scholarly journals Long-term Soil Moisture Time Series Analyses based on Active Microwave Backscatter Measurements

2015 ◽  
Vol XL-7/W3 ◽  
pp. 545-550
Author(s):  
W. Wagner ◽  
C. Reimer ◽  
B. Bauer-Marschallinger ◽  
M. Enenkel ◽  
S. Hahn ◽  
...  
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Microwave Frequencies ◽  
Vegetation Modelling ◽  
Time Series Analyses ◽  
Vegetation Parameters ◽  
Microwave Backscatter ◽  
Microwave Sensors ◽  
Modelling Approach

Active microwave sensors operating at lower microwave frequencies in the range from 1 to 10 GHz provide backscatter measurements that are sensitive to the moisture content of the soil. Thanks to a series of European C-band (5.3 GHz) scatterometers, which were first flown on board of the European Remote Sensing satellites ERS-1 and ERS-2, and later on board of MetOp-A and MetOp -B, we are now in the possession of a long-term soil moisture time series starting in 1991. The creation of globally consistent long-term soil moisture time series is a challenging task. The TU-Wien soil moisture algorithm is adopted to tackle these challenges. In this paper we present two methodologies that were developed to ensure radiometric stability of the European C-band scatterometers. The objective of sensor intra-calibration is to monitor and correct for radiometric instabilities within one scatterometer mission, while sensor inter-calibration aims to remove radiometric differences across several missions. In addition, a novel vegetation modelling approach is presented that enables the estimation of vegetation parameters for each day across several years to account for yearly to longer-term changes in vegetation phenology and land cover.

Availability and Sales of Alcohol in Four Canadian Provinces: A Time-Series Analysis

2005 ◽  
Vol 32 (3) ◽  
pp. 343-372 ◽  
Author(s):  
Björn Trolldal
Keyword(s):  
Time Series ◽  
Research Question ◽  
Pure Alcohol ◽  
Dependent Variables ◽  
Long Term Trends ◽  
Time Series Analyses ◽  
Canadian Provinces ◽  
Physical Availability ◽  
Total Sales

The research question addressed in the present study, with ARIMA time-series analyses, was the extent to which changes in economic and physical availability had an effect on sales of alcohol in four Canadian provinces during the second half of the 20th century. The annual sales, by type of beverage (spirits, wine and beer) as well as total sales, measured in pure alcohol per inhabitant age 15 and above in each province, were used as dependent variables in the analyses. The inhabitants' real disposable income, the real price of alcohol, and the number of on- and off-premise outlets per 100,000 inhabitants were used as independent variables. All the time-series were differenced to remove long-term trends. The main study period was 1951–2000. In some of the analyses the study periods were shorter, primarily due to lack of data. Changes in economic availability in general, and in price in particular, had larger effects on sales than physical availability. Among the beverages analyzed in the study, the demand for spirits was most sensitive to changes in availability. Economic availability had a greater effect on sales than the number of outlets. However, one might question to what extent the number of outlets really is a feasible measure of transaction costs associated with purchases of alcohol.

scholarly journals Close co-variation between soil moisture and runoff emerging from multi-catchment data across Europe

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Navid Ghajarnia ◽  
Zahra Kalantari ◽  
René Orth ◽  
Georgia Destouni
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Large Scale ◽  
Temperature Anomaly ◽  
Important Variable ◽  
Climatic Variables ◽  
New Approach ◽  
European Climate ◽  
Moisture Conditions

AbstractSoil moisture is an important variable for land-climate and hydrological interactions. To investigate emergent large-scale, long-term interactions between soil moisture and other key hydro-climatic variables (precipitation, actual evapotranspiration, runoff, temperature), we analyze monthly values and anomalies of these variables in 1378 hydrological catchments across Europe over the period 1980–2010. The study distinguishes results for the main European climate regions, and tests how sensitive or robust they are to the use of three alternative observational and re-analysis datasets. Robustly across the European climates and datasets, monthly soil moisture anomalies correlate well with runoff anomalies, and extreme soil moisture and runoff values also largely co-occur. For precipitation, evapotranspiration, and temperature, anomaly correlation and extreme value co-occurrence with soil moisture are overall lower than for runoff. The runoff results indicate a possible new approach to assessing variability and change of large-scale soil moisture conditions by use of long-term time series of monitored catchment-integrating stream discharges.

On the influence of soil moisture on intra-annual peat soil dynamics as observed from SAR amplitude and phase data

2020 ◽  
Author(s):  
Falco Bentvelsen ◽  
Floris Heuff ◽  
Susan Steele-Dunne ◽  
Wolfgang Wagner ◽  
Raphael Quast ◽  
...  
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Surface Soil ◽  
Peat Soil ◽  
Soil Dynamics ◽  
Surface Elevation ◽  
Driving Mechanism ◽  
Surface Soil Moisture ◽  
Precipitation And Temperature

<p>Polders in the western Netherlands are often covered by pastures. Around 30 percent of the pastures are situated on peat soils, which are artificially drained. Consequently, the exposure to oxygen leads to a decomposition (oxidation) of the material and desiccation leading to shrinking. This results in a decadal subsidence, up to a few centimeters per year, which causes increasingly severe socio-economic impact. However, this long-term subsidence signal has a high spatial variability due to local soil morphology, and possibly high intra-annual temporal variability which is caused by precipitation and evaporation. The problem is that there are currently no geodetic methods that can reliably measure these soil dynamics over wide areas and with high temporal revisits.</p><p>Here we show how Sentinel-1 SAR interferometry (InSAR) can potentially be used to estimate the surface displacements, given prior information on precipitation and temperature. We observe intra-annual dynamics of surface elevation which seem to be one order of magnitude stronger than the decadal long-term subsidence. InSAR surface elevation measurements show  discontinuities (hysteresis) in late summer and early autumn due to strong vegetation and changes in temperature and precipitation patterns. As soil moisture variability appears to be the main driving mechanism for the observed surface elevation dynamics, we investigate whether we can use the amplitude of the identical SAR acquisitions to estimate the soil moisture directly, to reduce the dependency on external precipitation and temperature data.</p><p>The analysis is performed on time series of the European Space Agency’s Sentinel-1 mission. Subsidence and upheaval are estimated using a novel InSAR algorithm, which was specially designed for peat soil dynamics. The surface elevation dynamics are compared to surface soil moisture estimates from Sentinel-1 amplitude  data. Soil moisture is retrieved from backscatter time series using a first-order radiative transfer model (RT1) developed at TU Wien. This model describes the scattering behaviour of both soil- and vegetation by using linear combinations of idealized scattering distribution functions. Clay Soil swelling and subsidence are likely influenced by soil layers much deeper than those associated with the surface soil moisture estimates. Therefore, the subsidence estimates are also compared to Soil Water Index (SWI) derived from the surface soil moisture product. This is considered an indicator of moisture availability in the top 100 cm. These results show that the same complex SAR data acquisitions can be used simultaneously, but independently, for estimating soil moisture and for estimating surface elevation dynamics. An integrated application is proposed and evaluated for further exploration.</p>

scholarly journals The Role of Hydrological Signatures in Calibration of Conceptual Hydrological Model

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3401
Author(s):  
Eva Melišová ◽  
Adam Vizina ◽  
Linda R. Staponites ◽  
Martin Hanel
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Goodness Of Fit ◽  
Hydrological Model ◽  
Hydrological Models ◽  
Balance Assessment ◽  
The Czech Republic ◽  
Hydrological Signatures

Determining an optimal calibration strategy for hydrological models is essential for a robust and accurate water balance assessment, in particular, for catchments with limited observed data. In the present study, the hydrological model Bilan was used to simulate hydrological balance for 20 catchments throughout the Czech Republic during the period 1981–2016. Calibration strategies utilizing observed runoff and estimated soil moisture time series were compared with those using only long-term statistics (signatures) of runoff and soil moisture as well as a combination of signatures and time series. Calibration strategies were evaluated considering the goodness-of-fit, the bias in flow duration curve and runoff signatures and uncertainty of the Bilan model. Results indicate that the expert calibration and calibration with observed runoff time series are, in general, preferred. On the other hand, we show that, in many cases, the extension of the calibration criteria to also include runoff or soil moisture signatures is beneficial, particularly for decreasing the uncertainty in parameters of the hydrological model. Moreover, in many cases, fitting the model with hydrological signatures only provides a comparable fit to that of the calibration strategies employing runoff time series.

scholarly journals Spatiotemporal Change Analysis of Soil Moisture Based on Downscaling Technology in Africa

Water ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 74
Author(s):  
Zijin Yuan ◽  
Nusseiba NourEldeen ◽  
Kebiao Mao ◽  
Zhihao Qin ◽  
Tongren Xu
Keyword(s):  
Soil Moisture ◽  
Crop Production ◽  
Central Africa ◽  
Spatiotemporal Variability ◽  
Change Analysis ◽  
Spatiotemporal Trends ◽  
Ocean Salinity ◽  
Hydrological Cycles ◽  
Microwave Sensors

Evaluating the long-term spatiotemporal variability in soil moisture (SM) over Africa is crucial for understanding how crop production is affected by drought or flooding. However, the lack of continuous and stable long-term series and high-resolution soil moisture records impedes such research. To overcome the inconsistency of different microwave sensors (Advanced Microwave Scanning Radiometer-EOS, AMSR-E; Soil Moisture and Ocean Salinity, SMOS; and Advanced Microwave Scanning Radiometer 2, AMSR2) in measuring soil moisture over time and depth, we built a time series reconstruction model to correct SM, and then used a Spatially Weighted Downscaling Model to downscale the SM data from three different sensors to a 1 km spatial resolution. The verification of the reconstructed data shows that the product has high accuracy, and can be used for application and analysis. The spatiotemporal trends of SM in Africa were examined for 2003–2017. The analysis indicated that soil moisture is declining in Africa as a whole, and it is notably higher in central Africa than in other subregions. The most significant decrease in SM was observed in the savanna zone (slope < −0.08 m3 m−3 and P < 0.001), followed by South Africa and Namibia (slope < −0.07 m3 m−3 and P < 0.01). Seasonally, the most significant downward trends in SM were observed during the spring, mainly over eastern and central Africa (slope < −0.07 m3 m−3, R < −0.58 and P < 0.001). The analysis of spatiotemporal changes in soil moisture can help improve the understanding of hydrological cycles, and provide benchmark information for drought management in Africa.

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