Gaofeng Zhu

Heihe Watershed Allied Telemetry Experimental Research (HiWATER): Scientific Objectives and Experimental Design

A major research plan entitled “Integrated research on the ecohydrological process of the Heihe River Basin” was launched by the National Natural Science Foundation of China in 2010. One of the key aims of this research plan is to establish a research platform that integrates observation, data management, and model simulation to foster twenty-first-century watershed science in China. Based on the diverse needs of interdisciplinary studies within this research plan, a program called the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) was implemented. The overall objective of HiWATER is to improve the observability of hydrological and ecological processes, to build a world-class watershed observing system, and to enhance the applicability of remote sensing in integrated ecohydrological studies and water resource management at the basin scale. This paper introduces the background, scientific objectives, and experimental design of HiWATER. The instrumental setting and airborne mission plans a...

Seasonal fluctuations and temperature dependence in photosynthetic parameters and stomatal conductance at the leaf scale of Populus euphratica Oliv.

A combined model to simulate CO₂ and H₂O gas exchange at the leaf scale was parameterized using data obtained from in situ leaf-scale observations of diurnal and seasonal changes in CO₂ and H₂O gas exchange. The Farquhar et al.-type model of photosynthesis was parameterized by using the Bayesian approach and the Ball et al.-type stomatal conductance model was optimized using the linear least-squares procedure. The results show that the seasonal physiological changes in photosynthetic parameters (e.g., V(cmax25), J(max25), R(d25) and g(m25)) in the biochemical model of photosynthesis and m in the stomatal conductance model should be counted in estimating long-term CO₂ and H₂O gas exchange. Overall, the coupled model successfully reproduced the observed response in net assimilation and transpiration rates.

Estimation of parameters of a biochemically based model of photosynthesis using a genetic algorithm

Photosynthesis response to carbon dioxide concentration can provide data on a number of important parameters related to leaf physiology. The genetic algorithm (GA), which is a robust stochastic evolutionary computational algorithm inspired by both natural selection and natural genetics, is proposed to simultaneously estimate the parameters [including maximum carboxylation rate allowed by ribulose 1.5-bisphosphate carboxylase/oxygenase (Rubisco) carboxylation rate (V(cmax)), potential light-saturated electron transport rate (J(max)), triose-phosphate utilization (TPU), leaf dark respiration in the light (R(d)) and mesophyll conductance (g(m))] of the photosynthesis models presented by Farquhar, von Caemmerer and Berry, and Ethier and Livingston. The results show that by properly constraining the parameter bounds the GA-based estimate methods can effectively and efficiently obtain globally (or, at least near globally) optimal solutions, which are as good as or better than those obtained by non-linear curve fitting methods used in previous studies. More complicated problems such as taking the g(m) variation response to CO(2) into account can be easily formulated and solved by using GA. The influence of the crossover probability (P(c)), mutation probability (P(m)), population size and generation on the performance of GA was also investigated.

Identification and Evolution of Groundwater Chemistry in the Ejin Sub-Basin of the Heihe River, Northwest China

Hydro-chemical characteristics of groundwater and their changes as affected by human activities were studied in the Ejin Sub-Basin of the Inner Mongolia Autonomous Region, China, to understand the groundwater evolution, to identify the predominant geochemical processes taking place along the horizontal groundwater flow path, and to characterize anthropogenic factors affecting the groundwater environment based on previous data. The concentrations of major ions and total dissolved solids (TDS) in the groundwater showed a great variation, with 62.5% of the samples being brackish (TDS≥1000 mg L^(-1)). The groundwater system showed a gradual hydro-chemical zonation composed of Na(superscript +)-HCO(superscript – subscript 3), Na(superscript +)-Mg(superscript 2+)-SO(superscript 2 subscript 4)-Cl(superscript -), and Na(superscript +)-Cl(superscript -). The relationships among the dissolved species allowed identification of the origin of solutes and the processes that generated the observed water compositions. The dissolution of halite, dolomite, and gypsum explained, in part, the presence of Na(superscript +), K(superscript +), Cl(superscript -), SO(superscript 2- subscript 4), and Ca(superscript 2+), but other processes, such as mixing, Na(superscript +) exchange for Ca(superscript 2+) and Mg(superscript 2+), and calcite precipitation also contributed to the composition of water. Human activity, in particular large-scale water resources development associated with dramatic population growth in the last 50 years, has led to tremendous changes in the groundwater regime, which reflected in surface water runoff change, decline of groundwater table and degeneration of surface water and groundwater quality. Solving these largely anthropogenic problems requires concerted, massive and long-term efforts.

Emerging role of wetland methane emissions in driving 21st century climate change

Significance Conventional greenhouse gas mitigation policies ignore the role of global wetlands in emitting methane (CH4) from feedbacks associated with changing climate. Here we investigate wetland feedbacks and whether, and to what degree, wetlands will exceed anthropogenic 21st century CH4 emissions using an ensemble of climate projections and a biogeochemical methane model with dynamic wetland area and permafrost. Our results reveal an emerging contribution of global wetland CH4 emissions due to processes mainly related to the sensitivity of methane emissions to temperature and changing global wetland area. We highlight that climate-change and wetland CH4 feedbacks to radiative forcing are an important component of climate change and should be represented in policies aiming to mitigate global warming below 2°C. Wetland methane (CH4) emissions are the largest natural source in the global CH4 budget, contributing to roughly one third of total natural and anthropogenic emissions. As the second most important anthropogenic greenhouse gas in the atmosphere after CO2, CH4 is strongly associated with climate feedbacks. However, due to the paucity of data, wetland CH4 feedbacks were not fully assessed in the Intergovernmental Panel on Climate Change Fifth Assessment Report. The degree to which future expansion of wetlands and CH4 emissions will evolve and consequently drive climate feedbacks is thus a question of major concern. Here we present an ensemble estimate of wetland CH4 emissions driven by 38 general circulation models for the 21st century. We find that climate change-induced increases in boreal wetland extent and temperature-driven increases in tropical CH4 emissions will dominate anthropogenic CH4 emissions by 38 to 56% toward the end of the 21st century under the Representative Concentration Pathway (RCP2.6). Depending on scenarios, wetland CH4 feedbacks translate to an increase in additional global mean radiative forcing of 0.04 W·m−2 to 0.19 W·m−2 by the end of the 21st century. Under the “worst-case” RCP8.5 scenario, with no climate mitigation, boreal CH4 emissions are enhanced by 18.05 Tg to 41.69 Tg, due to thawing of inundated areas during the cold season (December to May) and rising temperature, while tropical CH4 emissions accelerate with a total increment of 48.36 Tg to 87.37 Tg by 2099. Our results suggest that climate mitigation policies must consider mitigation of wetland CH4 feedbacks to maintain average global warming below 2 °C.

Parameter sensitivity analysis and optimization for a satellite‐based evapotranspiration model across multiple sites using Moderate Resolution Imaging Spectroradiometer and flux data

Global and regional estimates of daily evapotranspiration are essential to our understanding of the hydrologic cycle and climate change. In this study, we selected the radiation-based Priestly-Taylor Jet Propulsion Laboratory (PT-JPL) model and assessed it at a daily time scale by using 44 flux towers. These towers distributed in a wide range of ecological systems: croplands, deciduous broadleaf forest, evergreen broadleaf forest, evergreen needleleaf forest, grasslands, mixed forests, savannas, and shrublands. A regional land surface evapotranspiration model with a relatively simple structure, the PT-JPL model largely uses ecophysiologically-based formulation and parameters to relate potential evapotranspiration to actual evapotranspiration. The results using the original model indicate that the model always overestimates evapotranspiration in arid regions. This likely results from the misrepresentation of water limitation and energy partition in the model. By analyzing physiological processes and determining the sensitive parameters, we identified a series of parameter sets that can increase model performance. The model with optimized parameters showed better performance (R2 = 0.2–0.87; Nash-Sutcliffe efficiency (NSE) = 0.1–0.87) at each site than the original model (R2 = 0.19–0.87; NSE = −12.14–0.85). The results of the optimization indicated that the parameter β (water control of soil evaporation) was much lower in arid regions than in relatively humid regions. Furthermore, the optimized value of parameter m1 (plant control of canopy transpiration) was mostly between 1 to 1.3, slightly lower than the original value. Also, the optimized parameter Topt correlated well to the actual environmental temperature at each site. We suggest that using optimized parameters with the PT-JPL model could provide an efficient way to improve the model performance.

A comparison of two photosynthesis parameterization schemes for an alpine meadow site on the Qinghai-Tibetan Plateau

Photosynthesis is a very important sub-process in the carbon cycle and is a crucial sub-modular function in carbon cycle models. In this study, two typical photosynthesis parameterization schemes were compared based on meteorological and eddy covariance (EC) observations at an alpine meadow site. The photosynthesis model parameters were estimated using the Markov Chain Monte Carlo (MCMC) method. The results indicated that the Farquhar-conductance coupled model better predicted the gross primary production (GPP) for the alpine meadow ecosystem at an hourly time scale than the light use efficiency (LUE) model even though the Farquhar-conductance coupled model has a lower computational efficiency than the LUE model. Compared to the Ball–Woodrow–Berry (BWB) stomatal conductance model, coupling the Farquhar model with the Leuning stomatal conductance model more accurately simulated GPP.

A hierarchical Bayesian approach for multi-site optimization of a satellite-based evapotranspiration model

Key Laboratory of Eco‐hydrology of Inland River Basin (CAS), Northwest Institute of Eco‐ Environment and Resources, CAS, Lanzhou, China Laboratory of Western Chinas Environmental Systems (Ministry of Education), Lanzhou University, Lanzhou, China School of Environmental Studies, China University of Geosciences, Wuhan, China Correspondence Gaofeng Zhu, Laboratory of Western Chinas Environmental Systems (Ministry of Education), Lanzhou University, Lanzhou 730000, China. Email: zhugf@lzu.edu.cn Funding information National Key R & D Program of China, Grant/ Award Number: 2016YFC0501002; National Natural Science Foundation of China, Grant/ Award Numbers: 41571016 and 41871078