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A reliable accuracy is essential for the application of land surface temperature (LST) products. Current satellite retrieved LSTs are mainly validated over a few homogeneous sites. However, most of the existing ground sites are located in inhomogeneous areas: thus, their spatial representativeness on satellite pixel scales is unknown. In this situation, how to evaluate the spatial representativeness of these inhomogeneous sites, quantify the influence introduced by the spatial representativeness and describe the variation of the site's spatial representativeness are critical questions for satellite LST validation. In an attempt to answer those questions, a so-called temporal variation method (TVM) is proposed for evaluating a ground site's spatial representativeness. The method defines a spatial representativeness indicator (SRI), which is the LST difference between a ground radiometer's field-of-view (FOV) and a satellite pixel, and describes a site's spatial representativeness. Based on the temporal variation of LST, the SRI time series consists of three temporal components: ∆ATC, ∆DTCF-P, and ∆USC, which describe the annual, diurnal, and instantaneous variations of SRI, respectively. Associated with the Landsat TM/ETM+ data and weather parameters, the method is implemented and tested at 16 Chinese ground sites for the validation of MODIS and AATSR LST products. Results show that the temporally continuous SRI (SRITPR) shows high correlations with the original SRI (SRIORI). The variation of SRITPR is mainly determined by changes in surface coverage (i.e. NDVI difference on the two scales) and affected by weather conditions (e.g. near-surface air temperature, accumulative downward solar radiation, and wind speed). Since the SRI is defined as the LST difference between the two scales, it can be used as a bridge to convert the in-situ LST to pixel scale to address the spatial scale mismatch in LST validation. With this idea, the in-situ LST at daytime was converted to pixel scale associated with the SRITPR, and the corresponding MODIS and AATSR LST were validated at the 16 ground sites. Results for MODIS and AATSR LST show that the effect of spatial representativeness on the validation results over the sites is large, with mean biases between −1.95 K and 5.60 K and standard deviations between 0.07 K and 3.72 K. Since the TVM method does not rely on a specific satellite or land surface product, it is readily applied to other LST products (e.g. Sentinel-3 SLSTR LST, NOAA VIIRS LST) and surface parameters (e.g. surface longwave radiation).
Jin Ma; Ji Zhou; Shaomin Liu; Frank-Michael Göttsche; Xiaodong Zhang; Shaofei Wang; Mingsong Li. Continuous evaluation of the spatial representativeness of land surface temperature validation sites. Remote Sensing of Environment 2021, 265, 112669 .
AMA StyleJin Ma, Ji Zhou, Shaomin Liu, Frank-Michael Göttsche, Xiaodong Zhang, Shaofei Wang, Mingsong Li. Continuous evaluation of the spatial representativeness of land surface temperature validation sites. Remote Sensing of Environment. 2021; 265 ():112669.
Chicago/Turabian StyleJin Ma; Ji Zhou; Shaomin Liu; Frank-Michael Göttsche; Xiaodong Zhang; Shaofei Wang; Mingsong Li. 2021. "Continuous evaluation of the spatial representativeness of land surface temperature validation sites." Remote Sensing of Environment 265, no. : 112669.
Automatically registration of unmanned aerial vehicle (UAV) multispectral images is fundamental for subsequent applications. Although many studies exist for visible camera images and satellite multispectral image registration, studies for UAV are still rare. Under this context, this study firstly evaluates the performance of several widely used traditional methods (i.e., SIFT, SURF, ORB, and CFOG) for visible camera and satellite images in UAV multispectral image registration. This study further proposes an unsupervised and end-to-end deep learning network (i.e., DSIM) for multispectral image registration. An evident feature of DSIM is to regress the homography parameters with convolutional neural networks and to use the pyramid structural similarity loss to optimize the network. 1200 groups of UAV multispectral images acquired over three different sites in four months are used to comprehensively test the aforementioned five methods. Results show that CFOG achieves the highest correct matching rate in the test set, followed by DSIM and SIFT. Nevertheless, DSIM is more robust in images with weak or repeated texture than CFOG and SIFT. In addition, performance of CFOG and SIFT is closely related to the number of the found matching points. Based on the findings, we propose a multi-method ensemble strategy to combine CFOG, DSIM, and SIFT according to the number of the found matching points. This strategy outperforms the individual methods with a correct matching rate of 96.2%. Lower correct matching rate of CFOG + SIFT confirms that DSIM and traditional methods are very complementary in UAV multispectral image registrations.
Lingxuan Meng; Ji Zhou; Shaomin Liu; Lirong Ding; Jirong Zhang; Shaofei Wang; Tianjie Lei. Investigation and evaluation of algorithms for unmanned aerial vehicle multispectral image registration. International Journal of Applied Earth Observation and Geoinformation 2021, 102, 102403 .
AMA StyleLingxuan Meng, Ji Zhou, Shaomin Liu, Lirong Ding, Jirong Zhang, Shaofei Wang, Tianjie Lei. Investigation and evaluation of algorithms for unmanned aerial vehicle multispectral image registration. International Journal of Applied Earth Observation and Geoinformation. 2021; 102 ():102403.
Chicago/Turabian StyleLingxuan Meng; Ji Zhou; Shaomin Liu; Lirong Ding; Jirong Zhang; Shaofei Wang; Tianjie Lei. 2021. "Investigation and evaluation of algorithms for unmanned aerial vehicle multispectral image registration." International Journal of Applied Earth Observation and Geoinformation 102, no. : 102403.
Partitioning of evapotranspiration (ET) into evaporation (E) and transpiration (T) is challenging but important to better understand the mechanisms of water loss from the ground surface to the atmosphere, especially in semiarid and arid regions. In this study, the underlying water use efficiency (uWUE) method is compared with hydrometric and remote sensing-based ET partitioning methods. The uWUE method is considered to be a promising method for partitioning ET, and can also be used to obtain temporal continuous data with fine spatial representation. Thus, the uWUE method was used to partition ET in six typical ecosystems in the Heihe River basin (HRB), which is the second largest endorheic river basin in western China. During 2008–2016, the daily average contributions of T to ET (T/ET) were 0.53, 0.52, 0.59, 0.37, 0.56, and 0.59 in the alpine meadow, Qinghai spruce, maize, desert, Tamarix, and Populus euphratica–Tamarix ecosystems, respectively. The T/ET ratio exhibited obvious seasonal variations in alpine meadow, maize, Tamarix, and Populus euphratica–Tamarix ecosystems. The ET partitioning results were related to air temperature in all ecosystems, especially in areas with sufficient precipitation or irrigation water supply. The vapor pressure deficit was also a main controlling factor in the upper- and middle-reach ecosystems, especially in the Qinghai spruce ecosystem. Groundwater and/or soil moisture made high relative contributions (RCs, %) to the T/ET ratio of the riparian forest in the lower reaches. Additionally, the leaf area index also made a high RC to the T/ET ratio of deciduous vegetation. Determining the quantitative contribution of T to ET in the HRB is beneficial for water resource management to guide the rational allocation and efficient use of water resources.
Ziwei Xu; Zhongli Zhu; Shaomin Liu; Lisheng Song; Xiaochen Wang; Sha Zhou; Xiaofan Yang; Tongren Xu. Evapotranspiration partitioning for multiple ecosystems within a dryland watershed: Seasonal variations and controlling factors. Journal of Hydrology 2021, 598, 126483 .
AMA StyleZiwei Xu, Zhongli Zhu, Shaomin Liu, Lisheng Song, Xiaochen Wang, Sha Zhou, Xiaofan Yang, Tongren Xu. Evapotranspiration partitioning for multiple ecosystems within a dryland watershed: Seasonal variations and controlling factors. Journal of Hydrology. 2021; 598 ():126483.
Chicago/Turabian StyleZiwei Xu; Zhongli Zhu; Shaomin Liu; Lisheng Song; Xiaochen Wang; Sha Zhou; Xiaofan Yang; Tongren Xu. 2021. "Evapotranspiration partitioning for multiple ecosystems within a dryland watershed: Seasonal variations and controlling factors." Journal of Hydrology 598, no. : 126483.
Successfully applied in the carbon research area, sun-induced chlorophyll fluorescence (SIF) has raised the interest of researchers from the water research domain. However, current works focused on the empirical relationship between SIF and plant transpiration (T), while the mechanistic linkage between them has not been fully explored. Two mechanism methods were developed to estimate T via SIF, namely the water-use efficiency (WUE) method and conductance method based on the carbon–water coupling framework. The T estimated by these two methods was compared with T partitioned from eddy covariance instrument measured evapotranspiration at four different sites. Both methods showed good performance at the hourly (R2 = 0.57 for the WUE method and 0.67 for the conductance method) and daily scales (R2 = 0.67 for the WUE method and 0.78 for the conductance method). The developed mechanism methods provide theoretical support and have a great potential basis for deriving ecosystem T by satellite SIF observations.
Huaize Feng; Tongren Xu; Liangyun Liu; Sha Zhou; Jingxue Zhao; Shaomin Liu; Ziwei Xu; Kebiao Mao; Xinlei He; Zhongli Zhu; Linna Chai. Modeling Transpiration with Sun-Induced Chlorophyll Fluorescence Observations via Carbon-Water Coupling Methods. Remote Sensing 2021, 13, 804 .
AMA StyleHuaize Feng, Tongren Xu, Liangyun Liu, Sha Zhou, Jingxue Zhao, Shaomin Liu, Ziwei Xu, Kebiao Mao, Xinlei He, Zhongli Zhu, Linna Chai. Modeling Transpiration with Sun-Induced Chlorophyll Fluorescence Observations via Carbon-Water Coupling Methods. Remote Sensing. 2021; 13 (4):804.
Chicago/Turabian StyleHuaize Feng; Tongren Xu; Liangyun Liu; Sha Zhou; Jingxue Zhao; Shaomin Liu; Ziwei Xu; Kebiao Mao; Xinlei He; Zhongli Zhu; Linna Chai. 2021. "Modeling Transpiration with Sun-Induced Chlorophyll Fluorescence Observations via Carbon-Water Coupling Methods." Remote Sensing 13, no. 4: 804.
Land surface hydrothermal conditions (LSHCs) reflect land surface moisture and heat conditions, and play an important role in energy and water cycles in soil-plant-atmosphere continuum. Based on comparison of four evaluation methods (namely, the classic statistical method, geostatistical method, information theory method, and fractal method), this study proposed a new scheme for evaluating the spatial heterogeneity of LSHCs. This scheme incorporates diverse remotely sensed surface parameters, e.g., leaf area index-LAI, the normalized difference vegetation index-NDVI, net radiation-Rn, and land surface temperature-LST. The LSHCs can be classified into three categories, namely homogeneous, moderately heterogeneous and highly heterogeneous based on the remotely sensed LAI data with a 30 m spatial resolution and the combination of normalized information entropy (S′) and coefficient of variation (CV). Based on the evaluation scheme, the spatial heterogeneity of land surface hydrothermal conditions at six typical flux observation stations in the Heihe River Basin during the vegetation growing season were evaluated. The evaluation results were consistent with the land surface type characteristics exhibited by Google Earth imagery and spatial heterogeneity assessed by high resolution remote sensing evapotranspiration data. Impact factors such as precipitation and irrigation events, spatial resolutions of remote sensing data, heterogeneity in the vertical direction, topography and sparse vegetation could also affect the evaluation results. For instance, short-term changes (precipitation and irrigation events) in the spatial heterogeneity of LSHCs can be diagnosed by energy factors, while long-term changes can be indicated by vegetation factors. The spatial heterogeneity of LSHCs decreases when decreasing the spatial resolution of remote sensing data. The proposed evaluation scheme would be useful for the quantification of spatial heterogeneity of LSHCs over flux observation stations toward the global scale, and also contribute to the improvement of the accuracy of estimation and validation for remotely sensed (or model simulated) evapotranspiration.
Yuan Zhang; Shaomin Liu; Xiao Hu; Jianghao Wang; Xiang Li; Ziwei Xu; Yanfei Ma; Rui Liu; Tongren Xu; Xiaofan Yang. Evaluating Spatial Heterogeneity of Land Surface Hydrothermal Conditions in the Heihe River Basin. Chinese Geographical Science 2020, 30, 855 -875.
AMA StyleYuan Zhang, Shaomin Liu, Xiao Hu, Jianghao Wang, Xiang Li, Ziwei Xu, Yanfei Ma, Rui Liu, Tongren Xu, Xiaofan Yang. Evaluating Spatial Heterogeneity of Land Surface Hydrothermal Conditions in the Heihe River Basin. Chinese Geographical Science. 2020; 30 (5):855-875.
Chicago/Turabian StyleYuan Zhang; Shaomin Liu; Xiao Hu; Jianghao Wang; Xiang Li; Ziwei Xu; Yanfei Ma; Rui Liu; Tongren Xu; Xiaofan Yang. 2020. "Evaluating Spatial Heterogeneity of Land Surface Hydrothermal Conditions in the Heihe River Basin." Chinese Geographical Science 30, no. 5: 855-875.
Reliable estimates of terrestrial latent heat flux (LE) at high spatial and temporal resolutions are of vital importance for energy balance and water resource management. However, currently available LE products derived from satellite data generally have high revisit frequency or fine spatial resolution. In this study, we explored the feasibility of the high spatiotemporal resolution LE fusion framework to take advantage of the Moderate Resolution Imaging Spectroradiometer (MODIS) and Chinese GaoFen-1 Wide Field View (GF-1 WFV) data. In particular, three-fold fusion schemes based on Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) were employed, including fusion of surface reflectance (Scheme 1), vegetation indices (Scheme 2) and high order LE products (Scheme 3). Our results showed that the fusion of vegetation indices and further computing LE (Scheme 2) achieved better accuracy and captured more detailed information of terrestrial LE, where the determination coefficient (R2) varies from 0.86 to 0.98, the root-mean-square error (RMSE) ranges from 1.25 to 9.77 W/m2 and the relative RSME (rRMSE) varies from 2% to 23%. The time series of merged LE in 2017 using the optimal Scheme 2 also showed a relatively good agreement with eddy covariance (EC) measurements and MODIS LE products. The fusion approach provides spatiotemporal continuous LE estimates and also reduces the uncertainties in LE estimation, with an increment in R2 by 0.06 and a decrease in RMSE by 23.4% on average. The proposed high spatiotemporal resolution LE estimation framework using multi-source data showed great promise in monitoring LE variation at field scale, and may have value in planning irrigation schemes and providing water management decisions over agroecosystems.
Xiangyi Bei; Yunjun Yao; Lilin Zhang; Yi Lin; Shaomin Liu; Kun Jia; Xiaotong Zhang; Ke Shang; Junming Yang; Xiaowei Chen; Xiaozheng Guo. Estimation of Daily Terrestrial Latent Heat Flux with High Spatial Resolution from MODIS and Chinese GF-1 Data. Sensors 2020, 20, 2811 .
AMA StyleXiangyi Bei, Yunjun Yao, Lilin Zhang, Yi Lin, Shaomin Liu, Kun Jia, Xiaotong Zhang, Ke Shang, Junming Yang, Xiaowei Chen, Xiaozheng Guo. Estimation of Daily Terrestrial Latent Heat Flux with High Spatial Resolution from MODIS and Chinese GF-1 Data. Sensors. 2020; 20 (10):2811.
Chicago/Turabian StyleXiangyi Bei; Yunjun Yao; Lilin Zhang; Yi Lin; Shaomin Liu; Kun Jia; Xiaotong Zhang; Ke Shang; Junming Yang; Xiaowei Chen; Xiaozheng Guo. 2020. "Estimation of Daily Terrestrial Latent Heat Flux with High Spatial Resolution from MODIS and Chinese GF-1 Data." Sensors 20, no. 10: 2811.
To investigate oasis-desert microclimate effects, we performed a series of numerical simulations in an idealized oasis-desert system based on an improved computational fluid dynamics (CFD) model for simulating atmospheric boundary layer flows, air temperature and humidity. Numerical simulations were designed based on the hydrometeorological observations obtained during the HiWATER-MUSOEXE (Heihe Watershed Allied Telemetry Experimental Research, Multi-Scale Observation Experiment on Evapotranspiration over heterogeneous land surfaces) campaign. The results are summarized as follows: (1) Oasis-desert interactions are significantly affected by background wind conditions. We observed the oasis-desert local circulation under calm background wind conditions and the oasis thermal internal boundary layer under low wind speed conditions induced by hydrothermal contracts. These interactions will disappear when the background wind speed is sufficiently high, and there is only an oasis dynamic internal boundary layer caused by the aerodynamic roughness length contrast. (2) Oasis-desert interactions lead to a series of microclimate effects, including the oasis cold-wet island effect, air humidity inversion effect within the surrounding desert and oasis wind shield effect, which are important for the stability and sustainability of the oases-desert ecosystem. (3) The hydrothermal conditions due to the difference between the oasis and desert, the vegetation fraction and distribution patterns impact the oasis-desert microclimate effects. The intensity of oasis-desert interactions increases with the land surface temperature (LST) difference in the oasis-desert. The oasis-desert interactions are gradually strengthened with the increase of the vegetation fraction within the oasis. Integrated ecological and economic benefits of the oasis, the oasis vegetation pattern, which includes the croplands and shelterbelts staggered within the oasis and the shelterbelts surrounding the outside, is beneficial to limiting the loss of water vapor and preventing sandstorms from the oasis. The findings of the current study improve the fundamental understanding of the microclimate and provide implications for maintaining the sustainability of oasis-desert ecosystems.
Rui Liu; Andrey Sogachev; Xiaofan Yang; Shaomin Liu; Tongren Xu; Junjie Zhang. Investigating microclimate effects in an oasis-desert interaction zone. Agricultural and Forest Meteorology 2020, 290, 107992 .
AMA StyleRui Liu, Andrey Sogachev, Xiaofan Yang, Shaomin Liu, Tongren Xu, Junjie Zhang. Investigating microclimate effects in an oasis-desert interaction zone. Agricultural and Forest Meteorology. 2020; 290 ():107992.
Chicago/Turabian StyleRui Liu; Andrey Sogachev; Xiaofan Yang; Shaomin Liu; Tongren Xu; Junjie Zhang. 2020. "Investigating microclimate effects in an oasis-desert interaction zone." Agricultural and Forest Meteorology 290, no. : 107992.
The Heihe River Basin (HRB), with unique landscapes and coexisting cold and arid regions, is the second largest endorheic basin in northwestern China. The Heihe integrated observatory network was established in 2007, which included multi-element, multiscale, distributed, and incorporating satellite-airborne-ground based observations via Internet of Things technology; these observations span the main land cover of the basin. This observatory provides a great opportunity to analyze the spatiotemporal variation in evapotranspiration (ET) in the HRB, and ET characteristics were investigated on three scales (typical ecosystems, oasis-desert systems, watershed) taking the HRB as a research object. The average annual ET in typical ecosystems is approximately 380–530 mm upstream (alpine meadow, Qinghai spruce, shrub), 640–1000 mm midstream (maize, wetland), 610–680 mm downstream (riparian forest), and 190 mm and 50 mm in midstream and downstream desert surfaces, respectively. The ET from plant surfaces is strongly controlled by available energy in upstream and midstream regions, while it is controlled by vapor pressure deficit (VPD) and surface conductance downstream. The ET in oasis and desert systems is characterized by three gradients: plant, residential area/barren land, and desert, with a maximum difference of annual ET more than 500 mm. This difference is primarily caused by variations of soil moisture among different underlying surfaces. For watershed ET, higher ET was observed upstream, and it decreased from midstream to downstream, with the highest values in the oasis. The annual ET in the main plant surfaces was approximately 500–700 mm, 600–800 mm, and 600–700 mm in the up-, mid-, and downstream regions, respectively, while the ET was approximately 100–250 mm and 50–200 mm in desert and barren or sparsely vegetation surfaces in the mid- and downstream regions, respectively. The spatiotemporal variations of ET were primarily influenced by land cover, soil moisture, vegetation condition and available energy. The results improve our understanding of the spatiotemporal variations in ET in the HRB and apply to comparable endorheic basins with similar climatic and landscape conditions.
Ziwei Xu; Shaomin Liu; Zhongli Zhu; Ji Zhou; Wenjiao Shi; Tongren Xu; Xiaofan Yang; Yuan Zhang; Xinlei He. Exploring evapotranspiration changes in a typical endorheic basin through the integrated observatory network. Agricultural and Forest Meteorology 2020, 290, 108010 .
AMA StyleZiwei Xu, Shaomin Liu, Zhongli Zhu, Ji Zhou, Wenjiao Shi, Tongren Xu, Xiaofan Yang, Yuan Zhang, Xinlei He. Exploring evapotranspiration changes in a typical endorheic basin through the integrated observatory network. Agricultural and Forest Meteorology. 2020; 290 ():108010.
Chicago/Turabian StyleZiwei Xu; Shaomin Liu; Zhongli Zhu; Ji Zhou; Wenjiao Shi; Tongren Xu; Xiaofan Yang; Yuan Zhang; Xinlei He. 2020. "Exploring evapotranspiration changes in a typical endorheic basin through the integrated observatory network." Agricultural and Forest Meteorology 290, no. : 108010.
Water use efficiency (WUE) measures the tradeoff between carbon uptake and water consumption in terrestrial ecosystems. It remains unclear how the responses of WUE to drought vary with drought severity. We assessed the spatio-temporal variations of ecosystem WUE and its responses to drought for terrestrial ecosystems in Southwest China over the period 2000–2017. The annual WUE values varied with vegetation type in the region: Forests (3.25 gC kg−1H2O) > shrublands (2.00 gC kg−1H2O) > croplands (1.76 gC kg−1H2O) > grasslands (1.04 gC kg−1H2O). During the period 2000–2017, frequent droughts occurred in Southwest China, and overall, drought had an enhancement effect on WUE. However, the effects of drought on WUE varied with vegetation type and drought severity. Croplands were the most sensitive to drought, and slight water deficiency led to the decline of cropland WUE. Over grasslands, mild drought increased its WUE while moderate and severe drought reduced its WUE. For forests and shrublands, mild and moderate drought increased their WUE, and only severe drought reduce their WUE, indicating that these ecosystems had stronger resistance to drought. Assessing the patterns and trends of ecosystem WUE and its responses to drought are essential for understanding plant water use strategy and informing ecosystem water management.
Jingxue Zhao; Tongren Xu; Jingfeng Xiao; Shaomin Liu; Kebiao Mao; Lisheng Song; Yunjun Yao; Xinlei He; Huaize Feng. Responses of Water Use Efficiency to Drought in Southwest China. Remote Sensing 2020, 12, 199 .
AMA StyleJingxue Zhao, Tongren Xu, Jingfeng Xiao, Shaomin Liu, Kebiao Mao, Lisheng Song, Yunjun Yao, Xinlei He, Huaize Feng. Responses of Water Use Efficiency to Drought in Southwest China. Remote Sensing. 2020; 12 (1):199.
Chicago/Turabian StyleJingxue Zhao; Tongren Xu; Jingfeng Xiao; Shaomin Liu; Kebiao Mao; Lisheng Song; Yunjun Yao; Xinlei He; Huaize Feng. 2020. "Responses of Water Use Efficiency to Drought in Southwest China." Remote Sensing 12, no. 1: 199.
An accurate and spatially continuous estimation of terrestrial latent heat flux (LE) is crucial to the management and planning of water resources for arid and semi-arid areas, for which LE estimations from different satellite sensors unfortunately often contain data gaps and are inconsistent. Many integration approaches have been implemented to overcome these limitations; however, most suffer from either the persistent bias of relying on datasets at only one resolution or the spatiotemporal inconsistency of LE products. In this study, we exhibit an integration case in the midstream of the Heihe River Basin of northwest China by using a multi-resolution Kalman filter (MKF) method to develop continuous and consistent LE maps from satellite LE datasets across different resolutions. The Moderate Resolution Imaging Spectroradiometer (MODIS) LE product (MOD16), the Landsat-based LE product derived from the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor, and ground observations of eddy covariance flux tower from June to September 2012 are used. The integrated results illustrate that data gaps of MOD16 dropped to less than 0.4% from the original 27–52%, and the root-mean-square error (RMSE) between the LE products decreased by 50.7% on average. Our findings indicate that the MKF method has excellent capacity to fill data gaps, reduce uncertainty, and improve the consistency of multiple LE datasets at different resolutions.
Jia Xu; Yunjun Yao; Kanran Tan; Yufu Li; Shaomin Liu; Ke Shang; Kun Jia; Xiaotong Zhang; Xiaowei Chen; Xiangyi Bei. Integrating Latent Heat Flux Products from MODIS and Landsat Data Using Multi-Resolution Kalman Filter Method in the Midstream of Heihe River Basin of Northwest China. Remote Sensing 2019, 11, 1787 .
AMA StyleJia Xu, Yunjun Yao, Kanran Tan, Yufu Li, Shaomin Liu, Ke Shang, Kun Jia, Xiaotong Zhang, Xiaowei Chen, Xiangyi Bei. Integrating Latent Heat Flux Products from MODIS and Landsat Data Using Multi-Resolution Kalman Filter Method in the Midstream of Heihe River Basin of Northwest China. Remote Sensing. 2019; 11 (15):1787.
Chicago/Turabian StyleJia Xu; Yunjun Yao; Kanran Tan; Yufu Li; Shaomin Liu; Ke Shang; Kun Jia; Xiaotong Zhang; Xiaowei Chen; Xiangyi Bei. 2019. "Integrating Latent Heat Flux Products from MODIS and Landsat Data Using Multi-Resolution Kalman Filter Method in the Midstream of Heihe River Basin of Northwest China." Remote Sensing 11, no. 15: 1787.
Ground measured component radiative temperatures are basic inputs for modelling energy and hydrological processes and for simulating land surface temperature (LST) as “viewed” by remote sensors. However, knowledge of factors affecting the component temperatures and about their potential for upscaling LST over sparsely vegetated surfaces with high heterogeneity is still lacking. Here, a MUlti-Scale Observation Experiment on land Surface temperature (MUSOES) was performed under HiWATER over an arid sparsely vegetated surface. Component temperatures were obtained with different instruments on multiple spatial scales; for LST upscaling, a three-dimensional scene model was employed for two forest stations (MFS and PFS) and a two-dimensional model for a shrub station (SUP). Results show that intrinsic characteristics contribute to the temperature variability between different components and even within a single component. Using a thermal infrared (TIR) imager at MFS, average temperature difference of 24.9 K between sunlit bare soil and tree canopy was found; different components exhibit different internal temperature differences at direction-level and pixel-level. Furthermore, illumination conditions, viewing directions, and instrument types significantly affected the measured component temperatures. The measurements of the TIR radiometer and the imager can deviate considerably (e.g. 14.9 K for sunlit bare soil at MFS). When the longwave radiometers were selected as target sensors, the component temperatures measured by the imager exhibit good potential for LST upscaling: the upscaled LST has MBD/RMSD values of 2.0 K/2.3 K at MFS and 2.0 K/2.5 K at PFS. The TIR radiometer’s measurements introduce large uncertainties into LST upscaling at MFS and PFS, but result in good accuracy at SUP, mainly due to its simpler land cover and surface structure. Findings from this study can benefit our understanding of factors affecting observations of component temperatures and the LST upscaling process and are, therefore, relevant for further studying the evaluation of satellite LST products.
Mingsong Li; Ji Zhou; Zhixing Peng; Shaomin Liu; Frank-Michael Göttsche; Xiaodong Zhang; Lisheng Song. Component radiative temperatures over sparsely vegetated surfaces and their potential for upscaling land surface temperature. Agricultural and Forest Meteorology 2019, 276-277, 107600 .
AMA StyleMingsong Li, Ji Zhou, Zhixing Peng, Shaomin Liu, Frank-Michael Göttsche, Xiaodong Zhang, Lisheng Song. Component radiative temperatures over sparsely vegetated surfaces and their potential for upscaling land surface temperature. Agricultural and Forest Meteorology. 2019; 276-277 ():107600.
Chicago/Turabian StyleMingsong Li; Ji Zhou; Zhixing Peng; Shaomin Liu; Frank-Michael Göttsche; Xiaodong Zhang; Lisheng Song. 2019. "Component radiative temperatures over sparsely vegetated surfaces and their potential for upscaling land surface temperature." Agricultural and Forest Meteorology 276-277, no. : 107600.
High-quality and long time-series soil moisture (SM) data are increasingly required for the Qinghai-Tibet Plateau (QTP) to more accurately and effectively assess climate change. In this study, to evaluate the accuracy and effectiveness of SM data, five passive microwave remotely sensed SM products are collected over the QTP, including those from the soil moisture active passive (SMAP), soil moisture and ocean salinity INRA-CESBIO (SMOS-IC), Fengyun-3B microwave radiation image (FY3B), and two SM products derived from the advanced microwave scanning radiometer 2 (AMSR2). The two AMSR2 products are generated by the land parameter retrieval model (LPRM) and the Japan Aerospace Exploration Agency (JAXA) algorithm, respectively. The SM products are evaluated through a two-stage data comparison method. The first stage is direct validation at the grid scale. Five SM products are compared with corresponding in situ measurements at five in situ networks, including Heihe, Naqu, Pali, Maqu, and Ngari. Another stage is indirect validation at the regional scale, where the uncertainties of the data are quantified by using a three-cornered hat (TCH) method. The results at the regional scale indicate that soil moisture is underestimated by JAXA and overestimated by LPRM, some noise is contained in temporal variations in SMOS-IC, and FY3B has relatively low absolute accuracy. The uncertainty of SMAP is the lowest among the five products over the entire QTP. In the SM map composed by five SM products with the lowest pixel-level uncertainty, 66.64% of the area is covered by SMAP (JAXA: 19.39%, FY3B: 10.83%, LPRM: 2.11%, and SMOS-IC: 1.03%). This study reveals some of the reasons for the different performances of these five SM products, mainly from the perspective of the parameterization schemes of their corresponding retrieval algorithms. Specifically, the parameterization configurations and corresponding input datasets, including the land-surface temperature, the vegetation optical depth, and the soil dielectric mixing model are analyzed and discussed. This study provides quantitative evidence to better understand the uncertainties of SM products and explain errors that originate from the retrieval algorithms.
Jin Liu; Linna Chai; Zheng Lu; Shaomin Liu; Yuquan Qu; Deyuan Geng; Yongze Song; Yabing Guan; Zhixia Guo; Jian Wang; Zhongli Zhu. Evaluation of SMAP, SMOS-IC, FY3B, JAXA, and LPRM Soil Moisture Products over the Qinghai-Tibet Plateau and Its Surrounding Areas. Remote Sensing 2019, 11, 792 .
AMA StyleJin Liu, Linna Chai, Zheng Lu, Shaomin Liu, Yuquan Qu, Deyuan Geng, Yongze Song, Yabing Guan, Zhixia Guo, Jian Wang, Zhongli Zhu. Evaluation of SMAP, SMOS-IC, FY3B, JAXA, and LPRM Soil Moisture Products over the Qinghai-Tibet Plateau and Its Surrounding Areas. Remote Sensing. 2019; 11 (7):792.
Chicago/Turabian StyleJin Liu; Linna Chai; Zheng Lu; Shaomin Liu; Yuquan Qu; Deyuan Geng; Yongze Song; Yabing Guan; Zhixia Guo; Jian Wang; Zhongli Zhu. 2019. "Evaluation of SMAP, SMOS-IC, FY3B, JAXA, and LPRM Soil Moisture Products over the Qinghai-Tibet Plateau and Its Surrounding Areas." Remote Sensing 11, no. 7: 792.
Time series of soil moisture (SM) data in the Qinghai–Tibet plateau (QTP) covering a period longer than one decade are important for understanding the dynamics of land surface–atmosphere feedbacks in the global climate system. However, most existing SM products have a relatively short time series or show low performance over the challenging terrain of the QTP. In order to improve the spaceborne monitoring in this area, this study presents a random forest (RF) method to rebuild a high-accuracy SM product over the QTP from 19 June 2002 to 31 March 2015 by adopting the advanced microwave scanning radiometer for earth observing system (AMSR-E), and the advanced microwave scanning radiometer 2 (AMSR2), and tracking brightness temperatures with latitude and longitude using the International Geosphere–Biospheres Programme (IGBP) classification data, the digital elevation model (DEM) and the day of the year (DOY) as spatial predictors. Brightness temperature products (from frequencies 10.7 GHz, 18.7 GHz and 36.5 GHz) of AMSR2 were used to train the random forest model on two years of Soil Moisture Active Passive (SMAP) SM data. The simulated SM values were compared with third year SMAP data and in situ stations. The results show that the RF model has high reliability as compared to SMAP, with a high correlation (R = 0.95) and low values of root mean square error (RMSE = 0.03 m3/m3) and mean absolute percent error (MAPE = 19%). Moreover, the random forest soil moisture (RFSM) results agree well with the data from five in situ networks, with mean values of R = 0.75, RMSE = 0.06 m3/m3, and bias = −0.03 m3/m3 over the whole year and R = 0.70, RMSE = 0.07 m3/m3, and bias = −0.05 m3/m3 during the unfrozen seasons. In order to test its performance throughout the whole region of QTP, the three-cornered hat (TCH) method based on removing common signals from observations and then calculating the uncertainties is applied. The results indicate that RFSM has the smallest relative error in 56% of the region, and it performs best relative to the Japan Aerospace Exploration Agency (JAXA), Global Land Data Assimilation System (GLDAS), and European Space Agency’s Climate Change Initiative (ESA CCI) project. The spatial distribution shows that RFSM has a similar spatial trend as GLDAS and ESA CCI, but RFSM exhibits a more distinct spatial distribution and responds to precipitation more effectively than GLDAS and ESA CCI. Moreover, a trend analysis shows that the temporal variation of RFSM agrees well with precipitation and LST (land surface temperature), with a dry trend in most regions of QTP and a wet trend in few north, southeast and southwest regions of QTP. In conclusion, a spatiotemporally continuous SM product with a high accuracy over the QTP was obtained.
Yuquan Qu; Zhongli Zhu; Linna Chai; Shaomin Liu; Carsten Montzka; Jin Liu; Xiaofan Yang; Zheng Lu; Rui Jin; Xiang Li; Zhixia Guo; Jie Zheng. Rebuilding a Microwave Soil Moisture Product Using Random Forest Adopting AMSR-E/AMSR2 Brightness Temperature and SMAP over the Qinghai–Tibet Plateau, China. Remote Sensing 2019, 11, 683 .
AMA StyleYuquan Qu, Zhongli Zhu, Linna Chai, Shaomin Liu, Carsten Montzka, Jin Liu, Xiaofan Yang, Zheng Lu, Rui Jin, Xiang Li, Zhixia Guo, Jie Zheng. Rebuilding a Microwave Soil Moisture Product Using Random Forest Adopting AMSR-E/AMSR2 Brightness Temperature and SMAP over the Qinghai–Tibet Plateau, China. Remote Sensing. 2019; 11 (6):683.
Chicago/Turabian StyleYuquan Qu; Zhongli Zhu; Linna Chai; Shaomin Liu; Carsten Montzka; Jin Liu; Xiaofan Yang; Zheng Lu; Rui Jin; Xiang Li; Zhixia Guo; Jie Zheng. 2019. "Rebuilding a Microwave Soil Moisture Product Using Random Forest Adopting AMSR-E/AMSR2 Brightness Temperature and SMAP over the Qinghai–Tibet Plateau, China." Remote Sensing 11, no. 6: 683.
Evapotranspiration (ET) is a combination of two distinct processes, soil or water evaporation (E) and plant transpiration (T), that occur between plants and the atmosphere, soil and the atmosphere, and water and the atmosphere. ET is also an important link between the terrestrial ecosystem and hydrological processes. In this chapter, we focus primarily on ET measurements using micrometeorological methods. Three typical ET measurement techniques, namely, the Bowen ratio-energy balance, eddy covariance, and scintillometer methods, which have a long history and are used widely throughout the world, are introduced. A brief review of their theoretical background, installation and maintenance, data processing and quality control, and footprint is presented, in addition to a brief summary of the advantages and disadvantages of each method. Additionally, ET measurements at observational networks and intensive experiments are presented. The ET measurement methods differ in observational theory, temporal–spatial scales, and precision. Researchers can select a suitable method according to their research objectives.
Shaomin Liu; Ziwei Xu. Micrometeorological Methods to Determine Evapotranspiration. River Basin Management 2019, 201 -239.
AMA StyleShaomin Liu, Ziwei Xu. Micrometeorological Methods to Determine Evapotranspiration. River Basin Management. 2019; ():201-239.
Chicago/Turabian StyleShaomin Liu; Ziwei Xu. 2019. "Micrometeorological Methods to Determine Evapotranspiration." River Basin Management , no. : 201-239.
Research on land surface processes at the catchment scale has drawn much attention over the past few decades, and a number of watershed observatories have been established worldwide. The Heihe River Basin (HRB), which contains the second largest inland river in China, is an ideal natural field experimental area for investigation of land surface processes involving diverse landscapes and the coexistence of cold and arid regions. The Heihe Integrated Observatory Network was established in 2007. For long-term observations, a hydrometeorological observatory, ecohydrological wireless sensor network, and satellite remote sensing are now in operation. In 2012, a multiscale observation experiment on evapotranspiration over heterogeneous land surfaces was conducted in the midstream region of the HRB, which included a flux observation matrix, wireless sensor network, airborne remote sensing, and synchronized ground measurements. Under an open data policy, the datasets have been publicly released following careful data processing and quality control. The outcomes highlight the integrated research on land surface processes in the HRB and include observed trends, scaling methods, high spatiotemporal resolution remote sensing products, and model–data integration in the HRB, all of which are helpful to other endorheic basins in the “Silk Road Economic Belt.” Henceforth, the goal of the Heihe Integrated Observatory Network is to develop an intelligent monitoring system that incorporates ground-based observatory networks, unmanned aerial vehicles, and multi-source satellites through the Internet of Things technology. Furthermore, biogeochemical processes observation will be improved, and the study of integrating ground observations, remote sensing, and large-scale models will be promoted further. Copyright © 2018. . Copyright © by the Soil Science Society of America, Inc.
Shaomin Liu; Xin Li; Ziwei Xu; Tao Che; Qing Xiao; Mingguo Ma; Qinhuo Liu; Rui Jin; Jianwen Guo; Liangxu Wang; Weizhen Wang; Yuan Qi; Hongyi Li; Tongren Xu; Youhua Ran; Xiaoli Hu; ShengJin Shi; Zhongli Zhu; Junlei Tan; Yang Zhang; Zhiguo Ren. The Heihe Integrated Observatory Network: A Basin-Scale Land Surface Processes Observatory in China. Vadose Zone Journal 2018, 17, 180072 .
AMA StyleShaomin Liu, Xin Li, Ziwei Xu, Tao Che, Qing Xiao, Mingguo Ma, Qinhuo Liu, Rui Jin, Jianwen Guo, Liangxu Wang, Weizhen Wang, Yuan Qi, Hongyi Li, Tongren Xu, Youhua Ran, Xiaoli Hu, ShengJin Shi, Zhongli Zhu, Junlei Tan, Yang Zhang, Zhiguo Ren. The Heihe Integrated Observatory Network: A Basin-Scale Land Surface Processes Observatory in China. Vadose Zone Journal. 2018; 17 (1):180072.
Chicago/Turabian StyleShaomin Liu; Xin Li; Ziwei Xu; Tao Che; Qing Xiao; Mingguo Ma; Qinhuo Liu; Rui Jin; Jianwen Guo; Liangxu Wang; Weizhen Wang; Yuan Qi; Hongyi Li; Tongren Xu; Youhua Ran; Xiaoli Hu; ShengJin Shi; Zhongli Zhu; Junlei Tan; Yang Zhang; Zhiguo Ren. 2018. "The Heihe Integrated Observatory Network: A Basin-Scale Land Surface Processes Observatory in China." Vadose Zone Journal 17, no. 1: 180072.
A number of studies have estimated turbulent heat fluxes by assimilating sequences of land surface temperature (LST) observations into the strong constraint-variational data assimilation (SC-VDA) approaches. The SC-VDA approaches do not account for the structural model errors and uncertainties in the micrometeorological variables. In contrast to the SC-VDA approaches, the WC-VDA approach (the so-called weak constraint-VDA) accounts for the effects of structural and model errors by adding a model error term. In this study, the WC-VDA approach is tested at six study sites with different climatic and vegetative conditions. Its performance is also compared with that of SC-VDA at the six study sites. The results show that the WC-VDA produces 10.16% and 10.15% lower root mean square errors (RMSEs) for sensible and latent heat flux estimates compared with the SC-VDA approach. The model error term can capture errors in the turbulent heat flux estimates due to errors in LST and micrometeorological measurements, as well as structural model errors, and does not allow those errors to adversely affect the turbulent heat flux estimates. The findings also indicate that the estimated model error term varies reasonably well, so as to capture the misfit between predicted and observed net radiation in different hydrological and vegetative conditions. Finally, synthetically generated positive (negative) noises are added to the hydrological input variables (e.g., LST, air temperature, air humidity, incoming solar radiation, and wind speed) to examine whether the WC-VDA approach can capture those errors. It was found that the WC-VDA approach accounts for the errors in the input data and reduces their effect on the turbulent heat flux estimates.
Xinlei He; Tongren Xu; Sayed M. Bateni; Christopher M. U. Neale; Thomas Auligne; Shaomin Liu; Kaicun Wang; Kebiao Mao; Yunjun Yao. Evaluation of the Weak Constraint Data Assimilation Approach for Estimating Turbulent Heat Fluxes at Six Sites. Remote Sensing 2018, 10, 1994 .
AMA StyleXinlei He, Tongren Xu, Sayed M. Bateni, Christopher M. U. Neale, Thomas Auligne, Shaomin Liu, Kaicun Wang, Kebiao Mao, Yunjun Yao. Evaluation of the Weak Constraint Data Assimilation Approach for Estimating Turbulent Heat Fluxes at Six Sites. Remote Sensing. 2018; 10 (12):1994.
Chicago/Turabian StyleXinlei He; Tongren Xu; Sayed M. Bateni; Christopher M. U. Neale; Thomas Auligne; Shaomin Liu; Kaicun Wang; Kebiao Mao; Yunjun Yao. 2018. "Evaluation of the Weak Constraint Data Assimilation Approach for Estimating Turbulent Heat Fluxes at Six Sites." Remote Sensing 10, no. 12: 1994.
Operational estimation of spatio-temporal continuously daily evapotranspiration (ET), and the components evaporation (E) and transpiration (T), at river basin scale is very useful for developing sustainable water resource strategies, particularly in regions of limited water supplies. In this study, multi-year all-weather daily ET, E and T were estimated using MODIS-based (Dual Temperature Difference) DTD model under different land covers in the Heihe river basin in China, with a total area of approximately 143 × 103 km2. The remotely sensed ET was validated using ground measurements from large aperture scintillometer systems, with a source area of several kilometers, over grassland, cropland and riparian shrub-forest land cover. The results showed that the remotely sensed ET produced mean absolute percent differences (MAPD) of around 20% with the ground measurements during the growing season under clear sky conditions, but the model performance deteriorated for cloudy days. However, the daily ET product gave reasonable estimates for croplands with an MAPD value of about 20% and the estimates of T/ET and E/ET in good agreement with ground measurements. The DTD model also significantly outperformed other remote sensing-based models being applied globally. Based on these results the DTD model is considered reliable for monitoring crop water use and stress and to develop efficient irrigation strategies.
Lisheng Song; Shaomin Liu; William P. Kustas; Hector Nieto; Liang Sun; Ziwei Xu; Todd H. Skaggs; Yang Yang; Minguo Ma; Tongren Xu; Xuguang Tang; Qiuping Li. Monitoring and validating spatially and temporally continuous daily evaporation and transpiration at river basin scale. Remote Sensing of Environment 2018, 219, 72 -88.
AMA StyleLisheng Song, Shaomin Liu, William P. Kustas, Hector Nieto, Liang Sun, Ziwei Xu, Todd H. Skaggs, Yang Yang, Minguo Ma, Tongren Xu, Xuguang Tang, Qiuping Li. Monitoring and validating spatially and temporally continuous daily evaporation and transpiration at river basin scale. Remote Sensing of Environment. 2018; 219 ():72-88.
Chicago/Turabian StyleLisheng Song; Shaomin Liu; William P. Kustas; Hector Nieto; Liang Sun; Ziwei Xu; Todd H. Skaggs; Yang Yang; Minguo Ma; Tongren Xu; Xuguang Tang; Qiuping Li. 2018. "Monitoring and validating spatially and temporally continuous daily evaporation and transpiration at river basin scale." Remote Sensing of Environment 219, no. : 72-88.
The surface air temperature (Ta) dataset of the Tibetan Plateau is obtained by downscaling the China regional surface meteorological feature dataset (CRSMFD). It contains the daily mean Ta and 3-hourly instantaneous Ta. This dataset has a spatial resolution of 0.01°. Its time range for surface air temperature dataset is from 2000 to 2015. Spatial dimension of data: 73°E-106°E, 40°N-23°N. The Ta with a 0.01° can serve as an important input for the modeling of land surface processes, such as surface evapotranspiration estimation, agricultural monitoring, and climate change analysis.
Lirong Ding; Ji Zhou; Xiaodong Zhang; Shaomin Liu; Ruyin Cao. A long-term 0.01° surface air temperature dataset of Tibetan Plateau. Data in Brief 2018, 20, 748 -752.
AMA StyleLirong Ding, Ji Zhou, Xiaodong Zhang, Shaomin Liu, Ruyin Cao. A long-term 0.01° surface air temperature dataset of Tibetan Plateau. Data in Brief. 2018; 20 ():748-752.
Chicago/Turabian StyleLirong Ding; Ji Zhou; Xiaodong Zhang; Shaomin Liu; Ruyin Cao. 2018. "A long-term 0.01° surface air temperature dataset of Tibetan Plateau." Data in Brief 20, no. : 748-752.
The estimation of land-surface evapotranspiration (ET) at high spatial and temporal resolutions is important for management and planning of agricultural water resources, but available remote sensing data generally have either high spatial resolution or high temporal resolution. To overcome this limitation, we evaluated the use of a data fusion scheme, Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), to determine the surface parameters needed to estimate daily ET at a Landsat-like scale (100 m). In particular, we fused Moderate Resolution Imaging Spectroradiometer (MODIS) data with Landsat Enhanced Thematic Mapper Plus (ETM+) data in analysis of the Heihe River Basin (HRB), an arid region of Northwest China. The surface parameters were then used to drive the revised Surface Energy Balance System (SEBS) model to estimate daily ET at a spatial resolution of 100 m for this an arid irrigation area during the crop growth period (April to October) in 2012. The results showed that the daily ET estimates had a mean absolute percent error (MAPE) of 12% and a root mean square error (RMSE) of 0.81 mm/day relative to ground measurements from 18 eddy covariance (EC) sites in the study area. The validation results indicated good accuracy for land cover types of maize and vegetables, a slight overestimation for residential and wetland sites, and a slight underestimation for orchard site. Our comparison of the input parameter fusion approach (IPFA) and the ET fusion approach (ETFA) with field measurements indicated the IPFA was superior than the ETFA for land surfaces with high spatial heterogeneity. Furthermore, our high spatiotemporal ET estimates indicated that irrigation water efficiencies of the irrigation districts (mean: 70%) and villages (mean: 62%) had large spatial heterogeneity. These results point to the need for calculating ET at a high spatiotemporal resolution for monitoring and improving irrigation water efficiency at local scales. Our findings suggest that the proposed framework of estimating daily ET at a Landsat-like scale using multi-source data may also be applicable to other heterogeneous landscapes by providing a foundation for management of water resources at the basin or finer scales.
Yanfei Ma; Shaomin Liu; Lisheng Song; Ziwei Xu; Yaling Liu; Tongren Xu; Zhongli Zhu. Estimation of daily evapotranspiration and irrigation water efficiency at a Landsat-like scale for an arid irrigation area using multi-source remote sensing data. Remote Sensing of Environment 2018, 216, 715 -734.
AMA StyleYanfei Ma, Shaomin Liu, Lisheng Song, Ziwei Xu, Yaling Liu, Tongren Xu, Zhongli Zhu. Estimation of daily evapotranspiration and irrigation water efficiency at a Landsat-like scale for an arid irrigation area using multi-source remote sensing data. Remote Sensing of Environment. 2018; 216 ():715-734.
Chicago/Turabian StyleYanfei Ma; Shaomin Liu; Lisheng Song; Ziwei Xu; Yaling Liu; Tongren Xu; Zhongli Zhu. 2018. "Estimation of daily evapotranspiration and irrigation water efficiency at a Landsat-like scale for an arid irrigation area using multi-source remote sensing data." Remote Sensing of Environment 216, no. : 715-734.
Endorheic basins around the world are suffering from water and ecosystem crisis. To pursue sustainable development, quantifying the hydrological cycle is fundamentally important. However, knowledge gaps exist in how climate change and human activities influence the hydrological cycle in endorheic basins. We used an integrated eco-hydrological model, in combination with systematic observations, to analyze the hydrological cycle in the Heihe River Basin, a typical endorheic basin in arid region of China. The water budget was closed for different landscapes, river channel sections, and irrigation districts of the basin from 2001 to 2012. The results showed that climate warming, which has led to greater precipitation, snowmelt, glacier melt, and runoff, is a favorable factor in alleviating water scarcity. Human activities, including ecological water diversion, cropland expansion, and groundwater overexploitation, have both positive and negative effects. The natural oasis ecosystem has been restored considerably, but the overuse of water in midstream and the use of environmental flow for agriculture in downstream have exacerbated the water stress, resulting in unfavorable changes in surface-ground water interactions and raising concerns regarding how to fairly allocate water resources. Our results suggest that the water resource management in the region should be adjusted to adapt to a changing hydrological cycle and cropland area must be reduced and the abstraction of groundwater must be controlled. To foster long-term benefits, water conflicts should be handled from a broad socioeconomic perspective. The findings can provide useful information on endorheic basins to policy makers and stakeholders around the world.
Xin Li; Guodong Cheng; Yingchun Ge; Hongyi Li; Feng Han; Ge Yingchun; Wei Tian; Yong Tian; Xiaoduo Pan; Yanyun Nian; Yanlin Zhang; Youhua Ran; Yi Zheng; Bing Gao; Dawen Yang; Chunmiao Zheng; Xusheng Wang; Shaomin Liu; Ximing Cai. Hydrological Cycle in the Heihe River Basin and Its Implication for Water Resource Management in Endorheic Basins. Journal of Geophysical Research: Atmospheres 2018, 123, 890 -914.
AMA StyleXin Li, Guodong Cheng, Yingchun Ge, Hongyi Li, Feng Han, Ge Yingchun, Wei Tian, Yong Tian, Xiaoduo Pan, Yanyun Nian, Yanlin Zhang, Youhua Ran, Yi Zheng, Bing Gao, Dawen Yang, Chunmiao Zheng, Xusheng Wang, Shaomin Liu, Ximing Cai. Hydrological Cycle in the Heihe River Basin and Its Implication for Water Resource Management in Endorheic Basins. Journal of Geophysical Research: Atmospheres. 2018; 123 (2):890-914.
Chicago/Turabian StyleXin Li; Guodong Cheng; Yingchun Ge; Hongyi Li; Feng Han; Ge Yingchun; Wei Tian; Yong Tian; Xiaoduo Pan; Yanyun Nian; Yanlin Zhang; Youhua Ran; Yi Zheng; Bing Gao; Dawen Yang; Chunmiao Zheng; Xusheng Wang; Shaomin Liu; Ximing Cai. 2018. "Hydrological Cycle in the Heihe River Basin and Its Implication for Water Resource Management in Endorheic Basins." Journal of Geophysical Research: Atmospheres 123, no. 2: 890-914.