scholarly journals TOTAL WATER STORAGE ON TERRITORY OF POLAND – COMPARISON AND ANALYSIS OF GRACE AND GLDAS VALUES

Author(s):  
Zofia Rzepecka
2021 ◽  
Author(s):  
Markus Hrachowitz ◽  
Petra Hulsman ◽  
Hubert Savenije

<p>Hydrological models are often calibrated with respect to flow observations at the basin outlet. As a result, flow predictions may seem reliable but this is not necessarily the case for the spatiotemporal variability of system-internal processes, especially in large river basins. Satellite observations contain valuable information not only for poorly gauged basins with limited ground observations and spatiotemporal model calibration, but also for stepwise model development. This study explored the value of satellite observations to improve our understanding of hydrological processes through stepwise model structure adaption and to calibrate models both temporally and spatially. More specifically, satellite-based evaporation and total water storage anomaly observations were used to diagnose model deficiencies and to subsequently improve the hydrological model structure and the selection of feasible parameter sets. A distributed, process based hydrological model was developed for the Luangwa river basin in Zambia and calibrated with respect to discharge as benchmark. This model was modified stepwise by testing five alternative hypotheses related to the process of upwelling groundwater in wetlands, which was assumed to be negligible in the benchmark model, and the spatial discretization of the groundwater reservoir. Each model hypothesis was calibrated with respect to 1) discharge and 2) multiple variables simultaneously including discharge and the spatiotemporal variability in the evaporation and total water storage anomalies. The benchmark model calibrated with respect to discharge reproduced this variable well, as also the basin-averaged evaporation and total water storage anomalies. However, the evaporation in wetland dominated areas and the spatial variability in the evaporation and total water storage anomalies were poorly modelled. The model improved the most when introducing upwelling groundwater flow from a distributed groundwater reservoir and calibrating it with respect to multiple variables simultaneously. This study showed satellite-based evaporation and total water storage anomaly observations provide valuable information for improved understanding of hydrological processes through stepwise model development and spatiotemporal model calibration.</p>


2021 ◽  
Vol 48 (8) ◽  
Author(s):  
Fupeng Li ◽  
Jürgen Kusche ◽  
Nengfang Chao ◽  
Zhengtao Wang ◽  
Anno Löcher

2021 ◽  
Author(s):  
Steven Reinaldo Rusli ◽  
Albrecht Weerts ◽  
Victor Bense

<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>


2012 ◽  
Vol 16 (9) ◽  
pp. 3083-3099 ◽  
Author(s):  
H. Xie ◽  
L. Longuevergne ◽  
C. Ringler ◽  
B. R. Scanlon

Abstract. Irrigation development is rapidly expanding in mostly rainfed Sub-Saharan Africa. This expansion underscores the need for a more comprehensive understanding of water resources beyond surface water. Gravity Recovery and Climate Experiment (GRACE) satellites provide valuable information on spatio-temporal variability in water storage. The objective of this study was to calibrate and evaluate a semi-distributed regional-scale hydrologic model based on the Soil and Water Assessment Tool (SWAT) code for basins in Sub-Saharan Africa using seven-year (July 2002–April 2009) 10-day GRACE data and multi-site river discharge data. The analysis was conducted in a multi-criteria framework. In spite of the uncertainty arising from the tradeoff in optimising model parameters with respect to two non-commensurable criteria defined for two fluxes, SWAT was found to perform well in simulating total water storage variability in most areas of Sub-Saharan Africa, which have semi-arid and sub-humid climates, and that among various water storages represented in SWAT, water storage variations in soil, vadose zone and groundwater are dominant. The study also showed that the simulated total water storage variations tend to have less agreement with GRACE data in arid and equatorial humid regions, and model-based partitioning of total water storage variations into different water storage compartments may be highly uncertain. Thus, future work will be needed for model enhancement in these areas with inferior model fit and for uncertainty reduction in component-wise estimation of water storage variations.


2021 ◽  
Vol 25 (2) ◽  
pp. 957-982 ◽  
Author(s):  
Petra Hulsman ◽  
Hubert H. G. Savenije ◽  
Markus Hrachowitz

Abstract. Satellite observations can provide valuable information for a better understanding of hydrological processes and thus serve as valuable tools for model structure development and improvement. While model calibration and evaluation have in recent years started to make increasing use of spatial, mostly remotely sensed information, model structural development largely remains to rely on discharge observations at basin outlets only. Due to the ill-posed inverse nature and the related equifinality issues in the modelling process, this frequently results in poor representations of the spatio-temporal heterogeneity of system-internal processes, in particular for large river basins. The objective of this study is thus to explore the value of remotely sensed, gridded data to improve our understanding of the processes underlying this heterogeneity and, as a consequence, their quantitative representation in models through a stepwise adaptation of model structures and parameters. For this purpose, a distributed, process-based hydrological model was developed for the study region, the poorly gauged Luangwa River basin. As a first step, this benchmark model was calibrated to discharge data only and, in a post-calibration evaluation procedure, tested for its ability to simultaneously reproduce (1) the basin-average temporal dynamics of remotely sensed evaporation and total water storage anomalies and (2) their temporally averaged spatial patterns. This allowed for the diagnosis of model structural deficiencies in reproducing these temporal dynamics and spatial patterns. Subsequently, the model structure was adapted in a stepwise procedure, testing five additional alternative process hypotheses that could potentially better describe the observed dynamics and pattern. These included, on the one hand, the addition and testing of alternative formulations of groundwater upwelling into wetlands as a function of the water storage and, on the other hand, alternative spatial discretizations of the groundwater reservoir. Similar to the benchmark, each alternative model hypothesis was, in a next step, calibrated to discharge only and tested against its ability to reproduce the observed spatio-temporal pattern in evaporation and water storage anomalies. In a final step, all models were re-calibrated to discharge, evaporation and water storage anomalies simultaneously. The results indicated that (1) the benchmark model (Model A) could reproduce the time series of observed discharge, basin-average evaporation and total water storage reasonably well. In contrast, it poorly represented time series of evaporation in wetland-dominated areas as well as the spatial pattern of evaporation and total water storage. (2) Stepwise adjustment of the model structure (Models B–F) suggested that Model F, allowing for upwelling groundwater from a distributed representation of the groundwater reservoir and (3) simultaneously calibrating the model with respect to multiple variables, i.e. discharge, evaporation and total water storage anomalies, provided the best representation of all these variables with respect to their temporal dynamics and spatial patterns, except for the basin-average temporal dynamics in the total water storage anomalies. It was shown that satellite-based evaporation and total water storage anomaly data are not only valuable for multi-criteria calibration, but can also play an important role in improving our understanding of hydrological processes through the diagnosis of model deficiencies and stepwise model structural improvement.


2020 ◽  
Vol 12 (23) ◽  
pp. 3913
Author(s):  
Claudia Notarnicola

The quantification of snow cover changes and of the related water resources in mountain areas has a key role for understanding the impact on several sectors such as ecosystem services, tourism and energy production. By using NASA-Moderate Resolution Imaging Spectroradiometer (MODIS) images from 2000 to 2018, this study analyzes changes in snow cover in the High Mountain Asia region and compares them with global mountain areas. Globally, snow cover extent and duration are declining with significant trends in around 78% of mountain areas, and the High Mountain Asia region follows similar trends in around 86% of the areas. As an example, Shaluli Shan area in China shows significant negative trends for both snow cover extent and duration, with −11.4% (confidence interval: −17.7%, −5.5%) and −47.3 days (confidence interval: −70.4 days, −24.4 days) at elevations >5500 m a.s.l. respectively. In spring, an earlier snowmelt of −13.5 days (confidence interval: −24.3 days, −2.0 days) in 4000–5500 m a.s.l. is detected. On the other side, Tien Shan area shows an earlier snow onset of −28.8 days (confidence interval: −44.3 days, −8.2 days) between 2500 and 4000 m a.s.l., governed by decreasing temperature and increasing snowfall. In the current analysis, the Tibetan Plateau shows no significant changes. Regarding water resources, by using Gravity Recovery and Climate Experiment (GRACE) data it was found that around 50% of areas in the High Mountain Asia region and 30% at global level are suffering from significant negative temporal trends of total water storage (including groundwater, soil moisture, surface water, snow, and ice) in the period 2002–2015. In the High Mountain Asia region, this negative trend involves around 54% of the areas during spring period, while at a global level this percentage lies between 25% and 30% for all seasons. Positive trends for water storage are detected in a maximum 10% of the areas in High Mountain Asia region and in around 20% of the areas at global level. Overall snow mass changes determine a significant contribution to the total water storage changes up to 30% of the areas in winter and spring time over 2002–2015.


Author(s):  
Alexander Y. Sun ◽  
Bridget R. Scanlon ◽  
Himanshu Save ◽  
Ashraf Rateb

2019 ◽  
Vol 11 (3) ◽  
pp. 335 ◽  
Author(s):  
Kishore Pangaluru ◽  
Isabella Velicogna ◽  
Geruo A ◽  
Yara Mohajerani ◽  
Enrico Ciracì ◽  
...  

This study investigates the spatial and temporal variability of the soil moisture in India using Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) gridded datasets from June 2002 to April 2017. Significant relationships between soil moisture and different land surface–atmosphere fields (Precipitation, surface air temperature, total cloud cover, and total water storage) were studied, using maximum covariance analysis (MCA) to extract dominant interactions that maximize the covariance between two fields. The first leading mode of MCA explained 56%, 87%, 81%, and 79% of the squared covariance function (SCF) between soil moisture with precipitation (PR), surface air temperature (TEM), total cloud count (TCC), and total water storage (TWS), respectively, with correlation coefficients of 0.65, −0.72, 0.71, and 0.62. Furthermore, the covariance analysis of total water storage showed contrasting patterns with soil moisture, especially over northwest, northeast, and west coast regions. In addition, the spatial distribution of seasonal and annual trends of soil moisture in India was estimated using a robust regression technique for the very first time. For most regions in India, significant positive trends were noticed in all seasons. Meanwhile, a small negative trend was observed over southern India. The monthly mean value of AMSR soil moisture trend revealed a significant positive trend, at about 0.0158 cm3/cm3 per decade during the period ranging from 2002 to 2017.


2019 ◽  
Vol 11 (24) ◽  
pp. 2949 ◽  
Author(s):  
Justyna Śliwińska ◽  
Monika Birylo ◽  
Zofia Rzepecka ◽  
Jolanta Nastula

The Gravity Recovery and Climate Experiment (GRACE) observations have provided global observations of total water storage (TWS) changes at monthly intervals for over 15 years, which can be useful for estimating changes in GWS after extracting other water storage components. In this study, we analyzed the TWS and groundwater storage (GWS) variations of the main Polish basins, the Vistula and the Odra, using GRACE observations, in-situ data, 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 was conducted for the period between September 2006 and October 2015. The TWS data were taken directly from GRACE measurements and also computed from four GLDAS (VIC, CLM, MOSAIC, and NOAH) and six CMIP5 (FGOALS-g2, GFDL-ESM2G, GISS-E2-H, inmcm4, MIROC5, and MPI-ESM-LR) models. The GWS data were obtained by subtracting the model TWS from the GRACE TWS. The resulting GWS values were compared with in-situ well measurements calibrated using porosity coefficients. For each time series, the trends, spectra, amplitudes, and seasonal components were computed and analyzed. The results suggest that in Poland there has been generally no major TWS or GWS depletion. Our results indicate that when comparing TWS values, better compliance with GRACE data was obtained for GLDAS than for CMIP5 models. However, the GWS analysis showed better consistency of climate models with the well results. The results can contribute toward selection of an appropriate model that, in combination with global GRACE observations, would provide information on groundwater changes in regions with limited or inaccurate ground measurements.


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