hydrological fluxes
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2021 ◽  
Author(s):  
Andrew M. Ireson ◽  
Ines Sanchez‐Rodriguez ◽  
Sujan Basnet ◽  
Haley Brauner ◽  
Talia Bobenic ◽  
...  

MAUSAM ◽  
2021 ◽  
Vol 57 (4) ◽  
pp. 639-652
Author(s):  
A. A. L. N. SARMA ◽  
S. SRINIVAS

bl 'kks/k&i= esa ;g crk;k x;k gS fd lewps fo’o esa fo|eku izkÑfrd lalk/kuksa ds nksguksa ¼VsªLM QqVfizaV½ ds QyLo:Ik fo’o tyok;q Ik)fr vO;ofLFkr gks tkrh gSA tks {ks=h; leL;kvksa lesr fo’o tyh; pØ dks vkSj vf/kd rhoz djus ds fy, mRrjnk;h ekuh tk ldrh gSA bl 'kks/k&i= esa ty larqyu fun’kZ ds ek/;e ls Hkkjr esa tyh; {ks= ds ekeys esa bl rF; dks le>us dk iz;kl fd;k x;k gSA bl laca/k esa dh xbZ tk¡p ls eq[;r% lewps Hkkjr ds tyh; QyDlksa ij bulks@yulks flXuy ds tyok;q laca/kh nwj laidZ ds izHkkoksa dh tkudkjh izkIr gqbZ gSA       It is reported that the traced footprints across the world are the consequences of the perturbed world climate system that might be responsible in intensifying the world hydrological cycle with regional implications. An attempt is made here to understand this fact in case of hydrological regime over India through water balance model. The investigation mainly addresses the climate teleconnection impacts of ENSO/LNSO signal on the hydrological fluxes for All India.


2021 ◽  
Vol 48 (2) ◽  
pp. 205-214
Author(s):  
Panagiotis Michopoulos

Abstract The distribution and cycling of nickel (Ni) in forests is greatly affected by their proximity to emission sources of the metal. The throughfall deposition is always richer in Ni than the bulk deposition. It can be inferred that some dry deposition enriches the throughfall. In remote forested areas, the hydrological fluxes of Ni do not differ a lot from those in litterfall. In addition, the current year needles in conifers have higher concentrations than the older needles, a sign of absorption and mobility of the metal. In contrast, near an industrial Ni source the older needles accumulate much more of the metal. The Ni content in bark tissue can be used to map the deposition distribution of the metal around an area (rural or urban). The concentrations of Ni in forest soils is also dependent on their distances from the Ni emission sources and the nature of the soil parent material. The Ni concentrations increase with soil depth due to the geogenic origin of the metal. Low pH greatly enhances the mobility of the metal in soils, much more than the leachability of organic matter.


Author(s):  
Andrew Ireson ◽  
Seth Amankwah ◽  
Sujan Basnet ◽  
Talia Bobenic ◽  
Morgan Braaten ◽  
...  

Using data from five long-term field sites measuring soil moisture, we show the limitations of using soil moisture observations alone to constrain modelled hydrological fluxes. We test a land surface model, MESH/CLASS, with two configurations: one where the soil hydraulic properties are determined using a pedotransfer function (the texture-based calibration) and one where they are assigned directly (the hydraulic properties-based calibration). The hydraulic properties-based calibration outperforms the texture-based calibration in terms of reproducing changes in soil moisture storage within a 1.6 m deep profile at each site, but both perform reasonably well, especially in the summer months. When the models are constrained using observations of changes in soil moisture, the predicted hydrological fluxes are subject to very large uncertainties associated with equifinality. The uncertainty is larger for the hydraulic properties-based calibration, even though the performance was better. We argue that since the pedotransfer functions constrain the model parameters in the texture-based calibrations in an unrealistic way, the texture-based calibration underestimates the uncertainty in the fluxes. We recommend that reproducing observed cumulative changes in soil moisture storage should be considered a necessary but insufficient criterion of model success. Additional sources of information are needed to reduce uncertainties, and these could include improved estimation of the soil hydraulic properties and direct observations of fluxes, particularly evapotranspiration.


Geophysics ◽  
2021 ◽  
pp. 1-84
Author(s):  
Andrew D. Parsekian ◽  
Dario Grana ◽  
Felipe dos Anjos Neves ◽  
Mark S. Pleasants ◽  
Mark Seyfried ◽  
...  

The belowground architecture of the Critical Zone consists of soil and rock in various stages of weathering and wetness that acts as a medium for biological growth, mediates chemical reactions, and controls partitioning of hydrological fluxes. Hydrogeophysical imaging provides unique insights into geometries and properties of the earth materials that are present in the Critical Zone and beyond the reach of direct observation besides sparse wellbores. Improved understanding of Critical Zone architecture can be achieved by leveraging geophysical measurements of the subsurface. Creating categorical models of the Critical Zone is valuable for driving hydrological models and comparing belowground architectures between different sites to interpret weathering processes. The Critical Zone architecture is revealed through a novel comparison of hillslopes by applying facies classification in the elastic-electric domain driven by surface-based hydrogeophysical measurements. Three pairs of hillslopes grouped according to common geologic substrates – granite, volcanic extrusive, and glacially altered, are classified by five different hydro-facies classes to reveal relative wetness and weathering states. The hydro-facies classifications are robust to the choice of initial mean values used in the classification and non-contemporaneous timing of geophysical data acquisition. These results will lead to improved interdisciplinary models of Critical Zone processes at various scales, and to an increased ability to predict hydrologic timing and partitioning. Beyond the hillslope scale, this enhanced capability to compare Critical Zone architecture can also be exploited at the catchment scale with implications for improved understanding of the link between rock weathering, hydrochemical fluxes, and landscape morphology.


Author(s):  
Sujay V. Kumar ◽  
Thomas Holmes ◽  
Niels Andela ◽  
Imtiaz Dharssi ◽  
Vinodkumar ◽  
...  
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