Spatiotemporal Analysis of Actual Evapotranspiration and Its Causes in the Hai Basin

Niu, Y.; Tian, Fuyou; Wu, Bingfang; Zhu, Weiwei; Yu, Mingzhou

doi:10.3390/rs10020332

Cited by 13 publications

(11 citation statements)

References 53 publications

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“…It helps to know about climate change, land use, water budget and irrigation. It transfers large volumes of water and energy, in the form of latent heat) from the soil (evaporation) and vegetation (transpiration) into the atmosphere (Yan et al,2018). Traditionally, ET from agricultural fields has been estimated by multiplying the weather-based reference ET by crop coefficients (Kc) determined according to the crop type and the crop growth stage.…”

Section: Introductionmentioning

confidence: 99%

EVAPOTRANSPIRATION ESTIMATION USING SSEBop METHOD WITH SENTINEL -2 AND LANDSAT-8 DATA SET

Sharma

Tare

2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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<p><strong>Abstract.</strong> Estimation of evapotranspiration (ET) parameters is essential for understanding crop water requirements and to find out the ground water recharge. In situ data collection procedures are generally adopted to measure the parameters required to find ET. Latest remote sensing technologies accompanied by newly launched satellite datasets can supplement the field data collection and analysis by finding out some of the parameters such as land surface temperature, normalized difference vegetation index (NDVI), albedo, emissivity, etc. The Upper Ganga Canal Command Area (UGC) lying between two rivers Ganga and Yamuna situated between two states, namely Uttarakhand and Uttar Pradesh in North India is selected as the study area for this research work. Operational Simplified Surface Energy Balance (SSEBop) method is used to derive high resolution (10m) ET map for the Upper Ganga Canal Command Area. Sentinel-2 multi spectral images were used to derive land use, land cover (LU/LC) maps, NDVI, albedo, etc. Downscaled Landsat 8 images were used to derive land surface temperature of the command area. Meteorological data retrieved from the Indian Meteorological Department (IMD) was used to calculate reference evapotranspiration. ET map of the study area was generated using the above estimated parameters. Further, validation of the obtained ET values was accomplished by gridded ET data obtained from IMD.</p>

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Section: Introductionmentioning

confidence: 99%

EVAPOTRANSPIRATION ESTIMATION USING SSEBop METHOD WITH SENTINEL -2 AND LANDSAT-8 DATA SET

Sharma

Tare

2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Annual ET over the entire basin shows an increasing trend as determined using the M-K approach, which has a high correlation with the average NDVI. The relationship between water consumption and vegetation has also been discussed by a peer researcher [42].…”

Section: Discussionmentioning

confidence: 99%

“…The time-series water consumption trend was analysed using a Mann-Kendal (M-K) trend test [39] at the basin scale. The non-parametric rank-based strategy has been widely used to analyse time-series trends in hydrological data by other researchers [40][41][42]. Figure 3a-c.…”

Section: Trend Analysismentioning

confidence: 99%

“…In this research, time-series NDVI maps after Savitzky-Golay filtering covering the entire growing season (April to October) were employed to calculate yearly average area with vegetation cover [43]. Annual precipitation was not investigated because, unlike in other regions, rainfall scarcely affects water consumption in this region [24,42]. According to the results of the M-K test, the ETa from Turpan displays a non-significant increasing trend starting in 2006 with a slope of 0.70.…”

Section: Water Consumption Dynamicsmentioning

confidence: 99%

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Satellite-Based Water Consumption Dynamics Monitoring in an Extremely Arid Area

Tan

Niu

et al. 2018

Remote Sensing

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Evapotranspiration (ET) involves actual water consumption directly from the land surface; however, regional ET maps are usually neglected during water management and allocation. In this study, an integrated satellite-based ET monitoring approach with two spatial resolutions is proposed over an extremely arid basin in China that has experienced crop area expansion and has been the focus of a water-saving project since 2012. The proposed ETWatch approach combined with an empirical downscaling strategy based on vegetation condition was employed to produce monthly ET maps. This method achieves satisfactory accuracy and is validated by its reasonable spatial and temporal pattern results. Yearly results exhibit an increasing ET trend before 2012, which subsequently gradually decrease. This trend fits well with the dynamics of the basin-wide vegetation condition, indicating that there is a stronger correlation between water consumption and vegetation than between other environmental indicators. The average ET over three main crop types in the region (grape, cotton, and melon) decreased by approximately 5% due to optimizations of the irrigation timeline during the project, while 13% of the water savings can be attributed to the fallowing of crop areas. Based on the irrigation distribution in 2012, a comparison between drip and border irrigation that achieves water savings of 3.6% from grape and 5.8% from cotton is conducted. However, an afforestation project that involved planting young trees led to an approximate 25% increase in water consumption. Overall, since 2012, the water-saving project has achieved satisfactory performance regarding excessive groundwater withdrawal, showing a reduction trend of 3 million m3/year and an increase in Lake Aiding water levels since 2011. The results reveal the potential of the ET monitoring strategy as a basis for basin-scale water management.

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“…These RS-based ET products provide regional and global ET results at daily or eight-day intervals with moderate spatial resolutions, usually at 500-m to one-km scales. Such ET data have been adopted for studying regional ecological impacts on water resources [14][15][16], modeling land-surface processes [17], analyzing water cycling, and evaluating regional available water resources [16]. However, the spatial scales of these moderate-resolution ET products are too coarse for agricultural water management, especially within small irrigation districts that usually occupy tens to hundreds of square meters, and detailed spatial information is omitted from km-level ET data.…”

Section: Introductionmentioning

confidence: 99%

Spatial Allocation Method from Coarse Evapotranspiration Data to Agricultural Fields by Quantifying Variations in Crop Cover and Soil Moisture

Niu

et al. 2021

Remote Sensing

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Cropland evapotranspiration (ET) is the major source of water consumption in agricultural systems. The precise management of agricultural ET helps optimize water resource usage in arid and semiarid regions and requires field-scale ET data support. Due to the combined limitations of satellite sensors and ET mechanisms, the current high-resolution ET models need further refinement to meet the demands of field-scale ET management. In this research, we proposed a new field-scale ET estimation method by developing an allocation factor to quantify field-level ET variations and allocate coarse ET to the field scale. By regarding the agricultural field as the object of the ET parcel, the allocation factor is calculated with combined high-resolution remote sensing indexes indicating the field-level ET variations under different crop growth and land-surface water conditions. The allocation ET results are validated at two ground observation stations and show improved accuracy compared with that of the original coarse data. This allocated ET model provides reasonable spatial results of field-level ET and is adequate for precise agricultural ET management. This allocation method provides new insight into calculating field-level ET from coarse ET datasets and meets the demands of wide application for controlling regional water consumption, supporting the ET management theory in addressing the impacts of water scarcity on social and economic developments.

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Spatiotemporal Analysis of Actual Evapotranspiration and Its Causes in the Hai Basin

Cited by 13 publications

References 53 publications

EVAPOTRANSPIRATION ESTIMATION USING SSEBop METHOD WITH SENTINEL -2 AND LANDSAT-8 DATA SET

EVAPOTRANSPIRATION ESTIMATION USING SSEBop METHOD WITH SENTINEL -2 AND LANDSAT-8 DATA SET

Satellite-Based Water Consumption Dynamics Monitoring in an Extremely Arid Area

Spatial Allocation Method from Coarse Evapotranspiration Data to Agricultural Fields by Quantifying Variations in Crop Cover and Soil Moisture

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