Huade Guan

Mountain‐Block Hydrology and Mountain‐Front Recharge

In semiarid climates, a significant component of recharge to basin aquifers occurs along the mountain front. Traditionally called “mountain-front recharge” (MFR), this process has been treated by modelers of basins as a boundary condition. In general, mountain-front recharge estimates are based on the general precipitation characteristics of the mountain (as estimated, e.g., by the chloride mass balance and water balance methods), or by calibration of a basin groundwater model. These methods avoid altogether the complexities of the hydrologic system above the mountain front, or at best consider only traditional runoff process. Consequently hydrology above the mountain front is an area ripe for significant scientific advancement. A complete view would consider the entire mountain block system and examine hydrologic processes from the slope of the highest peak to the depth of the deepest circulating groundwater. Important aspects above the mountain front include the partitioning of rainfall and snowmelt into vegetation-controlled evapotranspiration, surface runoff, and deep infiltration through bedrock, especially its fractures and faults. Focused flow along mountain stream channels and the diffuse movement of groundwater through the underlying mountain block would both be considered. This paper first defines some key terms, then reviews methods of studying MFR in arid and semiarid regions, discusses hydrological processes in the mountain block, and finally addresses some of the basic questions raised by the new mountain-block hydrology approach, as well as future directions for mountain-block hydrology research.

Geostatistical Mapping of Mountain Precipitation Incorporating Autosearched Effects of Terrain and Climatic Characteristics

Hydrologic and ecologic studies in mountainous terrain are sensitive to the temporal and spatial distribution of precipitation. In this study a geostatistical model, Auto-Searched Orographic and Atmospheric Effects Detrended Kriging (ASOADeK), is introduced to map mountain precipitation using only precipitation gauge data. The ASOADeK model considers both precipitation spatial covariance and orographic and atmospheric effects in estimating precipitation distribution. The model employs gauge data and a multivariate linear regression approach to autosearch regional and local climatic settings (i.e., infer the spatial gradient in atmospheric moisture distribution and the effective moisture flux direction), and local orographic effects (the effective terrain elevation and aspect). The observed gauge precipitation data are then spatially detrended by the autosearched regression surface. The spatially detrended gauge data are further interpolated by ordinary kriging to generate a residual precipitation surface. The precipitation map is then constructed by adding the regression surface to the kriged residual surface. The ASOADeK model was applied to map monthly precipitation for a mountainous area in semiarid northern New Mexico. The effective moisture flux directions and spatial moisture trends identified by the optimal multiple linear regressions, using only gauge data, agree with the regional climate setting. When compared to a common precipitation mapping product [Precipitation-elevation Regression on Independent Slopes Model (PRISM)], the ASOADeK summer precipitation maps of the study area agree well with the PRISM estimates, and with higher spatial resolution. The ASOADeK winter maps improve upon PRISM estimates. ASOADeK gives better estimates than precipitation kriging and precipitation-elevation cokriging because it considers orographic and atmospheric effects more completely.

Variation in performance of surfactant loading and resulting nitrate removal among four selected natural zeolites

Surfactant modified zeolites (SMZs) have the capacity to target various types of water contaminants at relatively low cost and thus are being increasingly considered for use in improving water quality. It is important to know the surfactant loading performance of a zeolite before it is put into application. In this work we compare the loading capacity of a surfactant, hexadecyltrimethylammonium bromide (HDTMA-Br), onto four natural zeolites obtained from specific locations in the USA, Croatia, China, and Australia. The surfactant loading is examined using thermogravimetric analysis (TGA), Fourier transform infrared (FT-IR) spectroscopy, and Raman spectroscopy. We then compare the resulting SMZs performance in removing nitrate from water. Results show that TGA is useful to determine the HDTMA loading capacity on natural zeolites. It is also useful to distinguish between a HDTMA bi-layer and a HDTMA mono-layer on the SMZ surface, which has not been previously reported in the literature. TGA results infer that HDTMA (bi-layer) loading decreases in the order of US zeolite>Croatian zeolite>Chinese zeolite>Australian zeolite. This order of loading explains variation in performance of nitrate removal between the four SMZs. The SMZs remove 8-18 times more nitrate than the raw zeolites. SMZs prepared from the selected US and Croatian zeolites were more efficient in nitrate removal than the two zeolites commercially obtained from Australia and China.

Changes in autumn vegetation dormancy onset date and the climate controls across temperate ecosystems in China from 1982 to 2010

Vegetation phenology is a sensitive indicator of the dynamic response of terrestrial ecosystems to climate change. In this study, the spatiotemporal pattern of vegetation dormancy onset date (DOD) and its climate controls over temperate China were examined by analysing the satellite-derived normalized difference vegetation index and concurrent climate data from 1982 to 2010. Results show that preseason (May through October) air temperature is the primary climatic control of the DOD spatial pattern across temperate China, whereas preseason cumulative precipitation is dominantly associated with the DOD spatial pattern in relatively cold regions. Temporally, the average DOD over Chinas temperate ecosystems has delayed by 0.13 days per year during the past three decades. However, the delay trends are not continuous throughout the 29-year period. The DOD experienced the largest delay during the 1980s, but the delay trend slowed down or even reversed during the 1990s and 2000s. Our results also show that interannual variations in DOD are most significantly related with preseason mean temperature in most ecosystems, except for the desert ecosystem for which the variations in DOD are mainly regulated by preseason cumulative precipitation. Moreover, temperature also determines the spatial pattern of temperature sensitivity of DOD, which became significantly lower as temperature increased. On the other hand, the temperature sensitivity of DOD increases with increasing precipitation, especially in relatively dry areas (e.g. temperate grassland). This finding stresses the importance of hydrological control on the response of autumn phenology to changes in temperature, which must be accounted in current temperature-driven phenological models.

GRACE satellite observed hydrological controls on interannual and seasonal variability in surface greenness over mainland Australia

Water-limited ecosystems, covering ~50% of the global land, are controlled primarily by hydrologic factors. Because climate change is predicted to markedly alter current hydroclimatic conditions later this century, a better hydrological indicator of ecosystem performance is warranted to improve understanding of hydrological controls on vegetation and to predict changes in the future. Here we show that the observed total water storage anomaly (TWSA) from the Gravity Recovery and Climate Experiment (GRACE) can serve as this indicator. Using the Australian mainland as a case study, where ecosystems are generally water limited, we found that GRACE-observed TWSA can explain changes in surface greenness (as measured by the normalized difference vegetation index, NDVI) both interannually and seasonally. In addition, we found that TWSA shows a significant decreasing trend during the millennium drought from 1997 through 2009 in the region. However, decline in annual mean NDVI during the same period was mainly driven by decline in annual minimum monthly NDVI, whereas annual maximum monthly NDVI remained relatively constant across biomes. This phenomenon reveals an intrinsic sensitivity of ecosystems to water availability that drought-induced reductions in surface greenness are more likely expressed through its influence on vegetation during lower NDVI months, whereas ecosystem activities tend to recover to their maximum level during periods when the combined environmental conditions favor vegetation growth within a year despite the context of the prolonged drought.

Comparison of three dual‐source remote sensing evapotranspiration models during the MUSOEXE‐12 campaign: Revisit of model physics

Various remote sensing-based terrestrial evapotranspiration (ET) models have been developed during the past four decades. These models vary in conceptual and mathematical representations of the physics, consequently leading to different performances. Examination of uncertainties associated with limitations in model physics will be useful for model selection and improvement. Here, three dual-source remote sensing ET models (i.e., the Hybrid dual-source scheme and Trapezoid framework-based ET Model (HTEM), the Two-Source Energy Balance (TSEB) model, and the MOD16 ET algorithm) using ASTER images were compared during the MUSOEXE-12 campaign in the Heihe River Basin in Northwest China, aiming to better understand the differences in model physics that potentially lead to differences in model performance. Model results were first compared against observations from a dense network of eddy covariance towers and isotope-based evaporation (E) and transpiration (T) partitioning. Results show that HTEM outperformed the other two models in simulating ET and its partitioning, whereas MOD16 performed worst (i.e., ET root-mean-square errors are 42.3 W/m2 (HTEM), 49.8 W/m2 (TSEB), and 95.3 W/m2 (MOD16)). On to model limitations, HTEM tends to underestimate ET under high advection due mostly to the underestimation of temperatures for the wet edge in its trapezoidal space. For TSEB, large uncertainties occur in determining the initial Priestley-Taylor coefficient and the iteration procedure for ET partitioning, leading to overestimation/underestimation of T/E in most cases, particularly over sparse vegetation. Primary use of meteorological data for MOD16 does not effectively capture the soil moisture restriction on ET, and therefore results in unreasonable spatial ET patterns.

Contrasting responses of water use efficiency to drought across global terrestrial ecosystems

Drought is an intermittent disturbance of the water cycle that profoundly affects the terrestrial carbon cycle. However, the response of the coupled water and carbon cycles to drought and the underlying mechanisms remain unclear. Here we provide the first global synthesis of the drought effect on ecosystem water use efficiency (WUE = gross primary production (GPP)/evapotranspiration (ET)). Using two observational WUE datasets (i.e., eddy-covariance measurements at 95 sites (526 site-years) and global gridded diagnostic modelling based on existing observation and a data-adaptive machine learning approach), we find a contrasting response of WUE to drought between arid (WUE increases with drought) and semi-arid/sub-humid ecosystems (WUE decreases with drought), which is attributed to different sensitivities of ecosystem processes to changes in hydro-climatic conditions. WUE variability in arid ecosystems is primarily controlled by physical processes (i.e., evaporation), whereas WUE variability in semi-arid/sub-humid regions is mostly regulated by biological processes (i.e., assimilation). We also find that shifts in hydro-climatic conditions over years would intensify the drought effect on WUE. Our findings suggest that future drought events, when coupled with an increase in climate variability, will bring further threats to semi-arid/sub-humid ecosystems and potentially result in biome reorganization, starting with low-productivity and high water-sensitivity grassland.

Search parameters for the remote detection of extraterrestrial life

Abstract Direct consequences of biological activity (biosignatures) and alterations of the geological environment due to biological processes (geosignatures) are currently known only for the planet Earth. However, geoindicators remotely detectable by robotic technology have revealed a number of sites in the solar system where conditions compatible with the support of life may exist. By focusing on a search for energy gradients, complex chemistry, liquids that may act as solvents, atmospheres, and indicators of geological differentiation, robotic exploration of the solar system and beyond should lead to fruitful targets in the search for extraterrestrial life. An analysis of all major solar system bodies for these parameters suggests that Mars, Titan, and the Galilean satellites should be given the highest priority in the search for extraterrestrial life in our solar system. Extending them to other bodies in the solar system, however, draws attention to Io, Triton, Titania, Enceladus, and Iapetus, among others, as worthy of greater attention.

Optimization of canopy conductance models from concurrent measurements of sap flow and stem water potential on Drooping Sheoak in South Australia

Canopy conductance (gc) is a critical component in hydrological modeling for transpiration estimate. It is often formulated as functions of environmental variables. These functions are climate and vegetation specific. Thus, it is important to determine the appropriate functions in gc models and corresponding parameter values for a specific environment. In this study, sap flow, stem water potential, and microclimatic variables were measured for three Drooping Sheoak (Allocasuarina verticillata) trees in year 2011, 2012, and 2014. Canopy conductance was calculated from the inversed Penman-Monteith (PM) equation, which was then used to examine 36 gc models that comprise different response functions. Parameters were optimized using the DiffeRential Evolution Adaptive Metropolis (DREAM) model based on a training data set in 2012. Use of proper predawn stem water potential function, vapor pressure deficit function, and temperature function improves model performance significantly, while no pronounced difference is observed between models that differ in solar radiation functions. The best model gives a correlation coefficient of 0.97, and root-mean-square error of 0.0006 m/s in comparison to the PM-calculated gc. The optimized temperature function shows different characteristics from its counterparts in other similar studies. This is likely due to strong interdependence between air temperature and vapor pressure deficit in the study area or Sheoak tree physiology. Supported by the measurements and optimization results, we suggest that the effects of air temperature and vapor pressure deficit on canopy conductance should be represented together.

Effects of pH and Geological Medium on Bacteriophage MS2 Transport in a Model Aquifer

A 1-meter long model aquifer has been used to simulate the effects of pH on the fate and transport of bacteriophage MS2 in a shallow groundwater system. The results show that transport of MS2 is sensitive to the pH of groundwater and the isoelectric points of minerals in the groundwater medium. At a slightly alkaline groundwater pH, transport rates of the MS2 bacteriophage were greater than that of a conservative tracer, bromide. Greater transport rates were interpreted as a preferential pathway effect due to the larger size of MS2. Pore exclusion and straining may also have contributed to the faster transport of MS2. At a neutral pH similar transport rates for both MS2 and the conservative tracer were observed. At a slightly acidic pH, however, the MS2 breakthrough concentration was trailing the breakthrough of the conservative tracer that was attributed to the pronounced effect of reversible adsorption at lower pH values. Acidic conditions also increased greatly the effect of irreversible sorption. The effect of increased reversible and irreversible sorption of MS2 at lower pHs can be explained with the Derjaguin-Landau-Verwey-Overbeek (DLVO) potential energy profile. Irreversible sorption corresponds to the primary energy minimum of MS2-feldspar attraction, while reversible sorption corresponds to the secondary minimum of MS2-quartz attraction that can be overcome by Brownian motion.