Soil Moisture and Temperature Hourly Data for Dry Creek Experimental Watershed, Southwest Idaho, Treeline Weather Station Pits 3 and 4

Soil Moisture (SM) is one of the key observable variables of the hydrological cycle and therefore of high importance for many disciplines, from meteorology to agriculture. This contribution presents a comparison of different products for the mapping of SM. The aim was to identify the best available solution for the operational monitoring of SM as a drought indicator for the entire area of the European Alps, to be applied in the context of the Interreg Alpine Space project, the Alpine Drought Observatory.The following datasets were considered: Soil Water Index (SWI) of the Copernicus Global Land Service [1]; ERA5 [2]; ERA5-Land [3]; UERRA MESCAN-SURFEX land-surface component [4]. All four datasets offer a different set of advantages and disadvantages related to their spatial resolution, update frequency and latency. As a reference, modelled SM time-series for 307 catchments in Switzerland were used [5]. Switzerland is well suited as a test case for the Alps, due to its different landscapes, from lowlands to high mountain.The intercomparison was based on a correlation analysis of daily absolute SM values and the daily anomalies. Furthermore, the probability to detect certain events, such as persistent dry conditions, was evaluated for each of the SM datasets. First results showed that the temporal dynamics (both in terms of absolute values as well as anomalies) of the re-analysis datasets show a high correlation to the reference. A clear gradient, from the lowlands in the north to the high mountains in the south, with decreasing correlation is evident. The SWI data showed weak correlations to the temporal dynamics of the reference in general. Especially, during spring and the first part of the summer SM is significantly underestimated. This might be related to the influence of snowmelt, which is not taken into account in the two-layer water balance model used to model SM for deeper soil layers. Low coverage in the high mountain areas hampered a thorough comparison with the reference in these areas.The results presented here are the foundation for selecting a suitable source for the operational mapping of SM for the Alpine Drought Observatory. The next steps will be to test the potential of MESCAN-SURFEX and ERA5-Land for the downscaling of ERA5 to take advantage of the low latency of ERA5 and the improved spatial detail of the other two datasets. &#160;Literature:[1]&#160; B. Bauer-marschallinger et al., &#8220;Sentinel-1&#8239;: Harnessing Assets and Overcoming Obstacles,&#8221; IEEE Trans. Geosci. Remote Sens., vol. 57, no. 1, pp. 520&#8211;539, 2019, doi: 10.1109/TGRS.2018.2858004.[2]&#160; H. Hersbach et al., &#8220;ERA5 hourly data on single levels from 1979 to present.&#8221; Copernicus Climate Change Service (C3S) Climate Data Store (CDS), 2018.[3]&#160; Copernicus Climate Change Service, &#8220;ERA5-Land hourly data from 2001 to present.&#8221; ECMWF, 2019, doi: 10.24381/CDS.E2161BAC.[4]&#160; E. Bazile, et al., &#8220;MESCAN-SURFEX Surface Analysis. Deliverable D2.8 of the UERRA Project,&#8221; 2017. Accessed: Jan. 11, 2020. [Online]. Available: http://www.uerra.eu/publications/deliverable-reports.html.[5]&#160; Brunner, et al.: Extremeness of recent drought events in &#160;&#160;&#160;Switzerland: dependence on variable and return period choice, Nat. Hazards Earth Syst. Sci., 19, 2311&#8211;2323, https://doi.org/10.5194/nhess-19-2311-2019, 2019.

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Measurements of soil respiration and simple models dependent on moisture and temperature for an Amazonian southwest tropical forest

Biogeosciences Discussions ◽

10.5194/bgd-6-6147-2009 ◽

2009 ◽

Vol 6 (3) ◽

pp. 6147-6177 ◽

Cited By ~ 1

Author(s):

F. B. Zanchi ◽

H. R. da Rocha ◽

H. C. de Freitas ◽

B. Kruijt ◽

M. J. Waterloo ◽

...

Keyword(s):

Soil Moisture ◽

Soil Respiration ◽

Soil Temperature ◽

Field Measurements ◽

Dry Season ◽

Wet Season ◽

Hourly Data ◽

Fresh Litter ◽

Favorable Conditions

Abstract. Soil respiration plays a significant role in the carbon cycle of Amazonian tropical forests, although in situ measurements have only been poorly reported and the dependence of soil moisture and soil temperature also weakly understood. This work investigates the temporal variability of soil respiration using field measurements, which also included soil moisture, soil temperature and litterfall, from April 2003 to January 2004, in a southwest Brazilian tropical rainforest near Ji-Paraná, Rondônia. The experimental design deployed five automatic (static, semi-opened) soil chambers connected to an infra-red CO2 gas analyzer. The mean half-hourly soil respiration showed a large scattering from 0.6 to 18.9 μmol CO2 m−2 s−1 and the average was 8.0±3.4 μmol CO2 m−2 s−1. Soil respiration varied seasonally, being lower in the dry season and higher in the wet season, which generally responded positively to the variation of soil moisture and temperature year round. The peak was reached in the dry-to-wet season transition (September), this coincided with increasing sunlight, evapotranspiration and ecosystem productivity. Litterfall processes contributed to meet very favorable conditions for biomass decomposition in early wet season, especially the fresh litter on the forest floor accumulated during the dry season. We attempted to fit three models with the data: the exponential Q10 model, the Reichstein model, and the log-soil moisture model. The models do not contradict the scattering of observations, but poorly explain the variance of the half-hourly data, which is improved when the lag-time days averaging is longer. The observations suggested an optimum range of soil moisture, between 0.115

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Factors affecting in the use of weather stations data in predicting surface soil moisture for agricultural applications

Canadian Journal of Soil Science ◽

10.1139/cjss-2021-0034 ◽

2021 ◽

Author(s):

Umesh Acharya ◽

Aaron Lee M. Daigh ◽

Peter G. Oduor

Keyword(s):

Soil Moisture ◽

Cover Crop ◽

Crop Residue ◽

Surface Soil ◽

Agricultural Fields ◽

Growth Stages ◽

Weather Station ◽

Surface Soil Moisture ◽

Crop Type ◽

Weather Stations

Weather stations often provide key information related to soil moisture, temperature and evaporation are used by farmers to decide farm operations of nearby agricultural fields. However, the site conditions at the weather stations where data are recorded may not be similar with these nearby fields. The objective of this study was to determine the level of discrepancies in surface soil moisture between weather stations and nearby agricultural fields based on 1) the soil texture, crop residue cover, crop type, growth stages and 2) temporal dependency of soil moisture to recent rainfall and evaporation rates. Soil moisture from 25 weather stations in the North Dakota Agricultural Weather Network (NDAWN) and 75 nearby fields were measured biweekly during the 2019 growing season in Red River Valley. Field characteristics including soil texture, crop residue cover, crop type and growth stages along with rainfall and potential evapotranspiration were collected during the study period. The regression analysis between surface soil moisture at weather station and nearby field showed higher values for corn at V10 stage (r2=0.92) and for wheat at flowering stage (r2=0.68) and opposite was observed with soybean. We found the regression coefficient of soil moisture with four-day cumulative rainfall slightly increased to 0.51 with an increase in percent residue cover resulting in a decreased root mean square error (RMSE) to 0.063 m3 m-3. In general, we observed that surface soil moisture at weather stations could reasonably predict moisture in nearby agricultural fields considering crop type, soil type, weather, and distance from weather station.

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Review of automatized meteorological stations use for agricultural purposes

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/937/3/032097 ◽

2021 ◽

Vol 937 (3) ◽

pp. 032097

Author(s):

I Dunaieva ◽

V Vecherkov ◽

Y Filina ◽

V Popovych ◽

E Barbotkina ◽

...

Keyword(s):

Soil Moisture ◽

Real Time ◽

Measurement Accuracy ◽

Measured Data ◽

Meteorological Conditions ◽

Weather Station ◽

Weather Stations ◽

The Cost ◽

Operational Data ◽

Soil Moisture Reserves

Abstract The article deals with the questions of application and functioning of automated weather stations in agriculture. Digitalization of agriculture can significantly increase the efficiency of production and reduce the cost of manufacturing products by obtaining and accumulating information about the ongoing technological processes and making appropriate management decisions. A huge role is given to the possibility of obtaining operational data on the level of soil moisture reserves, the prevailing meteorological conditions, etc. in real time. The use of automated meteorological stations makes it possible to obtain data that can be used in the management of operations, requiring control and monitoring. This paper discusses the application and operation of automated meteorological stations in agriculture, and provides an analysis of the operation of the Davis Vantage Pro 2, Sokol-M and Meteobot® Pro weather stations in Krasnogvardeisky, Belogorsky and Saky regions. The analysis of weather station configurations, sensor installation methods, measurement accuracy, and more is made. The measured data was evaluated with the data, obtained from the weather stations of the WMO network. The prospects of further use of automated weather stations in agricultural monitoring tasks are considered.

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Influence of Mesoscale Soil Moisture Patterns on Convective Initiation over the Tibetan Plateau

10.5194/egusphere-egu2020-4943 ◽

2020 ◽

Author(s):

Emma Barton ◽

Christopher Taylor ◽

Cornelia Klein ◽

Phil Harris

Keyword(s):

Soil Moisture ◽

Tibetan Plateau ◽

Land Surface ◽

Climate Models ◽

Monsoon Season ◽

The Tibetan Plateau ◽

Extreme Rainfall Events ◽

Convective Initiation ◽

Hourly Data ◽

The Impact

The Tibetan Plateau is the highest and most extensive plateau in the world, profoundly affecting climate and weather in the region. Due to its average elevation of more than 4000m, provides a strong thermal and dynamical forcing in the mid-troposphere during the summer months, fostering the frequent development of intense storms. Mesoscale convective systems (MCSs) are known to be associated with particularly extreme rainfall events and contribute up to ~60% of rainfall over the Tibetan Plateau (TP) and adjacent areas. In particular, MCSs that form on the TP may move off and bring heavy rain and flooding to downstream parts of China, affecting millions of people. A better understanding of the processes that impact MCS genesis over the TP could contribute to improved forecasting of these extreme events. Furthermore, there is strong evidence for accelerated climate warming on the TP, which may affect convection and makes the identification of factors for MCS development even more important.Previous work in the Sahel has shown that mesoscale soil moisture patterns can influence the initiation of new MCSs, however the relationship has yet to be investigated for the more hydrologically and topographically complex TP. In this study we investigate the impact of mesoscale soil moisture features on convective initiation over the TP during the monsoon season (May &#8211; September) using satellite imagery. Convective clouds are identified using the Fengyun-2 cloud top temperature product. Fengyun-2 is a series of geostationary satellites that provide hourly data, allowing us to track systems as they evolve. Land surface temperature anomalies are used as a proxy to map pre-storm mesoscale soil moisture patterns.Despite the presence of complex topography, we identify a tendency for MCS initiations to occur in the vicinity of mesoscale soil moisture gradients. Our results suggest that improved representation of land-atmosphere coupling on the TP within weather and climate models could impact the entire region.

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Reconstruction of the hazardous flood of 2014 in Magadan city based on coupled hydrometeorological modelling

E3S Web of Conferences ◽

10.1051/e3sconf/202016301007 ◽

2020 ◽

Vol 163 ◽

pp. 01007

Author(s):

Viktoriia Kurovskaia ◽

Olga Makarieva ◽

Nataliia Nesterova ◽

Andrey Shikhov ◽

Tatyana Vinogradova

Keyword(s):

Model Parameters ◽

Correction Coefficient ◽

Weather Station ◽

Distributed Hydrological Model ◽

Time Step ◽

Regional Modelling ◽

Meteorological Model ◽

Catastrophic Flood ◽

North East ◽

Hourly Data

The study assessed the possibility of using a deterministic distributed hydrological model Hydrograph to calculate the maximum discharge of catastrophic flood at the Magadanka River (48.5 km2, city of Magadan, North-East of Russia) in 2014. The model parameters were not calibrated but borrowed from previously performed regional modelling studies. To verify the Hydrograph model streamflow simulations with daily time step were carried out for the period 1971-2015. The median value of Nash-Sutcliffe efficiency was 0.42 for a period of 44 years, which, given the lack of a meteorological station within the catchment, made it possible to evaluate the results as satisfactory. For the catastrophic flood calculation, two types of precipitation data were used: hourly data on precipitation from the nearest weather station and distribution of precipitation for the watershed from the meteorological model WRF. The flood hydrographs were estimated for the initial and corrected sets of the model parameters. The initial set of the model parameters allowed for proper timing of the flood peak but underestimated “observed” maximum value. We introduced the decreasing correction coefficient to the infiltration parameter of the model to “stretch out” the peak and volume of hydrographs. The results have shown that combining the meteorological input from weather station and regional meteorological model may allow for successful flood simulations in ensemble mode.

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