Articles | Volume 22, issue 2
https://doi.org/10.5194/hess-22-1095-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/hess-22-1095-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Cutting-edge case studies
| 
08 Feb 2018
Cutting-edge case studies |
| 08 Feb 2018
| 08 Feb 2018
Assessment of the Weather Research and Forecasting (WRF) model for simulation of extreme rainfall events in the upper Ganga Basin
Ila Chawla
Department of Civil Engineering, Indian Institute of Science,
Bangalore, 560012, India
Department of Earth, Atmospheric and Planetary Sciences, Purdue
University, West Lafayette, IN 47907, USA
Krishna K. Osuri
Department of Earth and Atmospheric Sciences, NIT Rourkela, Odisha,
769008, India
Department of Agronomy- Crops, Soils, Water Sciences, Purdue
University, West Lafayette, IN 47907, USA
Department of Civil Engineering, Indian Institute of Science,
Bangalore, 560012, India
Divecha Centre for Climate Change, Indian Institute of Science,
Bangalore, 560012, India
Dev Niyogi
Department of Agronomy- Crops, Soils, Water Sciences, Purdue
University, West Lafayette, IN 47907, USA
Department of Earth, Atmospheric and Planetary Sciences, Purdue
University, West Lafayette, IN 47907, USA
Related authors
I. Chawla and P. P. Mujumdar
Hydrol. Earth Syst. Sci., 19, 3633–3651, https://doi.org/10.5194/hess-19-3633-2015, https://doi.org/10.5194/hess-19-3633-2015, 2015
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A simple hydrologic modeling-based approach to segregate the impacts of land use (LU) and climate change on streamflow is presented. Upper part of Ganga River basin in India is selected as study area for investigation. Results suggest that climate is the dominant contributor to the changes observed in the simulated streamflow. LU did not contribute significantly to the simulated streamflow which could be attributed to smaller spatial extent of sensitive LU categories in the study region.
Pankaj Dey, Jeenu Mathai, Murugesu Sivapalan, and Pradeep P. Mujumdar
Hydrol. Earth Syst. Sci., 28, 1493–1514, https://doi.org/10.5194/hess-28-1493-2024, https://doi.org/10.5194/hess-28-1493-2024, 2024
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This study explores the regional streamflow variability in Peninsular India. This variability is governed by monsoons, mountainous systems, and geologic gradients. A linkage between these influencing factors and streamflow variability is established using a Wegenerian approach and flow duration curves.
Pankaj Dey, Jeenu Mathai, Murugesu Sivapalan, and Pradeep Mujumdar
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-286, https://doi.org/10.5194/hess-2022-286, 2023
Preprint withdrawn
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This study explores the regional streamflow variability in Peninsular India – which is governed by monsoons, mountainous systems and geologic gradients. A linkage between these influencers and streamflow variability is established.
Sneha Santy, Pradeep Mujumdar, and Govindasamy Bala
EGUsphere, https://doi.org/10.5194/egusphere-2022-796, https://doi.org/10.5194/egusphere-2022-796, 2022
Preprint archived
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The percentage contribution of climate change, land use, population and industry to Ganga pollution is quantified using a coupled hydrological-water quality simulation model. Climate change is identified as the prominent driver with a percentage contribution above 70 %. Hence, due to the added pollution load from climate change, land use projections, and industrial growth, the proposed treatment for Ganga in mid 21st century is not sufficient to bring down Ganga pollution.
Jeenu Mathai and Pradeep P. Mujumdar
Hydrol. Earth Syst. Sci., 26, 2019–2033, https://doi.org/10.5194/hess-26-2019-2022, https://doi.org/10.5194/hess-26-2019-2022, 2022
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With availability of large samples of data in catchments, it is necessary to develop indices that describe the streamflow processes. This paper describes new indices applicable for the rising and falling limbs of streamflow hydrographs. The indices provide insights into the drivers of the hydrographs. The novelty of the work is on differentiating hydrographs by their time irreversibility property and offering an alternative way to recognize primary drivers of streamflow hydrographs.
Pushpendra Kumar Singh, Pankaj Dey, Sharad Kumar Jain, and Pradeep P. Mujumdar
Hydrol. Earth Syst. Sci., 24, 4691–4707, https://doi.org/10.5194/hess-24-4691-2020, https://doi.org/10.5194/hess-24-4691-2020, 2020
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Like in all ancient civilisations, the need to manage water propelled the growth of hydrological science in ancient India also. In this paper, we provide some fascinating glimpses into the hydrological, hydraulic, and related engineering knowledge that existed in ancient India, as discussed in contemporary literature and recent explorations and findings. Many interesting dimensions of early scientific endeavours emerge as we investigate deeper into ancient texts, including Indian mythology.
I. Chawla and P. P. Mujumdar
Hydrol. Earth Syst. Sci., 19, 3633–3651, https://doi.org/10.5194/hess-19-3633-2015, https://doi.org/10.5194/hess-19-3633-2015, 2015
Short summary
Short summary
A simple hydrologic modeling-based approach to segregate the impacts of land use (LU) and climate change on streamflow is presented. Upper part of Ganga River basin in India is selected as study area for investigation. Results suggest that climate is the dominant contributor to the changes observed in the simulated streamflow. LU did not contribute significantly to the simulated streamflow which could be attributed to smaller spatial extent of sensitive LU categories in the study region.
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
Potential for historically unprecedented Australian droughts from natural variability and climate change
Flood risk assessment for Indian sub-continental river basins
Key ingredients in regional climate modelling for improving the representation of typhoon tracks and intensities
Divergent future drought projections in UK river flows and groundwater levels
Predicting extreme sub-hourly precipitation intensification based on temperature shifts
Hydroclimatic processes as the primary drivers of the Early Khvalynian transgression of the Caspian Sea: new developments
Accounting for hydroclimatic properties in flood frequency analysis procedures
Understanding the influence of “hot” models in climate impact studies: a hydrological perspective
A semi-parametric hourly space–time weather generator
A principal-component-based strategy for regionalisation of precipitation intensity–duration–frequency (IDF) statistics
Accounting for precipitation asymmetry in a multiplicative random cascade disaggregation model
Seasonal soil moisture and crop yield prediction with fifth-generation seasonal forecasting system (SEAS5) long-range meteorological forecasts in a land surface modelling approach
A genetic particle filter scheme for univariate snow cover assimilation into Noah-MP model across snow climates
Investigating the response of land–atmosphere interactions and feedbacks to spatial representation of irrigation in a coupled modeling framework
Validation of precipitation reanalysis products for rainfall-runoff modelling in Slovenia
Identification of compound drought and heatwave events on a daily scale and across four seasons
Statistical post-processing of precipitation forecasts using circulation classifications and spatiotemporal deep neural networks
Sensitivity of the pseudo-global warming method under flood conditions: a case study from the northeastern US
Hybrid forecasting: blending climate predictions with AI models
Sensitivities of subgrid-scale physics schemes, meteorological forcing, and topographic radiation in atmosphere-through-bedrock integrated process models: a case study in the Upper Colorado River basin
Simulating one century (1902–2009) of river discharges, low flow sequences and flood events of an alpine river from large-scale atmospheric information
Local moisture recycling across the globe
How well does a convection-permitting regional climate model represent the reverse orographic effect of extreme hourly precipitation?
Regionalisation of rainfall depth–duration–frequency curves with different data types in Germany
The suitability of a seasonal ensemble hybrid framework including data-driven approaches for hydrological forecasting
Continuous streamflow prediction in ungauged basins: long short-term memory neural networks clearly outperform traditional hydrological models
Daily ensemble river discharge reforecasts and real-time forecasts from the operational Global Flood Awareness System
Spatial distribution of oceanic moisture contributions to precipitation over the Tibetan Plateau
Ensemble streamflow prediction considering the influence of reservoirs in Narmada River Basin, India
Declining water resources in response to global warming and changes in atmospheric circulation patterns over southern Mediterranean France
Linking the complementary evaporation relationship with the Budyko framework for ungauged areas in Australia
Risks of seasonal extreme rainfall events in Bangladesh under 1.5 and 2.0 °C warmer worlds – how anthropogenic aerosols change the story
Pan evaporation is increased by submerged macrophytes
Evaluation of water flux predictive models developed using eddy-covariance observations and machine learning: a meta-analysis
Characterizing basin-scale precipitation gradients in the Third Pole region using a high-resolution atmospheric simulation-based dataset
Assessing decadal to centennial scale nonstationary variability in meteorological drought trends
A comparison of hydrological models with different level of complexity in Alpine regions in the context of climate change
Modelling evaporation with local, regional and global BROOK90 frameworks: importance of parameterization and forcing
Hydrological concept formation inside long short-term memory (LSTM) networks
A two-step merging strategy for incorporating multi-source precipitation products and gauge observations using machine learning classification and regression over China
Hydrometeorological evaluation of two nowcasting systems for Mediterranean heavy precipitation events with operational considerations
On the links between sub-seasonal clustering of extreme precipitation and high discharge in Switzerland and Europe
Regional, multi-decadal analysis on the Loire River basin reveals that stream temperature increases faster than air temperature
Investigating the response of leaf area index to droughts in southern African vegetation using observations and model simulations
Recent decrease in summer precipitation over the Iberian Peninsula closely links to reduction in local moisture recycling
Exploring the possible role of satellite-based rainfall data in estimating inter- and intra-annual global rainfall erosivity
Critical transitions in the hydrological system: early-warning signals and network analysis
Testing a maximum evaporation theory over saturated land: implications for potential evaporation estimation
The role of morphology in the spatial distribution of short-duration rainfall extremes in Italy
Impact of correcting sub-daily climate model biases for hydrological studies
Georgina M. Falster, Nicky M. Wright, Nerilie J. Abram, Anna M. Ukkola, and Benjamin J. Henley
Hydrol. Earth Syst. Sci., 28, 1383–1401, https://doi.org/10.5194/hess-28-1383-2024, https://doi.org/10.5194/hess-28-1383-2024, 2024
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Multi-year droughts have severe environmental and economic impacts, but the instrumental record is too short to characterise multi-year drought variability. We assessed the nature of Australian multi-year droughts using simulations of the past millennium from 11 climate models. We show that multi-decadal
megadroughtsare a natural feature of the Australian hydroclimate. Human-caused climate change is also driving a tendency towards longer droughts in eastern and southwestern Australia.
Urmin Vegad, Yadu Pokhrel, and Vimal Mishra
Hydrol. Earth Syst. Sci., 28, 1107–1126, https://doi.org/10.5194/hess-28-1107-2024, https://doi.org/10.5194/hess-28-1107-2024, 2024
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A large population is affected by floods, which leave their footprints through human mortality, migration, and damage to agriculture and infrastructure, during almost every summer monsoon season in India. Despite the massive damage of floods, sub-basin level flood risk assessment is still in its infancy and needs to be improved. Using hydrological and hydrodynamic models, we reconstructed sub-basin level observed floods for the 1901–2020 period.
Qi Sun, Patrick Olschewski, Jianhui Wei, Zhan Tian, Laixiang Sun, Harald Kunstmann, and Patrick Laux
Hydrol. Earth Syst. Sci., 28, 761–780, https://doi.org/10.5194/hess-28-761-2024, https://doi.org/10.5194/hess-28-761-2024, 2024
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Tropical cyclones (TCs) often cause high economic loss due to heavy winds and rainfall, particularly in densely populated regions such as the Pearl River Delta (China). This study provides a reference to set up regional climate models for TC simulations. They contribute to a better TC process understanding and assess the potential changes and risks of TCs in the future. This lays the foundation for hydrodynamical modelling, from which the cities' disaster management and defence could benefit.
Simon Parry, Jonathan D. Mackay, Thomas Chitson, Jamie Hannaford, Eugene Magee, Maliko Tanguy, Victoria A. Bell, Katie Facer-Childs, Alison Kay, Rosanna Lane, Robert J. Moore, Stephen Turner, and John Wallbank
Hydrol. Earth Syst. Sci., 28, 417–440, https://doi.org/10.5194/hess-28-417-2024, https://doi.org/10.5194/hess-28-417-2024, 2024
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We studied drought in a dataset of possible future river flows and groundwater levels in the UK and found different outcomes for these two sources of water. Throughout the UK, river flows are likely to be lower in future, with droughts more prolonged and severe. However, whilst these changes are also found in some boreholes, in others, higher levels and less severe drought are indicated for the future. This has implications for the future balance between surface water and groundwater below.
Francesco Marra, Marika Koukoula, Antonio Canale, and Nadav Peleg
Hydrol. Earth Syst. Sci., 28, 375–389, https://doi.org/10.5194/hess-28-375-2024, https://doi.org/10.5194/hess-28-375-2024, 2024
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We present a new physical-based method for estimating extreme sub-hourly precipitation return levels (i.e., intensity–duration–frequency, IDF, curves), which are critical for the estimation of future floods. The proposed model, named TENAX, incorporates temperature as a covariate in a physically consistent manner. It has only a few parameters and can be easily set for any climate station given sub-hourly precipitation and temperature data are available.
Alexander Gelfan, Andrey Panin, Andrey Kalugin, Polina Morozova, Vladimir Semenov, Alexey Sidorchuk, Vadim Ukraintsev, and Konstantin Ushakov
Hydrol. Earth Syst. Sci., 28, 241–259, https://doi.org/10.5194/hess-28-241-2024, https://doi.org/10.5194/hess-28-241-2024, 2024
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Paleogeographical data show that 17–13 ka BP, the Caspian Sea level was 80 m above the current level. There are large disagreements on the genesis of this “Great” Khvalynian transgression of the sea, and we tried to shed light on this issue. Using climate and hydrological models as well as the paleo-reconstructions, we proved that the transgression could be initiated solely by hydroclimatic factors within the deglaciation period in the absence of the glacial meltwater effect.
Joeri B. Reinders and Samuel E. Munoz
Hydrol. Earth Syst. Sci., 28, 217–227, https://doi.org/10.5194/hess-28-217-2024, https://doi.org/10.5194/hess-28-217-2024, 2024
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Flooding presents a major hazard for people and infrastructure along waterways; however, it is challenging to study the likelihood of a flood magnitude occurring regionally due to a lack of long discharge records. We show that hydroclimatic variables like Köppen climate regions and precipitation intensity explain part of the variance in flood frequency distributions and thus reduce the uncertainty of flood probability estimates. This gives water managers a tool to locally improve flood analysis.
Mehrad Rahimpour Asenjan, Francois Brissette, Jean-Luc Martel, and Richard Arsenault
Hydrol. Earth Syst. Sci., 27, 4355–4367, https://doi.org/10.5194/hess-27-4355-2023, https://doi.org/10.5194/hess-27-4355-2023, 2023
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Climate models are central to climate change impact studies. Some models project a future deemed too hot by many. We looked at how including hot models may skew the result of impact studies. Applied to hydrology, this study shows that hot models do not systematically produce hydrological outliers.
Ross Pidoto and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 3957–3975, https://doi.org/10.5194/hess-27-3957-2023, https://doi.org/10.5194/hess-27-3957-2023, 2023
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Long continuous time series of meteorological variables (i.e. rainfall, temperature) are required for the modelling of floods. Observed time series are generally too short or not available. Weather generators are models that reproduce observed weather time series. This study extends an existing station-based rainfall model into space by enforcing observed spatial rainfall characteristics. To model other variables (i.e. temperature) the model is then coupled to a simple resampling approach.
Kajsa Maria Parding, Rasmus Emil Benestad, Anita Verpe Dyrrdal, and Julia Lutz
Hydrol. Earth Syst. Sci., 27, 3719–3732, https://doi.org/10.5194/hess-27-3719-2023, https://doi.org/10.5194/hess-27-3719-2023, 2023
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Intensity–duration–frequency (IDF) curves describe the likelihood of extreme rainfall and are used in hydrology and engineering, for example, for flood forecasting and water management. We develop a model to estimate IDF curves from daily meteorological observations, which are more widely available than the observations on finer timescales (minutes to hours) that are needed for IDF calculations. The method is applied to all data at once, making it efficient and robust to individual errors.
Kaltrina Maloku, Benoit Hingray, and Guillaume Evin
Hydrol. Earth Syst. Sci., 27, 3643–3661, https://doi.org/10.5194/hess-27-3643-2023, https://doi.org/10.5194/hess-27-3643-2023, 2023
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High-resolution precipitation data, needed for many applications in hydrology, are typically rare. Such data can be simulated from daily precipitation with stochastic disaggregation. In this work, multiplicative random cascades are used to disaggregate time series of 40 min precipitation from daily precipitation for 81 Swiss stations. We show that very relevant statistics of precipitation are obtained when precipitation asymmetry is accounted for in a continuous way in the cascade generator.
Theresa Boas, Heye Reemt Bogena, Dongryeol Ryu, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 27, 3143–3167, https://doi.org/10.5194/hess-27-3143-2023, https://doi.org/10.5194/hess-27-3143-2023, 2023
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In our study, we tested the utility and skill of a state-of-the-art forecasting product for the prediction of regional crop productivity using a land surface model. Our results illustrate the potential value and skill of combining seasonal forecasts with modelling applications to generate variables of interest for stakeholders, such as annual crop yield for specific cash crops and regions. In addition, this study provides useful insights for future technical model evaluations and improvements.
Yuanhong You, Chunlin Huang, Zuo Wang, Jinliang Hou, Ying Zhang, and Peipei Xu
Hydrol. Earth Syst. Sci., 27, 2919–2933, https://doi.org/10.5194/hess-27-2919-2023, https://doi.org/10.5194/hess-27-2919-2023, 2023
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This study aims to investigate the performance of a genetic particle filter which was used as a snow data assimilation scheme across different snow climates. The results demonstrated that the genetic algorithm can effectively solve the problem of particle degeneration and impoverishment in a particle filter algorithm. The system has revealed a low sensitivity to the particle number in point-scale application of the ground snow depth measurement.
Patricia Lawston-Parker, Joseph A. Santanello Jr., and Nathaniel W. Chaney
Hydrol. Earth Syst. Sci., 27, 2787–2805, https://doi.org/10.5194/hess-27-2787-2023, https://doi.org/10.5194/hess-27-2787-2023, 2023
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Irrigation has been shown to impact weather and climate, but it has only recently been considered in prediction models. Prescribing where (globally) irrigation takes place is important to accurately simulate its impacts on temperature, humidity, and precipitation. Here, we evaluated three different irrigation maps in a weather model and found that the extent and intensity of irrigated areas and their boundaries are important drivers of weather impacts resulting from human practices.
Marcos Julien Alexopoulos, Hannes Müller-Thomy, Patrick Nistahl, Mojca Šraj, and Nejc Bezak
Hydrol. Earth Syst. Sci., 27, 2559–2578, https://doi.org/10.5194/hess-27-2559-2023, https://doi.org/10.5194/hess-27-2559-2023, 2023
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For rainfall-runoff simulation of a certain area, hydrological models are used, which requires precipitation data and temperature data as input. Since these are often not available as observations, we have tested simulation results from atmospheric models. ERA5-Land and COSMO-REA6 were tested for Slovenian catchments. Both lead to good simulations results. Their usage enables the use of rainfall-runoff simulation in unobserved catchments as a requisite for, e.g., flood protection measures.
Baoying Shan, Niko E. C. Verhoest, and Bernard De Baets
EGUsphere, https://doi.org/10.5194/egusphere-2023-147, https://doi.org/10.5194/egusphere-2023-147, 2023
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This study developed a convenient and new method to identify the occurrence of droughts, heatwaves, and co-occurring droughts and heatwaves across four seasons. From that, we could know the drought (or heatwave) starts on which day and ends on which day. We found an increase in the frequency of heatwaves and the co-occurring droughts and heatwaves in Belgium caused by climate change. We also found that different months have different chances of co-occurring droughts and heatwaves.
Tuantuan Zhang, Zhongmin Liang, Wentao Li, Jun Wang, Yiming Hu, and Binquan Li
Hydrol. Earth Syst. Sci., 27, 1945–1960, https://doi.org/10.5194/hess-27-1945-2023, https://doi.org/10.5194/hess-27-1945-2023, 2023
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We use circulation classifications and spatiotemporal deep neural networks to correct raw daily forecast precipitation by combining large-scale circulation patterns with local spatiotemporal information. We find that the method not only captures the westward and northward movement of the western Pacific subtropical high but also shows substantially higher bias-correction capabilities than existing standard methods in terms of spatial scale, timescale, and intensity.
Zeyu Xue, Paul Ullrich, and Lai-Yung Ruby Leung
Hydrol. Earth Syst. Sci., 27, 1909–1927, https://doi.org/10.5194/hess-27-1909-2023, https://doi.org/10.5194/hess-27-1909-2023, 2023
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We examine the sensitivity and robustness of conclusions drawn from the PGW method over the NEUS by conducting multiple PGW experiments and varying the perturbation spatial scales and choice of perturbed meteorological variables to provide a guideline for this increasingly popular regional modeling method. Overall, we recommend PGW experiments be performed with perturbations to temperature or the combination of temperature and wind at the gridpoint scale, depending on the research question.
Louise J. Slater, Louise Arnal, Marie-Amélie Boucher, Annie Y.-Y. Chang, Simon Moulds, Conor Murphy, Grey Nearing, Guy Shalev, Chaopeng Shen, Linda Speight, Gabriele Villarini, Robert L. Wilby, Andrew Wood, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 27, 1865–1889, https://doi.org/10.5194/hess-27-1865-2023, https://doi.org/10.5194/hess-27-1865-2023, 2023
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Hybrid forecasting systems combine data-driven methods with physics-based weather and climate models to improve the accuracy of predictions for meteorological and hydroclimatic events such as rainfall, temperature, streamflow, floods, droughts, tropical cyclones, or atmospheric rivers. We review recent developments in hybrid forecasting and outline key challenges and opportunities in the field.
Zexuan Xu, Erica R. Siirila-Woodburn, Alan M. Rhoades, and Daniel Feldman
Hydrol. Earth Syst. Sci., 27, 1771–1789, https://doi.org/10.5194/hess-27-1771-2023, https://doi.org/10.5194/hess-27-1771-2023, 2023
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The goal of this study is to understand the uncertainties of different modeling configurations for simulating hydroclimate responses in the mountainous watershed. We run a group of climate models with various configurations and evaluate them against various reference datasets. This paper integrates a climate model and a hydrology model to have a full understanding of the atmospheric-through-bedrock hydrological processes.
Caroline Legrand, Benoît Hingray, Bruno Wilhelm, and Martin Ménégoz
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-92, https://doi.org/10.5194/hess-2023-92, 2023
Revised manuscript accepted for HESS
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Climate change is expected to increase flood hazard worldwide. The evolution is typically estimated from multi-model chains, where regional hydrological scenarios are simulated from weather scenarios derived from coarse resolution atmospheric outputs of climate models. We show that two such chains are able to reproduce, from an atmospheric reanalysis, the 1902–2009 discharge variations and floods of the Upper Rhône alpine River, provided that the weather scenarios are bias-corrected.
Jolanda J. E. Theeuwen, Arie Staal, Obbe A. Tuinenburg, Bert V. M. Hamelers, and Stefan C. Dekker
Hydrol. Earth Syst. Sci., 27, 1457–1476, https://doi.org/10.5194/hess-27-1457-2023, https://doi.org/10.5194/hess-27-1457-2023, 2023
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Evaporation changes over land affect rainfall over land via moisture recycling. We calculated the local moisture recycling ratio globally, which describes the fraction of evaporated moisture that rains out within approx. 50 km of its source location. This recycling peaks in summer as well as over wet and elevated regions. Local moisture recycling provides insight into the local impacts of evaporation changes and can be used to study the influence of regreening on local rainfall.
Eleonora Dallan, Francesco Marra, Giorgia Fosser, Marco Marani, Giuseppe Formetta, Christoph Schär, and Marco Borga
Hydrol. Earth Syst. Sci., 27, 1133–1149, https://doi.org/10.5194/hess-27-1133-2023, https://doi.org/10.5194/hess-27-1133-2023, 2023
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Convection-permitting climate models could represent future changes in extreme short-duration precipitation, which is critical for risk management. We use a non-asymptotic statistical method to estimate extremes from 10 years of simulations in an orographically complex area. Despite overall good agreement with rain gauges, the observed decrease of hourly extremes with elevation is not fully represented by the model. Climate model adjustment methods should consider the role of orography.
Bora Shehu, Winfried Willems, Henrike Stockel, Luisa-Bianca Thiele, and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 1109–1132, https://doi.org/10.5194/hess-27-1109-2023, https://doi.org/10.5194/hess-27-1109-2023, 2023
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Rainfall volumes at varying duration and frequencies are required for many engineering water works. These design volumes have been provided by KOSTRA-DWD in Germany. However, a revision of the KOSTRA-DWD is required, in order to consider the recent state-of-the-art and additional data. For this purpose, in our study, we investigate different methods and data available to achieve the best procedure that will serve as a basis for the development of the new KOSTRA-DWD product.
Sandra M. Hauswirth, Marc F. P. Bierkens, Vincent Beijk, and Niko Wanders
Hydrol. Earth Syst. Sci., 27, 501–517, https://doi.org/10.5194/hess-27-501-2023, https://doi.org/10.5194/hess-27-501-2023, 2023
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Forecasts on water availability are important for water managers. We test a hybrid framework based on machine learning models and global input data for generating seasonal forecasts. Our evaluation shows that our discharge and surface water level predictions are able to create reliable forecasts up to 2 months ahead. We show that a hybrid framework, developed for local purposes and combined and rerun with global data, can create valuable information similar to large-scale forecasting models.
Richard Arsenault, Jean-Luc Martel, Frédéric Brunet, François Brissette, and Juliane Mai
Hydrol. Earth Syst. Sci., 27, 139–157, https://doi.org/10.5194/hess-27-139-2023, https://doi.org/10.5194/hess-27-139-2023, 2023
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Predicting flow in rivers where no observation records are available is a daunting task. For decades, hydrological models were set up on these gauges, and their parameters were estimated based on the hydrological response of similar or nearby catchments where records exist. New developments in machine learning have now made it possible to estimate flows at ungauged locations more precisely than with hydrological models. This study confirms the performance superiority of machine learning models.
Shaun Harrigan, Ervin Zsoter, Hannah Cloke, Peter Salamon, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 27, 1–19, https://doi.org/10.5194/hess-27-1-2023, https://doi.org/10.5194/hess-27-1-2023, 2023
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Real-time river discharge forecasts and reforecasts from the Global Flood Awareness System (GloFAS) have been made publicly available, together with an evaluation of forecast skill at the global scale. Results show that GloFAS is skillful in over 93 % of catchments in the short (1–3 d) and medium range (5–15 d) and skillful in over 80 % of catchments in the extended lead time (16–30 d). Skill is summarised in a new layer on the GloFAS Web Map Viewer to aid decision-making.
Ying Li, Chenghao Wang, Ru Huang, Denghua Yan, Hui Peng, and Shangbin Xiao
Hydrol. Earth Syst. Sci., 26, 6413–6426, https://doi.org/10.5194/hess-26-6413-2022, https://doi.org/10.5194/hess-26-6413-2022, 2022
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Spatial quantification of oceanic moisture contribution to the precipitation over the Tibetan Plateau (TP) contributes to the reliable assessments of regional water resources and the interpretation of paleo archives in the region. Based on atmospheric reanalysis datasets and numerical moisture tracking, this work reveals the previously underestimated oceanic moisture contributions brought by the westerlies in winter and the overestimated moisture contributions from the Indian Ocean in summer.
Urmin Vegad and Vimal Mishra
Hydrol. Earth Syst. Sci., 26, 6361–6378, https://doi.org/10.5194/hess-26-6361-2022, https://doi.org/10.5194/hess-26-6361-2022, 2022
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Floods cause enormous damage to infrastructure and agriculture in India. However, the utility of ensemble meteorological forecast for hydrologic prediction has not been examined. Moreover, Indian river basins have a considerable influence of reservoirs that alter the natural flow variability. We developed a hydrologic modelling-based streamflow prediction considering the influence of reservoirs in India.
Camille Labrousse, Wolfgang Ludwig, Sébastien Pinel, Mahrez Sadaoui, Andrea Toreti, and Guillaume Lacquement
Hydrol. Earth Syst. Sci., 26, 6055–6071, https://doi.org/10.5194/hess-26-6055-2022, https://doi.org/10.5194/hess-26-6055-2022, 2022
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The interest of this study is to demonstrate that we identify two zones in our study area whose hydroclimatic behaviours are uneven. By investigating relationships between the hydroclimatic conditions in both clusters for past observations with the overall atmospheric functioning, we show that the inequalities are mainly driven by a different control of the atmospheric teleconnection patterns over the area.
Daeha Kim, Minha Choi, and Jong Ahn Chun
Hydrol. Earth Syst. Sci., 26, 5955–5969, https://doi.org/10.5194/hess-26-5955-2022, https://doi.org/10.5194/hess-26-5955-2022, 2022
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We proposed a practical method that predicts the evaporation rates on land surfaces (ET) where only atmospheric data are available. Using a traditional equation that describes partitioning of precipitation into ET and streamflow, we could approximately identify the key parameter of the predicting formulation based on land–atmosphere interactions. The simple method conditioned by local climates outperformed sophisticated models in reproducing water-balance estimates across Australia.
Ruksana H. Rimi, Karsten Haustein, Emily J. Barbour, Sarah N. Sparrow, Sihan Li, David C. H. Wallom, and Myles R. Allen
Hydrol. Earth Syst. Sci., 26, 5737–5756, https://doi.org/10.5194/hess-26-5737-2022, https://doi.org/10.5194/hess-26-5737-2022, 2022
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Extreme rainfall events are major concerns in Bangladesh. Heavy downpours can cause flash floods and damage nearly harvestable crops in pre-monsoon season. While in monsoon season, the impacts can range from widespread agricultural loss, huge property damage, to loss of lives and livelihoods. This paper assesses the role of anthropogenic climate change drivers in changing risks of extreme rainfall events during pre-monsoon and monsoon seasons at local sub-regional-scale within Bangladesh.
Brigitta Simon-Gáspár, Gábor Soós, and Angela Anda
Hydrol. Earth Syst. Sci., 26, 4741–4756, https://doi.org/10.5194/hess-26-4741-2022, https://doi.org/10.5194/hess-26-4741-2022, 2022
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Due to climate change, it is extremely important to determine evaporation as accurately as possible. In nature, there are sediments and macrophytes in the open waters; thus, one of the aims was to investigate their effect on evaporation. The second aim of this paper was to estimate daily evaporation by using different models, which, according to results, have high priority in the evaporation prediction. Water management can obtain useful information from the results of the current research.
Haiyang Shi, Geping Luo, Olaf Hellwich, Mingjuan Xie, Chen Zhang, Yu Zhang, Yuangang Wang, Xiuliang Yuan, Xiaofei Ma, Wenqiang Zhang, Alishir Kurban, Philippe De Maeyer, and Tim Van de Voorde
Hydrol. Earth Syst. Sci., 26, 4603–4618, https://doi.org/10.5194/hess-26-4603-2022, https://doi.org/10.5194/hess-26-4603-2022, 2022
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There have been many machine learning simulation studies based on eddy-covariance observations for water flux and evapotranspiration. We performed a meta-analysis of such studies to clarify the impact of different algorithms and predictors, etc., on the reported prediction accuracy. It can, to some extent, guide future global water flux modeling studies and help us better understand the terrestrial ecosystem water cycle.
Yaozhi Jiang, Kun Yang, Hua Yang, Hui Lu, Yingying Chen, Xu Zhou, Jing Sun, Yuan Yang, and Yan Wang
Hydrol. Earth Syst. Sci., 26, 4587–4601, https://doi.org/10.5194/hess-26-4587-2022, https://doi.org/10.5194/hess-26-4587-2022, 2022
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Our study quantified the altitudinal precipitation gradients (PGs) over the Third Pole (TP). Most sub-basins in the TP have positive PGs, and negative PGs are found in the Himalayas, the Hengduan Mountains and the western Kunlun. PGs are positively correlated with wind speed but negatively correlated with relative humidity. In addition, PGs tend to be positive at smaller spatial scales compared to those at larger scales. The findings can assist precipitation interpolation in the data-sparse TP.
Kyungmin Sung, Max Carl Arne Torbenson, and James H. Stagge
EGUsphere, https://doi.org/10.5194/egusphere-2022-476, https://doi.org/10.5194/egusphere-2022-476, 2022
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This study is aims to analyze seasonal and long-term trend of meteorological drought trends under climate change. We merge tree-ring proxy with instrumental datasets to understand multi-centennial trends. We develop an approach for temporal downscaling from bi-annual time series to monthly scale, and develop a model for bias correction and trend analysis across all datasets. The model was applied to 14 sites in US, and found regions with recent wetting/drying trends and rapid seasonal shifts.
Francesca Carletti, Adrien Michel, Francesca Casale, Alice Burri, Daniele Bocchiola, Mathias Bavay, and Michael Lehning
Hydrol. Earth Syst. Sci., 26, 3447–3475, https://doi.org/10.5194/hess-26-3447-2022, https://doi.org/10.5194/hess-26-3447-2022, 2022
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High Alpine catchments are dominated by the melting of seasonal snow cover and glaciers, whose amount and seasonality are expected to be modified by climate change. This paper compares the performances of different types of models in reproducing discharge among two catchments under present conditions and climate change. Despite many advantages, the use of simpler models for climate change applications is controversial as they do not fully represent the physics of the involved processes.
Ivan Vorobevskii, Thi Thanh Luong, Rico Kronenberg, Thomas Grünwald, and Christian Bernhofer
Hydrol. Earth Syst. Sci., 26, 3177–3239, https://doi.org/10.5194/hess-26-3177-2022, https://doi.org/10.5194/hess-26-3177-2022, 2022
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In the study we analysed the uncertainties of the meteorological data and model parameterization for evaporation modelling. We have taken a physically based lumped BROOK90 model and applied it in three different frameworks using global, regional and local datasets. Validating the simulations with eddy-covariance data from five stations in Germany, we found that the accuracy model parameterization plays a bigger role than the quality of the meteorological forcing.
Thomas Lees, Steven Reece, Frederik Kratzert, Daniel Klotz, Martin Gauch, Jens De Bruijn, Reetik Kumar Sahu, Peter Greve, Louise Slater, and Simon J. Dadson
Hydrol. Earth Syst. Sci., 26, 3079–3101, https://doi.org/10.5194/hess-26-3079-2022, https://doi.org/10.5194/hess-26-3079-2022, 2022
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Despite the accuracy of deep learning rainfall-runoff models, we are currently uncertain of what these models have learned. In this study we explore the internals of one deep learning architecture and demonstrate that the model learns about intermediate hydrological stores of soil moisture and snow water, despite never having seen data about these processes during training. Therefore, we find evidence that the deep learning approach learns a physically realistic mapping from inputs to outputs.
Huajin Lei, Hongyu Zhao, and Tianqi Ao
Hydrol. Earth Syst. Sci., 26, 2969–2995, https://doi.org/10.5194/hess-26-2969-2022, https://doi.org/10.5194/hess-26-2969-2022, 2022
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How to combine multi-source precipitation data effectively is one of the hot topics in hydrometeorological research. This study presents a two-step merging strategy based on machine learning for multi-source precipitation merging over China. The results demonstrate that the proposed method effectively distinguishes the occurrence of precipitation events and reduces the error in precipitation estimation. This method is robust and may be successfully applied to other areas even with scarce data.
Alexane Lovat, Béatrice Vincendon, and Véronique Ducrocq
Hydrol. Earth Syst. Sci., 26, 2697–2714, https://doi.org/10.5194/hess-26-2697-2022, https://doi.org/10.5194/hess-26-2697-2022, 2022
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The hydrometeorological skills of two new nowcasting systems for forecasting Mediterranean intense rainfall events and floods are investigated. The results reveal that up to 75 or 90 min of forecast the performance of the nowcasting system blending numerical weather prediction and extrapolation of radar estimation is higher than the numerical weather model. For lead times up to 3 h the skills are equivalent in general. Using these nowcasting systems for flash flood forecasting is also promising.
Alexandre Tuel, Bettina Schaefli, Jakob Zscheischler, and Olivia Martius
Hydrol. Earth Syst. Sci., 26, 2649–2669, https://doi.org/10.5194/hess-26-2649-2022, https://doi.org/10.5194/hess-26-2649-2022, 2022
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River discharge is strongly influenced by the temporal structure of precipitation. Here, we show how extreme precipitation events that occur a few days or weeks after a previous event have a larger effect on river discharge than events occurring in isolation. Windows of 2 weeks or less between events have the most impact. Similarly, periods of persistent high discharge tend to be associated with the occurrence of several extreme precipitation events in close succession.
Hanieh Seyedhashemi, Jean-Philippe Vidal, Jacob S. Diamond, Dominique Thiéry, Céline Monteil, Frédéric Hendrickx, Anthony Maire, and Florentina Moatar
Hydrol. Earth Syst. Sci., 26, 2583–2603, https://doi.org/10.5194/hess-26-2583-2022, https://doi.org/10.5194/hess-26-2583-2022, 2022
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Stream temperature appears to be increasing globally, but its rate remains poorly constrained due to a paucity of long-term data. Using a thermal model, this study provides a large-scale understanding of the evolution of stream temperature over a long period (1963–2019). This research highlights that air temperature and streamflow can exert joint influence on stream temperature trends, and riparian shading in small mountainous streams may mitigate warming in stream temperatures.
Shakirudeen Lawal, Stephen Sitch, Danica Lombardozzi, Julia E. M. S. Nabel, Hao-Wei Wey, Pierre Friedlingstein, Hanqin Tian, and Bruce Hewitson
Hydrol. Earth Syst. Sci., 26, 2045–2071, https://doi.org/10.5194/hess-26-2045-2022, https://doi.org/10.5194/hess-26-2045-2022, 2022
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To investigate the impacts of drought on vegetation, which few studies have done due to various limitations, we used the leaf area index as proxy and dynamic global vegetation models (DGVMs) to simulate drought impacts because the models use observationally derived climate. We found that the semi-desert biome responds strongly to drought in the summer season, while the tropical forest biome shows a weak response. This study could help target areas to improve drought monitoring and simulation.
Yubo Liu, Monica Garcia, Chi Zhang, and Qiuhong Tang
Hydrol. Earth Syst. Sci., 26, 1925–1936, https://doi.org/10.5194/hess-26-1925-2022, https://doi.org/10.5194/hess-26-1925-2022, 2022
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Our findings indicate that the reduction in contribution to the Iberian Peninsula (IP) summer precipitation is mainly concentrated in the IP and its neighboring grids. Compared with 1980–1997, both local recycling and external moisture were reduced during 1998–2019. The reduction in local recycling in the IP closely links to the disappearance of the wet years and the decreasing contribution in the dry years.
Nejc Bezak, Pasquale Borrelli, and Panos Panagos
Hydrol. Earth Syst. Sci., 26, 1907–1924, https://doi.org/10.5194/hess-26-1907-2022, https://doi.org/10.5194/hess-26-1907-2022, 2022
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Rainfall erosivity is one of the main factors in soil erosion. A satellite-based global map of rainfall erosivity was constructed using data with a 30 min time interval. It was shown that the satellite-based precipitation products are an interesting option for estimating rainfall erosivity, especially in regions with limited ground data. However, ground-based high-frequency precipitation measurements are (still) essential for accurate estimates of rainfall erosivity.
Xueli Yang, Zhi-Hua Wang, and Chenghao Wang
Hydrol. Earth Syst. Sci., 26, 1845–1856, https://doi.org/10.5194/hess-26-1845-2022, https://doi.org/10.5194/hess-26-1845-2022, 2022
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In this study, we investigated potentially catastrophic transitions in hydrological processes by identifying the early-warning signals which manifest as a
critical slowing downin complex dynamic systems. We then analyzed the precipitation network of cities in the contiguous United States and found that key network parameters, such as the nodal density and the clustering coefficient, exhibit similar dynamic behaviour, which can serve as novel early-warning signals for the hydrological system.
Zhuoyi Tu, Yuting Yang, and Michael L. Roderick
Hydrol. Earth Syst. Sci., 26, 1745–1754, https://doi.org/10.5194/hess-26-1745-2022, https://doi.org/10.5194/hess-26-1745-2022, 2022
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Here we test a maximum evaporation theory that acknowledges the interdependence between radiation, surface temperature, and evaporation over saturated land. We show that the maximum evaporation approach recovers observed evaporation and surface temperature under non-water-limited conditions across a broad range of bio-climates. The implication is that the maximum evaporation concept can be used to predict potential evaporation that has long been a major difficulty for the hydrological community.
Paola Mazzoglio, Ilaria Butera, Massimiliano Alvioli, and Pierluigi Claps
Hydrol. Earth Syst. Sci., 26, 1659–1672, https://doi.org/10.5194/hess-26-1659-2022, https://doi.org/10.5194/hess-26-1659-2022, 2022
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We have analyzed the spatial dependence of rainfall extremes upon elevation and morphology in Italy. Regression analyses show that previous rainfall–elevation relations at national scale can be substantially improved with new data, both using topography attributes and constraining the analysis within areas stemming from geomorphological zonation. Short-duration mean rainfall depths can then be estimated, all over Italy, using different parameters in each area of the geomorphological subdivision.
Mina Faghih, François Brissette, and Parham Sabeti
Hydrol. Earth Syst. Sci., 26, 1545–1563, https://doi.org/10.5194/hess-26-1545-2022, https://doi.org/10.5194/hess-26-1545-2022, 2022
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The diurnal cycles of precipitation and temperature generated by climate models are biased. This work investigates whether or not impact modellers should correct the diurnal cycle biases prior to conducting hydrological impact studies at the sub-daily scale. The results show that more accurate streamflows are obtained when the diurnal cycles biases are corrected. This is noticeable for smaller catchments, which have a quicker reaction time to changes in precipitation and temperature.
Cited articles
Argüeso, D., Hidalgo-Muñoz, J. M., Gámiz-Fortis, S. R., Esteban-Parra, M. J., Dudhia, J., and Castro-Díez, Y.: Evaluation of WRF parameterizations for climate studies over Southern Spain using a multistep regionalization, J. Climate, 24, 5633–5651, 2011.
Betts, A. K., Ball, J. H., Beljaars, A., Miller, M. J., and Viterbo, P. A.: The land surface-atmosphere interaction: A review based on observational and global modeling perspectives, J. Geophys. Res.-Atmos., 101, 7209–7225, 1996.
Betts, A. K., Chen, F., Mitchell, K. E., and Janjić, Z. I.: Assessment of the land surface and boundary layer models in two operational versions of the NCEP Eta model using FIFE data, Mon. Weather Rev., 125, 2896–2916, 1997.
Bharti, V., Singh, C., Ettema, J., and Turkington, T.: Spatiotemporal characteristics of extreme rainfall events over the Northwest Himalaya using satellite data, Int. J. Climatol., 36, 3949–3962, 2016.
Bohra, A., Basu, S., Rajagopal, E., Iyengar, G., Gupta, M. D., Ashrit, R., and Athiyaman, B.: Heavy rainfall episode over Mumbai on 26 July 2005: Assessment of NWP guidance, Curr. Sci., 90, 1188–1194, 2006.
Bright, D. R. and Mullen, S. L.: The sensitivity of the numerical simulation of the southwest monsoon boundary layer to the choice of PBL turbulence parameterization in MM5, Weather Forecast., 17, 99–114, 2002.
Cardoso, R., Soares, P., Miranda, P., and Belo-Pereira, M.: WRF high resolution simulation of Iberian mean and extreme precipitation climate, Int. J. Climatol., 33, 2591–2608, 2013.
Chang, H.-I., Kumar, A., Niyogi, D., Mohanty, U., Chen, F., and Dudhia, J.: The role of land surface processes on the mesoscale simulation of the July 26, 2005 heavy rain event over Mumbai, India, Global Planet. Change, 67, 87–103, 2009.
Chawla, I.: Chawla_2018_HESS_Data, GitHub repository, available at: https://github.com/ilachawla/Chawla_2018_HESS_Data, last access: 5 February 2018.
Chen, D. and Brutsaert, W.: Diagnostics of land surface spatial variability and water vapor flux, J. Geophys. Res.-Atmos., 100, 25595–25606, 1995.
Chen, F. and Dudhia, J.: Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: Model implementation and sensitivity, Mon. Weather Rev., 129, 569–585, 2001.
Chen, S.-H. and Sun, W.-Y.: A one-dimensional time dependent cloud model, J. Meteorol. Soc. Jpn., 80, 99–118, 2002.
Chevuturi, A. and Dimri, A.: Investigation of Uttarakhand (India) disaster-2013 using weather research and forecasting model, Nat. Hazards, 82, 1703–1726, 2016.
Chevuturi, A., Dimri, A. P., and Gunturu, U. B.: Numerical simulation of a rare winter hailstorm event over Delhi, India on 17 January 2013, Nat. Hazards Earth Syst. Sci., 14, 3331–3344, https://doi.org/10.5194/nhess-14-3331-2014, 2014.
Chevuturi, A., Dimri, A., Das, S., Kumar, A., and Niyogi, D.: Numerical simulation of an intense precipitation event over Rudraprayag in the central Himalayas during 13–14 September 2012, J. Earth Syst. Sci., 124, 1545–1561, 2015.
Choudhury, D. and Das, S.: The sensitivity to the microphysical schemes on the skill of forecasting the track and intensity of tropical cyclones using WRF-ARW model, J. Earth Syst. Sci., 126, 1–10, 2017.
Das, S., Ashrit, R., Iyengar, G. R., Mohandas, S., Gupta, M. D., George, J. P., Rajagopal, E., and Dutta, S. K.: Skills of different mesoscale models over Indian region during monsoon season: Forecast errors, J. Earth Syst. Sci., 117, 603–620, 2008.
Deardorff, J.: Efficient prediction of ground surface temperature and moisture, with inclusion of a layer of vegetation, J. Geophys. Res.-Ocean, 83, 1889–1903, 1978.
Deb, S., Srivastava, T., and Kishtawal, C.: The WRF model performance for the simulation of heavy precipitating events over Ahmedabad during August 2006, J. Earth Syst. Sci., 117, 589–602, 2008.
Dimri, A., Thayyen, R., Kibler, K., Stanton, A., Jain, S., Tullos, D., and Singh, V.: A review of atmospheric and land surface processes with emphasis on flood generation in the Southern Himalayan rivers, Sci. Total Environ., 556, 98–115, 2016.
Dube, A., Ashrit, R., Ashish, A., Sharma, K., Iyengar, G., Rajagopal, E., and Basu, S.: Forecasting the heavy rainfall during Himalayan flooding – June 2013, Weather Clim. Extr., 4, 22–34, 2014.
Dudhia, J.: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model, J. Atmos. Sci., 46, 3077–3107, 1989.
Dudhia, J.: A multi-layer soil temperature model for MM5, Preprints, The Sixth PSU/NCAR mesoscale model users' workshop, 22–24, 1996.
Efstathiou, G., Zoumakis, N., Melas, D., Lolis, C., and Kassomenos, P.: Sensitivity of WRF to boundary layer parameterizations in simulating a heavy rainfall event using different microphysical schemes. Effect on large-scale processes, Atmos. Res., 132, 125–143, 2013.
Ek, M., Mitchell, K., Lin, Y., Rogers, E., Grunmann, P., Koren, V., Gayno, G., and Tarpley, J.: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model, J. Geophys. Res.-Atmos., 108, 12-1–12-16, 2003.
Entekhabi, D., Rodriguez-Iturbe, I., and Castelli, F.: Mutual interaction of soil moisture state and atmospheric processes, J. Hydrol., 184, 3–17, 1996.
Fasullo, J. and Webster, P.: A hydrological definition of Indian monsoon onset and withdrawal, J. Climate, 16, 3200–3211, 2003.
Fonseca, R. M., Zhang, T., and Yong, K.-T.: Improved simulation of precipitation in the tropics using a modified BMJ scheme in the WRF model, Geosci. Model Dev., 8, 2915–2928, https://doi.org/10.5194/gmd-8-2915-2015, 2015.
Gadgil, S. and Sajani, S.: Monsoon precipitation in the AMIP runs, Clim. Dynam., 14, 659–689, 1998.
Gallus Jr., W. A.: Eta simulations of three extreme precipitation events: Sensitivity to resolution and convective parameterization, Weather Forecast., 14, 405–426, 1999.
Giorgi, F. and Gutowski Jr., W. J.: Regional dynamical downscaling and the CORDEX initiative, Annu. Rev. Env. Resour., 40, 467–490, 2015.
Hariprasad, K., Srinivas, C., Singh, A. B., Rao, S. V. B., Baskaran, R., and Venkatraman, B.: Numerical simulation and intercomparison of boundary layer structure with different PBL schemes in WRF using experimental observations at a tropical site, Atmos. Res., 145, 27–44, 2014.
Hazra, A., Chaudhari, H. S., Ranalkar, M., and Chen, J. P.: Role of interactions between cloud microphysics, dynamics and aerosol in the heavy rainfall event of June 2013 over Uttarakhand, India, Q. J. Roy. Meteorol. Soc., 143, 986–998, 2017.
Hong, S.-Y. and Lee, J.-W.: Assessment of the WRF model in reproducing a flash-flood heavy rainfall event over Korea, Atmos. Res., 93, 818–831, 2009.
Hong, S.-Y. and Lim, J.-O. J.: The WRF single-moment 6-class microphysics scheme (WSM6), J. Korean Meteor. Soc, 42, 129–151, 2006.
Hong, S.-Y., Noh, Y., and Dudhia, J.: A new vertical diffusion package with an explicit treatment of entrainment processes, Mon. Weather Rev., 134, 2318–2341, 2006.
Hong, S.-Y., Sunny Lim, K.-S., Kim, J.-H., Jade Lim, J.-O., and Dudhia, J.: Sensitivity study of cloud-resolving convective simulations with WRF using two bulk microphysical parameterizations: ice-phase microphysics versus sedimentation effects, J. Appl. Meteorol. Clim., 48, 61–76, 2009.
Hu, X.-M., Nielsen-Gammon, J. W., and Zhang, F.: Evaluation of three planetary boundary layer schemes in the WRF model, J. Appl. Meteorol. Clim., 49, 1831–1844, 2010.
Huffman, G.: TRMM (TMPA-RT) Near Real-Time Precipitation L3 3 hour 0.25 degree × 0.25 degree V7, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC), available at: https://disc.gsfc.nasa.gov/datacollection/TRMM_3B42RT_7.html (last access: 2 November 2017), 2016.
Janjić, Z. I.: The step-mountain eta coordinate model: Further developments of the convection, viscous sublayer, and turbulence closure schemes, Mon. Weather Rev., 122, 927–945, 1994.
Janjić, Z. I.: Comments on “Development and evaluation of a convection scheme for use in climate models”, J. Atmos. Sci., 57, 3686–3686, 2000.
Janić, Z. I.: Nonsingular implementation of the Mellor-Yamada level 2.5 scheme in the NCEP Meso model, US Department of Commerce, National Oceanic and Atmospheric Administration, National Weather Service, National Centers for Environmental Prediction, 2001.
Kain, J. S.: The Kain–Fritsch convective parameterization: an update, J. Appl. Meteorol., 43, 170–181, 2004.
Kneis, D., Chatterjee, C., and Singh, R.: Evaluation of TRMM rainfall estimates over a large Indian river basin (Mahanadi), Hydrol. Earth Syst. Sci., 18, 2493–2502, https://doi.org/10.5194/hess-18-2493-2014, 2014.
Koren, V., Schaake, J., Mitchell, K., Duan, Q. Y., Chen, F., and Baker, J.: A parameterization of snowpack and frozen ground intended for NCEP weather and climate models, J. Geophys. Res.-Atmos., 104, 19569–19585, 1999.
Kotal, S., Roy, S. S., and Roy Bhowmik, S.: Catastrophic heavy rainfall episode over Uttarakhand during 16–18 June 2013 – observational aspects, Curr. Sci, 107, 234–245, 2014.
Krishnamurthy, C. K. B., Lall, U., and Kwon, H.-H.: Changing frequency and intensity of rainfall extremes over India from 1951 to 2003, J. Climate, 22, 4737–4746, 2009.
Kumar, A., Dudhia, J., Rotunno, R., Niyogi, D., and Mohanty, U.: Analysis of the 26 July 2005 heavy rain event over Mumbai, India using the Weather Research and Forecasting (WRF) model, Q. J. Roy. Meteorol. Soc., 134, 1897–1910, 2008.
Kumar, A., Houze Jr., R. A., Rasmussen, K. L., and Peters-Lidard, C.: Simulation of a flash flooding storm at the steep edge of the Himalayas, J. Hydrometeorol., 15, 212–228, 2014.
Kumar, M. S., Shekhar, M., Krishna, S. R., Bhutiyani, M., and Ganju, A.: Numerical simulation of cloud burst event on August 05, 2010, over Leh using WRF mesoscale model, Nat. Hazards, 62, 1261–1271, 2012.
Kumar, R. A., Dudhia, J., and Roy Bhowmik, S.: Evaluation of Physics options of the Weather Research and Forecasting (WRF) Model to simulate high impact heavy rainfall events over Indian Monsoon region, Geofizika, 27, 101–125, 2010.
Li, L., Gochis, D. J., Sobolowski, S., and Mesquita, M. D.: Evaluating the present annual water budget of a Himalayan headwater river basin using a high-resolution atmosphere-hydrology model, J. Geophys. Res.-Atmos., 122, 4786–4807, 2017.
Li, X. and Pu, Z.: Sensitivity of numerical simulation of early rapid intensification of Hurricane Emily (2005) to cloud microphysical and planetary boundary layer parameterizations, Mon. Weather Rev., 136, 4819–4838, 2008.
Lin, Y.-L., Farley, R. D., and Orville, H. D.: Bulk parameterization of the snow field in a cloud model, J. Climate Appl. Meteorol., 22, 1065–1092, 1983.
Liu, J., Bray, M., and Han, D.: Sensitivity of the Weather Research and Forecasting (WRF) model to downscaling ratios and storm types in rainfall simulation, Hydrol. Processes, 26, 3012–3031, 2012.
Madala, S., Satyanarayana, A., and Rao, T. N.: Performance evaluation of PBL and cumulus parameterization schemes of WRF ARW model in simulating severe thunderstorm events over Gadanki MST radar facility – case study, Atmos. Res., 139, 1–17, 2014.
Medina, S., Houze, R. A., Kumar, A., and Niyogi, D.: Summer monsoon convection in the Himalayan region: Terrain and land cover effects, Q. J. Roy. Meteorol. Soc., 136, 593–616, 2010.
Misenis, C. and Zhang, Y.: An examination of sensitivity of WRF/Chem predictions to physical parameterizations, horizontal grid spacing, and nesting options, Atmos. Res., 97, 315–334, 2010.
Mishra, A. and Srinivasan, J.: Did a cloud burst occur in Kedarnath during 16 and 17 June 2013?, Curr. Sci., 105, 1351–1352, 2013.
Mishra, V., Kumar, D., Ganguly, A. R., Sanjay, J., Mujumdar, M., Krishnan, R., and Shah, R. D.: Reliability of regional and global climate models to simulate precipitation extremes over India, J. Geophys. Res.-Atmos., 119, 9301–9323, 2014.
Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., and Clough, S. A.: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave, J. Geophys. Res.-Atmos., 102, 16663–16682, 1997.
Mohanty, U., Routray, A., Osuri, K. K., and Prasad, S. K.: A study on simulation of heavy rainfall events over Indian region with ARW-3DVAR modeling system, Pure Appl. Geophys., 169, 381–399, 2012.
Mukhopadhyay, P., Taraphdar, S., Goswami, B., and Krishnakumar, K.: Indian summer monsoon precipitation climatology in a high-resolution regional climate model: Impacts of convective parameterization on systematic biases, Weather Forecast., 25, 369–387, 2010.
NCEP (National Centers for Environmental Prediction): National Weather Service/NOAA/U.S. Department of Commerce, 2000, updated daily, NCEP FNL Operational Model Global Tropospheric Analyses, continuing from July 1999, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, available at: https://doi.org/10.5065/D6M043C6, last access: 2 November 2017.
Niyogi, D., Holt, T., Zhong, S., Pyle, P. C., and Basara, J.: Urban and land surface effects on the 30 July 2003 mesoscale convective system event observed in the southern Great Plains, J. Geophys. Res.-Atmos., 111, 1–20, D19107, 2006.
Niyogi, D., Subramanian, S., and Osuri, K. K.: The Role of Land Surface Processes on Tropical Cyclones: Introduction to Land Surface Models, in: Advanced Numerical Modeling and Data Assimilation Techniques for Tropical Cyclone Prediction, Springer, 221–246, 2016.
NOAA: National Oceanic and Atmospheric Administration Changes to the NCEP Meso Eta Analysis and Forecast System: Increase in resolution, new cloud microphysics, modified precipitation assimilation, modified 3DVAR analysis, 2001.
Noilhan, J. and Planton, S.: A simple parameterization of land surface processes for meteorological models, Mon. Weather Rev., 117, 536–549, 1989.
Osuri, K., Nadimpalli, R., Mohanty, U., Chen, F., Rajeevan, M., and Niyogi, D.: Improved prediction of severe thunderstorms over the Indian Monsoon region using high-resolution soil moisture and temperature initialization, Scientific Reports, 7, 1–12, 41377, 2017a.
Osuri, K. K., Nadimpalli, R., Mohanty, U. C., and Niyogi, D.: Prediction of rapid intensification of tropical cyclone Phailin over the Bay of Bengal using the HWRF modelling system, Q. J. Roy. Meteorol. Soc., 143, 678–690, 2017b.
Osuri, K. K., Mohanty, U., Routray, A., Kulkarni, M. A., and Mohapatra, M.: Customization of WRF-ARW model with physical parameterization schemes for the simulation of tropical cyclones over North Indian Ocean, Nat. Hazards, 63, 1337–1359, 2012.
Osuri, K. K., Mohanty, U., Routray, A., and Niyogi, D.: Improved prediction of Bay of Bengal Tropical cyclones through assimilation of doppler weather radar observations, Mon. Weather Rev., 143, 4533–4560, 2015.
Pai, D., Sridhar, L., Rajeevan, M., Sreejith, O., Satbhai, N., and Mukhopadhyay, B.: Development of a new high spatial resolution (0.25 × 0.25) long period (1901–2010) daily gridded rainfall data set over India and its comparison with existing data sets over the region, available at: http://www.imd.gov.in/advertisements/20170320_advt_34.pdf, Mausam, 65, 1–18, 2014.
Pieri, A. B., von Hardenberg, J., Parodi, A., and Provenzale, A.: Sensitivity of precipitation statistics to resolution, microphysics, and convective parameterization: A case study with the high-resolution WRF climate model over Europe, J. Hydrometeorol., 16, 1857–1872, 2015.
Rahman, S., Sengupta, D., and Ravichandran, M.: Variability of Indian summer monsoon rainfall in daily data from gauge and satellite, J. Geophys. Res.-Atmos., 114, 1–14, D17113, 2009.
Rajeevan, M., Kesarkar, A., Thampi, S. B., Rao, T. N., Radhakrishna, B., and Rajasekhar, M.: Sensitivity of WRF cloud microphysics to simulations of a severe thunderstorm event over Southeast India, Ann. Geophys., 28, 603–619, https://doi.org/10.5194/angeo-28-603-2010, 2010.
Rajesh, P., Pattnaik, S., Rai, D., Osuri, K., Mohanty, U., and Tripathy, S.: Role of land state in a high resolution mesoscale model for simulating the Uttarakhand heavy rainfall event over India, J. Earth Syst. Sci., 125, 475–498, 2016.
Raju, P., Potty, J., and Mohanty, U.: Sensitivity of physical parameterizations on prediction of tropical cyclone Nargis over the Bay of Bengal using WRF model, Meteorol. Atmos. Phys., 113, 125–137, 2011.
Rao, Y. R., Hatwar, H., Salah, A. K., and Sudhakar, Y.: An experiment using the high resolution Eta and WRF models to forecast heavy precipitation over India, Pure Appl. Geophys., 164, 1593–1615, 2007.
Ratna, S. B., Sikka, D., Dalvi, M., and Venkata Ratnam, J.: Dynamical simulation of Indian summer monsoon circulation, rainfall and its interannual variability using a high resolution atmospheric general circulation model, Int. J. Climatol., 31, 1927–1942, 2011.
Ratnam, J. V. and Kumar, K. K.: Sensitivity of the simulated monsoons of 1987 and 1988 to convective parameterization schemes in MM5, J. Climate, 18, 2724–2743, 2005.
Rauscher, S. A., Coppola, E., Piani, C., and Giorgi, F.: Resolution effects on regional climate model simulations of seasonal precipitation over Europe, Clim. Dynam., 35, 685–711, 2010.
Ray, K., Bhan, S., and Sunitha Devi, S.: A Meteorological Analysis Of Very Heavy Rainfall Event Over Uttarakhand During 14–17 June 2013, Monsoon 2013 a report, IMD Met. Monograph: Synoptic Meteorology No.: ESSO/IMD/SYNOPTIC MET/01-2014/15, available at: http://www.tropmet.res.in/~kolli/MOL/Monsoon/year2013/Monsoon-2013-NEW.pdf (last access: 7 February 2018), 37–54, 2014.
Routray, A., Mohanty, U., Niyogi, D., Rizvi, S., and Osuri, K. K.: Simulation of heavy rainfall events over Indian monsoon region using WRF-3DVAR data assimilation system, Meteorol. Atmos. Phys., 106, 107–125, 2010.
Routray, A., Mohanty, U., Osuri, K. K., Kar, S., and Niyogi, D.: Impact of satellite radiance data on simulations of Bay of Bengal tropical cyclones using the WRF-3DVAR modeling system, IEEE Trans. Geosci. Remote Sens., 54, 2285–2303, 2016.
Rutledge, S. A. and Hobbs, P. V.: The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. XII: A diagnostic modeling study of precipitation development in narrow cold-frontal rainbands, J. Atmos. Sci., 41, 2949–2972, 1984.
Schaake, J. C., Koren, V. I., Duan, Q. Y., Mitchell, K., and Chen, F.: Simple water balance model for estimating runoff at different spatial and temporal scales, J. Geophys. Res.-Atmos., 101, 7461–7475, 1996.
Shekhar, M., Pattanayak, S., Mohanty, U., Paul, S., and Kumar, M. S.: A study on the heavy rainfall event around Kedarnath area (Uttarakhand) on 16 June 2013, J. Earth Syst. Sci., 124, 1531–1544, 2015.
Sikder, S. and Hossain, F.: Assessment of the weather research and forecasting model generalized parameterization schemes for advancement of precipitation forecasting in monsoon-driven river basins, J. Adv. Model. Earth Sy., 8, 1210–1228, 2016.
Sikka, D. and Gadgil, S.: On the maximum cloud zone and the ITCZ over Indian, longitudes during the southwest monsoon, Mon. Weather Rev., 108, 1840–1853, 1980.
Sing, K. S. and Mandal, M.: Sensitivity of Mesoscale Simulation of Aila Cyclone to the Parameterization of Physical Processes Using WRF Model, in: Monitoring and Prediction of Tropical Cyclones in the Indian Ocean and Climate Change, Springer, 300–308, 2014.
Singh, S., Ghosh, S., Sahana, A., Vittal, H., and Karmakar, S.: Do dynamic regional models add value to the global model projections of Indian monsoon?, Clim. Dynam., 48, 1375–1397, 2017.
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Wang, W., and Powers, J. G.: A description of the advanced research WRF version 2, National Center For Atmospheric Research Boulder Co Mesoscale and Microscale Meteorology Div, available at: http://www2.mmm.ucar.edu/wrf/users/downloads.html (last access: 2 June 2017), 2005.
Srinivas, C., Hariprasad, D., Bhaskar Rao, D., Anjaneyulu, Y., Baskaran, R., and Venkatraman, B.: Simulation of the Indian summer monsoon regional climate using advanced research WRF model, Int. J. Climatol., 33, 1195–1210, 2013.
Tao, W.-K., Simpson, J., and McCumber, M.: An ice-water saturation adjustment, Mon. Weather Rev., 117, 231–235, 1989.
Tewari, M., Chen, F., Wang, W., Dudhia, J., LeMone, M., Mitchell, K., Ek, M., Gayno, G., Wegiel, J., and Cuenca, R.: Implementation and verification of the unified NOAH land surface model in the WRF model, 20th conference on weather analysis and forecasting/16th conference on numerical weather prediction, 2004,
Thayyen, R. J., Dimri, A., Kumar, P., and Agnihotri, G.: Study of cloudburst and flash floods around Leh, India, during August 4–6, 2010, Nat. Hazards, 65, 2175–2204, 2013.
Trapp, R. J., Halvorson, B. A., and Diffenbaugh, N. S.: Telescoping, multimodel approaches to evaluate extreme convective weather under future climates, J. Geophys. Res.-Atmos., 112, 1–13, D20109, 2007.
Vaidya, S.: The performance of two convective parameterization schemes in a mesoscale model over the Indian region, Meteorol. Atmos. Phys., 92, 175–190, 2006.
Vaidya, S. and Kulkarni, J.: Simulation of heavy precipitation over Santacruz, Mumbai on 26 July 2005, using mesoscale model, Meteorol. Atmos. Phys., 98, 55–66, 2007.
Vaidya, S. and Singh, S.: Applying the Betts–Miller–Janjic scheme of convection in prediction of the Indian monsoon, Weather Forecast., 15, 349–356, 2000.
Vellore, R. K., Kaplan, M. L., Krishnan, R., Lewis, J. M., Sabade, S., Deshpande, N., Singh, B. B., Madhura, R., and Rao, M. R.: Monsoon-extratropical circulation interactions in Himalayan extreme rainfall, Clim. Dynam., 46, 3517–3546, 2016.
Webster, P. J., Magana, V. O., Palmer, T., Shukla, J., Tomas, R., Yanai, M., and Yasunari, T.: Monsoons: Processes, predictability, and the prospects for prediction, J. Geophys. Res.-Ocean, 103, 14451–14510, 1998.
Short summary
For realistic flood predictions, it is necessary to have accurate rainfall estimates. The Weather Research and Forecasting (WRF) model is often used to correctly simulate heavy rainfall events, but setting up the model over a region is a challenging task. In this study, the sensitivity of the WRF model is assessed for physics schemes, parameterization options, land surface models and downscaling ratios, by simulating several extreme rainfall events in the Ganges basin.
For realistic flood predictions, it is necessary to have accurate rainfall estimates. The...
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