scholarly journals On the Appropriate Definition of Soil Profile Configuration and Initial Conditions for Land Surface-Hydrology Models in Cold Regions

2017 ◽  
Author(s):  
Gonzalo Sapriza-Azuri ◽  
Pablo Gamazo ◽  
Saman Razavi ◽  
Howard S. Wheater

Abstract. Arctic and sub-arctic regions are amongst the most susceptible regions on Earth to global warming and climate change. Understanding and predicting the impact of climate change in these regions require a proper process representation of the interactions between climate, the carbon cycle, and hydrology in Earth system models. This study focuses on Land Surface Models (LSMs) that represent the lower boundary condition of General Circulation Models (GCMs) and Regional Climate Models (RCMs), which simulate climate change evolution at the global and regional scales, respectively. LSMs typically utilize a standard soil configuration with a depth of no more than 4 meters, whereas for cold, permafrost regions, field experiments show that attention to deep soil profiles is needed to understand and close the water and energy balances, which are tightly coupled through the phase change. To address this, we design and run a series of model experiments with a one-dimensional LSM, called CLASS (Canadian Land Surface Scheme), as embedded in the MESH (Modélisation Environmentale Communautaire – Surface and Hydrology) modelling system, to (1) characterize the effect of soil profile depth under different climate conditions and in the presence of parameter uncertainty, and (2) develop a methodology for temperature profile initialization in permafrost regions, where the system has an extended memory, by the use of paleo-records and bootstrapping. Our study area is in Norman Wells, Northwest Territories of Canada, where measurements of soil temperature profiles and historical reconstructed climate data are available. Our results demonstrate that the adequate depth of soil profile in an LSM varies for warmer and colder conditions and is sensitive to model parameters and the uncertainty around them. In general, however, we show that a minimum of 20 meters of soil profile is essential to adequately represent the temperature dynamics. Our results also indicate the significance of model initialization in permafrost regions and our proposed spin-up method requires running the LSM over more than 300 years of reconstructed climate time series.

2018 ◽  
Vol 22 (6) ◽  
pp. 3295-3309 ◽  
Author(s):  
Gonzalo Sapriza-Azuri ◽  
Pablo Gamazo ◽  
Saman Razavi ◽  
Howard S. Wheater

Abstract. Arctic and subarctic regions are amongst the most susceptible regions on Earth to global warming and climate change. Understanding and predicting the impact of climate change in these regions require a proper process representation of the interactions between climate, carbon cycle, and hydrology in Earth system models. This study focuses on land surface models (LSMs) that represent the lower boundary condition of general circulation models (GCMs) and regional climate models (RCMs), which simulate climate change evolution at the global and regional scales, respectively. LSMs typically utilize a standard soil configuration with a depth of no more than 4 m, whereas for cold, permafrost regions, field experiments show that attention to deep soil profiles is needed to understand and close the water and energy balances, which are tightly coupled through the phase change. To address this gap, we design and run a series of model experiments with a one-dimensional LSM, called CLASS (Canadian Land Surface Scheme), as embedded in the MESH (Modélisation Environmentale Communautaire – Surface and Hydrology) modelling system, to (1) characterize the effect of soil profile depth under different climate conditions and in the presence of parameter uncertainty; (2) assess the effect of including or excluding the geothermal flux in the LSM at the bottom of the soil column; and (3) develop a methodology for temperature profile initialization in permafrost regions, where the system has an extended memory, by the use of paleo-records and bootstrapping. Our study area is in Norman Wells, Northwest Territories of Canada, where measurements of soil temperature profiles and historical reconstructed climate data are available. Our results demonstrate a dominant role for parameter uncertainty, that is often neglected in LSMs. Considering such high sensitivity to parameter values and dependency on the climate condition, we show that a minimum depth of 20 m is essential to adequately represent the temperature dynamics. We further show that our proposed initialization procedure is effective and robust to uncertainty in paleo-climate reconstructions and that more than 300 years of reconstructed climate time series are needed for proper model initialization.


2004 ◽  
Vol 5 (6) ◽  
pp. 1131-1146 ◽  
Author(s):  
H. Richter ◽  
A. W. Western ◽  
F. H. S. Chiew

Abstract Numerical Weather Prediction (NWP) and climate models are sensitive to evapotranspiration at the land surface. This sensitivity requires the prediction of realistic surface moisture and heat fluxes by land surface models that provide the lower boundary condition for the atmospheric models. This paper compares simulations of a stand-alone version of the European Centre for Medium-Range Weather Forecasts (ECMWF) land surface scheme, or the Viterbo and Beljaars scheme (VB95), with various soil and vegetation parameter sets against soil moisture observations across the Murrumbidgee River catchment in southeast Australia. The study is, in part, motivated by the adoption of VB95 as the operational land surface scheme by the Australian Bureau of Meteorology in 1999. VB95 can model the temporal fluctuations in soil moisture, and therefore the moisture fluxes, fairly realistically. The monthly model latent heat flux is also fairly insensitive to soil or vegetation parameters. The VB95 soil moisture is sensitive to the soil and, to a lesser degree, the vegetation parameters. The model exhibits a significant (generally wet) bias in the absolute soil moisture that varies spatially. The use of the best Australia-wide available soils and vegetation information did not improve VB95 simulations consistently, compared with the original model parameters. Comparisons of model and observed soil moistures revealed that more realistic soil parameters are needed to reduce the model soil moisture bias. Given currently available continent-wide soils parameters, any initialization of soil moisture with observed values would likely result in significant flux errors. The soil moisture bias could be largely eliminated by using soil parameters that were derived directly from the actual soil moisture observations. Such parameters, however, are only available at very few point locations.


1999 ◽  
Vol 30 (3) ◽  
pp. 209-230 ◽  
Author(s):  
Stefan Hagemann ◽  
Lydia Dümenil

In this study, a hydrological discharge model is presented which may be applied as a tool to validate the simulation of the hydrologic cycle of atmospheric models that are used in climate change studies. It can also be applied in studies of global climate change to investigate how changes in climate may affect the discharge of large rivers. The model was developed for the application with the climate models used at the Max-Planck-Institute for Meteorology. It describes the translation and retention of the lateral waterflows on the global scale as a function of the spatially distributed land surface characteristics which are globally available. Here, global scale refers to the resolution of 0.5° and lower, corresponding to a typical average gridbox area of about 2,500 km2. The hydrological discharge model separates between the flow processes of overland flow, baseflow and riverflow. The model parameters are mainly functions of the gridbox characteristics of topography and gridbox length. The hydrological discharge model is applied to the BALTEX (Baltic Sea Experiment) region using input from an atmospheric general circulation model (ECHAM4) as well as from a regional climate model (REMO). The simulated inflows into the Baltic Sea and its sub-catchments are compared to observed and naturalized discharges. The results of this comparison are discussed and the simulated values of precipitation, surface air temperature and accumulated snowpack are compared to both observed data and surrogate data.


2007 ◽  
Vol 8 (1) ◽  
pp. 68-87 ◽  
Author(s):  
Margaret A. LeMone ◽  
Fei Chen ◽  
Joseph G. Alfieri ◽  
Mukul Tewari ◽  
Bart Geerts ◽  
...  

Abstract Analyses of daytime fair-weather aircraft and surface-flux tower data from the May–June 2002 International H2O Project (IHOP_2002) and the April–May 1997 Cooperative Atmosphere Surface Exchange Study (CASES-97) are used to document the role of vegetation, soil moisture, and terrain in determining the horizontal variability of latent heat LE and sensible heat H along a 46-km flight track in southeast Kansas. Combining the two field experiments clearly reveals the strong influence of vegetation cover, with H maxima over sparse/dormant vegetation, and H minima over green vegetation; and, to a lesser extent, LE maxima over green vegetation, and LE minima over sparse/dormant vegetation. If the small number of cases is producing the correct trend, other effects of vegetation and the impact of soil moisture emerge through examining the slope ΔxyLE/ΔxyH for the best-fit straight line for plots of time-averaged LE as a function of time-averaged H over the area. Based on the surface energy balance, H + LE = Rnet − Gsfc, where Rnet is the net radiation and Gsfc is the flux into the soil; Rnet − Gsfc ∼ constant over the area implies an approximately −1 slope. Right after rainfall, H and LE vary too little horizontally to define a slope. After sufficient drying to produce enough horizontal variation to define a slope, a steep (∼−2) slope emerges. The slope becomes shallower and better defined with time as H and LE horizontal variability increases. Similarly, the slope becomes more negative with moister soils. In addition, the slope can change with time of day due to phase differences in H and LE. These trends are based on land surface model (LSM) runs and observations collected under nearly clear skies; the vegetation is unstressed for the days examined. LSM runs suggest terrain may also play a role, but observational support is weak.


2017 ◽  
Vol 18 (7) ◽  
pp. 2029-2042
Author(s):  
Tony E. Wong ◽  
William Kleiber ◽  
David C. Noone

Abstract Land surface models are notorious for containing many parameters that control the exchange of heat and moisture between land and atmosphere. Properly modeling the partitioning of total evapotranspiration (ET) between transpiration and evaporation is critical for accurate hydrological modeling, but depends heavily on the treatment of turbulence within and above canopies. Previous work has constrained estimates of evapotranspiration and its partitioning using statistical approaches that calibrate land surface model parameters by assimilating in situ measurements. These studies, however, are silent on the impacts of the accounting of uncertainty within the statistical calibration framework. The present study calibrates the aerodynamic, leaf boundary layer, and stomatal resistance parameters, which partially control canopy turbulent exchange and thus the evapotranspiration flux partitioning. Using an adaptive Metropolis–Hastings algorithm to construct a Markov chain of draws from the joint posterior distribution of these resistance parameters, an ensemble of model realizations is generated, in which latent and sensible heat fluxes and top soil layer temperature are optimized. A set of five calibration experiments demonstrate that model performance is sensitive to the accounting of various sources of uncertainty in the field observations and model output and that it is critical to account for model structural uncertainty. After calibration, the modeled fluxes and top soil layer temperature are largely free from bias, and this calibration approach successfully informs and characterizes uncertainty in these parameters, which is essential for model improvement and development. The key points of this paper are 1) a Markov chain Monte Carlo calibration approach successfully improves modeled turbulent fluxes; 2) ET partitioning estimates hinge on the representation of uncertainties in the model and data; and 3) despite these inherent uncertainties, constrained posterior estimates of ET partitioning emerge.


2013 ◽  
Vol 17 (1) ◽  
pp. 1-20 ◽  
Author(s):  
B. Shrestha ◽  
M. S. Babel ◽  
S. Maskey ◽  
A. van Griensven ◽  
S. Uhlenbrook ◽  
...  

Abstract. This paper evaluates the impact of climate change on sediment yield in the Nam Ou basin located in northern Laos. Future climate (temperature and precipitation) from four general circulation models (GCMs) that are found to perform well in the Mekong region and a regional circulation model (PRECIS) are downscaled using a delta change approach. The Soil and Water Assessment Tool (SWAT) is used to assess future changes in sediment flux attributable to climate change. Results indicate up to 3.0 °C shift in seasonal temperature and 27% (decrease) to 41% (increase) in seasonal precipitation. The largest increase in temperature is observed in the dry season while the largest change in precipitation is observed in the wet season. In general, temperature shows increasing trends but changes in precipitation are not unidirectional and vary depending on the greenhouse gas emission scenarios (GHGES), climate models, prediction period and season. The simulation results show that the changes in annual stream discharges are likely to range from a 17% decrease to 66% increase in the future, which will lead to predicted changes in annual sediment yield ranging from a 27% decrease to about 160% increase. Changes in intra-annual (monthly) discharge as well as sediment yield are even greater (−62 to 105% in discharge and −88 to 243% in sediment yield). A higher discharge and sediment flux are expected during the wet seasons, although the highest relative changes are observed during the dry months. The results indicate high uncertainties in the direction and magnitude of changes of discharge as well as sediment yields due to climate change. As the projected climate change impact on sediment varies remarkably between the different climate models, the uncertainty should be taken into account in both sediment management and climate change adaptation.


2021 ◽  
Author(s):  
Borja Rodríguez Lozano ◽  
Emilio Rodriguez-Caballero ◽  
Yolanda Cantón

<p>Drylands are one of the largest biomes over the Earth, covering around 40% of land surface. These are water limited ecosystems where vegetation occupies the most favourable positions over the landscape. Less favourable areas are frequently covered by other biotic and abiotic components such as biological soil crusts, bare soil, or stones. During most rainfall events, runoff is generated in open areas (runoff sources) and redistributed through vegetation patches (runoff sinks), therefore increasing water and nutrient availability for plants. Water redistribution feedbacks determine vegetation coverage and productivity, modulate changes in its spatial distribution, and could ameliorate the predicted negative effects of climate change over these ecosystems.</p><p>The principal aim of this study was to quantify the impact of water redistribution processes on vegetation performance, and to evaluate how this effect varies in response to aridity. To achieve it, we analysed the relationships between runoff redistribution from open areas and vegetation productivity, by combining satellite information on vegetation state and topography. More precisely, we calculated Normalized Difference Vegetation Index (NDVI) dynamics during three hydrological years in 17 study sites along an aridity gradient in the SE of the Iberian Peninsula using SENTINEL 2 images. Then we used a DEM and a high spatial resolution vegetation map to derive a water redistribution index that simulate source-sinks interactions between vegetation and open areas. Finally, we analyse the relationship between, potential water redistribution and vegetation dynamics and how it varies along the aridity gradient.</p><p>We found a non-linear relationship between potential water redistribution and vegetation productivity. Overall, vegetation NDVI increases as potential water redistribution did, which demonstrated the importance of water redistribution processes on drylands vegetation performance. However, vegetation capacity to retain runoff water is limited and there is a clear threshold above which increased potential water redistribution does not promote vegetation productivity. Thresholds are caused by the limit capacity of vegetation to infiltrate run off when preferential flows are forming, increasing ecosystem connectivity, and involving local water losses for vegetation.  Therefore, an increase in open areas between vegetation patches could have a positive effect over vegetation through hydrological connectivity but until to a certain point in which global connectivity supposed water losses for plants. This process could have important effects under climate change, by controlling the resistance and resilience of vegetation in drylands ecosystems.</p><p>Acknowledgements. This research was supported by the FPU predoctoral fellowship from the Educational, Culture and Sports Ministry of Spain (FPU17/01886) REBIOARID (RTI2018-101921-B-I00) projects, funded by the FEDER/Science and Innovation Ministry-National Research Agency, and the RH2O-ARID (P18-RT-5130) funded by Junta de Andalucía and the European Union for Regional Development.</p>


2021 ◽  
Author(s):  
Thedini Asali Peiris ◽  
Petra Döll

<p>Unlike global climate models, hydrological models cannot simulate the feedbacks among atmospheric processes, vegetation, water, and energy exchange at the land surface. This severely limits their ability to quantify the impact of climate change and the concurrent increase of atmospheric CO<sub>2</sub> concentrations on evapotranspiration and thus runoff. Hydrological models generally calculate actual evapotranspiration as a fraction of potential evapotranspiration (PET), which is computed as a function of temperature and net radiation and sometimes of humidity and wind speed. Almost no hydrological model takes into account that PET changes because the vegetation responds to changing CO<sub>2</sub> and climate. This active vegetation response consists of three components. With higher CO<sub>2</sub> concentrations, 1) plant stomata close, reducing transpiration (physiological effect) and 2) plants may grow better, with more leaves, increasing transpiration (structural effect), while 3) climatic changes lead to changes in plants growth and even biome shifts, changing evapotranspiration. Global climate models, which include dynamic vegetation models, simulate all these processes, albeit with a high uncertainty, and take into account the feedbacks to the atmosphere.</p><p>Milly and Dunne (2016) (MD) found that in the case of RCP8.5 the change of PET (computed using the Penman-Monteith equation) between 1981- 2000 and 2081-2100 is much higher than the change of non-water-stressed evapotranspiration (NWSET) computed by an ensemble of global climate models. This overestimation is partially due to the neglect of active vegetation response and partially due to the neglected feedbacks between the atmosphere and the land surface.</p><p>The objective of this paper is to present a simple approach for hydrological models that enables them to mimic the effect of active vegetation on potential evapotranspiration under climate change, thus improving computation of freshwater-related climate change hazards by hydrological models. MD proposed an alternative approach to estimate changes in PET for impact studies that is only a function of the changes in energy and not of temperature and achieves a good fit to the ensemble mean change of evapotranspiration computed by the ensemble of global climate models in months and grid cells without water stress. We developed an implementation of the MD idea for hydrological models using the Priestley-Taylor equation (PET-PT) to estimate PET as a function of net radiation and temperature. With PET-PT, an increasing temperature trend leads to strong increases in PET. Our proposed methodology (PET-MD) helps to remove this effect, retaining the impact of temperature on PET but not on long-term PET change.</p><p>We implemented the PET-MD approach in the global hydrological model WaterGAP2.2d. and computed daily time series of PET between 1981 and 2099 using bias-adjusted climate data of four global climate models for RCP 8.5. We evaluated, computed PET-PT and PET-MD at the grid cell level and globally, comparing also to the results of the Milly-Dunne study. The global analysis suggests that the application of PET-MD reduces the PET change until the end of this century from 3.341 mm/day according to PET-PT to 3.087 mm/day (ensemble mean over the four global climate models).</p><p>Milly, P.C.D., Dunne K.A. (2016). DOI:10.1038/nclimate3046.</p>


Hydrology ◽  
2019 ◽  
Vol 6 (3) ◽  
pp. 61 ◽  
Author(s):  
Kleoniki Demertzi ◽  
Dimitris Papadimos ◽  
Vassilis Aschonitis ◽  
Dimitris Papamichail

This study proposes a simplistic model for assessing the hydroclimatic vulnerability of lakes/reservoirs (LRs) that preserve their steady-state conditions based on regulated superficial discharge (Qd) out of the LR drainage basin. The model is a modification of the Bracht-Flyr et al. method that was initially proposed for natural lakes in closed basins with no superficial discharge outside the basin (Qd = 0) and under water-limited environmental conditions {mean annual ratio of potential/reference evapotranspiration (ETo) versus rainfall (P) greater than 1}. In the proposed modified approach, an additional Qd function is included. The modified model is applied using as a case study the Oreastiada Lake, which is located inside the Kastoria basin in Greece. Six years of observed data of P, ETo, Qd, and lake topography were used to calibrate the modified model based on the current conditions. The calibrated model was also used to assess the future lake conditions based on the future climatic projections (mean conditions of 2061-2080) derived by 19 general circulation models (GCMs) for three cases of climate change (three cases of Representative Concentration Pathways: RCP2.6, RCP4.5 and RCP8.5). The modified method can be used as a diagnostic tool in water-limited environments for analyzing the superficial discharge changes of LRs under different climatic conditions and to support the design of new management strategies for mitigating the impact of climate change on (a) flooding conditions, (b) hydroelectric production, (c) irrigation/industrial/domestic use and (d) minimum ecological flows to downstream rivers.


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