Climate change impact on terrestrial water balance components at continental and global scales

2020 ◽  
Author(s):  
Olga Nasonova ◽  
Yeugeniy Gusev ◽  
Evgeny Kovalev
Keyword(s):  
Climate Change ◽  
Water Balance ◽  
Land Surface ◽  
Large Scale ◽  
Regional Scale ◽  
Global Climate Models ◽  
Surface Model ◽  
Water Balance Components ◽  
Rcp Scenarios ◽  
Terrestrial Water

<p>This work is a continuation of our previous investigations performed within the framework of the International Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) on a regional scale when hydrological projections and their uncertainties were obtained for 11 large-scale river basins using the physically based land surface model Soil Water – Atmosphere – Plants (SWAP) driven by meteorological projections from five Global Climate Models (GCMs). In the present work, we decided to spread our investigations to continental and global scales. The main goals are as follows: (i) projecting changes in terrestrial water balance components in the 21<sup>st</sup> century due to possible climate change for different continents and for the whole globe, (ii) evaluation of uncertainties in the obtained projections sourced from application of different GCMs and different climatic scenarios, (iii) studying the patterns of spatial distribution of changes in the water balance components and their uncertainties.</p><p>Simulations of the water balance components (evapotranspiration and runoff) for the entire land surface of the globe (with the exception of Antarctica) were performed by the SWAP model with a spatial resolution of 0.5<sup>o</sup>×0.5<sup>o</sup> for the period of 1961-2099. The model was driven by daily meteorological outputs from five GCMs (including GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, and NorESM1-M) obtained for each of four Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP4.5, RCP6.0, and RCP8.5). As a result, 20 variants of daily values of evapotranspiration, runoff, and precipitation were obtained for each calculational grid cell. Then, the climatic annual values of the water balance components for four periods (historical and three prognostic ones: 2006-2036, 2037-2067, 2068-2099) were obtained and their changes for different prognostic periods compared to historical values were calculated. Besides, uncertainties in the projected changes of the water balance components resulted from application of different GCMs and RCP scenarios were estimated. The obtained results were mapped and averaged over the continents, latitudinal zones, and the globe that allowed us to identify spatio-temporal patterns of changes in the water balance components and their uncertainties due to possible climate changes.</p>

Data Assimilation for Estimating the Terrestrial Water Budget Using a Constrained Ensemble Kalman Filter

2006 ◽  
Vol 7 (3) ◽  
pp. 534-547 ◽  
Author(s):  
Ming Pan ◽  
Eric F. Wood
Keyword(s):  
Kalman Filter ◽  
Data Assimilation ◽  
Water Balance ◽  
Ensemble Kalman Filter ◽  
Land Surface ◽  
The United States ◽  
Surface Model ◽  
Infiltration Capacity ◽  
Water Balance Components ◽  
Terrestrial Water

Abstract A procedure is developed to incorporate equality constraints in Kalman filters, including the ensemble Kalman filter (EnKF), and is referred to as the constrained ensemble Kalman filter (CEnKF). The constraint is carried out as a two-step filtering approach, with the first step being the standard (ensemble) Kalman filter. The second step is the constraint step carried out by another Kalman filter that optimally redistributes any imbalance from the first step. The CEnKF is implemented over a 75 000 km2 domain in the southern Great Plains region of the United States, using the terrestrial water balance as the constraint. The observations, consisting of gridded fields of the upper two soil moisture layers from the Oklahoma Mesonet system, Atmospheric Radiation Measurement Program Cloud and Radiation Testbed (ARM-CART) energy balance Bowen ratio (EBBR) latent heat estimates, and U.S. Geological Survey (USGS) streamflow from unregulated basins, are assimilated into the Variable Infiltration Capacity (VIC) land surface model. The water balance was applied at the domain scale, and estimates of the water balance components for the domain are updated from the data assimilation step so as to assure closure.

scholarly journals Multisource Estimation of Long-Term Terrestrial Water Budget for Major Global River Basins

2012 ◽  
Vol 25 (9) ◽  
pp. 3191-3206 ◽  
Author(s):  
Ming Pan ◽  
Alok K. Sahoo ◽  
Tara J. Troy ◽  
Raghuveer K. Vinukollu ◽  
Justin Sheffield ◽  
...  
Keyword(s):  
Water Balance ◽  
Error Analysis ◽  
Land Surface ◽  
Water Budget ◽  
Large Scale ◽  
Land Surface Model ◽  
Data Sources ◽  
Surface Model ◽  
Terrestrial Water

A systematic method is proposed to optimally combine estimates of the terrestrial water budget from different data sources and to enforce the water balance constraint using data assimilation techniques. The method is applied to create global long-term records of the terrestrial water budget by merging a number of global datasets including in situ observations, remote sensing retrievals, land surface model simulations, and global reanalyses. The estimation process has three steps. First, a conventional analysis on the errors and biases in different data sources is conducted based on existing validation/error studies and other information such as sensor network density, model physics, and calibration procedures. Then, the data merging process combines different estimates so that biases and errors from different data sources can be compensated to the greatest extent and the merged estimates have the best possible confidence. Finally, water balance errors are resolved using the constrained Kalman filter technique. The procedure is applied to 32 globally distributed major basins for 1984–2006. The authors believe that the resulting global water budget estimates can be used as a baseline dataset for large-scale diagnostic studies, for example, integrated assessment of basin water resources, trend analysis and attribution, and climate change studies. The global scale of the analysis presents significant challenges in carrying out the error analysis for each water budget variable. For some variables (e.g., evapotranspiration) the assumptions underpinning the error analysis lack supporting quantitative analysis and, thus, may not hold for specific locations. Nevertheless, the merging and water balance constraining technique can be applied to many problems.

scholarly journals Simulating carbon exchange using a regional atmospheric model coupled to an advanced land-surface model

2008 ◽  
Vol 5 (5) ◽  
pp. 4161-4207 ◽  
Author(s):  
H. W. Ter Maat ◽  
R. W. A. Hutjes
Keyword(s):  
Carbon Dioxide ◽  
Land Surface ◽  
Large Scale ◽  
Regional Scale ◽  
Atmospheric Model ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Surface Model ◽  
Carbon Exchange ◽  
Regional Atmospheric Modelling System

Abstract. A large scale mismatch exists between our understanding and quantification of ecosystem atmosphere exchange of carbon dioxide at local scale and continental scales. This paper will focus on the carbon exchange on the regional scale to address the following question: What are the main controlling factors determining atmospheric carbon dioxide content at a regional scale? We use the Regional Atmospheric Modelling System (RAMS), coupled with a land surface scheme simulating carbon, heat and momentum fluxes (SWAPS-C), and including also sub models for urban and marine fluxes, which in principle include the main controlling mechanisms and capture the relevant dynamics of the system. To validate the model, observations are used which were taken during an intensive observational campaign in the central Netherlands in summer 2002. These included flux-site observations, vertical profiles at tall towers and spatial fluxes of various variables taken by aircraft. The coupled regional model (RAMS-SWAPS-C) generally does a good job in simulating results close to reality. The validation of the model demonstrates that surface fluxes of heat, water and CO2 are reasonably well simulated. The comparison against aircraft data shows that the regional meteorology is captured by the model. Comparing spatially explicit simulated and observed fluxes we conclude that in general simulated latent heat fluxes are underestimated by the model to the observations which exhibit large standard deviation for all flights. Sensitivity experiments demonstrated the relevance of the urban emissions of carbon dioxide for the carbon balance in this particular region. The same test also show the relation between uncertainties in surface fluxes and those in atmospheric concentrations.

scholarly journals Climate change impact on streamflow in large-scale river basins: projections and their uncertainties sourced from GCMs and RCP scenarios

2018 ◽  
Vol 379 ◽  
pp. 139-144 ◽  
Author(s):  
Olga N. Nasonova ◽  
Yeugeniy M. Gusev ◽  
Evgeny E. Kovalev ◽  
Georgy V. Ayzel
Keyword(s):  
Climate Change ◽  
River Runoff ◽  
Climate Change Impact ◽  
Large Scale ◽  
River Basins ◽  
Surface Model ◽  
Second Phase ◽  
Rcp Scenarios ◽  
Data Set ◽  
Change Impact

Abstract. Climate change impact on river runoff was investigated within the framework of the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP2) using a physically-based land surface model Soil Water – Atmosphere – Plants (SWAP) (developed in the Institute of Water Problems of the Russian Academy of Sciences) and meteorological projections (for 2006–2099) simulated by five General Circulation Models (GCMs) (including GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, and NorESM1-M) for each of four Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP4.5, RCP6.0, and RCP8.5). Eleven large-scale river basins were used in this study. First of all, SWAP was calibrated and validated against monthly values of measured river runoff with making use of forcing data from the WATCH data set and all GCMs' projections were bias-corrected to the WATCH. Then, for each basin, 20 projections of possible changes in river runoff during the 21st century were simulated by SWAP. Analysis of the obtained hydrological projections allowed us to estimate their uncertainties resulted from application of different GCMs and RCP scenarios. On the average, the contribution of different GCMs to the uncertainty of the projected river runoff is nearly twice larger than the contribution of RCP scenarios. At the same time the contribution of GCMs slightly decreases with time.

Revealing the spatial pattern of subsurface soil salinity over the Argentinean Dry Chaco

2021 ◽  
Author(s):  
Michiel Maertens ◽  
Veerle Vanacker ◽  
Gabriëlle De Lannoy ◽  
Frederike Vincent ◽  
Raul Giménez ◽  
...  
Keyword(s):  
Soil Salinity ◽  
Land Surface ◽  
Large Scale ◽  
Hydrological Cycle ◽  
Regional Scale ◽  
Shallow Groundwater ◽  
Soil Salinization ◽  
Dry Forest ◽  
Surface Model ◽  
Subsurface Soil

<p>The South-American Dry Chaco is a unique ecoregion as it is one of the largest sedimentary plains in the world hosting the planet’s largest dry forest. The 787.000 km² region covers parts of Argentina, Paraguay, and Bolivia and is characterized by a negative climatic water balance as a consequence of limited rainfall inputs (800 mm/year) and high temperatures (21°C). In combination with the region’s extreme flat topography (slopes < 0.1%) and shallow groundwater tables, saline soils are expected in substantial parts of the region. In addition, it is expected that large-scale deforestation processes disrupt the hydrological cycle resulting in rising groundwater tables and further increase the risk for soil salinization.</p><p>In this study, we identified the regional-scale patterns of subsurface soil salinity in the Dry Chaco.  Field data were obtained during a two-month field campaign in the dry season of 2019. A total of 492 surface- and 142 subsurface-samples were collected along East-West transects to determine soil electric conductivity, pH, bulk density and humidity. Spatial regression techniques were used to reveal the topographic and ecohydrological variables that are associated with subsurface soil salinity over the Dry Chaco. The hydrological information was obtained from a state-of-the-art land surface model with an improved set of satellite-derived vegetation and land cover parameters.</p><p>In the presentation, we will present a subsurface soil salinity map for a part of the Argentinean Dry Chaco and provide relevant insights into the driving mechanisms behind it.</p>

scholarly journals Modelling sun-induced fluorescence and photosynthesis with a land surface model at local and regional scales in northern Europe

2017 ◽  
Vol 14 (7) ◽  
pp. 1969-1987 ◽  
Author(s):  
Tea Thum ◽  
Sönke Zaehle ◽  
Philipp Köhler ◽  
Tuula Aalto ◽  
Mika Aurela ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Land Surface ◽  
Large Scale ◽  
Model Simulation ◽  
Gross Primary Production ◽  
Regional Scale ◽  
Coniferous Forest ◽  
Flux Measurement ◽  
Surface Model ◽  
Fluorescence Measurements

Abstract. Recent satellite observations of sun-induced chlorophyll fluorescence (SIF) are thought to provide a large-scale proxy for gross primary production (GPP), thus providing a new way to assess the performance of land surface models (LSMs). In this study, we assessed how well SIF is able to predict GPP in the Fenno-Scandinavian region and what potential limitations for its application exist. We implemented a SIF model into the JSBACH LSM and used active leaf-level chlorophyll fluorescence measurements (Chl F) to evaluate the performance of the SIF module at a coniferous forest at Hyytiälä, Finland. We also compared simulated GPP and SIF at four Finnish micrometeorological flux measurement sites to observed GPP as well as to satellite-observed SIF. Finally, we conducted a regional model simulation for the Fenno-Scandinavian region with JSBACH and compared the results to SIF retrievals from the GOME-2 (Global Ozone Monitoring Experiment-2) space-borne spectrometer and to observation-based regional GPP estimates. Both observations and simulations revealed that SIF can be used to estimate GPP at both site and regional scales. At regional scale the model was able to simulate observed SIF averaged over 5 years with r2 of 0.86. The GOME-2-based SIF was a better proxy for GPP than the remotely sensed fAPAR (fraction of absorbed photosynthetic active radiation by vegetation). The observed SIF captured the seasonality of the photosynthesis at site scale and showed feasibility for use in improving of model seasonality at site and regional scale.

scholarly journals On the Use of a Water Balance to Evaluate Interannual Terrestrial ET Variability

2015 ◽  
Vol 16 (3) ◽  
pp. 1102-1108 ◽  
Author(s):  
Eunjin Han ◽  
Wade T. Crow ◽  
Christopher R. Hain ◽  
Martha C. Anderson
Keyword(s):  
Water Balance ◽  
Land Surface ◽  
Land Surface Model ◽  
Past Research ◽  
Surface Model ◽  
Strongly Correlated ◽  
Thermal Infrared Remote Sensing ◽  
Cast Doubt ◽  
Terrestrial Water ◽  
Balance Analysis

Abstract Accurately measuring interannual variability in terrestrial evapotranspiration ET is a major challenge for efforts to detect trends in the terrestrial hydrologic cycle. Based on comparisons with annual values of terrestrial evapotranspiration derived from a terrestrial water balance analysis, past research has cast doubt on the ability of existing products to accurately capture variability. Using a variety of estimates, this analysis reexamines this conclusion and finds that estimates of variations obtained from a land surface model are more strongly correlated with independently acquired from thermal infrared remote sensing than derived from water balance considerations. This tendency is attributed to significant interannual variations in terrestrial water storage neglected by the water balance approach. Overall, results demonstrate the need to reassess perceptions concerning the skill of estimates derived from land surface models and show the value of accurate remotely sensed ET products for the validation of interannual ET.

scholarly journals Evaluation of Evapotranspiration for Exorheic Catchments of China during the GRACE Era: From a Water Balance Perspective

2020 ◽  
Vol 12 (3) ◽  
pp. 511 ◽  
Author(s):  
Yulong Zhong ◽  
Min Zhong ◽  
Yuna Mao ◽  
Bing Ji
Keyword(s):  
Water Balance ◽  
Balance Equation ◽  
Land Surface ◽  
Regional Scale ◽  
Water Balance Equation ◽  
Direct Measurements ◽  
Terrestrial Water ◽  
Gravity Recovery ◽  
The Impact ◽  
Mean Square Errors

Evapotranspiration (ET) is usually difficult to estimate at the regional scale due to scarce direct measurements. This study uses the water balance equation to calculate the regional ET with observations of precipitation, runoff, and terrestrial water storage changes (TWSC) in nine exorheic catchments of China. We compared the regional ET estimates from a water balance perspective with and without considering TWSC (ETWB: ET estimates with considering TWSC, and ETPQ: ET estimates from precipitation minus runoff without considering TWSC). Results show that the regional annual ET ranges from 417.7 mm/yr to 831.5 mm/yr in the nine exorheic catchments based on the water balance equation. The impact of ignoring TWSC on calculating ET is notable, as the root mean square errors (RMSEs) of annual ET between ETWB and ETPQ range from 12.0–105.8 mm/yr (2.6–12.7% in corresponding annual ET) among the exorheic catchments. We also compared the estimated regional ET with other ET products. Different precipitation products are assessed to explain the inconsistency between different ET products and regional ET from a water balance perspective. The RMSEs between ET estimates from Gravity Recovery and Climate Experiment (GRACE) and ET from land surface models can be reduced if the deviation of precipitation forcing data is considered. ET estimates from Global Land Evaporation Amsterdam Model (GLEAM) can be improved by reducing the uncertainty of precipitation forcing data in three semiarid catchments. This study emphasizes the importance of considering TWSC when calculating the regional ET using a water balance equation and provides more accurate ET estimates to help improve modeled ET results.

The calibration-free complementary relationship (CR) approach aids large-scale ET estimation

2020 ◽  
Author(s):  
Ning Ma ◽  
Jozsef Szilagyi ◽  
Yinsheng Zhang
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
Eddy Covariance ◽  
Land Surface ◽  
Large Scale ◽  
Relative Bias ◽  
Dew Point ◽  
Surface Model ◽  
Complementary Relationship ◽  
Calibration Free

<p>Having recognized the limitations in spatial representativeness and/or temporal coverage of (i) current ground evapotranspiration (ET<sub>a</sub>) observations, and; (ii) land surface model (LSM) and remote sensing (RS) based ET<sub>a</sub> estimates due to uncertainties in soil and vegetation parameters, a calibration-free nonlinear complementary relationship (CR) model is employed with inputs of air and dew-point temperature, wind speed, and net radiation to estimate monthly ET<sub>a</sub> over conterminous United States during 1979–2015. Similar estimates of three land surface models (Noah, VIC, Mosaic), two reanalysis products (NCEP-II, ERA-Interim), two remote-sensing-based (GLEAM, PML) algorithms, and the spatially upscaled eddy-covariance ET<sub>a</sub> measurements of FLUXNET-MTE plus this new result from CR were validated against water-balance-derived results. We found that the CR outperforms all other methods in the multiyear mean annual HUC2-averaged ET<sub>a</sub> estimates with RMSE = 51 mm yr<sup>−1</sup>, R = 0.98, relative bias of −1 %, and NSE = 0.94, respectively. Inclusion of the GRACE data into the annual water balances for the considerably shorter 2003–2015 period does not have much effect on model performance. Besides, the CR outperforms all other models for the linear trends in annual ET rates over the HUC2 basins. Over the significantly smaller HUC6 basins where the water-balance validation is more uncertain, the CR still outperforms all other models except FLUXNET-MTE, which has the advantage of possible local ET<sub>a</sub> measurements, a benefit that clearly diminishes at the HUC2 scale.</p><p>   Because the employed CR method is calibration-free and requires only very few meteorological inputs, yet it yields superior ET performance at the regional scale, we further employed this method to develop a new 34-year (1982-2015) ET<sub>a</sub> product for China. The new Chinese ET<sub>a</sub> product was first validated against 13 eddy-covariance measurements in China, producing NSE values in the range of 0.72–0.95. On the basin scale, the modeled ET<sub>a</sub> values yielded a relative bias of 6%, and an NSE value of 0.80 in comparison with water-balance-derived evapotranspiration rates across ten major river basins in China, indicating the CR-simulated ET<sub>a</sub> rates reliable over China. Further evaluations suggest that the CR-based ET<sub>a</sub> product is more accurate than seven other mainstream ET<sub>a</sub> products. During last three decades, our new ET<sub>a</sub> product showed that annual ET<sub>a</sub> increased significantly over most parts of western and northeastern China, but decreased significantly in many regions of the North China Plain as well as in the eastern and southern coastal regions of China. This new CR-derived ET<sub>a</sub> product would benefit the community for long-term large-scale hydroclimatological studies.</p>

Examining the vulnerability of Australian eucalypts to future drought-induced tree mortality

2021 ◽  
Author(s):  
Martin De Kauwe ◽  
Manon Sabot ◽  
Andrew Pitman ◽  
Sami Rifai ◽  
Patrick Meir ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Surface ◽  
Tree Mortality ◽  
Climate Models ◽  
Global Climate Models ◽  
Annual Rainfall ◽  
Surface Model ◽  
Eucalyptus Species ◽  
Drought Risk ◽  
The Impact

<p>Australia is the driest inhabited continent. Annual rainfall is low and is accompanied by marked inter-annual variability, leading to multi-year droughts. Climate change is expected to alter the frequency, magnitude, and intensity of future droughts, with potentially major environmental and socio-economic consequences for Australia. However, Australian vegetation is well adapted to extended dry periods, thus, the likelihood of drought-induced mortality in the future depends both on the severity of future drought events and inherent vegetation resilience. Here, we used the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model, coupled with a stomatal optimisation scheme, to examine the projected impact of future drought for 24 Eucalyptus species. We forced CABLE with future climate from four global climate models (MIROC, ECHAM, CCCMA, and CSIRO) dynamically downscaled by three regional climate models. We separated the impact of climate change (e.g. increasing VPD, precipitation variability) from rising CO<sub>2</sub> (increasing water use-efficiency) to provide the first assessment of future drought risk to Australian trees.</p>

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