High-resolution mapping of evapotranspiration over heterogeneous cropland affected by soil salinity
Evapotranspiration (ET) plays a crucial role in the terrestrial water cycle, particularly in arid areas such as those of the Hetao Irrigation District (HID) in Inner Mongolia, China, where water scarcity and salinity variability pose significant challenges for irrigated agriculture and ecological mo...
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| Language: | English |
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Elsevier
2025-03-01
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| Series: | Agricultural Water Management |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0378377425000150 |
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| author | Meihan Liu Huimin Lei Xingwang Wang Paula Paredes |
| author_facet | Meihan Liu Huimin Lei Xingwang Wang Paula Paredes |
| author_sort | Meihan Liu |
| collection | DOAJ |
| description | Evapotranspiration (ET) plays a crucial role in the terrestrial water cycle, particularly in arid areas such as those of the Hetao Irrigation District (HID) in Inner Mongolia, China, where water scarcity and salinity variability pose significant challenges for irrigated agriculture and ecological monitoring. Although advances in remote sensing have enhanced ET estimates, high spatial (30 m) and temporal resolution (daily) datasets, which are critical for detailed monitoring remain scarce. This study fills this gap by focusing on the ET variations influenced by salinity, with the aim of assessing the water consumption of saline cropland more accurately. Extensive datasets, including meteorological parameters, normalized difference vegetation index (NDVI), land surface temperature (LST), reflectance and salinity measurements were extracted across the region in 2017. Using a spatiotemporal image fusion algorithm implemented on the Google Earth Engine (GEE) platform, daily NDVI and LST datasets with a 30 m resolution were generated by fusing Landsat 8 and MODIS satellite data. Subsequently, the high-resolution datasets were fed into the revised Priestley Taylor Jet Propulsion Laboratory (PT-JPL) model, which incorporates salinity effects, to generate the final ET estimates. The extended NDVI and LST datasets showed high spatiotemporal accuracy (NDVI: r ≥ 0.78, RMSE=0.029–0.083; LST: r ≥ 0.99, RMSE=0.47∼1.82°C), and effectively captured significant ET changes influenced by salinity variations. Compared to the remote sensing products including PML_V2 and ETMonitor (both with resolutions below 1 km), the modeling results in this study provided greater detail in highly heterogeneous cropland. It was found that crop ET during the growing season accounted for nearly 88 % of the annual ET in HID. Among the components of crop ET, canopy transpiration contributed 75.4 %, soil evaporation 16.5 %, and canopy interception 8.1 %. By comparing PT-JPL model simulations without considering salt stress, the contribution of salt stress to the inhibition of crop ET reached 10 %. These findings enable more accurate ET modeling and prediction in arid regions and provide valuable insights for water resource management, particularly irrigation scheduling, in areas affected by salt-induced stress. By incorporating salinity factor, this research lays the groundwork for more efficient water use and land management strategies in arid and heterogeneous landscapes. |
| format | Article |
| id | doaj-art-66019b7433a14c3fa63a9a2013612be8 |
| institution | Kabale University |
| issn | 1873-2283 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Agricultural Water Management |
| spelling | doaj-art-66019b7433a14c3fa63a9a2013612be82025-01-25T04:10:53ZengElsevierAgricultural Water Management1873-22832025-03-01308109301High-resolution mapping of evapotranspiration over heterogeneous cropland affected by soil salinityMeihan Liu0Huimin Lei1Xingwang Wang2Paula Paredes3State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, ChinaState Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China; Corresponding author.State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, ChinaLEAF – Landscape, Environment, Agricultural and Food, Institute of Agronomy, University of Lisbon, Tapada da Ajuda, Lisbon 1349-017, PortugalEvapotranspiration (ET) plays a crucial role in the terrestrial water cycle, particularly in arid areas such as those of the Hetao Irrigation District (HID) in Inner Mongolia, China, where water scarcity and salinity variability pose significant challenges for irrigated agriculture and ecological monitoring. Although advances in remote sensing have enhanced ET estimates, high spatial (30 m) and temporal resolution (daily) datasets, which are critical for detailed monitoring remain scarce. This study fills this gap by focusing on the ET variations influenced by salinity, with the aim of assessing the water consumption of saline cropland more accurately. Extensive datasets, including meteorological parameters, normalized difference vegetation index (NDVI), land surface temperature (LST), reflectance and salinity measurements were extracted across the region in 2017. Using a spatiotemporal image fusion algorithm implemented on the Google Earth Engine (GEE) platform, daily NDVI and LST datasets with a 30 m resolution were generated by fusing Landsat 8 and MODIS satellite data. Subsequently, the high-resolution datasets were fed into the revised Priestley Taylor Jet Propulsion Laboratory (PT-JPL) model, which incorporates salinity effects, to generate the final ET estimates. The extended NDVI and LST datasets showed high spatiotemporal accuracy (NDVI: r ≥ 0.78, RMSE=0.029–0.083; LST: r ≥ 0.99, RMSE=0.47∼1.82°C), and effectively captured significant ET changes influenced by salinity variations. Compared to the remote sensing products including PML_V2 and ETMonitor (both with resolutions below 1 km), the modeling results in this study provided greater detail in highly heterogeneous cropland. It was found that crop ET during the growing season accounted for nearly 88 % of the annual ET in HID. Among the components of crop ET, canopy transpiration contributed 75.4 %, soil evaporation 16.5 %, and canopy interception 8.1 %. By comparing PT-JPL model simulations without considering salt stress, the contribution of salt stress to the inhibition of crop ET reached 10 %. These findings enable more accurate ET modeling and prediction in arid regions and provide valuable insights for water resource management, particularly irrigation scheduling, in areas affected by salt-induced stress. By incorporating salinity factor, this research lays the groundwork for more efficient water use and land management strategies in arid and heterogeneous landscapes.http://www.sciencedirect.com/science/article/pii/S0378377425000150Crop water useRemote sensingSalinity impactsSoil variabilityComposite cropping systems |
| spellingShingle | Meihan Liu Huimin Lei Xingwang Wang Paula Paredes High-resolution mapping of evapotranspiration over heterogeneous cropland affected by soil salinity Agricultural Water Management Crop water use Remote sensing Salinity impacts Soil variability Composite cropping systems |
| title | High-resolution mapping of evapotranspiration over heterogeneous cropland affected by soil salinity |
| title_full | High-resolution mapping of evapotranspiration over heterogeneous cropland affected by soil salinity |
| title_fullStr | High-resolution mapping of evapotranspiration over heterogeneous cropland affected by soil salinity |
| title_full_unstemmed | High-resolution mapping of evapotranspiration over heterogeneous cropland affected by soil salinity |
| title_short | High-resolution mapping of evapotranspiration over heterogeneous cropland affected by soil salinity |
| title_sort | high resolution mapping of evapotranspiration over heterogeneous cropland affected by soil salinity |
| topic | Crop water use Remote sensing Salinity impacts Soil variability Composite cropping systems |
| url | http://www.sciencedirect.com/science/article/pii/S0378377425000150 |
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