Weiwei Zhu

An Improved Method for Deriving Daily Evapotranspiration Estimates From Satellite Estimates on Cloud-Free Days

An improved method, based on the daily surface resistance, is proposed to extend satellite evapotranspiration (ET) on a clear day into ET for each and every day. Alternative climatic variables such as soil moisture, wind speed, and net radiation are explored for estimating daily surface resistance using a Penman-Monteith (P-M) formulation. The study was carried out for the Yingke (YK) oasis plains area (maize cropland) and the Arou (AR) alpine meadow area (grassland) located in the midstream and upstream, respectively, of the Heihe River Basin of northwestern China. Statistical results show that the proposed method performs well for estimating daily ET for both study areas, with results slightly superior in the midstream, cropland area where the coefficient of determination (R2) was 0.9249 and the index of agreement (d) was 0.978. In the upstream alpine meadow area, the coefficient of determination (R2) was 0.9074, and the index of agreement (d) was 0.961. The proposed method provides an enhanced approach for estimating daily ET in the ETWatch model. Future work will focus on scaling this improved method to the estimation of regional daily ET map.

A method for sensible heat flux model parameterization based on radiometric surface temperature and environmental factors without involving the parameter KB−1

Abstract Sensible heat flux is a key component of land–atmosphere interaction. In most parameterizations it is calculated with surface-air temperature differences and total aerodynamic resistance to heat transfer ( R ae ) that is related to the KB −1 parameter. Suitable values are hard to obtain since KB −1 is related both to canopy characteristics and environmental conditions. In this paper, a parameterize method for sensible heat flux over vegetated surfaces (maize field and grass land in the Heihe river basin of northwest China) was proposed based on the radiometric surface temperature, surface resistance ( R s ) and vapor pressures (saturated and actual) at the surface and the atmosphere above the canopy. A biophysics-based surface resistance model was revised to compute surface resistance with several environmental factors. The total aerodynamic resistance to heat transfer is directly calculated by combining the biophysics-based surface resistance and vapor pressures. One merit of this method is that the calculation of KB −1 can be avoided. The method provides a new way to estimate sensible heat flux over vegetated surfaces and its performance compares well to the LAS measured sensible heat and other empirical or semi-empirical KB −1 based estimations.

An improved satellite‐based approach for estimating vapor pressure deficit from MODIS data

Vapor pressure deficit (VPD) is an important variable widely used in ecosystem and climate models. In this paper, an improved satellite-based approach to estimating VPD was presented that uses several remote sensing products coupled with field measured data. The proposed method exploits an optimized algorithm to derive near-surface actual vapor pressure (ea) from Moderate Resolution Imaging Spectroradiometer (MODIS) data and upgrades Smiths (1966) methodology for estimating ea. The proposed new algorithm for calculating ea was evaluated against in situ measurements at 119 validation sites in China for 2 months in 2013. The mean absolute error (MAE) and root-mean-square error (RMSE) were less than 0.25 kPa and 0.33 kPa, respectively. The near-surface air temperature (Ta), which is an important input data for calculating VPD, was estimated from satellite-retrieved land surface temperature, and had an RMSE of less than 2.5 K. The estimated VPD values were validated with ground observation data from the Heihe River Basin for 5 months in 2012 and for all of China for August 2013. A coefficient of determination (R2) of 0.912, MAE of 0.27 kPa, and RMSE value of 0.32 kPa were achieved for the 2012 test data, and corresponding values of 0.88, 0.278 kPa, and 0.367 kPa for the 2013 test data. These results are promising, especially considering the comparatively high spatial resolution (1 km) of the VPD map estimated from the satellite data. Potential applications include global evapotranspiration estimation, fire warning, and vegetation analysis.

An Improved Approach for Estimating Daily Net Radiation over the Heihe River Basin

Net radiation plays an essential role in determining the thermal conditions of the Earth’s surface and is an important parameter for the study of land-surface processes and global climate change. In this paper, an improved satellite-based approach to estimate the daily net radiation is presented, in which sunshine duration were derived from the geostationary meteorological satellite (FY-2D) cloud classification product, the monthly empirical as and bs Angstrom coefficients for net shortwave radiation were calibrated by spatial fitting of the ground data from 1997 to 2006, and the daily net longwave radiation was calibrated with ground data from 2007 to 2010 over the Heihe River Basin in China. The estimated daily net radiation values were validated against ground data for 12 months in 2008 at four stations with different underlying surface types. The average coefficient of determination (R2) was 0.8489, and the averaged Nash-Sutcliffe equation (NSE) was 0.8356. The close agreement between the estimated daily net radiation and observations indicates that the proposed method is promising, especially given the comparison between the spatial distribution and the interpolation of sunshine duration. Potential applications include climate research, energy balance studies and the estimation of global evapotranspiration.

A Method to Estimate Sunshine Duration Using Cloud Classification Data from a Geostationary Meteorological Satellite (FY-2D) over the Heihe River Basin

Sunshine duration is an important variable that is widely used in atmospheric energy balance studies, analysis of the thermal loadings on buildings, climate research, and the evaluation of agricultural resources. In most cases, it is calculated using an interpolation method based on regional-scale meteorological data from field stations. Accurate values in the field are difficult to obtain without ground measurements. In this paper, a satellite-based method to estimate sunshine duration is introduced and applied over the Heihe River Basin. This method is based on hourly cloud classification product data from the FY-2D geostationary meteorological satellite (FY-2D). A new index—FY-2D cloud type sunshine factor—is proposed, and the Shuffled Complex Evolution Algorithm (SCE-UA) was used to calibrate sunshine factors from different coverage types based on ground measurement data from the Heihe River Basin in 2007. The estimated sunshine duration from the proposed new algorithm was validated with ground observation data for 12 months in 2008, and the spatial distribution was compared with the results of an interpolation method over the Heihe River Basin. The study demonstrates that geostationary satellite data can be used to successfully estimate sunshine duration. Potential applications include climate research, energy balance studies, and global estimations of evapotranspiration.

A Method for Estimating the Aerodynamic Roughness Length with NDVI and BRDF Signatures Using Multi-Temporal Proba-V Data

Aerodynamic roughness length is an important parameter for surface fluxes estimates. This paper developed an innovative method for estimation of aerodynamic roughness length (z0m) over farmland with a new vegetation index, the Hot-darkspot Vegetation Index (HDVI). To obtain this new index, the normalized-difference hot-darkspot index (NDHD) is introduced using a semi-empirical, kernel-driven bidirectional reflectance model with multi-temporal Proba-V 300-m top-of-canopy (TOC) reflectance products. A linear relationship between HDVI and z0m was found during the crop growth period. Wind profiles data from two field automatic weather station (AWS) were used to calibrate the model: one site is in Guantao County in Hai Basin, in which double-cropping systems and crop rotations with summer maize and winter wheat are implemented; the other is in the middle reach of the Heihe River Basin from the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) project, with the main crop of spring maize. The iterative algorithm based on Monin–Obukhov similarity theory is employed to calculate the field z0m from time series. Results show that the relationship between HDVI and z0m is more pronounced than that between NDVI and z0m for spring maize at Yingke site, with an R2 value that improved from 0.636 to 0.772. At Guantao site, HDVI also exhibits better performance than NDVI, with R2 increasing from 0.630 to 0.793 for summer maize and from 0.764 to 0.790 for winter wheat. HDVI can capture the impacts of crop residue on z0m, whereas NDVI cannot.

A Linear Relationship Between Temporal Multiband MODIS BRDF and Aerodynamic Roughness in HiWATER Wind Gradient Data

Aerodynamic roughness (AR) is an important parameter affecting land-atmosphere interactions. Previous studies on inversions based on bidirectional reflectance distribution functions (BRDFs) have focused on spatial analysis over desert and gobi, which are vegetation-free areas, due to the lack of wind gradient data for continuous time periods over vegetated surfaces. This study uses meteorological gradient data from a new long-term site that is supported by the Heihe Watershed Allied Telemetry Experimental Research project and is located in an irrigated farmland area in the Heihe River Basin of northwestern China. These data are used to calculate a field AR time series over maize using an iterative computation method based on Monin-Obukhov similarity theory. A linear relationship is demonstrated between the field AR and the BRDF parameters derived from multiband Moderate Resolution Imaging Spectroradiometer data. The correlation analysis for the near-infrared and shortwave bands reveals R2 values of 0.8739 and 0.8833, respectively; however, R2 is only 0.0146 for the visible band. Various band combinations do not improve the outcome. Thus, the near-infrared and shortwave parameters have the potential to be used to infer AR and its related evapotranspiration at more extensive temporal and spatial scales.

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

Evapotranspiration (ET) is an important component of the eco-hydrological process. Comprehensive analyses of ET change at different spatial and temporal scales can enhance the understanding of hydrological processes and improve water resource management. In this study, monthly ET data and meteorological data from 57 meteorological stations between 2000 and 2014 were used to study the spatiotemporal changes in actual ET and the associated causes in the Hai Basin. A spatial analysis was performed in GIS to explore the spatial pattern of ET in the basin, while parametric t-test and nonparametric Mann-Kendall test methods were used to analyze the temporal characteristics of interannual and annual ET. The primary causes of the spatiotemporal variations were partly explained by detrended fluctuation analysis. The results were as follows: (i) generally, ET increased from northwest to southeast across the basin, with significant differences in ET due to the heterogeneous landscape. Notably, the ET of water bodies was highest, followed by those of paddy fields, forests, cropland, brush, grassland and settlement; (ii) from 2000 to 2014, annual ET exhibited an increasing trend of 3.7 mm per year across the basin, implying that the excessive utilization of water resources had not been alleviated and the water resource crisis worsened; (iii) changes in vegetation coverage, wind speed and air pressure were the major factors that influenced interannual ET trends. Temperature and NDVI largely explained the increases in ET in 2014 and can be used as indicators to evaluate annual ET and provide early warning for associated issues.

Spatial-temporal change analysis of evapotranspiration in the Heihe River Basin

Evapotranspiration (ET) is one important component of hydrological process. It is also a limited factor for ecological environment conservation. The unreasonable utilization of water resources resulted in many problems in the Heihe River Basin, such as the over exploited of water resources, especial the ground water, the river flow decrease, land degradation. A correct understanding of the water consumption characteristics is undoubtedly a base of achieving the sustainable development of society, economy, and improving the eco-environment. In this paper, the time series of ET data estimated by ETWatch model which had been validated for different landscapes during the period of 2000-2010, were analyzed in spatial and temporal scales. The deviation of annual ET estimated by ETWatch with the observation ET data from eddy covariance system (EC) in the four observation stations of the basin was in the range of 5-8%. The conversion of land use type had a great impact on total water consumption across the basin due to lower variance of ET for three vegetation types. Base on the correlation analysis of climate factors and ET, there were apparent impact on ET in the upstream and midstream, but not in the downstream because of complicated human activities. The significant relations between temperature and ET (R=0.842~0.941), and between precipitation and ET (R=0.582~0.840), indicated that these two climate parameters were key influence factors on ET for grass land; The soil water storage was likely another influence factor on ET for the forest besides the temperature which had close relations with ET (R2=0.617~0.822). The spatial-temporal change analysis of ET and driven factors can be contributed to better understanding the eco-hydrological effect of the specific forest in Qilian Mountains.

The improved ET calculation for semiarid region based on an innovative aerodynamic roughness inversion method using multi-source remote sensing data

The aerodynamic roughness is one of the major parameters in describing the turbulent exchange process between terrestrial and atmosphere. Remote Sensing is recognized as an effective way to inverse this parameter at the regional scale. However, in the long time the inversion method is either dependent on the lookup table for different land covers or the Normalized Difference Vegetation Index (NDVI) factor only, which plays a very limited role in describing the spatial heterogeneity of this parameter and the evapotranspiration (ET) for different land covers. In fact, the aerodynamic roughness is influenced by different factors at the same time, including the roughness unit for hard surfaces, the vegetation dynamic growth and the undulating terrain. Therefore, this paper aims at developing an innovative aerodynamic roughness inversion method based on multi-source remote sensing data in a semiarid region, within the upper and middle reaches of Heihe River Basin. The radar backscattering coefficient was used to inverse the micro-relief of the hard surface. The NDVI was utilized to reflect the dynamic change of vegetated surface. Finally, the slope extracted from SRTM DEM (Shuttle Radar Topography Mission Digital Elevation Model) was used to correct terrain influence. The inversed aerodynamic roughness was imported into ETWatch system to validate the availability. The inversed and tested results show it plays a significant role in improving the spatial heterogeneity of the aerodynamic roughness and related ET for the experimental site.