The synergistic use of microwave coarse-scale measurements and two adopted high-resolution indices driven from long-term T-V scatter plot for fine-scale soil moisture estimation

2021 ◽  
pp. 1-28
Author(s):  
Farzane Mohseni ◽  
Mehdi Mokhtarzade
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Fine Scale ◽  
Scatter Plot ◽  
Coarse Scale ◽  
Moisture Estimation

Hyperspectral-derived indices for soil moisture estimation at very high resolution

2014 ◽  
Author(s):  
N. Sanchez ◽  
J. Martinez-Fernandez ◽  
M. Piles ◽  
A. Camps ◽  
M. Vall-llossera ◽  
...  
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Moisture Estimation ◽  
Very High

scholarly journals Deep desiccation of soils observed by long-term high-resolution measurements on a large inclined lysimeter

2020 ◽  
Author(s):  
Markus Merk ◽  
Nadine Goeppert ◽  
Nico Goldscheider
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Vegetation Period ◽  
Test Site ◽  
Change Point Detection ◽  
Key Factors ◽  
Moisture Fluxes ◽  
Meteorological Influences ◽  
Point Detection

Abstract. Availability of long-term and high-resolution measurements of soil moisture is crucial when it comes to understanding all sorts of changes to past soil moisture variations and the prediction of future dynamics. This is particularly true in a world struggling against climate change and its impacts on ecology and economy. Feedback mechanisms between soil moisture dynamics and meteorological influences are key factors when it comes to understanding the occurrence of drought events. We used long-term high-resolution measurements of soil moisture on a large inclined lysimeter at a test site near Karlsruhe, Germany. The measurements indicate (i) a seasonal evaporation depth of over two meters. Statistical analysis and linear regressions indicate (ii) a significant decrease in soil moisture levels over the past two decades. This decrease is most pronounced at the start and the end of the vegetation period. Furthermore, Bayesian change point detection revealed (iii), that this decrease is not uniformly distributed over the complete observation period. Largest changes occur at tipping points during years of extreme drought, with significant changes to the subsequent soil moisture levels. This change affects not only the overall trend in soil moisture, but also the seasonal dynamics. A comparison to modeled data showed (iv) that the occurrence of deep desiccation is not merely dependent on the properties of the soil but is spatially heterogeneous. The study highlights the importance of soil moisture measurements for the understanding of soil moisture fluxes in the vadose zone.

scholarly journals Deep desiccation of soils observed by long-term high-resolution measurements on a large inclined lysimeter

2021 ◽  
Vol 25 (6) ◽  
pp. 3519-3538
Author(s):  
Markus Merk ◽  
Nadine Goeppert ◽  
Nico Goldscheider
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Vegetation Period ◽  
Test Site ◽  
Change Point Detection ◽  
Key Factors ◽  
Moisture Fluxes ◽  
Meteorological Influences ◽  
Point Detection

Abstract. Availability of long-term and high-resolution measurements of soil moisture is crucial when it comes to understanding all sorts of changes to past soil moisture variations and the prediction of future dynamics. This is particularly true in a world struggling against climate change and its impacts on ecology and the economy. Feedback mechanisms between soil moisture dynamics and meteorological influences are key factors when it comes to understanding the occurrence of drought events. We used long-term high-resolution measurements of soil moisture on a large inclined lysimeter at a test site near Karlsruhe, Germany. The measurements indicate (i) a seasonal evaporation depth of over 2 m. Statistical analysis and linear regressions indicate (ii) a significant decrease in soil moisture levels over the past 2 decades. This decrease is most pronounced at the start and the end of the vegetation period. Furthermore, Bayesian change-point detection revealed (iii) that this decrease is not uniformly distributed over the complete observation period. The largest changes occur at tipping points during years of extreme drought, with significant changes to the subsequent soil moisture levels. This change affects not only the overall trend in soil moisture, but also the seasonal dynamics. A comparison to modeled data showed (iv) that the occurrence of deep desiccation is not merely dependent on the properties of the soil but is spatially heterogeneous. The study highlights the importance of soil moisture measurements for the understanding of moisture fluxes in the vadose zone.

scholarly journals Evaluation of TOPMODEL-Based Land Surface–Atmosphere Transfer Scheme (TOPLATS) through a Soil Moisture Simulation

2018 ◽  
Vol 22 (15) ◽  
pp. 1-19 ◽  
Author(s):  
Xiaolei Fu ◽  
Lifeng Luo ◽  
Ming Pan ◽  
Zhongbo Yu ◽  
Ying Tang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Land Surface ◽  
Spatial Scales ◽  
Absolute Difference ◽  
Coarse Scale ◽  
Transfer Scheme ◽  
Surface Atmosphere ◽  
Spatial Coverage

Abstract Better quantification of the spatiotemporal distribution of soil moisture across different spatial scales contributes significantly to the understanding of land surface processes on the Earth as an integrated system. While observational data for root-zone soil moisture (RZSM) often have sparse spatial coverage, model-simulated soil moisture may provide a useful alternative. TOPMODEL-Based Land Surface–Atmosphere Transfer Scheme (TOPLATS) has been widely studied and actively modified in recent years, while a detailed regional application with evaluation currently is still lacking. Thus, TOPLATS was used to generate high-resolution (30 arc s) RZSM based on coarse-scale (0.125°) forcing data over part of the Arkansas–Red River basin. First, the simulated RZSM was resampled to coarse scale to compare with the results of Mosaic, Noah, and VIC from NLDAS. Second, TOPLATS performance was assessed based on the spatial absolute difference among the models. The comparison shows that TOPLATS performance is similar to VIC, but different from Mosaic and Noah. Last, the simulated RZSM was compared with in situ observations of 16 stations in the study area. The results suggest that the simulated spatial distribution of RZSM is largely consistent with the distribution of topographic index (TI) in most instances, as topography was traditionally considered a major, but not the only, factor in horizontal redistribution of soil moisture. In addition, the finer-resolution RZSM can reflect the in situ soil moisture change at most local sites to a certain degree. The evaluation confirms that TOPLATS is a useful tool to estimate high-resolution soil moisture and has great potential to provide regional soil moisture estimates.

A combination of DISPATCH downscaling algorithm with CLASS land surface scheme for soil moisture estimation at fine scale during cloudy days

2016 ◽  
Vol 184 ◽  
pp. 1-14 ◽  
Author(s):  
Najib Djamai ◽  
Ramata Magagi ◽  
Kalifa Goïta ◽  
Olivier Merlin ◽  
Yann Kerr ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Fine Scale ◽  
Land Surface Scheme ◽  
Surface Scheme ◽  
Moisture Estimation

scholarly journals A high-resolution daily gridded meteorological dataset for Serbia made by Random Forest Spatial Interpolation

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Aleksandar Sekulić ◽  
Milan Kilibarda ◽  
Dragutin Protić ◽  
Branislav Bajat
Keyword(s):  
High Resolution ◽  
Random Forest ◽  
Sea Level ◽  
Spatial Interpolation ◽  
Total Precipitation ◽  
Coarse Scale ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Maximum Minimum

AbstractWe produced the first daily gridded meteorological dataset at a 1-km spatial resolution across Serbia for 2000–2019, named MeteoSerbia1km. The dataset consists of five daily variables: maximum, minimum and mean temperature, mean sea-level pressure, and total precipitation. In addition to daily summaries, we produced monthly and annual summaries, and daily, monthly, and annual long-term means. Daily gridded data were interpolated using the Random Forest Spatial Interpolation methodology, based on using the nearest observations and distances to them as spatial covariates, together with environmental covariates to make a random forest model. The accuracy of the MeteoSerbia1km daily dataset was assessed using nested 5-fold leave-location-out cross-validation. All temperature variables and sea-level pressure showed high accuracy, although accuracy was lower for total precipitation, due to the discontinuity in its spatial distribution. MeteoSerbia1km was also compared with the E-OBS dataset with a coarser resolution: both datasets showed similar coarse-scale patterns for all daily meteorological variables, except for total precipitation. As a result of its high resolution, MeteoSerbia1km is suitable for further environmental analyses.

scholarly journals Integrating coarse-scale uncertain soil moisture data into a fine-scale hydrological modelling scenario

2011 ◽  
Vol 8 (3) ◽  
pp. 6031-6067
Author(s):  
H. Vernieuwe ◽  
B. De Baets ◽  
J. Minet ◽  
V. R. N. Pauwels ◽  
S. Lambot ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Epistemic Uncertainty ◽  
Hydrological Modelling ◽  
Scale Model ◽  
Fine Scale ◽  
Coarse Scale ◽  
Soil Moisture Data ◽  
External Data

Abstract. In a hydrological modelling scenario, often the modeller is confronted with external data, such as remotely-sensed soil moisture observations, that become available to update the model output. However, the scale triplet (spacing, extent and support) of these data is often inconsistent with that of the model. Furthermore, the external data can be cursed with epistemic uncertainty. Hence, a method is needed that not only integrates the external data into the model, but that also takes into account the difference in scale and the uncertainty of the observations. In this paper, a synthetic hydrological modelling scenario is set up in which a high-resolution distributed hydrological model is run over an agricultural field. At regular time steps, coarse-scale field-averaged soil moisture data, described by means of possibility distributions (epistemic uncertainty), are retrieved by synthetic aperture radar and assimilated into the model. A method is presented that allows to integrate the coarse-scale possibility distribution of soil moisture content data with the fine-scale model-based soil moisture data. To this end, a scaling relationship between field-averaged soil moisture content data and its corresponding standard deviation is employed.

scholarly journals Portraying Gradients of Structural Complexity in Coral Reefs Using Fine-Scale Depth Profiles

2021 ◽  
Vol 8 ◽  
Author(s):  
Lauriane Ribas-Deulofeu ◽  
Pierre-Alexandre Château ◽  
Vianney Denis ◽  
Chaolun Allen Chen
Keyword(s):  
High Resolution ◽  
Surface Profile ◽  
Structural Complexity ◽  
Mean Square ◽  
Fine Scale ◽  
Coarse Scale ◽  
Predator Prey ◽  
Depth Profiles ◽  
Multiple Levels

Structural complexity is an important feature to understand reef resilience abilities, through its role in mediating predator-prey interactions, regulating competition, and promoting recruitment. Most of the current methods used to measure reef structural complexity fail to quantify the contributions of fine and coarse scales of rugosity simultaneously, while other methods require heavy data computation. In this study, we propose estimating reef structural complexity based on high-resolution depth profiles to quantify the contributions of both fine and coarse rugosities. We adapted the root mean square of the deviation from the assessed surface profile (Rq) with polynomials. The efficiency of the proposed method was tested on nine theoretical cases and 50 in situ transects from South Taiwan, and compared to both the chain method and the visual rugosity index commonly employed to characterize reef structural complexity. The Rq indices proposed as rugosity estimators in this study consider multiple levels of reef rugosity, which the chain method and the visual rugosity index fail to apprehend. Furthermore, relationships were found between Rq scores and specific functional groups in the benthic community. Indeed, the fine scale rugosity of the South Taiwan reefs mainly comes from biotic components such as hard corals, while their coarse scale rugosity is essentially provided by the topographic variations that reflect the geological context of the reefs. This approach allows identifying the component of the rugosity that could be managed and which could, ultimately, improve strategies designed for conservation.

The 2018 drought and its consequences: Investigating the resilience of different tree species based on comprehensive long-term monitoring of forest hydrology

2020 ◽  
Author(s):  
Theresa Blume ◽  
Daniel Balanzategui ◽  
Lisa Schneider ◽  
Daniel Rasche ◽  
Markus Morgner ◽  
...  
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Water Deficit ◽  
Tree Growth ◽  
Tree Species ◽  
Temperate Forest ◽  
Subsurface Water ◽  
Forest Stands ◽  
Northeastern Germany

<p>Many forests in Central Europe experienced unprecedented drought conditions in 2018. The exceptionally long dry period, lasting from early-summer 2018 and into the winter, was followed by another dry summer with record-breaking temperatures.   Ecohydrological consequences of extended droughts for these temperate forest systems are difficult to anticipate, and investigating the resilience of forest hydrological systems requires comprehensive and systematic long-term observations.</p><p>Monitoring at the TERENO-NE temperate forest observatory in northeastern Germany includes input characterization (throughfall and stemflow), high-resolution soil moisture observations in 14 different forest stands down to a depth of 2 m below the soil surface, shallow and deep groundwater observations, sap flow, tree water deficit and high-resolution tree growth measurements since 2012. The investigated forest stands cover the three tree species pine, oak and beech in both pure and mixed stands. This is complemented by terrestrial gravimetric measurements of total water storage changes. Steep hillslope transects allow us to investigate the impact of presence or absence of groundwater availability on tree water uptake and growth.</p><p>We find that after the unprecedented drought in 2018, which already had pronounced ecohydrological effects, the rainfall amounts over the winter 2018/19 were insufficient to refill the subsurface water storages. Dry conditions altered the growth phenology of each monitored tree species, while tree-water deficit and tree growth were negatively impacted in both years, but to varying extent. Soil moisture storage and dynamics are strongly affected and the drought caused a long-term memory effect.</p>

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