scholarly journals Changing Characteristics of Runoff and Freshwater Export From Watersheds Draining Northern Alaska

2019 ◽  
Author(s):  
Michael A. Rawlins ◽  
Lei Cai ◽  
Svetlana L. Stuefer ◽  
Dmitry Nicolsky
Keyword(s):  
River Discharge ◽  
Hydrological Cycle ◽  
Water Storage ◽  
Cold Season ◽  
Active Layer Thickness ◽  
Permafrost Degradation ◽  
Total Runoff ◽  
Spring Freshet ◽  
Terrestrial Water ◽  
Freshwater Export

Abstract. The quantity and quality of river discharge in arctic regions is influenced by many processes including climate, watershed attributes and, increasingly, hydrological cycle intensification and permafrost thaw. We used a hydrological model to quantify baseline conditions and investigate the changing character of hydrological elements for Arctic watersheds between Point Barrow and just west of Mackenzie River over the period 1981–2010. The region annually exports 28.1 km3 yr−1 of freshwater via river discharge, with 51.9 % (14.6 km3 yr−1) coming collectively from the Colville, Kuparuk, and Sagavanirktok rivers. Our results point to significant (p < 0.05) increases (134–212 % of average) in cold season discharge (CSD) for several large North Slope rivers including the Colville and Kuparuk, and for the region as a whole. A significant increase in the proportion of subsurface runoff to total runoff is noted for the region and 24 of 42 study basins, with the change most prevalent across the northern foothills of the Brooks Range. Relatively large increases in simulated active-layer thickness (ALT) suggest a physical connection between warming climate, permafrost degradation, and increasing subsurface flow to streams and rivers. A decline in terrestrial water storage (TWS) is attributed to losses in soil ice that outweigh gains in soil liquid water storage. Over the 30 yr period the timing of peak spring (freshet) discharge shifts earlier by 4.5 days, though the time trend is only marginally (p = 0.1) significant. These changing characteristics of Arctic rivers have important implications for water, carbon, and nutrient cycling in coastal environments.

scholarly journals Changing characteristics of runoff and freshwater export from watersheds draining northern Alaska

2019 ◽  
Vol 13 (12) ◽  
pp. 3337-3352 ◽  
Author(s):  
Michael A. Rawlins ◽  
Lei Cai ◽  
Svetlana L. Stuefer ◽  
Dmitry Nicolsky
Keyword(s):  
River Discharge ◽  
Hydrological Cycle ◽  
Water Storage ◽  
Cold Season ◽  
Active Layer Thickness ◽  
Permafrost Degradation ◽  
Total Runoff ◽  
Spring Freshet ◽  
Terrestrial Water ◽  
Freshwater Export

Abstract. The quantity and quality of river discharge in Arctic regions is influenced by many processes including climate, watershed attributes and, increasingly, hydrological cycle intensification and permafrost thaw. We used a hydrological model to quantify baseline conditions and investigate the changing character of hydrological elements for Arctic watersheds between Utqiagvik (formerly known as Barrow)) and just west of Mackenzie River over the period 1981–2010. A synthesis of measurements and model simulations shows that the region exports 31.9 km3 yr−1 of freshwater via river discharge, with 55.5 % (17.7 km3 yr−1) coming collectively from the Colville, Kuparuk, and Sagavanirktok rivers. The simulations point to significant (p<0.05) increases (134 %–212 % of average) in cold season discharge (CSD) for several large North Slope rivers including the Colville and Kuparuk, and for the region as a whole. A significant increase in the proportion of subsurface runoff to total runoff is noted for the region and for 24 of the 42 study basins, with the change most prevalent across the northern foothills of the Brooks Range. Relatively large increases in simulated active-layer thickness (ALT) suggest a physical connection between warming climate, permafrost degradation, and increasing subsurface flow to streams and rivers. A decline in terrestrial water storage (TWS) is attributed to losses in soil ice that outweigh gains in soil liquid water storage. Over the 30-year period, the timing of peak spring (freshet) discharge shifts earlier by 4.5 d, though the time trend is only marginally (p=0.1) significant. These changing characteristics of Arctic rivers have important implications for water, carbon, and nutrient cycling in coastal environments.

scholarly journals Data assimilation of GRACE terrestrial water storage estimates into a regional hydrological model of the Rhine River basin

2015 ◽  
Vol 19 (4) ◽  
pp. 2079-2100 ◽  
Author(s):  
N. Tangdamrongsub ◽  
S. C. Steele-Dunne ◽  
B. C. Gunter ◽  
P. G. Ditmar ◽  
A. H. Weerts
Keyword(s):  
Correlation Coefficient ◽  
River Basin ◽  
Hydrological Cycle ◽  
Water Storage ◽  
Model Parameters ◽  
Hydrological Models ◽  
Rhine River ◽  
Terrestrial Water Storage ◽  
Grace Data ◽  
Terrestrial Water

Abstract. The ability to estimate terrestrial water storage (TWS) realistically is essential for understanding past hydrological events and predicting future changes in the hydrological cycle. Inadequacies in model physics, uncertainty in model land parameters, and uncertainties in meteorological data commonly limit the accuracy of hydrological models in simulating TWS. In an effort to improve model performance, this study investigated the benefits of assimilating TWS estimates derived from the Gravity Recovery and Climate Experiment (GRACE) data into the OpenStreams wflow_hbv model using an ensemble Kalman filter (EnKF) approach. The study area chosen was the Rhine River basin, which has both well-calibrated model parameters and high-quality forcing data that were used for experimentation and comparison. Four different case studies were examined which were designed to evaluate different levels of forcing data quality and resolution including those typical of other less well-monitored river basins. The results were validated using in situ groundwater (GW) and stream gauge data. The analysis showed a noticeable improvement in GW estimates when GRACE data were assimilated, with a best-case improvement of correlation coefficient from 0.31 to 0.53 and root mean square error (RMSE) from 8.4 to 5.4 cm compared to the reference (ensemble open-loop) case. For the data-sparse case, the best-case GW estimates increased the correlation coefficient from 0.46 to 0.61 and decreased the RMSE by 35%. For the average improvement of GW estimates (for all four cases), the correlation coefficient increases from 0.6 to 0.7 and the RMSE was reduced by 15%. Only a slight overall improvement was observed in streamflow estimates when GRACE data were assimilated. Further analysis suggested that this is likely due to sporadic short-term, but sizeable, errors in the forcing data and the lack of sufficient constraints on the soil moisture component. Overall, the results highlight the benefit of assimilating GRACE data into hydrological models, particularly in data-sparse regions, while also providing insight on future refinements of the methodology.

scholarly journals Global Evaluation of the ISBA-TRIP Continental Hydrological System. Part I: Comparison to GRACE Terrestrial Water Storage Estimates and In Situ River Discharges

2010 ◽  
Vol 11 (3) ◽  
pp. 583-600 ◽  
Author(s):  
R. Alkama ◽  
B. Decharme ◽  
H. Douville ◽  
M. Becker ◽  
A. Cazenave ◽  
...  
Keyword(s):  
River Discharge ◽  
Water Storage ◽  
Additional Constraint ◽  
Terrestrial Water Storage ◽  
Discharge Data ◽  
Continental Hydrology ◽  
Wide Range ◽  
Terrestrial Water ◽  
Hydrological System

Abstract In earth system models, the partitioning of precipitation among the variations of continental water storage, evapotranspiration, and freshwater runoff to the ocean has a major influence on the terrestrial water and energy budgets and thereby on simulated climate on a wide range of scales. The evaluation of continental hydrology is therefore a crucial task that requires offline simulations driven by realistic atmospheric forcing to avoid the systematic biases commonly found in global atmospheric models. Generally, this evaluation is done mainly by comparison with in situ river discharge data, which does not guarantee that the spatiotemporal distribution of water storage and evapotranspiration is correctly simulated. In this context, the Interactions between Soil, Biosphere, and Atmosphere–Total Runoff Integrating Pathways (ISBA-TRIP) continental hydrological system of the Centre National de Recherches Météorologiques is evaluated by using the additional constraint of terrestrial water storage (TWS) variations derived from three independent gravity field retrievals (datasets) from the Gravity Recovery and Climate Experiment (GRACE). On the one hand, the results show that, in general, ISBA-TRIP captures the seasonal and the interannual variability in both TWS and discharges. GRACE provides an additional constraint on the simulated hydrology and consolidates the former evaluation only based on river discharge observations. On the other hand, results indicate that river storage variations represent a significant contribution to GRACE measurements. While this remark highlights the need to improve the TRIP river routing model for a more useful comparison with GRACE [Decharme et al. (Part II of the present study)], it also suggests that low-resolution gravimetry products do not necessarily represent a strong additional constraint for model evaluation, especially in downstream areas of large river basins where long-term discharge data are available.

An observation-based approach for global runoff estimation: exploiting satellite soil moisture and Grace

2020 ◽  
Author(s):  
Stefania Camici ◽  
Luca Brocca ◽  
Christian Massari ◽  
Gabriele Giuliani ◽  
Nico Sneeuw ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Water Storage ◽  
Data Access ◽  
Satellite Observations ◽  
Terrestrial Water Storage ◽  
Total Runoff ◽  
The World ◽  
Terrestrial Water ◽  
Trmm 3B42

&lt;p&gt;Water is at the centre of economic and social development; it is vital to maintain health, grow food, manage the environment, produce renewable energy, support industrial processes and create jobs. Despite the importance of water, to date over one third of the world's population still lacks access to drinking water resources and this number is expected to increase due to climate change and outdated water management. As over half of the world&amp;#8217;s potable water supply is extracted from rivers, either directly or from reservoirs, understanding the variability of the stored water on and below landmasses, i.e., runoff, is of primary importance. Apart from river discharge observation networks that suffer from many known limitations (e.g., low station density and often incomplete temporal coverage, substantial delay in data access and large decline in monitoring capacity), runoff can be estimated through model-based or observation-based approaches whose outputs can be highly model or data dependent and characterised by large uncertainties.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;On this basis, developing innovative methods able to maximize the recovery of information on runoff contained in current satellite observations of climatic and environmental variables (i.e., precipitation, soil moisture, terrestrial water storage anomalies and land cover) becomes mandatory and urgent. In this respect, within the European Space Agency (ESA) STREAM Project (SaTellite based Runoff Evaluation And Mapping), a solid &amp;#8220;observational&amp;#8221; approach, exploiting space-only observations of Precipitation (P), Soil Moisture (SM) and Terrestrial Water Storage Anomalies (TWSA) to derive total runoff has been developed and validated. Different P and SM products have been considered. For P, both in situ and satellite-based (e.g., Tropical Rainfall Measuring Mission, TRMM 3B42) datasets have been collected; for SM, Advanced SCATterometer, ASCAT, and ESA Climate Change Initiative, ESA CCI, soil moisture products have been extracted. TWSA time series are obtained from the latest Goddard Space Flight Center&amp;#8217;s global mascon model, which provides storage anomalies and their uncertainties in the form of monthly surface mass densities per approximately 1&amp;#176;x1&amp;#176; blocks.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Total runoff estimates have been simulated for the period 2003-2017 at 5 pilot basins across the world (Mississippi, Amazon, Niger, Danube and Murray Darling) characterised by different physiographic/climatic features. Results proved the potentiality of satellite observations to estimate runoff at daily time scale and at spatial resolution better than GRACE spatial sampling. In particular, by using satellite TRMM 3B42 rainfall data and ESA CCI soil moisture data, very good runoff estimates have been obtained over Amazon basin, with a Kling-Gupta efficiency (KGE) index greater than 0.92 both at the closure and over several inner stations in the basin. Good results found for Mississippi and Danube are also encouraging with KGE index greater than 0.75 for both the basins.&lt;/p&gt;

scholarly journals Assessment of Three Common Methods for Estimating Terrestrial Water Storage Change with Three Reanalysis Datasets

2020 ◽  
Vol 33 (2) ◽  
pp. 511-525 ◽  
Author(s):  
Shanshan Deng ◽  
Suxia Liu ◽  
Xingguo Mo
Keyword(s):  
Water Balance ◽  
Hydrological Cycle ◽  
Regional Scale ◽  
Water Storage ◽  
Balance Method ◽  
Terrestrial Water Storage ◽  
Water Balance Method ◽  
Terrestrial Water ◽  
The Impact ◽  
Storage Change

AbstractTerrestrial water storage change (TWSC) plays a crucial role in the hydrological cycle and climate system. To date, methods including 1) the terrestrial water balance method (PER), 2) the combined atmospheric and terrestrial water balance method (AT), and 3) the summation method (SS) have been developed to estimate TWSC, but the accuracy of these methods has not been systematically compared. This paper compares the spatial and temporal differences of the TWSC estimates by the three methods comprehensively with the GRACE data during the 2002–13 period. To avoid the impact of different inputs in the comparison, three advanced reanalysis datasets are used, namely 1) the National Centers for Environmental Prediction (NCEP)–Department of Energy (DOE) Reanalysis II (NCEP R2), 2) the ECMWF interim reanalysis (ERA-Interim), and 3) the Japanese 55-Year Reanalysis (JRA-55). The results show that all estimates with PER and AT considerably overestimate the long-term mean on a regional scale because the data assimilation in the reanalysis opens the water budget. The difficulty of atmospheric observation and simulation in arid and polar tundra regions is the documented reason for the failure of the AT method to represent the TWSC phase over 30% of the region found in this study. Although the SS result exhibited the best overall agreement with GRACE, the amplitude of TWSC based on SS differed substantially from that of GRACE and the similarity coefficient of the global distribution between the SS-derived estimate and GRACE is still not high. More detailed considerations of groundwater and human activities, for example, irrigation and reservoir impoundments, can help SS to achieve a higher accuracy.

scholarly journals Impact of variability in the hydrological cycle components on vegetation growth in an alpine basin of the southeastern Tibet Plateau, China

2021 ◽  
Author(s):  
Chunguang Ban ◽  
Zongxue Xu ◽  
Depeng Zuo ◽  
Rui Zhang ◽  
Hao Chen ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Snow Water Equivalent ◽  
Hydrological Cycle ◽  
Water Storage ◽  
Tibet Plateau ◽  
Upstream Region ◽  
Terrestrial Water Storage ◽  
Vegetation Growth ◽  
Terrestrial Water ◽  
The Impact

Abstract Vegetation is affected by hydrological cycle components that have altered under the influence of climate change. Therefore, it is necessary to investigate the impact of hydrological cycle components on regional vegetation growth, especially in alpine regions. In this study, we employed multiple satellite observations to comprehensively investigate the spatial heterogeneity of hydrological cycle components in the Yarlung Zangbo River (YZR) basin for the period 1982–2014 and to determine the underlying mechanisms driving regional vegetation growth. Results showed that the normalized difference vegetation index (NDVI) values during May–October were high, and the NDVI values increased from the upper reaches of the YZR to its lower reaches, reflecting the enhancement of vegetation growth. Annual precipitation, precipitation-actual evapotranspiration (AET), and snow water equivalent (SWE) all affect terrestrial water storage in the YZR basin through changes in soil moisture (SM), i.e., SM is the intermediate variable. Seasonal variability of vegetation is controlled mainly by precipitation, temperature, AET, SM anomaly, and SWE. Groundwater storage anomalies (GWA) and terrestrial water storage anomalies (TWSA) were not reliable indicators of vegetation growth in the YZR basin and the midstream and downstream regions. The effects of GWA and TWSA on vegetation occurred in the upstream region.

Permafrost degradation monitoring by InSAR at different spatial resolution in Sanjiangyuan region, China

2020 ◽  
Author(s):  
Deying Ma ◽  
Mahdi Motagh ◽  
Guoxiang Liu
Keyword(s):  
Hydrological Cycle ◽  
Yellow River ◽  
Active Layer Thickness ◽  
Water Tank ◽  
Permafrost Degradation ◽  
Sar Images ◽  
Qinghai Province ◽  
Persistent Scatterer ◽  
Degradation Monitoring ◽  
Warming Process

&lt;p&gt;Sanjiangyuan, as the Chinese &amp;#8216;water tank&amp;#8217;, is located in Qinghai province, China. It is the fountainhead of yellow river, Yangzi river and Lancang river. Therefore, it&amp;#8217;s extraordinary valuable to the environment of China and Asia. The continuous permafrost spreads widely in this area. With the global warming process, the degradation of permafrost becomes faster and consequently changes the distribution of vegetation and hydrological cycle.&lt;/p&gt;&lt;p&gt;In this study, we use Persistent Scatterer InSAR (PSI) technique to efficiently detect the seasonal settlement around Elin lake and Zhaling lake, which are the main parts of Sanjiangyuan region. The subsidence was analyzed by processing 56 Sentinel-1 SAR images from 2015 to 2019 using SNAP and StaMPS. The results were then inverted to derive the corresponding active layer thickness over this region. Moreover, in order to investigate the detailed influence of degradation on infrastructures, we analyzed 3m resolution TerraSAR-X images in StripMap mode from May to October 2015 to get the heterogeneous subsidence along the Gonghe-Yushu road. Results indicate mean subsidence rates exceeding 4 cm/yr along the Gonghe-Yushu road .&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

scholarly journals Study on the Variation of Terrestrial Water Storage and the Identification of Its Relationship with Hydrological Cycle Factors in the Tarim River Basin, China

2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Peng Yang ◽  
Jun Xia ◽  
Chesheng Zhan ◽  
Yongyong Zhang ◽  
Jie Chen
Keyword(s):  
River Basin ◽  
River Discharge ◽  
Water Storage ◽  
Tarim River ◽  
Tarim River Basin ◽  
Terrestrial Water Storage ◽  
Water Deficits ◽  
The Tarim River ◽  
Terrestrial Water ◽  
The Tarim River Basin

The terrestrial water storage anomalies (TWSAs) in the Tarim River Basin (TRB) were investigated and the related factors of water variations in the mountain areas were analyzed based on Gravity Recovery and Climate Experiment (GRACE) data, in situ river discharge, and precipitation during the period of 2002–2015. The results showed that three obvious flood events in 2005, 2006, and 2010 resulted in significant water surplus, although TWSA decreased in the TRB during 2002–2015. However, while the significant water deficits in 2004, 2009, and 2011 were associated with obvious negative river discharge anomalies at the hydrological stations, the significant water deficits were not well consistent with the negative anomalies of precipitation. While the river discharge behaved with low correlations with TWSA, linear relationships between TWSA and climate indices were insignificant in the TRB from 2002 to 2015. The closest relationship was found between TWSA and Pacific Decadal Oscillation (PDO), with correlations of -0.56 and 0.58 during January 2010–December 2015 and during January 2006–December 2009, respectively. Meanwhile, the correlation coefficient between TWSA and El Niño-Southern Oscillation (ENSO) index in the period of April 2002–December 2005 was -0.25, which reached the significant level (p<0.05).

scholarly journals The change of hydrological variables and its effects on vegetation in Central Asia

2021 ◽  
Author(s):  
Qing Peng ◽  
Ranghui Wang ◽  
Yelin Jiang ◽  
Cheng Li ◽  
Wenhui Guo
Keyword(s):  
Soil Moisture ◽  
Central Asia ◽  
Vegetation Dynamics ◽  
Hydrological Cycle ◽  
Water Storage ◽  
Terrestrial Water Storage ◽  
Spatiotemporal Changes ◽  
Global Land ◽  
Terrestrial Water ◽  
Hydrological Variables

AbstractWater is an important factor that affects local ecological environments, especially in drylands. The hydrological cycle and vegetation dynamics in Central Asia (CA) have been severely affected by climate change. In this study, we employed data from Gravity Recovery and Climate Experiment (GRACE), Global Land Data Assimilation System (GLDAS), Global Land Evaporation Amsterdam Model, and Climate Research Unit to analyze the spatiotemporal changes in hydrological factors (terrestrial water storage (TWS), evapotranspiration, precipitation, and groundwater) in CA from 2003 to 2015. Additionally, the spatiotemporal changes in vegetation dynamics and the influence of hydrological variables on vegetation were analyzed. The results showed that the declining rates of precipitation, evapotranspiration, GRACE-TWS change, GLDAS-TWS change and GW change were 0.40 mm/year, 0.11 mm/year, 50.46 mm/year (p < 0.05), 8.38 mm/year, and 41.18 mm/year (p < 0.05), respectively. Human activity (e.g., groundwater pumping) was the dominant in determining the GW decline in CA. Precipitation dominated the changes in evapotranspiration, GRACE-TWS and GLDAS-TWS (p < 0.05). The 2- to 3-month lagging signal has to do with the transportation from the ground surface to groundwater. The change in the normalized difference vegetation index (NDVI) from 2003 to 2015 indicated the slight vegetation degradation in CA. The results highlighted that precipitation, terrestrial water storage, and soil moisture make important contributions to the vegetation dynamics changes in CA. The effect of precipitation on vegetation growth in spring was significant (p < 0.05), while the soil moisture effect on vegetation in summer and autumn was higher than that of precipitation.

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