scholarly journals Introduction of a Superconducting Gravimeter as Novel Hydrological Sensor for the Alpine Research Catchment Zugspitze

2021 ◽  
Author(s):  
Christian Voigt ◽  
Karsten Schulz ◽  
Franziska Koch ◽  
Karl-Friedrich Wetzel ◽  
Ludger Timmen ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Snow Water Equivalent ◽  
Water Storage ◽  
High Sensitivity ◽  
Superconducting Gravimeter ◽  
Large Variability ◽  
Alpine Regions ◽  
Alpine Research ◽  
Set Up ◽  
Natural Test

Abstract. The Zugspitze Geodynamic Observatory Germany has been set up with a worldwide unique installation of a superconducting gravimeter at the summit of Mount Zugspitze. With regard to hydrology, this karstic high-alpine site is largely dominated by high precipitation amounts and a long seasonal snow cover period with significant importance for water supply to its forelands, while it shows a high sensitivity to climate change. However, regarding the majority of alpine regions worldwide there is only weak knowledge on temporal water storage variations due to only sparsely distributed hydrological and meteorological point sensors and the large variability and complexity of alpine signals. This underlines the importance of well-equipped areas such as Mount Zugspitze serving as natural test laboratories for an improved monitoring, understanding and prediction of alpine hydrological processes. The observatory superconducting gravimeter OSG 052 supplements the existing sensor network as a novel hydrological sensor system for the direct observation of the integral gravity effect of total water storage variations in the alpine research catchment Zugspitze. Besides the experimental setup and the available datasets, the required gravimetric prerequisites are presented such as calibration, tidal analysis and signal separation of the superconducting gravimeter observations from the first 2 years. The snowpack is identified as primary contributor to seasonal water storage variations and thus to the gravity residuals with a signal range of up to 750 nm/s2 corresponding to 1957 mm snow water equivalent measured at a representative station at the end of May 2019. First hydro-gravimetric sensitivity analysis are based on simplified assumptions of the snowpack distribution within the area around Mount Zugspitze. These reveal a snow-gravimetric footprint of up to 4 km distance around the gravimeter with a dominant gravity contribution from the snowpack in the Partnach spring catchment. This study already shows that the hydro-gravimetric approach can deliver important and representative integral insights into this high-alpine site. This work is regarded as a concept study showing preliminary gravimetric results and sensitivity analysis for upcoming long-term hydro-gravimetric research projects.

scholarly journals Technical note: Introduction of a superconducting gravimeter as novel hydrological sensor for the Alpine research catchment Zugspitze

2021 ◽  
Vol 25 (9) ◽  
pp. 5047-5064
Author(s):  
Christian Voigt ◽  
Karsten Schulz ◽  
Franziska Koch ◽  
Karl-Friedrich Wetzel ◽  
Ludger Timmen ◽  
...  
Keyword(s):  
Snow Water Equivalent ◽  
Water Storage ◽  
Superconducting Gravimeter ◽  
Technical Note ◽  
Research Centre ◽  
Mean Annual Precipitation ◽  
Large Variability ◽  
Spring Catchment ◽  
Alpine Research ◽  
Set Up

Abstract. GFZ (German Research Centre for Geosciences) set up the Zugspitze Geodynamic Observatory Germany with a worldwide unique installation of a superconducting gravimeter at the summit of Mount Zugspitze on top of the Partnach spring catchment. This high alpine catchment is well instrumented, acts as natural lysimeter and has significant importance for water supply to its forelands, with a large mean annual precipitation of 2080 mm and a long seasonal snow cover period of 9 months, while showing a high sensitivity to climate change. However, regarding the majority of alpine regions worldwide, there is only limited knowledge on temporal water storage variations due to sparsely distributed hydrological and meteorological sensors and the large variability and complexity of signals in alpine terrain. This underlines the importance of well-equipped areas such as Mount Zugspitze serving as natural test laboratories for improved monitoring, understanding and prediction of alpine hydrological processes. The observatory superconducting gravimeter, OSG 052, supplements the existing sensor network as a novel hydrological sensor system for the direct observation of the integral gravity effect of total water storage variations in the alpine research catchment at Zugspitze. Besides the experimental set-up and the available data sets, the gravimetric methods and gravity residuals are presented based on the first 27 months of observations from 29 December 2018 to 31 March 2021. The snowpack is identified as being a primary contributor to seasonal water storage variations and, thus, to the gravity residuals with a signal range of up to 750 nm s−2 corresponding to 1957 mm snow water equivalent measured with a snow scale at an altitude of 2420 m at the end of May 2019. Hydro-gravimetric sensitivity analysis reveal a snow–gravimetric footprint of up to 4 km distance around the gravimeter, with a dominant gravity contribution from the snowpack in the Partnach spring catchment. This shows that the hydro-gravimetric approach delivers representative integral insights into the water balance of this high alpine site.

scholarly journals A time series assessment of terrestrial water storage and its relationship with hydro-meteorological factors in Gilgit-Baltistan region using GRACE observation and GLDAS-Noah model

2021 ◽  
Vol 3 (5) ◽  
Author(s):  
Dostdar Hussain ◽  
Aftab Ahmed Khan ◽  
Syed Najam Ul Hassan ◽  
Syed Ali Asad Naqvi ◽  
Akhtar Jamil
Keyword(s):  
Snow Water Equivalent ◽  
Gravity Data ◽  
Water Storage ◽  
Indus Basin ◽  
Flood Hazards ◽  
Terrestrial Water Storage ◽  
Satellite Gravity ◽  
Terrestrial Water ◽  
Gilgit Baltistan

AbstractMountains regions like Gilgit-Baltistan (GB) province of Pakistan are solely dependent on seasonal snow and glacier melt. In Indus basin which forms in GB, there is a need to manage water in a sustainable way for the livelihood and economic activities of the downstream population. It is important to monitor water resources that include glaciers, snow-covered area, lakes, etc., besides traditional hydrological (point-based measurements by using the gauging station) and remote sensing-based studies (traditional satellite-based observations provide terrestrial water storage (TWS) change within few centimeters from the earth’s surface); the TWS anomalies (TWSA) for the GB region are not investigated. In this study, the TWSA in GB region is considered for the period of 13 years (from January 2003 to December 2016). Gravity Recovery and Climate Experiment (GRACE) level 2 monthly data from three processing centers, namely Centre for Space Research (CSR), German Research Center for Geosciences (GFZ), and Jet Propulsion Laboratory (JPL), System Global Land Data Assimilation System (GLDAS)-driven Noah model, and in situ precipitation data from weather stations, were used for the study investigation. GRACE can help to forecast the possible trends of increasing or decreasing TWS with high accuracy as compared to the past studies, which do not use satellite gravity data. Our results indicate that TWS shows a decreasing trend estimated by GRACE (CSR, GFZ, and JPL) and GLDAS-Noah model, but the trend is not significant statistically. The annual amplitude of GLDAS-Noah is greater than GRACE signal. Mean monthly analysis of TWSA indicates that TWS reaches its maximum in April, while it reaches its minimum in October. Furthermore, Spearman’s rank correlation is determined between GRACE estimated TWS with precipitation, soil moisture (SM) and snow water equivalent (SWE). We also assess the factors, SM and SWE which are the most efficient parameters producing GRACE TWS signal in the study area. In future, our results with the support of more in situ data can be helpful for conservation of natural resources and to manage flood hazards, droughts, and water distribution for the mountain regions.

scholarly journals Groundwater Depletion Signals in the Beqaa Plain, Lebanon: Evidence from GRACE and Sentinel-1 Data

2021 ◽  
Vol 13 (5) ◽  
pp. 915
Author(s):  
Elias C. Massoud ◽  
Zhen Liu ◽  
Amin Shaban ◽  
Mhamad Hage
Keyword(s):  
Snow Water Equivalent ◽  
Water Storage ◽  
Hydrologic Cycle ◽  
Groundwater Depletion ◽  
Satellite Mission ◽  
Groundwater Storage ◽  
Significant Drop ◽  
Monitoring Wells ◽  
High Productivity ◽  
Soil Moisture Storage

Regions with high productivity of agriculture, such as the Beqaa Plain, Lebanon, often rely on groundwater supplies for irrigation demand. Recent reports have indicated that groundwater consumption in this region has been unsustainable, and quantifying rates of groundwater depletion has remained a challenge. Here, we utilize 15 years of data (June 2002–April 2017) from the Gravity Recovery and Climate Experiment (GRACE) satellite mission to show Total Water Storage (TWS) changes in Lebanon’s Beqaa Plain. We then obtain complimentary information on various hydrologic cycle variables, such as soil moisture storage, snow water equivalent, and canopy water storage from the Global Land Data Assimilation System (GLDAS) model, and surface water data from the largest body of water in this region, the Qaraaoun Reservoir, to disentangle the TWS signal and calculate groundwater storage changes. After combining the information from the remaining hydrologic cycle variables, we determine that the majority of the losses in TWS are due to groundwater depletion in the Beqaa Plain. Results show that the rate of groundwater storage change in the West Beqaa is nearly +0.08 cm/year, in the Rashaya District is −0.01 cm/year, and in the Zahle District the level of depletion is roughly −1.10 cm/year. Results are confirmed using Sentinel-1 interferometric synthetic aperture radar (InSAR) data, which provide high-precision measurements of land subsidence changes caused by intense groundwater usage. Furthermore, data from local monitoring wells are utilized to further showcase the significant drop in groundwater level that is occurring through much of the region. For monitoring groundwater storage changes, our recommendation is to combine various data sources, and in areas where groundwater measurements are lacking, we especially recommend the use of data from remote sensing.

scholarly journals Sensitivity Analysis of Bistatic Scattering for Soil Moisture Retrieval

2021 ◽  
Vol 13 (2) ◽  
pp. 188
Author(s):  
Tingting Li ◽  
Irena Hajnsek ◽  
Kun-Shan Chen
Keyword(s):  
Sensitivity Analysis ◽  
Soil Moisture ◽  
Quality Index ◽  
High Sensitivity ◽  
Bare Soil ◽  
Sensitivity Index ◽  
Scattering Coefficients ◽  
Observation Systems ◽  
Bistatic Scattering ◽  
Scattering Response

Soil moisture is one of the vital environmental variables in the land–atmosphere cycle. A study of the sensitivity analysis of bistatic scattering coefficients from bare soil at the Ku-band is presented, with the aim of deepening our understanding of the bistatic scattering features and exploring its potential in soil moisture retrieval. First, a well-established advanced integral method was adopted for simulating the bistatic scattering response of bare soil. Secondly, a sensitivity index and a normalized weight quality index were proposed to evaluate the effect of soil moisture on the bistatic scattering coefficient in terms of polarization and angular diversity, and the combinations thereof. The results of single-polarized VV data show that the regions with the maximum sensitivity and high quality index, simultaneously, to soil moisture are in the forward off-specular direction. However, due to the effect of surface roughness and surface autocorrelation function (ACF), the single-polarized data have some limitations for soil moisture inversion. By contrast, the results of two different polarization combinations, as well as a dual-angular simulation of one transmitter and two receivers, show significant estimation benefits. It can be seen that they all provide better ACF suppression capabilities, larger high-sensitivity area, and higher quality indices compared to single-polarized estimation. In addition, dual polarization or dual angular combined measurement provides the possibility of retrieving soil moisture in backward regions. These results are expected to contribute to the design of future bistatic observation systems.

Development of paper substrate for paper spray MS in high-sensitivity analysis of biological samples

Bioanalysis ◽  
2018 ◽  
Vol 10 (24) ◽  
pp. 2047-2067 ◽  
Author(s):  
Weiwei Han ◽  
Yajun Zheng ◽  
Theoneste Muyizere ◽  
Zhiping Zhang
Keyword(s):  
Sensitivity Analysis ◽  
Biological Samples ◽  
High Sensitivity ◽  
Paper Substrate ◽  
Paper Spray

scholarly journals Local sensitivity analysis for compositional data with application to soil texture in hydrologic modelling

2013 ◽  
Vol 17 (2) ◽  
pp. 461-478 ◽  
Author(s):  
L. Loosvelt ◽  
H. Vernieuwe ◽  
V. R. N. Pauwels ◽  
B. De Baets ◽  
N. E. C. Verhoest
Keyword(s):  
Sensitivity Analysis ◽  
Soil Texture ◽  
Compositional Data ◽  
High Sensitivity ◽  
Hydrologic Model ◽  
Model Output ◽  
Local Sensitivity ◽  
Hydrologic Modelling ◽  
Compositional Model ◽  
Additional Data Collection

Abstract. Compositional data, such as soil texture, are hard to deal with in the geosciences as standard statistical methods are often inappropriate to analyse this type of data. Especially in sensitivity analysis, the closed character of the data is often ignored. To that end, we developed a method to assess the local sensitivity of a model output with resect to a compositional model input. We adapted the finite difference technique such that the different parts of the input are perturbed simultaneously while the closed character of the data is preserved. This method was applied to a hydrologic model and the sensitivity of the simulated soil moisture content to local changes in soil texture was assessed. Based on a high number of model runs, in which the soil texture was varied across the entire texture triangle, we identified zones of high sensitivity in the texture triangle. In such zones, the model output uncertainty induced by the discrepancy between the scale of measurement and the scale of model application, is advised to be reduced through additional data collection. Furthermore, the sensitivity analysis provided more insight into the hydrologic model behaviour as it revealed how the model sensitivity is related to the shape of the soil moistureretention curve.

scholarly journals Downscaling of GRACE-Derived Groundwater Storage Based on the Random Forest Model

2019 ◽  
Vol 11 (24) ◽  
pp. 2979 ◽  
Author(s):  
Li Chen ◽  
Qisheng He ◽  
Kun Liu ◽  
Jinyang Li ◽  
Chenlin Jing
Keyword(s):  
Random Forest ◽  
Spatial Resolution ◽  
Large Scale ◽  
Snow Water Equivalent ◽  
Water Storage ◽  
Research Area ◽  
Groundwater Storage ◽  
Coarse Spatial Resolution ◽  
Long Time ◽  
Local Water

Groundwater is an important part of water storage and one of the important sources of agricultural irrigation, urban living, and industrial water use. The recent launch of Gravity Recovery and Climate Experiment (GRACE) Satellite has provided a new way for studying large-scale water storage. The application of GRACE in local water resources has been greatly limited because of the coarse spatial resolution, and low temporal resolution. Therefore, it is of great significance to improve the spatial resolution of groundwater storage for regional water management. Based on the method of random forest (RF), this study combined six hydrological variables, including precipitation, evapotranspiration, runoff, soil moisture, snow water equivalent, and canopy water to conduct downscaling study, aiming at downscaling the resolution of the total water storage and groundwater storage from 1° (110 km) and to 0.25° (approximately 25 km). The results showed that, from the perspective of long time series, the prediction results of the RF model are ideal in the whole research area and the observations wells area. From the perspective of space, the detailed changes of water storage could be captured in greater detail after downscaling. The verification results show that, on the monthly scale and annual scale, the correlation between the downscaling results and the observation wells is 0.78 and 0.94, respectively, and they both reach the confidence level of 0.01. Therefore, the RF downscaling model has great potential for predicting groundwater storage.

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