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Increased model complexity and data quantities have raised the computing power requirement for efficient evapotranspiration (ET) estimation. A cloud-based service is presented to encapsulate and publish the ETWatch modeling algorithms as web application programming interfaces (APIs) in a consistent style to provide extensible model calculation service and data storage service in a cloud platform for water managers and stakeholders. The prototype system, named ETWatch Cloud allows users to rapidly and easily set up an ET generation project for any region of interest by invoking APIs directly to produce ET data using a web browser or local integrated development environment. The case study demonstrates that ETWatch Cloud can provide a highly scalable and interoperable ET generation tool for stakeholders from ET community, helping to facilitate the application of remote sensing-based ET algorithms for water management in hydrology sector.
Fangming Wu; Bingfang Wu; Weiwei Zhu; Nana Yan; Zonghan Ma; Linjiang Wang; Yuming Lu; Jiaming Xu. ETWatch cloud: APIs for regional actual evapotranspiration data generation. Environmental Modelling & Software 2021, 145, 105174 .
AMA StyleFangming Wu, Bingfang Wu, Weiwei Zhu, Nana Yan, Zonghan Ma, Linjiang Wang, Yuming Lu, Jiaming Xu. ETWatch cloud: APIs for regional actual evapotranspiration data generation. Environmental Modelling & Software. 2021; 145 ():105174.
Chicago/Turabian StyleFangming Wu; Bingfang Wu; Weiwei Zhu; Nana Yan; Zonghan Ma; Linjiang Wang; Yuming Lu; Jiaming Xu. 2021. "ETWatch cloud: APIs for regional actual evapotranspiration data generation." Environmental Modelling & Software 145, no. : 105174.
Global climate change and human activities have resulted in immense changes in the Earth’s ecosystem, and the interaction between the land surface and the atmosphere is one of the most important processes. Wind is a reference for studying atmospheric dynamics and climate change, analyzing the wind speed change characteristics in historical periods, and studying the influence of wind on the Earth-atmosphere interaction; additionally, studying the wind, contributes to analyzing and alleviating a series of problems, such as the energy crisis, environmental pollution, and ecological deterioration facing human beings. In this study, data from 697 meteorological stations in China from 2000 to 2019 were used to study the distribution and trend of wind speed over the past two decades. The relationships between wind speed and climate factors were explored using statistical methods; furthermore, combined with terrain, climate change, and human activities, we quantified the contribution of environmental factors to wind speed. The results show that a downward trend was recorded before 2011, but overall, there was an increasing trend that was not significant; moreover, the wind speed changes showed obvious seasonality and were more complicated on the monthly scale. The wind speed trend mainly increased in the western region, decreased in the eastern region, was higher in the northeastern, northwestern, and coastal areas, and was lower in the central area. Temperature, bright sunshine duration, evaporation, and precipitation had a strong influence, in which wind speed showed a significant negative correlation with temperature and precipitation and vice versa for sunshine and evapotranspiration. The influence of environmental factors is diverse, and these results could help to develop environmental management strategies across ecologically fragile areas and improve the design of wind power plants to make better use of wind energy.
Yuming Lu; Bingfang Wu; Nana Yan; Weiwei Zhu; Hongwei Zeng; Zonghan Ma; Jiaming Xu; Xinghua Wu; Bo Pang. Quantifying the Contributions of Environmental Factors to Wind Characteristics over 2000–2019 in China. ISPRS International Journal of Geo-Information 2021, 10, 515 .
AMA StyleYuming Lu, Bingfang Wu, Nana Yan, Weiwei Zhu, Hongwei Zeng, Zonghan Ma, Jiaming Xu, Xinghua Wu, Bo Pang. Quantifying the Contributions of Environmental Factors to Wind Characteristics over 2000–2019 in China. ISPRS International Journal of Geo-Information. 2021; 10 (8):515.
Chicago/Turabian StyleYuming Lu; Bingfang Wu; Nana Yan; Weiwei Zhu; Hongwei Zeng; Zonghan Ma; Jiaming Xu; Xinghua Wu; Bo Pang. 2021. "Quantifying the Contributions of Environmental Factors to Wind Characteristics over 2000–2019 in China." ISPRS International Journal of Geo-Information 10, no. 8: 515.
Crop evapotranspiration (ET) is an essential part of agricultural water consumption, and robust monitoring of remote sensing (RS)-based ET at the field scale improves agricultural water management against water shortages. In this study, we propose a high-resolution optical RS-driven daily ET estimation framework coupling water vaporization and carbon assimilation based on Sentinel-2 satellite data. To determine if the proposed framework is accurate compared with flux observations, three tower sites are chosen (Guantao and Huailai from the Haihe Basin; Daman from the Heihe Basin), with a total of four years of observations adopted for model validation. The correlation coefficient R ranges from 0.870 to 0.912, and the RMSE ranges from 0.89 to 1.21 mm/day. Sensitivity analyses indicate that ET is most sensitive to air temperature, followed by ambient CO2 concentration and absorbed shortwave radiation, which provides indications into potential future farming strategies to confront global climate change. Finally, we discuss the scale effects on the proposed model at the field scale. Results from three sites show that for a larger area of interest (AOI) the impact of scales increases. This research provides insights into ET calculations across several spatial scales and application potential in precision agricultural water management.
Zonghan Ma; Bingfang Wu; Nana Yan; Weiwei Zhu; Jiaming Xu. Coupling water and carbon processes to estimate field-scale maize evapotranspiration with Sentinel-2 data. Agricultural and Forest Meteorology 2021, 306, 108421 .
AMA StyleZonghan Ma, Bingfang Wu, Nana Yan, Weiwei Zhu, Jiaming Xu. Coupling water and carbon processes to estimate field-scale maize evapotranspiration with Sentinel-2 data. Agricultural and Forest Meteorology. 2021; 306 ():108421.
Chicago/Turabian StyleZonghan Ma; Bingfang Wu; Nana Yan; Weiwei Zhu; Jiaming Xu. 2021. "Coupling water and carbon processes to estimate field-scale maize evapotranspiration with Sentinel-2 data." Agricultural and Forest Meteorology 306, no. : 108421.
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.
Zonghan Ma; Bingfang Wu; Nana Yan; Weiwei Zhu; Hongwei Zeng; Jiaming Xu. Spatial Allocation Method from Coarse Evapotranspiration Data to Agricultural Fields by Quantifying Variations in Crop Cover and Soil Moisture. Remote Sensing 2021, 13, 343 .
AMA StyleZonghan Ma, Bingfang Wu, Nana Yan, Weiwei Zhu, Hongwei Zeng, Jiaming Xu. Spatial Allocation Method from Coarse Evapotranspiration Data to Agricultural Fields by Quantifying Variations in Crop Cover and Soil Moisture. Remote Sensing. 2021; 13 (3):343.
Chicago/Turabian StyleZonghan Ma; Bingfang Wu; Nana Yan; Weiwei Zhu; Hongwei Zeng; Jiaming Xu. 2021. "Spatial Allocation Method from Coarse Evapotranspiration Data to Agricultural Fields by Quantifying Variations in Crop Cover and Soil Moisture." Remote Sensing 13, no. 3: 343.
Droughts can cause tremendous losses to agricultural and economic development; humans have explored many anti-drought measures to mitigate the influence of drought and accordingly altering the characteristics of actual agricultural drought. In this study, a method is proposed to detect the spatiotemporal changes in drought characteristics, which show the effects of anti-drought measures on drought mitigation. Two agricultural drought mitigation evaluation indices are proposed, the agricultural drought frequency change (ADFC) and agricultural drought area change (ADAC), which are calculated by combining the Palmer drought severity index (PDSI) and vegetation health index (VHI), two widely used drought monitoring indices. The PDSI and VHI represent the natural and actual agricultural drought severity under natural and actual conditions respectively, and their differences in drought frequency and affected area reflect the level of anti-drought measures in mitigating agricultural drought. The feasibility of using ADFC and ADAC to quantify the effects of anti-drought measures for agriculture is explored using data from six typical agricultural provinces in the North China Plain and Northeast China. The results show that ADFC and ADAC could reflect both the spatiotemporal changes in agricultural drought characteristics and the influence of anti-drought measures on agricultural drought. The trend of the drought mitigation index is consistent with agricultural activity statistics. These two indices could be further used to evaluate the effects of different anti-drought methods and aid in defeating agricultural drought across many countries.
Bingfang Wu; Zonghan Ma; Nana Yan. Agricultural drought mitigating indices derived from the changes in drought characteristics. Remote Sensing of Environment 2020, 244, 111813 .
AMA StyleBingfang Wu, Zonghan Ma, Nana Yan. Agricultural drought mitigating indices derived from the changes in drought characteristics. Remote Sensing of Environment. 2020; 244 ():111813.
Chicago/Turabian StyleBingfang Wu; Zonghan Ma; Nana Yan. 2020. "Agricultural drought mitigating indices derived from the changes in drought characteristics." Remote Sensing of Environment 244, no. : 111813.
Water use efficiency (WUE) is defined as the ratio between gross primary production (GPP) and evapotranspiration (ET) at ecosystem scale, which can help understand the mechanism between water consumption and crop production in guiding field water management. Water consumption control is important in precision agriculture development. Mapping WUE at field scale using remote sensing data could provide crop water use status at high resolution and acquire the WUE spatial distribution. In this study we proposed a method to estimate field-scale maize WUE with Sentienl-2 data. The GPP of maize is estimated by a light use efficiency model with RS observed albedo, sunshine radiation, fraction of photosynthetically active radiation (fpar) fitted using in site observation. Maize ET is modelled using FAO-PM model with crop coefficient simulated using vegetation indexes acquired from Sentinel-2 bands. We compared the GPP, ET and final WUE estimation with eddy covariance (EC) observations in a maize field of North China Plain where water scarcity is a main limit factor of crop development. Comparation results show a high correlation between in site observation and modelled results. Combining the phenology development of maize, the temporal characteristics of maize WUE change is associated with phenology. WUE was low after sowing, then increased during Elongation stage. Maize WUE peaked at Heading and Grouting period and decreased in Maturation stage. Our WUE estimation method with high resolution could guide adopting various irrigation strategies based on different WUE conditions at field scale. This research could help shed light on the future WUE development under climate change background and improve our knowledge of precise water management.
Zonghan Ma; Bingfang Wu; Nana Yan; Weiwei Zhu. Capability of maize water use efficiency estimation at field scale using Sentinel-2 data. 2020, 1 .
AMA StyleZonghan Ma, Bingfang Wu, Nana Yan, Weiwei Zhu. Capability of maize water use efficiency estimation at field scale using Sentinel-2 data. . 2020; ():1.
Chicago/Turabian StyleZonghan Ma; Bingfang Wu; Nana Yan; Weiwei Zhu. 2020. "Capability of maize water use efficiency estimation at field scale using Sentinel-2 data." , no. : 1.
Evapotranspiration (ET) is one of the components in the water cycle and the surface energy balance systems. It is fundamental information for agriculture, water resource management, and climate change research. This study presents a scheme for regional actual evapotranspiration estimation using multi-source satellite data to compute key land and meteorological variables characterizing land surface, soil, vegetation, and the atmospheric boundary layer. The algorithms are validated using ground observations from the Heihe River Basin of northwest China. Monthly data estimates at a resolution of 1 km from the proposed algorithms compared well with ground observation data, with a root mean square error (RMSE) of 0.80 mm and a mean relative error (MRE) of −7.11%. The overall deviation between the average yearly ET derived from the proposed algorithms and ground-based water balance measurements was 9.44% for a small watershed and 1% for the entire basin. This study demonstrates that both accuracy and spatial depiction of actual evapotranspiration estimation can be significantly improved by using multi-source satellite data to measure the required land surface and meteorological variables. This reduces dependence on spatial interpolation of ground-derived meteorological variables which can be problematic, especially in data-sparse regions, and allows the production of region-wide ET datasets.
Bingfang Wu; Weiwei Zhu; Nana Yan; Qiang Xing; Jiaming Xu; Zonghan Ma; Linjiang Wang. Regional Actual Evapotranspiration Estimation with Land and Meteorological Variables Derived from Multi-Source Satellite Data. Remote Sensing 2020, 12, 332 .
AMA StyleBingfang Wu, Weiwei Zhu, Nana Yan, Qiang Xing, Jiaming Xu, Zonghan Ma, Linjiang Wang. Regional Actual Evapotranspiration Estimation with Land and Meteorological Variables Derived from Multi-Source Satellite Data. Remote Sensing. 2020; 12 (2):332.
Chicago/Turabian StyleBingfang Wu; Weiwei Zhu; Nana Yan; Qiang Xing; Jiaming Xu; Zonghan Ma; Linjiang Wang. 2020. "Regional Actual Evapotranspiration Estimation with Land and Meteorological Variables Derived from Multi-Source Satellite Data." Remote Sensing 12, no. 2: 332.
Sunshine duration is an important indicator of the amount of solar radiation received in a region and an important input parameter for the study of atmospheric energy balance, climate change, ecosystem evolution, and social sustainability. Currently, extrapolation and interpolation of data from meteorological stations are the most common methods used to calculate sunshine duration on a regional scale. However, it is difficult to obtain high precision sunshine duration in areas lacking ground observation or where sunshine duration is highly heterogeneous on the ground. In this paper, a new method is proposed to estimate sunshine duration with hourly total cloud amount (CTA) data from sunrise to sunset derived from the Fengyun-2G geostationary meteorological satellite (FY-2G). This method constructs a new index known as daytime mean total cloud coverage amount and provides quadratic equations relating daytime mean total cloud coverage amount to relative sunshine duration in different seasons. The method was validated with ground observation data for 2016 from 18 meteorological stations in the Three-River Headwaters Region of Qinghai Province, China. For individual stations, the coefficient of determination (R2) between estimated and measured sunshine was at least 0.894, the RMSE (root mean square error) was 0.977 h/day or less, the MAE (mean absolute error) was 0.824 h/day or less, the RE (relative error) was 0.150 or lower, and the value of d was 0.963 or greater, which validated that the proposed method can effectively predict daily sunshine duration. These equations can also provide higher precision estimates of regional-scale sunshine duration. This was demonstrated by comparing, for the entire study region, the spatial distribution of sunshine duration estimated from season-based equations with results from three different interpolation methods based on ground observations. Overall, the study confirms that total cloud amount measures from a geostationary satellite can be used to successfully estimate sunshine duration.
Weiwei Zhu; Bingfang Wu; Nana Yan; Zonghan Ma; Linjiang Wang; Wenjun Liu; Qiang Xing; Jiaming Xu. Estimating Sunshine Duration Using Hourly Total Cloud Amount Data from a Geostationary Meteorological Satellite. Atmosphere 2019, 11, 26 .
AMA StyleWeiwei Zhu, Bingfang Wu, Nana Yan, Zonghan Ma, Linjiang Wang, Wenjun Liu, Qiang Xing, Jiaming Xu. Estimating Sunshine Duration Using Hourly Total Cloud Amount Data from a Geostationary Meteorological Satellite. Atmosphere. 2019; 11 (1):26.
Chicago/Turabian StyleWeiwei Zhu; Bingfang Wu; Nana Yan; Zonghan Ma; Linjiang Wang; Wenjun Liu; Qiang Xing; Jiaming Xu. 2019. "Estimating Sunshine Duration Using Hourly Total Cloud Amount Data from a Geostationary Meteorological Satellite." Atmosphere 11, no. 1: 26.
The spatial distribution of water resources largely influences Earth ecosystems and human civilization. Being a major component of the global water cycle, evapotranspiration (ET) serves as an indicator of the availability of water resources. Understanding the actual ET (ETa) variation mechanism at different spatial and temporal scales can improve management of water use within the sustainable development limits. In this study, remote sensing derived ETa data were used to study water resource fluctuations in the Loess Plateau, China. This region covers diverse climate types from humid to arid and experienced large changes in vegetation cover during a revegetation project between 2000 and 2015. The relations between spatiotemporal variation of ETa, climate factors and vegetation change were explored using statistical methods. The results show that cropland, forestland and grassland take the largest percentage of total ETa. Total ETa exhibited a marginally increasing trend (p < 0.1) during 2000–2010 and no trend during 2011–2015. Windspeed and vegetation cover index highly influenced ETa, followed by atmospheric pressure, air humidity, precipitation, bright sunshine duration and temperature. Temperature has little effect on ETa throughout the Loess Plateau. The monitoring of water resources based upon water balance between precipitation, ETa and river flow changes shows that water consumption deficit is consistent with vegetation changes: it was large during 2000–2010 when vegetation increased rapidly and decreased after 2010. These results could help to develop different water saving strategies across the Loess Plateau and build a better monitoring system of water resources.
Zonghan Ma; Nana Yan; Bingfang Wu; Alfred Stein; Weiwei Zhu; Hongwei Zeng. Variation in actual evapotranspiration following changes in climate and vegetation cover during an ecological restoration period (2000–2015) in the Loess Plateau, China. Science of The Total Environment 2019, 689, 534 -545.
AMA StyleZonghan Ma, Nana Yan, Bingfang Wu, Alfred Stein, Weiwei Zhu, Hongwei Zeng. Variation in actual evapotranspiration following changes in climate and vegetation cover during an ecological restoration period (2000–2015) in the Loess Plateau, China. Science of The Total Environment. 2019; 689 ():534-545.
Chicago/Turabian StyleZonghan Ma; Nana Yan; Bingfang Wu; Alfred Stein; Weiwei Zhu; Hongwei Zeng. 2019. "Variation in actual evapotranspiration following changes in climate and vegetation cover during an ecological restoration period (2000–2015) in the Loess Plateau, China." Science of The Total Environment 689, no. : 534-545.