Comparison and analysis of bare soil evaporation models combined with ASTER data in Heihe River Basin

AbstractBased on ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) remote sensing data, bare soil evaporation was estimated with the Penman-Monteith model, the Priestley-Taylor model, and the aerodynamics model. Evaporation estimated by each of the three models was compared with actual evaporation, and error sources of the three models were analyzed. The mean absolute relative error was 9% for the Penman-Monteith model, 14% for the Priestley-Taylor model, and 32% for the aerodynamics model; the Penman-Monteith model was the best of these three models for estimating bare soil evaporation. The error source of the Penman-Monteith model is the neglect of the advection estimation. The error source of the Priestley-Taylor model is the simplification of the component of aerodynamics as 0.72 times the net radiation. The error source of the aerodynamics model is the difference of vapor pressure and neglect of the radiometric component. The spatial distribution of bare soil evaporation is evident, and its main factors are soil water content and elevation

Seasonality of the Transpiration Fraction and Its Controls Across Typical Ecosystems Within the Heihe River Basin

Understanding the seasonality of the transpiration fraction (T/ET) of total terrestrial evapotranspiration (ET) is vital for coupling ecological and hydrological systems and quantifying the heterogeneity among various ecosystems. In this study, a two‐source model was used to estimate T/ET in five ecosystems over the Heihe River Basin. In situ measurements of daily energy flux, sap flow, and surface soil temperature were compared with model outputs for 2014 and 2015. Agreement between model predictions and observations demonstrates good performance in capturing the ecosystem seasonality of T/ET. In addition, sensitivity analysis indicated that the model is insensitive to errors in measured input variables and parameters. T/ET among the five sites showed only slight interannual fluctuations while exhibited significant seasonality. All the ecosystems presented a single‐peak trend, reaching the maximum value in July and fluctuating day to day. During the growing season, average T/ET was the highest for the cropland ecosystem (0.80 ± 0.13), followed by the alpine meadow ecosystem (0.79 ± 0.12), the desert riparian forest Populus euphratica (0.67 ± 0.07), the Tamarix ramosissima Ledeb desert riparian shrub ecosystem (0.67 ± 0.06), and the alpine swamp meadow (0.55 ± 0.23). Leaf area index exerted a first‐order control on T/ET and showed divergence among the five ecosystems because of different vegetation dynamics and environmental conditions (e.g., water availability or vapor pressure deficits). This study quantified transpiration fraction across diverse ecosystems within the same water basin and emphasized the biotic controls on the seasonality of the transpiration fraction

Mapping Regional Turbulent Heat Fluxes via Assimilation of MODIS Land Surface Temperature Data into an Ensemble Kalman Smoother Framework

Estimation of turbulent heat fluxes via variational data assimilation (VDA) approaches has been the subject of several studies. The VDA approaches need an adjoint model that is difficult to derive. In this study, remotely sensed land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are assimilated into the heat diffusion equation within an ensemble Kalman smoother (EnKS) approach to estimate turbulent heat fluxes. The EnKS approach is tested in the Heihe River Basin (HRB) in northwest China. The results show that the EnKS approach can estimate turbulent heat fluxes by assimilating low temporal resolution LST data from MODIS. The findings indicate that the EnKS approach performs fairly well in various hydrological and vegetative conditions. The estimated sensible (H) and latent (LE) heat fluxes are compared with the corresponding observations from large aperture scintillometer systems at three sites (namely, Arou, Daman, and Sidaoqiao) in the HRB. The turbulent heat flux estimates from EnKS agree reasonably well with the observations, and are comparable to those of the VDA approach. The EnKS approach also provides statistical information on the H and LE estimates. It is found that the uncertainties of H and LE estimates are higher over wet and/or densely vegetated areas (grassland and forest) compared to the dry and/or slightly vegetated areas (cropland, shrubland, and barren land)

Diurnal cycle of surface energy fluxes in high mountain terrain: high‐resolution fully coupled atmosphere‐hydrology modelling and impact of lateral flow

Water and energy fluxes are inextricably interlinked within the interface of the land surface and the atmosphere. In the regional earth system models, the lower boundary parameterization of land surface neglects lateral hydrological processes, which may inadequately depict the surface water and energy fluxes variations, thus affecting the simulated atmospheric system through land-atmosphere feedbacks. Therefore, the main objective of this study is to evaluate the hydrologically enhanced regional climate modelling in order to represent the diurnal cycle of surface energy fluxes in high spatial and temporal resolution. In this study, the Weather Research and Forecasting model (WRF) and coupled WRF Hydrological modelling system (WRF-Hydro) are applied in a high alpine catchment in Northeastern Tibetan Plateau, the headwater area of the Heihe River. By evaluating and intercomparing model results by both models, the role of lateral flow processes on the surface energy fluxes dynamics is investigated. The model evaluations suggest that both WRF and coupled WRF-Hydro reasonably represent the diurnal variations of the near-surface meteorological fields, surface energy fluxes and hourly partitioning of available energy. By incorporating additional lateral flow processes, the coupled WRF-Hydro simulates higher surface soil moisture over the mountainous area, resulting in increased latent heat flux and decreased sensible heat flux of around 20–50 W/m2 in their diurnal peak values during summertime, although the net radiation and ground heat fluxes remain almost unchanged. The simulation results show that the diurnal cycle of surface energy fluxes follows the local terrain and vegetation features. This highlights the importance of consideration of lateral flow processes over areas with heterogeneous terrain and land surfaces

Diurnal cycle of surface energy fluxes in high mountain terrain: High-resolution fully coupled atmosphere-hydrology modelling and impact of lateral flow

Water and energy fluxes are inextricably interlinked within the interface of the land surface and the atmosphere. In the regional earth system models, the lower boundary parameterization of land surface neglects lateral hydrological processes, which may inadequately depict the surface water and energy fluxes variations, thus affecting the simulated atmospheric system through land-atmosphere feedbacks. Therefore, the main objective of this study is to evaluate the hydrologically enhanced regional climate modelling in order to represent the diurnal cycle of surface energy fluxes in high spatial and temporal resolution. In this study, the Weather Research and Forecasting model (WRF) and coupled WRF Hydrological modelling system (WRF-Hydro) are applied in a high alpine catchment in Northeastern Tibetan Plateau, the headwater area of the Heihe River. By evaluating and intercomparing model results by both models, the role of lateral flow processes on the surface energy fluxes dynamics is investigated. The model evaluations suggest that both WRF and coupled WRF-Hydro reasonably represent the diurnal variations of the near-surface meteorological fields, surface energy fluxes and hourly partitioning of available energy. By incorporating additional lateral flow processes, the coupled WRF-Hydro simulates higher surface soil moisture over the mountainous area, resulting in increased latent heat flux and decreased sensible heat flux of around 20–50 W/m2 in their diurnal peak values during summertime, although the net radiation and ground heat fluxes remain almost unchanged. The simulation results show that the diurnal cycle of surface energy fluxes follows the local terrain and vegetation features. This highlights the importance of consideration of lateral flow processes over areas with heterogeneous terrain and land surfaces

Ecohydrology in water-limited environment using quantitative remote sensing - the Heihe River basin (China) case

Water-limited environments exist on all continents of the globe and they cover more than 30% of the Earth’s land surface. The eco-environments of these regions tend to be fragile and they are changing in a dramatic way through processes like land desertification, shrinking of oases, groundwater depletion, and soil erosion. These are either human induced or results of a changing climate. Implications of these changes for both the regional hydrologic cycle and the vegetation have been documented. Since these changes occur over a wide range of scales in space and time, remote sensing methods are needed to monitor the land surface characteristics, to observe changes in vegetation and hydrological states, and to compare these with predictions from hydrological models. It is widely accepted that remote sensing methods offer the ability to acquire spatially continuous measurements over large areas. Remote sensing can also help to visualize complex processes because the spatial data can be captured regularly over time. China is one of several countries with large arid and semi-arid areas. The Heihe River basin, situated in the arid inland of northwestern China, is one of the areas severely affected by ecoenvironmental degradation and recovery. The problem of the degraded environment is due to overexploitation of surface and ground water leading to shrinking of oases, including the decline and death of natural vegetation, and the lowering of the groundwater table. Exhaustive (over-)use of water resources is the main cause of land degradation in the lower reaches of the basin, called the Ejina oasis. The whole Heihe River basin is therefore selected as study area in this thesis to analyze the long-term eco-environmental changes. What happens in this river basin is likely to have a growing influence on regional hydrological cycles, even affecting human life. Effective management of eco-environmental problems in this critical zone of water-limited conditions will provide scientific evidence for protecting and improving the eco-environment in these Chinese northwestern arid regions, eventually resulting in land improvement. Studies on quantifying the relationship between the vegetation and the water resources are a critical step in developing an ecohydrological approach to resources management in order to minimize environmental degradation. Remote sensing measurements can help us to better understand the effects of changes in water management on hydrological processes and their subsequent feedback to the eco-environment at the regional scale. Remote sensing methods can also provide information to quantify heterogeneity and change at a large scale. Therefore, the main objective of this thesis is to develop a methodology for the quantitative assessment of eco-environmental changes at a large scale in arid regions by integrating remote sensing methods in ecohydrological approaches. Chapter 1 outlines the significance of quantitative assessment of eco-environmental changes using remote sensing methods and applying them for ecohydrology in northwestern China, resulting in the specific research objectives of this thesis. Chapter 2 quantifies both the vertical and horizontal distribution of vegetation in the Qilian Mountains area, representing the upper reaches of the Heihe River basin, based on MODIS NDVI images from the year 2000 - 2006. Our analysis reveals that elevation and aspect are two important impact factors for the vertical distribution of vegetation in a mountainous area. The NDVI increases with the elevation and reaches a maximum value at a certain elevation threshold, and then decreases as the elevation increases beyond this threshold. The optimal vegetation growth is on the shady side of the mountains because of less evapotranspiration. The best combination of temperature and precipitation is assessed providing good conditions for vegetation growth. Chapter 3 presents an efficient method to estimate the regional annual evapotranspiration (ET) based on the SEBS algorithm (Surface Energy Balance System) in the Zhangye basin, representing the middle reaches of the Heihe River basin. The method proposed is a combination of the daily SEBS results and data collected by meteorological stations. The result shows that the annual ET increased gradually during the period 1990-2004 and the main impact factor on the long-term increase of annual ET was the vegetation change. The accuracy of the ET result is validated using a water balance for the whole watershed and the validation reveals that the SEBS algorithm can be used to effectively estimate annual ET in the Zhangye basin. Chapter 4 establishes the quantitative relationship between the runoff of the Heihe River and the long-term vegetation change of the Ejina oasis, located in the lower reaches of the Heihe River. In this part, two time periods are distinguished corresponding to before and after the implementation of a new water allocation scheme in the Heihe River basin. The GIMMS NDVI and MODIS NDVI data sets are used to quantify the long-term change of the oasis vegetation in the first period 1989-2002 and the second period 2000-2006, respectively. The vegetation change shows a decreasing trend from 1989 to 2002 and an increasing trend between 2000 and 2006. Good relation between the runoff of the river and the vegetation growth are found at both stages and the time lag of the observed hysteresis effect of the runoff of the river on the oasis vegetation is one year. In addition, the yearly smallest water amount which sustains the demand of the eco-environment of the Ejina area is estimated to be 4×108 m3 based on MODIS images. Chapter 5 explores a method to quantify the effect of the groundwater depth on the vegetation growth in the year 2000 in the oasis area by combining MODIS NDVI with groundwater observation data. The result demonstrates that the groundwater depth suitable for vegetation growth in this region ranges from 2.8 to 5 m, depending on species composition. Hardly any vegetation growth occurs when the groundwater depth is below 5 m because the rooting depth of the occurring species is limited and cannot maintain adequate water supplies to their canopies when the water depth is below 5 m. The situation changes after implementation of the new water allocation scheme since 2000. The mean NDVI increased and the annual conversion of bare land into vegetated land is about 38 km2 per year during the period 2000 – 2008. It reflects a potential recovery of the eco-environment of the Ejina area. Chapter 6 comprises the main conclusions and the outlook for possible improvements in future research. The main contribution of this study is the successful integration of remote sensing with ecohydrology in quantifying the relationship between water resources and vegetation occurrence at large scale. It provides a methodology to evaluate the long-term vegetation change and the water resources impact using remote sensing data in water-limited areas. The approach of vegetation dynamics, runoff and groundwater impacts presented in this thesis serves as a sound foundation for predicting the effects of future environmental changes. <br/

Evapotranspiration estimation using Landsat-8 data with a two-layer framework

This work was partially supported by the National Natural Science Foundation of China (41401042), National Key Basic Research Program of China (973 Program) (Grant No. 2015CB452701) and National Natural Science Foundation of China (Grant Nos. 41571019 and 41371043).Peer reviewedproo

Spatial representativeness and uncertainty of eddy covariance carbon flux measurements for upscaling net ecosystem productivity to the grid scale

Eddy covariance (EC) measurements are often used to validate net ecosystem productivity (NEP) estimated from satellite remote sensing data and biogeochemical models. However, EC measurements represent an integrated flux over their footprint area, which usually differs from respective model grids or remote sensing pixels. Quantifying the uncertainties of scale mismatch associated with gridded flux estimates by upscaling single EC tower NEP measurements to the grid scale is an important but not yet fully investigated issue due to limited data availability as well as knowledge of flux variability at the grid scale. The Heihe Watershed Allied Telemetry Experimental Research (HiWATER) Multi-Scale Observation Experiment on Evapotranspiration (MUSOEXE) built a flux observation matrix that includes 17 EC towers within a 5 km × 5 km area in a heterogeneous agricultural landscape in northwestern China, providing an unprecedented opportunity to evaluate the uncertainty of upscaling due to spatial representative differences at the grid scale. Based on the HiWATER-MUSOEXE data, this study evaluated the spatial representativeness and uncertainty of EC CO2 flux measurements for upscaling to the grid scale using a scheme that combines a footprint model and a model-data fusion method. The results revealed the large spatial variability of gross primary productivity (GPP), ecosystem respiration (Re), and NEP within the study site during the growing season from 10 June to 14 September 2012. The variability of fluxes led to high variability in the representativeness of single EC towers for grid-scale NEP. The systematic underestimations of a single EC tower may reach 92(±11)%, 30(±11)%, and 165(±150)% and the overestimations may reach 25(±14)%, 20(±13)%, and 40(±33)% for GPP, Re, and NEP, respectively. This finding suggests that remotely sensed NEP at the global scale (e.g., MODIS products) should not be validated against single EC tower data in the case of heterogeneous surfaces. Any systematic bias should be addressed before upscaling EC data to grid scale. Otherwise, most of the systematic bias may be propagated to grid scale due to the scale dependence of model parameters. A systematic bias greater than 20% of the EC measurements can be corrected effectively using four indicators proposed in this study. These results will contribute to the understanding of spatial representativeness of EC towers within a heterogeneous landscape, to upscaling carbon fluxes from the footprint to the grid scale, to the selection of the location of EC towers, and to the reduction in the bias of NEP products by using an improved parameterization scheme of remote-sensing driven models, such as VPRM