Evaluation of Crop Water Status and Vegetation Dynamics For Alternate Partial Root-Zone Drip Irrigation of Alfalfa: Observation With an UAV Thermal Infrared Imagery

Characterization of the spatiotemporal patterns of crop water status and vegetation dynamics are a prerequisite to overcome water scarcity and obtain precise agricultural water management. Based on high-resolution aerial thermal imagery, we estimated crop water stress index (CWSI), transpiration rate (T), and crop growth status. The research was conducted with conventional subsurface drip irrigation (abbreviated as R) and alternate partial root-zone drip irrigation (abbreviated as P) under four different irrigation quotas: 0 mm, 10 mm, 20 mm, and 30 mm, which are denoted as CK, R10 (P10), R20 (P20), and R30 (P30), respectively. Results indicate that the CWSI is a suitable tool to define alfalfa water status under different irrigation regimes. The CWSI values reflect CK > R10 > R20 > P10 > P20 > R30 > P30, with values of 0.57, 0.41, 0.26, 0.24, 0.18, 0.17, and 0.13, respectively. The T values show that CK < R10 < P10 < R20 < P20 < R30 < P30, with values of 0.46 mm/h, 0.61 mm/h, 0.70 mm/h, 0.71 mm/h, 0.76 mm/h, 0.77 mm/h, and 0.78 mm/h, respectively. In addition, under the same irrigation quotas, the CWSI presented as P10, P20, and P30 was lower than R10, R20, and R30, respectively, while the T was the opposite. Taking the improved transpiration rate as the amount of water saving, it was demonstrated that the alternate partial root-zone drip irrigation was a water-saving method, and each increase of 10 mm in alternating irrigation quotas could save 67.2, 18.4, and 4.6% of water, respectively. This evaluation contributes to a better understanding of the spatiotemporal variations of water and growth status and provides references and theories for the development of modern precise agriculture.

[1]  A. Lin,et al.  Estimation of crop transpiration and its scale effect based on ground and UAV thermal infrared remote sensing images , 2021, European Journal of Agronomy.

[2]  S. Ortega-Farías,et al.  Evaluation of a two-source patch model to estimate vineyard energy balance using high-resolution thermal images acquired by an unmanned aerial vehicle (UAV) , 2021, Agricultural and Forest Meteorology.

[3]  M. Andersen,et al.  Did water-saving irrigation protect water resources over the past 40 years? A global analysis based on water accounting framework , 2021 .

[4]  Minghui Cheng,et al.  A global meta-analysis of yield and water use efficiency of crops, vegetables and fruits under full, deficit and alternate partial root-zone irrigation , 2021 .

[5]  Jianquan Liu,et al.  A chromosome-scale genome assembly of a diploid alfalfa, the progenitor of autotetraploid alfalfa , 2020, Horticulture research.

[6]  P. Zhu,et al.  Regulation of soil water threshold on tomato plant growth and fruit quality under alternate partial root-zone drip irrigation , 2020 .

[7]  Florian Ellsäßer,et al.  Airborne Tree Crown Detection for Predicting Spatial Heterogeneity of Canopy Transpiration in a Tropical Rainforest , 2020, Remote. Sens..

[8]  Thomas Udelhoven,et al.  Challenges and Future Perspectives of Multi-/Hyperspectral Thermal Infrared Remote Sensing for Crop Water-Stress Detection: A Review , 2019, Remote. Sens..

[9]  P. Zarco-Tejada,et al.  Transpiration from canopy temperature: Implications for the assessment of crop yield in almond orchards , 2019, European Journal of Agronomy.

[10]  Jiang Bian,et al.  Simplified Evaluation of Cotton Water Stress Using High Resolution Unmanned Aerial Vehicle Thermal Imagery , 2019, Remote. Sens..

[11]  Ricardo Díaz-Delgado,et al.  Enhancement of Ecological Field Experimental Research by Means of UAV Multispectral Sensing , 2019, Drones.

[12]  A. Yazar,et al.  Evaluation of crop water stress index and leaf water potential for deficit irrigation management of sprinkler-irrigated wheat , 2018, Irrigation Science.

[13]  Iván Francisco García-Tejero,et al.  Thermal imaging at plant level to assess the crop-water status in almond trees (cv. Guara) under deficit irrigation strategies , 2018, Agricultural Water Management.

[14]  N. Ouazzani,et al.  Soil properties and agro-physiological responses of alfalfa (Medicago sativa L.) irrigated by treated domestic wastewater , 2018 .

[15]  María Romero,et al.  Vineyard water status estimation using multispectral imagery from an UAV platform and machine learning algorithms for irrigation scheduling management , 2018, Comput. Electron. Agric..

[16]  F. Armah,et al.  Meta-analysis of crop yields of full, deficit, and partial root-zone drying irrigation , 2018 .

[17]  Elías Fereres,et al.  Yield response of almond trees to transpiration deficits , 2018, Irrigation Science.

[18]  X. Wen,et al.  Spatiotemporal variability of temperature and precipitation in Gansu Province (Northwest China) during 1951-2015 , 2017 .

[19]  Hoam Chung,et al.  Adaptive Estimation of Crop Water Stress in Nectarine and Peach Orchards Using High-Resolution Imagery from an Unmanned Aerial Vehicle (UAV) , 2017, Remote. Sens..

[20]  L. G. Santesteban,et al.  High-resolution UAV-based thermal imaging to estimate the instantaneous and seasonal variability of plant water status within a vineyard , 2017 .

[21]  Xuhui Lee,et al.  Evapotranspiration partitioning through in-situ oxygen isotope measurements in an oasis cropland , 2016 .

[22]  D. Gong,et al.  Effects of water stress on photosynthetic characteristics, dry matter translocation and WUE in two winter wheat genotypes , 2016 .

[23]  Ajay Sharda,et al.  Development and evaluation of thermal infrared imaging system for high spatial and temporal resolution crop water stress monitoring of corn within a greenhouse , 2016, Comput. Electron. Agric..

[24]  Guo Yu Qiu,et al.  An evapotranspiration product for arid regions based on the three-temperature model and thermal remote sensing , 2015 .

[25]  Ling Tong,et al.  Ecosystem water use efficiency for a sparse vineyard in arid northwest China , 2015 .

[26]  Pablo J. Zarco-Tejada,et al.  Applicability and limitations of using the crop water stress index as an indicator of water deficits in citrus orchards , 2014 .

[27]  Yujiu Xiong,et al.  Use of high-resolution thermal infrared remote sensing and "three-temperature model" for transpiration monitoring in arid inland river catchment , 2014 .

[28]  Li Bo,et al.  Crop water stress index for off-season greenhouse green peppers in Liaoning, China , 2014 .

[29]  Q. Lier,et al.  Canopy temperature versus soil water pressure head for the prediction of crop water stress , 2013 .

[30]  C. Ghoulam,et al.  Assessment of summer drought tolerance variability in Mediterranean alfalfa (Medicago sativa L.) cultivars under Moroccan fields conditions , 2013 .

[31]  Wei Guo,et al.  Research on early Fault Prediction of Wind Turbine Gearbox , 2012 .

[32]  Paul D. Colaizzi,et al.  A crop water stress index and time threshold for automatic irrigation scheduling of grain sorghum , 2012 .

[33]  Shaohua Zhao,et al.  Remote detection of bare soil moisture using a surface-temperature-based soil evaporation transfer coefficient , 2010, Int. J. Appl. Earth Obs. Geoinformation.

[34]  Y. Cohen,et al.  Crop water stress mapping for site-specific irrigation by thermal imagery and artificial reference surfaces , 2010, Precision Agriculture.

[35]  Z. Qiang,et al.  Research Progress of the Impact of Global Climate Warming on Crops in Gansu Province , 2008 .

[36]  Changming Liu,et al.  [A review on research of land surface water and heat fluxes]. , 2003, Ying yong sheng tai xue bao = The journal of applied ecology.

[37]  Manfred Stoll,et al.  Use of infrared thermography for monitoring stomatal closure in the field: application to grapevine. , 2002, Journal of experimental botany.

[38]  Hamlyn G. Jones,et al.  Use of infrared thermometry for estimation of stomatal conductance as a possible aid to irrigation scheduling , 1999 .

[39]  G. Qiu,et al.  Experimental verification of a mechanistic model to partition evapotranspiration into soil water and plant evaporation , 1999 .

[40]  Guo Yu Qiu,et al.  An improved methodology to measure evaporation from bare soil based on comparison of surface temperature with a dry soil surface , 1998 .

[41]  William P. Kustas,et al.  A reexamination of the crop water stress index , 1988, Irrigation Science.

[42]  Sherwood B. Idso,et al.  Non-water-stressed baselines: A key to measuring and interpreting plant water stress , 1982 .

[43]  Yang Shihong,et al.  Diagnosing crop water stress of rice using infrared thermal imager under water deficit condition. , 2016 .

[44]  Cheng Zi-yong Impact of Water Stress on Leaf Water Potential,Transpiration Rate(T_r) and Stomatal Conductance (G_s) of Alfalfa , 2011 .

[45]  A. Sepaskhah,et al.  Relationships between yield, crop water stress index (CWSI) and transpiration of cowpea (Vigna sinensis L) , 1996 .

[46]  C. B. Tanner Plant Temperatures 1 , 1963 .