scholarly journals A new approach to model the spatial and temporal variability of recharge to karst aquifers

2012 ◽  
Vol 16 (7) ◽  
pp. 2219-2231 ◽  
Author(s):  
A. Hartmann ◽  
J. Lange ◽  
M. Weiler ◽  
Y. Arbel ◽  
N. Greenbaum
Keyword(s):  
Time Series ◽  
Spatial Variability ◽  
Temporal Variability ◽  
Model Performance ◽  
Spatial And Temporal Variability ◽  
Hydrological Models ◽  
Near Surface ◽  
New Approach ◽  
Spatially Distributed ◽  
Karst Systems

Abstract. In karst systems, near-surface dissolution of carbonate rock results in a high spatial and temporal variability of groundwater recharge. To adequately represent the dominating recharge processes in hydrological models is still a challenge, especially in data scarce regions. In this study, we developed a recharge model that is based on a conceptual model of the epikarst. It represents epikarst heterogeneity as a set of system property distributions to produce not only a single recharge time series, but a variety of time series representing the spatial recharge variability. We tested the new model with a unique set of spatially distributed flow and tracer observations in a karstic cave at Mt. Carmel, Israel. We transformed the spatial variability into statistical variables and apply an iterative calibration strategy in which more and more data was added to the calibration. Thereby, we could show that the model is only able to produce realistic results when the information about the spatial variability of the observations was included into the model calibration. We could also show that tracer information improves the model performance if data about the spatial variability is not included.

scholarly journals A new approach to model the variability of karstic recharge

2012 ◽  
Vol 9 (2) ◽  
pp. 2443-2473
Author(s):  
A. Hartmann ◽  
J. Lange ◽  
M. Weiler ◽  
Y. Arbel ◽  
N. Greenbaum
Keyword(s):  
Time Series ◽  
Spatial Variability ◽  
Model Calibration ◽  
Model Performance ◽  
Spatial And Temporal Variability ◽  
Hydrological Models ◽  
New Approach ◽  
Perceptual Model ◽  
Spatially Distributed ◽  
Karst Systems

Abstract. In karst systems, surface near dissolution carbonate rock results in a high spatial and temporal variability of groundwater recharge. To adequately represent the dominating recharge processes in hydrological models is still a challenge, especially in data scare regions. In this study, we developed a recharge model that is based on a perceptual model of the epikarst. It represents epikarst heterogeneity as a set of system property distributions to produce not only a single recharge time series, but a variety of time series representing the spatial recharge variability. We tested the new model with a unique set of spatially distributed flow and tracer observations in a karstic cave at Mt. Carmel, Israel. We transformed the spatial variability into statistical variables and apply an iterative calibration strategy in which more and more data was added to the calibration. Thereby, we could show that the model is only able to produce realistic results when the information about the spatial variability of the observations was included into the model calibration. We could also show that tracer information improves the model performance if data about the variability is not included.

scholarly journals Representation of spatial and temporal variability in large-domain hydrological models: Case study for a mesoscale prealpine basin

2016 ◽  
Author(s):  
Lieke Melsen ◽  
Adriaan Teuling ◽  
Paul Torfs ◽  
Massimiliano Zappa ◽  
Naoki Mizukami ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Temporal Variability ◽  
Large Degree ◽  
Spatial And Temporal Variability ◽  
Hydrological Models ◽  
Infiltration Capacity ◽  
Large Domain ◽  
Modelling Studies ◽  
Temporal And Spatial ◽  
Set Up

Abstract. The transfer of parameter sets over different temporal and spatial resolutions is common practice in many large-domain hydrological modelling studies. The degree to which parameters are transferable across temporal and spatial resolutions is an indicator for how well spatial and temporal variability are represented in the models. A large degree of transferability may well indicate a poor representation of such variability in the employed models. To investigate parameter transferability over resolution in time and space we have set-up a study in which the Variable Infiltration Capacity (VIC) model for the Thur basin in Switzerland was run with four different spatial resolutions (1×1 km, 5×5 km, 10×10 km, lumped) and evaluated for three relevant temporal resolutions (hour, day, month), both applied with uniform and distributed forcing. The model was run 3,150 times using a Hierarchical Latin Hypercube Sample and the best 1 % of the runs was selected as behavioural. The overlap in behavioural sets for different spatial and temporal resolutions was used as indicator for parameter transferability. A key result from this study is that the overlap in parameter sets for different spatial resolutions was much larger than for different temporal resolutions, also when the forcing was applied in a distributed fashion. This result suggests that it is easier to transfer parameters across different spatial resolutions than across different temporal resolutions. However, the result also indicates a substantial underestimation in the spatial variability represented in the hydrological simulations, suggesting that the high spatial transferability may occur because the current generation of large-domain models have an inadequate representation of spatial variability and hydrologic connectivity. The results presented in this paper provide a strong motivation to further investigate and substantially improve the representation of spatial and temporal variability in large-domain hydrological models.

scholarly journals Representation of spatial and temporal variability in large-domain hydrological models: case study for a mesoscale pre-Alpine basin

2016 ◽  
Vol 20 (6) ◽  
pp. 2207-2226 ◽  
Author(s):  
Lieke Melsen ◽  
Adriaan Teuling ◽  
Paul Torfs ◽  
Massimiliano Zappa ◽  
Naoki Mizukami ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Temporal Variability ◽  
Large Degree ◽  
Spatial And Temporal Variability ◽  
Hydrological Models ◽  
Infiltration Capacity ◽  
Large Domain ◽  
Modelling Studies ◽  
Temporal And Spatial ◽  
Set Up

Abstract. The transfer of parameter sets over different temporal and spatial resolutions is common practice in many large-domain hydrological modelling studies. The degree to which parameters are transferable across temporal and spatial resolutions is an indicator of how well spatial and temporal variability is represented in the models. A large degree of transferability may well indicate a poor representation of such variability in the employed models. To investigate parameter transferability over resolution in time and space we have set up a study in which the Variable Infiltration Capacity (VIC) model for the Thur basin in Switzerland was run with four different spatial resolutions (1 km  ×  1 km, 5 km  ×  5 km, 10 km  ×  10 km, lumped) and evaluated for three relevant temporal resolutions (hour, day, month), both applied with uniform and distributed forcing. The model was run 3150 times using the Hierarchical Latin Hypercube Sample and the best 1 % of the runs was selected as behavioural. The overlap in behavioural sets for different spatial and temporal resolutions was used as an indicator of parameter transferability. A key result from this study is that the overlap in parameter sets for different spatial resolutions was much larger than for different temporal resolutions, also when the forcing was applied in a distributed fashion. This result suggests that it is easier to transfer parameters across different spatial resolutions than across different temporal resolutions. However, the result also indicates a substantial underestimation in the spatial variability represented in the hydrological simulations, suggesting that the high spatial transferability may occur because the current generation of large-domain models has an inadequate representation of spatial variability and hydrologic connectivity. The results presented in this paper provide a strong motivation to further investigate and substantially improve the representation of spatial and temporal variability in large-domain hydrological models.

scholarly journals Multiscale observations of NH<sub>3</sub> around Toronto, Canada

2021 ◽  
Vol 14 (2) ◽  
pp. 905-921
Author(s):  
Shoma Yamanouchi ◽  
Camille Viatte ◽  
Kimberly Strong ◽  
Erik Lutsch ◽  
Dylan B. A. Jones ◽  
...  
Keyword(s):  
Temporal Variability ◽  
Grid Point ◽  
Regional Scale ◽  
Model Performance ◽  
In Situ Measurements ◽  
Coefficient Of Determination ◽  
Spatial And Temporal Variability ◽  
Predictive Capacity ◽  
Total Column

Abstract. Ammonia (NH3) is a major source of nitrates in the atmosphere and a major source of fine particulate matter. As such, there have been increasing efforts to measure the atmospheric abundance of NH3 and its spatial and temporal variability. In this study, long-term measurements of NH3 derived from multiscale datasets are examined. These NH3 datasets include 16 years of total column measurements using Fourier transform infrared (FTIR) spectroscopy, 3 years of surface in situ measurements, and 10 years of total column measurements from the Infrared Atmospheric Sounding Interferometer (IASI). The datasets were used to quantify NH3 temporal variability over Toronto, Canada. The multiscale datasets were also compared to assess the representativeness of the FTIR measurements. All three time series showed positive trends in NH3 over Toronto: 3.34 ± 0.89 %/yr from 2002 to 2018 in the FTIR columns, 8.88 ± 5.08 %/yr from 2013 to 2017 in the surface in situ data, and 8.38 ± 1.54 %/yr from 2008 to 2018 in the IASI columns. To assess the representative scale of the FTIR NH3 columns, correlations between the datasets were examined. The best correlation between FTIR and IASI was obtained with coincidence criteria of ≤25 km and ≤20 min, with r=0.73 and a slope of 1.14 ± 0.06. Additionally, FTIR column and in situ measurements were standardized and correlated. Comparison of 24 d averages and monthly averages resulted in correlation coefficients of r=0.72 and r=0.75, respectively, although correlation without averaging to reduce high-frequency variability led to a poorer correlation, with r=0.39. The GEOS-Chem model, run at 2∘ × 2.5∘ resolution, was compared to FTIR and IASI to assess model performance and investigate the correlation of observational data and model output, both with local column measurements (FTIR) and measurements on a regional scale (IASI). Comparisons on a regional scale (a domain spanning 35 to 53∘ N and 93.75 to 63.75∘ W) resulted in r=0.57 and thus a coefficient of determination, which is indicative of the predictive capacity of the model, of r2=0.33, but comparing a single model grid point against the FTIR resulted in a poorer correlation, with r2=0.13, indicating that a finer spatial resolution is needed for modeling NH3.

scholarly journals A hydrochemical modelling framework for combined assessment of spatial and temporal variability in stream chemistry: application to Plynlimon, Wales

2001 ◽  
Vol 5 (1) ◽  
pp. 49-58 ◽  
Author(s):  
H.J. Foster ◽  
M.J. Lees ◽  
H.S. Wheater ◽  
C. Neal ◽  
B. Reynolds
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Spatial Variability ◽  
Temporal Variability ◽  
Biological Diversity ◽  
Spatial And Temporal Variability ◽  
Stream Chemistry ◽  
Two Component ◽  
End Members

Abstract. Recent concern about the risk to biota from acidification in upland areas, due to air pollution and land-use change (such as the planting of coniferous forests), has generated a need to model catchment hydro-chemistry to assess environmental risk and define protection strategies. Previous approaches have tended to concentrate on quantifying either spatial variability at a regional scale or temporal variability at a given location. However, to protect biota from ‘acid episodes’, an assessment of both temporal and spatial variability of stream chemistry is required at a catchment scale. In addition, quantification of temporal variability needs to represent both episodic event response and long term variability caused by deposition and/or land-use change. Both spatial and temporal variability in streamwater chemistry are considered in a new modelling methodology based on application to the Plynlimon catchments, central Wales. A two-component End-Member Mixing Analysis (EMMA) is used whereby low and high flow chemistry are taken to represent ‘groundwater’ and ‘soil water’ end-members. The conventional EMMA method is extended to incorporate spatial variability in the two end-members across the catchments by quantifying the Acid Neutralisation Capacity (ANC) of each in terms of a statistical distribution. These are then input as stochastic variables to a two-component mixing model, thereby accounting for variability of ANC both spatially and temporally. The model is coupled to a long-term acidification model (MAGIC) to predict the evolution of the end members and, hence, the response to future scenarios. The results can be plotted as a function of time and space, which enables better assessment of the likely effects of pollution deposition or land-use changes in the future on the stream chemistry than current methods which use catchment average values. The model is also a useful basis for further research into linkage between hydrochemistry and intra-catchment biological diversity. Keywords: hydrochemistry, End-Member Mixing Analysis (EMMA), uplands, acidification

scholarly journals Analyzing spatial and temporal variability in short-term rates of post-fire vegetation return from Landsat time series

2018 ◽  
Vol 205 ◽  
pp. 32-45 ◽  
Author(s):  
Ryan J. Frazier ◽  
Nicholas C. Coops ◽  
Michael A. Wulder ◽  
Txomin Hermosilla ◽  
Joanne C. White
Keyword(s):  
Time Series ◽  
Temporal Variability ◽  
Spatial And Temporal Variability ◽  
Short Term

scholarly journals Analysis of Long-Term Solar Resource Variability Using NSRDB Version 3

2021 ◽  
Author(s):  
Manajit Sengupta ◽  
Aron Habte
Keyword(s):  
Solar Radiation ◽  
Spatial Variability ◽  
Temporal Variability ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Spatial And Temporal Variability ◽  
Cloud Optical Depth ◽  
Resource Variability ◽  
Solar Resource

&lt;p&gt;Understanding long-term solar resource variability is essential for planning and deployment of solar energy systems. These variabilities occur due to deterministic effects such as sun cycle and nondeterministic such as complex weather patterns. The NREL&amp;#8217;s National Solar Radiation Database (NSRDB) provides long term solar resource data covering 1998- 2019 containing more than 2 million pixels over the Americas and gets updated on an annual basis. This dataset is satellite-based and uses a two-step physical model for it&amp;#8217;s development. In the first step we retrieve cloud properties such as cloud mask, cloud type, cloud optical depth and effective radius. The second step uses a fast radiative transfer model to compute solar radiation. &amp;#160;This dataset is ideal for studying solar resource variability. For this study, NSRDB version 3 which contains data from 1998-2017 on a half hourly and 4x4 km temporal and spatial resolution was used. The study analyzed the spatial and temporal trend of solar resource of global horizontal irradiance (GHI) and direct normal irradiance (DNI) using long-term 20-years NSRDB data. The coefficient of variation (COV) was used to analyze the spatio-temporal interannual and seasonal variabilities. The spatial variability was analyzed by comparing the center pixel to neighboring pixels. The spatial variability result showed higher COV as the number of neighboring pixels increased. Similarly, the temporal variability for the NSRDB domain ranges on average from &amp;#177;10% for GHI and &amp;#177;20% for DNI. Furthermore, the long-term variabilities were also analyzed using the K&amp;#246;ppen-Geiger climate classification. This assisted in the interpretation of the result by reducing the originally large number of pixels into a smaller number of groups. This presentation will provided a unique look at long-term spatial and temporal variability of solar radiation using high-resolution satellite-based datasets.&lt;/p&gt;

scholarly journals Approaches to evaluate spatial and temporal variability of deep marine sediment characteristics under the impact of dense water formation events

2020 ◽  
Author(s):  
XAVIER DURRIEU de MADRON ◽  
MARION STABHOLZ ◽  
LARS-ERIC HEIMBÜRGER-BOAVIDA ◽  
DOMINIQUE AUBERT ◽  
PHILIPPE KERHERVÉ ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Temporal Variability ◽  
Small Scale ◽  
Spatial And Temporal Variability ◽  
Geochemical Composition ◽  
Dense Water ◽  
Water Formation ◽  
Dense Water Formation ◽  
Northwestern Mediterranean Sea ◽  
The Impact

Dense shelf water cascading and open-ocean convection frequently occurs in the Gulf of Lions, northwestern Mediterranean Sea. These intense dense water formation events are capable of supplying large amounts of particulate matter as well as remobilizing and dispersing local sediments and, therefore, are thought to leave an imprint on superficial deposits. Here, we compared the spatial variability of the superficial sediment composition (grain size, organic parameters, and metals) at different scales (from decimetric to kilometric) on the continental slope and rise with the temporal variability linked to the occurrence of intense dense water formation events. The spatial and temporal variability of the geochemical composition of deep sediments was assessed using multivariate and geostatistical analysis. The results indicate that, on the outer reach of the Cap de Creus Canyon, where both processes interact, no clear relation was found between the temporal variability of the superficial sediment and the deep-water formation events, and that the small-scale spatial variability of the sediment is masking the temporal variability. Measurements across the southern slope indicate the presence of a somehow distinct geochemical signature that likely results from the influence of recurrent intense, dense water formation events as well as an unabating bottom trawling activity.

scholarly journals Variación espacio-temporal del vapor de agua precipitable (PWV) en la costa norte del Perú para el periodo 2001-2017

2018 ◽  
pp. 102-108
Keyword(s):  
Time Series ◽  
Water Vapor ◽  
Temporal Variability ◽  
Extreme Values ◽  
Power Spectral Analysis ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Spatial And Temporal Variability ◽  
Northern Coast ◽  
San Marcos

Variación espacio-temporal del vapor de agua precipitable (PWV) en la costa norte del Perú para el periodo 2001-2017  Jhon Brayan Guerrero Salinas, Rolando Renee Badaracco Meza, Joel Rojas Acuña Universidad Nacional Mayor de San Marcos, Ap. Postal 14-0149, Lima, Perú Recibido 11 de octubre del 2018, Revisado el 7 de diciembre de 2018. Aceptado el 12 de diciembre de 2018 DOI: https://doi.org/10.33017/RevECIPeru2018.0016/ Resumen El objetivo de este estudio fue realizar el análisis de la variabilidad espacial y temporal de la columna de vapor de agua precipitable (PWV, por sus siglas en inglés) en la costa norte del Perú (3°S-7°S). Se analizaron un total de 17 años de datos PWV obtenidas del sensor MODIS/Terra, de las cuales se generaron mapas de climatología provisional y de desviación estándar, para así obtener los patrones de distribución espacial promedio y variabilidad temporal. El mapa climatológico provisional de PWV muestra en general que las zonas de mayor variabilidad de PWV se encuentran en el océano y tierras bajas, mientras que las zonas de menor variabilidad se encuentran en la región de los Andes. Los diagramas de Hovmöller y la serie de tiempo identificaron un ciclo anual y el aumento de los valores extremos en los meses de verano a partir del año 2010. El análisis espectral de potencia de la serie de tiempo aparte de identificar el periodo anual también identifica un periodo semianual que se debe al cambio estacional verano-invierno. Descriptores: Vapor de agua precipitable, Costa norte, MODIS/TERRA, Hovmöller. Abstract The objective of this study was to perform the analysis of the spatial and temporal variability of the precipitable water vapor column (PWV) on the northern coast of Peru (3°S-7°S). A total of 17 years of PWV data obtained from the MODIS/Terra sensor were analyzed, from which maps of provisional climatology and standard deviation were generated, in order to obtain the patterns of average spatial distribution and temporal variability. The provisional climatological map of PWV shows in general that the areas with the greatest variability of PWV are found in the ocean and lowlands, while the areas of least variability are found in the Andes region. The Hovmöller diagrams and the time series identified an annual cycle and the increase of the extreme values in the summer months from the year 2010. The power spectral analysis of the time series apart from identifying the annual period also identifies a period semiannual that is due to the seasonal change summer-winter. Keywords: Precipitable water vapor, Northern coast, MODIS/TERRA, Hovmöller.

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