Long-Term Yields From Individual Plots: Implications for Managing Spatial Variability

2015 ◽  
pp. 541-552
Author(s):  
Paul M. Porter ◽  
David R. Huggins ◽  
Catherine A. Perillo ◽  
Joseph G. Lauer ◽  
Edward S. Oplinger ◽  
...  
Keyword(s):  
Spatial Variability

scholarly journals Climatological and statistical characteristics of the Haines Index for North America

2007 ◽  
Vol 16 (2) ◽  
pp. 139 ◽  
Author(s):  
Julie A. Winkler ◽  
Brian E. Potter ◽  
Dwight F. Wilhelm ◽  
Ryan P. Shadbolt ◽  
Krerk Piromsopa ◽  
...  
Keyword(s):  
North America ◽  
Spatial Variability ◽  
Atmospheric Pressure ◽  
Statistical Characteristics ◽  
Potential Contribution ◽  
Extensive Analysis ◽  
Temperature And Humidity ◽  
Humidity Measurements ◽  
Operational Tool

The Haines Index is an operational tool for evaluating the potential contribution of dry, unstable air to the development of large or erratic plume-dominated wildfires. The index has three variants related to surface elevation, and is calculated from temperature and humidity measurements at atmospheric pressure levels. To effectively use the Haines Index, fire forecasters and managers must be aware of the climatological and statistical characteristics of the index for their location. However, a detailed, long-term, and spatially extensive analysis of the index does not currently exist. To meet this need, a 40-year (1961–2000) climatology of the Haines Index was developed for North America. The climatology is based on gridded (2.5° latitude × 2.5° longitude) temperature and humidity fields from the NCEP/NCAR reanalysis. The climatology illustrates the large spatial variability in the Haines Index both within and between regions using the different index variants. These spatial variations point to the limitations of the index and must be taken into account when using the Haines Index operationally.

Using hillslope-scale groundwater model to bridge the gap between basin inputs and river concentrations. The case of nitrates in Brittany (France).

2021 ◽  
Author(s):  
Luca Guillaumot ◽  
Luc Aquilina ◽  
Jean-Raynald de Dreuzy ◽  
Jean Marçais ◽  
Patrick Durand
Keyword(s):  
Spatial Variability ◽  
Groundwater Resources ◽  
Residence Times ◽  
Groundwater Model ◽  
Nitrogen Inputs ◽  
Nitrate Concentrations ◽  
Physically Based ◽  
Nutrient Surplus ◽  
Hillslope Scale

<p>Over the past decades, intensive agriculture has altered surface water and groundwater resources quality. Nutrient surplus increased nitrate concentrations in groundwater and rivers resulting in eutrophication or drinking water risk having ecosystem, sanitary and economic repercussions. Legislations led to a reduction of agricultural inputs of nitrogen since 1990’s followed by a decrease of nitrate concentrations in rivers, but still difficult to predict and evaluate. Indeed, the incomplete knowledge of the spatial variability of climate and nitrogen inputs, cumulated to the unknown groundwater heterogeneity,  leads to hydrological and biogeochemical processes difficult to model. This study deals with the long-term variations (~decades) of nitrate concentrations in three rivers (~30 km² catchment) located in Brittany. Thus, we focus on groundwater modelling because they constitute the bigger hydrological reservoir. We developed a parsimonious equivalent hillslope-scale groundwater model. The model parameterization, which controls hydrological functioning such as mean groundwater residence times, young water contribution to the river or denitrification, relies on long-term monitored streamflow and nitrate river concentrations. In addition, dissolved CFC were sampled in the catchments. Finally, we found that uncertainty on simulated nitrate river concentrations is low. The physically-based model also brings information on temporal and spatial variability of groundwater residence times highlighting the relative importance of young (1-5 yr) and old waters (~decades) for nitrate river concentrations. Moreover, calibrated models show similar trends looking at two fictive input scenarios from 2015 to 2050.</p>

scholarly journals Effects of Fire and Large Herbivores on Canopy Nitrogen in a Tallgrass Prairie

2019 ◽  
Vol 11 (11) ◽  
pp. 1364 ◽  
Author(s):  
Bohua Ling ◽  
Edward J. Raynor ◽  
Douglas G. Goodin ◽  
Anthony Joern
Keyword(s):  
Spatial Variability ◽  
Nitrogen Content ◽  
Tallgrass Prairie ◽  
High Nitrogen Content ◽  
High Nitrogen ◽  
Grazing History ◽  
One Year ◽  
Canopy Nitrogen

This study analyzed the spatial heterogeneity of grassland canopy nitrogen in a tallgrass prairie with different treatments of fire and ungulate grazing (long-term bison grazing vs. recent cattle grazing). Variogram analysis was applied to continuous remotely sensed canopy nitrogen images to examine the spatial variability in grassland canopies. Heterogeneity metrics (e.g., the interspersion/juxtaposition index) were calculated from the categorical canopy nitrogen maps and compared among fire and grazing treatments. Results showed that watersheds burned within one year had higher canopy nitrogen content and lower interspersions of high-nitrogen content patches than watersheds with longer fire intervals, suggesting an immediate and transient fire effect on grassland vegetation. In watersheds burned within one year, high-intensity grazing reduced vegetation density, but promoted grassland heterogeneity, as indicated by lower canopy nitrogen concentrations and greater interspersions of high-nitrogen content patches at the grazed sites than at the ungrazed sites. Variogram analyses across watersheds with different grazing histories showed that long-term bison grazing created greater spatial variability of canopy nitrogen than recent grazing by cattle. This comparison between bison and cattle is novel, as few field experiments have evaluated the role of grazing history in driving grassland heterogeneity. Our analyses extend previous research of effects from pyric herbivory on grassland heterogeneity by highlighting the role of grazing history in modulating the spatial and temporal distribution of aboveground nitrogen content in tallgrass prairie vegetation using a remote sensing approach. The comparison of canopy nitrogen properties and the variogram analysis of canopy nitrogen distribution provided by our study are useful for further mapping grassland canopy features and modeling grassland dynamics involving interplays among fire, large grazers, and vegetation communities.

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

A Comparison of Daily Temperature-Averaging Methods: Spatial Variability and Recent Change for the CONUS

2018 ◽  
Vol 31 (3) ◽  
pp. 979-996 ◽  
Author(s):  
Jase Bernhardt ◽  
Andrew M. Carleton ◽  
Chris LaMagna
Keyword(s):  
Spatial Variability ◽  
Daily Temperature ◽  
Maximum Temperature ◽  
Underlying Assumption ◽  
First Order ◽  
Daily Average ◽  
Hourly Temperature ◽  
Significant Difference ◽  
Weather Stations

Abstract Traditionally, the daily average air temperature at a weather station is computed by taking the mean of two values, the maximum temperature (Tmax) and the minimum temperature (Tmin), over a 24-h period. These values form the basis for numerous studies of long-term climatologies (e.g., 30-yr normals) and recent temperature trends and changes. However, many first-order weather stations—such as those at airports—also record hourly temperature data. Using an average of the 24 hourly temperature readings to compute daily average temperature has been shown to provide a more precise and representative estimate of a given day’s temperature. This study assesses the spatial variability of the differences in these two methods of daily temperature averaging [i.e., (Tmax + Tmin)/2; average of 24 hourly temperature values] for 215 first-order weather stations across the conterminous United States (CONUS) over the 30-yr period 1981–2010. A statistically significant difference is shown between the two methods, as well as consistent overestimation of temperature by the traditional method [(Tmax + Tmin)/2], particularly in southern and coastal portions of the CONUS. The explanation for the long-term difference between the two methods is the underlying assumption for the twice-daily method that the diurnal curve of temperature is symmetrical. Moreover, this paper demonstrates a spatially coherent pattern in the difference compared to the most recent part of the temperature record (2001–15). The spatial and temporal differences shown have implications for assessments of the physical factors influencing the diurnal temperature curve, as well as the exact magnitude of contemporary climate change.

Temporal and Spatial Variability and Trend Investigation of Total Ozone Column over Iraq Employing Remote Sensing Data: 1979-2012

2015 ◽  
Vol 53 ◽  
pp. 1-18
Author(s):  
Ali M. Al-Salihi ◽  
Zehraa M. Hassan
Keyword(s):  
Remote Sensing ◽  
Spatial Variability ◽  
Total Ozone ◽  
Positive Trend ◽  
Climate Change Research ◽  
Total Ozone Column ◽  
Temporal And Spatial Variability ◽  
Temporal And Spatial ◽  
Ozone Column

The objective of this paper is to analyze the temporal and spatial variability of the total ozone column (TOC) distributions and trends over Iraq, during the last 30 years (1979–2012) using remote sensing-derived TOC data. Due to shortage of ground-based TOC measurements. TOC data derived from the Total Ozone Mapping Spectrometer (TOMS) for the period 1979–2004 and Ozone Monitoring Instrument (OMI) for the period 2005–2012 with spatial resolution (1o×1o) were used in present study. The spatial, long-term, monthly variations of TOC over Iraq were analysed. For the spatial variability, the latitudinal variability has a large range between (45 to 55) DU in winter and spring whereas during summer and autumn months ranged between (6 to 10) DU. Also represents an annual cycle with maximum in March and minimum in October. In contrast, the longitudinal variability is not significant. The long-term variability represented a notable decline for the period 1979–2012. The ozone negative trend was observed significantly during 1979–2004, for all months with trend ranged between (− 0.3 to 2) DU/year whereas the ozone positive trend was appear clearly during 2005–2007, for all months (0.1 to 2.3) DU/year ,except February and September which presented negative trends. The results can provide comprehensive descriptions of the TOC variations in Iraq and benefit climate change research in this region.

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