Campbell Scientific Research Articles

Modeling and Monitoring of Wood Moisture Content Using Time-Domain Reflectometry

Time-domain reflectometry (TDR) can monitor the moisture content (MC) of water saturated logs stored in wet-decks where the MC exceeds the range that can be measured using traditional moisture meters (>50%). For this application to become routine, it is required that TDR monitoring of wet-decks occurs after establishment, and tools are needed that automate data collection and analysis. We developed models that predict wood MC using three-rod epoxy encased TDR probes inserted into the transverse surface of bolts (prior wet-deck studies were installed on the tangential surface). Models were developed for southern pine, sweetgum, yellow poplar, hickory, red oak, and white oak using a Campbell Scientific TDR100. For each species, at least 37 bolts were soaked for a minimum of three months and then air dried with TDR waveforms, and MC was periodically recorded. Calibrations were developed between MC and the TDR signal using nonlinear mixed effects models. Fixed effects ranged from excellent (southern pine R2 = 0.93) to poor (red oak R2 = 0.36, hickory R2 = 0.38). Independent of wood species, random effects all had a R2 greater than 0.80, which indicates that TDR detects changes in MC at the individual sample level. Use of TDR combined with a datalogger was demonstrated in an operational wet-deck that monitored changes in MC over 12 months, and in a laboratory trial where bolts were exposed to successive wet-dry cycles over 400 days. Both applications demonstrated the utility of TDR to monitor changes in wood MC in high MC environments where periodic measurement is not feasible due to operational safety concerns. Because a saturated TDR reading indicates a saturated MC, and because of the relatively accurate random effects found here, developing individual species models is not necessary for monitoring purposes. Therefore, application of TDR monitoring can be broadly applied for wet-decks, regardless of the species stored.

Impact of Disdrometer Types on Rainfall Erosivity Estimation

Soil erosion by water is affected by the rainfall erosivity, which controls the initial detachment and mobilization of soil particles. Rainfall erosivity is expressed through the rainfall intensity (I) and the rainfall kinetic energy (KE). KE–I relationships are an important tool for rainfall erosivity estimation, when direct measurement of KE is not possible. However, the rainfall erosivity estimation varies depending on the chosen KE–I relationship, as the development of KE–I relationships is affected by the measurement method, geographical rainfall patterns and data handling. This study investigated how the development of KE–I relationships and rainfall erosivity estimation is affected by the use of different disdrometer types. Rainfall data were collected in 1-min intervals from six optical disdrometers at three measurement sites in Austria, one site in Czech Republic and one site in New Zealand. The disdrometers included two disdrometers of each of the following types: the PWS100 Present Weather Sensor from Campbell Scientific, the Laser Precipitation Monitor from Thies Clima and the first generation Parsivel from OTT Hydromet. The fit of KE–I relationships from the literature varied among disdrometers and sites. Drop size and velocity distributions and developed KE–I relationships were device-specific and showed similarities for disdrometers of the same type across measurement sites. This hindered direct comparison of results from different types of disdrometers, even when placed at the same site. Thus, to discern spatial differences in rainfall characteristics the same type of measurement instrument should be used.

Performance of Soil Moisture Sensors in Florida Sandy Soils

Soil moisture sensors can improve water management efficiency by measuring soil volumetric water content (θv) in real time. Soil-specific calibration equations used to calculate θv can increase sensor accuracy. A laboratory study was conducted to evaluate the performance of several commercial sensors and to establish soil-specific calibration equations for different soil types. We tested five Florida sandy soils used for citrus production (Pineda, Riviera, Astatula, Candler, and Immokalee) divided into two depths (0.0–0.3 and 0.3–0.6 m). Readings were taken using twelve commercial sensors (CS650, CS616, CS655 (Campbell Scientific), GS3, 10HS, 5TE, GS1 (Meter), TDT-ACC-SEN-SDI, TDR315, TDR315S, TDR135L (Acclima), and Hydra Probe (Stevens)) connected to a datalogger (CR1000X; Campbell Scientific). Known amounts of water were added incrementally to obtain a broad range of θv. Small 450 cm3 samples were taken to determine the gravimetric water content and calculate the θv used to obtain the soil-specific calibration equations. Results indicated that factory-supplied calibration equations performed well for some sensors in sandy soils, especially 5TE, TDR315L, and GS1 (R2 = 0.92) but not for others (10HS, GS3, and Hydra Probe). Soil-specific calibrations from this study resulted in accuracy expressed as root mean square error (RMSE) ranging from 0.018 to 0.030 m3 m−3 for 5TE, CS616, CS650, CS655, GS1, Hydra Probe, TDR310S, TDR315, TDR315L, and TDT-ACC-SEN-SDI, while lower accuracies were found for 10HS (0.129 m3 m−3) and GS3 (0.054 m3 m−3). This study provided soil-specific calibration equations to increase the accuracy of commercial soil moisture sensors to facilitate irrigation scheduling and water management in Florida sandy soils used for citrus production.

Comparison of three types of laser optical disdrometers under natural rainfall conditions

ABSTRACTOptical disdrometers can be used to estimate rainfall erosivity; however, the relative accuracy of different disdrometers is unclear. This study compared three types of optical laser-based disdrometers to quantify differences in measured rainfall characteristics and to develop correction factors for kinetic energy (KE). Two identical PWS100 (Campbell Scientific), one Laser Precipitation Monitor (Thies Clima) and a first-generation Parsivel (OTT) were collocated with a weighing rain gauge (OTT Pluvio2) at a site in Austria. All disdrometers underestimated total rainfall compared to the rain gauge with relative biases from 2% to 29%. Differences in drop size distribution and velocity resulted in different KE estimates. By applying a linear regression to the KE–intensity relationship of each disdrometer, a correction factor for KE between the disdrometers was developed. This factor ranged from 1.15 to 1.36 and allowed comparison of KE between different disdrometer types despite differences in measured drop size and velocity.

Evaluation and Calibration of Soil Moisture Sensors in Undisturbed Soils

Highlights Evaluated and calibrated soil moisture sensors TDR315, CS655, and GS1 in both field and laboratory. The three sensors were tested in six predominant undisturbed soil types across Mississippi state. Sensors with built-in factory calibration overestimated soil moisture, performed better in sandy loam than clayey soils. It is imperative to calibrate sensors in situ or in undisturbed soils. Abstract. There is increasing interest and demand for growers and researchers to use soil moisture sensors for water management and research in the state of Mississippi. Previous studies demonstrated great challenges in the selection and deployment of sensors for accurate monitoring of soil moisture due to the high variability of soil types and properties. In this study, we evaluated and calibrated three soil moisture sensors, TDR315 (Acclima), CS655 (Campbell Scientific), and GS1 (Meter Group), on-site in fields and in undisturbed soil samples in the laboratory. We selected six predominant soil types from across Mississippi, including four clayey soils (Sharkey clay loam, Brooksville silty clay, Tunica clay, and Dowling clay) and two loamy soils (Commerce sandy loam and Leeper sandy loam) for the tests. Results indicated that these three types of sensors with built-in factory calibration generally overestimated the volumetric water content (θv) of the soils in both field and laboratory. The θv readings of these sensors were closer to the θv determined by gravimetric method in the sandy loam than in the clayey soils. The three types of sensors basically met their factory root mean squared error (RMSE) criteria in loamy soils, but they varied in their performance. The RMSE of TDR315 ranged from 0.03 to 0.17, while CS655 and GS1 had greater RMSE, ranging from 0.03 to 0.29 cm3 cm-3. Specific calibration of TDR315 and CS655 was conducted for each of the six soils using combinations of on-site field data and laboratory undisturbed soil data. Field validation on clay and sandy loam soils suggested that the accuracy of the soil water content measurements by CS655 and TDR315 was acceptable (R2 > 0.6) with proper and undisturbed soil-specific calibration.

Factory-Calibrated Soil Water Sensor Performance Using Multiple Installation Orientations and Depths

Abstract. The use of soil water sensors is commonly advocated to aid and improve irrigation management in crop production systems. However, there are concerns about how sensor type, installation technique, sensor orientation, and soil texture may affect sensor accuracy. A field study was conducted to compare the performance of three commercially available soil water sensors (Acclima 315L, Decagon GS1, and Campbell Scientific 655) and a soil water potential sensor (Watermark 200SS) using different installation orientations of horizontal insertion, laid horizontal placement, and vertical insertion at depths of 15, 46, and 76 cm (6, 18, and 30 in.) in an irrigated clay loam soil field. Results indicated all sensors demonstrated similar trends of soil water content in response to wetting events (precipitation and irrigation) at the 15 cm depth following a 4-month settling period prior from the start of the growing season. Comparatively, the Acclima 315L performed well using horizontal insertion compared to calibrated neutron moisture meters (NMMs) at depths of 46 and 76 cm with R2 of 0.73 and 0.96 and slopes of 1.36 and 1.47, respectively. In addition, water storage in the 0.9 m soil profile integrated using the horizontally inserted Acclima 315L across the three depths matched closely with profile water storage determined by the NMMs with a mean difference (MD) and root mean square error (RMSE) of 25.7 and 36.4 mm. However, site-specific corrections or calibrations for each sensor type are required for accurate soil water content estimations with this clay loam soil for irrigation management applications. Keywords: Corn, Irrigation management, Neutron moisture meter, Soil water content, Soil water sensors, Semi-arid region.

Lysimeter measurements of nocturnal and diurnal grapevine transpiration: Effect of soil water content, and phenology

An experiment was carried out in a semi-arid area of Spain (Albacete) with the objective of quantifying the transpiration of grapevine cv. Tempranillo. Measurements of transpiration were taken in a weighing lysimeter over five years (2012–2016); the soil surface was covered with a waterproof canvas to avoid the evaporative component of evapotranspiration. The sample frequency was 1 s, and a mean value was recorded with a datalogger (CR10X, Campbell Scientific) every 15 min, which allowed for measuring the transpiration every quarter of an hour and therefore identify night-time (Enight) and daytime transpiration (Eday). The results show values of Enight between 3 % of total daily transpiration, in the days with the highest soil water content, and 35 %, in the days in which the value of Eday and the soil water content were very low; although most days it was 12 %. We highlight the Enight in the period after sunset more than we do that in predawn, although in this last period, it was higher close to sunrise. Finally, Enight was analysed throughout the growing season, and from veraison to harvest was the period with the highest values.

Irradiance forecast model for PV generation based on cloudiness web service

Among renewable energies that play a critically important role to achieve a sustainable development in the future, solar photovoltaic (PV) power have been growing dramatically recently. Despite the enormous potential of solar PV, its drawback, which is intermittent in generation, imposes a significant issue on electrical system, such as stability or operation planning of the system. One of the solutions for the problem is PV generation forecast that have been researched in various studies. This paper presents a methodology to obtain an indirect PV production forecast model. Processes of model formation, validation and test are performed in the study using real data from a Campbell Scientific weather station Grenoble, France.

Soil Water Sensor Performance and Corrections with Multiple Installation Orientations and Depths under Three Agricultural Irrigation Treatments.

Performance evaluations and corrections of soil water sensors have not been studied using different installation orientations under various irrigation treatments in the Texas High Plains. This study evaluated the performance of four sensors using factory calibration and derived field corrections as compared to calibrated neutron moisture meters (NMMs). Sensor performance was assessed using horizontal insertion, laid horizontal placement, and vertical insertion at 15.2, 45.7, and 76.2 cm depths in a clay loam soil with three irrigation treatments. Results indicated the factory-calibrated Acclima 315 L performed satisfactorily using horizontal insertion as compared to NMM measurements at 45.7 and 76.2 cm depths with a ±2% mean difference (MD) and <3.5% root mean square error (RMSE). The factory-calibrated Acclima 315 L using horizontal insertion also performed satisfactorily across all irrigation treatments according to soil profile water storage (MD = 0.36% and RMSE = 3.25%). Generally, the factory-calibrated Decagon GS1 and Campbell Scientific 655 using vertical insertion agreed more closely with NMM measurements compared with other installation orientations. There was a significant underestimation of water storage (>60 mm) in the 0.9 m soil profile using the Watermark 200SS. In summary, field corrections are required for Decagon GS1, Campbell Scientific 655, and Watermark 200SS sensors.

Adjustment of CO2 flux measurements due to the bias in the EC150 infrared gas analyzer

During the Regional Approaches to Climate Change (REACCH) program, eddy covariance monitoring over agricultural fields were used to estimate annual carbon and water budgets in the inland Pacific Northwest. Here, we assess the effect of a bias in the high-frequency CO2 concentration measurements using the Campbell Scientific EC150 infra-red gas analyzer on the CO2 fluxes and field-scale carbon balances. The bias stems from using a lower frequency temperature measurement to calculate the CO2 density, which misses higher frequency temperature fluctuations. To generate the bias adjustment, data were collected over four similar agricultural sites as part of the Long-Term Agroecosystem Research network for multiple months using the same four instrument sets used in the REACCH project. The difference between the high-frequency and low-frequency CO2 fluxes were regressed against the kinematic heat fluxes to generate a correction equation for each instrument set, which were applied to the historical REACCH data to determine the effect of the bias on the measured and gap-filled flux values. The re-calculated positive biases in the measured fluxes were 40 gC-CO2 m−2 yr-1 to 126 gC-CO2 m−2 yr-1, indicating greater losses to the atmosphere than initially estimated. Once gap-filled, three out of fourteen site-years switched from weak carbon sinks to weak carbon sources. When the carbon exported via harvest was included in the budget calculation the bias correction still impacted the source/sink strength but did not change the sign of the carbon balance. Overall, the total net ecosystem exchange decreased between 300–470 gC-CO2 m-2 per site (29–46%) over the 4 crop-years from the bias adjustment process.

A low-cost Arduino-based datalogger with cellular modem and FTP communication for irrigation water use monitoring to enable access to CropManage

Abstract The Resource Conservation District of Santa Cruz County implemented a project to improve irrigation management through providing field assistance to growers. A web-based decision support tool called CropManage ( https://v3.cropmanage.ucanr.edu ) developed by the University of California Cooperative Extension (UCCE) of Monterey County aids growers with irrigation scheduling. However, CropManage requires a flowmeter and a monitoring station to track water use in the field. In this article, we describe a device that was conceived as a low-cost alternative to Campbell Scientific flowmeter-monitoring stations that include data logger, modem, enclosure, battery, solar panel and charge regulator and cost above $2000. The device was designed for low-cost, ease of construction and with the capability of emulating the Campbell Scientific equipment functions and outputs. The devices were enabled with FTP communication to a central FTP server and were built with an Arduino MEGA, an Adafruit Datalogging Shield and an Adafruit FONA cellular modem. A voltage divider was added to monitor the external 12 V battery voltage and a DC/DC converter was used to convert 12 V to 5 V. Each field station, including the device, battery, enclosure and solar panel has a total cost below $300, while the FTP server costs less than $100. The device was tested for two years in filed conditions and gave output equivalent to the Campbell Scientific equipment. The device is a low-cost technology that enables growers to gain access to CropManage cheaply and reliably.

A Device for Instantaneously Estimating Duff Moisture Content Is also Effective for Grassland Fuels

Fine-fuel moisture is an important variable in the wildland fire environment, but measuring live fuel moisture is time-consuming. There is a strong incentive to develop technologies that provide instantaneous measurements of fine-fuel moisture. Campbell Scientific, Inc. markets a device that uses dielectric permittivity to measure the moisture content of duff fuels in forests; this Duff Moisture Meter (DMM600) might also be applied to herbaceous grassland fuels but its effectiveness has not been tested. This paper describes how grassland fuel samples collected for the DMM600 do well to represent the broader fuelbed, and that the dielectric permittivity values of the DMM600 correlate well with the actual moisture content of uncured grassland fuels. Results suggest the DMM600 can effectively estimate moisture content in uncured grassland fuels, including the overall fuelbed as well as live herbaceous fuels and well-aggregated samples of the grassland litter layer. Calibration equations and tips to ensure representative data are provided.

Aerosol backscatter profiles from ceilometers: validation of water vapor correction in the framework of CeiLinEx2015

Abstract. With the rapidly growing number of automated single-wavelength backscatter lidars (ceilometers), their potential benefit for aerosol remote sensing received considerable scientific attention. When studying the accuracy of retrieved particle backscatter coefficients, it must be considered that most of the ceilometers are influenced by water vapor absorption in the spectral range around 910 nm. In the literature methodologies have been proposed to correct for this effect; however, a validation was not yet performed. In the framework of the ceilometer intercomparison campaign CeiLinEx2015 in Lindenberg, Germany, hosted by the German Weather Service, it was possible to tackle this open issue. Ceilometers from Lufft (CHM15k and CHM15kx, operating at 1064 nm), from Vaisala (CL51 and CL31) and from Campbell Scientific (CS135), all operating at a wavelength of approximately 910 nm, were deployed together with a multi-wavelength research lidar (RALPH) that served as a reference. In this paper the validation of the water vapor correction is performed by comparing ceilometer backscatter signals with measurements of the reference system extrapolated to the water vapor regime. One inherent problem of the validation is the spectral extrapolation of particle optical properties. For this purpose AERONET measurements and inversions of RALPH signals were used. Another issue is that the vertical range where validation is possible is limited to the upper part of the mixing layer due to incomplete overlap and the generally low signal-to-noise ratio and signal artifacts above that layer. Our intercomparisons show that the water vapor correction leads to quite a good agreement between the extrapolated reference signal and the measurements in the case of CL51 ceilometers at one or more wavelengths in the specified range of the laser diode's emission. This ambiguity is due to the similar effective water vapor transmission at several wavelengths. In the case of CL31 and CS135 ceilometers the validation was not always successful. That suggests that error sources beyond the water vapor absorption might be dominant. For future applications we recommend monitoring the emitted wavelength and providing “dark” measurements on a regular basis.

Determining groundwater recharge and vapor flow in dune sediments using a weighable precision meteo lysimeter

Dune belts are crucial for the recharge of coastal aquifers. In spite of their hydrological relevance for the maintenance of precious natural wetland and wildlife environments and a range of other ecosystem services, only limited knowledge of soil water dynamics in dune belts is currently available. This study presents soil water balance components measured during one hydrological year using a high precision meteo-lysimeter with lower boundary control installed in a coastal dune belt under a dry subhumid climate in southern Spain close to the Atlantic Ocean. The site is equipped with a cylindrical lysimeter of 1 m2 surface and 1.50 m height (METER Group, Inc. USA) and a weighing resolution of 10 g, 2 SC650 soil moisture sensors (Campbell Scientific, Logan, UT) and 1 automatic meteorological station. The lower boundary condition at the bottom of the lysimeter is controlled at 1.4 m depth by a bidirectional peristaltic pump to maintain field conditions. Results show a recharge rate of 64% of the precipitation measured by the lysimeter. Diurnal oscillations of the measured upper boundary flow during days without rainfall represented vapor adsorption and real evaporation rates ranging between 0.3 and 0.4 mm/day and 0.4 and 0.6 mm/day, respectively throughout the whole year summing up an annual vapor adsorption of 77 mm. The measured precipitation of the lysimeter exceeded pluviometer data by 13% as a result of vapor adsorption. The presented results provide a precise balance of soil water components in a coastal dune belt including the relevant contribution of vapor flow.

Performance evaluation of a recently developed soil water content, dielectric permittivity, and bulk electrical conductivity electromagnetic sensor

CS655 Water Content Reflectometer (WCR) (Campbell Scientific, Inc., Logan, UT, USA) is a recently developed multiparameter electromagnetic sensor measuring volumetric soil water content (θ), bulk soil electrical conductivity (σb), and temperature. In this study, CS655 sensor’s performance was investigated through laboratory experiments using a set of liquids with known dielectric and salinity properties and soils featuring a wide range of conditions (including physico-chemical properties, water regimes and salinity of the water solution). The sensor’s performance was analyzed in comparison with WET and ML2 theta probe (Delta-T Device Ltd, Cambridge, UK) dielectric sensors. It was found that CS655 apparent dielectric permittivity (εa) readings were higher than that of Topp’s permittivity-water content relationship, especially at higher soil water content values, as much as 12 dimensionless permittivity units. The results suggested that the relationship between experimentally measured soil water content (θm) and εa was strongly linear (0.911<R2<0.997). The most accurate results were provided by the multi-point calibration method. Moreover, for the case of non-conductive soils, Kelleners’s method provides similar εa values with CS655 sensor readings for a maximum σb value of about 0.8 dS m−1. Concerning the use of empirical calibration equations, which include the effect of bulk electrical conductivity in εa, the obtained results suggest that the equation θ=aεa+b+cσb has a strong physical basis and adequate performance (RMSE<0.03 m3 m-3). Finally, the investigation of the εa-σb relationship revealed that it is strongly linear and that slope mainly depends on the pore water electrical conductivity (σp), which is closely related to the soil solution salinity in contact with plant roots that influences plants growth. The Malliki-Walzcak model provide more reliable σp predictions as compared to the Hilhorst model.

Spatio-temporal evolution of temperature and fluid flow through a new “thermo-lithological” boundary; the case of a pit crater of Karthala volcano (Comoros archipelago) refilled on January 13th 2007 by a lava flow

On January 13th 2007 an effusive eruption on the top of Karthala volcano, in the Comoros islands, emitted a lava flow which has been perfectly constrained inside the cylindrical shape of the Choungou Chagnoumeni pit crater; 225 m in diameter and with a thickness of about 7 m.This eruptive event, with a known geometry before the eruptive event, give a unique opportunity to study a “thermo-lithological” structural boundary recently born, and follow its thermal and fluid flow evolution in time.The motivation of this survey is to better understand some scientific questions such as: How fluid flows evolve in time along a new thermo-lithological boundary? How lava temperature cooling induce changes in hydrothermal circulation? Different data set have been acquired on the field in order to discuss these problematics. On March 2008, a temperature monitoring was installed with a data logger (CR 1000 Campbell Scientific) and 11 sensors placed at 30 cm depth, 1 m apart, inside the crater, along a straight profile, perpendicular to the western rim of the Choungou Chagnoumeni crater. Data were recorded during 275 days out of 677 days, through 4 different periods between 3rd March 2008 and 8th January 2010.On June 2009, high resolution electrical resistivity tomography (ERT) coupled with soil CO2 diffuse degassing was performed above the monitoring line of temperature sensors along a profile of 128 m long, with ERT electrodes and CO2 measurements located each 2 m.Numerical modeling of the temperatures was also tested on this case study, thanks to a finite element method (FEM) code using the Rheolef C++ library. The aim of using a numerical code, integrating a maximum of parameters, have been to better interpret the other data acquired on the field.The lateral permeability transition induced by the crater refilled with lava flow material was attested by the soil diffuse degassing profile.Coupling ERT and temperature modeling allow evidencing the heat transfer with conductive processes.The most striking result has been the inversion of the lateral temperature gradient which evolves during the first three years of cooling, from the highest temperature in direction to the center of the crater to the highest temperature in direction to the boundary of the crater.Such a result highlights the importance of structural boundary in dragging hydrothermal fluids and has been interpreted by a change in the main parameter governing the heat transfer close to the boundary of the crater, which evolved from (1) a lava heat source toward (2) a higher permeability area constituted by the boundary of the crater. This study clearly displays the importance of the lateral permeability gradient in changing the hydrothermal circulation in time.

Assessing water demand with remote sensing for two coriander varieties

The use of remote sensing to determine water needs has been successfully applied by several authors to different crops, maintaining, as an important basis, the relationship between the normalized difference vegetation index (NDVI) and biophysical variables, such as the fraction of coverage (fc) and the basal crop coefficient (Kcb). Therefore, this study quantified the water needs of two varieties of coriander (UNAPAL Laurena CL and UNAPAL Precoso CP) based on the response of fc and Kcb, using remote sensors and a water balance according to the FAO-56 methodology. A Campbell Scientific meteorological station, a commercial digital camera and a portable spectro radiometer were used to obtain information on the environmental conditions and the crop. By means of remote sensing associated with a water balance, it was found that the water demand was 156 mm for CL and 151 mm for CP until the foliage harvest (41 d after sowing); additionally, the initial Kcb was 0.14, the mean Kcb was 1.16 (approximately) and the final Kcb was 0.71 (approximately).

Two months of disdrometer data in the Paris area

Abstract. The Hydrology, Meteorology, and Complexity laboratory of École des Ponts ParisTech (hmco.enpc.fr) has made a data set of optical disdrometer measurements available that come from a campaign involving three collocated devices from two different manufacturers, relying on different underlying technologies (one Campbell Scientific PWS100 and two OTT Parsivel2 instruments). The campaign took place in January–February 2016 in the Paris area (France). Disdrometers provide access to information on the size and velocity of drops falling through the sampling area of the devices of roughly a few tens of cm2. It enables the drop size distribution to be estimated and rainfall microphysics, kinetic energy, or radar quantities, for example, to be studied further. Raw data, i.e. basically a matrix containing a number of drops according to classes of size and velocity, along with more aggregated ones, such as the rain rate or drop size distribution with filtering, are available. Link to the data set: https://zenodo.org/record/1240168 (DOI: https://doi.org/10.5281/zenodo.1240168).

Characterization of land surface energy fluxes in a tropical lowland rice paddy

A field experiment was conducted in 2015 to study the land surface energy fluxes from tropical lowland rice paddy in eastern India with an objective to determine the mass, momentum, and energy exchange rates between rice paddies and the atmosphere. All the land surface energy fluxes were measured by eddy covariance (EC) system (make Campbell Scientific) in dry season (DS, 1–125 Julian days), dry fallow (DF, 126–181 Julian days), wet season (WS, 182–324 Julian days), and wet fallow (WF, 325–365 Julian days). The rice was cultivated in dry season (January–May) and wet season (July–November) in low wet lands and the ground is kept fallow during the remainder of the year. Results showed that albedo varied from 0.09 to 0.24 and showed positive value from morning 6:00 h until evening 18:00 h. Mean soil temperature (Tg) was highest in DF, while the skin temperature (Ts) was highest in WS. Average Bowen ratio (B) ranged from 0.21 to 0.64 and large variation in B was observed during the fallow periods as compared to the cropping seasons. The magnitude of aerodynamic, canopy, and climatological resistances increased with the progress of cropping season and their magnitudes decreased during the end of both cropping seasons and found minimum during the fallow periods. At a constant vapor pressure deficit (VPD) at 0.16, 0.18, 0.15, and 0.43 kPa, latent heat flux (LE) initially increased, but later it tended to level off with an increase in VPD. The actual evapotranspiration (ETa) during both the cropping seasons was higher than the fallow period. This study can be used as a source of default values for many land surface energy fluxes which are required in various meteorological or air-quality models for rice paddies. A larger imbalance of energy was observed during the wet season as the energy is stored and perhaps advected in the fresh water.

Shore-based monitoring of flow dynamics in a steep bedrock canyon river

The pace of landscape evolution is set by bedrock erosion in canyons. This phenomenon occurs by various geological processes including plucking of bedrock blocks and abrasion by saltating bedload and suspended load in highly turbulent flows. For a better understanding of the river flow characteristics in bedrock rivers, a comprehensive study of flow dynamics was undertaken in Black Canyon in the Fraser River, British Columbia. We used shore-based video imagery of the river to study surface flow dynamics. The shore-based monitoring system consisted of a Campbell Scientific camera mounted at the top of the canyon walls. We monitored the water surface boils due to upwelling and determined river surface flow velocities from the shore-based imagery. Automatic detection of the upwelling surface boils leads to a better understanding of the secondary circulation patterns and flow structures in this large steep river bedrock canyon. The data collection and analytical procedures developed in this research are cost-effective tools for remotely determining flow dynamics, which can be applied to other rivers.