Temporal variation of soil moisture over the Wuding River basin assessed with an eco-hydrological model, in-situ observations and remote sensing

The change pattern and trend of soil moisture (SM) in the Wuding River basin, Loess Plateau, China is explored based on the simulated long-term SM data from 1956 to 2004 using an eco-hydrological process-based model, Vegetation Interface Processes model, VIP. In-situ SM observations together with a remotely sensed SM dataset retrieved by the Vienna University of Technology are used to validate the model. In the VIP model, climate-eco-hydrological (CEH) variables such as precipitation, air temperature and runoff observations and also simulated evapotranspiration (<I>E<sub>T</sub></I>), leaf area index (LAI), and vegetation production are used to analyze the soil moisture evolution mechanism. The results show that the model is able to capture seasonal SM variations. The seasonal pattern, multi-year variation, standard deviation and coefficient of variation (<I>C<sub>V</sub></I>) of SM at the daily, monthly and annual scale are well explained by CEH variables. The annual and inter-annual variability of SM is the lowest compared with that of other CEH variables. The trend analysis shows that SM is in decreasing tendency at α=0.01 level of significance, confirming the Northern Drying phenomenon. This trend can be well explained by the decreasing tendency of precipitation (α=0.1) and increasing tendency of temperature (α=0.01). The decreasing tendency of runoff has higher significance level (α=0.001). Because of SM's decreasing tendency, soil evaporation (<I>E<sub>S</sub></I>) is also decreasing (α=0.05). The tendency of net radiation (<I>R<sub>n</sub></I>), evapotranspiration (<I>E<sub>T</sub></I>), transpiration (<I>E<sub>C</sub></I>), canopy intercept (<I>E<sub>I</sub></I>) is not obvious. Net primary productivity (NPP), of which the significance level is lower than α=0.1, and gross primary productivity (GPP) at α=0.01 are in increasing tendency

Error characterisation of global active and passive microwave soil moisture data sets

Understanding the error structures of remotely sensed soil moisture products is essential for correctly interpreting observed variations and trends in the data or assimilating them in hydrological or numerical weather prediction models. Nevertheless, a spatially coherent assessment of the quality of the various globally available data sets is often hampered by the limited availability over space and time of reliable in-situ measurements. This study explores the triple collocation error estimation technique for assessing the relative quality of several globally available soil moisture products from active (ASCAT) and passive (AMSR-E and SSM/I) microwave sensors. The triple collocation technique is a powerful tool to estimate the root mean square error while simultaneously solving for systematic differences in the climatologies of a set of three independent data sources. In addition to the scatterometer and radiometer data sets, we used the ERA-Interim and GLDAS-NOAH reanalysis soil moisture data sets as a third, independent reference. The prime objective is to reveal trends in uncertainty related to different observation principles (passive versus active), the use of different frequencies (C-, X-, and Ku-band) for passive microwave observations, and the choice of the independent reference data set (ERA-Interim versus GLDAS-NOAH). <br><br> The results suggest that the triple collocation method provides realistic error estimates. Observed spatial trends agree well with the existing theory and studies on the performance of different observation principles and frequencies with respect to land cover and vegetation density. In addition, if all theoretical prerequisites are fulfilled (e.g. a sufficiently large number of common observations is available and errors of the different data sets are uncorrelated) the errors estimated for the remote sensing products are hardly influenced by the choice of the third independent data set. The results obtained in this study can help us in developing adequate strategies for the combined use of various scatterometer and radiometer-based soil moisture data sets, e.g. for improved flood forecast modelling or the generation of superior multi-mission long-term soil moisture data sets

Cross-evaluation of modelled and remotely sensed surface soil moisture with in situ data in southwestern France

The SMOSMANIA soil moisture network in Southwestern France is used to evaluate modelled and remotely sensed soil moisture products. The surface soil moisture (SSM) measured in situ at 5 cm permits to evaluate SSM from the SIM operational hydrometeorological model of Météo-France and to perform a cross-evaluation of the normalised SSM estimates derived from coarse-resolution (25 km) active microwave observations from the ASCAT scatterometer instrument (C-band, onboard METOP), issued by EUMETSAT and resampled to the Discrete Global Grid (DGG, 12.5 km gridspacing) by TU-Wien (Vienna University of Technology) over a two year period (2007–2008). A downscaled ASCAT product at one kilometre scale is evaluated as well, together with operational soil moisture products of two meteorological services, namely the ALADIN numerical weather prediction model (NWP) and the Integrated Forecasting System (IFS) analysis of Météo-France and ECMWF, respectively. In addition to the operational SSM analysis of ECMWF, a second analysis using a simplified extended Kalman filter and assimilating the ASCAT SSM estimates is tested. The ECMWF SSM estimates correlate better with the in situ observations than the Météo-France products. This may be due to the higher ability of the multi-layer land surface model used at ECMWF to represent the soil moisture profile. However, the SSM derived from SIM corresponds to a thin soil surface layer and presents good correlations with ASCAT SSM estimates for the very first centimetres of soil. At ECMWF, the use of a new data assimilation technique, which is able to use the ASCAT SSM, improves the SSM and the root-zone soil moisture analyses

Heart Disease Is Associated With Anthropometric Indices and Change in Body Size Perception Over the Life Course. The Golestan Cohort Study

Background: Cardiovascular disease and obesity are now becoming leading causes of morbidity and mortality in low- and middle-income countries. Objectives: We investigated the relationship between prevalent heart disease (HD) and current anthropometric indices and body size perception over time from adolescence to adulthood in Iran. Methods: We present a cross-sectional analysis of baseline data from a prospective study of adults in Golestan Province, Iran. Demographics, cardiac history, and current anthropometric indices-body mass index, waist circumference, and waist to hip ratio-were recorded. Body size perception for ages 15 years, 30 years, and at the time of interview was assessed via pictograms. Associations of these factors and temporal change in perceived body size with HD were evaluated using multivariable logistic regression models. Results: Complete data were available for 50,044 participants; 6.1% of which reported having HD. Higher body mass index, waist circumference, and waist to hip ratio were associated with HD (p < 0.001). Men had a U-shaped relationship between HD and body size perception at younger ages. For change in body size perception, men and women demonstrated a U-shaped relationship with prevalent HD from adolescence to early adulthood, but a J-shaped pattern from early to late adulthood. Conclusions: HD was associated with anthropometric indices and change in body size perception over time for men and women in Iran. Due to the increasing prevalence of overweight and obesity in low- and middle-income countries, interventions focused on decreasing the cumulative burden of risk factors throughout the life course may be an important component of cardiovascular risk reduction. © 2015 World Heart Federation (Geneva)

Addressing Grand Challenges in Earth Observation Science: The Earth Observation Data Centre for Water Resources Monitoring

Earth observation is entering a new era where the increasing availability of free and open global satellite data sets combined with the computing power offered by modern information technologies opens up the possibility to process high-resolution data sets at global scale and short repeat intervals in a fully automatic fashion. This will not only boost the availability of higher level earth observation data in purely quantitative terms, but can also be expected to trigger a step change in the quality and usability of earth observation data. However, the technical, scientific, and organisational challenges that need to be overcome to arrive at this point are significant. First of all, Petabyte-scale data centres are needed for storing and processing complete satellite data records. Second, innovative processing chains that allow fully automatic processing of the satellite data from the raw sensor records to higher-level geophysical products need to be developed. Last but not least, new models of cooperation between public and private actors need to be found in order to live up to the first two challenges. This paper offers a discussion of how the Earth Observation Data Centre for Water Resources Monitoring (EODC) – a catalyser for an open and international cooperation of public and private organisations – will address these three grand challenges with the aim to foster the use of earth observation for monitoring of global water resources

4E assessment of power generation systems for a mobile house in emergency condition using solar energy: a case study

In this study, a solar parabolic trough concentrator (PTC) was evaluated as a heat source of a power generation system based on energy (E1), exergy (E2), environmental (E3), and economic (E4) analyses. Various configurations of power generation systems were investigated, including the solar SRC (SRC) and solar ORC (ORC). Water and R113 were used as heat transfer fluids of SRC and ORC system, respectively. It should be mentioned that the proposed solar systems were evaluated for providing the required power of a mobile house in an emergency condition such as an earthquake that was happened in Kermanshah, Iran, in 2016 with many homeless people. The PTC system was optically and thermally investigated based on sensitivity analysis. The optimized PTC system was assumed as a heat source of the RC with two various configurations for power generation. Then, the solar RC systems were investigated based on 4E analyses for providing the power of the mobile house based on various numbers of solar RC units. It was concluded that the solar SRC system could be recommended for achieving the highest 4E performance. The highest value of its energy efficiency was found at 24.60% and of his exergy at 26.37%. On the other hand, the ORC system has energy and exergy efficiencies at 17.64% and 18.91%, respectively, which are significantly lower than the efficiencies of the SRC system. The optimum heat source temperature for the SRC system is found at 650 K, while for the ORC system at 499 K. Moreover, the best economic performance was found with the SRC system with a payback period of 7.47 years. Finally, the CO2 mitigated per annum (φCO2) was estimated at 5.29 (tones year−1), and the carbon credit (ZCO2) was calculated equal to 76.71 ($ year−1)