Groundwater storage change in the Jinsha River basin from GRACE, hydrologic models, and in situ data

2020 ◽  
Author(s):  
Nengfang Chao
Keyword(s):  
Sediment Transport ◽  
River Basin ◽  
Human Activities ◽  
Water Storage ◽  
Hydrologic Models ◽  
Groundwater Storage ◽  
Jinsha River ◽  
In Situ Data ◽  
Storage Change

<p>Groundwater plays a major role in the hydrological processes driven by climate change and human activities, particularly in upper mountainous basins. The Jinsha River Basin (JRB) is the uppermost region of the Yangtze River and the largest hydropower production region in China. With the construction of artificial cascade reservoirs increasing in this region, the annual and seasonal flows are changing and affecting the water cycles. Here, we first infer the groundwater storage changes (GWSC), accounting for sediment transport in JRB, by combining the Gravity Recovery and Climate Experiment (GRACE) mission, hydrologic models and in situ data. The results indicate: (1) the average estimation of the GWSC trend, accounting for sediment transport in JRB, is 0.76±0.10 cm/year during the period 2003–2015, and the contribution of sediment transport accounts for 15%; (2) precipitation (P), evapotranspiration (ET), soil moisture change (SMC), GWSC and land water storage changes (LWSC) show clear seasonal cycles; the interannual trends of LWSC and GWSC increase, but P, runoff (R), surface water storage change (SWSC) and SMC decrease, and ET remains basically unchanged; (3) the main contributor to the increase in LWSC in JRB is GWSC, and the increased GWSC may be dominated by human activities, such as cascade damming, and climate variations (such as snow and glacier melt due to increased temperatures). This study can provide valuable information regarding JRB in China for understanding GWSC patterns and exploring their implications for regional water management.</p>

Groundwater Storage Change in the Jinsha River Basin from GRACE, Hydrologic Models, and In Situ Data

Ground Water ◽  
2019 ◽  
Author(s):  
Nengfang Chao ◽  
Gang Chen ◽  
Jian Li ◽  
Longwei Xiang ◽  
Zhengtao Wang ◽  
...  
Keyword(s):  
River Basin ◽  
Hydrologic Models ◽  
Groundwater Storage ◽  
Jinsha River ◽  
In Situ Data ◽  
Storage Change

Analysis of groundwater storage changes in main Polish river basins using GRACE observations, in-situ data, and hydrological and climate models

2020 ◽  
Author(s):  
Jolanta Nastula ◽  
Justyna Śliwińska ◽  
Zofia Rzepecka ◽  
Monika Birylo
Keyword(s):  
Climate Models ◽  
Water Storage ◽  
Coupled Model ◽  
Research Programme ◽  
Climate Data ◽  
Groundwater Storage ◽  
In Situ Data ◽  
Snow Water ◽  
Land Data Assimilation System

<p>The Gravity Recovery and Climate Experiment (GRACE) measurements have provided global observations of total water storage (TWS) changes at monthly intervals for almost 20 years. They are useful for estimating changes in groundwater storage (GWS) after extracting other water storage components like soil water or snow water.</p><p>In this study, we analyse the GWS variations of two main Polish basins, the Vistula and the Odra, using GRACE observations, in-situ wells measurements, GLDAS (Global Land Data Assimilation System) hydrological models, and CMIP5 (the World Climate Research Programme’s Coupled Model Intercomparison Project Phase 5) climate data. The research is conducted for the period between September 2006 and October 2015.</p><p>Here, TWS is taken directly from GRACE measurements and also computed from all considered models. GWS is obtained by subtracting the modelled sum of soil moisture and snow water from the GRACE-based TWS. The resultant GWS series are validated by comparing with appropriately calibrated in-situ wells measurements. For each GWS time series, the trends, spectra, amplitudes, and seasonal components were computed and analysed. The results suggest that in Poland there has been generally no major GWS depletion. The results can contribute toward selection of an appropriate model that, in combination with GRACE observations, would provide information on groundwater changes in regions with limited or inaccurate in-situ groundwater storage measurements.</p>

Exploring meso-scale soil water and groundwater storage changes within the USA through a Bayesian combination of GRACE data with monthly 12.5 km model simulations

2020 ◽  
Author(s):  
Nooshin Mehrnegar ◽  
Owen Jones ◽  
Michael B. Singer ◽  
Maike Schumacher ◽  
Thomas Jagdhuber ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Soil Water ◽  
Water Storage ◽  
Balance Model ◽  
Soil Water Storage ◽  
Groundwater Storage ◽  
In Situ Data ◽  
Grace Data ◽  
The Usa

<p>Climatic changes in precipitation intensity across the United States (USA) may also affect the frequency and magnitude of drought and flooding events, with potentially serious consequences for water supply across this country. Reliable estimation of water storage changes in the soil root zone and groundwater aquifers is important for predicting future water availability, drought and flood monitoring and weather prediction. In this study, we assimilate Terrestrial Water Storage (TWS) derived from Gravity Recovery and Climate Experiment (GRACE) satellite observations into a water balance model with 12.5-km spatial resolution. Our goal is to explore meso-scale surface and deep-level soil water storage, as well as groundwater changes within the USA covering the period 2003-2017. A new Bayesian approach is formulated and implemented in this study, which provides a dynamic solution for a state-space equation between hydrological model outputs and TWS observations, while considering their error structures. The unknown state parameters and temporal dependency between them are estimated through a combination of forward/backward Kalman Filtering and Markov Chain Monto Carlo (MCMC) methods.</p><p>The outputs of this methodological approach are evaluated using in situ data from historical USGS groundwater data (over 6600 wells) and the ESA CCI surface soil moisture data. The results indicate that our GRACE data assimilation generally improves the simulation of groundwater and soil moisture across the USA. For example, the long-term linear trend fitted to the Bayesian-derived groundwater and soil water storage are in a same direction as those of in situ data in 63% and 58% of regions studied across the USA, respectively. However, this vale is estimated less than 51% for both water storage estimates derived from the original water balance model, which suggesting that the data assimilation modulates the hydrological models to perform more realistically. The biggest improvements are observed in the southeast USA with considerably large inter-annual variability in precipitation, where modelled groundwater apparently responded too strongly to the changes in atmospheric forcing. The Bayesian data assimilation method also improves the temporal correlation coefficients between the in situ USGS and ESA CCI data and model outputs after merging with GRACE TWS estimates. For instance, the correlation coefficient between groundwater storage and USGS observation increased from -0.52 to 0.48 and from -0.28 to 0.25 in southeast and southwest of USA, respectively. Finally, we will explore changes in Bayesian-derived groundwater and soil water storage within the Florida, California and South of Mississippi regions and interpret their relations with climate-induced factors such as precipitation and ENSO index.</p><p><strong>Keywords:</strong> USA; Data Assimilation; Bayesian Method; Kalman Filtering; MCMC; GRACE; W3RA; groundwater storage; soil water storage; USGS; ESA CCI.</p><p> </p>

scholarly journals Improved Understanding of Groundwater Storage Changes under the Influence of River Basin Governance in Northwestern China Using GRACE Data

2021 ◽  
Vol 13 (14) ◽  
pp. 2672
Author(s):  
Xin Liu ◽  
Litang Hu ◽  
Kangning Sun ◽  
Zhengqiu Yang ◽  
Jianchong Sun ◽  
...  
Keyword(s):  
River Basin ◽  
Groundwater Level ◽  
Regional Scale ◽  
Water Storage ◽  
Northwestern China ◽  
In Situ Observation ◽  
Observation Data ◽  
Groundwater Storage ◽  
Grace Data

Groundwater is crucial for economic development in arid and semiarid areas. The Shiyang River Basin (SRB) has the most prominent water use issues in northwestern China, and overexploited groundwater resources have led to continuous groundwater-level decline. The key governance planning project of the SRB was issued in 2007. This paper synthetically combines remote-sensing data from Gravity Recovery and Climate Experiment (GRACE) data and precipitation, actual evapotranspiration, land use, and in situ groundwater-level data to evaluate groundwater storage variations on a regional scale. Terrestrial water storage anomalies (TWSA) and groundwater storage anomalies (GWSA), in addition to their influencing factors in the SRB since the implementation of the key governance project, are analyzed in order to evaluate the effect of governance. The results show that GRACE-derived GWS variations are consistent with in situ observation data in the basin, with a correlation coefficient of 0.68. The GWS in the SRB had a slow downward trend from 2003 to 2016, and this increased by 0.38 billion m³/year after 2018. As the meteorological data did not change significantly, the changes in water storage are mainly caused by human activities, which are estimated by using the principle of water balance. The decline in GWS in the middle and lower reaches of the SRB has been curbed since 2009 and has gradually rebounded since 2014. GWS decreased by 2.2 mm EWH (equivalent water height) from 2011 to 2016, which was 91% lower than that from 2007 to 2010. The cropland area in the middle and lower reaches of the SRB also stopped increasing after 2011 and gradually decreased after 2014, while the area of natural vegetation gradually increased, indicating that the groundwater level and associated ecology significantly recovered after the implementation of the project.

scholarly journals REMOTE SENSING OF WATER BALANCE IN PANTANAL

2019 ◽  
Vol 46 (3) ◽  
pp. 20
Author(s):  
Adriana Aparecida Moreira ◽  
Alice César Fassoni-Andrade ◽  
Anderson Luis Ruhoff ◽  
Rodrigo Cauduro Dias de Paiva
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
Water Storage ◽  
Remote Sensing Data ◽  
Northern Region ◽  
Sensing Data ◽  
In Situ Data ◽  
Storage Change ◽  
Hydrological Variables

Pantanal, located in the Upper Paraguay basin, is the world’s largest tropical wetland. The maintenance of this ecosystem depends on the water balance since precipitation is seasonal and high losses of water occur due to the high evapotranspiration. Water balance assessment using in situ data is still a challenge due to the large extension of the area and the complexity to be represented. In this study, the water balance in the Upper Paraguay basin was investigated based on hydrological variables derived from remote sensing data. Precipitation, evapotranspiration, and water storage change data were estimated with accuracy by the water balance, but the same was not possible for the discharge. However, high uncertainties in the estimates were verified, mainly during the rainy season. The remote sensing data allowed the identification of the seasonality of hydrological variables in the Pantanal system and in the different regions of the basin: Chaco, Pantanal and Planalto. Water deficit in the basin was observed from March/April to September as well as a positive water balance due to precipitation during the rest of the year. The spatial analysis of the basin showed that in the northern region, the precipitation, the evapotranspiration, and the water storage variation are higher than in the southern region. Results demonstrated that remote sensing data can help in the comprehension of hydrological systems operation, especially in large wetland regions.

scholarly journals Identification of the Impacts of Climate Changes and Human Activities on Runoff in the Jinsha River Basin, China

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Xiaowan Liu ◽  
Dingzhi Peng ◽  
Zongxue Xu
Keyword(s):  
Water Balance ◽  
River Basin ◽  
Human Activities ◽  
Climate Changes ◽  
Balance Method ◽  
Variation Method ◽  
Rainfall Runoff ◽  
Jinsha River ◽  
Water Balance Method ◽  
Double Mass

Quantifying the impacts of climate changes and human activities on runoff has received extensive attention, especially for the regions with significant elevation difference. The contributions of climate changes and human activities to runoff were analyzed using rainfall-runoff relationship, double mass curve, slope variation, and water balance method during 1961–2010 at the Jinsha River basin, China. Results indicate that runoff at upstream and runoff at midstream are both dominated by climate changes, and the contributions of climate changes to runoff are 63%~72% and 53%~68%, respectively. At downstream, climate changes account for only 13%~18%, and runoff is mainly controlled by human activities, contributing 82%~87%. The availability and stability of results were compared and analyzed in the four methods. Results in slope variation, double mass curve, and water balance method except rainfall-runoff relationship method are of good agreement. And the rainfall-runoff relationship, double mass curve, and slope variation method are all of great stability. The four methods and availability evaluation of them could provide a reference to quantification in the contributions of climate changes and human activities to runoff at similar basins in the future.

Estimating the water balance and uncertainty bounds in a highly groundwater-dependent and data-scarce areas: An example for the upper Citarum basin

2021 ◽  
Author(s):  
Steven Reinaldo Rusli ◽  
Albrecht Weerts ◽  
Victor Bense
Keyword(s):  
Water Balance ◽  
Water Storage ◽  
Total Water ◽  
Groundwater Abstraction ◽  
Water Balance Components ◽  
Groundwater Storage ◽  
Actual Evaporation ◽  
Basin Scale ◽  
Basin Water ◽  
Storage Change

<p>In this study, we estimate the water balance components of a highly groundwater-dependent and hydrological data-scarce basin of the upper reaches of the Citarum river in West Java, Indonesia. Firstly, we estimate the groundwater abstraction volumes based on population size and a review of literature (0.57mm/day). Estimates of other components like rainfall, actual evaporation, discharge, and total water storage changes are derived from global datasets and are simulated using a distributed hydrological wflow_sbm model which yields additional estimates of discharge, actual evaporation, and total water storage change. We compare each basin water balance estimate as well as quantify the uncertainty of some of the components using the Extended Triple Collocation (ETC) method.</p><p>The ETC application on four different rainfall estimates suggests a preference of using the CHIRPS product as the input to the water balance components estimates as it delivers the highest r<sup>2</sup>  and the lowest RMSE compared to three other sources. From the different data sources and results of the distributed hydrological modeling using CHIRPS as rainfall forcing, we estimate a positive groundwater storage change between 0.12 mm/day - 0.60 mm/day. These results are in agreement with groundwater storage change estimates based upon GRACE gravimetric satellite data, averaged at 0.25 mm/day. The positive groundwater storage change suggests sufficient groundwater recharge occurs compensating for groundwater abstraction. This conclusion seems in agreement with the observation since 2005, although measured in different magnitudes. To validate and narrow the estimated ranges of the basin water storage changes, a devoted groundwater model is necessary to be developed. The result shall also aid in assessing the current and future basin-scale groundwater level changes to support operational water management and policy in the Upper Citarum basin.</p>

scholarly journals Recent changes in terrestrial water storage in the Upper Nile Basin: an evaluation of commonly used gridded GRACE products

2017 ◽  
Vol 21 (9) ◽  
pp. 4533-4549 ◽  
Author(s):  
Mohammad Shamsudduha ◽  
Richard G. Taylor ◽  
Darren Jones ◽  
Laurent Longuevergne ◽  
Michael Owor ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Lake Victoria ◽  
Water Storage ◽  
Terrestrial Water Storage ◽  
Nile Basin ◽  
Lake Victoria Basin ◽  
Groundwater Storage ◽  
Terrestrial Water ◽  
Substantial Uncertainty

Abstract. GRACE (Gravity Recovery and Climate Experiment) satellite data monitor large-scale changes in total terrestrial water storage (ΔTWS), providing an invaluable tool where in situ observations are limited. Substantial uncertainty remains, however, in the amplitude of GRACE gravity signals and the disaggregation of TWS into individual terrestrial water stores (e.g. groundwater storage). Here, we test the phase and amplitude of three GRACE ΔTWS signals from five commonly used gridded products (i.e. NASA's GRCTellus: CSR, JPL, GFZ; JPL-Mascons; GRGS GRACE) using in situ data and modelled soil moisture from the Global Land Data Assimilation System (GLDAS) in two sub-basins (LVB: Lake Victoria Basin; LKB: Lake Kyoga Basin) of the Upper Nile Basin. The analysis extends from January 2003 to December 2012, but focuses on a large and accurately observed reduction in ΔTWS of 83 km3 from 2003 to 2006 in the Lake Victoria Basin. We reveal substantial variability in current GRACE products to quantify the reduction of ΔTWS in Lake Victoria that ranges from 80 km3 (JPL-Mascons) to 69 and 31 km3 for GRGS and GRCTellus respectively. Representation of the phase in TWS in the Upper Nile Basin by GRACE products varies but is generally robust with GRGS, JPL-Mascons, and GRCTellus (ensemble mean of CSR, JPL, and GFZ time-series data), explaining 90, 84, and 75 % of the variance respectively in "in situ" or "bottom-up" ΔTWS in the LVB. Resolution of changes in groundwater storage (ΔGWS) from GRACE ΔTWS is greatly constrained by both uncertainty in changes in soil-moisture storage (ΔSMS) modelled by GLDAS LSMs (CLM, NOAH, VIC) and the low annual amplitudes in ΔGWS (e.g. 1.8–4.9 cm) observed in deeply weathered crystalline rocks underlying the Upper Nile Basin. Our study highlights the substantial uncertainty in the amplitude of ΔTWS that can result from different data-processing strategies in commonly used, gridded GRACE products; this uncertainty is disregarded in analyses of ΔTWS and individual stores applying a single GRACE product.

scholarly journals Recent changes in terrestrial water storage in the Upper Nile Basin: an evaluation of commonly used gridded GRACE products

2017 ◽  
Author(s):  
Mohammad Shamsudduha ◽  
Richard G. Taylor ◽  
Darren Jones ◽  
Laurent Longuevergne ◽  
Michael Owor ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Lake Victoria ◽  
Water Storage ◽  
Series Data ◽  
Terrestrial Water Storage ◽  
Nile Basin ◽  
Groundwater Storage ◽  
Terrestrial Water ◽  
Substantial Uncertainty

Abstract. GRACE (Gravity Recovery and Climate Experiment) satellite data monitor large-scale changes in total terrestrial water storage (ΔTWS) providing an invaluable tool where in situ observations are limited. Substantial uncertainty remains, however, in the amplitude of GRACE gravity signals and the disaggregation of ΔTWS into individual terrestrial water stores (e.g. groundwater storage). Here, we test the phase and amplitude of GRACE ΔTWS signals from 5 commonly-used gridded products (i.e., NASA's GRCTellus: CSR, JPL GFZ; JPL-Mascons; GRGS GRACE) using in situ data and modelled soil-moisture from the Global Land Data Assimilation System (GLDAS). The focus of this analysis is a large and accurately observed reduction in ΔTWS of 75 km3 from 2004 to 2006 in Lake Victoria in the Upper Nile Basin. We reveal substantial variability in current GRACE products to quantify the reduction of ΔTWS in Lake Victoria that ranges from 68 km3 (GRGS) to 50 km3 and 26 km3 for JPL-Mascons and GRCTellus, respectively. Representation of the phase in ΔTWS in the Upper Nile Basin by GRACE products varies but is generally robust with GRGS, JPL-Mascons and GRCTellus (ensemble mean of CSR, JPL and GFZ time-series data) explaining 91 %, 85 %, and 77 % of the variance, respectively, in in-situ ΔTWS. Resolution of changes in groundwater storage (ΔGWS) from GRACE ΔTWS is greatly constrained by both uncertainty in modelled changes in soil-moisture storage (ΔSMS) and the low annual amplitudes in ΔGWS (e.g., 3.5 to 4.4 cm) observed in deeply weathered crystalline rocks underlying the Upper Nile Basin. Our study highlights the substantial uncertainty in the amplitude of ΔTWS that can result from different data-processing strategies in commonly used, gridded GRACE products.

A Comparative Study on Calculating Water Storage Change of River Basin Based on Two Methods

2014 ◽  
Vol 1030-1032 ◽  
pp. 465-471
Author(s):  
Min Xu ◽  
Jian Wang ◽  
Qiu Dong Zhao
Keyword(s):  
River Basin ◽  
Yangtze River ◽  
Yellow River ◽  
Yangtze River Basin ◽  
Water Storage ◽  
Critical Issue ◽  
Frozen Soil ◽  
Global Land ◽  
Grace Satellites ◽  
Storage Change

Water scarcity is a critical issue in most regions of China; however, river basin groundwater monitoring is extremely limited.This study evaluates the ability of the GRACE satellites and Global Land Data Assimilation System(GLDAS) to monitor groundwater storage in the Yellow River Basin and Yangtze River Basin, China, which is subjected to intense irrigation, production and living. The simulated terrestrial water storage change data which was calculateed by Global Land Data Assimilate System was used to compare the accuracy of GRACE data. Results show that both two datas show significant seasonal cycle in the Yangtze River and Yellow River (except frozen soil), the correlation is 0.89 and 0.84(p<0.05).Two methods have some differences on grid scales, the results which was retrieved by GRACE satellites have better continuity than simulated by GLDAS. GRACE inversion results reflect deeper water storge change in soil, and GLDAS simply reflect surface soil moisture.

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