as an alternative method for runoff prediction in ungauged basins characterized by highly variable-climatic conditions. Full article
(This article belongs to the Special Issue Study for Ungauged Catchments—Data, Models and Uncertainties)
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21 pages, 27549 KiB  
Article
Similarity Analysis of Small- and Medium-Sized Watersheds Based on Clustering Ensemble Model
by Qun Zhao, Yuelong Zhu, Dingsheng Wan, Yufeng Yu and Yuqing Lu
Water 2020, 12(1), 69; https://doi.org/10.3390/w12010069 - 23 Dec 2019
Cited by 11 | Viewed by 3242
Abstract
Similarity analysis of small- and medium-sized watersheds mainly depends on manual work, and there is no complete automated analysis method. In order to solve this problem, we propose a similarity analysis method based on clustering ensemble model. First, the iterative clustering ensemble construction [...] Read more.
Similarity analysis of small- and medium-sized watersheds mainly depends on manual work, and there is no complete automated analysis method. In order to solve this problem, we propose a similarity analysis method based on clustering ensemble model. First, the iterative clustering ensemble construction algorithm with weighted random sampling (WRS-CCE) is proposed to get great clustering collectives. Then, we combine spectral clustering with the fuzzy C-means method to design a consensus function for small- and medium-sized watershed data sets. Finally, the similarity analysis of small- and medium-sized watersheds is carried out according to the clustering results. Experiments show that the proposed clustering ensemble model can effectively find more potential similar watersheds and can output the similarity of these watersheds. Full article
(This article belongs to the Special Issue Study for Ungauged Catchments—Data, Models and Uncertainties)
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Graphical abstract

21 pages, 4449 KiB  
Article
Regionalization of a Rainfall-Runoff Model: Limitations and Potentials
by Jung-Hun Song, Younggu Her, Kyo Suh, Moon-Seong Kang and Hakkwan Kim
Water 2019, 11(11), 2257; https://doi.org/10.3390/w11112257 - 28 Oct 2019
Cited by 21 | Viewed by 5171
Abstract
Regionalized lumped rainfall-runoff (RR) models have been widely employed as a means of predicting the streamflow of an ungauged watershed because of their simple yet effective simulation strategies. Parameter regionalization techniques relate the parameter values of a model calibrated to the observations of [...] Read more.
Regionalized lumped rainfall-runoff (RR) models have been widely employed as a means of predicting the streamflow of an ungauged watershed because of their simple yet effective simulation strategies. Parameter regionalization techniques relate the parameter values of a model calibrated to the observations of gauged watersheds to the geohydrological characteristics of the watersheds. Thus, the accuracy of regionalized models is dependent on the calibration processes, as well as the structure of the model used and the quality of the measurements. In this study, we have discussed the potentials and limitations of hydrological model parameter regionalization to provide practical guidance for hydrological modeling of ungauged watersheds. This study used a Tank model as an example model and calibrated its parameters to streamflow observed at the outlets of 39 gauged watersheds. Multiple regression analysis identified the statistical relationships between calibrated parameter values and nine watershed characteristics. The newly developed regional models provided acceptable accuracy in predicting streamflow, demonstrating the potential of the parameter regionalization method. However, uncertainty associated with parameter calibration processes was found to be large enough to affect the accuracy of regionalization. This study demonstrated the importance of objective function selection of the RR model regionalization. Full article
(This article belongs to the Special Issue Study for Ungauged Catchments—Data, Models and Uncertainties)
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19 pages, 8044 KiB  
Article
Small-Scale Rainfall Variability Impacts Analyzed by Fully-Distributed Model Using C-Band and X-Band Radar Data
by Igor Paz, Bernard Willinger, Auguste Gires, Bianca Alves de Souza, Laurent Monier, Hervé Cardinal, Bruno Tisserand, Ioulia Tchiguirinskaia and Daniel Schertzer
Water 2019, 11(6), 1273; https://doi.org/10.3390/w11061273 - 18 Jun 2019
Cited by 9 | Viewed by 3621
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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15 pages, 7128 KiB  
Article
Assessment of Agricultural Drought Considering the Hydrological Cycle and Crop Phenology in the Korean Peninsula
by Chul-Hee Lim, Seung Hee Kim, Jong Ahn Chun, Menas C. Kafatos and Woo-Kyun Lee
Water 2019, 11(5), 1105; https://doi.org/10.3390/w11051105 - 27 May 2019
Cited by 20 | Viewed by 5154
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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12 pages, 5201 KiB  
Article
Evaluation of Future Flood Risk According to RCP Scenarios Using a Regional Flood Frequency Analysis for Ungauged Watersheds
by Nam Won Kim, Jin-Young Lee, Dong-Hyeok Park and Tae-Woong Kim
Water 2019, 11(5), 992; https://doi.org/10.3390/w11050992 - 11 May 2019
Cited by 14 | Viewed by 4272
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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24 pages, 50352 KiB  
Article
Quantification of Stream Drying Phenomena Using Grid-Based Hydrological Modeling via Long-Term Data Mining throughout South Korea including Ungauged Areas
by Chunggil Jung, Jiwan Lee, Yonggwan Lee and Seongjoon Kim
Water 2019, 11(3), 477; https://doi.org/10.3390/w11030477 - 7 Mar 2019
Cited by 7 | Viewed by 6430
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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22 pages, 2342 KiB  
Article
Modelling Snowmelt in Ungauged Catchments
by Carolina Massmann
Water 2019, 11(2), 301; https://doi.org/10.3390/w11020301 - 11 Feb 2019
Cited by 18 | Viewed by 4281
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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