Articles | Volume 25, issue 1
Research article 04 Jan 2021
Research article | 04 Jan 2021
Developing a hydrological monitoring and sub-seasonal to seasonal forecasting system for South and Southeast Asian river basins
Yifan Zhou et al.
No articles found.
Jawairia A. Ahmad, Barton A. Forman, and Sujay V. Kumar
Hydrol. Earth Syst. Sci. Discuss.,
Preprint under review for HESSShort summary
Assimilation of remotely sensed data into a land surface model to improve the spatiotemporal estimation of soil moisture across South Asia exhibits potential. Satellite retrieval assimilation corrects biases that are generated due to unmodeled hydrologic phenomenon, i.e., irrigation. The improvements in fine-scale, modeled soil moisture estimates by assimilating coarse-scale retrievals indicates the utility of the described methodology for data scarce regions.
Min Huang, James H. Crawford, Joshua P. DiGangi, Gregory R. Carmichael, Kevin W. Bowman, Sujay V. Kumar, and Xiwu Zhan
Atmos. Chem. Phys., 21, 11013–11040,Short summary
This study evaluates the impact of satellite soil moisture data assimilation on modeled weather and ozone fields at various altitudes above the southeastern US during the summer. It emphasizes the importance of soil moisture in the understanding of surface ozone pollution and upper tropospheric chemistry, as well as air pollutants’ source–receptor relationships between the US and its downwind areas.
Michiel Maertens, Gabriëlle J. M. De Lannoy, Sebastian Apers, Sujay V. Kumar, and Sarith P. P. Mahanama
Hydrol. Earth Syst. Sci., 25, 4099–4125,Short summary
In this study, we simulated the water balance over the South American Dry Chaco and assessed the impact of land cover changes thereon using three different land surface models. Our simulations indicated that different models result in a different partitioning of the total water budget, but all showed an increase in soil moisture and percolation over the deforested areas. We also found that, relative to independent data, no specific land surface model is significantly better than another.
Wanshu Nie, Sujay V. Kumar, Kristi R. Arsenault, Christa D. Peters-Lidard, Iliana E. Mladenova, Karim Bergaoui, Abheera Hazra, Benjamin F. Zaitchik, Sarith P. Mahanama, Rachael McDonnell, David M. Mocko, and Mahdi Navari
Hydrol. Earth Syst. Sci. Discuss.,
Revised manuscript under review for HESSShort summary
The Middle East and North Africa region faces significant food/water insecurity and hydrological hazards. Here we investigate the value of assimilating remote sensing datasets into an earth system model to help build an effective drought monitoring system, supporting risk mitigation and management by countries in the region. We highlight incorporating satellite-informed vegetation condition into the model as one of the key processes to be captured for a successful application for the region.
Rhae Sung Kim, Sujay Kumar, Carrie Vuyovich, Paul Houser, Jessica Lundquist, Lawrence Mudryk, Michael Durand, Ana Barros, Edward J. Kim, Barton A. Forman, Ethan D. Gutmann, Melissa L. Wrzesien, Camille Garnaud, Melody Sandells, Hans-Peter Marshall, Nicoleta Cristea, Justin M. Pflug, Jeremy Johnston, Yueqian Cao, David Mocko, and Shugong Wang
The Cryosphere, 15, 771–791,Short summary
High SWE uncertainty is observed in mountainous and forested regions, highlighting the need for high-resolution snow observations in these regions. Substantial uncertainty in snow water storage in Tundra regions and the dominance of water storage in these regions points to the need for high-accuracy snow estimation. Finally, snow measurements during the melt season are most needed at high latitudes, whereas observations at near peak snow accumulations are most beneficial over the midlatitudes.
Mahmoud Osman, Benjamin F. Zaitchik, Hamada S. Badr, Jordan I. Christian, Tsegaye Tadesse, Jason A. Otkin, and Martha C. Anderson
Hydrol. Earth Syst. Sci., 25, 565–581,Short summary
Our study of flash droughts' definitions over the United States shows that published definitions yield markedly different inventories of flash drought geography and frequency. Results suggest there are several pathways that can lead to events that are characterized as flash droughts. Lack of consensus across definitions helps to explain apparent contradictions in the literature on trends and indicates the selection of a definition is important for accurate monitoring of different mechanisms.
Justin Schulte, Frederick Policelli, and Benjamin Zaitchik
Nonlin. Processes Geophys. Discuss.,
Revised manuscript accepted for NPGShort summary
The skewness of a time series is commonly used to quantify the extent to which positive (negative) deviations from the mean are larger than negative (positive) ones. However, in some cases, traditional skewness may not provide reliable information about time series skewness, motivating the development of a waveform skewness index in this paper. The waveform skewness index is used to show that changes in the relationship strength between climate time series could arise from changes in skewness.
Justin Schulte, Frederick Policielli, and Benjamin Zaitchik
Hydrol. Earth Syst. Sci., 24, 5473–5489,Short summary
Wavelet coherence is now a commonly used method for detecting scale-dependent relationships between time series. In this study, the concept of wavelet coherence is generalized to higher-order wavelet coherence methods that quantify the relationship between higher-order statistical moments associated with two time series. The methods are applied to the El Niño–Southern Oscillation (ENSO) and the Indian monsoon to show that the ENSO–Indian monsoon relationship is impacted by ENSO nonlinearity.
Xinxuan Zhang, Viviana Maggioni, Azbina Rahman, Paul Houser, Yuan Xue, Timothy Sauer, Sujay Kumar, and David Mocko
Hydrol. Earth Syst. Sci., 24, 3775–3788,Short summary
This study assesses the extent to which a land surface model can be optimized via the assimilation of leaf area index (LAI) observations at the global scale. The model performance is evaluated by the model-estimated LAI and five water flux/storage variables. Results show the LAI assimilation reduces errors in the model-estimated LAI. The LAI assimilation also improves the five water variables under wet conditions, but some of the model-estimated variables tend to be worse under dry conditions.
Sujay V. Kumar, Thomas R. Holmes, Rajat Bindlish, Richard de Jeu, and Christa Peters-Lidard
Hydrol. Earth Syst. Sci., 24, 3431–3450,Short summary
Vegetation optical depth (VOD) is a byproduct of the soil moisture retrieval from passive microwave instruments. This study demonstrates that VOD information can be utilized for improving land surface water budget and carbon conditions through data assimilation.
Shraddhanand Shukla, Kristi R. Arsenault, Abheera Hazra, Christa Peters-Lidard, Randal D. Koster, Frank Davenport, Tamuka Magadzire, Chris Funk, Sujay Kumar, Amy McNally, Augusto Getirana, Greg Husak, Ben Zaitchik, Jim Verdin, Faka Dieudonne Nsadisa, and Inbal Becker-Reshef
Nat. Hazards Earth Syst. Sci., 20, 1187–1201,Short summary
The region of southern Africa is prone to climate-driven food insecurity events, as demonstrated by the major drought event in 2015–2016. This study demonstrates that recently developed NASA Hydrological Forecasting and Analysis System-based root-zone soil moisture monitoring and forecasting products are well correlated with interannual regional crop yield, can identify below-normal crop yield events and provide skillful crop yield forecasts, and hence support early warning of food insecurity.
Pankaj Sadavarte, Maheswar Rupakheti, Prakash Bhave, Kiran Shakya, and Mark Lawrence
Atmos. Chem. Phys., 19, 12953–12973,Short summary
Emission inventory studies are an important regulatory tool for quantifying the amount of pollutants released in the atmosphere using the fuel consumption and emission rates for different fuels. This study developed an emission inventory over Nepal for 2001–2016 that reveals the changing fuel consumption and subsequently the pollution across different sectors of industrial, transport, agricultural, commercial and residential uses with the use of spatial distribution of anthropogenic activities.
Kristi R. Arsenault, Sujay V. Kumar, James V. Geiger, Shugong Wang, Eric Kemp, David M. Mocko, Hiroko Kato Beaudoing, Augusto Getirana, Mahdi Navari, Bailing Li, Jossy Jacob, Jerry Wegiel, and Christa D. Peters-Lidard
Geosci. Model Dev., 11, 3605–3621,Short summary
The Earth’s land surface hydrology and physics can be represented in highly sophisticated models known as land surface models. The Land surface Data Toolkit (LDT) software was developed to meet these models’ input processing needs. LDT supports a variety of land surface and hydrology models and prepares the inputs (e.g., meteorological data, satellite observations to be assimilated into a model), which can be used for inter-model studies and to initialize weather and climate forecasts.
Sujay V. Kumar, Jiarui Dong, Christa D. Peters-Lidard, David Mocko, and Breogán Gómez
Hydrol. Earth Syst. Sci., 21, 2637–2647,Short summary
Data assimilation deals with the blending of model forecasts and observations based on their relative errors. This paper addresses the importance of accurately representing the errors in the model forecasts for skillful data assimilation performance.
Julie E. Shortridge, Seth D. Guikema, and Benjamin F. Zaitchik
Hydrol. Earth Syst. Sci., 20, 2611–2628,Short summary
This paper compares six methods for data-driven rainfall–runoff simulation in terms of predictive accuracy, error structure, interpretability, and uncertainty. We demonstrate that autocorrelation in model errors can result in biased estimates of important values and show how certain model structures can be more easily interpreted to yield insights on physical watershed function. Finally, we explore how model structure can impact uncertainty in climate change sensitivity estimates.
S. V. Kumar, C. D. Peters-Lidard, J. A. Santanello, R. H. Reichle, C. S. Draper, R. D. Koster, G. Nearing, and M. F. Jasinski
Hydrol. Earth Syst. Sci., 19, 4463–4478,
M. A. Matin and C. P.-A. Bourque
Hydrol. Earth Syst. Sci., 19, 3387–3403,Short summary
This paper describes a methodology in analysing the interdependencies between components of the hydrological cycle and vegetation characteristics at different elevation zones of two endorheic river basins in an arid-mountainous region of NW China. The analysis shows that oasis vegetation has an important function in sustaining the water cycle in the river basins and oasis vegetation is dependent on surface and shallow subsurface water flow from mountain sources.
S. Satti, B. Zaitchik, and S. Siddiqui
Hydrol. Earth Syst. Sci., 19, 2275–2293,
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Modelling approachesImproved parameterization of snow albedo in Noah coupled with Weather Research and Forecasting: applicability to snow estimates for the Tibetan PlateauA 10 km North American precipitation and land-surface reanalysis based on the GEM atmospheric modelContribution of moisture sources to precipitation changes in the Three Gorges Reservoir RegionImpacts of land use and land cover change and reforestation on summer rainfall in the Yangtze River basinMass balance and hydrological modeling of the Hardangerjøkulen ice cap in south-central NorwayLong-term relative decline in evapotranspiration with increasing runoff on fractional land surfacesDecision tree-based detection of blowing snow events in the European AlpsEasy-to-use spatial Random Forest-based downscaling-calibration method for producing high resolution and accurate precipitation dataChanges in the simulation of atmospheric instability over the Iberian Peninsula due to the use of 3DVAR data assimilationSimulating the evolution of the topography–climate coupled systemUsing data assimilation to optimize pedotransfer functions using field-scale in situ soil moisture observationsImpact of frozen soil processes on soil thermal characteristics at seasonal to decadal scales over the Tibetan Plateau and North ChinaThe development and persistence of soil moisture stress during drought across southwestern GermanySummary and synthesis of Changing Cold Regions Network (CCRN) research in the interior of western Canada – Part 2: Future change in cryosphere, vegetation, and hydrologyImproving soil moisture prediction of a high-resolution land surface model by parameterising pedotransfer functions through assimilation of SMAP satellite dataLand-use and climate change effects on water yield from East African Forested Water TowersEvaluating a land surface model at a water-limited site: implications for land surface contributions to droughts and heatwavesA two-stage blending approach for merging multiple satellite precipitation estimates and rain gauge observations: an experiment in the northeastern Tibetan PlateauIdentifying robust bias adjustment methods for European extreme precipitation in a multi-model pseudo-reality settingSimulation analysis of local land atmosphere coupling in rainy season over a typical underlying surface in the Tibetan PlateauRainfall-induced shallow landslides and soil wetness: comparison of physically-based and probabilistic predictionsIntensification characteristics of hydroclimatic extremes in the Asian monsoon region under 1.5 and 2.0 °C of global warmingLast-decade progress in understanding and modeling the land surface processes on the Tibetan PlateauOn the potential of variational calibration for a fully distributed hydrological model: application on a Mediterranean catchmentAccelerated hydrological cycle over the Sanjiangyuan region induces more streamflow extremes at different global warming levelsContrasting seasonal changes in total and intense precipitation in the European Alps from 1903 to 2010Technical note: Precipitation-phase partitioning at landscape scales to regional scalesData assimilation for continuous global assessment of severe conditions over terrestrial surfacesA coupled atmospheric–hydrologic modeling system with variable grid sizes for rainfall–runoff simulation in semi-humid and semi-arid watersheds: how does the coupling scale affects the results?Assessment and projection of the water budget over western Canada using convection-permitting weather research and forecasting simulationsClimate-dependent propagation of precipitation uncertainty into the water cycleA meteorological–hydrological regional ensemble forecast for an early-warning system over small Apennine catchments in Central ItalyBias in dynamically downscaled rainfall characteristics for hydroclimatic projectionsImpact of downscaled rainfall biases on projected runoff changesComparing Palmer Drought Severity Index drought assessments using the traditional offline approach with direct climate model outputsUncovering the shortcomings of a weather typing methodHigh-resolution fully coupled atmospheric–hydrological modeling: a cross-compartment regional water and energy cycle evaluationTracking the global flows of atmospheric moisture and associated uncertaintiesAssessing the factors governing the ability to predict late-spring flooding in cold-region mountain basinsRevisiting extreme precipitation amounts over southern South America and implications for the Patagonian IcefieldsInfluence of multidecadal variability on high and low flows: the case of the Seine basinTechnical Note: Evaluation of the skill in monthly-to-seasonal soil moisture forecasting based on SMAP satellite observations over the southeastern USComparison of probabilistic post-processing approaches for improving numerical weather prediction-based daily and weekly reference evapotranspiration forecastsThe impact of initial conditions on convection-permitting simulations of a flood event over complex mountainous terrainMultimodel simulation of vertical gas transfer in a temperate lakeDual state/rainfall correction via soil moisture assimilation for improved streamflow simulation: evaluation of a large-scale implementation with Soil Moisture Active Passive (SMAP) satellite dataThe AquiFR hydrometeorological modelling platform as a tool for improving groundwater resource monitoring over France: evaluation over a 60-year periodImpact of revegetation of the Loess Plateau of China on the regional growing season water balanceAn ensemble square root filter for the joint assimilation of surface soil moisture and leaf area index within the Land Data Assimilation System LDAS-Monde: application over the Euro-Mediterranean regionImpact of high-resolution sea surface temperature representation on the forecast of small Mediterranean catchments' hydrological responses to heavy precipitation
Lian Liu, Yaoming Ma, Massimo Menenti, Rongmingzhu Su, Nan Yao, and Weiqiang Ma
Hydrol. Earth Syst. Sci., 25, 4967–4981,Short summary
Albedo is a key factor in land surface energy balance, which is difficult to successfully reproduce by models. Here, we select eight snow events on the Tibetan Plateau to evaluate the universal improvements of our improved albedo scheme. The RMSE relative reductions for temperature, albedo, sensible heat flux and snow depth reach 27%, 32%, 13% and 21%, respectively, with remarkable increases in the correlation coefficients. This presents a strong potential of our scheme for modeling snow events.
Nicolas Gasset, Vincent Fortin, Milena Dimitrijevic, Marco Carrera, Bernard Bilodeau, Ryan Muncaster, Étienne Gaborit, Guy Roy, Nedka Pentcheva, Maxim Bulat, Xihong Wang, Radenko Pavlovic, Franck Lespinas, Dikra Khedhaouiria, and Juliane Mai
Hydrol. Earth Syst. Sci., 25, 4917–4945,Short summary
In this paper, we highlight the importance of including land-data assimilation as well as offline precipitation analysis components in a regional reanalysis system. We also document the performance of the first multidecadal 10 km reanalysis performed with the GEM atmospheric model that can be used for seamless land-surface and hydrological modelling in North America. It is of particular interest for transboundary basins, as existing datasets often show discontinuities at the border.
Ying Li, Chenghao Wang, Hui Peng, Shangbin Xiao, and Denghua Yan
Hydrol. Earth Syst. Sci., 25, 4759–4772,Short summary
Precipitation change in the Three Gorges Reservoir Region (TGRR) plays a critical role in the operation and regulation of the Three Gorges Dam and the protection of residents and properties. We investigated the long-term contribution of moisture sources to precipitation changes in this region with an atmospheric moisture tracking model. We found that southwestern source regions (especially the southeastern tip of the Tibetan Plateau) are the key regions that control TGRR precipitation changes.
Wei Li, Lu Li, Jie Chen, Qian Lin, and Hua Chen
Hydrol. Earth Syst. Sci., 25, 4531–4548,Short summary
Reforestation can influence climate, but the sensitivity of summer rainfall to reforestation is rarely investigated. We take two reforestation scenarios to assess the impacts of reforestation on summer rainfall under different reforestation proportions and explore the potential mechanisms. This study concludes that reforestation increases summer rainfall amount and extremes through thermodynamics processes, and the effects are more pronounced in populated areas than over the whole basin.
Trude Eidhammer, Adam Booth, Sven Decker, Lu Li, Michael Barlage, David Gochis, Roy Rasmussen, Kjetil Melvold, Atle Nesje, and Stefan Sobolowski
Hydrol. Earth Syst. Sci., 25, 4275–4297,Short summary
We coupled a detailed snow–ice model (Crocus) to represent glaciers in the Weather Research and Forecasting (WRF)-Hydro model and tested it on a well-studied glacier. Several observational systems were used to evaluate the system, i.e., satellites, ground-penetrating radar (used over the glacier for snow depth) and stake observations for glacier mass balance and discharge measurements in rivers from the glacier. Results showed improvements in the streamflow projections when including the model.
Ren Wang, Pierre Gentine, Jiabo Yin, Lijuan Chen, Jianyao Chen, and Longhui Li
Hydrol. Earth Syst. Sci., 25, 3805–3818,Short summary
Assessment of changes in the global water cycle has been a challenge. This study estimated long-term global latent heat and sensible heat fluxes for recent decades using machine learning and ground observations. The results found that the decline in evaporative fraction was typically accompanied by an increase in long-term runoff in over 27.06 % of the global land areas. The observation-driven findings emphasized that surface vegetation has great impacts in regulating water and energy cycles.
Zhipeng Xie, Weiqiang Ma, Yaoming Ma, Zeyong Hu, Genhou Sun, Yizhe Han, Wei Hu, Rongmingzhu Su, and Yixi Fan
Hydrol. Earth Syst. Sci., 25, 3783–3804,Short summary
Ground information on the occurrence of blowing snow has been sorely lacking because direct observations of blowing snow are sparse in time and space. In this paper, we investigated the potential capability of the decision tree model to detect blowing snow events in the European Alps. Trained with routine meteorological observations, the decision tree model can be used as an efficient tool to detect blowing snow occurrences across different regions requiring limited meteorological variables.
Chuanfa Chen, Baojian Hu, and Yanyan Li
Hydrol. Earth Syst. Sci. Discuss.,
Revised manuscript under review for HESSShort summary
High resolution and accurate precipitation data is significantly important for numerous hydrological applications. Thus, to enhance the spatial resolution and accuracy of satellite-based precipitation products, an easy-to-use downscaling-calibration method based on spatial Random Forest is proposed in this paper. Results show that the proposed method outperforms the other methods as well as the original IMERG for downscaling and calibration of IMERG products.
Santos J. González-Rojí, Sheila Carreno-Madinabeitia, Jon Sáenz, and Gabriel Ibarra-Berastegi
Hydrol. Earth Syst. Sci., 25, 3471–3492,Short summary
The simulation of precipitation extreme events is a known problem in modelling. That is why the atmospheric conditions favourable for its development as simulated by two WRF experiments are evaluated in this paper. The experiment including 3DVAR data assimilation outperforms the one without in simulating the TT index, CAPE, and CIN over the Iberian Peninsula. The ingredients for convective precipitation in winter are found at the Atlantic coast, but in summer they are at the Mediterranean coast.
Kyungrock Paik and Won Kim
Hydrol. Earth Syst. Sci., 25, 2459–2474,Short summary
Climate, topography, and tectonics evolve together. To simulate their co-evolution, a fully coupled computer simulation model between local climate and topography is developed in this study. We simulated how the mountain development enhances local rainfall and its feedback on topography through stronger erosion. We found that the evolution of the coupled system can be more complicated than previously thought. The channel concavity on the windward side becomes lower as the wind grows.
Elizabeth Cooper, Eleanor Blyth, Hollie Cooper, Rich Ellis, Ewan Pinnington, and Simon J. Dadson
Hydrol. Earth Syst. Sci., 25, 2445–2458,Short summary
Soil moisture estimates from land surface models are important for forecasting floods, droughts, weather, and climate trends. We show that by combining model estimates of soil moisture with measurements from field-scale, ground-based sensors, we can improve the performance of the land surface model in predicting soil moisture values.
Qian Li, Yongkang Xue, and Ye Liu
Hydrol. Earth Syst. Sci., 25, 2089–2107,Short summary
Most land surface models have difficulty in capturing the freeze–thaw cycle in the Tibetan Plateau and North China. This paper introduces a physically more realistic and efficient frozen soil module (FSM) into the SSiB3 model (SSiB3-FSM). A new and more stable semi-implicit scheme and a physics-based freezing–thawing scheme were applied, and results show that SSiB3-FSM can be used as an effective model for soil thermal characteristics at seasonal to decadal scales over frozen ground.
Erik Tijdeman and Lucas Menzel
Hydrol. Earth Syst. Sci., 25, 2009–2025,Short summary
Low amounts of soil moisture (SM) in the root zone negatively affect crop health. We characterized the development and duration of SM stress across the croplands of southwestern Germany. Development time mainly varied within drought years and was related to the available water-holding capacity of the root zone. Duration varied both within and between drought years and was especially high in 2018. Sensitivity analyses showed that (controls on) SM stress and SM drought characteristics differ.
Chris M. DeBeer, Howard S. Wheater, John W. Pomeroy, Alan G. Barr, Jennifer L. Baltzer, Jill F. Johnstone, Merritt R. Turetsky, Ronald E. Stewart, Masaki Hayashi, Garth van der Kamp, Shawn Marshall, Elizabeth Campbell, Philip Marsh, Sean K. Carey, William L. Quinton, Yanping Li, Saman Razavi, Aaron Berg, Jeffrey J. McDonnell, Christopher Spence, Warren D. Helgason, Andrew M. Ireson, T. Andrew Black, Mohamed Elshamy, Fuad Yassin, Bruce Davison, Allan Howard, Julie M. Thériault, Kevin Shook, Michael N. Demuth, and Alain Pietroniro
Hydrol. Earth Syst. Sci., 25, 1849–1882,Short summary
This article examines future changes in land cover and hydrological cycling across the interior of western Canada under climate conditions projected for the 21st century. Key insights into the mechanisms and interactions of Earth system and hydrological process responses are presented, and this understanding is used together with model application to provide a synthesis of future change. This has allowed more scientifically informed projections than have hitherto been available.
Ewan Pinnington, Javier Amezcua, Elizabeth Cooper, Simon Dadson, Rich Ellis, Jian Peng, Emma Robinson, Ross Morrison, Simon Osborne, and Tristan Quaife
Hydrol. Earth Syst. Sci., 25, 1617–1641,Short summary
Land surface models are important tools for translating meteorological forecasts and reanalyses into real-world impacts at the Earth's surface. We show that the hydrological predictions, in particular soil moisture, of these models can be improved by combining them with satellite observations from the NASA SMAP mission to update uncertain parameters. We find a 22 % reduction in error at a network of in situ soil moisture sensors after combining model predictions with satellite observations.
Charles Nduhiu Wamucii, Pieter R. van Oel, Arend Ligtenberg, John Mwangi Gathenya, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci. Discuss.,
Revised manuscript accepted for HESSShort summary
The East-African water towers are under pressure from human influences both within and outside. The patterns in water yield showed a strong longitudinal difference, though the elevation is a key factor that ensures the generation of water in the water towers located in drier environments. A hydroclimatic phenomenon is occurring in the East-African region as the water towers show a strong shift towards wetter conditions while at the same time, the atmospheric demand is gradually increasing.
Mengyuan Mu, Martin G. De Kauwe, Anna M. Ukkola, Andy J. Pitman, Teresa E. Gimeno, Belinda E. Medlyn, Dani Or, Jinyan Yang, and David S. Ellsworth
Hydrol. Earth Syst. Sci., 25, 447–471,Short summary
Land surface model (LSM) is a critical tool to study land responses to droughts and heatwaves, but lacking comprehensive observations limited past model evaluations. Here we use a novel dataset at a water-limited site, evaluate a typical LSM with a range of competing model hypotheses widely used in LSMs and identify marked uncertainty due to the differing process assumptions. We show the extensive observations constrain model processes and allow better simulated land responses to these extremes.
Yingzhao Ma, Xun Sun, Haonan Chen, Yang Hong, and Yinsheng Zhang
Hydrol. Earth Syst. Sci., 25, 359–374,Short summary
A two-stage blending approach is proposed for the data fusion of multiple satellite precipitation estimates (SPEs), which firstly reduces the systematic errors of original SPEs based on a Bayesian correction model and then merges the bias-corrected SPEs with a Bayesian weighting model. The model is evaluated in the warm season of 2010–2014 in the northeastern Tibetan Plateau. Results show that the blended SPE is greatly improved compared with the original SPEs, even in heavy rainfall events.
Torben Schmith, Peter Thejll, Peter Berg, Fredrik Boberg, Ole Bøssing Christensen, Bo Christiansen, Jens Hesselbjerg Christensen, Marianne Sloth Madsen, and Christian Steger
Hydrol. Earth Syst. Sci., 25, 273–290,Short summary
European extreme precipitation is expected to change in the future; this is based on climate model projections. But, since climate models have errors, projections are uncertain. We study this uncertainty in the projections by comparing results from an ensemble of 19 climate models. Results can be used to give improved estimates of future extreme precipitation for Europe.
Genhou Sun, Zeyong Hu, Yaoming Ma, Zhipeng Xie, Jiemin Wang, and Song Yang
Hydrol. Earth Syst. Sci., 24, 5937–5951,Short summary
We investigate the influence of soil conditions on the planetary boundary layer (PBL) thermodynamics and convective cloud formations over a typical underlying surface, based on a series of simulations on a sunny day in the Tibetan Plateau, using the Weather Research and Forecasting (WRF) model. The real-case simulation and sensitivity simulations indicate that the soil moisture could have a strong impact on PBL thermodynamics, which may be favorable for the convective cloud formations.
Elena Leonarduzzi, Brian W. McArdell, and Peter Molnar
Hydrol. Earth Syst. Sci. Discuss.,
Revised manuscript accepted for HESSShort summary
Landslides are a dangerous natural hazard affecting alpine regions, calling for effective warning systems. Here we consider different approaches for the prediction of rainfall-induced shallow landslides at the regional scale, based on open access datasets and operational hydrological forecasting systems. We find antecedent wetness useful to improve upon the classical rainfall thresholds and the resolution of the hydrological model used for its estimate to be a critical aspect.
Jeong-Bae Kim and Deg-Hyo Bae
Hydrol. Earth Syst. Sci., 24, 5799–5820,Short summary
We examine changes in hydroclimatic extremes for different climate zones in Asia in response to 1.5 and 2.0 °C global warming. Our results indicate consistent changes in temperature extremes and high precipitation (and maximum runoff) extremes across Asia. Extra 0.5 °C warming will lead to enhanced regional hydroclimatic extremes, especially in cold (and polar) climate zones. However, hydroclimatic sensitivities can differ based on regional climate characteristics and types of extreme variables.
Hui Lu, Donghai Zheng, Kun Yang, and Fan Yang
Hydrol. Earth Syst. Sci., 24, 5745–5758,Short summary
The Tibetan Plateau (TP), known as the Asian water tower, plays an important role in the regional climate system, while the land surface process is a key component through which the TP impacts the water and energy cycles. In this paper, we reviewed the progress achieved in the last decade in understanding and modeling the land surface processes on the TP. Based on this review, perspectives on the further improvement of land surface modelling on the TP are also provided.
Maxime Jay-Allemand, Pierre Javelle, Igor Gejadze, Patrick Arnaud, Pierre-Olivier Malaterre, Jean-Alain Fine, and Didier Organde
Hydrol. Earth Syst. Sci., 24, 5519–5538,Short summary
This study contributes to flash flood prediction using a hydrological model. The model describes the spatial properties of the watersheds with hundreds of unknown parameters. The Gardon d'Anduze watershed is chosen as the study benchmark. A sophisticated numerical algorithm and the downstream discharge measurements make the identification of the model parameters possible. Results provide better model predictions and relevant spatial variability of some parameters inside this watershed.
Peng Ji, Xing Yuan, Feng Ma, and Ming Pan
Hydrol. Earth Syst. Sci., 24, 5439–5451,Short summary
By performing high-resolution land surface modeling driven by the latest CMIP6 climate models, we find both the dry streamflow extreme over the drought-prone Yellow River headwater and the wet streamflow extreme over the flood-prone Yangtze River headwater will increase under 1.5, 2.0 and 3.0 °C global warming levels and emphasize the importance of considering ecological changes (i.e., vegetation greening and CO2 physiological forcing) in the hydrological projection.
Martin Ménégoz, Evgenia Valla, Nicolas C. Jourdain, Juliette Blanchet, Julien Beaumet, Bruno Wilhelm, Hubert Gallée, Xavier Fettweis, Samuel Morin, and Sandrine Anquetin
Hydrol. Earth Syst. Sci., 24, 5355–5377,Short summary
The study investigates precipitation changes in the Alps, using observations and a 7 km resolution climate simulation over 1900–2010. An increase in mean precipitation is found in winter over the Alps, whereas a drying occurred in summer in the surrounding plains. A general increase in the daily annual maximum of precipitation is evidenced (20 to 40 % per century), suggesting an increase in extreme events that is significant only when considering long time series, typically 50 to 80 years.
Elissa Lynn, Aaron Cuthbertson, Minxue He, Jordi P. Vasquez, Michael L. Anderson, Peter Coombe, John T. Abatzoglou, and Benjamin J. Hatchett
Hydrol. Earth Syst. Sci., 24, 5317–5328,Short summary
Precipitation partitioning across western US landscapes (1948–present) is estimated by combining gridded precipitation data with freezing level and precipitation data from an atmospheric reanalysis. Spatial patterns and trends in the precipitation phase over elevational and latitudinal gradients are examined. The largest increases in precipitation falling as rain occur during spring. This technique can be used as a diagnostic indicator to inform adaptive water management strategy development.
Clément Albergel, Yongjun Zheng, Bertrand Bonan, Emanuel Dutra, Nemesio Rodríguez-Fernández, Simon Munier, Clara Draper, Patricia de Rosnay, Joaquin Muñoz-Sabater, Gianpaolo Balsamo, David Fairbairn, Catherine Meurey, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 24, 4291–4316,Short summary
LDAS-Monde is a global offline land data assimilation system (LDAS) that jointly assimilates satellite-derived observations of surface soil moisture (SSM) and leaf area index (LAI) into the ISBA (Interaction between Soil Biosphere and Atmosphere) land surface model (LSM). This study demonstrates that LDAS-Monde is able to detect, monitor and forecast the impact of extreme weather on land surface states.
Jiyang Tian, Jia Liu, Yang Wang, Wei Wang, Chuanzhe Li, and Chunqi Hu
Hydrol. Earth Syst. Sci., 24, 3933–3949,Short summary
The aim of this study is to explore the appropriate coupling scale of the coupled atmospheric–hydrologic modeling system, which is established by the Weather Research and Forecasting (WRF) model and the gridded Hebei model with different sizes. The results show that the flood simulation results may not always be improved with higher-dimension precision and a more complicated system, and the grid size selection has a strong relationship with the rainfall evenness.
Sopan Kurkute, Zhenhua Li, Yanping Li, and Fei Huo
Hydrol. Earth Syst. Sci., 24, 3677–3697,Short summary
Our research has analyzed the surface water budget and atmospheric water vapour budget over western Canada from a set of convection-permitting regional climate simulations. The pseudo-global-warming simulation shows a great increase in evapotranspiration and an enhanced water cycle. We found that the orographic effect on the water vapour budget is significant over the Saskatchewan River basin, indicating the need for high-resolution regional climate modelling to reflect the effects.
Ali Fallah, Sungmin O, and Rene Orth
Hydrol. Earth Syst. Sci., 24, 3725–3735,Short summary
We find that simulated runoff values are highly dependent on the accuracy of precipitation inputs. In contrast, simulated evapotranspiration is generally much less influenced in our comparatively wet study region. We also find that the impact of precipitation uncertainty on simulated runoff increases towards wetter regions, while the opposite is observed in the case of evapotranspiration.
Rossella Ferretti, Annalina Lombardi, Barbara Tomassetti, Lorenzo Sangelantoni, Valentina Colaiuda, Vincenzo Mazzarella, Ida Maiello, Marco Verdecchia, and Gianluca Redaelli
Hydrol. Earth Syst. Sci., 24, 3135–3156,Short summary
Floods and severe rainfall are among the major natural hazards in the Mediterranean basin. Though precipitation weather forecasts have improved considerably, precipitation estimation is still affected by errors that can deteriorate the hydrological forecast. To improve hydrological forecasting, a regional-scale meteorological–hydrological ensemble is presented. This allows for predicting potential severe events days in advance and for characterizing the uncertainty of the hydrological forecast.
Nicholas J. Potter, Francis H. S. Chiew, Stephen P. Charles, Guobin Fu, Hongxing Zheng, and Lu Zhang
Hydrol. Earth Syst. Sci., 24, 2963–2979,Short summary
There is a growing need for information about possible changes to water resource availability in the future due to climate change. Large-scale outputs from global climate models need to be translated to finer-resolution spatial scales before hydrological modelling. Biases in this downscaled data often need to be corrected. We show that usual bias correction methods can retain residual biases in multi-day occurrences of rainfall, which can result in biases in modelled runoff.
Stephen P. Charles, Francis H. S. Chiew, Nicholas J. Potter, Hongxing Zheng, Guobin Fu, and Lu Zhang
Hydrol. Earth Syst. Sci., 24, 2981–2997,Short summary
This paper assesses the suitability of bias-corrected (BC) WRF daily rainfall across the state of Victoria, Australia, for input to hydrological models to determine plausible climate change impacts on runoff. It compares rainfall and runoff changes using BC WRF with those obtained from empirical scaling (ES) using raw WRF changes. It concludes that BC-derived changes are more plausible than ES-derived changes but that remaining biases in BC WRF daily data add uncertainty to runoff projections.
Yuting Yang, Shulei Zhang, Michael L. Roderick, Tim R. McVicar, Dawen Yang, Wenbin Liu, and Xiaoyan Li
Hydrol. Earth Syst. Sci., 24, 2921–2930,Short summary
Many previous studies using offline drought indices report that future warming will increase worldwide drought. However, this contradicts observations/projections of vegetation greening and increased runoff. We resolved this paradox by re-calculating the same drought indices using direct climate model outputs and find no increase in future drought as the climate warms. We also find that accounting for the impact of CO2 on plant transpiration avoids the previous overestimation of drought.
Els Van Uytven, Jan De Niel, and Patrick Willems
Hydrol. Earth Syst. Sci., 24, 2671–2686,Short summary
In recent years many methods have been developed for the statistical downscaling of climate model outputs. Each statistical downscaling method has strengths and limitations, but those are rarely evaluated. This paper illustrates an approach to evaluating the skill of statistical downscaling methods for the specific purpose of impact analysis in hydrology.
Benjamin Fersch, Alfonso Senatore, Bianca Adler, Joël Arnault, Matthias Mauder, Katrin Schneider, Ingo Völksch, and Harald Kunstmann
Hydrol. Earth Syst. Sci., 24, 2457–2481,
Obbe A. Tuinenburg and Arie Staal
Hydrol. Earth Syst. Sci., 24, 2419–2435,Short summary
Several models exist to track water through the atmosphere from its evaporation location to the next rain location. These models are typically driven by atmospheric wind and humidity data. Recently, a new version of these driving data sets has become available, with a higher spatial resolution of about 25 km. Here, we test the assumptions of these atmospheric moisture tracking models, given the high-resolution forcing data and find that the vertical mixing assumptions are the most important.
Vincent Vionnet, Vincent Fortin, Etienne Gaborit, Guy Roy, Maria Abrahamowicz, Nicolas Gasset, and John W. Pomeroy
Hydrol. Earth Syst. Sci., 24, 2141–2165,Short summary
The 2013 Alberta flood in Canada was typical of late-spring floods in mountain basins combining intense precipitation with rapid melting of late-lying snowpack. Hydrological simulations of this event are mainly influenced by (i) the spatial resolution of the atmospheric forcing due to the best estimate of precipitation at the kilometer scale and changes in turbulent fluxes contributing to snowmelt and (ii) uncertainties in initial snow conditions at high elevations. Soil texture has less impact.
Hydrol. Earth Syst. Sci., 24, 2003–2016,Short summary
Patagonia is thought to be one of the wettest – if not the wettest – places on Earth. The plausibility of these numbers has never been carefully scrutinized, despite the significance of this topic to our understanding of observed environmental changes, such as glacier recession. The revised precipitation values are significantly smaller than the previously reported values, thus opening up a new perspective on the Patagonian glaciers' response to climate change.
Rémy Bonnet, Julien Boé, and Florence Habets
Hydrol. Earth Syst. Sci., 24, 1611–1631,Short summary
In this paper, the multidecadal variations of the Seine basin since the 1850s are investigated, based on a new hydrometeorological reconstruction derived from hydrological modeling. The hydrological and climatic mechanisms underlying these variations are highlighted. The analysis of the hydrometeorological reconstruction shows that high and low flows are influenced by these multidecadal hydroclimate variations.
Amirhossein Mazrooei, Arumugam Sankarasubramanian, and Venkat Lakshmi
Hydrol. Earth Syst. Sci., 24, 1073–1079,Short summary
Reliable forecasts of soil moisture conditions help water-related sectors to better prepare for drought and flooding events. This paper describes an approach in which monthly-to-seasonal soil moisture forecasts are developed and compared to remotely sensed observations from SMAP satellite. Our results reveal a promising skill in forecasting long-range soil moisture conditions, suggesting its great potential for real-time and practical applications.
Hanoi Medina and Di Tian
Hydrol. Earth Syst. Sci., 24, 1011–1030,Short summary
Reference evapotranspiration (ET0) forecasts play an important role in agricultural, environmental, and water management. This study evaluated probabilistic post-processing approaches for improving daily and weekly ensemble ET0 forecasting based on single or multiple numerical weather predictions. The three approaches used consistently improved the skill and reliability of the ET0 forecasts compared with the conventional method, due to the adjustment in the spread of the ensemble forecast.
Lu Li, Marie Pontoppidan, Stefan Sobolowski, and Alfonso Senatore
Hydrol. Earth Syst. Sci., 24, 771–791,Short summary
We assessed the impact of initial conditions on convection-permitting simulations of a flood event over mountainous terrain. The calibrated convection-permitting model performs better than the simpler conceptual model. Discharge is slightly more sensitive to spin-up time than precipitation due to the influence of soil moisture. A maximum of 0.5 m of snow is converted to runoff irrespective of the initial snow depth, and this snowmelt contributes to discharge mostly during peak flow period.
Sofya Guseva, Tobias Bleninger, Klaus Jöhnk, Bruna Arcie Polli, Zeli Tan, Wim Thiery, Qianlai Zhuang, James Anthony Rusak, Huaxia Yao, Andreas Lorke, and Victor Stepanenko
Hydrol. Earth Syst. Sci., 24, 697–715,Short summary
We compare lake models with different complexity focusing on the key factors (e.g., eddy diffusivity) which can have an influence on the distribution of the dissolved gases in water. For the first time, we compare the biogeochemical modules in the ALBM and LAKE models. The result showed a good agreement with observed data (O2), but not for CO2. It indicates the need to improve the representation of physical and biogeochemical processes in lake models.
Yixin Mao, Wade T. Crow, and Bart Nijssen
Hydrol. Earth Syst. Sci., 24, 615–631,Short summary
The new generation of satellite soil moisture observations are used to correct the streamflow in a regional-scale river basin simulated by a mathematical model. The correction is done via both the direct updating of soil moisture and correction of rainfall input. Results show some streamflow improvement, but the magnitude is small. A larger improvement will need future generations of even higher-quality satellite soil moisture data and better process representation in the mathematical model.
Jean-Pierre Vergnes, Nicolas Roux, Florence Habets, Philippe Ackerer, Nadia Amraoui, François Besson, Yvan Caballero, Quentin Courtois, Jean-Raynald de Dreuzy, Pierre Etchevers, Nicolas Gallois, Delphine J. Leroux, Laurent Longuevergne, Patrick Le Moigne, Thierry Morel, Simon Munier, Fabienne Regimbeau, Dominique Thiéry, and Pascal Viennot
Hydrol. Earth Syst. Sci., 24, 633–654,Short summary
The AquiFR hydrogeological modelling platform aims to provide short-term-to-seasonal hydrological forecasts over France for daily water management and long-term simulations for climate impact studies. The results described in this study confirm the feasibility of gathering independent groundwater models into the same numerical tool. This new tool encourages the development of groundwater modelling, and it has the potential to be valuable for many operational and research applications.
Jun Ge, Andrew J. Pitman, Weidong Guo, Beilei Zan, and Congbin Fu
Hydrol. Earth Syst. Sci., 24, 515–533,Short summary
We investigate the impact of revegetation on the hydrology of the Loess Plateau based on high-resolution simulations using the Weather Research and Forecasting (WRF) model. We find that past revegetation has caused decreased runoff and soil moisture with increased evapotranspiration as well as little response from rainfall. WRF suggests that further revegetation could aggravate this water imbalance. We caution that further revegetation might be unsustainable in this region.
Bertrand Bonan, Clément Albergel, Yongjun Zheng, Alina Lavinia Barbu, David Fairbairn, Simon Munier, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 24, 325–347,Short summary
This paper introduces an ensemble square root filter (EnSRF), a deterministic ensemble Kalman filter, for jointly assimilating observations of the surface soil moisture and leaf area index in the Land Data Assimilation System LDAS-Monde. LDAS-Monde constrains the Interaction between Soil, Biosphere and Atmosphere (ISBA) land surface model to improve the reanalysis of land surface variables. EnSRF is compared with the simplified extended Kalman filter over the European Mediterranean region.
Alfonso Senatore, Luca Furnari, and Giuseppe Mendicino
Hydrol. Earth Syst. Sci., 24, 269–291,Short summary
This paper addresses the question of how different resolutions of sea surface temperature (SST) representation affect regional operational hydro-meteorological forecasting chains over coastal Mediterranean catchments by analysing two different severe events that affected southern Italy in 2015. Even if the benefits of high-resolution SST representation are hidden by other sources of uncertainty, the experiments highlight that the impact is non-negligible in most cases.
Alfieri, L., Burek, P., Dutra, E., Krzeminski, B., Muraro, D., Thielen, J., and Pappenberger, F.: GloFAS – global ensemble streamflow forecasting and flood early warning, Hydrol. Earth Syst. Sci., 17, 1161–1175, https://doi.org/10.5194/hess-17-1161-2013, 2013.
Arsenault, K. R., Kumar, S. V., Geiger, J. V., Wang, S., Kemp, E., Mocko, D. M., Beaudoing, H. K., Getirana, A., Navari, M., Li, B., Jacob, J., Wegiel, J., and Peters-Lidard, C. D.: The Land surface Data Toolkit (LDT v7.2) – a data fusion environment for land data assimilation systems, Geosci. Model Dev., 11, 3605–3621, https://doi.org/10.5194/gmd-11-3605-2018, 2018.
Barros, V. R. and Field, C. B.: Climate change 2014: impacts, adaptation, and vulnerability. Part B: regional aspects, Cambridge University Press, Cambridge, UK, 2014.
Bell, V. A., Davies, H. N., Kay, A. L., Brookshaw, A., and Scaife, A. A.: A national-scale seasonal hydrological forecast system: development and evaluation over Britain, Hydrol. Earth Syst. Sci., 21, 4681–4691, https://doi.org/10.5194/hess-21-4681-2017, 2017.
Borovikov, A., Cullather, R., Kovach, R., Marshak, J., Vernieres, G., Vikhliaev, Y., Zhao, B., and Li, Z.: GEOS-5 seasonal forecast system, Clim. Dynam., 53, 7335–7361, 2019.
Cai, X., Yang, Z. L., David, C. H., Niu, G. Y., and Rodell, M.: Hydrological evaluation of the Noah-MP land surface model for the Mississippi River Basin, J. Geophys. Res.-Atmos., 119, 23–38, 2014.
Chen, G., Yang, Y., Yang, Z., Xie, J., Guo, J., Gao, R., Yin, Y., and Robinson, D.: Accelerated soil carbon turnover under tree plantations limits soil carbon storage, Sci. Rep., 6, 19693, https://doi.org/10.1038/srep19693, 2016.
Csiszar, I. and Gutman, G.: Mapping global land surface albedo from NOAA AVHRR, J. Geophys. Res.-Atmos., 104, 6215–6228, 1999.
de Andrade, F. M., Coelho, C. A., and Cavalcanti, I. F.: Global precipitation hindcast quality assessment of the Subseasonal to Seasonal (S2S) prediction project models, Clim. Dynam., 52, 5451–5475, 2019.
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, 8851, https://doi.org/10.1029/2002JD003296, 2003.
Farr, T. G., Rosen, P. A., Caro, E., Crippen, R., Duren, R., Hensley, S., Kobrick, M., Paller, M., Rodriguez, E., and Roth, L.: The shuttle radar topography mission, Rev. Geophys., 45, RG2004 https://doi.org/10.1029/2005RG000183, 2007.
Fowler, H. and Archer, D.: Conflicting signals of climatic change in the Upper Indus Basin, J. Climate, 19, 4276–4293, 2006.
Friedl, M. A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N., Sibley, A., and Huang, X.: MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets, Remote Sens. Environ., 114, 168–182, 2010.
Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., Husak, G., Rowland, J., Harrison, L., and Hoell, A.: The climate hazards infrared precipitation with stations – a new environmental record for monitoring extremes, Scientific Data, 2, 1–21, 2015.
Getirana, A., Jung, H. C., Arsenault, K., Shukla, S., Kumar, S., Peters-Lidard, C., Maigari, I., and Mamane, B.: Satellite gravimetry improves seasonal streamflow forecast initialization in Africa, Water Resour. Res., 56, e2019WR026259, https://doi.org/10.1029/2019WR026259, 2020a.
Getirana, A., Rodell, M., Kumar, S., Beaudoing, H. K., Arsenault, K., Zaitchik, B., Save, H., and Bettadpur, S.: GRACE Improves Seasonal Groundwater Forecast Initialization over the United States, J. Hydrometeorol., 21, 59–71, 2020c.
Getirana, A. C., Bonnet, M.-P., Calmant, S., Roux, E., Rotunno Filho, O. C., and Mansur, W. J.: Hydrological monitoring of poorly gauged basins based on rainfall-runoff modeling and spatial altimetry, J. Hydrol., 379, 205–219, 2009.
Ghatak, D., Zaitchik, B., Kumar, S., Matin, M., Bajracharya, B., Hain, C., and Anderson, M.: Influence of Precipitation Forcing Uncertainty on Hydrological Simulations with the NASA South Asia Land Data Assimilation System, Hydrology, 5, 57, https://doi.org/10.3390/hydrology5040057, 2018.
Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W.: Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019, 2019.
Gutman, G. and Ignatov, A.: The derivation of the green vegetation fraction from NOAA/AVHRR data for use in numerical weather prediction models, Int. J. Remote Sens., 19, 1533–1543, 1998.
Gutmann, E. D., Hamman, J. J., Clark, M. P., Eidhammer, T., Wood, A. W., Arnold, J. R., and Nowak, K.: Evaluating the effect of regional climate inference methodologies in a common framework, in preparation, 2020.
Hao, Z., Yuan, X., Xia, Y., Hao, F., and Singh, V. P.: An overview of drought monitoring and prediction systems at regional and global scales, B. Am. Meteorol. Soc., 98, 1879–1896, 2017.
Hatfield, J. L., Boote, K. J., Kimball, B., Ziska, L., Izaurralde, R. C., Ort, D., Thomson, A. M., and Wolfe, D.: Climate impacts on agriculture: implications for crop production, Agron. J., 103, 351–370, 2011.
ICIMOD: Regional Drought Monitoring and Outlook System for South Asia, available at: http://tethys.icimod.org/apps/regionaldrought/current/, last access: 17 December 2020.
Immerzeel, W.: Historical trends and future predictions of climate variability in the Brahmaputra basin, International Journal of Climatology, Q. J. Roy. Meteorol. Soc., 28, 243–254, 2008.
Jie, W., Vitart, F., Wu, T., and Liu, X.: Simulations of Asian Summer Monsoon in the Sub-seasonal to Seasonal Prediction Project (S2S) database, Q. J. Roy. Meteorol. Soc., 143, 2282–2295, https://doi.org/10.1002/qj.3085, 2017.
Koster, R. D., Suarez, M. J., Liu, P., Jambor, U., Berg, A., Kistler, M., Reichle, R., Rodell, M., and Famiglietti, J.: Realistic initialization of land surface states: Impacts on subseasonal forecast skill, J. Hydrometeorol., 5, 1049–1063, 2004.
Koster, R. D., Mahanama, S. P., Livneh, B., Lettenmaier, D. P., and Reichle, R. H.: Skill in streamflow forecasts derived from large-scale estimates of soil moisture and snow, Nat. Geosci., 3, 613–616, https://doi.org/10.1038/ngeo944, 2010.
Kumar, S., Mocko, D., Vuyovich, C., and Peters-Lidard, C.: Impact of Surface Albedo Assimilation on Snow Estimation, Remote Sens., 12, 645, https://doi.org/10.3390/rs12040645, 2020.
Kumar, S. V., Peters-Lidard, C. D., Tian, Y., Houser, P. R., Geiger, J., Olden, S., Lighty, L., Eastman, J. L., Doty, B., and Dirmeyer, P.: Land information system: An interoperable framework for high resolution land surface modeling, Environ. Modell. Softw., 21, 1402–1415, 2006.
Kumar, S. V., Mocko, M. D., Wang, S., Peters-Lidard, C. D., and Borak, J.: Assimilation of Remotely Sensed Leaf Area Index into the Noah-MP Land Surface Model: Impacts on Water and Carbon Fluxes and States over the Continental United States, J. Hydrometeorol., 20, 1359–1377, 2019.
Luo, L., Sheffield, J., and Wood, E.: Towards a Global Drought Monitoring and Forecasting Capability, in: 33rd NOAA Annual Climate Diagnostics and Prediction Workshop, 20–24 October 2008, Lincoln, Niger, 2008.
Ma, F., Luo, L., Ye, A., and Duan, Q.: Seasonal drought predictability and forecast skill in the semi-arid endorheic Heihe River basin in northwestern China, Hydrol. Earth Syst. Sci., 22, 5697–5709, https://doi.org/10.5194/hess-22-5697-2018, 2018.
Madadgar, S., AghaKouchak, A., Shukla, S., Wood, A. W., Cheng, L., Hsu, K. L., and Svoboda, M.: A hybrid statistical-dynamical framework for meteorological drought prediction: Application to the southwestern United States, Water Resour. Res., 52, 5095–5110, 2016.
Mitchell, K. E., Lohmann, D., Houser, P. R., Wood, E. F., Schaake, J. C., Robock, A., Cosgrove, B. A., Sheffield, J., Duan, Q., and Luo, L.: The multi-institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system, J. Geophys. Res.-Atmos., 109, 1–32, https://doi.org/10.1029/2003JD003823, 2004.
Molod, A., Hackert, E., Vikhliaev, Y., Zhao, B., Barahona, D., Vernieres, G., Borovikov, A., Kovach, R. M., Marshak, J., and Schubert, S.: GEOS-S2S Version 2: The GMAO High-Resolution Coupled Model and Assimilation System for Seasonal Prediction, J. Geophys. Res.-Atmos., 125, e2019JD031767, https://doi.org/10.1029/2019JD031767, 2020.
National Climatic Data Center: NCEP EDAS and GDAS (FNL) Model Data (DSI-6141), NESDIS, NOAA, https://doi.org/10.5065/D65Q4T4Z, 2020.
Nie, W., Zaitchik, B. F., Rodell, M., Kumar, S. V., Anderson, M. C., and Hain, C.: Groundwater withdrawals under drought: Reconciling GRACE and land surface models in the United States High Plains Aquifer, Water Resour. Res., 54, 5282–5299, 2018.
Nie, W., Zaitchik, B. F., Rodell, M., Kumar, S. V., Arsenault, K. R., Li, B., and Getirana, A.: Assimilating GRACE into a Land Surface Model in the presence of an irrigation-induced groundwater trend, Water Resour. Res., 55, 11274–11294, https://doi.org/10.1029/2019WR025363, 2019.
Niu, G. Y., Yang, Z. L., Mitchell, K. E., Chen, F., Ek, M. B., Barlage, M., Kumar, A., Manning, K., Niyogi, D., and Rosero, E.: The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements, J. Geophys. Res.-Atmos., 116, D12109, https://doi.org/10.1029/2010JD015139, 2011.
Pegion, K., Kirtman, B. P., Becker, E., Collins, D. C., LaJoie, E., Burgman, R., Bell, R., DelSole, T., Min, D., and Zhu, Y.: The Subseasonal Experiment (SubX): A Multimodel Subseasonal Prediction Experiment, B. Am. Meteorol. Soc., 100, 2043–2060, 2019.
Qian, X., Qiu, B., and Zhang, Y.: Widespread decline in vegetation photosynthesis in Southeast Asia due to the prolonged drought during the 2015/2016 El Niño, Remote Sens., 11, 910, https://doi.org/10.3390/rs11080910, 2019.
Rodell, M., Houser, P., Jambor, U., Gottschalck, J., Mitchell, K., Meng, C.-J., Arsenault, K., Cosgrove, B., Radakovich, J., and Bosilovich, M.: The global land data assimilation system, B. Am. Meteorol. Soc., 85, 381–394, 2004.
Rodrigues, E. R., Oliveira, I., Cunha, R., and Netto, M.: DeepDownscale: a deep learning strategy for high-resolution weather forecast, Proceedings of the IEEE 14th International Conference on e-Science, 29 October–1 November, Amsterdam, Netherlands, 415–422, 2018.
Samaniego, L., Thober, S., Kumar, R., Wanders, N., Rakovec, O., Pan, M., Zink, M., Sheffield, J., Wood, E. F., and Marx, A.: Anthropogenic warming exacerbates European soil moisture droughts, Nat. Clim. Change, 8, 421–426, 2018.
Samaniego, L., Thober, S., Wanders, N., Pan, M., Rakovec, O., Sheffield, J., Wood, E. F., Prudhomme, C., Rees, G., and Houghton-Carr, H.: Hydrological forecasts and projections for improved decision-making in the water sector in Europe, B. Am. Meteorol. Soc., 100, 2451–2472, 2019.
Seck, A., Welty, C., and Maxwell, R. M.: Spin-up behavior and effects of initial conditions for an integrated hydrologic model, Water Resour. Res., 51, 2188–2210, 2015.
Shah, R., Sahai, A. K., and Mishra, V.: Short to sub-seasonal hydrologic forecast to manage water and agricultural resources in India, Hydrol. Earth Syst. Sci., 21, 707–720, https://doi.org/10.5194/hess-21-707-2017, 2017.
Sheffield, J., Wood, E. F., Chaney, N., Guan, K., Sadri, S., Yuan, X., Olang, L., Amani, A., Ali, A., and Demuth, S.: A drought monitoring and forecasting system for sub-Sahara African water resources and food security, B. Am. Meteorol. Soc., 95, 861–882, 2014.
Shukla, S. and Lettenmaier, D. P.: Seasonal hydrologic prediction in the United States: understanding the role of initial hydrologic conditions and seasonal climate forecast skill, Hydrol. Earth Syst. Sci., 15, 3529–3538, https://doi.org/10.5194/hess-15-3529-2011, 2011.
Shukla, S., Funk, C., and Hoell, A.: Using constructed analogs to improve the skill of National Multi-Model Ensemble March–April–May precipitation forecasts in equatorial East Africa, Environ. Res. Lett., 9, 094009, https://doi.org/10.1088/1748-9326/9/9/094009, 2014.
Sivakumar, M. V. and Stefanski, R.: Climate change in South Asia, in: Climate change and food security in South Asia, edited by: Lal, R., Mannava, V. K., Sivakumar, S. M. A., Faiz, A. H. M, Rahman, M., and Islam, K. R., Springer, London, England, 13–30, 2010.
Svoboda, M., LeComte, D., Hayes, M., Heim, R., Gleason, K., Angel, J., Rippey, B., Tinker, R., Palecki, M., and Stooksbury, D.: The drought monitor, B. Am. Meteorol. Soc., 83, 1181–1190, 2002.
Syaukat, Y.: Irrigation in Southern and Eastern Asia in figures AQUASTAT Survey-2011, FAO the United Nation, Rome, Italy, 2012.
Van Der Schrier, G., Klein Tank, A. M., Van Den Besselaar, E. J., and Swarinoto, Y.: Observed trends and variability in climate indices relevant for crop yields in Southeast Asia, J. Climate, 29, 2651–2669, 2016.
Wanders, N. and Van Lanen, H. A. J.: Future discharge drought across climate regions around the world modelled with a synthetic hydrological modelling approach forced by three general circulation models, Nat. Hazards Earth Syst. Sci., 15, 487–504, https://doi.org/10.5194/nhess-15-487-2015, 2015.
Wanders, N. and Wada, Y.: Human and climate impacts on the 21st century hydrological drought, J. Hydrol., 526, 208–220, 2015.
Wanders, N., Karssenberg, D., de Roo, A., de Jong, S. M., and Bierkens, M. F. P.: The suitability of remotely sensed soil moisture for improving operational flood forecasting, Hydrol. Earth Syst. Sci., 18, 2343–2357, https://doi.org/10.5194/hess-18-2343-2014, 2014.
Wanders, N., Thober, S., Kumar, R., Pan, M., Sheffield, J., Samaniego, L., and Wood, E. F.: Development and evaluation of a pan-European multimodel seasonal hydrological forecasting system, J. Hydrometeorol., 20, 99–115, 2019.
Whitney, J. W.: Geology, water, and wind in the lower Helmand Basin, Southern Afghanistan U.S. Geological Survey, Reston, Virginia, USA, 2006.
Xia, Y., Mitchell, K., Ek, M., Sheffield, J., Cosgrove, B., Wood, E., Luo, L., Alonge, C., Wei, H., and Meng, J.: Continental-scale water and energy flux analysis and validation for the North American Land Data Assimilation System project phase 2 (NLDAS-2): 1. Intercomparison and application of model products, J. Geophys. Res.-Atmos., 117, D03109, https://doi.org/10.1029/2011JD016048, 2012.
Yang, Z. L., Niu, G. Y., Mitchell, K. E., Chen, F., Ek, M. B., Barlage, M., Longuevergne, L., Manning, K., Niyogi, D., and Tewari, M.: The community Noah land surface model with multiparameterization options (Noah-MP): 2. Evaluation over global river basins, J. Geophys. Res.-Atmos., 116, D12110, https://doi.org/10.1029/2010JD015140, 2011.
Yuan, X., Wood, E. F., Luo, L., and Pan, M.: A first look at Climate Forecast System version 2 (CFSv2) for hydrological seasonal prediction, Geophys. Res. Lett., 38, L13402, https://doi.org/10.1029/2011GL047792, 2011.
Yuan, X., Wood, E. F., Roundy, J. K., and Pan, M.: CFSv2-based seasonal hydroclimatic forecasts over the conterminous United States, J. Climate, 26, 4828–4847, 2013.
Yuan, X., Wood, E. F., and Liang, M.: Integrating weather and climate prediction: Toward seamless hydrologic forecasting, Geophys. Res. Lett., 41, 5891–5896, 2014.
Yuan, X., Wood, E. F., and Ma, Z.: A review on climate-model-based seasonal hydrologic forecasting: physical understanding and system development, WiRes. Water, 2, 523–536, 2015.
Yuan, X., Ma, F., Wang, L., Zheng, Z., Ma, Z., Ye, A., and Peng, S.: An experimental seasonal hydrological forecasting system over the Yellow River basin – Part 1: Understanding the role of initial hydrological conditions, Hydrol. Earth Syst. Sci., 20, 2437–2451, https://doi.org/10.5194/hess-20-2437-2016, 2016.
Zhou, Y., Zaitchik, B. F.., Kumar, S. V., Arsenault, K. R., and Zamora, R. A.: “Data associated with publication: Developing a hydrological monitoring and sub-seasonal to seasonal forecasting system for South and Southeast Asian river basins”, https://doi.org/10.7281/T1/JYAHTN, Johns Hopkins University Data Archive, V1, 2020.
South and Southeast Asia face significant food insecurity and hydrological hazards. Here we introduce a South and Southeast Asia hydrological monitoring and sub-seasonal to seasonal forecasting system (SAHFS-S2S) to help local governments and decision-makers prepare for extreme hydroclimatic events. The monitoring system captures soil moisture variability well in most regions, and the forecasting system offers skillful prediction of soil moisture variability 2–3 months in advance, on average.
South and Southeast Asia face significant food insecurity and hydrological hazards. Here we...