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Dr. Hatim Geli
New Mexico State University, Las Cruces, New Mexico 88003, USA

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Research Keywords & Expertise

0 water resources management
0 Food-Energy-Water Nexus
0 Land use land cover change
0 Hydrology and remote sensing
0 Surface energy balance fluxes

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water resources management
Food-Energy-Water Nexus
Land use land cover change
Surface energy balance fluxes
Drought monitoring and impact analysis

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Journal article
Published: 15 July 2021 in Water
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New Mexico (NM) has been identified as the state in the US that will be most adversely impacted by climate change and associated water stress. Roughly 92% of NM is rangeland, most of which is grazed by beef cattle. We calculated the blue (surface and ground) and green (precipitation) water footprints (WF) of NM beef cattle industry (cow-calf, backgrounding, and feedlot). This analysis indicated that the weighted average WF of NM beef cattle was 28,203 L/kgmeat. The majority of the WF was accounted for green water (82%; 23,063 L/kgmeat) used by rangeland forages. Blue water accounted for only 18% (5140 L/kgmeat) of the total beef WF estimate. The relative contribution of green vs. blue water varied significantly among the different phases of beef production. In cow-calf, green water accounted for 99.5% of the WF whereas blue water, accounted for 100% of beef WF during backgrounding and feedlot. Based on our estimate, NM cow-calf operations is about a third or a quarter of the blue water (m3/year) used to produce corn or wheat, and only 5% or less of the water used to produce cotton or hay. In NM, irrigation accounts for about 84% of freshwater use followed by public/domestic use of 10%. Mining, thermo-electric, livestock production, aquaculture, and industrial uses collectively account for the other 6%.

ACS Style

Mohammed Sawalhah; Hatim Geli; Jerry Holechek; Andres Cibils; Sheri Spiegal; Craig Gifford. Water Footprint of Rangeland Beef Production in New Mexico. Water 2021, 13, 1950 .

AMA Style

Mohammed Sawalhah, Hatim Geli, Jerry Holechek, Andres Cibils, Sheri Spiegal, Craig Gifford. Water Footprint of Rangeland Beef Production in New Mexico. Water. 2021; 13 (14):1950.

Chicago/Turabian Style

Mohammed Sawalhah; Hatim Geli; Jerry Holechek; Andres Cibils; Sheri Spiegal; Craig Gifford. 2021. "Water Footprint of Rangeland Beef Production in New Mexico." Water 13, no. 14: 1950.

Original research article
Published: 04 June 2021 in Frontiers in Environmental Science
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Interconnected food, energy, and water (FEW) nexus systems face many challenges to support human well-being (HWB) and maintain resilience, especially in arid and semiarid regions like New Mexico (NM), United States (US). Insufficient FEW resources, unstable economic growth due to fluctuations in prices of crude oil and natural gas, inequitable education and employment, and climate change are some of these challenges. Enhancing the resilience of such coupled socio-environmental systems depends on the efficient use of resources, improved understanding of the interlinkages across FEW system components, and adopting adaptable alternative management strategies. The goal of this study was to develop a framework that can be used to enhance the resilience of these systems. An integrated food, energy, water, well-being, and resilience (FEW-WISE) framework was developed and introduced in this study. This framework consists mainly of five steps to qualitatively and quantitatively assess FEW system relationships, identify important external drivers, integrate FEW systems using system dynamics models, develop FEW and HWB performance indices, and develop a resilience monitoring criterion using a threshold-based approach that integrates these indices. The FEW-WISE framework can be used to evaluate and predict the dynamic behavior of FEW systems in response to environmental and socioeconomic changes using resilience indicators. In conclusion, the derived resilience index can be used to inform the decision-making processes to guide the development of alternative scenario-based management strategies to enhance the resilience of ecological and socioeconomic well-being of vulnerable regions like NM.

ACS Style

Kamini Yadav; Hatim M. E. Geli; Andres F. Cibils; Michael Hayes; Alexander Fernald; James Peach; Mohammed N. Sawalhah; Vincent C. Tidwell; Lindsay E. Johnson; Ashraf J. Zaied; Melakeneh G. Gedefaw. An Integrated Food, Energy, and Water Nexus, Human Well-Being, and Resilience (FEW-WISE) Framework: New Mexico. Frontiers in Environmental Science 2021, 9, 1 .

AMA Style

Kamini Yadav, Hatim M. E. Geli, Andres F. Cibils, Michael Hayes, Alexander Fernald, James Peach, Mohammed N. Sawalhah, Vincent C. Tidwell, Lindsay E. Johnson, Ashraf J. Zaied, Melakeneh G. Gedefaw. An Integrated Food, Energy, and Water Nexus, Human Well-Being, and Resilience (FEW-WISE) Framework: New Mexico. Frontiers in Environmental Science. 2021; 9 ():1.

Chicago/Turabian Style

Kamini Yadav; Hatim M. E. Geli; Andres F. Cibils; Michael Hayes; Alexander Fernald; James Peach; Mohammed N. Sawalhah; Vincent C. Tidwell; Lindsay E. Johnson; Ashraf J. Zaied; Melakeneh G. Gedefaw. 2021. "An Integrated Food, Energy, and Water Nexus, Human Well-Being, and Resilience (FEW-WISE) Framework: New Mexico." Frontiers in Environmental Science 9, no. : 1.

Journal article
Published: 21 April 2021 in Remote Sensing
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Rangelands provide significant socioeconomic and environmental benefits to humans. However, climate variability and anthropogenic drivers can negatively impact rangeland productivity. The main goal of this study was to investigate structural and productivity changes in rangeland ecosystems in New Mexico (NM), in the southwestern United States of America during the 1984–2015 period. This goal was achieved by applying the time series segmented residual trend analysis (TSS-RESTREND) method, using datasets of the normalized difference vegetation index (NDVI) from the Global Inventory Modeling and Mapping Studies and precipitation from Parameter elevation Regressions on Independent Slopes Model (PRISM), and developing an assessment framework. The results indicated that about 17.6% and 12.8% of NM experienced a decrease and an increase in productivity, respectively. More than half of the state (55.6%) had insignificant change productivity, 10.8% was classified as indeterminant, and 3.2% was considered as agriculture. A decrease in productivity was observed in 2.2%, 4.5%, and 1.7% of NM’s grassland, shrubland, and ever green forest land cover classes, respectively. Significant decrease in productivity was observed in the northeastern and southeastern quadrants of NM while significant increase was observed in northwestern, southwestern, and a small portion of the southeastern quadrants. The timing of detected breakpoints coincided with some of NM’s drought events as indicated by the self-calibrated Palmar Drought Severity Index as their number increased since 2000s following a similar increase in drought severity. Some breakpoints were concurrent with some fire events. The combination of these two types of disturbances can partly explain the emergence of breakpoints with degradation in productivity. Using the breakpoint assessment framework developed in this study, the observed degradation based on the TSS-RESTREND showed only 55% agreement with the Rangeland Productivity Monitoring Service (RPMS) data. There was an agreement between the TSS-RESTREND and RPMS on the occurrence of significant degradation in productivity over the grasslands and shrublands within the Arizona/NM Tablelands and in the Chihuahua Desert ecoregions, respectively. This assessment of NM’s vegetation productivity is critical to support the decision-making process for rangeland management; address challenges related to the sustainability of forage supply and livestock production; conserve the biodiversity of rangelands ecosystems; and increase their resilience. Future analysis should consider the effects of rising temperatures and drought on rangeland degradation and productivity.

ACS Style

Melakeneh Gedefaw; Hatim Geli; Temesgen Abera. Assessment of Rangeland Degradation in New Mexico Using Time Series Segmentation and Residual Trend Analysis (TSS-RESTREND). Remote Sensing 2021, 13, 1618 .

AMA Style

Melakeneh Gedefaw, Hatim Geli, Temesgen Abera. Assessment of Rangeland Degradation in New Mexico Using Time Series Segmentation and Residual Trend Analysis (TSS-RESTREND). Remote Sensing. 2021; 13 (9):1618.

Chicago/Turabian Style

Melakeneh Gedefaw; Hatim Geli; Temesgen Abera. 2021. "Assessment of Rangeland Degradation in New Mexico Using Time Series Segmentation and Residual Trend Analysis (TSS-RESTREND)." Remote Sensing 13, no. 9: 1618.

Journal article
Published: 29 January 2021 in Water
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The spatial and temporal distribution of precipitation is of great importance for the rain-fed agricultural production and the socioeconomics of Mato Grosso (MT), Brazil. MT has a sparse network of ground rain gauges that limits the effective use of precipitation information for sustainable agricultural production and water resources in the region. Several gridded precipitation products from remote sensing and reanalysis of land surface models are currently available that can enhance the use of such information. However, these products are available at different spatial and temporal resolutions which add some challenges to stakeholders (users) to identify their appropriateness for specific applications (e.g., irrigation requirements, length of growing season, and drought monitoring). Thus, it is necessary to provide an assessment of the reliability of these precipitation estimates. The objective of this work was to compare regional precipitation estimates over MT as provided by the Global Land Data Assimilation (GLDAS), Modern-Era Retrospective Analysis for Research and Applications (MERRA), Tropical Rainfall Measurement Mission (TRMM), Global Precipitation Measurement (GPM), and the Global Precipitation Climatology Project (GPCP) with ground-based measurements. The comparison was conducted for the 2000–2018 period at eleven ground-based weather stations that covered different climate zones in MT using daily, monthly, and annual temporal resolutions. The comparison used the Pearson correlation index–r, Willmott index–d, root mean square error—RMSE, and the Wilks methods. The results showed GPM and GLDAS estimates did not differ significantly with the measured daily, monthly, and annual precipitation. TRMM estimates slightly overestimated daily precipitation by about 4.7% but did not show significant difference on the monthly and annual scales when compared with local measurements. The GPCP underestimated annual precipitation by about 7.1%. MERRA underestimated daily, monthly, and annual precipitation by about 22.9% on average. In general, all products satisfactorily estimated monthly precipitation, and most of them satisfactorily estimated annual precipitation; however, they showed low accuracy when estimating daily precipitation. The TRMM, GPM, GPCP, and GLDAS estimates had the highest performance, from high to low, while MERRA showed the lowest performance. The findings of this study can be used to support the decision-making process in the region in application related to water resources management, sustainability of agriculture production, and drought management.

ACS Style

Altemar Junior; Marcelo Biudes; Nadja Machado; George Vourlitis; Hatim Geli; Luiz Santos; Carlos Querino; Israel Ivo; Névio Neto. Assessment of Remote Sensing and Re-Analysis Estimates of Regional Precipitation over Mato Grosso, Brazil. Water 2021, 13, 333 .

AMA Style

Altemar Junior, Marcelo Biudes, Nadja Machado, George Vourlitis, Hatim Geli, Luiz Santos, Carlos Querino, Israel Ivo, Névio Neto. Assessment of Remote Sensing and Re-Analysis Estimates of Regional Precipitation over Mato Grosso, Brazil. Water. 2021; 13 (3):333.

Chicago/Turabian Style

Altemar Junior; Marcelo Biudes; Nadja Machado; George Vourlitis; Hatim Geli; Luiz Santos; Carlos Querino; Israel Ivo; Névio Neto. 2021. "Assessment of Remote Sensing and Re-Analysis Estimates of Regional Precipitation over Mato Grosso, Brazil." Water 13, no. 3: 333.

Review
Published: 17 June 2020 in Sustainability
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Accelerated climate change is a global challenge that is increasingly putting pressure on the sustainability of livestock production systems that heavily depend on rangeland ecosystems. Rangeland management practices have low potential to sequester greenhouse gases. However, mismanagement of rangelands and their conversion into ex-urban, urban, and industrial landscapes can significantly exacerbate the climate change process. Under conditions of more droughts, heat waves, and other extreme weather events, management of risks (climate, biological, financial, political) will probably be more important to the sustainability of ranching than capability to expand output of livestock products in response to rising demand due to population growth. Replacing traditional domestic livestock with a combination of highly adapted livestock and game animals valued for both hunting and meat may be the best strategy on many arid rangelands. Eventually, traditional ranching could become financially unsound across large areas if climate change is not adequately addressed. Rangeland policy, management, and research will need to be heavily focused on the climate change problem.

ACS Style

Jerry L. Holechek; Hatim M. E. Geli; Andres F. Cibils; Mohammed N. Sawalhah. Climate Change, Rangelands, and Sustainability of Ranching in the Western United States. Sustainability 2020, 12, 4942 .

AMA Style

Jerry L. Holechek, Hatim M. E. Geli, Andres F. Cibils, Mohammed N. Sawalhah. Climate Change, Rangelands, and Sustainability of Ranching in the Western United States. Sustainability. 2020; 12 (12):4942.

Chicago/Turabian Style

Jerry L. Holechek; Hatim M. E. Geli; Andres F. Cibils; Mohammed N. Sawalhah. 2020. "Climate Change, Rangelands, and Sustainability of Ranching in the Western United States." Sustainability 12, no. 12: 4942.

Journal article
Published: 05 June 2020 in Remote Sensing
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Accurate estimation of land use/land cover (LULC) areas is critical, especially over the semi-arid environments of the southwestern United States where water shortage and loss of rangelands and croplands are affecting the food production systems. This study was conducted within the context of providing an improved understanding of New Mexico’s (NM’s) Food–Energy–Water Systems (FEWS) at the county level. The main goal of this analysis was to evaluate the most important LULC classes for NM’s FEWS by implementing standardized protocols of accuracy assessment and providing bias-corrected area estimates of these classes. The LULC data used in the study was based on National Land Cover Database (NLCD) legacy maps of 1992, 2001, 2006, 2011, and 2016. The analysis was conducted using the cloud-based geospatial processing and modeling tools available from System for Earth Observation Data Access, Processing, and Analysis for Land Monitoring (SEPAL) of the Food and Agricultural Organization. Accuracy assessment, uncertainty analysis, and bias-adjusted area estimates were evaluated by collecting a total of 11,428 reference samples using the Open Foris Collect Earth tool that provided access to high spatial and temporal resolution images available in Google Earth. The reference samples were allocated using a stratified random sampling approach. The results showed an overall accuracy that ranged from 71%–100% in all six study counties. The user’s and producer’s accuracy of most LULC classes were about or above 80%. The obtained bias-adjusted area estimates were higher than those based on pixel counting. The bias-adjusted area estimates simultaneously showed decreasing and increasing trends in grassland and shrubland, respectively in four counties that include Curry, Roosevelt, Lea, and Eddy during the 1992–2016 period. Doña Ana county experienced increasing and decreasing trends in grassland and shrubland areas, respectively. San Juan county experienced decreasing trends in both grassland and shrubland areas. Cultivated cropland areas showed decreasing trends in three counties in southeast NM that rely on groundwater resources including Curry, Roosevelt, and Lea. Similarly, cultivated cropland areas showed increasing trends in the other three counties that rely on surface water or conjunctive use of surface and groundwater resources including San Juan, Doña Ana, and Eddy. The use of SEPAL allowed for efficient assessment and production of more accurate bias-adjusted area estimates compared to using pixel counting. Providing such information can help in understanding the behavior of NM’s food production systems including rangelands and croplands, better monitoring and characterizing NM’s FEWS, and evaluating their behavior under changing environmental and climatic conditions. More effort is needed to evaluate the ability of the NLCD data and other similar products to provide more accurate LULC area estimates at local scales.

ACS Style

Melakeneh G. Gedefaw; Hatim M.E. Geli; Kamini Yadav; Ashraf J. Zaied; Yelena Finegold; Kenneth G. Boykin. A Cloud-Based Evaluation of the National Land Cover Database to Support New Mexico’s Food–Energy–Water Systems. Remote Sensing 2020, 12, 1830 .

AMA Style

Melakeneh G. Gedefaw, Hatim M.E. Geli, Kamini Yadav, Ashraf J. Zaied, Yelena Finegold, Kenneth G. Boykin. A Cloud-Based Evaluation of the National Land Cover Database to Support New Mexico’s Food–Energy–Water Systems. Remote Sensing. 2020; 12 (11):1830.

Chicago/Turabian Style

Melakeneh G. Gedefaw; Hatim M.E. Geli; Kamini Yadav; Ashraf J. Zaied; Yelena Finegold; Kenneth G. Boykin. 2020. "A Cloud-Based Evaluation of the National Land Cover Database to Support New Mexico’s Food–Energy–Water Systems." Remote Sensing 12, no. 11: 1830.

Journal article
Published: 06 March 2020 in Sustainability
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This study was conducted within the context of providing an improved understanding of New Mexico’s food, energy, water systems (FEWS) and their behavior under variable climate and socioeconomic conditions. The goal of this paper was to characterize the relationships between production and prices of some forage crops (hay, grain sorghum, and corn) that can be used as feed supplements for beef cattle production and the potential impacts from a changing climate (precipitation, temperature) and energy inputs (crude oil production and prices). The analysis was based on 60 years of data (1958–2017) using generalized autoregressive conditional heteroscedasticity models. Hay production showed a declining trend since 2000 and in 2017, it dropped by ~33% compared to that of 2000. Crude oil production (R2 = 0.83) and beef cattle population (R2 = 0.85) were negatively correlated with hay production. A moderate declining trend in mean annual hay prices was also observed. Mean annual range conditions (R2 = 0.60) was negatively correlated with mean annual hay prices, whereas mean annual crude oil prices (R2 = 0.48) showed a positive relationship. Grain sorghum production showed a consistent declining trend since 1971 and in 2017, it dropped by ~91% compared to that of 1971. Mean annual temperature (R2 = 0.58) was negatively correlated with grain sorghum production, while beef cattle population (R2 = 0.61) and range conditions (R2 = 0.51) showed positive linear relationships. Mean annual grain sorghum prices decreased since the peak of 1974 and in 2017, they dropped by ~77% compared to those of 1974. Crude oil prices (R2 = 0.72) and beef cattle population (R2 = 0.73) were positively correlated with mean annual grain sorghum prices. Corn production in 2017 dropped by ~61% compared to the peak that occurred in 1999. Crude oil production (R2 = 0.85) and beef cattle population (R2 = 0.86) were negatively correlated with corn production. Mean annual corn prices showed a declining trend since 1974 and in 2017, they dropped by ~75% compared to those of 1974. Mean annual corn prices were positively correlated with mean annual precipitation (R2 = 0.83) and negatively correlated with crude oil production (R2 = 0.84). These finding can particularly help in developing a more holistic model that integrates FEWS components to explain their response to internal (i.e., management practices) and external (i.e., environmental) stressors. Such holistic modeling can further inform the development and adoption of more sustainable production and resource use practices.

ACS Style

Ashraf J. Zaied; Hatim M. E. Geli; Mohammed N. Sawalhah; Jerry L. Holechek; Andres F. Cibils; Charlotte C. Gard. Historical Trends in New Mexico Forage Crop Production in Relation to Climate, Energy, and Rangelands. Sustainability 2020, 12, 2051 .

AMA Style

Ashraf J. Zaied, Hatim M. E. Geli, Mohammed N. Sawalhah, Jerry L. Holechek, Andres F. Cibils, Charlotte C. Gard. Historical Trends in New Mexico Forage Crop Production in Relation to Climate, Energy, and Rangelands. Sustainability. 2020; 12 (5):2051.

Chicago/Turabian Style

Ashraf J. Zaied; Hatim M. E. Geli; Mohammed N. Sawalhah; Jerry L. Holechek; Andres F. Cibils; Charlotte C. Gard. 2020. "Historical Trends in New Mexico Forage Crop Production in Relation to Climate, Energy, and Rangelands." Sustainability 12, no. 5: 2051.

Journal article
Published: 24 December 2019 in Water
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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 > 0.5 and β > 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.

ACS Style

Hatim M. E. Geli; José González-Piqueras; Christopher M. U. Neale; Claudio Balbontín; Isidro Campos; Alfonso Calera. Effects of Surface Heterogeneity Due to Drip Irrigation on Scintillometer Estimates of Sensible, Latent Heat Fluxes and Evapotranspiration over Vineyards. Water 2019, 12, 81 .

AMA Style

Hatim M. E. Geli, José González-Piqueras, Christopher M. U. Neale, Claudio Balbontín, Isidro Campos, Alfonso Calera. Effects of Surface Heterogeneity Due to Drip Irrigation on Scintillometer Estimates of Sensible, Latent Heat Fluxes and Evapotranspiration over Vineyards. Water. 2019; 12 (1):81.

Chicago/Turabian Style

Hatim M. E. Geli; José González-Piqueras; Christopher M. U. Neale; Claudio Balbontín; Isidro Campos; Alfonso Calera. 2019. "Effects of Surface Heterogeneity Due to Drip Irrigation on Scintillometer Estimates of Sensible, Latent Heat Fluxes and Evapotranspiration over Vineyards." Water 12, no. 1: 81.

Journal article
Published: 02 December 2019 in Sustainability
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In support of Food-Energy-Water Systems (FEWS) analysis to enhance its sustainability for New Mexico (NM), this study evaluated observed trends in beef cattle population in response to environmental and economic changes. The specific goal was to provide an improved understanding of the behavior of NM’s beef cattle production systems relative to precipitation, temperature, rangeland conditions, production of hay and crude oil, and prices of hay and crude oil. Historical data of all variables were available for the 1973–2017 period. The analysis was conducted using generalized autoregressive conditional heteroscedasticity models. The results indicated declining trends in beef cattle population and prices. The most important predictors of beef cattle population variation were hay production, mean annual hay prices, and mean annual temperature, whereas mean annual temperature, cattle feed sold, and crude oil production were the most important predictors for calf population that weigh under 500 lb. Prices of beef cattle showed a strong positive relationship with crude oil production, mean annual hay prices, rangeland conditions, and mean annual precipitation. However, mean annual temperature had a negative relationship with mean annual beef prices. Variation in mean annual calf prices was explained by hay production, mean annual temperature, and crude oil production. This analysis suggested that NM’s beef cattle production systems were affected mainly and directly by mean annual temperature and crude oil production, and to a lesser extent by other factors studied in this research.

ACS Style

Ashraf Zaied; Hatim Geli; Jerry Holechek; Andres Cibils; Mohammed Sawalhah; Charlotte Gard. An Evaluation of Historical Trends in New Mexico Beef Cattle Production in Relation to Climate and Energy. Sustainability 2019, 11, 6840 .

AMA Style

Ashraf Zaied, Hatim Geli, Jerry Holechek, Andres Cibils, Mohammed Sawalhah, Charlotte Gard. An Evaluation of Historical Trends in New Mexico Beef Cattle Production in Relation to Climate and Energy. Sustainability. 2019; 11 (23):6840.

Chicago/Turabian Style

Ashraf Zaied; Hatim Geli; Jerry Holechek; Andres Cibils; Mohammed Sawalhah; Charlotte Gard. 2019. "An Evaluation of Historical Trends in New Mexico Beef Cattle Production in Relation to Climate and Energy." Sustainability 11, no. 23: 6840.

Preprint content
Published: 16 November 2015 in Hydrology and Earth System Sciences Discussions
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Thermal and multispectral remote sensing data from low-altitude aircraft can provide high spatial resolution necessary for sub-field (≤ 10 m) and plant canopy (≤ 1m) scale evapotranspiration (ET) monitoring. In this study, high resolution aircraft sub-meter scale thermal infrared and multispectral shortwave data are used to map ET over vineyards in central California with the Two Source Energy Balance (TSEB) model and with a simple model called DATTUTDUT (Deriving Atmosphere Turbulent Transport Useful To Dummies Using Temperature) which uses contextual information within the image to scale between radiometric land surface temperature (TR) values representing hydrologic limits of potential ET and a non-evaporative surface. Imagery from five days throughout the growing season is used for mapping ET at the sub-field scale. The performance of the two models is evaluated using tower-based energy flux measurements of sensible (H) and latent heat (LE) or ET. The comparison indicates that TSEB was able to derive reasonable ET estimates under varying conditions, likely due to the physically based treatment of the energy and the surface temperature partitioning between the soil/cover crop inter-row and vine canopy elements. On the other hand, DATTUTDUT performance was somewhat degraded presumably because the simple scaling scheme does not consider differences in the two sources (vine and inter-row) of heat and temperature contributions or the effect of surface roughness on the efficiency of heat exchange. Maps of the evaporative fraction (EF = LE/(H + LE)) from the two models had similar spatial patterns but different magnitudes in some areas within the fields on certain days. Large EF discrepancies between the models were found on two of the five days (DOY 162 and 219) when there were significant differences with the tower-based ET measurements, particularly using the DATTUTDUT model. These differences in EF between the models translate to significant variations in daily water use estimates for these two days for the vineyards. Model sensitivity analysis demonstrated the high degree of sensitivity of the TSEB model to the accuracy of the TR data while the DATTUTDUT model was insensitive as is the case with contextual-based models. However, study domain and spatial resolution will significantly influence the ET estimation from the DATTUTDUT model. Future work is planned for developing a hybrid approach that leverages the strengths of both modeling schemes and is simple enough to be used operationally with high resolution imagery.

ACS Style

Ting Xia; William P. Kustas; Martha C. Anderson; Joseph G. Alfieri; Feng Gao; Lynn McKee; John H. Prueger; Hatim M. E. Geli; Christopher M. U. Neale; Luis Sanchez; Maria Mar Alsina; Zhongjing Wang. Mapping evapotranspiration with high resolution aircraft imagery over vineyards using one and two source modeling schemes. Hydrology and Earth System Sciences Discussions 2015, 20, 1523 -1545.

AMA Style

Ting Xia, William P. Kustas, Martha C. Anderson, Joseph G. Alfieri, Feng Gao, Lynn McKee, John H. Prueger, Hatim M. E. Geli, Christopher M. U. Neale, Luis Sanchez, Maria Mar Alsina, Zhongjing Wang. Mapping evapotranspiration with high resolution aircraft imagery over vineyards using one and two source modeling schemes. Hydrology and Earth System Sciences Discussions. 2015; 20 (4):1523-1545.

Chicago/Turabian Style

Ting Xia; William P. Kustas; Martha C. Anderson; Joseph G. Alfieri; Feng Gao; Lynn McKee; John H. Prueger; Hatim M. E. Geli; Christopher M. U. Neale; Luis Sanchez; Maria Mar Alsina; Zhongjing Wang. 2015. "Mapping evapotranspiration with high resolution aircraft imagery over vineyards using one and two source modeling schemes." Hydrology and Earth System Sciences Discussions 20, no. 4: 1523-1545.

Journal article
Published: 01 August 2012 in Journal of Hydrometeorology
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The estimation of sensible heat flux, H, using large aperture scintillometer (LAS) under varying surface heterogeneity conditions was investigated. Surface roughness features characterized by variable topography and vegetation height were represented using data derived from the highly accurate light detection and range (lidar) techniques as well as from traditional vegetation survey and topographic map methods. The study was conducted at the Cibola National Wildlife Refuge, Southern California, over a riparian zone covered with natural vegetation dominated by tamarisk trees interspersed with bare soil in a region characterized by arid to semiarid climatic conditions. Estimates of H were obtained using different representations of surface roughness features derived from both traditional and lidar methods to estimate LAS beam height [z(u)] at each increment u along its path, vegetation height (hc), displacement height (d), and roughness length (z0) combined with the LAS weighing function, W(u), along the path. The effect of the LAS 3D footprint was examined to account for the contribution from the individual patches in the upwind direction, hence on the estimates of H. The results showed better agreement between LAS and Bowen ratio sensible heat fluxes when lidar-derived surface roughness was used, especially when considering the LAS 3D footprint effects. It was also found that, under certain conditions, the LAS path weighted hc and d obtained using the LAS weighting function W(u) is a good approximation of the 3D weighted footprint values.

ACS Style

Hatim M. E. Geli; Christopher M. U. Neale; Doyle Watts; John Osterberg; Henk A. R. De Bruin; Wim Kohsiek; Robert T. Pack; Lawrence E. Hipps. Scintillometer-Based Estimates of Sensible Heat Flux Using Lidar-Derived Surface Roughness. Journal of Hydrometeorology 2012, 13, 1317 -1331.

AMA Style

Hatim M. E. Geli, Christopher M. U. Neale, Doyle Watts, John Osterberg, Henk A. R. De Bruin, Wim Kohsiek, Robert T. Pack, Lawrence E. Hipps. Scintillometer-Based Estimates of Sensible Heat Flux Using Lidar-Derived Surface Roughness. Journal of Hydrometeorology. 2012; 13 (4):1317-1331.

Chicago/Turabian Style

Hatim M. E. Geli; Christopher M. U. Neale; Doyle Watts; John Osterberg; Henk A. R. De Bruin; Wim Kohsiek; Robert T. Pack; Lawrence E. Hipps. 2012. "Scintillometer-Based Estimates of Sensible Heat Flux Using Lidar-Derived Surface Roughness." Journal of Hydrometeorology 13, no. 4: 1317-1331.