scholarly journals Comparative analysis of hydrologic signatures in two agricultural watersheds in east-central Illinois: legacies of the past to inform the future

2013 ◽  
Vol 17 (11) ◽  
pp. 4607-4623 ◽  
Author(s):  
M. A. Yaeger ◽  
M. Sivapalan ◽  
G. F. McIsaac ◽  
X. Cai
Keyword(s):  
Land Use ◽  
Comparative Analysis ◽  
Time Series Data ◽  
Past History ◽  
Series Data ◽  
Agricultural System ◽  
Current Response ◽  
Geologic History ◽  
The Past ◽  
Central Illinois

Abstract. Historically, the central Midwestern US has undergone drastic anthropogenic land use change, having been transformed, in part through government policy, from a natural grassland system to an artificially drained agricultural system devoted to row cropping corn and soybeans. Current federal policies are again influencing land use in this region with increased corn acreage and new biomass crops proposed as part of an energy initiative emphasizing biofuels. To better address these present and future challenges it is helpful to understand whether and how the legacies of past changes have shaped the current response of the system. To this end, a comparative analysis of the hydrologic signatures in both spatial and time series data from two central Illinois watersheds was undertaken. The past history of these catchments is reflected in their current hydrologic responses, which are highly heterogeneous due to differences in geologic history, artificial drainage patterns, and reservoir operation, and manifest temporally, from annual to daily timescales, and spatially, both within and between the watersheds. These differences are also apparent from analysis of the summer low flows, where the more tile-drained watershed shows greater variability overall than does the more naturally drained one. In addition, precipitation in this region is also spatially heterogeneous even at small scales, and this, interacting with and filtering through the historical modifications to the system, increases the complexity of the problem of predicting the catchment response to future changes.

scholarly journals Comparative analysis of hydrologic signatures in two agricultural watersheds in east-central Illinois: legacies of the past to inform the future

2013 ◽  
Vol 10 (5) ◽  
pp. 6515-6558 ◽  
Author(s):  
M. A. Yaeger ◽  
M. Sivapalan ◽  
G. F. McIsaac ◽  
X. Cai
Keyword(s):  
Land Use ◽  
Comparative Analysis ◽  
Land Use Change ◽  
Low Flow ◽  
Series Data ◽  
Small Scale ◽  
Agricultural System ◽  
Current Response ◽  
The Past ◽  
Central Illinois

Abstract. Historically, the central Midwestern US has undergone drastic anthropogenic land use change, having been transformed, in part through federal government policy, from a natural grassland system to an artificially-drained agricultural system devoted to row cropping corn and soybeans. Current federal policies are again influencing land use change in this region with increased corn acreage and new biomass crops proposed as part of an energy initiative emphasizing biofuels. To better address these present and future challenges it is helpful to understand how the legacies of past changes have shaped the current response of the system. To this end, a comparative analysis of the hydrologic signatures in both spatial and time series data from two central Illinois watersheds was undertaken. The past history of these catchments is reflected in their current hydrologic responses, which are highly heterogeneous, more so in the extensively tile-drained Sangamon watershed. The differences in geologic history, artificial drainage patterns, and to some extent, reservoir construction, manifest at all time scales, from annual to daily, and spatially within the watersheds. These differences can also be seen in the summer low flow patterns, where the more tile-drained watershed shows more variability than does the more naturally drained one. Of interest is the scaling behavior of the low flows; generally as drainage area increases, small-scale heterogeneity decreases. This is not seen in the more tile-drained watershed, thus adding complexity to the problem of predicting the catchment response to future changes.

scholarly journals Polarimetric SAR Time-Series for Identification of Winter Land Use

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5574
Author(s):  
Julien Denize ◽  
Laurence Hubert-Moy ◽  
Eric Pottier
Keyword(s):  
Land Use ◽  
Time Series ◽  
Time Series Data ◽  
High Spatial Resolution ◽  
Synthetic Aperture ◽  
Series Data ◽  
Band Frequency ◽  
The Past ◽  
Land Use Types ◽  
L Band

In the past decade, high spatial resolution Synthetic Aperture Radar (SAR) sensors have provided information that contributed significantly to cropland monitoring. However, the specific configurations of SAR sensors (e.g., band frequency, polarization mode) used to identify land-use types remains underexplored. This study investigates the contribution of C/L-Band frequency, dual/quad polarization and the density of image time-series to winter land-use identification in an agricultural area of approximately 130 km² located in northwestern France. First, SAR parameters were derived from RADARSAT-2, Sentinel-1 and Advanced Land Observing Satellite 2 (ALOS-2) time-series, and one quad-pol and six dual-pol datasets with different spatial resolutions and densities were calculated. Then, land use was classified using the Random Forest algorithm with each of these seven SAR datasets to determine the most suitable SAR configuration for identifying winter land-use. Results highlighted that (i) the C-Band (F1-score 0.70) outperformed the L-Band (F1-score 0.57), (ii) quad polarization (F1-score 0.69) outperformed dual polarization (F1-score 0.59) and (iii) a dense Sentinel-1 time-series (F1-score 0.70) outperformed RADARSAT-2 and ALOS-2 time-series (F1-score 0.69 and 0.29, respectively). In addition, Shannon Entropy and SPAN were the SAR parameters most important for discriminating winter land-use. Thus, the results of this study emphasize the interest of using Sentinel-1 time-series data for identifying winter land-use.

Phosphorus and land-use changes are significant drivers of cladoceran community composition and diversity: an analysis over spatial and temporal scales

2010 ◽  
Vol 67 (8) ◽  
pp. 1262-1273 ◽  
Author(s):  
Marc Richard Albert ◽  
Guangjie Chen ◽  
Graham K. MacDonald ◽  
Jesse C. Vermaire ◽  
Elena M. Bennett ◽  
...  
Keyword(s):  
Land Use ◽  
Community Composition ◽  
Time Series Data ◽  
Temporal Analysis ◽  
Phosphorus Loading ◽  
Series Data ◽  
Phosphorus Concentration ◽  
Total Phosphorus Concentration ◽  
Watershed Disturbance ◽  
Subfossil Cladoceran

We conducted paleolimnological studies over spatial and temporal gradients to define the responses of subfossil cladoceran community composition and diversity to changes in land use and phosphorus concentrations in shallow lakes. We predicted that watershed disturbance by humans, through its impact on water quality, would explain significant variation in cladoceran diversity and composition. Across lakes, water-column total phosphorus concentration was a significant (p < 0.05) predictor of the subfossil cladoceran community composition. Chydorid diversity was also found to be related significantly to phosphorus concentration (r = –0.55, p < 0.05) and the proportion of disturbed land in the watershed (r = –0.47, p < 0.05). However, net load of phosphorus to the watershed rather than proportion of watershed disturbance was a significant predictor of chydorid diversity (r = –0.86, p < 0.001) in our temporal analysis of an eutrophying lake. Given that phosphorus loading to surface waters is often related to phosphorus concentrations in soils, we suggest that the net phosphorus load to the watershed is a more sensitive metric of land-use change and necessary for detecting ecological responses in time series data.

scholarly journals The Forecast of the Number of Soldiers in the Saudi Arabian Army in Terms of Military Security

2021 ◽  
Vol 50 ◽  
pp. 1-10
Author(s):  
Bartosz Kozicki ◽  
◽  
Jarosław Zelkowski ◽  
Szymon Mitkow ◽  
Mariusz Gontarczyk ◽  
...  
Keyword(s):  
Saudi Arabia ◽  
Comparative Analysis ◽  
Time Series Data ◽  
Saudi Arabian ◽  
Series Data ◽  
Middle East Countries ◽  
Military Security ◽  
Time Series Data Analysis ◽  
Klein’S Model ◽  
The Impact

The study concerns forecasting the number of soldiers in the Saudi Arabian army based on information obtained from the website: https://data.worldbank.org (The World Bank, 9.03.2020). The research began with a comparative analysis of the number of soldiers in the armies of Saudi Arabia and Russia. The idea for a comparative analysis of the number of armies of Saudi Arabia and the Russian Federation arises from Russian policy in the region of the Middle East countries, including the impact on world oil prices. The comparative analysis showed the similarities and differences in the dynamics of changes in the number of both armies dynamically. Subsequently, the primary time series data analysis on the number of Saudi Arabian troops was performed. The study selected methods for predicting raw data: Holt’s exponential smoothing and Klein’s model for the future. The next stage of the research was forecasting and the analysis and evaluation of the obtained forecasts. Klein’s model was the best forecasting model. The forecast of the number of soldiers in the Saudi Arabian army for 2020 is 251454, and for 2021, it has increased to 251006. The study ends with a summary and conclusions.

scholarly journals Population Pressure on Land Resources in Nigeria: The Past and Projected Outcome

2020 ◽  
pp. 20-34
Author(s):  
H. I. Eririogu ◽  
R. N. Echebiri ◽  
E. S. Ebukiba
Keyword(s):  
Carrying Capacity ◽  
Time Series Data ◽  
Arable Land ◽  
Population Pressure ◽  
Series Data ◽  
Land Resources ◽  
Exploration And Exploitation ◽  
The Past ◽  
Land Consumption ◽  
Per Capita

Aims: This paper assesses the population pressure on land resources in Nigeria: The past and projected outcome. Study Design: 1967 to 2068 time series data were used. The data sets were resorted to due to lack of complete national data. Place and Duration of Study: Past (1967-2017) and projected (2018-2068) five decades in Nigeria. Methodology: The time series data were obtained from the United Nations Population Division, Department of Economic and Social Affairs, National Population Commission, International Energy Statistics and Food and Agriculture Organization (FAO) on population levels, renewable and non renewable resources in Nigeria. Others such as transformity were adapted from Odum (1996) and Odum (2000) for specific objectives. Data collected were analyzed using modified ecological footprint/carrying capacity approach, descriptive statistics and Z-statistics. Results: Results showed that the mean annual pressure on land resources in the past five decades (1967-2017) was 9.323 hectares per capita, while the projected pressure in the next five decades (2018-2068) was 213.178 hectares per capita. Results also showed that about 73.08 percent of the pressure per capita in the past five decades emanated from arable land consumption (6.813ha), while 75.91percent of the pressure is expected to emanate from fossil land in the next projected five decades due to crude oil and mineral resource exploration and exploitation. The carrying capacity of land resources in the past five decades was 6.4091 hectares per capita, while that of the projected five decades was 1.667 hectares per capita, an indication of ecological overshoot in both periods. Conclusion: Population pressures on land resources per capita in the past and projected five decades are higher than the carrying capacity of these resources in the country. Citizens lived and are expected to live unsustainably by depleting and degrading available land resources. Arable land consumption is the major contributor to the total pressure on land resources in the past five decades, while the consumption of fossil land due to exploration and exploitation of crude oil and mineral resources is expected to contribute majorly to the total pressure on land resources in the next five decades. Limiting affluence (per capita consumption of resources) and improving technology will not only ensure sustainable use of arable and fossil lands but place consumption within the limits of these resources for a sustainable future.

scholarly journals Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine

2020 ◽  
Vol 12 (17) ◽  
pp. 2735 ◽  
Author(s):  
Carlos M. Souza ◽  
Julia Z. Shimbo ◽  
Marcos R. Rosa ◽  
Leandro L. Parente ◽  
Ane A. Alencar ◽  
...  
Keyword(s):  
Land Use ◽  
Time Series ◽  
Land Cover ◽  
Time Series Data ◽  
Google Earth ◽  
Series Data ◽  
Data Series ◽  
Forest Conversion ◽  
Pixel Resolution ◽  
Historical Land Use

Brazil has a monitoring system to track annual forest conversion in the Amazon and most recently to monitor the Cerrado biome. However, there is still a gap of annual land use and land cover (LULC) information in all Brazilian biomes in the country. Existing countrywide efforts to map land use and land cover lack regularly updates and high spatial resolution time-series data to better understand historical land use and land cover dynamics, and the subsequent impacts in the country biomes. In this study, we described a novel approach and the results achieved by a multi-disciplinary network called MapBiomas to reconstruct annual land use and land cover information between 1985 and 2017 for Brazil, based on random forest applied to Landsat archive using Google Earth Engine. We mapped five major classes: forest, non-forest natural formation, farming, non-vegetated areas, and water. These classes were broken into two sub-classification levels leading to the most comprehensive and detailed mapping for the country at a 30 m pixel resolution. The average overall accuracy of the land use and land cover time-series, based on a stratified random sample of 75,000 pixel locations, was 89% ranging from 73 to 95% in the biomes. The 33 years of LULC change data series revealed that Brazil lost 71 Mha of natural vegetation, mostly to cattle ranching and agriculture activities. Pasture expanded by 46% from 1985 to 2017, and agriculture by 172%, mostly replacing old pasture fields. We also identified that 86 Mha of the converted native vegetation was undergoing some level of regrowth. Several applications of the MapBiomas dataset are underway, suggesting that reconstructing historical land use and land cover change maps is useful for advancing the science and to guide social, economic and environmental policy decision-making processes in Brazil.

scholarly journals Reconsidering the importance of the past in predator–prey models: both numerical and functional responses depend on delayed prey densities

2013 ◽  
Vol 280 (1768) ◽  
pp. 20131389 ◽  
Author(s):  
Jiqiu Li ◽  
Andy Fenton ◽  
Lee Kettley ◽  
Phillip Roberts ◽  
David J. S. Montagnes
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Prey Abundance ◽  
Series Data ◽  
Functional Responses ◽  
New Approach ◽  
Predator Prey ◽  
The Past ◽  
Predator Prey Models ◽  
Underlying Mechanisms

We propose that delayed predator–prey models may provide superficially acceptable predictions for spurious reasons. Through experimentation and modelling, we offer a new approach: using a model experimental predator–prey system (the ciliates Didinium and Paramecium ), we determine the influence of past-prey abundance at a fixed delay (approx. one generation) on both functional and numerical responses (i.e. the influence of present : past-prey abundance on ingestion and growth, respectively). We reveal a nonlinear influence of past-prey abundance on both responses, with the two responding differently. Including these responses in a model indicated that delay in the numerical response drives population oscillations, supporting the accepted (but untested) notion that reproduction, not feeding, is highly dependent on the past. We next indicate how delays impact short- and long-term population dynamics. Critically, we show that although superficially the standard (parsimonious) approach to modelling can reasonably fit independently obtained time-series data, it does so by relying on biologically unrealistic parameter values. By contrast, including our fully parametrized delayed density dependence provides a better fit, offering insights into underlying mechanisms. We therefore present a new approach to explore time-series data and a revised framework for further theoretical studies.

scholarly journals WHICH VARIABLES PREDICT INDONESIA'S INFLATION?

2019 ◽  
Vol 22 (1) ◽  
pp. 87-102 ◽  
Author(s):  
Susan Sunila Sharma
Keyword(s):  
Time Series ◽  
Comparative Analysis ◽  
Inflation Rate ◽  
Time Series Data ◽  
Predictor Variables ◽  
Series Data ◽  
Macroeconomic Variables ◽  
Monthly Time Series ◽  
Out Of Sample ◽  
Exhaustive List

We use an exhaustive list of Indonesia’s macroeconomic variables in a comparative analysis to determine which predictor variables are most important in forecasting Indonesia’s inflation rate. We use monthly time-series data for 30 macroeconomic variables. Using both in-sample and out-of-sample predictability evaluations, we report consistent evidence of inflation rate predictability using 11 out of 30 macroeconomic variables.

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