The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform

Florence Cassel - One of the best experts on this subject based on the ideXlab platform.

  • policy driven sustainable saline drainage disposal and Forage Production in the western san joaquin valley of california
    Sustainability, 2020
    Co-Authors: Amninder Singh, Nigel W T Quinn, Sharon E Benes, Florence Cassel
    Abstract:

    Environmental policies to address water quality impairments in the San Joaquin River of California have focused on the reduction of salinity and selenium-contaminated subsurface agricultural drainage loads from westside sources. On 31 December 2019, all of the agricultural drainage from a 44,000 ha subarea on the western side of the San Joaquin River basin was curtailed. This policy requires the on-site disposal of all of the agricultural drainage water in perpetuity, except during flooding events, when emergency drainage to the River is sanctioned. The reuse of this saline agricultural drainage water to irrigate Forage crops, such as ‘Jose’ tall wheatgrass and alfalfa, in a 2428 ha reuse facility provides an economic return on this pollutant disposal option. Irrigation with brackish water requires careful management to prevent salt accumulation in the crop root zone, which can impact Forage yields. The objective of this study was to optimize the sustainability of this reuse facility by maximizing the evaporation potential while achieving cost recovery. This was achieved by assessing the spatial and temporal distribution of the root zone salinity in selected fields of ‘Jose’ tall wheatgrass and alfalfa in the drainage reuse facility, some of which have been irrigated with brackish subsurface drainage water for over fifteen years. Electromagnetic soil surveys using an EM-38 instrument were used to measure the spatial variability of the salinity in the soil profile. The tall wheatgrass fields were irrigated with higher salinity water (1.2–9.3 dS m−1) compared to the fields of alfalfa (0.5–6.5 dS m−1). Correspondingly, the soil salinity in the tall wheatgrass fields was higher (12.5 dS m−1–19.3 dS m−1) compared to the alfalfa fields (8.97 dS m−1–14.4 dS m−1) for the years 2016 and 2017. Better leaching of salts was observed in the fields with a subsurface drainage system installed (13–1 and 13–2). The depth-averaged root zone salinity data sets are being used for the calibration of the transient hydro-salinity computer model CSUID-ID (a one-dimensional version of the Colorado State University Irrigation Drainage Model). This user-friendly decision support tool currently provides a useful framework for the data collection needed to make credible, field-scale salinity budgets. In time, it will provide guidance for appropriate leaching requirements and potential blending decisions for sustainable Forage Production. This paper shows the tie between environmental drainage policy and the role of local governance in the development of sustainable irrigation practices, and how well-directed collaborative field research can guide future resource management.

Sarah Covello - One of the best experts on this subject based on the ideXlab platform.

  • estimating rangeland Forage Production using remote sensing data from a small unmanned aerial system suas and planetscope satellite
    Remote Sensing, 2019
    Co-Authors: Han Liu, Royce E. Larsen, Scott M. Devine, Leslie M. Roche, Anthony O’ T. Geen, Andy J.y. Wong, Sarah Covello, Ra Dahlgren, Yufang Jin
    Abstract:

    Author(s): Liu, H; Dahlgren, RA; Larsen, RE; Devine, SM; Roche, LM; O' Geen, AT; Wong, AJY; Covello, S; Jin, Y | Abstract: Rangelands cover ~23 million hectares and support a $3.4 billion annual cattle industry in California. Large variations in Forage Production from year to year and across the landscape make grazing management difficult. We here developed optimized methods to map high-resolution Forage Production using multispectral remote sensing imagery. We conducted monthly flights using a Small Unmanned Aerial System (sUAS) in 2017 and 2018 over a 10-ha deferred grazing rangeland. Daily maps of NDVI at 30-cm resolution were first derived by fusing monthly 30-cm sUAS imagery and more frequent 3-m PlanetScope satellite observations. We estimated aboveground net primary Production as a product of absorbed photosynthetically active radiation (APAR) derived from NDVI and light use efficiency (LUE), optimized as a function of topography and climate stressors. The estimated Forage Production agreed well with field measurements having a R2 of 0.80 and RMSE of 542 kg/ha. Cumulative NDVI and APAR were less correlated with measured biomass (R2 = 0.68). Daily Forage Production maps captured similar seasonal and spatial patterns compared to field-based biomass measurements. Our study demonstrated the utility of aerial and satellite remote sensing technology in supporting adaptive rangeland management, especially during an era of climatic extremes, by providing spatially explicit and near-real-time Forage Production estimates.

  • estimating rangeland Forage Production using remote sensing data from a small unmanned aerial system suas and planetscope satellite
    Remote Sensing, 2019
    Co-Authors: Randy A. Dahlgren, Royce E. Larsen, Scott M. Devine, Leslie M. Roche, Anthony O’ T. Geen, Andy J.y. Wong, Sarah Covello
    Abstract:

    Author(s): Liu, H; Dahlgren, RA; Larsen, RE; Devine, SM; Roche, LM; O' Geen, AT; Wong, AJY; Covello, S; Jin, Y | Abstract: © 2019 by the authors. Rangelands cover ~23 million hectares and support a $3.4 billion annual cattle industry in California. Large variations in Forage Production from year to year and across the landscape make grazing management difficult. We here developed optimized methods to map high-resolution Forage Production using multispectral remote sensing imagery. We conducted monthly flights using a Small Unmanned Aerial System (sUAS) in 2017 and 2018 over a 10-ha deferred grazing rangeland. Daily maps of NDVI at 30-cm resolution were first derived by fusing monthly 30-cm sUAS imagery and more frequent 3-m PlanetScope satellite observations. We estimated aboveground net primary Production as a product of absorbed photosynthetically active radiation (APAR) derived from NDVI and light use efficiency (LUE), optimized as a function of topography and climate stressors. The estimated Forage Production agreed well with field measurements having a R2 of 0.80 and RMSE of 542 kg/ha. Cumulative NDVI and APAR were less correlated with measured biomass (R2 = 0.68). Daily Forage Production maps captured similar seasonal and spatial patterns compared to field-based biomass measurements. Our study demonstrated the utility of aerial and satellite remote sensing technology in supporting adaptive rangeland management, especially during an era of climatic extremes, by providing spatially explicit and near-real-time Forage Production estimates.

  • Estimating Rangeland Forage Production Using Remote Sensing Data from a Small Unmanned Aerial System (sUAS) and PlanetScope Satellite
    MDPI AG, 2019
    Co-Authors: Han Liu, Randy A. Dahlgren, Royce E. Larsen, Scott M. Devine, Leslie M. Roche, Anthony O’ T. Geen, Andy J.y. Wong, Sarah Covello, Yufang Jin
    Abstract:

    Rangelands cover ~23 million hectares and support a $3.4 billion annual cattle industry in California. Large variations in Forage Production from year to year and across the landscape make grazing management difficult. We here developed optimized methods to map high-resolution Forage Production using multispectral remote sensing imagery. We conducted monthly flights using a Small Unmanned Aerial System (sUAS) in 2017 and 2018 over a 10-ha deferred grazing rangeland. Daily maps of NDVI at 30-cm resolution were first derived by fusing monthly 30-cm sUAS imagery and more frequent 3-m PlanetScope satellite observations. We estimated aboveground net primary Production as a product of absorbed photosynthetically active radiation (APAR) derived from NDVI and light use efficiency (LUE), optimized as a function of topography and climate stressors. The estimated Forage Production agreed well with field measurements having a R2 of 0.80 and RMSE of 542 kg/ha. Cumulative NDVI and APAR were less correlated with measured biomass ( R 2 = 0.68). Daily Forage Production maps captured similar seasonal and spatial patterns compared to field-based biomass measurements. Our study demonstrated the utility of aerial and satellite remote sensing technology in supporting adaptive rangeland management, especially during an era of climatic extremes, by providing spatially explicit and near-real-time Forage Production estimates

Amninder Singh - One of the best experts on this subject based on the ideXlab platform.

  • policy driven sustainable saline drainage disposal and Forage Production in the western san joaquin valley of california
    Sustainability, 2020
    Co-Authors: Amninder Singh, Nigel W T Quinn, Sharon E Benes, Florence Cassel
    Abstract:

    Environmental policies to address water quality impairments in the San Joaquin River of California have focused on the reduction of salinity and selenium-contaminated subsurface agricultural drainage loads from westside sources. On 31 December 2019, all of the agricultural drainage from a 44,000 ha subarea on the western side of the San Joaquin River basin was curtailed. This policy requires the on-site disposal of all of the agricultural drainage water in perpetuity, except during flooding events, when emergency drainage to the River is sanctioned. The reuse of this saline agricultural drainage water to irrigate Forage crops, such as ‘Jose’ tall wheatgrass and alfalfa, in a 2428 ha reuse facility provides an economic return on this pollutant disposal option. Irrigation with brackish water requires careful management to prevent salt accumulation in the crop root zone, which can impact Forage yields. The objective of this study was to optimize the sustainability of this reuse facility by maximizing the evaporation potential while achieving cost recovery. This was achieved by assessing the spatial and temporal distribution of the root zone salinity in selected fields of ‘Jose’ tall wheatgrass and alfalfa in the drainage reuse facility, some of which have been irrigated with brackish subsurface drainage water for over fifteen years. Electromagnetic soil surveys using an EM-38 instrument were used to measure the spatial variability of the salinity in the soil profile. The tall wheatgrass fields were irrigated with higher salinity water (1.2–9.3 dS m−1) compared to the fields of alfalfa (0.5–6.5 dS m−1). Correspondingly, the soil salinity in the tall wheatgrass fields was higher (12.5 dS m−1–19.3 dS m−1) compared to the alfalfa fields (8.97 dS m−1–14.4 dS m−1) for the years 2016 and 2017. Better leaching of salts was observed in the fields with a subsurface drainage system installed (13–1 and 13–2). The depth-averaged root zone salinity data sets are being used for the calibration of the transient hydro-salinity computer model CSUID-ID (a one-dimensional version of the Colorado State University Irrigation Drainage Model). This user-friendly decision support tool currently provides a useful framework for the data collection needed to make credible, field-scale salinity budgets. In time, it will provide guidance for appropriate leaching requirements and potential blending decisions for sustainable Forage Production. This paper shows the tie between environmental drainage policy and the role of local governance in the development of sustainable irrigation practices, and how well-directed collaborative field research can guide future resource management.

Yufang Jin - One of the best experts on this subject based on the ideXlab platform.

  • estimating rangeland Forage Production using remote sensing data from a small unmanned aerial system suas and planetscope satellite
    Remote Sensing, 2019
    Co-Authors: Han Liu, Royce E. Larsen, Scott M. Devine, Leslie M. Roche, Anthony O’ T. Geen, Andy J.y. Wong, Sarah Covello, Ra Dahlgren, Yufang Jin
    Abstract:

    Author(s): Liu, H; Dahlgren, RA; Larsen, RE; Devine, SM; Roche, LM; O' Geen, AT; Wong, AJY; Covello, S; Jin, Y | Abstract: Rangelands cover ~23 million hectares and support a $3.4 billion annual cattle industry in California. Large variations in Forage Production from year to year and across the landscape make grazing management difficult. We here developed optimized methods to map high-resolution Forage Production using multispectral remote sensing imagery. We conducted monthly flights using a Small Unmanned Aerial System (sUAS) in 2017 and 2018 over a 10-ha deferred grazing rangeland. Daily maps of NDVI at 30-cm resolution were first derived by fusing monthly 30-cm sUAS imagery and more frequent 3-m PlanetScope satellite observations. We estimated aboveground net primary Production as a product of absorbed photosynthetically active radiation (APAR) derived from NDVI and light use efficiency (LUE), optimized as a function of topography and climate stressors. The estimated Forage Production agreed well with field measurements having a R2 of 0.80 and RMSE of 542 kg/ha. Cumulative NDVI and APAR were less correlated with measured biomass (R2 = 0.68). Daily Forage Production maps captured similar seasonal and spatial patterns compared to field-based biomass measurements. Our study demonstrated the utility of aerial and satellite remote sensing technology in supporting adaptive rangeland management, especially during an era of climatic extremes, by providing spatially explicit and near-real-time Forage Production estimates.

  • Estimating Rangeland Forage Production Using Remote Sensing Data from a Small Unmanned Aerial System (sUAS) and PlanetScope Satellite
    MDPI AG, 2019
    Co-Authors: Han Liu, Randy A. Dahlgren, Royce E. Larsen, Scott M. Devine, Leslie M. Roche, Anthony O’ T. Geen, Andy J.y. Wong, Sarah Covello, Yufang Jin
    Abstract:

    Rangelands cover ~23 million hectares and support a $3.4 billion annual cattle industry in California. Large variations in Forage Production from year to year and across the landscape make grazing management difficult. We here developed optimized methods to map high-resolution Forage Production using multispectral remote sensing imagery. We conducted monthly flights using a Small Unmanned Aerial System (sUAS) in 2017 and 2018 over a 10-ha deferred grazing rangeland. Daily maps of NDVI at 30-cm resolution were first derived by fusing monthly 30-cm sUAS imagery and more frequent 3-m PlanetScope satellite observations. We estimated aboveground net primary Production as a product of absorbed photosynthetically active radiation (APAR) derived from NDVI and light use efficiency (LUE), optimized as a function of topography and climate stressors. The estimated Forage Production agreed well with field measurements having a R2 of 0.80 and RMSE of 542 kg/ha. Cumulative NDVI and APAR were less correlated with measured biomass ( R 2 = 0.68). Daily Forage Production maps captured similar seasonal and spatial patterns compared to field-based biomass measurements. Our study demonstrated the utility of aerial and satellite remote sensing technology in supporting adaptive rangeland management, especially during an era of climatic extremes, by providing spatially explicit and near-real-time Forage Production estimates

Anthony O’ T. Geen - One of the best experts on this subject based on the ideXlab platform.

  • estimating rangeland Forage Production using remote sensing data from a small unmanned aerial system suas and planetscope satellite
    Remote Sensing, 2019
    Co-Authors: Randy A. Dahlgren, Royce E. Larsen, Scott M. Devine, Leslie M. Roche, Anthony O’ T. Geen, Andy J.y. Wong, Sarah Covello
    Abstract:

    Author(s): Liu, H; Dahlgren, RA; Larsen, RE; Devine, SM; Roche, LM; O' Geen, AT; Wong, AJY; Covello, S; Jin, Y | Abstract: © 2019 by the authors. Rangelands cover ~23 million hectares and support a $3.4 billion annual cattle industry in California. Large variations in Forage Production from year to year and across the landscape make grazing management difficult. We here developed optimized methods to map high-resolution Forage Production using multispectral remote sensing imagery. We conducted monthly flights using a Small Unmanned Aerial System (sUAS) in 2017 and 2018 over a 10-ha deferred grazing rangeland. Daily maps of NDVI at 30-cm resolution were first derived by fusing monthly 30-cm sUAS imagery and more frequent 3-m PlanetScope satellite observations. We estimated aboveground net primary Production as a product of absorbed photosynthetically active radiation (APAR) derived from NDVI and light use efficiency (LUE), optimized as a function of topography and climate stressors. The estimated Forage Production agreed well with field measurements having a R2 of 0.80 and RMSE of 542 kg/ha. Cumulative NDVI and APAR were less correlated with measured biomass (R2 = 0.68). Daily Forage Production maps captured similar seasonal and spatial patterns compared to field-based biomass measurements. Our study demonstrated the utility of aerial and satellite remote sensing technology in supporting adaptive rangeland management, especially during an era of climatic extremes, by providing spatially explicit and near-real-time Forage Production estimates.

  • estimating rangeland Forage Production using remote sensing data from a small unmanned aerial system suas and planetscope satellite
    Remote Sensing, 2019
    Co-Authors: Han Liu, Royce E. Larsen, Scott M. Devine, Leslie M. Roche, Anthony O’ T. Geen, Andy J.y. Wong, Sarah Covello, Ra Dahlgren, Yufang Jin
    Abstract:

    Author(s): Liu, H; Dahlgren, RA; Larsen, RE; Devine, SM; Roche, LM; O' Geen, AT; Wong, AJY; Covello, S; Jin, Y | Abstract: Rangelands cover ~23 million hectares and support a $3.4 billion annual cattle industry in California. Large variations in Forage Production from year to year and across the landscape make grazing management difficult. We here developed optimized methods to map high-resolution Forage Production using multispectral remote sensing imagery. We conducted monthly flights using a Small Unmanned Aerial System (sUAS) in 2017 and 2018 over a 10-ha deferred grazing rangeland. Daily maps of NDVI at 30-cm resolution were first derived by fusing monthly 30-cm sUAS imagery and more frequent 3-m PlanetScope satellite observations. We estimated aboveground net primary Production as a product of absorbed photosynthetically active radiation (APAR) derived from NDVI and light use efficiency (LUE), optimized as a function of topography and climate stressors. The estimated Forage Production agreed well with field measurements having a R2 of 0.80 and RMSE of 542 kg/ha. Cumulative NDVI and APAR were less correlated with measured biomass (R2 = 0.68). Daily Forage Production maps captured similar seasonal and spatial patterns compared to field-based biomass measurements. Our study demonstrated the utility of aerial and satellite remote sensing technology in supporting adaptive rangeland management, especially during an era of climatic extremes, by providing spatially explicit and near-real-time Forage Production estimates.

  • Estimating Rangeland Forage Production Using Remote Sensing Data from a Small Unmanned Aerial System (sUAS) and PlanetScope Satellite
    MDPI AG, 2019
    Co-Authors: Han Liu, Randy A. Dahlgren, Royce E. Larsen, Scott M. Devine, Leslie M. Roche, Anthony O’ T. Geen, Andy J.y. Wong, Sarah Covello, Yufang Jin
    Abstract:

    Rangelands cover ~23 million hectares and support a $3.4 billion annual cattle industry in California. Large variations in Forage Production from year to year and across the landscape make grazing management difficult. We here developed optimized methods to map high-resolution Forage Production using multispectral remote sensing imagery. We conducted monthly flights using a Small Unmanned Aerial System (sUAS) in 2017 and 2018 over a 10-ha deferred grazing rangeland. Daily maps of NDVI at 30-cm resolution were first derived by fusing monthly 30-cm sUAS imagery and more frequent 3-m PlanetScope satellite observations. We estimated aboveground net primary Production as a product of absorbed photosynthetically active radiation (APAR) derived from NDVI and light use efficiency (LUE), optimized as a function of topography and climate stressors. The estimated Forage Production agreed well with field measurements having a R2 of 0.80 and RMSE of 542 kg/ha. Cumulative NDVI and APAR were less correlated with measured biomass ( R 2 = 0.68). Daily Forage Production maps captured similar seasonal and spatial patterns compared to field-based biomass measurements. Our study demonstrated the utility of aerial and satellite remote sensing technology in supporting adaptive rangeland management, especially during an era of climatic extremes, by providing spatially explicit and near-real-time Forage Production estimates

  • Estimating rangeland Forage Production using remote sensing data from a Small Unmanned Aerial System (sUAS) and planetscope satellite
    eScholarship University of California, 2019
    Co-Authors: Liu H, Anthony O’ T. Geen, Ra Dahlgren, Re Larsen, Sm Devine, Lm Roche, Wong Ajy, Covello S, Jin Y
    Abstract:

    © 2019 by the authors. Rangelands cover ~23 million hectares and support a $3.4 billion annual cattle industry in California. Large variations in Forage Production from year to year and across the landscape make grazing management difficult. We here developed optimized methods to map high-resolution Forage Production using multispectral remote sensing imagery. We conducted monthly flights using a Small Unmanned Aerial System (sUAS) in 2017 and 2018 over a 10-ha deferred grazing rangeland. Daily maps of NDVI at 30-cm resolution were first derived by fusing monthly 30-cm sUAS imagery and more frequent 3-m PlanetScope satellite observations. We estimated aboveground net primary Production as a product of absorbed photosynthetically active radiation (APAR) derived from NDVI and light use efficiency (LUE), optimized as a function of topography and climate stressors. The estimated Forage Production agreed well with field measurements having a R2 of 0.80 and RMSE of 542 kg/ha. Cumulative NDVI and APAR were less correlated with measured biomass (R2 = 0.68). Daily Forage Production maps captured similar seasonal and spatial patterns compared to field-based biomass measurements. Our study demonstrated the utility of aerial and satellite remote sensing technology in supporting adaptive rangeland management, especially during an era of climatic extremes, by providing spatially explicit and near-real-time Forage Production estimates