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.

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 GROUNDWATER STORAGE CHANGE ESTIMATION USING GRACE SATELLITE DATA IN INDUS BASIN

2020 ◽  
Vol 1 (1) ◽  
pp. 10-15
Author(s):  
Muhammad Salam ◽  
Muhammad Jehanzeb Masud Cheema ◽  
Wanchang Zhang ◽  
Saddam Hussain ◽  
Azeem Khan ◽  
...  
Keyword(s):  
Water Table ◽  
Land Surface ◽  
Large Scale ◽  
Water Storage ◽  
Indus Basin ◽  
Groundwater Storage ◽  
Grace Satellite ◽  
Over Exploitation ◽  
Flooding Events ◽  
Storage Change

Over exploitation of Ground Water (GW) has resulted in lowering of water table in the Indus Basin. While waterlogging, salinity and seawater intrusion has resulted in rising of water table in Indus Basin. The sparse piezometer network cannot provide sufficient data to map groundwater changes spatially. To estimate groundwater change in this region, data from Gravity Recovery and Climate Experiment (GRACE) satellite was used. GRACE measures (Total Water Storage) TWS and used to estimate groundwater storage change. Net change in storage of groundwater was estimated from the change in TWS by including the additional components such as Soil Moisture (SM), Surface water storage (Qs) and snowpack equivalent water (SWE). For the estimation of these components Global Land Data Assimilation system (GLDAS) Land Surface Models (LSMs) was used. Both GRACE and GLDAS produce results for the Indus Basin for the period of April 2010 to January 2017. The monitoring well water-level records from the Scarp Monitoring Organization (SMO) and the Punjab Irrigation and Drainage Authority (PIDA) from April 2009 to December 2016 were used. The groundwater results from different combinations of GRACE products GFZ (GeoforschungsZentrum Potsdam) CSR (Center for Space Research at University of Texas, Austin) JPL (Jet Propulsion Laboratory) and GLDAS LSMs (CLM, NOAH and VIC) are calibrated (April 2009-2014) and validated (April 2015-April 2016) with in-situ measurements. For yearly scale, their correlation coefficient reaches 0.71 with Nash-Sutcliffe Efficiency (NSE) 0.82. It was estimated that net loss in groundwater storage is at mean rate of 85.01 mm per year and 118,668.16 Km3 in the 7 year of study period (April 2010-Jan 2017). GRACE TWS data were also able to pick up the signals from the large-scale flooding events observed in 2010 and 2014. These flooding events played a significant role in the replenishment of the groundwater system in the Indus Basin. Our study indicates that the GRACE based estimation of groundwater storage changes is skillful enough to provide monthly updates on the trend of the groundwater storage changes for resource managers and policy makers of Indus Basin.

Future approaches to facilitate large-scale adoption of thermal based images as key input in the production of dynamic irrigation management zones

2017 ◽  
Vol 8 (2) ◽  
pp. 546-550 ◽  
Author(s):  
Y. Cohen ◽  
N. Agam ◽  
I. Klapp ◽  
A. Karnieli ◽  
O. Beeri ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Large Scale ◽  
Near Infrared ◽  
Water Status ◽  
Irrigation Management ◽  
Atmospheric Conditions ◽  
Management Zones ◽  
Financial Investments ◽  
Coarse Spatial Resolution ◽  
Aerial Platforms

To use VRI systems, a field is divided into irrigation management zones (IMZs). While IMZs are dynamic in nature, most of IMZs prescription maps are static. High-resolution thermal images (TI) coupled with measured atmospheric conditions have been utilized to map the within-field water status variability and to delineate in-season IMZs. Unfortunately, spaceborne TIs have coarse spatial resolution and aerial platforms require substantial financial investments, which may inhibit their large-scale adoption. Three approaches are proposed to facilitate large-scale adoption of TI-based IMZs: 1) increase of the capacity of aerial TI by enhancing their spatial resolution; 2) sharpening the spatial resolution of satellite TI by fusing satellite multi-spectral images in the visible-near-infrared (VIS-NIR) range; 3) increase the capacity of aerial TI by fusing satellite multi-spectral images in the VIS-NIR range. The scientific and engineering basis of each of the approaches is described together with initial results.

Testing a remotely-sensed snow water equivalent product in the framework of the operational European Drought Observatory (EDO)

2020 ◽  
Author(s):  
Carmelo Cammalleri ◽  
Paulo Barbosa ◽  
Jürgen Vogt
Keyword(s):  
Time Series ◽  
Spatial Resolution ◽  
Snow Water Equivalent ◽  
Remote Sensing Data ◽  
Cold Season ◽  
Snow Accumulation ◽  
Continental Scale ◽  
Basin Scale ◽  
Coarse Spatial Resolution ◽  
Snow Water

<p>Winter droughts, defined as periods of reduced precipitation and snow accumulation during the cold season, can have significant impacts on the subsequent summer season, especially over areas that strongly rely on stored water resources released during the spring melting.</p><p>The Snow Water Equivalent, SWE, represents a reliable means to quantify the amount of liquid water in the snowpack, and its anomalies can be used to evaluate deviations from the amount usually stored. Unfortunately, the use of SWE for operational monitoring of winter droughts is constrained by the limited availability of long time series of ground observations, and the lack of coordinated measuring networks at European continental scale.</p><p>Remote sensing data from microwave sensors, therefore, represent a valuable source of continuously-updated SWE data. Products such as the H-SAF (EUMETSAT Hydrology Satellite Application Facility, http://hsaf.meteoam.it/) SNOBS4-H13 are updated in almost near-real time, providing daily maps covering continental Europe and northern Africa. Limitations include data gaps, difficult retrievals over impervious terrain, coarse spatial resolution and a reduced length of the time series.</p><p>In this study, we tested the potential inclusion of a drought indicator based on the H-SAF SWE product in the European Drought Observatory (EDO, http://edo.jrc.ec.europa.eu), with the aim to fill the current gap faced over mountainous basins in terms of early warning of spring water deficits.</p><p>An analysis of the full dataset collected between 2013 and 2019 highlights how, currently, the main drawback of the product seems to be represented by the limited length of the time series, as well as by the difficulties to capture snow accumulation over some mountainous areas (e.g., Pyrenees) likely due to the coarse spatial resolution. Spatial aggregation at water basin scale was also tested, in order to evaluate the possibility to reduce the effects of some of these limitations.     </p>

Regression Downscaling of Coarse Resolution Globsnow Snow Water Equivalent Estimates in the Red River Basin

2020 ◽  
Author(s):  
Margot Flemming ◽  
Richard Kelly
Keyword(s):  
Remote Sensing ◽  
Random Forest ◽  
Spatial Resolution ◽  
Snow Water Equivalent ◽  
Passive Microwave ◽  
Red River ◽  
Random Forest Regression ◽  
Red River Basin ◽  
Snow Water

<p>The spatial and temporal heterogeneity of seasonal snow and its impact on socio-economic and environmental functionality make accurate, real-time estimates of snow water equivalent (SWE) important for hydrological and climatological predictions. Remote sensing techniques facilitate a cost effective, temporally and spatiallyconsistent approach to SWE monitoring in areas where insitu measurements are notsufficient. Passive microwave remote sensing has been used to successfully estimate SWE globally by measuring the microwave attenuation from the Earth’s surface as a function of SWE. However, passive microwave derived SWE estimates at local scales are subject to large errors given the coarse spatial resolution of observations (~625 km<sup>2</sup>).Regression downscaling techniques can be implemented to increase the spatial resolution of gridded datasets with the use of related auxiliary datasets at a finer spatial resolution. These techniques have been successfully implemented to remote sensing datasets such as soil moisture estimates, however, limited work has applied such techniques to snow-related datasets.This study focuses on assessing the feasibility of using regression downscaling to increase the spatial resolution of the European Space Agency’s (ESA) Globsnow SWE product in the Red River basin, an agriculturally important region of the northern United States.</p><p>Prior to downscaling Globsnow SWE, three regression downscaling techniques (Multiple Linear Regression, Random Forest Regression and Geographically Weighted Regression) were assessed in an internal experiment using 1 km grid scale Snow Data Assimilation System (SNODAS) SWE estimates, developed by the National Weather Service’s National Operational Hydrological Remote Sensing Center (NOHRSC). SNODAS SWE estimates for 5-year period between 2013-2018 were linearly aggregated to a 25 km grid scale to match the Globsnow spatial resolution. Three regression downscaling techniques were implemented along with correlative datasets available at the 1 km grid scale to downscale the aggregated SNODAS data back to the original 1 km grid scale spatial resolution. When compared with the original SNODAS SWE estimates, the downscaled SWE estimates from the Random Forest Regression performed the best. Random Forest Regression Downscaling was then implemented on the original Globsnow SWE data for the same time period, as well as a corrected Globsnow SWE dataset. The downscaled SWE results from both the corrected and uncorrected Globsnow data were validated using the original SNODAS SWE estimates as well as in situ SWE measurements from a set of 40-45 (depending on the season) weather stations within the study region. Spatial and temporal error distributions were assessed through both validation datasets. The downscaled results from the corrected Globsnow dataset showed similar overall statistics to the original SNODAS SWE estimates, performing better than the downscaled results from the uncorrected Globsnow SWE dataset. The overall aim of this study is to assess the applicability of regression downscaling as a reliable and reproducible method for local scale SWE estimation in areas where finer resolution data such as SNODAS does not exist. Therefore, the goal is to reproduce the optimal regression downscaling procedure in an area other snow dominated regions across the globe using in situ snow transect data for validation.</p>

scholarly journals An observation-based evaluation and ranking of historical Earth System Model simulations for regional downscaling in the northwest North Atlantic Ocean

2020 ◽  
Author(s):  
Arnaud Laurent ◽  
Katja Fennel ◽  
Angela Kuhn
Keyword(s):  
Spatial Resolution ◽  
North Atlantic ◽  
Large Scale ◽  
North Atlantic Ocean ◽  
Circulation Model ◽  
Biogeochemical Model ◽  
Earth System ◽  
Labrador Current ◽  
Coarse Spatial Resolution ◽  
Regional Downscaling

Abstract. Continental shelf regions in the ocean play an important role in the global cycling of carbon and nutrients but their responses to global change are understudied. Global Earth System Models (ESM), as essential tools for building understanding of ocean biogeochemistry, are used extensively and routinely for projections of future climate states; however, their relatively coarse spatial resolution is likely not appropriate for accurately representing the complex patterns of circulation and elemental fluxes on the shelves along ocean margins. Here, we compared 29 ESMs used in the IPCC’s Assessment Rounds (AR) 5 and 6 and a regional biogeochemical model for the northwest North Atlantic (NWA) shelf to assess their ability to reproduce observations of temperature, nitrate, and chlorophyll. The NWA region is biologically productive, influenced by the large-scale Gulf Stream and Labrador Current systems, and particularly sensitive to climate change. Most ESMs compare relatively poorly to observed nitrate and chlorophyll and show differences with observed temperature due to spatial mismatches in their large-scale circulation. Model-simulated nitrate and chlorophyll compare better with available observations in AR6 than in AR5, but none of the models performs equally well for all 3 parameters. The ensemble means of all ESMs, and of the five best performing ESMs, strongly underestimate observed chlorophyll and nitrate. The regional model has a much higher spatial resolution and reproduces the observations significantly better than any of the ESMs. It also simulates reasonably well vertically resolved observations from gliders and bi-monthly ship-based monitoring observations. A ranking of the ESMs suggests that the top 3 models are appropriate as boundary forcing for regional projections of future changes in the NWA region.

Microspectroscopy Using a Solid Immersion Lens

2001 ◽  
Vol 7 (S2) ◽  
pp. 148-149
Author(s):  
C.D. Poweleit ◽  
J Menéndez
Keyword(s):  
Spatial Resolution ◽  
Focal Plane ◽  
Numerical Aperture ◽  
Normal Incidence ◽  
Spot Size ◽  
Index Of Refraction ◽  
Objective Lens ◽  
Improvement Factor ◽  
Oil Immersion ◽  
Long Time

Oil immersion lenses have been used in optical microscopy for a long time. The light’s wavelength is decreased by the oil’s index of refraction n and this reduces the minimum spot size. Additionally, the oil medium allows a larger collection angle, thereby increasing the numerical aperture. The SIL is based on the same principle, but offers more flexibility because the higher index material is solid. in particular, SILs can be deployed in cryogenic environments. Using a hemispherical glass the spatial resolution is improved by a factor n with respect to the resolution obtained with the microscope’s objective lens alone. The improvement factor is equal to n2 for truncated spheres.As shown in Fig. 1, the hemisphere SIL is in contact with the sample and does not affect the position of the focal plane. The focused rays from the objective strike the lens at normal incidence, so that no refraction takes place.

TO THE QUESTION OF RESPONSIBILITY FOR TORTURE IN THE RUSSIAN FEDERATION

2020 ◽  
Vol 10 (2) ◽  
pp. 103-106
Author(s):  
ASTEMIR ZHURTOV ◽  
Keyword(s):  
Human Rights ◽  
Russian Federation ◽  
Large Scale ◽  
Human Life ◽  
International Standards ◽  
World Community ◽  
The World ◽  
Long Time ◽  
Protection Of Human Rights ◽  
The Russian Federation

Cruel and inhumane acts that harm human life and health, as well as humiliate the dignity, are prohibited in most countries of the world, and Russia is no exception in this issue. The article presents an analysis of the institution of responsibility for torture in the Russian Federation. The author comes to the conclusion that the current criminal law of Russia superficially and fragmentally regulates liability for torture, in connection with which the author formulated the proposals to define such act as an independent crime. In the frame of modern globalization, the world community pays special attention to the protection of human rights, in connection with which large-scale international standards have been created a long time ago. The Universal Declaration of Human Rights and other international acts enshrine prohibitions of cruel and inhumane acts that harm human life and health, as well as degrade the dignity.Considering the historical experience of the past, these standards focus on the prohibition of any kind of torture, regardless of the purpose of their implementation.

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