Two source energy balance model

Presented at the fifth international conference on irrigation and drainage, Irrigation and drainage for food, energy and the environment on November 3-6, 2009 in Salt Lake City, Utah.Includes bibliographical references.Spatial estimation of evapotranspiration (ET) from satellite imagery is important in agricultural studies because it provides information about the spatial variability of crop growing patterns and health, as well as for crop water requirements. The two-source energy balance model is one of the techniques used successfully in estimating ET spatially, through the estimation of surface energy fluxes such as sensible heat flux H, soil heat flux G, net radiation Rn, and latent heat flux LE, the latter being extrapolated to daily ET. The current study applies the two-source model to rain fed agricultural field located in the Walnut Creek watershed south of Ames, Iowa. Landsat TM images used to perform the analysis with the support of ground based data were acquired during the SMACEX project conducted in the summer of 2002. A visual basic interface called SETMI was programmed to interact with ArcGIS and perform the analysis spatially. A footprint model was used to compare the estimates of the different fluxes with measurements from eddy covariance flux towers. Two different closure methods were used to overcome the lack of closure problem in the eddy covariance measurements. Generally, the results show good agreements between the measurements and the estimates. The results show an underestimation of sensible heat flux with RMSE of 30 (Wm-2) and latent heat flux with RMSE of 45 (Wm-2). The net radiation and the soil heat flux shows RMSE of 17 (Wm-2) and 29 (Wm-2), respectively. The daily ET resulted in a RMSE of 0.71 (mm/day) and BIAS of -0.29 (mm/day)

Improvement and further development of SSM/I overland parameter algorithms using the WetNet workstation

Since the launch of the DMSP Special Sensor Microwave/Imager (SSM/I), several algorithms have been developed to retrieve overland parameters. These include the present operational algorithms resulting from the Navy calibration/validation effort such as land surface type (Neale et al. 1990), land surface temperature (McFarland et al. 1990), surface moisture (McFarland and Neale, 1991) and snow parameters (McFarland and Neale, 1991). In addition, other work has been done including the classification of snow cover and precipitation using the SSM/I (Grody, 1991). Due to the empirical nature of most of the above mentioned algorithms, further research is warranted and improvements can probably be obtained through a combination of radiative transfer modelling to study the physical processes governing the microwave emissions at the SSM/I frequencies, and the incorporation of additional ground truth data and special cases into the regression data sets. We have proposed specifically to improve the retrieval of surface moisture and snow parameters using the WetNet SSM/I data sets along with ground truth information namely climatic variables from the NOAA cooperative network of weather stations as well as imagery from other satellite sensors such as the AVHRR and Thematic Mapper. In the case of surface moisture retrievals the characterization of vegetation density is of primary concern. The higher spatial resolution satellite imagery collected at concurrent periods will be used to characterize vegetation types and amounts which, along with radiative transfer modelling should lead to more physically based retrievals. Snow parameter retrieval algorithm improvement will initially concentrate on the classification of snowpacks (dry snow, wet snow, refrozen snow) and later on specific products such as snow water equivalent. Significant accomplishments in the past year are presented

Evaluation of a hybrid remote sensing evapotranspiration model for variable rate irrigation management

Accurate generation of spatial irrigation prescriptions is essential for implementation and evaluation of variable rate irrigation (VRI) technology. A hybrid remote sensing evapotranspiration (ET) model was evaluated for use in developing irrigation prescriptions for a VRI center pivot. The model is a combination of a two-source energy balance model and a reflectance based crop coefficient water balance model. Spatial ET and soil water depletion were modeled for a 10 km2 area consisting of rainfed and irrigated maize fields in eastern Nebraska for 2013. Multispectral images from Landsat 8 Operational Land Imager and Thermal Infrared Sensor were used as model input. Modeled net radiation and soil heat fluxes compared well with measurements from eddy covariance systems located within three fields in the study area. Modeled sensible heat flux did not compare well. Latent heat flux compared well for the only mid-summer image, but poorly for the one spring and two fall images. The water balance ET compared well with the two-source energy balance ET for irrigated maize, but not for dryland maize. Image frequency is thought to be a contributing factor in the poor performance of the water balance. In 2015 the hybrid model will be used to generate irrigation prescription maps for a VRI system located in the study area based on modeled soil moisture depletion. Future research will focus on model parameterization and utilize aerial imagery and satellite imagery from other sensors for improved image frequency. Note: this is a revision of the original paper correcting erroneous data where one of the flux sites was mistakenly analyzed as soybeans, when it was actually maize. Mean biased error signs have also been corrected

Twenty-three unsolved problems in hydrology (UPH) – a community perspective

This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through online media, followed by two workshops through which a large number of potential science questions were collated, prioritised, and synthesised. In spite of the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work. Questions remain focused on the process-based understanding of hydrological variability and causality at all space and time scales. Increased attention to environmental change drives a new emphasis on understanding how change propagates across interfaces within the hydrological system and across disciplinary boundaries. In particular, the expansion of the human footprint raises a new set of questions related to human interactions with nature and water cycle feedbacks in the context of complex water management problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will help guide research efforts for some years to come

Evaluation of a Hybrid Reflectance-Based Crop Coefficient and Energy Balance Evapotranspiration Model for Irrigation Management

Accurate generation of spatial soil water maps is useful for many types of irrigation management. A hybrid remote sensing evapotranspiration (ET) model combining reflectance-based basal crop coefficients (Kcbrf) and a two-source energy balance (TSEB) model was modified and validated for use in real-time irrigation management. We modeled spatial ET for maize and soybean fields in eastern Nebraska for the 2011-2013 growing seasons. We used Landsat 5, 7, and 8 imagery as remote sensing inputs. In the TSEB, we used the Priestly-Taylor (PT) approximation for canopy latent heat flux, as in the original model formulations. We also used the Penman-Monteith (PM) approximation for comparison. We compared energy balance fluxes and computed ET with measurements from three eddy covariance systems within the study area. Net radiation was underestimated by the model when data from a local weather station were used as input, with mean bias error (MBE) of -33.8 to -40.9 W m-2. The measured incident solar radiation appeared to be biased low. The net radiation model performed more satisfactorily when data from the eddy covariance flux towers were input into the model, with MBE of 5.3 to 11.2 W m-2. We removed bias in the daily energy balance ET using a dimensionless multiplier that ranged from 0.89 to 0.99. The bias-corrected TSEB ET, using weather data from a local weather station and with local ground data in thermal infrared imagery corrections, had MBE = 0.09 mm d-1 (RMSE = 1.49 mm d-1) for PM and MBE = 0.04 mm d-1 (RMSE = 1.18 mm d-1) for PT. The hybrid model used statistical interpolation to combine the two ET estimates. We computed weighting factors for statistical interpolation to be 0.37 to 0.50 for the PM method and 0.56 to 0.64 for the PT method. Provisions were added to the model, including a real-time crop coefficient methodology, which allowed seasonal crop coefficients to be computed with relatively few remote sensing images. This methodology performed well when compared to basal crop coefficients computed using a full season of input imagery. Water balance ET compared favorably with the eddy covariance data after incorporating the TSEB ET. For a validation dataset, the magnitude of MBE decreased from -0.86 mm d-1 (RMSE = 1.37 mm d-1) for the Kcbrfalone to -0.45 mm d-1 (RMSE = 0.98 mm d-1) and -0.39 mm d-1 (RMSE = 0.95 mm d-1) with incorporation of the TSEB ET using the PM and PT methods, respectively. However, the magnitudes of MBE and RMSE were increased for a running average of daily computations in the full May-October periods. The hybrid model did not necessarily result in improved model performance. However, the water balance model is adaptable for real-time irrigation scheduling and may be combined with forecasted reference ET, although the low temporal frequency of satellite imagery is expected to be a challenge in real-time irrigation management

Tools for evaluating and monitoring effectiveness of urban landscape water conservation interventions and programs

Our research objective was to investigate ways to evaluate landscape water use to help cities more effectively direct water conservation programs to locations with capacity to conserve. Research was conducted in connection with a landscape irrigation evaluation delivered through a city-sponsored Water Check Program. Research efforts led to development of several assessment and monitoring tools including: Landscape Irrigation Ratio (LIR), Participant Outcome Evaluation Tool, and Program Evaluation Tool. We utilized these tools to identify locations with capacity to conserve water applied to landscapes, compare water use before and after the water check, and evaluate Water Check Program effectiveness. We found the LIR approach successfully distinguished residential locations efficiently or acceptably using water applied to landscapes from ones with use considered inefficient or excessive. In analyzing change in participants’ water use and eliminating explanations other than the water check, we found factors influencing landscape water use tend to be highly contextualized and the intervention itself needed to be analyzed. The majority of participants who adopted the water check recommendations successfully reduced their landscape water use, but results indicate water check programs can be designed for greater effectiveness by accommodating participants’ differing knowledge and skill levels. We argue that the tools we developed provide the water conservation field with a needed set of common assessment methods. We conclude that landscape water checks have the potential to provide people with the information and problem-solving skills necessary to maintain residential landscapes using appropriate amounts of water if they are well designed, delivered, and monitored

Influence of Behavioral State, Sex, and Season on Resource Selection by Jaguars (Panthera onca): Always on the Prowl?

How a predator uses its landscape to move through its territory and acquire prey is a fundamental question for scientific research. The influence of abiotic and biotic factors on space use of large carnivores has profound implications for their future management and conservation. In the Pantanal, Brazil, jaguars (Panthera onca) are the apex predator, but conflicts with cattle depredations pose a risk to their future conservation. We examined whether behavioral state, sex, and season influenced how jaguars used the landscape in the Pantanal. To accomplish this, we radio‐collared four females and six males; radio‐collared jaguars were monitored for 76 radio‐months with 11,787 GPS locations acquired. We developed resource selection functions (RSFs) examining how female and male jaguars used their landscape during three behavioral states (moving, killing native prey, killing cattle) during two seasons (dry, wet). From the RSF models, we found similar variables and relationships of landscape characteristics that jaguars selected for when moving and when depredating native prey and cattle. While moving, jaguars selected for locations that were either in dense cover or very near dense cover, with higher plant diversity and closer to water than available across the landscape. While null models suggested jaguars opportunistically depredated native prey in the dry season and cattle in the wet season, there was some indication they selected for specific landscape characteristics, mainly dense cover when killing cattle in the dry season and native prey in the wet season. Both sexes killed native prey and cattle within dense cover or close to dense cover as expected of an ambush predator. Particular habitat types were not important as long as there was dense cover for concealment. Additionally, jaguars killed prey closer to water than was available on the landscape. The similar variables across the models showed the importance of dense cover and distance to dense cover during all three behavioral states indicating jaguars in the Pantanal were “always on the prowl.” Understanding the spatial requirements for jaguars during the acquisition of native prey and cattle may lead to improved management strategies to allow for continued coexistence of jaguars in an area of traditional cattle production

Influence of behavioral state, sex, and season on resource selection by jaguars (\u3ci\u3ePanthera onca\u3c/i\u3e): Always on the prowl?

How a predator uses its landscape to move through its territory and acquire prey is a fundamental question for scientific research. The influence of abiotic and biotic factors on space use of large carnivores has profound implications for their future management and conservation. In the Pantanal, Brazil, jaguars (Panthera onca) are the apex predator, but conflicts with cattle depredations pose a risk to their future conservation. We examined whether behavioral state, sex, and season influenced how jaguars used the landscape in the Pantanal. To accomplish this, we radio-collared four females and six males; radiocollared jaguars were monitored for 76 radio-months with 11,787 GPS locations acquired. We developed resource selection functions (RSFs) examining how female and male jaguars used their landscape during three behavioral states (moving, killing native prey, killing cattle) during two seasons (dry, wet). From the RSF models, we found similar variables and relationships of landscape characteristics that jaguars selected for when moving and when depredating native prey and cattle. While moving, jaguars selected for locations that were either in dense cover or very near dense cover, with higher plant diversity and closer to water than available across the landscape. While null models suggested jaguars opportunistically depredated native prey in the dry season and cattle in the wet season, there was some indication they selected for specific landscape characteristics, mainly dense cover when killing cattle in the dry season and native prey in the wet season. Both sexes killed native prey and cattle within dense cover or close to dense cover as expected of an ambush predator. Particular habitat types were not important as long as there was dense cover for concealment. Additionally, jaguars killed prey closer to water than was available on the landscape.The similar variables across the models showed the importance of dense cover and distance to dense cover during all three behavioral states indicating jaguars in the Pantanal were “always on the prowl.” Understanding the spatial requirements for jaguars during the acquisition of native prey and cattle may lead to improved management strategies to allow for continued coexistence of jaguars in an area of traditional cattle production

Effects of Surface Heterogeneity Due to Drip Irrigation on Scintillometer Estimates of Sensible, Latent Heat Fluxes and Evapotranspiration over Vineyards

Accurate estimates of sensible (H) and latent (LE) heat fluxes and actual evapotranspiration (ET) are required for monitoring vegetation growth and improved agricultural water management. A large aperture scintillometer (LAS) was used to provide these estimates with the objective of quantifying the effects of surface heterogeneity due to soil moisture and vegetation growth variability. The study was conducted over drip-irrigated vineyards located in a semi-arid region in Albacete, Spain during summer 2007. Surface heterogeneity was characterized by integrating eddy covariance (EC) observations of H, LE and ET; land surface temperature (LST) and normalized difference vegetation index (NDVI) data from Landsat and MODIS sensors; LST from an infrared thermometer (IRT); a data fusion model; and a two-source surface energy balance model. The EC observations showed 16% lack of closure during unstable atmospheric conditions and was corrected using the residual method. The comparison between the LAS and EC measurements of H, LE, and ET showed root mean square difference (RMSD) of 25 W m−2, 19 W m−2, and 0.41 mm day−1, respectively. LAS overestimated H and underestimated both LE and ET by 24 W m−2, 34 W m−2, and 0.36 mm day−1, respectively. The effects of soil moisture on LAS measurement of H was evaluated using the Bowen ratio, β. Discrepancies between HLAS and HEC were higher at β ≤ 0.5 but improved at 1 ≥ β \u3e 0.5 and β \u3e 1.0 with R2 of 0.76, 0.78, and 0.82, respectively. Variable vineyard growth affected LAS performance as its footprints saw lower NDVILAS compared to that of the EC (NDVIEC) by ~0.022. Surface heterogeneity increased during wetter periods, as characterized by the LST–NDVI space and temperature vegetation dryness index (TVDI). As TVDI increased (decreased) during drier (wetter) conditions, the discrepancies between HLAS and HEC, as well as LELAS and LEEC Re decreased (increased). Thresholds of TVDI of 0.3, 0.25, and 0.5 were identified, above which better agreements between LAS and EC estimates of H, LE, and ET, respectively, were obtained. These findings highlight the effectiveness and ability of LAS in monitoring vegetation growth over heterogonous areas with variable soil moisture, its potential use in supporting irrigation scheduling and agricultural water management over large regions

Water, Energy, and Carbon Footprints of Bioethanol from the U.S. and Brazil

Driven by biofuel policies, which aim to reduce greenhouse gas (GHG) emissions and increase domestic energy supply, global production and consumption of bioethanol have doubled between 2007 and 2016, with rapid growth in corn-based bioethanol in the U.S. and sugar cane-based bioethanol in Brazil. Advances in crop yields, energy use efficiency in fertilizer production, biomass-to-ethanol conversion rates, and energy efficiency in ethanol production have improved the energy balance and GHG emission reduction potential of bioethanol. In the current study, the water, energy, and carbon footprints of bioethanol from corn in the U.S. and sugar cane in Brazil were assessed. The results show that U.S. corn bioethanol has a smaller water footprint (541 L water/L bioethanol) than Brazilian sugar cane bioethanol (1115 L water/L bioethanol). Brazilian sugar cane bioethanol has, however, a better energy balance (17.7 MJ/L bioethanol) and smaller carbon footprint (38.5 g CO2e/MJ) than U.S. bioethanol, which has an energy balance of 11.2 MJ/L bioethanol and carbon footprint of 44.9 g CO2e/MJ. The results show regional differences in the three footprints and highlight the need to take these differences into consideration to understand the implications of biofuel production for local water resources, net energy production, and climate change mitigation