Articles | Volume 18, issue 2
https://doi.org/10.5194/hess-18-539-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-18-539-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
12 Feb 2014
Research article |
| 12 Feb 2014
Using the SWAT model to improve process descriptions and define hydrologic partitioning in South Korea
C. L. Shope
University of Bayreuth, Dept. of Hydrology, Universitatstrasse 30, 95440 Bayreuth, Germany
now at: US Geological Survey, 2329 Orton Circle, Salt Lake City, UT, USA
G. R. Maharjan
University of Bayreuth, Dept. of Plant Ecology, Universitatstrasse 30, 95440 Bayreuth, Germany
J. Tenhunen
University of Bayreuth, Dept. of Plant Ecology, Universitatstrasse 30, 95440 Bayreuth, Germany
B. Seo
University of Bayreuth, Dept. of Plant Ecology, Universitatstrasse 30, 95440 Bayreuth, Germany
K. Kim
University of Bayreuth, Dept. of Plant Ecology, Universitatstrasse 30, 95440 Bayreuth, Germany
J. Riley
University of Bayreuth, Dept. of Plant Ecology, Universitatstrasse 30, 95440 Bayreuth, Germany
S. Arnhold
University of Bayreuth, Dept. of Soil Physics, Universitatstrasse 30, 95440 Bayreuth, Germany
T. Koellner
University of Bayreuth, Professorship of Ecosystem Services, Universitatstrasse 30, 95440 Bayreuth, Germany
Y. S. Ok
Kangwon National University, Dept. of Biological Environment, 192-1 Hyoja-Dong, Gwangwon-do, Chuncheon 200-701, Republic of Korea
University of Alberta, Dept. of Renewable Resources, Alberta, Canada
S. Peiffer
University of Bayreuth, Dept. of Hydrology, Universitatstrasse 30, 95440 Bayreuth, Germany
B. Kim
Kangwon National University, Dept. of Env. Science, 192-1 Hyoja-Dong, Gwangwon-do, Chuncheon, 200-701, Republic of Korea
J.-H. Park
EWHA Womans University, Dept. of Environmental Science and Engineering, Seoul 120-750, Republic of Korea
B. Huwe
University of Bayreuth, Dept. of Soil Physics, Universitatstrasse 30, 95440 Bayreuth, Germany
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Hydrol. Earth Syst. Sci., 28, 4239–4249, https://doi.org/10.5194/hess-28-4239-2024, https://doi.org/10.5194/hess-28-4239-2024, 2024
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Hydrol. Earth Syst. Sci., 28, 4187–4201, https://doi.org/10.5194/hess-28-4187-2024, https://doi.org/10.5194/hess-28-4187-2024, 2024
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Recently, a special type of neural-network architecture became increasingly popular in hydrology literature. However, in most applications, this model was applied as a one-to-one replacement for hydrology models without adapting or rethinking the experimental setup. In this opinion paper, we show how this is almost always a bad decision and how using these kinds of models requires the use of large-sample hydrology data sets.
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Hydrol. Earth Syst. Sci., 28, 4219–4237, https://doi.org/10.5194/hess-28-4219-2024, https://doi.org/10.5194/hess-28-4219-2024, 2024
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Zehua Chang, Hongkai Gao, Leilei Yong, Kang Wang, Rensheng Chen, Chuntan Han, Otgonbayar Demberel, Batsuren Dorjsuren, Shugui Hou, and Zheng Duan
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Henry M. Zimba, Miriam Coenders-Gerrits, Kawawa E. Banda, Petra Hulsman, Nick van de Giesen, Imasiku A. Nyambe, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 3633–3663, https://doi.org/10.5194/hess-28-3633-2024, https://doi.org/10.5194/hess-28-3633-2024, 2024
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The fall and flushing of new leaves in the miombo woodlands co-occur in the dry season before the commencement of seasonal rainfall. The miombo species are also said to have access to soil moisture in deep soils, including groundwater in the dry season. Satellite-based evaporation estimates, temporal trends, and magnitudes differ the most in the dry season, most likely due to inadequate understanding and representation of the highlighted miombo species attributes in simulations.
Louise Akemi Kuana, Arlan Scortegagna Almeida, Emílio Graciliano Ferreira Mercuri, and Steffen Manfred Noe
Hydrol. Earth Syst. Sci., 28, 3367–3390, https://doi.org/10.5194/hess-28-3367-2024, https://doi.org/10.5194/hess-28-3367-2024, 2024
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The authors compared regionalization methods for river flow prediction in 126 catchments from the south of Brazil, a region with humid subtropical and hot temperate climate. The regionalization method based on physiographic–climatic similarity had the best performance for predicting daily and Q95 reference flow. We showed that basins without flow monitoring can have a good approximation of streamflow using machine learning and physiographic–climatic information as inputs.
Huy Dang and Yadu Pokhrel
Hydrol. Earth Syst. Sci., 28, 3347–3365, https://doi.org/10.5194/hess-28-3347-2024, https://doi.org/10.5194/hess-28-3347-2024, 2024
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By examining basin-wide simulations of a river regime over 83 years with and without dams, we present evidence that climate variation was a key driver of hydrologic variabilities in the Mekong River basin (MRB) over the long term; however, dams have largely altered the seasonality of the Mekong’s flow regime and annual flooding patterns in major downstream areas in recent years. These findings could help us rethink the planning of future dams and water resource management in the MRB.
Yongshin Lee, Francesca Pianosi, Andres Peñuela, and Miguel Angel Rico-Ramirez
Hydrol. Earth Syst. Sci., 28, 3261–3279, https://doi.org/10.5194/hess-28-3261-2024, https://doi.org/10.5194/hess-28-3261-2024, 2024
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Following recent advancements in weather prediction technology, we explored how seasonal weather forecasts (1 or more months ahead) could benefit practical water management in South Korea. Our findings highlight that using seasonal weather forecasts for predicting flow patterns 1 to 3 months ahead is effective, especially during dry years. This suggest that seasonal weather forecasts can be helpful in improving the management of water resources.
Mariam Khanam, Giulia Sofia, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 28, 3161–3190, https://doi.org/10.5194/hess-28-3161-2024, https://doi.org/10.5194/hess-28-3161-2024, 2024
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Flooding worsens due to climate change, with river dynamics being a key in local flood control. Predicting post-storm geomorphic changes is challenging. Using self-organizing maps and machine learning, this study forecasts post-storm alterations in stage–discharge relationships across 3101 US stream gages. The provided framework can aid in updating hazard assessments by identifying rivers prone to change, integrating channel adjustments into flood hazard assessment.
Yalan Song, Wouter J. M. Knoben, Martyn P. Clark, Dapeng Feng, Kathryn Lawson, Kamlesh Sawadekar, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 3051–3077, https://doi.org/10.5194/hess-28-3051-2024, https://doi.org/10.5194/hess-28-3051-2024, 2024
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Differentiable models (DMs) integrate neural networks and physical equations for accuracy, interpretability, and knowledge discovery. We developed an adjoint-based DM for ordinary differential equations (ODEs) for hydrological modeling, reducing distorted fluxes and physical parameters from errors in models that use explicit and operation-splitting schemes. With a better numerical scheme and improved structure, the adjoint-based DM matches or surpasses long short-term memory (LSTM) performance.
Florian Willkofer, Raul R. Wood, and Ralf Ludwig
Hydrol. Earth Syst. Sci., 28, 2969–2989, https://doi.org/10.5194/hess-28-2969-2024, https://doi.org/10.5194/hess-28-2969-2024, 2024
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Severe flood events pose a threat to riverine areas, yet robust estimates of the dynamics of these events in the future due to climate change are rarely available. Hence, this study uses data from a regional climate model, SMILE, to drive a high-resolution hydrological model for 98 catchments of hydrological Bavaria and exploits the large database to derive robust values for the 100-year flood events. Results indicate an increase in frequency and intensity for most catchments in the future.
Maik Renner and Corina Hauffe
Hydrol. Earth Syst. Sci., 28, 2849–2869, https://doi.org/10.5194/hess-28-2849-2024, https://doi.org/10.5194/hess-28-2849-2024, 2024
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Climate and land surface changes influence the partitioning of water balance components decisively. Their impact is quantified for 71 catchments in Saxony. Germany. Distinct signatures in the joint water and energy budgets are found: (i) past forest dieback caused a decrease in and subsequent recovery of evapotranspiration in the affected regions, and (ii) the recent shift towards higher aridity imposed a large decline in runoff that has not been seen in the observation records before.
Zhen Cui, Shenglian Guo, Hua Chen, Dedi Liu, Yanlai Zhou, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 28, 2809–2829, https://doi.org/10.5194/hess-28-2809-2024, https://doi.org/10.5194/hess-28-2809-2024, 2024
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Ensemble forecasting facilitates reliable flood forecasting and warning. This study couples the copula-based hydrologic uncertainty processor (CHUP) with Bayesian model averaging (BMA) and proposes the novel CHUP-BMA method of reducing inflow forecasting uncertainty of the Three Gorges Reservoir. The CHUP-BMA avoids the normal distribution assumption in the HUP-BMA and considers the constraint of initial conditions, which can improve the deterministic and probabilistic forecast performance.
Mazda Kompanizare, Diogo Costa, Merrin L. Macrae, John W. Pomeroy, and Richard M. Petrone
Hydrol. Earth Syst. Sci., 28, 2785–2807, https://doi.org/10.5194/hess-28-2785-2024, https://doi.org/10.5194/hess-28-2785-2024, 2024
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A new agricultural tile drainage module was developed in the Cold Region Hydrological Model platform. Tile flow and water levels are simulated by considering the effect of capillary fringe thickness, drainable water and seasonal regional groundwater dynamics. The model was applied to a small well-instrumented farm in southern Ontario, Canada, where there are concerns about the impacts of agricultural drainage into Lake Erie.
Eduardo Acuña Espinoza, Ralf Loritz, Manuel Álvarez Chaves, Nicole Bäuerle, and Uwe Ehret
Hydrol. Earth Syst. Sci., 28, 2705–2719, https://doi.org/10.5194/hess-28-2705-2024, https://doi.org/10.5194/hess-28-2705-2024, 2024
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Hydrological hybrid models promise to merge the performance of deep learning methods with the interpretability of process-based models. One hybrid approach is the dynamic parameterization of conceptual models using long short-term memory (LSTM) networks. We explored this method to evaluate the effect of the flexibility given by LSTMs on the process-based part.
Adam Griffin, Alison L. Kay, Paul Sayers, Victoria Bell, Elizabeth Stewart, and Sam Carr
Hydrol. Earth Syst. Sci., 28, 2635–2650, https://doi.org/10.5194/hess-28-2635-2024, https://doi.org/10.5194/hess-28-2635-2024, 2024
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Widespread flooding is a major problem in the UK and is greatly affected by climate change and land-use change. To look at how widespread flooding changes in the future, climate model data (UKCP18) were used with a hydrological model (Grid-to-Grid) across the UK, and 14 400 events were identified between two time slices: 1980–2010 and 2050–2080. There was a strong increase in the number of winter events in the future time slice and in the peak return periods.
Alberto Montanari, Bruno Merz, and Günter Blöschl
Hydrol. Earth Syst. Sci., 28, 2603–2615, https://doi.org/10.5194/hess-28-2603-2024, https://doi.org/10.5194/hess-28-2603-2024, 2024
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Floods often take communities by surprise, as they are often considered virtually
impossibleyet are an ever-present threat similar to the sword suspended over the head of Damocles in the classical Greek anecdote. We discuss four reasons why extremely large floods carry a risk that is often larger than expected. We provide suggestions for managing the risk of megafloods by calling for a creative exploration of hazard scenarios and communicating the unknown corners of the reality of floods.
Peter Reichert, Kai Ma, Marvin Höge, Fabrizio Fenicia, Marco Baity-Jesi, Dapeng Feng, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 2505–2529, https://doi.org/10.5194/hess-28-2505-2024, https://doi.org/10.5194/hess-28-2505-2024, 2024
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We compared the predicted change in catchment outlet discharge to precipitation and temperature change for conceptual and machine learning hydrological models. We found that machine learning models, despite providing excellent fit and prediction capabilities, can be unreliable regarding the prediction of the effect of temperature change for low-elevation catchments. This indicates the need for caution when applying them for the prediction of the effect of climate change.
Nicolás Álamos, Camila Alvarez-Garreton, Ariel Muñoz, and Álvaro González-Reyes
Hydrol. Earth Syst. Sci., 28, 2483–2503, https://doi.org/10.5194/hess-28-2483-2024, https://doi.org/10.5194/hess-28-2483-2024, 2024
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In this study, we assess the effects of climate and water use on streamflow reductions and drought intensification during the last 3 decades in central Chile. We address this by contrasting streamflow observations with near-natural streamflow simulations. We conclude that while the lack of precipitation dominates streamflow reductions in the megadrought, water uses have not diminished during this time, causing a worsening of the hydrological drought conditions and maladaptation conditions.
Fengjing Liu, Martha H. Conklin, and Glenn D. Shaw
Hydrol. Earth Syst. Sci., 28, 2239–2258, https://doi.org/10.5194/hess-28-2239-2024, https://doi.org/10.5194/hess-28-2239-2024, 2024
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Mountain snowpack has been declining and more precipitation falls as rain than snow. Using stable isotopes, we found flows and flow duration in Yosemite Creek are most sensitive to climate warming due to strong evaporation of waterfalls, potentially lengthening the dry-up period of waterfalls in summer and negatively affecting tourism. Groundwater recharge in Yosemite Valley is primarily from the upper snow–rain transition (2000–2500 m) and very vulnerable to a reduction in the snow–rain ratio.
Qiutong Yu, Bryan A. Tolson, Hongren Shen, Ming Han, Juliane Mai, and Jimmy Lin
Hydrol. Earth Syst. Sci., 28, 2107–2122, https://doi.org/10.5194/hess-28-2107-2024, https://doi.org/10.5194/hess-28-2107-2024, 2024
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It is challenging to incorporate input variables' spatial distribution information when implementing long short-term memory (LSTM) models for streamflow prediction. This work presents a novel hybrid modelling approach to predict streamflow while accounting for spatial variability. We evaluated the performance against lumped LSTM predictions in 224 basins across the Great Lakes region in North America. This approach shows promise for predicting streamflow in large, ungauged basin.
Marcus Buechel, Louise Slater, and Simon Dadson
Hydrol. Earth Syst. Sci., 28, 2081–2105, https://doi.org/10.5194/hess-28-2081-2024, https://doi.org/10.5194/hess-28-2081-2024, 2024
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Afforestation has been proposed internationally, but the hydrological implications of such large increases in the spatial extent of woodland are not fully understood. In this study, we use a land surface model to simulate hydrology across Great Britain with realistic afforestation scenarios and potential climate changes. Countrywide afforestation minimally influences hydrology, when compared to climate change, and reduces low streamflow whilst not lowering the highest flows.
Bu Li, Ting Sun, Fuqiang Tian, Mahmut Tudaji, Li Qin, and Guangheng Ni
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-54, https://doi.org/10.5194/hess-2024-54, 2024
Revised manuscript accepted for HESS
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This paper developed hybrid distributed hydrological models by employing a distributed model as the backbone, and utilizing deep learning to parameterize and replace internal modules. The main contribution is to provide a high-performance tool enriched with explicit hydrological knowledge for hydrological prediction and improves understanding about the hydrological sensitivities to climate change in large alpine basins.
Qian Zhu, Xiaodong Qin, Dongyang Zhou, Tiantian Yang, and Xinyi Song
Hydrol. Earth Syst. Sci., 28, 1665–1686, https://doi.org/10.5194/hess-28-1665-2024, https://doi.org/10.5194/hess-28-1665-2024, 2024
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Input data, model and calibration strategy can affect the accuracy of flood event simulation and prediction. Satellite-based precipitation with different spatiotemporal resolutions is an important input source. Data-driven models are sometimes proven to be more accurate than hydrological models. Event-based calibration and conventional strategy are two options adopted for flood simulation. This study targets the three concerns for accurate flood event simulation and prediction.
Fabio Ciulla and Charuleka Varadharajan
Hydrol. Earth Syst. Sci., 28, 1617–1651, https://doi.org/10.5194/hess-28-1617-2024, https://doi.org/10.5194/hess-28-1617-2024, 2024
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We present a new method based on network science for unsupervised classification of large datasets and apply it to classify 9067 US catchments and 274 biophysical traits at multiple scales. We find that our trait-based approach produces catchment classes with distinct streamflow behavior and that spatial patterns emerge amongst pristine and human-impacted catchments. This method can be widely used beyond hydrology to identify patterns, reduce trait redundancy, and select representative sites.
Cyril Thébault, Charles Perrin, Vazken Andréassian, Guillaume Thirel, Sébastien Legrand, and Olivier Delaigue
Hydrol. Earth Syst. Sci., 28, 1539–1566, https://doi.org/10.5194/hess-28-1539-2024, https://doi.org/10.5194/hess-28-1539-2024, 2024
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Streamflow forecasting is useful for many applications, ranging from population safety (e.g. floods) to water resource management (e.g. agriculture or hydropower). To this end, hydrological models must be optimized. However, a model is inherently wrong. This study aims to analyse the contribution of a multi-model approach within a variable spatial framework to improve streamflow simulations. The underlying idea is to take advantage of the strength of each modelling framework tested.
Lele Shu, Xiaodong Li, Yan Chang, Xianhong Meng, Hao Chen, Yuan Qi, Hongwei Wang, Zhaoguo Li, and Shihua Lyu
Hydrol. Earth Syst. Sci., 28, 1477–1491, https://doi.org/10.5194/hess-28-1477-2024, https://doi.org/10.5194/hess-28-1477-2024, 2024
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We developed a new model to better understand how water moves in a lake basin. Our model improves upon previous methods by accurately capturing the complexity of water movement, both on the surface and subsurface. Our model, tested using data from China's Qinghai Lake, accurately replicates complex water movements and identifies contributing factors of the lake's water balance. The findings provide a robust tool for predicting hydrological processes, aiding water resource planning.
Ricardo Mantilla, Morgan Fonley, and Nicolás Velásquez
Hydrol. Earth Syst. Sci., 28, 1373–1382, https://doi.org/10.5194/hess-28-1373-2024, https://doi.org/10.5194/hess-28-1373-2024, 2024
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Hydrologists strive to “Be right for the right reasons” when modeling the hydrologic cycle; however, the datasets available to validate hydrological models are sparse, and in many cases, they comprise streamflow observations at the outlets of large catchments. In this work, we show that matching streamflow observations at the outlet of a large basin is not a reliable indicator of a correct description of the small-scale runoff processes.
Lillian M. McGill, E. Ashley Steel, and Aimee H. Fullerton
Hydrol. Earth Syst. Sci., 28, 1351–1371, https://doi.org/10.5194/hess-28-1351-2024, https://doi.org/10.5194/hess-28-1351-2024, 2024
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This study examines the relationship between air and river temperatures in Washington's Snoqualmie and Wenatchee basins. We used classification and regression approaches to show that the sensitivity of river temperature to air temperature is variable across basins and controlled largely by geology and snowmelt. Findings can be used to inform strategies for river basin restoration and conservation, such as identifying climate-insensitive areas of the basin that should be preserved and protected.
Jari-Pekka Nousu, Kersti Leppä, Hannu Marttila, Pertti Ala-aho, Giulia Mazzotti, Terhikki Manninen, Mika Korkiakoski, Mika Aurela, Annalea Lohila, and Samuli Launiainen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-81, https://doi.org/10.5194/hess-2024-81, 2024
Revised manuscript accepted for HESS
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We used hydrological models, field measurements and satellite-based data to study the soil moisture dynamics in a subarctic catchment. The role of groundwater was studied with different ways to model the groundwater dynamics, and via comparisons to the observational data. The choice of groundwater model was shown to have a strong impact, and representation of lateral flow was important to capture wet soil conditions. Our results provide insights for ecohydrological studies in boreal regions.
Stephanie R. Clark, Julien Lerat, Jean-Michel Perraud, and Peter Fitch
Hydrol. Earth Syst. Sci., 28, 1191–1213, https://doi.org/10.5194/hess-28-1191-2024, https://doi.org/10.5194/hess-28-1191-2024, 2024
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To determine if deep learning models are in general a viable alternative to traditional hydrologic modelling techniques in Australian catchments, a comparison of river–runoff predictions is made between traditional conceptual models and deep learning models in almost 500 catchments spread over the continent. It is found that the deep learning models match or outperform the traditional models in over two-thirds of the river catchments, indicating feasibility in a wide variety of conditions.
Dipti Tiwari, Mélanie Trudel, and Robert Leconte
Hydrol. Earth Syst. Sci., 28, 1127–1146, https://doi.org/10.5194/hess-28-1127-2024, https://doi.org/10.5194/hess-28-1127-2024, 2024
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Calibrating hydrological models with multi-objective functions enhances model robustness. By using spatially distributed snow information in the calibration, the model performance can be enhanced without compromising the outputs. In this study the HYDROTEL model was calibrated in seven different experiments, incorporating the SPAEF (spatial efficiency) metric alongside Nash–Sutcliffe efficiency (NSE) and root-mean-square error (RMSE), with the aim of identifying the optimal calibration strategy.
Luis Andres De la Fuente, Mohammad Reza Ehsani, Hoshin Vijai Gupta, and Laura Elizabeth Condon
Hydrol. Earth Syst. Sci., 28, 945–971, https://doi.org/10.5194/hess-28-945-2024, https://doi.org/10.5194/hess-28-945-2024, 2024
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Long short-term memory (LSTM) is a widely used machine-learning model in hydrology, but it is difficult to extract knowledge from it. We propose HydroLSTM, which represents processes like a hydrological reservoir. Models based on HydroLSTM perform similarly to LSTM while requiring fewer cell states. The learned parameters are informative about the dominant hydrology of a catchment. Our results show how parsimony and hydrological knowledge extraction can be achieved by using the new structure.
Nienke Tessa Tempel, Laurene Bouaziz, Riccardo Taormina, Ellis van Noppen, Jasper Stam, Eric Sprokkereef, and Markus Hrachowitz
EGUsphere, https://doi.org/10.5194/egusphere-2024-115, https://doi.org/10.5194/egusphere-2024-115, 2024
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This study explores the impact of climatic variability on root zone water storage capacities thus on hydrological predictions. Analysing data from 286 areas in Europe and the US, we found that despite some variations in root zone storage capacity due to changing climatic conditions over multiple decades, these changes are generally minor and have a limited effect on water storage and river flow predictions.
Louise Mimeau, Annika Künne, Flora Branger, Sven Kralisch, Alexandre Devers, and Jean-Philippe Vidal
Hydrol. Earth Syst. Sci., 28, 851–871, https://doi.org/10.5194/hess-28-851-2024, https://doi.org/10.5194/hess-28-851-2024, 2024
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Modelling flow intermittence is essential for predicting the future evolution of drying in river networks and better understanding the ecological and socio-economic impacts. However, modelling flow intermittence is challenging, and observed data on temporary rivers are scarce. This study presents a new modelling approach for predicting flow intermittence in river networks and shows that combining different sources of observed data reduces the model uncertainty.
Elena Macdonald, Bruno Merz, Björn Guse, Viet Dung Nguyen, Xiaoxiang Guan, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 28, 833–850, https://doi.org/10.5194/hess-28-833-2024, https://doi.org/10.5194/hess-28-833-2024, 2024
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In some rivers, the occurrence of extreme flood events is more likely than in other rivers – they have heavy-tailed distributions. We find that threshold processes in the runoff generation lead to such a relatively high occurrence probability of extremes. Further, we find that beyond a certain return period, i.e. for rare events, rainfall is often the dominant control compared to runoff generation. Our results can help to improve the estimation of the occurrence probability of extreme floods.
Claire Kouba and Thomas Harter
Hydrol. Earth Syst. Sci., 28, 691–718, https://doi.org/10.5194/hess-28-691-2024, https://doi.org/10.5194/hess-28-691-2024, 2024
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In some watersheds, the severity of the dry season has a large impact on aquatic ecosystems. In this study, we design a way to predict, 5–6 months in advance, how severe the dry season will be in a rural watershed in northern California. This early warning can support seasonal adaptive management. To predict these two values, we assess data about snow, rain, groundwater, and river flows. We find that maximum snowpack and total wet season rainfall best predict dry season severity.
Yi Nan and Fuqiang Tian
Hydrol. Earth Syst. Sci., 28, 669–689, https://doi.org/10.5194/hess-28-669-2024, https://doi.org/10.5194/hess-28-669-2024, 2024
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This paper utilized a tracer-aided model validated by multiple datasets in a large mountainous basin on the Tibetan Plateau to analyze hydrological sensitivity to climate change. The spatial pattern of the local hydrological sensitivities and the influence factors were analyzed in particular. The main finding of this paper is that the local hydrological sensitivity in mountainous basins is determined by the relationship between the glacier area ratio and the mean annual precipitation.
Michael J. Vlah, Matthew R. V. Ross, Spencer Rhea, and Emily S. Bernhardt
Hydrol. Earth Syst. Sci., 28, 545–573, https://doi.org/10.5194/hess-28-545-2024, https://doi.org/10.5194/hess-28-545-2024, 2024
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Virtual stream gauging enables continuous streamflow estimation where a gauge might be difficult or impractical to install. We reconstructed flow at 27 gauges of the National Ecological Observatory Network (NEON), informing ~199 site-months of missing data in the official record and improving that accuracy of official estimates at 11 sites. This study shows that machine learning, but also routine regression methods, can be used to supplement existing gauge networks and reduce monitoring costs.
Sungwook Wi and Scott Steinschneider
Hydrol. Earth Syst. Sci., 28, 479–503, https://doi.org/10.5194/hess-28-479-2024, https://doi.org/10.5194/hess-28-479-2024, 2024
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We investigate whether deep learning (DL) models can produce physically plausible streamflow projections under climate change. We address this question by focusing on modeled responses to increases in temperature and potential evapotranspiration and by employing three DL and three process-based hydrological models. The results suggest that physical constraints regarding model architecture and input are necessary to promote the physical realism of DL hydrological projections under climate change.
Guillaume Evin, Matthieu Le Lay, Catherine Fouchier, David Penot, Francois Colleoni, Alexandre Mas, Pierre-André Garambois, and Olivier Laurantin
Hydrol. Earth Syst. Sci., 28, 261–281, https://doi.org/10.5194/hess-28-261-2024, https://doi.org/10.5194/hess-28-261-2024, 2024
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Hydrological modelling of mountainous catchments is challenging for many reasons, the main one being the temporal and spatial representation of precipitation forcings. This study presents an evaluation of the hydrological modelling of 55 small mountainous catchments of the northern French Alps, focusing on the influence of the type of precipitation reanalyses used as inputs. These evaluations emphasize the added value of radar measurements, in particular for the reproduction of flood events.
Lena Katharina Schmidt, Till Francke, Peter Martin Grosse, and Axel Bronstert
Hydrol. Earth Syst. Sci., 28, 139–161, https://doi.org/10.5194/hess-28-139-2024, https://doi.org/10.5194/hess-28-139-2024, 2024
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How suspended sediment export from glacierized high-alpine areas responds to future climate change is hardly assessable as many interacting processes are involved, and appropriate physical models are lacking. We present the first study, to our knowledge, exploring machine learning to project sediment export until 2100 in two high-alpine catchments. We find that uncertainties due to methodological limitations are small until 2070. Negative trends imply that peak sediment may have already passed.
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-264, https://doi.org/10.5194/hess-2023-264, 2024
Revised manuscript accepted for HESS
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Large-scale hydrologic a needed tool to explore complex watershed processes and how they may evolve under a changing climate. However, calibrating them can be difficult because they are costly to run and have many unknown parameters. We implement a state-of-the-art approach to model calibration with a set of experiments in the Upper Colorado River Basin.
Salam A. Abbas, Ryan T. Bailey, Jeremy T. White, Jeffrey G. Arnold, Michael J. White, Natalja Čerkasova, and Jungang Gao
Hydrol. Earth Syst. Sci., 28, 21–48, https://doi.org/10.5194/hess-28-21-2024, https://doi.org/10.5194/hess-28-21-2024, 2024
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Research highlights.
1. Implemented groundwater module (gwflow) into SWAT+ for four watersheds with different unique hydrologic features across the United States.
2. Presented methods for sensitivity analysis, uncertainty analysis and parameter estimation for coupled models.
3. Sensitivity analysis for streamflow and groundwater head conducted using Morris method.
4. Uncertainty analysis and parameter estimation performed using an iterative ensemble smoother within the PEST framework.
Shima Azimi, Christian Massari, Giuseppe Formetta, Silvia Barbetta, Alberto Tazioli, Davide Fronzi, Sara Modanesi, Angelica Tarpanelli, and Riccardo Rigon
Hydrol. Earth Syst. Sci., 27, 4485–4503, https://doi.org/10.5194/hess-27-4485-2023, https://doi.org/10.5194/hess-27-4485-2023, 2023
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We analyzed the water budget of nested karst catchments using simple methods and modeling. By utilizing the available data on precipitation and discharge, we were able to determine the response lag-time by adopting new techniques. Additionally, we modeled snow cover dynamics and evapotranspiration with the use of Earth observations, providing a concise overview of the water budget for the basin and its subbasins. We have made the data, models, and workflows accessible for further study.
Yuhang Zhang, Aizhong Ye, Bita Analui, Phu Nguyen, Soroosh Sorooshian, Kuolin Hsu, and Yuxuan Wang
Hydrol. Earth Syst. Sci., 27, 4529–4550, https://doi.org/10.5194/hess-27-4529-2023, https://doi.org/10.5194/hess-27-4529-2023, 2023
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Our study shows that while the quantile regression forest (QRF) and countable mixtures of asymmetric Laplacians long short-term memory (CMAL-LSTM) models demonstrate similar proficiency in multipoint probabilistic predictions, QRF excels in smaller watersheds and CMAL-LSTM in larger ones. CMAL-LSTM performs better in single-point deterministic predictions, whereas QRF model is more efficient overall.
Léo C. P. Martin, Sebastian Westermann, Michele Magni, Fanny Brun, Joel Fiddes, Yanbin Lei, Philip Kraaijenbrink, Tamara Mathys, Moritz Langer, Simon Allen, and Walter W. Immerzeel
Hydrol. Earth Syst. Sci., 27, 4409–4436, https://doi.org/10.5194/hess-27-4409-2023, https://doi.org/10.5194/hess-27-4409-2023, 2023
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Across the Tibetan Plateau, many large lakes have been changing level during the last decades as a response to climate change. In high-mountain environments, water fluxes from the land to the lakes are linked to the ground temperature of the land and to the energy fluxes between the ground and the atmosphere, which are modified by climate change. With a numerical model, we test how these water and energy fluxes have changed over the last decades and how they influence the lake level variations.
Diego Araya, Pablo A. Mendoza, Eduardo Muñoz-Castro, and James McPhee
Hydrol. Earth Syst. Sci., 27, 4385–4408, https://doi.org/10.5194/hess-27-4385-2023, https://doi.org/10.5194/hess-27-4385-2023, 2023
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Dynamical systems are used by many agencies worldwide to produce seasonal streamflow forecasts, which are critical for decision-making. Such systems rely on hydrology models, which contain parameters that are typically estimated using a target performance metric (i.e., objective function). This study explores the effects of this decision across mountainous basins in Chile, illustrating tradeoffs between seasonal forecast quality and the models' capability to simulate streamflow characteristics.
Cited articles
Abbaspour, K. C.: SWAT-CUP4: SWAT Calibration and Uncertainty Programs – A User Manual, EAWAG Swiss Federal Institute of Aquatic Science and Technology, 103 pp., 2011.
Abbaspour, K. C., Johnson, C. A., and van Genuchten, M. T.: Estimating uncertain flow and transport parameters using a sequential uncertainty fitting procedure, Vadose Zone J., 3, 1340–1352, 2004.
Abbaspour, K. C., Yang, J., Maximov, I., Siber, R., Bogner, K., Mieleitner, J., Zobrist, J., and Srinivasan, R.: Modelling hydrology and water quality in the pre-ailpine/alpine Thur watershed using SWAT, J. Hydrol., 333, 413–430, https://doi.org/10.1016/j.jhydrol.2006.09.014, 2007.
Abbaspour, K. C., Faramarzi, M., Ghasemi, S. S., and Yang, H.: Assessing the impact of climate change on water resources in Iran, Water Resour. Res., 45, W10434, https://doi.org/10.1029/2008wr007615, 2009.
Adiku, S. G. K., Reichstein, M., Lohila, A., Dinh, N. Q., Aurela, M., Laurila, T., Tenhunen, J. D.,: PIXGRO: A model for simulating the ecosystem CO2 exchange and growth of spring barley, Ecol. Modell., 190, 260–276, 2006.
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop Evapotranspiration – Guidlines for Computing Crop Water Requirements, FAO – Food and Agriculture Organization of the United Nations, Rome, Italy, FAO Irrigation and Drainage Paper 56, 203 pp., 1988.
Andersson, J. C. M., Zehnder, A. J. B., Jewitt, G. P. W., and Yang, H.: Water availability, demand and reliability of in situ water harvesting in smallholder rain-fed agriculture in the Thukela River Basin, South Africa, Hydrol. Earth Syst. Sci., 13, 2329–2347, https://doi.org/10.5194/hess-13-2329-2009, 2009.
Arnold, J. G., Srinivasan, R., Muttiah, R. S., and Williams, J. R.: Large area hydrologic modeling and assessment – Part 1: Model development, J. Am. Water Resour. Assoc., 34, 73–89, https://doi.org/10.1111/j.1752-1688.1998.tb05961.x, 1998.
Arnhold, S., Ruidisch, M., Bartsch, S., Shope, C. L., and Huwe, B.,: Simulation of runoff patterns and soil erosion on mountainous farmland with and without plastic-covered ridge-furrow cultivation in South Korea, Trans. ASABE, 56, 667–679, 2013.
Bartsch, S., Frei, S., Ruidisch, M., Shope, C. L., Peiffer, S., Kim, B., and Fleckenstein, J. H.: River-aquifer exchange fluxes under monsoonal climate conditions, J. Hydrol., 509, 601–614, https://doi.org/10.1016/j.jhydrol.2013.12.005, 2014.
Bennett, N. D., Croke, B. F., Guariso, G., Guillaume, J. H., Hamilton, S. H., Jakeman, A. J., and Andreassian, V.: Characterising performance of environmental models, Environ. Modell. Softw., 40, 20 pp., https://doi.org/10.1016/j.envsoft.2012.09.011, 2012.
Berka, C., Schreier, H., and Hall, K.: Linking water quality with agricultural intensification in a rural watershed, Water Air Soil Pollut., 127, 389–401, https://doi.org/10.1023/a:1005233005364, 2001.
Butts, M. B., Payne, J. T., Kristensen, M., and Madsen, H.: An evaluation of the impact of model structure on hydrological modelling uncertainty for streamflow simulation, J. Hydrol., 298, 242–266, https://doi.org/10.1016/j.jhydrol.2004.03.042, 2004.
Calder, I. R.: Hydrologic effects of land use change, in: Handbook of Hydrology, edited by: Maidment, D. R., McGraw Hill, Inc., New York, NY, 1992.
Cho, J., Bosch, D., Vellidis, G., Lowrance, R., and Strickland, T.: Multi-site evaluation of hydrology component of swat in the coastal plain of Southwest Georgia, Hydrol. Process., 27, 1691–1700, https://doi.org/10.1002/hyp.9341, 2012.
Choi, G., Lee, B., Kang, S., and Tenhunen, J.: Variations of Summertime Temperature Lapse Rate within a Mountainous Basin in the Republic of Korea – A case study of Punch Bowl, Yanggu in 2009, 2010.
Dessu, S. B. and Melesse, A. M.: Modelling the rainfall-runoff process of the Mara River basin using the Soil and Water Assessment Tool, Hydrol. Process., 26, 4038–4049, https://doi.org/10.1002/hyp.9205, 2012.
Duan, Q., Sorooshian, S., Gupta, V., Rousseau, A. N., and Turcotte, R.: Calibration of watershed models, American Geophysical Union, Washington D.C., 2003.
Eckhardt, K.: How to construct recursive digital filters for baseflow separation, Hydrol. Process., 19, 507–515, 2005.
Faramarzi, M., Abbaspour, K. C., Schulin, R., and Yang, H.: Modelling blue and green water resources availability in Iran, Hydrol. Process., 23, 486–501, https://doi.org/10.1002/hyp.7160, 2009.
Forti, M. C., Neal, C., and Jenkins, A.: Modeling perspective of the deforestation impact in stream water-quality of small preserved forested areas in the Amazonian rain-forest, Water Air Soil Pollut., 79, 325–337, https://doi.org/10.1007/bf01100445, 1995.
Gassman, P. W., Reyes, M. R., Green, C. H., and Arnold, J. G.: The soil and water assessment tool: Historical development, applications, and future research directions, Trans. ASABE, 50, 1211–1250, 2007.
Green, H. and Ampt, G. A.: Studies on Soil Physics: Part II – The Permeability of an Ideal Soil to Air and Water, The J. Agr. Sci., 5, 1–26, https://doi.org/10.1017/S0021859600001751, 1912.
Güngör, Ö. and Göncü, S.: Application of the soil and water assessment tool model on the Lower Porsuk Stream Watershed, Hydrol. Process., 27, 453–466, https://doi.org/10.1002/hyp.9228, 2012.
Hargreaves, G. H. and Samani, Z. A.: Reference crop evapotranspiration from temperature, Appl. Eng. Agr., 1, 96–99, 1985.
Haverkamp, S., Srinivasan, R., Frede, H.-G., and Santhi, C.: Subwatershed spatial analysis tool:discretization of a distributed hydrologic model by statistical criteria, J. Am. Water Resour. Assoc., 38, 1723–1733, 2002.
Jha, M., Gassman, P. W., Secchi, S., Gu, R., and Arnold, J.: Effect of watershed subdivision on swat flow, sediment, and nutrient predictions, J. Am. Water Resour. Assoc., 40, 811–825, https://doi.org/10.1111/j.1752-1688.2004.tb04460.x, 2004.
Jo, K.-W. and Park, J.-H.: Rapid Release and Changing Sources of Pb in a Mountainous Watershed during Extreme Rainfall Events, Environ. Sci. Technol., 44, 9324–9329, https://doi.org/10.1021/es102109a, 2010.
Jun, M.: Device for Reducing Muddy Water in the Watershed of Soyang Dam, Regional Institute of Gangwon, South Korea, 2009.
Jung, B.-J., Lee, H.-J., Jeong, J.-J., Owen, J., Kim, B., Meusburger, K., Alewell, C., Gebauer, G., Shope, C., and Park, J.-H.: Storm pulses and varying sources of hydrologic carbon export from a mountainous watershed, J. Hydrol., 440–441, 90–101, https://doi.org/10.1016/j.jhydrol.2012.03.030, 2012.
Khakbaz, B., Imam, B., Hsu, K., and Sorooshian, S.: From lumped to distributed via semi-distributed: Calibration strategies for semi-distributed hydrologic models, J. Hydrol., 418–419, 61–77, https://doi.org/10.1016/j.jhydrol.2009.02.021, 2012.
Kim, I., Jeong, G. Y., Park, S., and Tenhunen, J.: Predicted Land Use Change in the Soyang River Basin, South Korea, 2011 TERRECO Science Conference, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany, October 2–7, 2011.
Kwon, Y. S., Lee, H. H., Han, U., Kim, W. H., Kim, D. J., Kim, D. I., and Youm, S. J.: Terrain analysis of Haean Basin in terms of earth science, J. Korean Earth Sci. Soc., 11, 236–241, 1990.
Lam, Q. D., Schmalz, B., and Fohrer, N.: Assessing the spatial and temporal variations of water quality in lowland areas, Northern Germany, J. Hydrol., 438–439, 137–147, https://doi.org/10.1016/j.jhydrol.2012.03.011, 2012.
Lee, H. J., Chun, K. W. Shope, C. L., Park, J. H.,.: Detecting rapid changes in stream water quality in mountainous forested watersheds during the monsoon period – The importance of high-frequency monitoring, J. Hydrol., in review, 2014.
Lee, J. W., Eum, J. S., Kim, B., Jang, W. S., Ryu, J. C., Kang, H. W., Kim, K. S., and Lim, K. J.: Water Quality Prediction at Mandae Watershed using SWAT and Water Quality Improvement with Vegetated Filter Strip, J. Korean Soc. Agr. Eng., 53, 37–45, https://doi.org/10.5389/KSAE.2011.53.1.037, 2011.
Lee, J. M., Ryu, J. C., Kang, H. W., Kang, H. S., Kum, D. H., Jang, C. H., Choi, J. D., and Lim, K. J.: Evaluation of SWAT Flow and Sediment Estimation and Effects of Soil Erosion Best Management Practices, J. Korean Soc. Agr. Eng., 54, 99–108, https://doi.org/10.5389/KSAE.2012.54.1.099, 2012.
Mekonnen, M. A., Worman, A., Dargahi, B., and Gebeyehu, A.: Hydrological modelling of Ethiopian catchments using limited data, Hydrol. Process., 23, 3401–3408, https://doi.org/10.1002/hyp.7470, 2009.
Monteith, J. L.: Evaporation and the Environment, in: The state and movement of water in living organisms, edited by: Fogg, G. E., Cambridge University Press, 205–234, 1965.
Moriasi, D. N., Arnold, J. G., Liew, M. W. V., Bingner, R. L., Harmel, R. D., and Veith, T. L.: Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations, Trans. ASABE, 50, 885–900, 2007.
Nash, J. E. and Sutcliffe, J. V.: River Flow Forecasting through Conceptual Models Part 1 – A Discussion of Principles, J. Hydrol. (Amsterdam), 10, 282–290, 1970.
Neitsch, S. L., Arnold, J. G., Kiniry, J. R., Srinivasan, R., and Williams, J. R.: Soil and Water Assessment Tool Input/Output File Documentation Version 2009, Grassland, Soil and Water Research Laboratory, Agricultural Research Service and Blackland Research Center, Texas Agricultural Experiment Station, College Station, Texas, 2010.
Neitsch, S. L., Arnold, J. G., Kiniry, J. R., and Williams, J. R.: Soil and Water Assessment Tool Theoretical Documentation Version 2009, Grassland, Soil and Water Research Laboratory, Agricultural ResearchService and Blackland Research Center, Texas Agricultural Experiment Station, College Station, Texas, 2011.
Nguyen, T., Hoang, V. N., and Seo, B.: Cost and environmental efficiency of rice farms in South Korea, Agr. Econom., 43, 367–376, 2012.
Notter, B., MacMillan, L., Viviroli, D., Weingartner, R., and Liniger, H.-P.: Impacts of environmental change on water resources in the Mt. Kenya region, J. Hydrol., 343, 266–278, https://doi.org/10.1016/j.jhydrol.2007.06.022, 2007.
Notter, B., Hurni, H., Wiesmann, U., and Abbaspour, K. C.: Modelling water provision as an ecosystem service in a large East African river basin, Hydrol. Earth Syst. Sci., 16, 69–86, https://doi.org/10.5194/hess-16-69-2012, 2012.
Penman, H. L.: Natural Evaporation from Open Water, Bare Soil and Grass, Proc. Roy. Soci. Lond A, 193, 120–145, 1948.
Priestley, C. H. B. and Taylor, R. J.: On the Assessment of Surface Heat Flux and Evaporation Using Large-Scale Parameters, Mon. Weather Rev., 100, 81–92, 1972.
Ruidisch, M., Kettering, J., Arnhold, S., and Huwe, B.: Modeling water flow in a plastic mulched ridge cultivation system on hillslopes affected by South Korean summer monsoon, Agr. Water Manage., 116, 204–217, https://doi.org/10.1016/j.agwat.2012.07.011, 2013.
Schuol, J. and Abbaspour, K. C.: Calibration and uncertainty issues of a hydrological model (SWAT) applied to West Africa, Adv. Geosci., 9, 137–143, https://doi.org/10.5194/adgeo-9-137-2006, 2006.
Schuol, J., Abbaspour, K. C., Srinivasan, R., and Yang, H.: Estimation of freshwater availability in the West African sub-continent using the SWAT hydrologic model, J. Hydrol., 352, 30–49, https://doi.org/10.1016/j.jhydrol.2007.12.025, 2008.
Setegn, S., Srinivasan, G. R., and Dargahi, B.: Hydrological modelling in the Lake Tana Basin, Ethiopia using SWAT model, The Open Hydrol. J., 2, 49-62, 2008.
Shope, C. L., Bartsch, S., Kim, K., Kim, B., Tenhunen, J., Peiffer, S., Park, J. H., Ok, Y. S., Fleckenstein, J., and Koellner, T.: A weighted, multi-method approach for accurate basin-wide streamflow estimation in an ungauged watershed, J. Hydrol., 494, 72–82, 2013.
Stehr, A., Debels, P., Romero, F., and Alcayaga, H.: Hydrological modelling with SWAT under conditions of limited data availability: evaluation of results from a Chilean case study, Hydrol. Sci. J., 53, 588–601, https://doi.org/10.1623/hysj.53.3.588, 2008.
Strauch, M., Bernhofer, C., Koide, S., Volk, M., Lorz, C., and Makeschin, F.: Using precipitation data ensemble for uncertainty analysis in SWAT streamflow simulation, J. Hydrol., 414, 413–424, 2012.
Strauch, M., Lima, J. E., Volk, M., Lorz, C., and Makeschin, F.: The impact of Best Management Practices on simulated streamflow and sediment load in a Central Brazilian catchment, J. Environ. Manage., 127, S24–S36, 2013.
Tenhunen, J., Seo, B., and Lee, B.: Spatial setting of the TERRECO project in the Haean catchment of Yanggu-gun and the Soyang watershed in Gangwan-do, AsiaFlux Training Course on Flux Monitoring: From Theory to Application, Seoul, South Korea, 2011,
Tilman, D., Cassman, K. G., Matson, P. A., Naylor, R., and Polasky, S.: Agricultural sustainability and intensive production practices, Nature, 418, 671–677, https://doi.org/10.1038/nature01014, 2002.
Tripathi, M. P., Raghuwanshi, N. S., and Rao, G. P.: Effect of watershed subdivision on simulation of water balance components, Hydrol. Process., 20, 1137–1156, https://doi.org/10.1002/hyp.5927, 2006.
U.S.D.A.: Soil Conservation Survey SCS, National Engineering Hand Book, Section 4, in: Hydrology, edited by: U.S.D.A, Washington, DC, 1972.
Volk, M., Liersch, S., and Schmidt, G.: Towards the implementation of the European Water Framework Directive?: Lessons learned from water quality simulations in an agricultural watershed, Land Use Pol., 26, 580–588, 2009.
Wilson, C. B., Valdes, J. B., and Rodriguez-Iturbe, I.: On the influence of the spatial distribution of rainfall on storm runoff, Water Resour. Res., 15, 321–328, https://doi.org/10.1029/WR015i002p00321, 1979.
Xu, N., Saiers, J. E., Wilson, H. F., and Raymond, P. A.: Simulating streamflow and dissolved organic matter export from a forested watershed, Water Resour. Res., 48, W05519, https://doi.org/10.1029/2011wr011423, 2012a.
Xu, Y. D., Fu, B. J., He, C. S., and Gao, G. Y.: Watershed discretization based on multiple factors and its application in the Chinese Loess Plateau, Hydrol. Earth Syst. Sci., 16, 59–68, https://doi.org/10.5194/hess-16-59-2012, 2012b.
Yang, J., Reichert, P., Abbaspour, K. C., Xia, J., and Yang, H.: Comparing uncertainty analysis techniques for a SWAT application to the Chaohe Basin in China, J. Hydrol., 358, 23 pp., https://doi.org/10.1016/j.jhydrol.2008.05.012, 2008.
Yanggu County Office: Yanggu statististical year-book, 2002–2011, Yanggu, Gangwon, Republic of Korea, 2012.
