scholarly journals On the spatio-temporal analysis of hydrological droughts from global hydrological models

2011 ◽  
Vol 8 (1) ◽  
pp. 619-652 ◽  
Author(s):  
G. A. Corzo Perez ◽  
M. H. J. van Huijgevoort ◽  
F. Voß ◽  
H. A. J. van Lanen
Keyword(s):  
Time Series ◽  
20Th Century ◽  
Large Scale ◽  
Southern Oscillation ◽  
Regional Scale ◽  
Spatial Coherence ◽  
Temporal Analysis ◽  
Global Scale ◽  
Scale Models ◽  
Spatio Temporal

Abstract. The recent concerns for world-wide extreme events related to climate change phenomena have motivated the development of large scale models that simulate the global water cycle. In this context, analyses of extremes is an important topic that requires the adaptation of methods used for river basin and regional scale models. This paper presents two methodologies that extend the tools to analyze spatio-temporal drought development and characteristics using large scale gridded time series of hydrometeorological data. The methodologies are distinguished and defined as non-contiguous and contiguous drought area analyses (i.e. NCDA and CDA). The NCDA presents time series of percentages of areas in drought at the global scale and for pre-defined regions of known hydroclimatology. The CDA is introduced as a complementary method that generates information on the spatial coherence of drought events at the global scale. Spatial drought events are found through CDA by clustering patterns (contiguous areas). In this study the global hydrological model WaterGAP was used to illustrate the methodology development. Global gridded time series (resolution 0.5°) simulated with the WaterGAP model from land points were used. The NCDA and CDA were applied to identify drought events in subsurface runoff. The percentages of area in drought calculated with both methods show complementary information on the spatial and temporal events for the last decades of the 20th century. The NCDA provides relevant information on the average number of droughts, duration and severity (deficit volume) for pre-defined regions (globe, 2 selected climate regions). Additionally, the CDA provides information on the number of spatially linked areas in drought as well as their geographic location on the globe. An explorative validation process shows that the NCDA results capture the overall spatio-temporal drought extremes over the last decades of the 20th century. Events like the El Niño Southern Oscillation (ENSO) in South America and the pan-European drought in 1976 appeared clearly in both analyses. The methodologies introduced provide an important basis for the global characterization of droughts, model inter-comparison, and spatial events validation.

scholarly journals On the spatio-temporal analysis of hydrological droughts from global hydrological models

2011 ◽  
Vol 15 (9) ◽  
pp. 2963-2978 ◽  
Author(s):  
G. A. Corzo Perez ◽  
M. H. J. van Huijgevoort ◽  
F. Voß ◽  
H. A. J. van Lanen
Keyword(s):  
Time Series ◽  
20Th Century ◽  
Large Scale ◽  
Southern Oscillation ◽  
Spatial Coherence ◽  
Temporal Analysis ◽  
Global Scale ◽  
Hydrological Models ◽  
Context Analysis ◽  
Spatio Temporal

Abstract. The recent concerns for world-wide extreme events related to climate change have motivated the development of large scale models that simulate the global water cycle. In this context, analysis of hydrological extremes is important and requires the adaptation of identification methods used for river basin models. This paper presents two methodologies that extend the tools to analyze spatio-temporal drought development and characteristics using large scale gridded time series of hydrometeorological data. The methodologies are classified as non-contiguous and contiguous drought area analyses (i.e. NCDA and CDA). The NCDA presents time series of percentages of areas in drought at the global scale and for pre-defined regions of known hydroclimatology. The CDA is introduced as a complementary method that generates information on the spatial coherence of drought events at the global scale. Spatial drought events are found through CDA by clustering patterns (contiguous areas). In this study the global hydrological model WaterGAP was used to illustrate the methodology development. Global gridded time series of subsurface runoff (resolution 0.5°) simulated with the WaterGAP model from land points were used. The NCDA and CDA were developed to identify drought events in runoff. The percentages of area in drought calculated with both methods show complementary information on the spatial and temporal events for the last decades of the 20th century. The NCDA provides relevant information on the average number of droughts, duration and severity (deficit volume) for pre-defined regions (globe, 2 selected hydroclimatic regions). Additionally, the CDA provides information on the number of spatially linked areas in drought, maximum spatial event and their geographic location on the globe. Some results capture the overall spatio-temporal drought extremes over the last decades of the 20th century. Events like the El Niño Southern Oscillation (ENSO) in South America and the pan-European drought in 1976 appeared clearly in both analyses. The methodologies introduced provide an important basis for the global characterization of droughts, model inter-comparison of drought identified from global hydrological models and spatial event analyses.

scholarly journals Application of global models and satellite data for smaller-scale groundwater recharge studies

2016 ◽  
Author(s):  
Rogier Westerhoff ◽  
Paul White ◽  
Zara Rawlinson
Keyword(s):  
New Zealand ◽  
Satellite Data ◽  
Input Data ◽  
Large Scale ◽  
Regional Scale ◽  
Global Scale ◽  
Global Models ◽  
Scale Models ◽  
Boundary Issues ◽  
Rainfall Recharge

Abstract. Large-scale models and satellite data are increasingly used to characterise groundwater and its recharge at the global scale. Although these models have the potential to fill in data gaps and solve trans-boundary issues, they are often neglected in smaller-scale studies, since data are often coarse or uncertain. Large-scale models and satellite data could play a more important role in smaller-scale (i.e., national or regional) studies, if they could be adjusted to fit that scale. In New Zealand, large-scale models and satellite data are not used for groundwater recharge estimation at the national scale, since regional councils (i.e., the water managers) have varying water policy and models are calibrated at the local scale. Also, some regions have many localised ground observations (but poor record coverage), whereas others are data-sparse. Therefore, estimation of recharge is inconsistent at the national scale. This paper presents an approach to apply large-scale, global, models and satellite data to estimate rainfall recharge at the national to regional scale across New Zealand. We present a model, NGRM, that is largely inspired by the global-scale WaterGAP recharge model, but is improved and adjusted using national data. The NGRM model uses MODIS-derived ET and vegetation satellite data, and the available nation-wide datasets on rainfall, elevation, soil and geology. A valuable addition to the recharge estimation is the model uncertainty estimate, based on variance, covariance and sensitivity of all input data components in the model environment. This research shows that, with minor model adjustments and use of improved input data, large-scale models and satellite data can be used to derive rainfall recharge estimates, including their uncertainty, at the smaller scale, i.e., national and regional scale of New Zealand. The estimated New Zealand recharge of the NGRM model compare well to most local and regional lysimeter data and recharge models. The NGRM is therefore assumed to be capable to fill in gaps in data-sparse areas and to create more consistency between datasets from different regions, i.e., to solve trans-boundary issues. This research also shows that smaller-scale recharge studies in New Zealand should include larger boundaries than only a (sub-)aquifer, and preferably the whole catchment. This research points out the need for improved collaboration on the international to national to regional levels to further merge large-scale (global) models to smaller (i.e., national or regional) scales. Future research topics should, collaboratively, focus on: improvement of rainfall-runoff and snowmelt methods; inclusion of river recharge; further improvement of input data (rainfall, evapotranspiration, soil and geology); and the impact of recharge uncertainty in mountainous and irrigated areas.

Sea Surface Temperatures along the Coast of British Columbia: Regional Evidence for a Warming Trend

1990 ◽  
Vol 47 (2) ◽  
pp. 346-350 ◽  
Author(s):  
Howard J. Freeland
Keyword(s):  
British Columbia ◽  
Time Series ◽  
Large Scale ◽  
Southern Oscillation ◽  
Warming Trend ◽  
Global Scale ◽  
Sea Surface ◽  
Sea Surface Temperatures ◽  
Mean Values ◽  
Surface Temperatures

Sea-surface temperature has been measured at a large number of sites around the coast of British Columbia for periods well in excess of 50 yr. These time series are long enough to give clear evidence of a large scale secular warming. For the purposes of this paper the daily SST observations are decimated to monthly mean values. The observations are of particular value because observation methods have remained invariant throughout the observation period, and many of the stations are remote from civilisation allowing trends to be estimated that have not been contaminated with urbanization effects. Eighteen out of nineteen stations that are currently being sampled show a warming trend, the one that shows a cooling trend is the shortest time series, only in its eleventh year. The sea-surface temperatures at sites exposed to the Pacific Ocean show very high coherence with global scale air temperature variations but no relationship to the El Niño/Southern Oscillation signal.

scholarly journals GMD perspective: The quest to improve the evaluation of groundwater representation in continental- to global-scale models

2021 ◽  
Vol 14 (12) ◽  
pp. 7545-7571
Author(s):  
Tom Gleeson ◽  
Thorsten Wagener ◽  
Petra Döll ◽  
Samuel C. Zipper ◽  
Charles West ◽  
...  
Keyword(s):  
Model Evaluation ◽  
Land Surface ◽  
Large Scale ◽  
Groundwater Resources ◽  
Regional Scale ◽  
Global Scale ◽  
Expert Elicitation ◽  
Data Availability ◽  
Scale Model ◽  
Scale Models

Abstract. Continental- to global-scale hydrologic and land surface models increasingly include representations of the groundwater system. Such large-scale models are essential for examining, communicating, and understanding the dynamic interactions between the Earth system above and below the land surface as well as the opportunities and limits of groundwater resources. We argue that both large-scale and regional-scale groundwater models have utility, strengths, and limitations, so continued modeling at both scales is essential and mutually beneficial. A crucial quest is how to evaluate the realism, capabilities, and performance of large-scale groundwater models given their modeling purpose of addressing large-scale science or sustainability questions as well as limitations in data availability and commensurability. Evaluation should identify if, when, or where large-scale models achieve their purpose or where opportunities for improvements exist so that such models better achieve their purpose. We suggest that reproducing the spatiotemporal details of regional-scale models and matching local data are not relevant goals. Instead, it is important to decide on reasonable model expectations regarding when a large-scale model is performing “well enough” in the context of its specific purpose. The decision of reasonable expectations is necessarily subjective even if the evaluation criteria are quantitative. Our objective is to provide recommendations for improving the evaluation of groundwater representation in continental- to global-scale models. We describe current modeling strategies and evaluation practices, and we subsequently discuss the value of three evaluation strategies: (1) comparing model outputs with available observations of groundwater levels or other state or flux variables (observation-based evaluation), (2) comparing several models with each other with or without reference to actual observations (model-based evaluation), and (3) comparing model behavior with expert expectations of hydrologic behaviors in particular regions or at particular times (expert-based evaluation). Based on evolving practices in model evaluation as well as innovations in observations, machine learning, and expert elicitation, we argue that combining observation-, model-, and expert-based model evaluation approaches, while accounting for commensurability issues, may significantly improve the realism of groundwater representation in large-scale models, thus advancing our ability for quantification, understanding, and prediction of crucial Earth science and sustainability problems. We encourage greater community-level communication and cooperation on this quest, including among global hydrology and land surface modelers, local to regional hydrogeologists, and hydrologists focused on model development and evaluation.

scholarly journals GMD Perspective: the quest to improve the evaluation of groundwater representation in continental to global scale models

2021 ◽  
Author(s):  
Tom Gleeson ◽  
Thorsten Wagener ◽  
Petra Döll ◽  
Samuel C. Zipper ◽  
Charles West ◽  
...  
Keyword(s):  
Model Evaluation ◽  
Land Surface ◽  
Large Scale ◽  
Groundwater Resources ◽  
Regional Scale ◽  
Global Scale ◽  
Expert Elicitation ◽  
Data Availability ◽  
Scale Model ◽  
Scale Models

Abstract. Continental- to global-scale hydrologic and land surface models increasingly include representations of the groundwater system. Such large-scale models are essential for examining, communicating, and understanding the dynamic interactions between the Earth System above and below the land surface as well as the opportunities and limits of groundwater resources. We argue that both large-scale and regional-scale groundwater models have utility, strengths and limitations so continued modeling at both scales is essential and mutually beneficial. A crucial quest is how to evaluate the realism, capabilities and performance of large-scale groundwater models given their modeling purpose of addressing large-scale science or sustainability questions as well as limitations in data availability and commensurability. Evaluation should identify if, when or where large-scale models achieve their purpose or where opportunities for improvements exists so that such models better achieve their purpose. We suggest that reproducing the spatio-temporal details of regional-scale models and matching local data is not a relevant goal. Instead, it is important to decide on reasonable model expectations regarding when a large scale model is performing “well enough” in the context of its specific purpose. The decision of reasonable expectations is necessarily subjective even if the evaluation criteria is quantitative. Our objective is to provide recommendations for improving the evaluation of groundwater representation in continental- to global-scale models. We describe current modeling strategies and evaluation practices, and subsequently discuss the value of three evaluation strategies: 1) comparing model outputs with available observations of groundwater levels or other state or flux variables (observation-based evaluation); 2) comparing several models with each other with or without reference to actual observations (model-based evaluation); and 3) comparing model behavior with expert expectations of hydrologic behaviors in particular regions or at particular times (expert-based evaluation). Based on evolving practices in model evaluation as well as innovations in observations, machine learning and expert elicitation, we argue that combining observation-, model-, and expert-based model evaluation approaches, while accounting for commensurability issues, may significantly improve the realism of groundwater representation in large-scale models. Thus advancing our ability for quantification, understanding, and prediction of crucial Earth science and sustainability problems. We encourage greater community-level communication and cooperation on this quest, including among global hydrology and land surface modelers, local to regional hydrogeologists, and hydrologists focused on model development and evaluation.

scholarly journals Historical drought patterns over Canada and their teleconnections with large-scale climate signals

2018 ◽  
Vol 22 (6) ◽  
pp. 3105-3124 ◽  
Author(s):  
Zilefac Elvis Asong ◽  
Howard Simon Wheater ◽  
Barrie Bonsal ◽  
Saman Razavi ◽  
Sopan Kurkute
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Low Frequency ◽  
Kendall Test ◽  
Wavelet Coherence ◽  
Climate Indices ◽  
Data Sets ◽  
Canadian Prairies ◽  
Agriculture Industry ◽  
Spatio Temporal

Abstract. Drought is a recurring extreme climate event and among the most costly natural disasters in the world. This is particularly true over Canada, where drought is both a frequent and damaging phenomenon with impacts on regional water resources, agriculture, industry, aquatic ecosystems, and health. However, nationwide drought assessments are currently lacking and impacted by limited ground-based observations. This study provides a comprehensive analysis of historical droughts over the whole of Canada, including the role of large-scale teleconnections. Drought events are characterized by the Standardized Precipitation Evapotranspiration Index (SPEI) over various temporal scales (1, 3, 6, and 12 consecutive months, 6 months from April to September, and 12 months from October to September) applied to different gridded monthly data sets for the period 1950–2013. The Mann–Kendall test, rotated empirical orthogonal function, continuous wavelet transform, and wavelet coherence analyses are used, respectively, to investigate the trend, spatio-temporal patterns, periodicity, and teleconnectivity of drought events. Results indicate that southern (northern) parts of the country experienced significant trends towards drier (wetter) conditions although substantial variability exists. Two spatially well-defined regions with different temporal evolution of droughts were identified – the Canadian Prairies and northern central Canada. The analyses also revealed the presence of a dominant periodicity of between 8 and 32 months in the Prairie region and between 8 and 40 months in the northern central region. These cycles of low-frequency variability are found to be associated principally with the Pacific–North American (PNA) and Multivariate El Niño/Southern Oscillation Index (MEI) relative to other considered large-scale climate indices. This study is the first of its kind to identify dominant periodicities in drought variability over the whole of Canada in terms of when the drought events occur, their duration, and how often they occur.

Global scale hydrological modelling at 100 m, 1 h resolution, in Python

2021 ◽  
Author(s):  
Kor de Jong ◽  
Marc van Kreveld ◽  
Debabrata Panja ◽  
Oliver Schmitz ◽  
Derek Karssenberg
Keyword(s):  
Large Scale ◽  
Model Building ◽  
Flow Direction ◽  
Building Blocks ◽  
Global Scale ◽  
Data Availability ◽  
Hydrological Models ◽  
Continental Scale ◽  
Modelling Framework ◽  
Scale Models

<p>Data availability at global scale is increasing exponentially. Although considerable challenges remain regarding the identification of model structure and parameters of continental scale hydrological models, we will soon reach the situation that global scale models could be defined at very high resolutions close to 100 m or less. One of the key challenges is how to make simulations of these ultra-high resolution models tractable ([1]).</p><p>Our research contributes by the development of a model building framework that is specifically designed to distribute calculations over multiple cluster nodes. This framework enables domain experts like hydrologists to develop their own large scale models, using a scripting language like Python, without the need to acquire the skills to develop low-level computer code for parallel and distributed computing.</p><p>We present the design and implementation of this software framework and illustrate its use with a prototype 100 m, 1 h continental scale hydrological model. Our modelling framework ensures that any model built with it is parallelized. This is made possible by providing the model builder with a set of building blocks of models, which are coded in such a manner that parallelization of calculations occurs within and across these building blocks, for any combination of building blocks. There is thus full flexibility on the side of the modeller, without losing performance.</p><p>This breakthrough is made possible by applying a novel approach to the implementation of the model building framework, called asynchronous many-tasks, provided by the HPX C++ software library ([3]). The code in the model building framework expresses spatial operations as large collections of interdependent tasks that can be executed efficiently on individual laptops as well as computer clusters ([2]). Our framework currently includes the most essential operations for building large scale hydrological models, including those for simulating transport of material through a flow direction network. By combining these operations, we rebuilt an existing 100 m, 1 h resolution model, thus far used for simulations of small catchments, requiring limited coding as we only had to replace the computational back end of the existing model. Runs at continental scale on a computer cluster show acceptable strong and weak scaling providing a strong indication that global simulations at this resolution will soon be possible, technically speaking.</p><p>Future work will focus on extending the set of modelling operations and adding scalable I/O, after which existing models that are currently limited in their ability to use the computational resources available to them can be ported to this new environment.</p><p>More information about our modelling framework is at https://lue.computationalgeography.org.</p><p><strong>References</strong></p><p>[1] M. Bierkens. Global hydrology 2015: State, trends, and directions. Water Resources Research, 51(7):4923–4947, 2015.<br>[2] K. de Jong, et al. An environmental modelling framework based on asynchronous many-tasks: scalability and usability. Submitted.<br>[3] H. Kaiser, et al. HPX - The C++ standard library for parallelism and concurrency. Journal of Open Source Software, 5(53):2352, 2020.</p>

scholarly journals Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods

2017 ◽  
Author(s):  
Cherry May R. Mateo ◽  
Dai Yamazaki ◽  
Hyungjun Kim ◽  
Adisorn Champathong ◽  
Jai Vaze ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Large Scale ◽  
Flood Hazard ◽  
Regional Scale ◽  
Global Scale ◽  
Test Case ◽  
Efficiency Coefficient ◽  
Computational Power ◽  
Extreme Flood ◽  
Simulation Results

Abstract. Global-scale River Models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representation of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash–Sutcliffe Efficiency coefficient decreased by more than 35 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions in finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings are universal and can be extended to global-scale simulations. These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

scholarly journals Global biogeography of living brachiopods: Bioregionalization patterns and possible controls

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0259004
Author(s):  
Facheng Ye ◽  
G. R. Shi ◽  
Maria Aleksandra Bitner
Keyword(s):  
Large Scale ◽  
Coastal Upwelling ◽  
Seawater Temperature ◽  
Regional Scale ◽  
Distribution Patterns ◽  
Global Scale ◽  
Biodiversity Hotspots ◽  
Network Analyses ◽  
Ocean Gyres ◽  
Ecological Variable

The global distribution patterns of 14918 geo-referenced occurrences from 394 living brachiopod species were mapped in 5° grid cells, which enabled the visualization and delineation of distinct bioregions and biodiversity hotspots. Further investigation using cluster and network analyses allowed us to propose the first systematically and quantitatively recognized global bioregionalization framework for living brachiopods, consisting of five bioregions and thirteen bioprovinces. No single environmental or ecological variable is accountable for the newly proposed global bioregionalization patterns of living brachiopods. Instead, the combined effects of large-scale ocean gyres, climatic zonation as well as some geohistorical factors (e.g., formation of land bridges and geological recent closure of ancient seaways) are considered as the main drivers at the global scale. At the regional scale, however, the faunal composition, diversity and biogeographical differentiation appear to be mainly controlled by seawater temperature variation, regional ocean currents and coastal upwelling systems.

scholarly journals Modelling supraglacial debris-cover evolution from the single glacier to the regional scale: an application to High Mountain Asia

2021 ◽  
Author(s):  
Loris Compagno ◽  
Matthias Huss ◽  
Evan Stewart Miles ◽  
Michael James McCarthy ◽  
Harry Zekollari ◽  
...  
Keyword(s):  
Mass Balance ◽  
Temporal Evolution ◽  
Regional Scale ◽  
Global Scale ◽  
High Mountain ◽  
Surface Mass ◽  
Future Evolution ◽  
Debris Cover ◽  
Scale Modelling ◽  
Spatio Temporal

Abstract. Currently, about 12–13 % of High Mountain Asia's glacier area is debris-covered, altering its surface mass balance. However, in regional-scale modelling approaches, debris-covered glaciers are typically treated as clean-ice glaciers, leading to a potential bias when modelling their future evolution. Here, we present a new approach for modelling debris area and thickness evolution, applicable from single glaciers to the global scale. We implement the module into the Global Glacier Evolution Model (GloGEMflow), a combined mass-balance ice-flow model. The module is initialized with both glacier-specific observations of the debris’ spatial distribution and estimates of debris thickness, accounts for the fact that debris can either enhance or reduce surface melt depending on thickness, and enables representing the spatio-temporal evolution of debris extent and thickness. We calibrate and evaluate the module on a select subset of glaciers, and apply the model using different climate scenarios to project the future evolution of all glaciers in High Mountain Asia until 2100. Compared to 2020, total glacier volume is expected to decrease by between 35 ± 15 % and 80 ±11 %, which is in line with projections in the literature. Depending on the scenario, the mean debris-cover fraction is expected to increase, while mean debris thickness is modelled to show only minor changes, albeit large local thickening is expected. To isolate the influence of explicitly accounting for supraglacial debris-cover, we re-compute glacier evolution without the debris-cover module. We show that glacier geometry, area, volume and flow velocity evolve differently, especially at the level of individual glaciers. This highlights the importance of accounting for debris-cover and its spatio-temporal evolution when projecting future glacier changes.

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