An analysis of spatio-temporal variability of terrestrial water storage in India

2021 ◽  
Vol 14 ◽  
pp. 100099
Author(s):  
H. Munagapati ◽  
V.M. Tiwari ◽  
D.K. Panda
Keyword(s):  
Temporal Variability ◽  
Water Storage ◽  
Terrestrial Water Storage ◽  
Terrestrial Water ◽  
Spatio Temporal

Spatio-temporal coupling between Terrestrial Water Storage and Vegetation Index in Shule River Basin

2019 ◽  
Vol 39 (14) ◽  
Author(s):  
岳东霞 YUE Dongxia ◽  
苗俊霞 MIAO Junxia ◽  
朱敏翔 ZHU Minxiang ◽  
周妍妍 ZHOU Yanyan ◽  
邹明亮 ZOU Mingliang ◽  
...  
Keyword(s):  
River Basin ◽  
Vegetation Index ◽  
Water Storage ◽  
Terrestrial Water Storage ◽  
Terrestrial Water ◽  
Temporal Coupling ◽  
Spatio Temporal

scholarly journals Analysis of the spatio-temporal variability of terrestrial water storage in the Great Artesian Basin, Australia

2016 ◽  
Vol 17 (2) ◽  
pp. 324-341 ◽  
Author(s):  
Jiabao Yan ◽  
Shaofeng Jia ◽  
Aifeng Lv ◽  
Rashid Mahmood ◽  
Wenbin Zhu
Keyword(s):  
Groundwater Resources ◽  
Water Storage ◽  
Terrestrial Water Storage ◽  
Sea Level Changes ◽  
Satellite Gravity ◽  
Artesian Basin ◽  
Great Artesian Basin ◽  
Terrestrial Water ◽  
Spatio Temporal

The Great Artesian Basin (GAB) in Australia, the largest artesian basin in the world, is rich in groundwater resources. This study analyzed the spatio-temporal characteristics of terrestrial water storage (TWS) in the GAB for 2003–2014 using satellite (Gravity Recovery and Climate Experiment, GRACE) data, hydrological models’ outputs, and in situ data. A slight increase in TWS was observed for the study period. However, there was a rapid increase in TWS in 2010 and 2011 due to two strong La Nina events. Long-term mean monthly TWS changes showed remarkable agreements with net precipitation. Both GRACE derived and in situ groundwater disclosed similar trend patterns. Groundwater estimated from the PCR-GLOBWB model contributes 26.8% (26.4% from GRACE) to the total TWS variation in the entire basin and even more than 50% in the northern regions. Surface water contributes only 3% to the whole basin but more than 60% to Lake Eyre and the Cooper River. Groundwater, especially deeper than 50 meters, was insensitive to climate factors (i.e., rainfall). Similarly, the groundwater in the northern Cape York Peninsula was influenced by some other factors rather than precipitation. The time-lagged correlation analysis between sea surface height and groundwater storage indicated certain correlations between groundwater and sea level changes.

scholarly journals MULTI-PLATFORM SATELLITE BASED ESTIMATES OF RUNOFF IN UNGAUGED AREAS

2015 ◽  
Vol XL-2/W4 ◽  
pp. 61-62 ◽  
Author(s):  
J. Y. Seo ◽  
S.-I. Lee
Keyword(s):  
North Korea ◽  
Water Storage ◽  
Extreme Weather Events ◽  
Steady Increase ◽  
Observation Data ◽  
Terrestrial Water Storage ◽  
Terrestrial Water ◽  
Floods And Droughts ◽  
Spatio Temporal ◽  
Moderate Resolution Imaging Spectroradiometer

Over the past decades, extreme weather events such as floods and droughts have been on a steady increase. Especially, ungauged or hard-to-reach areas turn out to be the most affected areas by the unexpected water-related disasters. It is usually due to insufficient observation data, and deterioration of infra-structures as well as inadequate water management system. For such reasons, reliable estimation of runoff is important for the planning and the implementation of water projects in ungauged areas. North Korea, whose terrain is mostly hilly and mountainous, has become vulnerable to floods and droughts due to poor watershed management based on unreliable hydrological information along with rapid deforestation. Runoff estimation using data from multi-platform satellites having broad spatio-temporal coverage could be of a valuable substitute for ground-observed measurements. In this study, monthly runoff in North Korea (38°N - 43°N, 124°E - 131°E) was estimated by combining space-borne data from multi-platform satellites with ground observations. Period of analysis is from January 2003 to December 2013. Data sets used for this study are as in the following: {1} Terrestrial Water Storage Anomaly (TWSA) from Gravity Recovery and Climate Experiment (GRACE), (2) Evapotranspiration from Moderate Resolution Imaging Spectroradiometer (MODIS), (3) Satellite-observed precipitation from Tropical Rainfall Measurement Mission (TRMM), and (4) Ground-observed precipitation from World Meterological Organization (WMO) (see Figure 1 and Table 1). These components are balanced with the terrestrial water storage change, and runoff can be estimated from eq. (1).

scholarly journals Understanding terrestrial water storage variations in northern latitudes across scales

2018 ◽  
Vol 22 (7) ◽  
pp. 4061-4082 ◽  
Author(s):  
Tina Trautmann ◽  
Sujan Koirala ◽  
Nuno Carvalhais ◽  
Annette Eicker ◽  
Manfred Fink ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Liquid Water ◽  
Spatial Scales ◽  
Water Storage ◽  
Earth Observation ◽  
High Latitudes ◽  
Terrestrial Water Storage ◽  
Northern Latitudes ◽  
Terrestrial Water ◽  
Spatio Temporal

Abstract. The GRACE satellites provide signals of total terrestrial water storage (TWS) variations over large spatial domains at seasonal to inter-annual timescales. While the GRACE data have been extensively and successfully used to assess spatio-temporal changes in TWS, little effort has been made to quantify the relative contributions of snowpacks, soil moisture, and other components to the integrated TWS signal across northern latitudes, which is essential to gain a better insight into the underlying hydrological processes. Therefore, this study aims to assess which storage component dominates the spatio-temporal patterns of TWS variations in the humid regions of northern mid- to high latitudes. To do so, we constrained a rather parsimonious hydrological model with multiple state-of-the-art Earth observation products including GRACE TWS anomalies, estimates of snow water equivalent, evapotranspiration fluxes, and gridded runoff estimates. The optimized model demonstrates good agreement with observed hydrological spatio-temporal patterns and was used to assess the relative contributions of solid (snowpack) versus liquid (soil moisture, retained water) storage components to total TWS variations. In particular, we analysed whether the same storage component dominates TWS variations at seasonal and inter-annual temporal scales, and whether the dominating component is consistent across small to large spatial scales. Consistent with previous studies, we show that snow dynamics control seasonal TWS variations across all spatial scales in the northern mid- to high latitudes. In contrast, we find that inter-annual variations of TWS are dominated by liquid water storages at all spatial scales. The relative contribution of snow to inter-annual TWS variations, though, increases when the spatial domain over which the storages are averaged becomes larger. This is due to a stronger spatial coherence of snow dynamics that are mainly driven by temperature, as opposed to spatially more heterogeneous liquid water anomalies, that cancel out when averaged over a larger spatial domain. The findings first highlight the effectiveness of our model–data fusion approach that jointly interprets multiple Earth observation data streams with a simple model. Secondly, they reveal that the determinants of TWS variations in snow-affected northern latitudes are scale-dependent. In particular, they seem to be not merely driven by snow variability, but rather are determined by liquid water storages on inter-annual timescales. We conclude that inferred driving mechanisms of TWS cannot simply be transferred from one scale to another, which is of particular relevance for understanding the short- and long-term variability of water resources.

scholarly journals Multiple Data Products Reveal Long-Term Variation Characteristics of Terrestrial Water Storage and Its Dominant Factors in Data-Scarce Alpine Regions

2021 ◽  
Vol 13 (12) ◽  
pp. 2356
Author(s):  
Xuanxuan Wang ◽  
Liu Liu ◽  
Qiankun Niu ◽  
Hao Li ◽  
Zongxue Xu
Keyword(s):  
Abrupt Change ◽  
Water Storage ◽  
Terrestrial Water Storage ◽  
Alpine Regions ◽  
Increasing Trend ◽  
Term Variation ◽  
Terrestrial Water ◽  
Variation Characteristics ◽  
Spatio Temporal

As the “Water Tower of Asia” and “The Third Pole” of the world, the Qinghai–Tibet Plateau (QTP) shows great sensitivity to global climate change, and the change in its terrestrial water storage has become a focus of attention globally. Differences in multi-source data and different calculation methods have caused great uncertainty in the accurate estimation of terrestrial water storage. In this study, the Yarlung Zangbo River Basin (YZRB), located in the southeast of the QTP, was selected as the study area, with the aim of investigating the spatio-temporal variation characteristics of terrestrial water storage change (TWSC). Gravity Recovery and Climate Experiment (GRACE) data from 2003 to 2017, combined with the fifth-generation reanalysis product of the European Centre for Medium-Range Weather Forecasts (ERA5) data and Global Land Data Assimilation System (GLDAS) data, were adopted for the performance evaluation of TWSC estimation. Based on ERA5 and GLDAS, the terrestrial water balance method (PER) and the summation method (SS) were used to estimate terrestrial water storage, obtaining four sets of TWSC, which were compared with TWSC derived from GRACE. The results show that the TWSC estimated by the SS method based on GLDAS is most consistent with the results of GRACE. The time-lag effect was identified in the TWSC estimated by the PER method based on ERA5 and GLDAS, respectively, with 2-month and 3-month lags. Therefore, based on the GLDAS, the SS method was used to further explore the long-term temporal and spatial evolution of TWSC in the YZRB. During the period of 1948–2017, TWSC showed a significantly increasing trend; however, an abrupt change in TWSC was detected around 2002. That is, TWSC showed a significantly increasing trend before 2002 (slope = 0.0236 mm/month, p < 0.01) but a significantly decreasing trend (slope = −0.397 mm/month, p < 0.01) after 2002. Additional attribution analysis on the abrupt change in TWSC before and after 2002 was conducted, indicating that, compared with the snow water equivalent, the soil moisture dominated the long-term variation of TWSC. In terms of spatial distribution, TWSC showed a large spatial heterogeneity, mainly in the middle reaches with a high intensity of human activities and the Parlung Zangbo River Basin, distributed with great glaciers. The results obtained in this study can provide reliable data support and technical means for exploring the spatio-temporal evolution mechanism of terrestrial water storage in data-scarce alpine regions.

scholarly journals Spatio-temporal variations in terrestrial water storage and its controlling factors in the Eastern Qinghai-Tibet Plateau

2020 ◽  
Author(s):  
Yu Zhu ◽  
Shiyin Liu ◽  
Ying Yi ◽  
Miaomiao Qi ◽  
Wanqiu Li ◽  
...  
Keyword(s):  
Hydrological Model ◽  
Water Storage ◽  
Temporal Variations ◽  
Controlling Factors ◽  
Tibet Plateau ◽  
Terrestrial Water Storage ◽  
Terrestrial Water ◽  
Spatio Temporal ◽  
Qinghai Tibet Plateau ◽  
Level 2

Abstract The nature of the heterogeneity of terrestrial water storage (TWS) in the Eastern Qinghai-Tibet Plateau (EQTP) is poorly understood because of the lack of validated datasets and the complex topographical conditions. In this study, monthly GRACE Level 2 Release 6 (RL06) products were employed to characterize TWS changes between April 2002 and August 2016 in the EQTP. Based on the observations and hydrological model output, the dominant factors contributing to the changes in TWS in sub-basins, and areas of TWS decrease and increase were analyzed systematically. We concluded that the TWS in the EQTP showed a slight decreasing trend from 2002 to 2016 with obvious spatial heterogeneity. The decrease in TWS may be attributed to the increase in evapotranspiration, which explains approximately 59% of the variations. In the region where a substantial decrease in TWS was observed, the trend primarily depended on evapotranspiration, and was certainly affected by glacial ablation. Moreover, the expansion of lakes supplemented by glaciers was the main cause of TWS change in the areas where TWS increased. A decrease in TWS mainly occurred in summer and was mainly due to the increase in evapotranspiration because of warming, an increase in wind speed, and a decrease in relative humidity.

scholarly journals Understanding terrestrial water storage variations in northern latitudes across scales

2017 ◽  
Author(s):  
Tina Trautmann ◽  
Sujan Koirala ◽  
Nuno Carvalhais ◽  
Annette Eicker ◽  
Manfred Fink ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Spatial Scales ◽  
Water Storage ◽  
Earth Observation ◽  
Snow Pack ◽  
Terrestrial Water Storage ◽  
Northern Latitudes ◽  
Terrestrial Water ◽  
Spatial Domains ◽  
Spatio Temporal

Abstract. The GRACE satellites provide signals of total terrestrial water storage (TWS) variations over large spatial domains at seasonal to inter-annual time scales. While the GRACE data have been extensively and successfully used to assess spatio-temporal changes in TWS, little effort has been made to quantify the relative contributions of snow pack, soil moisture and other components to the integrated TWS signal across northern latitudes, which is essential to gain a better insight into the underlying hydrological processes. Therefore, this study aims to assess which storage component dominates the spatio-temporal patterns of TWS variations in the humid regions of northern mid-to-high latitudes. To do so, we constrained a rather parsimonious hydrological model with multiple state-of-the-art Earth observation products including GRACE TWS anomalies, estimates of snow water equivalent, evapotranspiration fluxes, and gridded runoff estimates. The optimized model demonstrates good agreement with observed hydrological patterns, and was used to assess the relative contributions of solid (snow pack) versus liquid (soil moisture, retained water) storage components to total TWS variations. In particular, we analysed whether the same storage component dominates TWS variations at seasonal and inter-annual temporal scales, and whether the dominating component is consistent across small to large spatial scales. Consistent with previous studies, we show that snow dynamics control seasonal TWS variations across spatial scales in the northern mid-to-high latitudes. In contrast, we find that inter-annual variations of TWS are dominated by liquid water storages, comprising mainly of soil moisture. However, as the spatial domain over which the storages are averaged becomes larger, the relative contribution of snow to inter-annual TWS variations increases. This is due to a stronger spatial coherence of snow anomalies as opposed to spatially more heterogeneous liquid water anomalies that cancel out over large spatial domains. The findings first highlight the effectiveness of our model-data fusion approach that jointly interprets multiple Earth observation data streams with a simple model. Secondly, they reveal that the determinants of TWS variations in snow-affected northern latitudes are scale dependent. We conclude that inferred driving mechanisms of TWS cannot simply be transferred from one scale to another, which is of particular relevance for understanding the short and long-term variability of water resources.

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