scholarly journals GRACE-Based Terrestrial Water Storage in Northwest China: Changes and Causes

2018 ◽  
Vol 10 (7) ◽  
pp. 1163 ◽  
Author(s):  
Yangyang Xie ◽  
Shengzhi Huang ◽  
Saiyan Liu ◽  
Guoyong Leng ◽  
Jian Peng ◽  
...  
Keyword(s):  
Yellow River ◽  
Sunshine Duration ◽  
Water Storage ◽  
Northwest China ◽  
Combined Effects ◽  
Terrestrial Water Storage ◽  
Qinghai Province ◽  
Level Ii ◽  
Terrestrial Water ◽  
Gravity Recovery

Monitoring variations in terrestrial water storage (TWS) is of great significance for the management of water resources. However, it remains a challenge to continuously monitor TWS variations using in situ observations and hydrological models because of a limited number of gauge stations and the complicated spatial distribution characteristics of TWS. In contrast, the Gravity Recovery and Climate Experiment (GRACE) could overcome the aforementioned restrictions, providing a new reliable means of observing TWS variation. Thus, GRACE was employed to investigate TWS variations in Northwest China (NWC) between April 2002 and March 2016. Unlike previous studies, we focused on the interactions of multiple climatic and vegetational factors, and their combined effects on TWS variation. In addition, we also analyzed the relationship between TWS variations and socioeconomic water consumption. The results indicated that (i) TWS had obvious seasonal variations in NWC, and showed significant decreasing trends in most parts of NWC at the 95% confidence level; (ii) decreasing sunshine duration and wind speed resulted in an increase in TWS in Qinghai province, whereas the increasing air temperature, ameliorative vegetational coverage, and excessive groundwater withdrawal jointly led to a decrease in TWS in the other provinces of NWC; (iii) TWS variations in NWC had a good correlation with water storage variations in cascade reservoirs of the upper Yellow River; and (iv) the overall interactions between multiple climatic and vegetational factors were obvious, and the strong effects of some climatic and vegetational factors could mask the weak influences of other factors in TWS variations in NWC. Hence, it is necessary to focus on the interactions of multiple factors and their combined effects on TWS variations when exploring the causes of TWS variations.

The uncertainty of storage-based drought indices from GRACE

2020 ◽  
Author(s):  
Peyman Saemian ◽  
Mohammad Javad Tourian ◽  
Nico Sneeuw
Keyword(s):  
Land Surface ◽  
Water Storage ◽  
Extended Period ◽  
Drought Indices ◽  
Terrestrial Water Storage ◽  
Earth’S Gravity Field ◽  
Grace Data ◽  
Temporal And Spatial Variability ◽  
Terrestrial Water ◽  
Gravity Recovery

<p>Climate change and the growing demand for freshwater have raised the frequency and intensity of extreme events like drought. Satellite observations have improved our understanding of the temporal and spatial variability of droughts. Since March 2002, the Gravity Recovery and Climate Experiment (GRACE) and its successor GRACE Follow-On (GRACE-FO) have been observing variations in Earth's gravity field yielding valuable information about changes in terrestrial water storage anomaly (TWSA). The terrestrial water storage vertically integrates all forms of water on and beneath land surface including snow, surface water, soil moisture, and groundwater storage.</p><p>Drought indices help to monitor drought by characterizing it in terms of their severity, location, duration and timing. Several drought indices have been developed based on GRACE water storage anomaly from a GRACE-based climatology, most of which suffer from the short record of GRACE, about 15 years, for their climatology. The limited duration of the GRACE observations necessitates the use of external datasets of TWSA with a more extended period for climatology. Drought characterization comes with its own uncertainties due to the inherent uncertainty in the GRACE data, the various post-processing approaches of GRACE data, and different options for external datasets on the other hand.</p><p>This study offers a method to quantify uncertainties for the storage-based drought index. Moreover, we assess the sensitivity of major global river basins to the duration of the observations. The outcome of the study is invaluable in the sense that it allows for a more informative storage based drought, including uncertainty, thus enabling a more realistic risk assessment.</p>

Understanding Terrestrial Water Storage Declining Trends in the Yellow River Basin

2019 ◽  
Vol 124 (23) ◽  
pp. 12963-12984 ◽  
Author(s):  
Wenlong Jing ◽  
Ling Yao ◽  
Xiaodan Zhao ◽  
Pengyan Zhang ◽  
Yangxiaoyue Liu ◽  
...  
Keyword(s):  
River Basin ◽  
Yellow River ◽  
Water Storage ◽  
Yellow River Basin ◽  
The Yellow River ◽  
Terrestrial Water Storage ◽  
Terrestrial Water ◽  
The Yellow River Basin

scholarly journals Monitoring and Analysis of Drought Using Gravity Recovery and Climate Experiment (GRACE)

Hydrology ◽  
2019 ◽  
Vol 6 (3) ◽  
pp. 75 ◽  
Author(s):  
Ahmad Nemati ◽  
Seyed Hossein Ghoreishi Najafabadi ◽  
Gholamreza Joodaki ◽  
S. Saeid Mousavi Nadoushani
Keyword(s):  
Water Resource Management ◽  
Arid Zone ◽  
Water Storage ◽  
Drought Indices ◽  
Arid Zones ◽  
Terrestrial Water Storage ◽  
Study Results ◽  
Terrestrial Water ◽  
Gravity Recovery ◽  
Semi Arid

Drought monitoring needs comprehensive and integrated meteorological and hydrologic data. However, such data are generally not available in extensive catchments. The present study aimed to analyze drought in the central plateau catchment of Iran using the terrestrial water storage deficit index (TSDI). In this arid catchment, the meteorological and hydrologic observed data are scarce. First, the time series of terrestrial water storage changes (TWSC) obtained from the gravity recovery and climate experiment (GRACE) was calculated and validated by the water budget output. Then, the studied area was divided into semi-arid, arid, and hyper-arid zones and the common drought indices of SPI and RDIe within a timescale of 3, 6, and 12 months were calculated to compare the results obtained from the TSDI by using the meteorological data of 105 synoptic stations. Based on the results, the study area experienced a drought with extreme severity and expansion during 2007–2008. The drought spatial distribution map obtained from three indices indicated good conformity. Based on the maps, the severity, duration, and frequency of drought in the semi-arid zone were greater than that in other zones, while no significant drought occurred in the hyper-arid zone. Furthermore, the temporal distribution of drought in all three zones indicated that the TSDI could detect all short- and long-term droughts. The study results showed that the TSDI is a reliable, integrated, and comprehensive index. Using this index in arid areas with little field data led to some valuable results for planning and water resource management.

scholarly journals Characterizing Drought in India Using GRACE Observations of Terrestrial Water Storage Deficit

2017 ◽  
Vol 18 (2) ◽  
pp. 381-396 ◽  
Author(s):  
Debanjan Sinha ◽  
Tajdarul H. Syed ◽  
James S. Famiglietti ◽  
John T. Reager ◽  
Reis C. Thomas
Keyword(s):  
Spatial Scales ◽  
Water Storage ◽  
Central India ◽  
Terrestrial Water Storage ◽  
Drought Intensity ◽  
West Central ◽  
Terrestrial Water ◽  
Almost All ◽  
Gravity Recovery

Abstract Frequent recurrences of drought in India have had major societal, economical, and environmental impacts. While region-specific assessments are abundant, exhaustive appraisal over large spatial scales has been insubstantial. Here a new drought index called Water Storage Deficit Index (WSDI) is devised and analyzed for holistic representation of drought. The crux of the method is the employment of terrestrial water storage (TWS) variations from Gravity Recovery and Climate Experiment (GRACE) for quantification of drought intensity and severity. Drought events in recent times are well identified and quantified using the approach over four homogenous rainfall regions of India over the period from April 2002 to April 2015. Among the four regions, the highest peak deficit of −158.00 mm is observed in January 2015 over central India. While the drought of 2002–04 is prominent in peninsular and west-central India, the drought of 2009–10 and 2012–13 is conspicuous in almost all four regions of India. The longest deficit period of 23 months (from February 2009 to December 2010) and the highest severity value of −26.31 are observed in central and northwestern India, respectively. WSDI values show an increasing trend in west-central India (0.07 yr−1), indicating recovery from previously existing drought conditions. On the contrary, a decreasing trend in WSDI is observed in northwestern (−0.07 yr−1) and central (−0.18 yr−1) India. Results demonstrate considerable confidence in the potential of WSDI for robust characterization of drought over large spatial scales.

scholarly journals Data Assimilation of Terrestrial Water Storage Observations to Estimate Precipitation Fluxes: A Synthetic Experiment

2021 ◽  
Vol 13 (6) ◽  
pp. 1223
Author(s):  
Manuela Girotto ◽  
Rolf Reichle ◽  
Matthew Rodell ◽  
Viviana Maggioni
Keyword(s):  
Data Assimilation ◽  
Snow Water Equivalent ◽  
Water Storage ◽  
Synthetic Data ◽  
Terrestrial Water Storage ◽  
Grace Data ◽  
Precipitation Estimates ◽  
Terrestrial Water ◽  
Snow Water ◽  
Gravity Recovery

The Gravity Recovery and Climate Experiment (GRACE) mission and its Follow-On (GRACE-FO) mission provide unprecedented observations of terrestrial water storage (TWS) dynamics at basin to continental scales. Established GRACE data assimilation techniques directly adjust the simulated water storage components to improve the estimation of groundwater, streamflow, and snow water equivalent. Such techniques artificially add/subtract water to/from prognostic variables, thus upsetting the simulated water balance. To overcome this limitation, we propose and test an alternative assimilation scheme in which precipitation fluxes are adjusted to achieve the desired changes in simulated TWS. Using a synthetic data assimilation experiment, we show that the scheme improves performance skill in precipitation estimates in general, but that it is more robust for snowfall than for rainfall, and it fails in certain regions with strong horizontal gradients in precipitation. The results demonstrate that assimilation of TWS observations can help correct (adjust) the model’s precipitation forcing and, in turn, enhance model estimates of TWS, snow mass, soil moisture, runoff, and evaporation. A key limitation of the approach is the assumption that all errors in TWS originate from errors in precipitation. Nevertheless, the proposed approach produces more consistent improvements in simulated runoff than the established GRACE data assimilation techniques.

scholarly journals Correction: Xie, Y.Y.; et al. GRACE-Based Terrestrial Water Storage in Northwest China: Changes and Causes. Remote Sens. 2018, 10, 1163

2018 ◽  
Vol 10 (8) ◽  
pp. 1301
Author(s):  
Yangyang Xie ◽  
Shengzhi Huang ◽  
Saiyan Liu ◽  
Guoyong Leng ◽  
Jian Peng ◽  
...  
Keyword(s):  
Water Storage ◽  
Northwest China ◽  
Terrestrial Water Storage ◽  
Terrestrial Water

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