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The stable oxygen isotope composition of precipitation (δ18Op) in southern China is considered as a valuable proxy of climatic conditions. However, their interpretations have been controversial. In this study, based on the observed and simulated data (isoGSM2) on oxygen isotope composition of precipitation, the linkage between summer precipitation (P) and δ18Op in the Dongting Lake basin and their possible influencing factors were investigated. The results indicate that the interannual variation of summer δ18Op is consistent with that of annual δ18Op. They both show a significantly negative correlation with the summer P, suggesting that the stable isotope composition in precipitation may be considered as a proxy of summer precipitation in the Dongting Lake basin. Statistically, the amount effect and circulation effect are significant in the isotope composition of precipitation in the basin. Based on either the observed data in Changsha or the simulated data for the basin, the local amount effect appears more important than large‐scale circulation for δ18Op during extreme summers. These results can potentially improve the reconstruction of paleoclimate in the East Asian monsoon region. Further study is needed to determine the contribution of local and large‐scale factors to the oxygen isotope composition of precipitation and to quantify the integral rainout along the moisture transporting paths. [ABSTRACT FROM AUTHOR]

Water ages in plant transpiration reveal important processes of water dynamics in soil‐plant‐atmosphere continuum, which is regulated by water variability and availability in both precipitation inputs and root zone. However, the impacts of climate patterns and rooting depth on water age dynamics in transpiration are inadequately investigated. In this study, variations in root‐zone water replenishment are estimated based on stable isotope compositions of precipitation and plant xylem water, and a piecewise linear mixing water age model is employed to quantify water ages in plant transpiration under five different climates. The results show that water ages in transpiration are very dynamic in all climates with a range between 1 and 229 days. Water replenishments in the root‐zone reveal whether and how much precipitation enters the root zone. Climate patterns control median (mean) water age in plant transpiration but modified by rooting depth. In wet climates, plants mainly rely on water source that originates from precipitation in the current month (accounting for about 60% on average of their water sources), while plants in dry climates largely rely on water source that originates from precipitation fallen on previous months/seasons. These indicate that climate has profound impacts on plant water source by regulating precipitation inputs, root zone water storage and residence time, and evapotranspiration. Despite the limitations of this study, our study provides an alternative way to reveal the precipitation partitioning in root‐zone and seasonal changes in plant water use of precipitation, which highlights different vegetation responses to water variability between climate types. Key Points: Stable isotopes reveal how precipitation is partitioned (replenishment/bypass) in the root‐zoneWater ages in plant transpiration are estimated as a function of root‐zone water replenishmentClimate patterns and rooting depth control median (mean) water age in plant transpiration [ABSTRACT FROM AUTHOR]

Australia, the driest inhabited continent, is prone to natural disasters, such as droughts, floods, bushfires, and heatwaves. Strong climate variability causes recurring threats to water supply, agriculture, and the environment. Improving our insight into changes in hydroclimatic patterns is required to provide useful information for society. Previous studies mainly focused on the causes of extreme wet or dry events in specific periods and their impacts on agriculture and ecosystems. An understanding of long‐term spatio‐temporal patterns of wetting and drying in Australia is still lacking. Here we show, based on analyses of Gravity Recovery and Climate Experiment satellite derived terrestrial water storage and extended datasets, that there are four consecutive periods of seesaw wetting and drying between eastern and western Australia in the past five decades. The seesaw phenomenon is characterized by eastern Australia gaining water, while western Australia is losing water, and vice versa. Strong La Niña induced continent‐wide wetting, resets this pattern, leaving each seesaw to last for 11 ± 5 years. We provide one possible mechanism related to vegetation response to climate variability and its feedback on hydrological processes to explain the seesaw pattern. The identified recurring seesaw pattern indicates that society would need to become more adaptive in managing forest, water, and disaster risks in the wake of a next strong La Niña induced continent‐wide wetting in Australia. Plain Language Summary: Here, we report for the first time a vegetation mediated seesaw wetting/drying phenomenon between eastern and western Australia. The seesaw phenomenon is characterized by eastern Australia gaining water, while western Australia is losing water, and vice versa. It is reset by strong La Niña induced continent‐wide wetting. The seesaw phase seems to depend on vegetation cover anomaly prior to the strong La Niña event, and can be explained by subsequent vegetation and soil moisture interactions. This finding provides society with valuable reference for managing forest, water, and disaster risks in the wake of a next strong La Niña induced continent‐wide wetting in Australia. Key Points: A seesaw wetting/drying phenomenon between eastern and western Australia is revealed for the first timeThis terrestrial water storage (TWS) seesaw pattern is reset by strong La Niña induced continent‐wide wettingThe TWS seesaws appear to be resulting from vegetation mediated hydrological responses to decadal precipitation variability [ABSTRACT FROM AUTHOR]

The root‐zone moisture replenishment mechanisms are key unknowns required to understand soil hydrological processes and water sources used by plants. Temporal patterns of root‐zone moisture replenishment reflect wetting events that contribute to plant growth and survival and to catchment water yield. In this study, stable oxygen and hydrogen isotopes of twigs and throughfall were continuously monitored to characterize the seasonal variations of the root‐zone moisture replenishment in a native vegetated catchment under Mediterranean climate in South Australia. The two studied hillslopes (the north‐facing slope [NFS] and the south‐facing slope [SFS]) had different environmental conditions with opposite aspects. The twig and throughfall samples were collected every ~20 days over 1 year on both hillslopes. The root‐zone moisture replenishment, defined as percentage of newly replenished root‐zone moisture as a complement to antecedent moisture for plant use, calculated by an isotope balance model, was about zero (±25% for the NFS and ± 15% for the SFS) at the end of the wet season (October), increased to almost 100% (±26% for the NFS and ± 29% for the SFS) after the dry season (April and May), then decreased close to zero (±24% for the NFS and ± 28% for the SFS) in the middle of the following wet season (August). This seasonal pattern of root‐zone moisture replenishment suggests that the very first rainfall events of the wet season were significant for soil moisture replenishment and supported the plants over wet and subsequent dry seasons, and that NFS completed replenishment over a longer time than SFS in the wet season and depleted the root zone moisture quicker in the dry season. The stable oxygen isotope composition of the intraevent samples and twigs further confirms that rain water in the late wet season contributed little to root‐zone moisture. This study highlights the significant role of the very first rain events in the early wet season for ecosystem and provides insights to understanding ecohydrological separation, catchment water yield, and vegetation response to climate changes. [ABSTRACT FROM AUTHOR]

Understanding global soil moisture‐air temperature (θ‐Ta) coupling is needed to improve the representation of land‐atmosphere interactions in Earth system models. Most studies on θ‐Ta coupling have focused on hot extremes, where precipitation‐related indices and model‐derived soil moisture products are commonly used. In this study, global θ‐Ta coupling is examined based on monthly air temperature anomalies and the Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS). A discrete wavelet decomposition is used to partition the TWS into different components. The results show that TWS is useful in revealing the spatial patterns of θ‐Ta coupling. Decomposed GRACE TWS shows improved skill compared to raw TWS in explaining temporal variability of monthly air temperature, which likely reflects different roles of soil moisture at different depths in the θ‐Ta coupling. The explanatory power improves further by using a combination of decomposed GRACE TWS and precipitation. Such improvement is observed particularly in places where vegetation tends to have a deeper rooting system, such as eastern region of South America, the southern tip of Africa, and north of the Tropic of Capricorn in Australia. The occurrence of θ‐Ta coupling is mainly constrained by the coupling of root zone moisture and land surface temperature. In addition to deeper rooting systems, clear wet and dry season alternation is another favorable factor for developing significant monthly θ‐Ta coupling. Key Points: Wavelet decomposition improves the skill of GRACE TWS in explaining temporal variability of monthly air temperature anomaliesA combination of decomposed GRACE TWS and precipitation better explains temperature variability than each of the two variables separatelyMonthly soil moisture‐air temperature coupling is strongest in areas with deeper rooting systems and clear dry‐wet seasonality [ABSTRACT FROM AUTHOR]

Plant transpiration depends on environmental conditions, and soil water availability is its primary control under water deficit conditions. In this study, we improve a simplified process‐based model (hereafter "BTA") by including soil water potential (ψsoil) to explicitly represent the dependence of plant transpiration on root‐zone moisture conditions. The improved model is denoted as the BTA‐ψ model. We assessed the performance of the BTA and BTA‐ψ models in a subtropical monsoon climate and a Mediterranean climate with different levels of water stress. The BTA model performed reasonably in estimating daily and hourly transpiration under sufficient water conditions, but it failed during dry periods. Overall, the BTA‐ψ model provided a significant improvement for estimating transpiration under a wide range of soil moisture conditions. Although both models could estimate transpiration (sap flow) at night, BTA‐ψ was superior to BTA in this regard. Species differences in the calibrated parameters of both models were consistent with leaf‐level photosynthetic measurements on each species, as expected given the physiological basis of these parameters. With a simplified representation of physiological regulation and reasonable performance across a range of soil moisture conditions, the BTA‐ψ model provides a useful alternative to purely empirical models for modelling transpiration. [ABSTRACT FROM AUTHOR]

The spatiotemporal variations of seasonal precipitation extremes during 1963–2013 over China and the possible teleconnections with large‐scale ocean–atmosphere indices are investigated by using the rotated empirical orthogonal functions, cross‐correlation analysis and stepwise variable selection methods. Results show that northwest China experiences the most frequent dry events but exhibits a wetting tendency in all seasons, while in south and central China, extreme wet conditions are remarkable in seasons except for winter but a drying tendency is found in spring and autumn. Precipitation extremes in four different seasons are influenced by the different combinations of large‐scale climate indices with different time lags, and their regional responses are complex when the climate indices are at different phases, such as winter heavy precipitation (R95p) in south of Nanling Mountain generally tends to be increased by the simultaneous positive El Niño–Southern Oscillation (ENSO) and sea surface temperature anomalies (SSTs) over South China Sea and positive Arctic Oscillation (AO) with 5‐month lag, while summer R95p in the middle and lower reaches of Yangtze River Basin be decreased by the simultaneous negative SSTs over Bay of Bengal and positive AO with 9‐month lag. Besides, the dominant climate indices identified by teleconnection analysis can partly explain the temporal changes of seasonal extreme precipitation in China, which can be confirmed by very similar fluctuation in the oscillatory patterns of eight chosen couples with higher correlation coefficient, and their explanation skill is more powerful in sensitive areas highlighted in the leading spatial modes of corresponding precipitation index. Moreover, this explanation skill generally enhances as the cumulative contribution of leading four rotated modes to total variance of the target variable over whole study area increases. In addition, the precipitation indices related to precipitation amount can be better explained than those related to wet or dry spell by identified dominant climate indices. Teleconnection patterns of seasonal precipitation extremes are investigated by REOFs and stepwise regression. South of Nanling Mountain highlighted in the figure is the sensitive area, and positive NINO3_0, NINO3_1, SCS_0 and AO_5 tend to increase winter R95p there. These identified indices together explain 58% variability in RPC1 of winter R95p. Furthermore, NINO3_0 can generally catch the fluctuation in first rotated temporal signal of winter R95p. The explanation skill of identified climate indices largely depends on cumulative variance of leading modes. [ABSTRACT FROM AUTHOR]

Abstract: Shallow groundwater plays a key role in agro‐hydrological processes of arid areas. Groundwater often supplies a necessary part of the water requirement of crops and surrounding native vegetation, such as groundwater‐dependent ecosystems. However, the impact of water‐saving irrigation on cropland water balance, such as the contribution of shallow groundwater to field evapotranspiration, requires further investigation. Increased understanding of quantitative evaluation of field‐scale water productivity under different irrigation methods aids policy and decision‐making. In this study, high‐resolution water table depth and soil water content in field maize were monitored under conditions of flood irrigation (FI) and drip irrigation (DI), respectively. Groundwater evapotranspiration (ETg) was estimated by the combination of the water table fluctuation method and an empirical groundwater–soil–atmosphere continuum model. The results indicate that daily ETg at different growth stages varies under the two irrigation methods. Between two consecutive irrigation events of the FI site, daily ETg rate increases from zero to greater than that of the DI site. Maize under DI steadily consumes more groundwater than FI, accounting for 16.4% and 14.5% of ETa, respectively. Overall, FI recharges groundwater, whereas DI extracts water from shallow groundwater. The yield under DI increases compared with that under FI, with less ETa (526 mm) compared with FI (578 mm), and irrigation water productivity improves from 3.51 kg m−3 (FI) to 4.58 kg m−3 (DI) through reducing deep drainage and soil evaporation by DI. These results highlight the critical role of irrigation method and groundwater on crop water consumption and productivity. This study provides important information to aid the development of agricultural irrigation schemes in arid areas with shallow groundwater. [ABSTRACT FROM AUTHOR]

A novel simple soil-plant-atmospheric continuum model that emphasizes the vegetation's role in controlling water transfer (v-SPAC) has been developed in this study. The v-SPAC model aims to incorporate both plant and soil hydrological measurements into plant water transfer modeling. The model is different from previous SPAC models in which v-SPAC uses (1) a dynamic plant resistance system in the form of a vulnerability curve that can be easily obtained from sap flow and stem xylem water potential time series and (2) a plant capacitance parameter to buffer the effects of transpiration on root water uptake. The unique representation of root resistance and capacitance allows the model to embrace SPAC hydraulic pathway from bulk soil, to soil-root interface, to root xylem, and finally to stem xylem where the xylem water potential is measured. The v-SPAC model was tested on a native tree species in Australia, Eucalyptus crenulata saplings, with controlled drought treatment. To further validate the robustness of the v-SPAC model, it was compared against a soil-focused SPAC model, LEACHM. The v-SPAC model simulation results closely matched the observed sap flow and stem water potential time series, as well as the soil moisture variation of the experiment. The v-SPAC model was found to be more accurate in predicting measured data than the LEACHM model, underscoring the importance of incorporating root resistance into SPAC models and the benefit of integrating plant measurements to constrain SPAC modeling. [ABSTRACT FROM AUTHOR]

Sap flow measurement techniques have been successfully applied in ecohydrological studies as they can be used to estimate watershed transpiration. Sapwood area ( As) is one of the most important tree parameters for estimating transpiration from point sap flow measurements. Accurate and efficient determination of As and the relationship between As and other tree parameters (e.g. diameter at 130 cm, DBH) is essential for the practical upscaling of sap flow data. The conventional methods for determining sapwood area are accurate (although coring can damage the trees) but prohibitive when a large number of trees need to be sampled. Electrical resistivity tomography (ERT) is a non-destructive geophysical method, which detects the moisture or electrolyte concentration difference in wood tissue to identify sapwood-heartwood boundaries. In this study, a rigorous method for quantifying sapwood width and area using ERT is detailed using measurements on 30 trees of three Australian native species (drooping sheoak and two eucalypts). Results show that sapwood widths estimated by ERT were in good agreement with those obtained from wood core analyses for the three species. A strong linear relationship was observed between As and DBH and between heartwood radius and DBH. The As-DBH relationship extends the synthesis for eucalypts species in previous studies. Sapwood width was overestimated for trees under wet conditions, which indicates that the ERT technique for sapwood width quantification is limited under such conditions. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 China's 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

ABSTRACT In this article, a rainfall forecasting model using monthly historical rainfall data and climate indices is developed by incorporating the multi-resolution analysis ( MRA) and multiple linear regression ( MLR) model. The monthly rainfall anomaly and large-scale climate index time series are decomposed using MRA into a certain number of component subseries at different temporal scales. The hierarchical lag relationship between the rainfall anomaly and each potential predictor is identified by cross correlation analysis with a lag time of at least one month at different temporal scales. The components of predictor variables with known lag times are then screened with a stepwise linear regression algorithm to be selectively included into the final forecast model. This MRA-based rainfall forecasting method is examined with 46 stations over South Australia, and compared to the traditional MLR model based on the original time series. The models are trained with data from the 1959-1995 period and then tested in the 1996-2008 period for each station. The performance is compared with observed rainfall values, and evaluated by common statistics of relative absolute error and correlation coefficient. The results show that the proposed MRA-based model provides considerably more accurate monthly rainfall forecasts for all of the selected stations over South Australia than the traditional regression model. For the MRA-based method, historical rainfall is consistently useful for all examined stations, while the large-scale climate signals are only partly useful for some stations. [ABSTRACT FROM AUTHOR]

Climatic teleconnections are often used to interpret and sometimes to predict precipitation temporal variability at various time scales. However, the teleconnections are intertwined between the effects of multiple large-scale climate signals which are often interdependent. Each climate signal is composed of multitemporal components, which may result in different teleconnection patterns. The time lags of precipitation response may vary with climate signals and their multitemporal components. In order to effectively address these problems, a multiresolution analysis (MRA) with a discrete wavelet transform is utilized, and a stepwise linear regression model based on MRA and cross correlation analysis is developed in this study. The method is applied to examine monthly precipitation teleconnections in South Australia (SA) with five large-scale climate signals. The MRA first decomposes each of original monthly precipitation anomaly and climate signals into several component series at different temporal scales. Then the hierarchical lag relationships between them are determined for regression modeling using cross-correlation analysis. The results indicate that the MRA-based method is able to reveal at which time scale(s) and with what time lag(s) the teleconnections occur, and their spatial patterns. The method is also useful to examine the time-scale patterns of the interdependence between climate signals. These altogether make the MRA-based method a promising tool to address the difficulties in the climate teleconnection studies. The multiple linear regression based on MRA-decomposed climate signals is expected to better interpret monthly precipitation temporal variability than that based on the original climate signals. [ABSTRACT FROM AUTHOR]

A simple field-based method for directly parameterizing root water uptake models is proposed. Stem psychrometers and sap flow meters are used to measure stem water potential and plant transpiration rate continuously and simultaneously. Predawn stem water potential is selected as a surrogate for root zone soil water potential to examine and parameterize the root water uptake-water stress response functions. The method is applied to two drooping sheoak ( Allocasuarina verticillata) trees for a period of 80 days, covering both a dry season and a wet season. The results indicate that the S-shape function is more appropriate than the Feddes piecewise linear function for drooping sheoak to represent the effect of soil moisture stress on its root water uptake performance. Besides, the water stress function is found to be not only a function of soil moisture but also dependent of the atmospheric demand. As a result, the water stress function is corrected for the effect of atmospheric conditions. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Application of the simple watershed chloride mass balance (CMB) method over areas of historical forest clearance is highly uncertain because the CMB method requires a steady state assumption, while the beginning, duration, and end of the transient period between preclearance and postclearance steady states is unknown. To address this difficulty, principal component analysis (PCA) with groundwater chemistry data is explored for the Piccadilly Valley in the Mount Lofty Ranges in South Australia, incorporated with hydrological modeling. The results indicate that PCA provides a potentially useful tool to identify postclearance dynamic hydrochemical response. Processes during the postclearance transient period, such as the release of historical soil chloride together with the charge-balance cations, alter ionic ratios from a steady state condition, which make the hydrochemical signals from the transient processes distinguishable from other processes by PCA. For the studied watershed, the effect of postclearance transient processes accounts for 24% of major-ion data variance, in comparison to 43% resulting from the effects of precipitation diluting and evapotranspiration concentrating processes. The PC scores associated with the transient processes are shown to be useful for estimating the timing of the postclearance transient, and estimating chloride concentration of groundwater recharge at the preclearance and postclearance steady states, even under conditions where the new steady state has not yet reached or the preclearance hydrochemical signal is lost. [ABSTRACT FROM AUTHOR]

ABSTRACT The sky view factor ( SVF) is a commonly used indicator in research fields of urban microclimate such as the urban heat island ( UHI). Analytical methods have been widely adapted in SVF estimation with the development of accurate three dimensional ( 3D) data, in which, however, the sky radiance is usually assumed to be isotropic. In this study, we discuss the sky temperature distribution and its influence on the SVF calculation based on its definition and differential geometry, and then according to the nocturnal net outgoing radiation ratio of cloudy skies to that of clear skies, the effective SVF ( ESVF) is presented and defined to explain UHI intensity variance. The results of numerical computation combined with calculations from true 3D building data for Adelaide, Australia, demonstrate that the sky temperature variance has little effect on SVF estimation. While for totally overcast or cloudy sky conditions, Ts is less different from the sky temperature than for clear skies, the proposed ESVF is sensitive to the sky temperature distribution and cloud cover fraction, providing the potential ability to analyse UHI intensity for various cloudy conditions. Copyright © 2013 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The article presents a study which investigated the effects of root distribution on deep percolation into the underlying permeable bedrock for a given soil profile and climate condition with the use of HYDRUS modelling at a semiarid ponderosa pine hillslope. Results of the sensitivity analysis show that the root macropore effect dominates saturated soil water flow in low conductivity soils. It was found that potential groundwater recharge is impeded by the clay-rich soil layer without root-induced macropores.

In semiarid complex terrain, the landscape creates spatial niches for different types of vegetation through the effects of aspect, slope and curvature on the water and energy balance at the soil surface. The ecohydrology of rangelands is defined by the interaction of soils, plants and climate occurring on a topographic surface. While these interactions have been studied for subtle terrain, little is known about the controls exerted by terrain position, in particular terrain aspect, on ecosystem processes. Furthermore, differential plant establishment can lead to measurable differences in rates of soil development, which in turn can affect soil hydraulic properties and the surface water balance. In this study, we outline the physical mechanisms affecting plant establishment, soil development and hydrologic fluxes in semiarid complex terrain. We illustrate the interactions between vegetation, root zone water fluxes and soil development using, as an example, a small drainage basin in the Sevilleta National Wildlife Refuge (SNWR), New Mexico. In the study basin, opposing hillslopes are characterized by marked differences in ecosystem composition and soil profile properties, with the north-facing hillslope dominated by one seed juniper (Juniperus monosperina) and the south-facing slope consisting of creosote bush (Larrea rridentata). We assess the effect of terrain aspect on root zone hydrologic fluxes and soil development in the two ecosystems by using soil observations, hydraulic properties from pedotransfer functions (PTFs), and numerical modelling of vadose zone fluxes. Modelling results show marked differences in root zone fluxes in the north-facing juniper and south-facing creosote ecosystems. Differences in the amplitude and frequency of soil water content and pressure correspond to changes in soil profile and vegetation characteristics. For example, soil properties of the calcium carbonate (CaCO3) horizons and differential plant water uptake impact the simulated soil water pressure over an 8-year period in the opposing ecosystems. It is believed that these variations in water fluxes reinforce the development of CaCO3 horizons present in the soil profiles, leading to a feedback between vegetation establishment, soil water fluxes and geomorphic processes in the catchment. Our results also indicate that soil properties and water fluxes compensate for large differences in evaporative demand and lead to similar actual evapotranspiration (AET) in the opposing slopes. [ABSTRACT FROM AUTHOR]

Field experiments were conducted to evaluate the efficiency of iron-oxide-coated sand (ICS) and surfactant modified zeolite (SMZ) to remove viruses and bacteria from ground water. The reactive media were employed as filter packs of a pumping well that withdrew sewage effluent from a constructed wetland at a rate of 0.72 L/min. The contact time of the pumped water with the filter pack (10 cm thick) was about two minutes. Upgradient of the pumping well, the sewage effluent was spiked with MS-2 bacteriophage and E. coli. While the employed ICS filter pack failed to remove viruses and bacteria to a significant degree, the SMZ filter pack removed more than 99% of the viruses and 100% of E. coli from the ground water while fresh. In an additional field experiment using the same configuration but leaving the filter pack in place for more than five months, the SMZ filter pack was still removing 100% of E. coli, but failed to reduce virus numbers to a significant degree. [ABSTRACT FROM AUTHOR]