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Готові списки джерел за темами / Terrestrial Water Storage

Добірка наукової літератури з теми "Terrestrial Water Storage"

Автор: Grafiati

Опубліковано: 6 вересня 2023

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Статті в журналах з теми "Terrestrial Water Storage"

1

Kuehne, John, and Clark R. Wilson. "Terrestrial water storage and polar motion." Journal of Geophysical Research: Solid Earth 96, B3 (March 10, 1991): 4337–45. http://dx.doi.org/10.1029/90jb02573.

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2

Savin, Igor Yu, and Bakhytnur S. Gabdullin. "Specifics of long-term dynamics of terrestrial water storage detected using GRACE satellite in Belgorod region." RUDN Journal of Agronomy and Animal Industries 15, no. 4 (December 15, 2020): 363–74. http://dx.doi.org/10.22363/2312-797x-2020-15-4-363-374.

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GRACE monthly satellite data for the period from 2002 to 2016 were used to analyze the longterm dynamics of the terrestrial water storage in the Belgorod region of Russia. The correlation of satellite data with climatic water balance with a lag varying on the territory from 2 to 4 months was revealed. There was found a stable tendency to decrease in terrestrial water storage, and predominance of negative values on the territory of the Belgorod region since 2008. The minimum attains the lowest values in comparison with the whole studied period. However, seasonality of the changes is maintained throughout the entire analyzed time series. The frequency of changes in the terrestrial water storage throughout the entire area is not very clear: only the long-term maximum of the terrestrial water storage of the territory in 2006 is well expressed. Another, less pronounced local maximum was observed in 2013. Local long-term minima of the terrestrial water storage of the territory were in 2002, 2009 and 2015. There is a positive trend in the amplitude of seasonal fluctuations in the terrestrial water storage of the territory: the amplitude has been constantly increasing in recent years. The territory of the Belgorod region has negative long-term trend of terrestrial water storage with their rather large spatial variation. The angle of inclination of the trend decreases from north-west to south-east in the region. GRACE satellite data can serve as a fairly reliable detection indicator of the trend of terrestrial water storage in large areas.

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3

Hirschi, Martin, and Sonia I. Seneviratne. "Basin-scale water-balance dataset (BSWB): an update." Earth System Science Data 9, no. 1 (March 30, 2017): 251–58. http://dx.doi.org/10.5194/essd-9-251-2017.

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Abstract. This paper presents an update of a basin-scale diagnostic dataset of monthly variations in terrestrial water storage for large river basins worldwide (BSWB v2016, doi:10.5905/ethz-1007-82). Terrestrial water storage comprises all forms of water storage on land surfaces, and its seasonal and inter-annual variations are mostly determined by soil moisture, groundwater, snow cover, and surface water. The dataset presented is derived using a combined atmospheric and terrestrial water-balance approach with conventional streamflow measurements and reanalysis data of atmospheric moisture flux convergence. It extends a previous, existing version of the dataset (Mueller et al., 2011) temporally and spatially.

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4

Trautmann, Tina, Sujan Koirala, Nuno Carvalhais, Annette Eicker, Manfred Fink, Christoph Niemann, and Martin Jung. "Understanding terrestrial water storage variations in northern latitudes across scales." Hydrology and Earth System Sciences 22, no. 7 (July 27, 2018): 4061–82. http://dx.doi.org/10.5194/hess-22-4061-2018.

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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.

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5

Trautmann, Tina, Sujan Koirala, Nuno Carvalhais, Andreas Güntner, and Martin Jung. "The importance of vegetation in understanding terrestrial water storage variations." Hydrology and Earth System Sciences 26, no. 4 (February 24, 2022): 1089–109. http://dx.doi.org/10.5194/hess-26-1089-2022.

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Abstract. So far, various studies have aimed at decomposing the integrated terrestrial water storage variations observed by satellite gravimetry (GRACE, GRACE-FO) with the help of large-scale hydrological models. While the results of the storage decomposition depend on model structure, little attention has been given to the impact of the way that vegetation is represented in these models. Although vegetation structure and activity represent the crucial link between water, carbon, and energy cycles, their representation in large-scale hydrological models remains a major source of uncertainty. At the same time, the increasing availability and quality of Earth-observation-based vegetation data provide valuable information with good prospects for improving model simulations and gaining better insights into the role of vegetation within the global water cycle. In this study, we use observation-based vegetation information such as vegetation indices and rooting depths for spatializing the parameters of a simple global hydrological model to define infiltration, root water uptake, and transpiration processes. The parameters are further constrained by considering observations of terrestrial water storage anomalies (TWS), soil moisture, evapotranspiration (ET) and gridded runoff (Q) estimates in a multi-criteria calibration approach. We assess the implications of including varying vegetation characteristics on the simulation results, with a particular focus on the partitioning between water storage components. To isolate the effect of vegetation, we compare a model experiment in which vegetation parameters vary in space and time to a baseline experiment in which all parameters are calibrated as static, globally uniform values. Both experiments show good overall performance, but explicitly including varying vegetation data leads to even better performance and more physically plausible parameter values. The largest improvements regarding TWS and ET are seen in supply-limited (semi-arid) regions and in the tropics, whereas Q simulations improve mainly in northern latitudes. While the total fluxes and storages are similar, accounting for vegetation substantially changes the contributions of different soil water storage components to the TWS variations. This suggests an important role of the representation of vegetation in hydrological models for interpreting TWS variations. Our simulations further indicate a major effect of deeper moisture storages and groundwater–soil moisture–vegetation interactions as a key to understanding TWS variations. We highlight the need for further observations to identify the adequate model structure rather than only model parameters for a reasonable representation and interpretation of vegetation–water interactions.

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6

Hatch, Mike. "Environmental geophysics/ Grace mapping of terrestrial water storage." Preview 2019, no. 202 (September 3, 2019): 38–39. http://dx.doi.org/10.1080/14432471.2019.1671159.

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7

Balcerak, Ernie. "Predicting fire activity using terrestrial water storage data." Eos, Transactions American Geophysical Union 94, no. 21 (May 21, 2013): 196. http://dx.doi.org/10.1002/2013eo210015.

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8

Chinnasamy, Pennan, and Revathi Ganapathy. "Long-term variations in water storage in Peninsular Malaysia." Journal of Hydroinformatics 20, no. 5 (November 7, 2017): 1180–90. http://dx.doi.org/10.2166/hydro.2017.043.

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Abstract Information on ongoing climate change impacts on water availability is limited for Asian regions, particularly for Peninsular Malaysia. Annual flash floods are common during peak monsoon seasons, while the dry seasons are hit by droughts, leading to socio-economic stress. This study, for the first time, analyzed the long-term trends (14 years, from 2002 to 2014) in terrestrial water storage and groundwater storage for Peninsular Malaysia, using Gravity Recovery And Climate Experiment data. Results indicate a decline in net terrestrial and groundwater storage over the last decade. Spatially, the northern regions are more affected by droughts, while the southern regions have more flash floods. Groundwater storage trends show strong correlations to the monsoon seasons, indicating that most of the shallow aquifer groundwater is used. Results also indicate that, with proper planning and management, excess monsoon/flash flood water can be stored in water storage structures up to the order of 87 billion liters per year. This can help in dry season water distribution and water transfer projects. Findings from this study can expand the understanding of ongoing climate change impacts on groundwater storage and terrestrial water storage, and can lead to better management of water resources in Peninsular Malaysia.

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9

Meng, Gaojia, Guofeng Zhu, Jiawei Liu, Kailiang Zhao, Siyu Lu, Rui Li, Dongdong Qiu, Yinying Jiao, Longhu Chen, and Niu Sun. "GRACE Data Quantify Water Storage Changes in the Shiyang River Basin, an Inland River in the Arid Zone." Remote Sensing 15, no. 13 (June 21, 2023): 3209. http://dx.doi.org/10.3390/rs15133209.

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Global changes and human activities have significantly altered water cycle processes and water resource patterns in inland river basins in arid zones. New tools are needed to conduct more comprehensive and scientific assessments of basin water cycle processes and water resource patterns. Based on GRACE satellite and Landsat data, this study investigated terrestrial water storage changes and surface water area in the Shiyang River Drainage Basin from 2002 to 2021. It explored the effects of climate change and water conservancy construction on terrestrial water storage changes in the basin. The results of the study show that, although the surface water quantity in the Shiyang River basin has increased in the past 20 years, the overall decreasing trend of terrestrial water storage in the basin of the Shiyang River has an interannual decreasing rate of 0.01 cm/a. The decreasing trend of water storage in the midstream and downstream areas is more prominent. The change in precipitation controls the change in water storage in the Shiyang River Drainage Basin. Artificial water transfer has changed the spatial distribution of water resources in the basin of the Shiyang River. However, it still has not completely reversed the trend of decreasing water storage in the middle and lower reaches of the Shiyang River.

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10

He, Yanfeng, Jinghua Xiong, Shenglian Guo, Sirui Zhong, Chuntao Yu, and Shungang Ma. "Using Multi-Source Data to Assess the Hydrologic Alteration and Extremes under a Changing Environment in the Yalong River Basin." Water 15, no. 7 (April 1, 2023): 1357. http://dx.doi.org/10.3390/w15071357.

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Climate change and human activities are two important factors in the changing environment that affect the variability of the hydrological cycle and river regime in the Yalong River basin. This paper analyzed the hydrological alteration and extremes in the Yalong River basin based on multi-source satellite data, and projected the hydrological response under different future climate change scenarios using the CwatM hydrological model. The results show that: (1) The overall change in hydrological alteration at Tongzilin station was moderate during the period of 1998–2011 and severe during the period of 2012–2020. (2) Precipitation (average 781 mm/a) is the dominant factor of water cycle on a monthly scale, which can explain the temporal variability of runoff, evaporation, and terrestrial water storage, while terrestrial water storage is also simultaneously regulated by runoff and evaporation. (3) The GRACE data are comparable with regional water resource bulletins. The terrestrial water storage is mainly regulated by surface water (average 1062 × 108 m3), while the contribution of groundwater (average 298 × 108 m3) is relatively small. (4) The evaporation and runoff processes will intensify in the future due to climate warming and increasing precipitation (~10%), and terrestrial water storage will be depleted. The magnitude of change will increase with the enhancement of emission scenarios.

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Більше джерел

Дисертації з теми "Terrestrial Water Storage"

1

Rodell, Matthew. "Estimating changes in terrestrial water storage /." Full text (PDF) from UMI/Dissertation Abstracts International, 2000. http://wwwlib.umi.com/cr/utexas/fullcit?p3004367.

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2

Hirschi, Martin. "Seasonal variations in terrestrial water storage : diagnosis and climate model analyses /." Zürich : ETH, 2006. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=16902.

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3

Chen, Yiqun. "Recovery of terrestrial water storage change from low-low satellite-to-satellite tracking." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1196098152.

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4

Zhang, Liangjing [Verfasser]. "Terrestrial water storage from GRACE gravity data for hydrometeorological applications / Liangjing Zhang." Berlin : Freie Universität Berlin, 2017. http://d-nb.info/1127046209/34.

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5

Najmaddin, Peshawa Mustafa. "Simulating river runoff and terrestrial water storage variability in data-scarce semi-arid catchments using remote sensing." Thesis, University of Leicester, 2017. http://hdl.handle.net/2381/40771.

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Remotely sensed data can be used as an alternative to ground based observations to predict river discharge and water storage variability. The latter dataset used consists of meteorological records from four stations (2003-2014) and daily river discharge records from one stations (2010-2014). A model was developed named ‘Leicester Model for Semi-Arid Region’ (LEMSAR). It was applied in the semi-arid Kurdistan region of Northern Iraq. TRMM Multi-satellite Precipitation Analysis (TMPA) data products (TMPA 3B42 and 3B42RT) were used with and without a bias correction. The uncorrected TMPA underestimated observed mean catchment rainfall by 10% compared to corrected data with 0.7%. Four methods of computing reference evapotranspiration (ETₒ) were applied which include Hargreaves-Samani (HS), Jensen-Haise (JH), McGuinness-Bordne(MB) and FAO Penman Monteith(PM). The variables utilised are air temperature, relative humidity and cloud cover fraction from the Atmospheric Infrared Sounder / Advanced Microwave Sounding (AIRS/AMSU), and wind speed at 10 m height from MERRA (Modern-Era Retrospective Analysis for Research and Application). Compared to ETₒ-G (PM), ETₒ-RS (HS) underestimated ETₒ-G (PM) by 3% while JH and MB overestimated by 8% to 40% at different stations. Nash-Sutcliffe Efficiency (NSE) for the LEMSAR fit with the observed hydrograph was 0.75, for a calibration period (2010-2011) using gauged rainfall data with ETₒ-G (PM). Model validation performance (2012–2014) was best (NSE =0.61) using the corrected 3B42 data with ETₒ-RS HS and poorest when driven by uncorrected 3B42RT data with ETₒ-RS JH (NSE =0.07). Data from the Gravity Recovery and Climate Experiment (GRACE: 2003-2014) were used to evaluate total water storage variability and compared with that of well observations data and LEMSAR. Trends in GRACE_TWSA were approximately -33.72 mm y-1 for the Lesser Zab catchment and -35.4 mm y-1 for the Hawler well monitoring zone while LEMSAR predicted 15 mm y-1 for the Lesser Zab Catchment. This suggest that reduction in recharge (modelled by LEMSAR) may only be responsible for about 50% of the reduction in groundwater storage. The rest could be the result of increased abstraction in response to the drought. Overall, results suggest that RS data can be usefully employed to simulate river discharge and to evaluate terrestrial water storage variability in semi-arid areas. It has the potential to help decision-makers improve water resources management.

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6

Arciniega-Esparza, Saúl, José Agustín Breña-Naranjo, and Peter A. Troch. "On the connection between terrestrial and riparian vegetation: the role of storage partitioning in water-limited catchments." WILEY-BLACKWELL, 2017. http://hdl.handle.net/10150/622781.

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7

Hultin, Eriksson Elin. "Quantification of Terrestrial CO2 Sources to a Headwater Streamin a Boreal Forest Catchment." Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-305435.

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Carbon Dioxide (CO2) emissions from streams are a significant component of the global carbon cycle.Terrestrial export of CO2 through runoff is increasingly recognized as a major source of CO2 in boreal headwater streams. However, the spatial and temporal distribution of soil water CO2 within theterrestrial landscape remains poorly quantified, contributing to large uncertainties about the origin of CO2 in headwater streams. The riparian zone (i.e. the area with fine sediments and organic rich soils closest to the stream) is accepted as a main contributor of organic carbon to streams, but its importanceas a source of CO2 is less evident. Here I evaluate the riparian zone as a main source by quantifying the contribution of lateral CO2 export from the riparian and hillslope zones to a headwater stream in a Swedish boreal catchment. Hourly measurements of CO2 concentration, conductivity, soil temperature and water table levels were taken in the riparian zone and the hillslope from June 2014 to October 2015. The riparian zone accounted for 58-89 % (August 2014 and March respectively) of the total terrestrial CO2 export from the slope to the stream. The hillslope, in turn, became a progressively larger source of CO2 to the stream during high flow events. To identify the drivers behind these zone-dependent and seasonal patterns in CO2 export, the CO2 production dissolved in the groundwater (groundwater- absorbed carbon) was estimated by taking the temporarily stored CO2 into account. The highest groundwater-absorbed carbon was observed during April and May (5.0 and 7.1 g C-CO2 m-2 month-1 respectively) which is the period with the highest discharge due to snow melt and the initiation of spring production. As such, conventional methods (gas chambers and the gradient method) may underestimate the soil respiration up to 50% during periods of high flow, as they exclude groundwater-absorbed carbon. CO2 consumption was observed in September 2014 and October 2015 (-0.2 and -0.7 g C-CO2 m-2 month-1 respectively) and may be explained by a major amount of the soil respiration being emitted instead of diluted in the groundwater during periods of low groundwater levels. It can be concludedthat, regardless of season, the riparian zone is a major source of CO2 to the headwater stream.
En signifikant mängd koldioxid (CO2) är lagrad i skog och marken. Marken i barrskogsregionernaförvarar en signifikant mängd CO2 där det partiella trycket av CO2 varierar mellan ~10 000 – 50 000 ppm i jämförelse med atmosfären (400 ppm). Mättnaden av CO2 gör att mycket avdunstar tillbaka till atmosfären. Dock absorberas en del CO2 av grundvattnet; vilket resulterar i en naturlig transport av CO2 vidare till ytvattnen där det kapillära nätverket av bäckar är största recipienten. Det är fortfarande oklart hur transporten av CO2 är distribuerad i ett vattenavrinningsområde vilket medför brister i förståelsen av en viktig processväg som kan komma att spela en större roll i framtidens kolkretslopp på grund av den globala uppvärmningen. Därför är en kvantifiering av olika områdens bidrag av CO2 till bäckarna nödvändig. Två betydande zoner i ett vattenavrinningsområde som troligen bidrar olika är: the riparian zone som är närmast bäcken och består av fina sediment med hög organisk halt och, the hillslope som är resterande område och består av grovkorniga jordar med låg organisk halt. Den förstnämnda misstänks transportera mer CO2 via grundvattnet på grund av dess närhet till bäcken, höga halter av CO2 och höga vattenmättnad men detta är ännu inte verifierat. Jag evaluerar the riparian zone som en viktig källa till CO2 i ett vattenavrinningsområde genom att kvantifiera transporten av CO2 från de två zonerna. För att förklara varför transporten varierar presenterar jag en ny modell (GVR) som beräknar den månatliga fluktuationen av den del av CO2-produktionen som absorberas i grundvattnet i the riparian zone. Mätningar av data utfördes i Västrabäcken, ett mindre vattenavrinningsområde i ett större vid namn Krycklan, i norra Sverige. En transekt av tre mätstationer (i bäcken, the riparian zone och the hillslope) installerades i den förmodade grundvattenströmningsriktningen. Resultaten visar på en hög produktion av CO2 under vårfloden (maj) då en hög grundvattenyta troligen absorberar en signifikant mängd CO2. Detta kan betyda att jordrespiration under våren underskattas då dagens mätmetoder är begränsade till mätningar i jorden av CO2 ovan grundvattenytan. Fortsatta studier rekommenderas där GVR-modellen och andra mätmetoder utförs samtidigt för att vidare utröna den kvantitativa underskattningen under perioder med hög grundvattenyta (speciellt under våren). Bidraget från the riparian zone till den totala laterala transporten av CO2 till bäcken under ett år varierar mellan 58-89 % och det månatliga transportmönstret kunde förklaras med resultaten från GVR-modellen. Resultaten verifierar att oberoende av säsong så är the riparian zone den huvudsakliga laterala koltransporten från landvegetationen; medan the hillslope procentuellt bidrar med mer CO2 under höga grundvattenflöden.

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8

Abelen, Sarah [Verfasser], Florian [Akademischer Betreuer] [Gutachter] Seitz, Wolfgang [Gutachter] Wagner, and Uwe [Gutachter] Stilla. "Signals of Weather Extremes in Soil Moisture and Terrestrial Water Storage from Multi-Sensor Earth Observations and Hydrological Modeling / Sarah Abelen. Betreuer: Florian Seitz. Gutachter: Wolfgang Wagner ; Uwe Stilla ; Florian Seitz." München : Universitätsbibliothek der TU München, 2016. http://d-nb.info/1107543363/34.

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9

Lin, Chin-Cheng, and 林晉丞. "Investigation of Terrestrial Water Storage Using GPS Seasonal Vertical Motion in Taiwan." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/kazzxw.

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Анотація:

碩士
國立臺灣大學
地質科學研究所
106
Global Positioning System (GPS) is widely used in studying seismic cycle deformation and plate tectonics. In Taiwan, we discover significant seasonal variation in GPS position time series and the seasonality greatly corresponds to hydrological cycle. In this study, we discuss the relation between the surface motion and seasonal water loading in southwestern Taiwan taking advantage of a dense spatial coverage of continuous GPS network. The annual GPS vertical deformation is mostly due to the elastic response to variations of surface loads in the wet and dry seasons, while some plain areas with massive water withdrawal are primary influenced by pore pressure effect. The seasonal vertical deformation on foothills is highly correlated to groundwater level, and is able to detect the occurrence of drought in the early 2010 and 2015 beforehand. We remove stations located in alluvial fan and estimate terrestrial water storage variation using a disk-load model with Green’s functions computed from an elastic earth model, PREM. We divide Taiwan into 0.2 by 0.2 grids and use seasonal GPS vertical displacements to invert the terrestrial water storage. In average, the inverted seasonal water variation is about 2 times larger in southern Taiwan compared to northern Taiwan due to heavy rainfalls during monsoons and typhoons in summer. Comparing soil moisture seasonal variation from GLDAS-Noah, GPS records integrated water storage variation including soil moisture, groundwater, reservoir etc. Consequently, GPS data from a dense array could be used as a tool to map the spatial variation of terrestrial water storage.

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Частини книг з теми "Terrestrial Water Storage"

1

Yi, Shuang. "Terrestrial Water Storage Changes in Asia." In Springer Theses, 65–95. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-7353-4_5.

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2

Famiglietti, James S. "Remote sensing of terrestrial water storage, soil moisture and surface waters." In Geophysical Monograph Series, 197–207. Washington, D. C.: American Geophysical Union, 2004. http://dx.doi.org/10.1029/150gm16.

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3

Awange, J. L., E. Forootan, K. Fleming, and G. Odhiambo. "Dominant Patterns of Water Storage Changes in the Nile Basin During 2003-2013." In Remote Sensing of the Terrestrial Water Cycle, 367–81. Hoboken, NJ: John Wiley & Sons, Inc, 2014. http://dx.doi.org/10.1002/9781118872086.ch22.

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4

Milly, P. C. D. Chris, Anny Cazenave, James S. Famiglietti, Vivien Gornitz, Katia Laval, Dennis P. Lettenmaier, Dork L. Sahagian, John M. Wahr, and Clark R. Wilson. "Terrestrial Water-Storage Contributions to Sea-Level Rise and Variability." In Understanding Sea-Level Rise and Variability, 226–55. Oxford, UK: Wiley-Blackwell, 2010. http://dx.doi.org/10.1002/9781444323276.ch8.

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5

Lee, Hyongki, Hahn Chul Jung, Ting Yuan, R. Edward Beighley, and Jianbin Duan. "Controls of Terrestrial Water Storage Changes Over the Central Congo Basin Determined by Integrating PALSAR ScanSAR, Envisat Altimetry, and GRACE Data." In Remote Sensing of the Terrestrial Water Cycle, 115–29. Hoboken, NJ: John Wiley & Sons, Inc, 2014. http://dx.doi.org/10.1002/9781118872086.ch7.

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6

Andersen, O. B., P. E. Krogh, P. Bauer-Gottwein, S. Leiriao, R. Smith, and P. Berry. "Terrestrial Water Storage from GRACE and Satellite Altimetry in the Okavango Delta (Botswana)." In Gravity, Geoid and Earth Observation, 521–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-10634-7_69.

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7

Wu, Luzhen, Ming ShangGuan, and Xu Cheng. "Monitoring of Terrestrial Water Storage Variations and Floods in Sichuan Province Using GNSS and GRACE." In Lecture Notes in Electrical Engineering, 178–89. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2588-7_17.

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8

Girotto, Manuela, and Matthew Rodell. "Terrestrial water storage." In Extreme Hydroclimatic Events and Multivariate Hazards in a Changing Environment, 41–64. Elsevier, 2019. http://dx.doi.org/10.1016/b978-0-12-814899-0.00002-x.

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9

Yamamoto, K., T. Hasegawa, Y. Fukuda, M. Taniguchi, and T. Nakaegawa. "Improvement of JLG terrestrial water storage model using GRACE satellite gravity data." In From Headwaters to the Ocean, 369–74. CRC Press, 2008. http://dx.doi.org/10.1201/9780203882849.ch55.

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10

Yeh, Pat J. F., Qiuhong Tang, and Hyungjun Kim. "Validation of Gravity Recovery and Climate Experiment Data for Assessment of Terrestrial Water Storage Variations." In Multiscale Hydrologic Remote Sensing, 481–506. CRC Press, 2012. http://dx.doi.org/10.1201/b11279-20.

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Тези доповідей конференцій з теми "Terrestrial Water Storage"

1

Cui, Aihong, Jianfeng Li, Qiming Zhou, Guofeng Wu, and Qingquan Li. "Hydrological drought measurement using GRACE terrestrial water storage anomaly." In IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2019. http://dx.doi.org/10.1109/igarss.2019.8898939.

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2

Cao, Yanping, and Zhuotong Nan. "Detecting terrestrial water storage variations in northwest China by GRACE." In SPIE Asia-Pacific Remote Sensing, edited by Thomas J. Jackson, Jing Ming Chen, Peng Gong, and Shunlin Liang. SPIE, 2014. http://dx.doi.org/10.1117/12.2067856.

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3

Gao, Shuxu, Binbin He, Yuwei Guan, Kaiwei Luo, Ningning Xiao, and Xiaofang Liu. "Correlation Between Grace Terrestrial Water Storage Anomaly and TRMM Precipitation." In IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2018. http://dx.doi.org/10.1109/igarss.2018.8517989.

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4

Xie, Zunyi, Alfredo Huete, Natalia Restrepo-Coupe, Rakhesh Devadas, Kevin Davies, and Chris Waston. "Terrestrial total water storage dynamics of Australia's recent dry and wet events." In IGARSS 2015 - 2015 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2015. http://dx.doi.org/10.1109/igarss.2015.7325935.

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5

Ahmed, Mohamed, Mohamed Sultan, and Tamer M. Elbayoumi. "PROJECTING GRACE-DERIVED TERRESTRIAL WATER STORAGE (TWS) DATA OVER THE AFRICAN WATERSHEDS." In GSA Annual Meeting in Denver, Colorado, USA - 2016. Geological Society of America, 2016. http://dx.doi.org/10.1130/abs/2016am-286035.

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6

Pengkun Xu and Wanchang Zhang. "Estimation of terrestrial water storage and ice mass changes from GRACE: A review." In 2012 7th International Conference on System of Systems Engineering (SoSE). IEEE, 2012. http://dx.doi.org/10.1109/sysose.2012.6333599.

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7

Wei, Haohan, Hongbo Yan, and Xiaoyun Shi. "Global terrestrial water storage variations revealed by gravity mission and hydrologic and climate model." In International Conference on Intelligent Earth Observing and Applications, edited by Guoqing Zhou and Chuanli Kang. SPIE, 2015. http://dx.doi.org/10.1117/12.2207430.

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8

Deng, Shiyu, Mingfang Zhang, Yiping Hou, Enxu Yu, and Yali Xu. "Assessing the Temporal Dynamics of Terrestrial Water Storage in Ten Large River Basins in China." In IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2022. http://dx.doi.org/10.1109/igarss46834.2022.9883975.

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9

Saini, D. "Candidate Trees for Terrestrial Carbon Storage in Regions with High Air Pollution and High Water Stress." In SPE Western Regional Meeting. Society of Petroleum Engineers, 2017. http://dx.doi.org/10.2118/185681-ms.

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10

Haq, M. Anul, Kamal Jain, M. Shoab, and K. P. R. Menon. "Estimation of Terrestrial Water Storage change in the Bhagirathi Ganga and Vishnu Ganga basins using satellite gravimetry." In IGARSS 2013 - 2013 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2013. http://dx.doi.org/10.1109/igarss.2013.6723153.

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