Controls of alluvial aquifers on continental drainage

2020 ◽  
Author(s):  
Stefan Kollet ◽  
Wendy Sharples ◽  
Bibi Naz
Keyword(s):  
Water Resource Management ◽  
Large Scale ◽  
Dynamic Equilibrium ◽  
Anthropogenic Impacts ◽  
Monitoring Networks ◽  
Spatial Continuity ◽  
Spatial And Temporal Scales ◽  
Alluvial Aquifers ◽  
Continental Scale ◽  
Surface Water Flow

<p>Continental-scale hydrological research is becoming more important as climate variability and change, and anthropogenic impacts on groundwater, are increasing over large spatial and temporal scales. Groundwater quantities and flows are usually difficult to observe due to sparse or spatially limited monitoring networks.  Thus, large-scale hydrological models are needed to provide continuous predictions of hydrological states and fluxes for water resource management. A large part of groundwater consumed comes from alluvial aquifers, which constitute valley fills of continental catchments. While the role of alluvial aquifers as a significant water store has been subject of many previous studies, the importance of the spatial extent and continuity of alluvial aquifers in the drainage characteristics of freshwater from the continental interior to the oceans is unclear. We present a high resolution (3km) hydrological model of continental Europe using ParFlow, a 3D, parallel groundwater and surface water flow model, which uses detailed hydrofacies information as input. We discuss the effect of spatial continuity and extent of alluvial aquifers on continental lateral groundwater flow and discharge to the oceans, water table depth, streamflow, and surface and subsurface storage. The results suggest that the alluvial valleys act as conduits that manage the drainage and retention of continental freshwater in sync with the atmospheric forcing. This dynamic equilibrium may be significantly disturbed by human interventions such as pumping and irrigation leading to a new equilibrium in terms of continental water quantity and also quality.</p>

scholarly journals Evaluating Machine Learning and Geostatistical Methods for Spatial Gap-filling of Monthly ESA CCI Soil Moisture in China

2021 ◽  
Vol 13 (14) ◽  
pp. 2848
Author(s):  
Hao Sun ◽  
Qian Xu
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Water Resource Management ◽  
Large Scale ◽  
Gap Filling ◽  
Spatial Continuity ◽  
Study Results ◽  
Data Gaps

Obtaining large-scale, long-term, and spatial continuous soil moisture (SM) data is crucial for climate change, hydrology, and water resource management, etc. ESA CCI SM is such a large-scale and long-term SM (longer than 40 years until now). However, there exist data gaps, especially for the area of China, due to the limitations in remote sensing of SM such as complex topography, human-induced radio frequency interference (RFI), and vegetation disturbances, etc. The data gaps make the CCI SM data cannot achieve spatial continuity, which entails the study of gap-filling methods. In order to develop suitable methods to fill the gaps of CCI SM in the whole area of China, we compared typical Machine Learning (ML) methods, including Random Forest method (RF), Feedforward Neural Network method (FNN), and Generalized Linear Model (GLM) with a geostatistical method, i.e., Ordinary Kriging (OK) in this study. More than 30 years of passive–active combined CCI SM from 1982 to 2018 and other biophysical variables such as Normalized Difference Vegetation Index (NDVI), precipitation, air temperature, Digital Elevation Model (DEM), soil type, and in situ SM from International Soil Moisture Network (ISMN) were utilized in this study. Results indicated that: 1) the data gap of CCI SM is frequent in China, which is found not only in cold seasons and areas but also in warm seasons and areas. The ratio of gap pixel numbers to the whole pixel numbers can be greater than 80%, and its average is around 40%. 2) ML methods can fill the gaps of CCI SM all up. Among the ML methods, RF had the best performance in fitting the relationship between CCI SM and biophysical variables. 3) Over simulated gap areas, RF had a comparable performance with OK, and they outperformed the FNN and GLM methods greatly. 4) Over in situ SM networks, RF achieved better performance than the OK method. 5) We also explored various strategies for gap-filling CCI SM. Results demonstrated that the strategy of constructing a monthly model with one RF for simulating monthly average SM and another RF for simulating monthly SM disturbance achieved the best performance. Such strategy combining with the ML method such as the RF is suggested in this study for filling the gaps of CCI SM in China.

scholarly journals Understanding and predicting large-scale hydrological variability in a changing environment

2020 ◽  
Vol 383 ◽  
pp. 141-149
Author(s):  
Nicolas Massei ◽  
Daniel G. Kingston ◽  
David M. Hannah ◽  
Jean-Philippe Vidal ◽  
Bastien Dieppois ◽  
...  
Keyword(s):  
Water Resource Management ◽  
Large Scale ◽  
Spatial Scales ◽  
Regional Scale ◽  
System Response ◽  
Event Scale ◽  
Spatial And Temporal Scales ◽  
Hydrological Variability ◽  
New Findings

Abstract. In a context of climate, environmental, ecological and socio-economical changes, understanding and predicting the response of hydrological systems on regional to global spatial scales, and on infra-seasonal to multidecadal time-scales, are major topics that must be considered to tackle the challenge of water resource management sustainability. In this context, a number of strongly-linked key issues need to be addressed by the scientific community, including: (i) identifying climate drivers of hydrological variations, (ii) understanding the multi-frequency characteristics of hydroclimate variability, including evolution of extremes (meteorological/hydrological event scale to long-term natural/internal climate- or anthropogenic-driven variations and trends), (iii) assessing the influence of local- to regional-scale basin properties on hydrological system response to climate variability and change, (iv) identifying the evolving contribution of anthropogenic water use in observed hydrological variations. Based on pan-European collaborations, activities of the EURO-FRIEND “Large-scale variations in hydrological characteristics” group aim at generating new findings to improve our understanding of hydrological systems behavior sensu lato (i.e. surface and sub-surface) on large spatial and temporal scales (i.e continental – multidecadal). Through selected examples, this contribution emphasizes recent research developments in characterizing and modeling of climate-hydrology linkages at different temporal and spatial scales, as well as recent insights on climate-hydrology scaling characteristics (i.e. long-term persistence, dependance of processes, of hydrological behaviors, of large-scale climate/hydrology linkages on time-/spatial scales), long-term hydrometeorological reconstructions, and large-scale hydrological model refinement taking into account spatial heterogeneity of watershed physical characteristics.

scholarly journals Mapping the Distribution of Water Resource Security in the Beijing-Tianjin-Hebei Region at the County Level under a Changing Context

2019 ◽  
Vol 11 (22) ◽  
pp. 6463 ◽  
Author(s):  
Li ◽  
Yin ◽  
Zhang ◽  
Croke ◽  
Guo ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Water Resource ◽  
Water Resource Management ◽  
Large Scale ◽  
Water Diversion ◽  
County Level ◽  
Populated Region ◽  
Water Resource Security ◽  
Resource Security

The Beijing-Tianjin-Hebei (Jingjinji) region is the most densely populated region in China and suffers from severe water resource shortage, with considerable water-related issues emerging under a changing context such as construction of water diversion projects (WDP), regional synergistic development, and climate change. To this end, this paper develops a framework to examine the water resource security for 200 counties in the Jingjinji region under these changes. Thus, county-level water resource security is assessed in terms of the long-term annual mean and selected typical years (i.e., dry, normal, and wet years), with and without the WDP, and under the current and projected future (i.e., regional synergistic development and climate change). The outcomes of such scenarios are assessed based on two water-crowding indicators, two use-to-availability indicators, and one composite indicator. Results indicate first that the water resources are distributed unevenly, relatively more abundant in the northeastern counties and extremely limited in the other counties. The water resources are very limited at the regional level, with the water availability per capita and per unit gross domestic product (GDP) being only 279/290 m3 and 46/18 m3 in the current and projected future scenarios, respectively, even when considering the WDP. Second, the population carrying capacity is currently the dominant influence, while economic development will be the controlling factor in the future for most middle and southern counties. This suggests that significant improvement in water-saving technologies, vigorous replacement of industries from high to low water consumption, as well as water from other supplies for large-scale applications are greatly needed. Third, the research identifies those counties most at risk to water scarcity and shows that most of them can be greatly relieved after supplementation by the planned WDP. Finally, more attention should be paid to the southern counties because their water resources are not only limited but also much more sensitive and vulnerable to climate change. This work should benefit water resource management and allocation decisions in the Jingjinji region, and the proposed assessment framework can be applied to other similar problems.

scholarly journals Rossby Waves in Astrophysics

2021 ◽  
Vol 217 (1) ◽  
Author(s):  
T. V. Zaqarashvili ◽  
M. Albekioni ◽  
J. L. Ballester ◽  
Y. Bekki ◽  
L. Biancofiore ◽  
...  
Keyword(s):  
Large Scale ◽  
Rossby Waves ◽  
Magnetic Activity ◽  
Future Research ◽  
Rotating Stars ◽  
Spatial And Temporal Scales ◽  
Physical Role ◽  
Astrophysical Objects ◽  
Exoplanetary Atmospheres ◽  
Rapidly Rotating Stars

AbstractRossby waves are a pervasive feature of the large-scale motions of the Earth’s atmosphere and oceans. These waves (also known as planetary waves and r-modes) also play an important role in the large-scale dynamics of different astrophysical objects such as the solar atmosphere and interior, astrophysical discs, rapidly rotating stars, planetary and exoplanetary atmospheres. This paper provides a review of theoretical and observational aspects of Rossby waves on different spatial and temporal scales in various astrophysical settings. The physical role played by Rossby-type waves and associated instabilities is discussed in the context of solar and stellar magnetic activity, angular momentum transport in astrophysical discs, planet formation, and other astrophysical processes. Possible directions of future research in theoretical and observational aspects of astrophysical Rossby waves are outlined.

scholarly journals Analog Downscaling of Seasonal Rainfall Forecasts in the Murray Darling Basin

2013 ◽  
Vol 141 (3) ◽  
pp. 1099-1117 ◽  
Author(s):  
Andrew Charles ◽  
Bertrand Timbal ◽  
Elodie Fernandez ◽  
Harry Hendon
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Seasonal Prediction ◽  
General Circulation Models ◽  
Meridional Wind ◽  
Seasonal Forecasts ◽  
Local Climate ◽  
Continental Scale ◽  
Predictive Skill ◽  
Murray Darling Basin

Abstract Seasonal predictions based on coupled atmosphere–ocean general circulation models (GCMs) provide useful predictions of large-scale circulation but lack the conditioning on topography required for locally relevant prediction. In this study a statistical downscaling model based on meteorological analogs was applied to continental-scale GCM-based seasonal forecasts and high quality historical site observations to generate a set of downscaled precipitation hindcasts at 160 sites in the South Murray Darling Basin region of Australia. Large-scale fields from the Predictive Ocean–Atmosphere Model for Australia (POAMA) 1.5b GCM-based seasonal prediction system are used for analog selection. Correlation analysis indicates modest levels of predictability in the target region for the selected predictor fields. A single best-match analog was found using model sea level pressure, meridional wind, and rainfall fields, with the procedure applied to 3-month-long reforecasts, initialized on the first day of each month from 1980 to 2006, for each model day of 10 ensemble members. Assessment of the total accumulated rainfall and number of rainy days in the 3-month reforecasts shows that the downscaling procedure corrects the local climate variability with no mean effect on predictive skill, resulting in a smaller magnitude error. The amount of total rainfall and number of rain days in the downscaled output is significantly improved over the direct GCM output as measured by the difference in median and tercile thresholds between station observations and downscaled rainfall. Confidence in the downscaled output is enhanced by strong consistency between the large-scale mean of the downscaled and direct GCM precipitation.

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 Herbarium specimens reveal substantial and unexpected variation in phenological sensitivity across the eastern United States

2018 ◽  
Vol 374 (1763) ◽  
pp. 20170394 ◽  
Author(s):  
Daniel S. Park ◽  
Ian Breckheimer ◽  
Alex C. Williams ◽  
Edith Law ◽  
Aaron M. Ellison ◽  
...  
Keyword(s):  
United States ◽  
Climatic Change ◽  
Large Scale ◽  
Critical Role ◽  
Flowering Plant ◽  
Reproductive Phenology ◽  
Herbarium Specimens ◽  
Eastern United States ◽  
Regional Patterns ◽  
Continental Scale

Phenology is a key biological trait that can determine an organism's survival and provides one of the clearest indicators of the effects of recent climatic change. Long time-series observations of plant phenology collected at continental scales could clarify latitudinal and regional patterns of plant responses and illuminate drivers of that variation, but few such datasets exist. Here, we use the web tool CrowdCurio to crowdsource phenological data from over 7000 herbarium specimens representing 30 diverse flowering plant species distributed across the eastern United States. Our results, spanning 120 years and generated from over 2000 crowdsourcers, illustrate numerous aspects of continental-scale plant reproductive phenology. First, they support prior studies that found plant reproductive phenology significantly advances in response to warming, especially for early-flowering species. Second, they reveal that fruiting in populations from warmer, lower latitudes is significantly more phenologically sensitive to temperature than that for populations from colder, higher-latitude regions. Last, we found that variation in phenological sensitivities to climate within species between regions was of similar magnitude to variation between species. Overall, our results suggest that phenological responses to anthropogenic climate change will be heterogeneous within communities and across regions, with large amounts of regional variability driven by local adaptation, phenotypic plasticity and differences in species assemblages. As millions of imaged herbarium specimens become available online, they will play an increasingly critical role in revealing large-scale patterns within assemblages and across continents that ultimately can improve forecasts of the impacts of climatic change on the structure and function of ecosystems. This article is part of the theme issue ‘Biological collections for understanding biodiversity in the Anthropocene’.

Late-summer carbon fluxes from Canadian forests and peatlands along an east–west continental transect

2006 ◽  
Vol 36 (3) ◽  
pp. 783-800 ◽  
Author(s):  
Carole Coursolle ◽  
Hank A Margolis ◽  
Alan G Barr ◽  
T Andrew Black ◽  
Brian D Amiro ◽  
...  
Keyword(s):  
Large Scale ◽  
Ecosystem Respiration ◽  
Late Summer ◽  
Ecosystem Productivity ◽  
Diurnal Courses ◽  
Continental Scale ◽  
Young Forest ◽  
C Cycle ◽  
Use Efficiency ◽  
East West

Net ecosystem productivity (NEP) during August 2003 was measured by using eddy covariance above 17 forest and 3 peatland sites along an east–west continental-scale transect in Canada. Measured sites included recently disturbed stands, young forest stands, intermediate-aged conifer stands, mature deciduous stands, mature conifer stands, fens, and an open shrub bog. Diurnal courses of NEP showed strong coherence within the different ecosystem categories. Recently disturbed sites showed the weakest diurnal cycle; and intermediate-aged conifers, the strongest. The western treed fen had a more pronounced diurnal pattern than the eastern shrub bog or the Saskatchewan patterned fen. All but three sites were clearly afternoon C sinks. Ecosystem respiration was highest for the young fire sites. The intermediate-aged conifer sites had the highest maximum NEP (NEPmax) and gross ecosystem productivity (GEPmax), attaining rates that would be consistent with the presence of a strong terrestrial C sink in regions where these types of forest are common. These results support the idea that large-scale C cycle modeling activities would benefit from information on the age-class distribution and disturbance types within larger grid cells. Light use efficiency followed a pattern similar to that of NEPmax and GEPmax. Four of the five recently disturbed sites and all three of the peatland sites had low water use efficiencies.

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