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  • Key words  Surface irrigation  (1)
  • LSM  (1)
  • LST hotspots  (1)
  • maximum land surface temperature (LST)  (1)
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  • 1
    Publication Date: 2024-02-28
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Extremely high land surface temperatures affect soil ecological processes, alter land‐atmosphere interactions, and may limit some forms of life. Extreme surface temperature hotspots are presently identified using satellite observations or deduced from complex Earth system models. We introduce a simple, yet physically based analytical approach that incorporates salient land characteristics and atmospheric conditions to globally identify locations of extreme surface temperatures and their upper bounds. We then provide a predictive tool for delineating the spatial extent of land hotspots at the limits to biological adaptability. The model is in good agreement with satellite observations showing that temperature hotspots are associated with high radiation and low wind speed and occur primarily in Middle East and North Africa, with maximum temperatures exceeding 85°C during the study period from 2005 to 2020. We observed an increasing trend in maximum surface temperatures at a rate of 0.17°C/decade. The model allows quantifying how upper bounds of extreme temperatures can increase in a warming climate in the future for which we do not have satellite observations and offers new insights on potential impacts of future warming on limits to plant growth and biological adaptability.〈/p〉
    Description: Plain Language Summary: While satellite imagery can identify extreme land surface temperatures, land and atmospheric conditions for the onset of maximum land surface temperature (LST) have not yet been globally explored. We developed a physically based analytical model for quantifying the value and spatial extent of maximum LST and provide insights into combinations of land and atmospheric conditions for the onset of such temperature extremes. Results show that extreme LST hotspots occur primarily in the Middle East and North Africa with highest values near 85°C. Importantly, persistence of surface temperatures exceeding 75°C limits vegetation growth and disrupts primary productivity such as in Lut desert in Iran. The study shows that with global warming, regions with prohibitive land surface temperatures will expand.〈/p〉
    Description: Key Points: 〈list list-type="bullet"〉 〈list-item〉 〈p xml:lang="en"〉Hotspots for high land surface temperatures (LSTs) were globally identified using a physically based analytical approach incorporating land and atmospheric conditions〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉High LSTs primarily occur in Middle East and North Africa with values exceeding 85°C〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉Maximum LSTs rising at a rate of 0.17°C/decade may limit plant growth and biological adaptability in a warming world〈/p〉〈/list-item〉 〈/list〉 〈/p〉
    Description: Hamburg University of Technology
    Description: European Union's Horizon Europe Research and Innovation Programme
    Description: https://disc.gsfc.nasa.gov/datasets/M2I1NXLFO_5.12.4/summary
    Description: https://disc.gsfc.nasa.gov/datasets/M2T1NXRAD_5.12.4/summary
    Description: https://doi.org/10.5067/MODIS/MCD12C1.006
    Description: https://doi.org/10.3133/ofr20111073
    Description: https://www.nccs.nasa.gov/services/data-collections/land-based-products/nex-gddp-cmip6
    Description: https://doi.org/10.3334/ORNLDAAC/1247
    Keywords: ddc:551.5 ; maximum land surface temperature (LST) ; land conditions ; atmospheric conditions ; LST hotspots
    Language: English
    Type: doc-type:article
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Irrigation science 16 (1996), S. 159-167 
    ISSN: 1432-1319
    Keywords: Key words  Surface irrigation ; Surge flow ; Intake properties ; Heterogeneous soils
    Source: Springer Online Journal Archives 1860-2000
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Notes: Abstract   A simple method for predicting surface irrigation advance trajectories using infiltration parameters and inflow rate as inputs was developed. The difference between the inflow rate and the sum of infiltration rates over the wetted portion of the field equals the flow rate available for advance. An average (characteristic) infiltration rate ahead of the wet portion is computed using a fixed time step. An advance step (for a fixed time step) is calculated from the ratio of the flow rate available for advance and characteristic infiltration rate. Predictions of advance by the proposed method were compared with field observations, with the kinematic wave model, and with analytical solutions of Philip and Farrell (1964). In all cases, the method provided predictions that were in good agreement with field observations, and performed similarly to the kinematic wave model. The method offers a simple and efficient tool for prediction and evaluation of surface irrigation systems under various soil types and variable inflow rates. The method is particularly useful for predictions in fields with spatially and temporally variable intake properties.
    Type of Medium: Electronic Resource
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  • 3
    Publication Date: 2021-07-21
    Description: Modeling of the land surface water‐, energy‐, and carbon balance provides insight into the behavior of the Earth System, under current and future conditions. Currently, there exists a substantial variability between model outputs, for a range of model types, whereby differences between model input parameters could be an important reason. For large‐scale land surface, hydrological, and crop models, soil hydraulic properties (SHP) are required as inputs, which are estimated from pedotransfer functions (PTFs). To analyze the functional sensitivity of widely used PTFs, the water fluxes for different scenarios using HYDRUS‐1D were simulated and predictions compared. The results showed that using different PTFs causes substantial variability in predicted fluxes. In addition, an in‐depth analysis of the soil SHPs and derived soil characteristics was performed to analyze why the SHPs estimated from the different PTFs cause the model to behave differently. The results obtained provide guidelines for the selection of PTFs in large scale models. The model performance in terms of numerical stability, time‐integrated behavior of cumulative fluxes, as well as instantaneous fluxes was evaluated, in order to compare the suitability of the PTFs. Based on this, the Rosetta, Wösten, and Tóth PTF seem to be the most robust PTFs for the Mualem van Genuchten SHPs and the PTF of Cosby for the Brooks Corey functions. Based on our findings, we strongly recommend to harmonize the PTFs used in model inter‐comparison studies to avoid artifacts originating from the choice of PTF rather from different model structures.
    Description: Plain Language Summary: Hydrological models need information about the soil physical characteristics (soil hydraulic parameters), which are in general not available if the models are applied at larger scales (region to global scale). Therefore, pedotransfer functions (PTFs) are classically used, which relate easily available soil properties such as sand‐, silt‐, clay‐content, soil organic carbon content, and soil bulk density, which are available from soil maps, to the soil hydraulic parameters. Unfortunately, there are many different PTFs available in literature. In the study presented, we analyzed the impact of different PTFs on the simulation results of water fluxes and found, that the choice of PTF impacts the simulation results. Further, some PTFs were identified as being less robust compared to others. In general, the study shows that harmonizing PTFs in model‐inter‐comparisons is needed to avoid artifacts originating from the choice of PTF rather from different model structures.
    Description: Key Points: Using different PTFs in hydrological models causes substantial variability in predicted fluxes. We strongly recommend to harmonize the PTFs used in model inter‐comparison studies.
    Keywords: 551.3 ; crop models ; hydrological models ; land surface models ; LSM ; model ensemble mean ; model inter‐comparison ; pedotransfer functions
    Type: article
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