鄱阳湖湿地土壤微生物活性对年际水文变化的响应

湿地自然水文节律的改变影响着湿地生态系统的稳定与安全.为探究湿地水文变化对土壤微生物活性的影响,以鄱阳湖洲滩湿地3种典型植被狗牙根（Cynodon dactylon）、南荻（Triarrhena lutarioriparia）和苔草（Carex cinerascens）下表层土壤（0~20 cm）为研究对象,对湿地土壤微生物呼吸、微生物生物量和水解酶等土壤活性特征进行连续3年的实验监测,分析年际水位变化对不同植被湿地土壤微生物活性的影响.结果表明：丰水年显著提高土壤中养分的可利用性（有机质、总磷、速效磷）,提高土壤微生物生物量、微生物熵、水解酶活性,表明丰水年有利于湿地生态系统的物质循环转化.水文条件也能通过影响湿地植被生长改变土壤养分状况,进而对植被下土壤微生物活性产生显著影响.诸多土壤理化因子中,可溶性有机碳是驱动微生物活性变化最关键的因子.进一步分析表明,由植被类型所代表的长期水文累积效应对湿地土壤理化及微生物活性的调节作用大于单纯的年际水文变化.     

A case study of spatial heterogeneity of soil moisture in the Loess Plateau, western China： A geostatistical approach

Soil moisture distribution shows highly variation both spatially and temporally. This study assesses the spatial heterogeneity of soil moisture on a hill-slope scale in the Loess Plateau in West China by using a geostatistical approach. Soil moisture was measured by time-domain reflectometry （TDR） in 313 samples. Two kinds of sampling scales were used （2 × 2 m and 20 ×20 m） at two soil layers （0-30 cm and 30-60 cm）. The general characteristics of soil moisture were analyzed by a classical statistics method, and the spatial heterogeneity of soil moisture was analyzed using a geostatistical approach. The results showed that the spherical model is the best-fit model to simulate soil moisture on the experimental hill-slope. The parameters of this model indicated that the spatial dependence of soil moisture in the selected hill-slope was moderate. Even the 2 × 2 m sampling scale was too coarse to show the detailed spatial variances of soil moisture in this area. The dependent distance increased from 27.4 m to 494.16 m as the sampling scale became coarse （from 2× 2 m to 20 ×20 m）. A map of soil moisture was generated by using original soil moisture data and interpolated values determined by the Kriging method. The average soil moisture （area weighted） in the different layers of soil was calculated on the basis of this map （10.94% for the 0-30 cm soil layer, 11.88% for the 30-60 cm soil layer）. This average soil moisture is lower than the corresponding average effective soil moisture, which suggests that the soil moisture is not sufficient to support vegetation in this area.     

An analysis of soil moisture dynamics using multi-year data from a network of micrometeorological observation sites

Soil moisture data, obtained from four AmeriFlux sites in the US, were examined using an ecohydrological framework. Sites were selected for the analysis to provide a range of plant functional type, climate, soil particle size distribution, and time series of data spanning a minimum of two growing seasons. Soil moisture trends revealed the importance of measuring water content at several depths throughout the rooting zone; soil moisture at the surface (0–10 cm) was approximately 20–30% less than that at 50–60 cm. A modified soil moisture dynamics model was used to generate soil moisture probability density functions at each site. Model calibration results demonstrated that the commonly used soil matric potential values for finding the vegetation stress point and field content may not be appropriate, particularly for vegetation adapted to a water-controlled environment. Projections of future soil moisture patterns suggest that two of the four sites will become severely stressed by climate change induced alterations to the precipitation regime.     

Differences in soil moisture in two Middle Eastern oak forests: Comparing the effects of trees and soil composition

The incidence of large rain events in Mediterranean ecosystems vary among years. Summer aridity is interpreted as a resetting event, eliminating previous soil‐moisture dynamics. The dynamics of soil moisture and retention are critical to tree survival, particularly in dry regions. This study examines the long‐term soil water content (θ_V) dynamics in two distinct locations within the forest, under the canopy and forest clearing, within two diverse oak forests: subhumid mixed oak forests (MG) and semiarid monospecific oak woodlands (YE). Plots were established at small‐scale catchments and soil water contents were measured during 2010–2013, at three depths in the two different locations. Cumulative rainfall was used as an independent proxy for θ_V analysis. A novel bell‐bilogistic mathematical model of wetting, saturation, and drying arms was developed. We aimed to study the θ_V distribution differences between soil profiles giving the large climatic gradient between the two forested sub basins, the differences in vegetation traits along with soil attributes. We further aimed at determining the role of an individual tree in regulating soil‐moisture dynamics. We hypothesized the occurrence of distinct responses between sites in all soil‐moisture indices with higher θ_V at the wetter site. We tested the hypothesis that seasonal cumulative rainfall dictates the variations in soil‐moisture regimes throughout contiguous years. Annual rainfall was higher than long‐term average throughout the study. Soil profiles under the canopies at both sites were consistently wetter. Infiltration and depletion constants were higher at MG whereas maximum soil moisture was higher at YE. Homogenous recharge patterns were seen at MG although YE evinced more variation. Oaks had no effect on recharge at MG compared with the forest clearing. Soil properties primarily affected the wetting arm whereas vegetation composition regulated the drying arm. Mixed‐stands characterized by ever‐green and deciduous species may maintain favourable soil‐moisture conditions, in comparison with other mixed stand morphologies. The increasing role of slacking forces in infiltration process may alter the interaction between trees and herbaceous vegetation.     

新疆艾比湖湿地土壤水盐空间变异性分析

为揭示艾比湖湿地土壤退化程度空间分布特征,在离艾比湖湖滨5~15 km,绕湖一周160 km范围内,以湖心质点为中心,将艾比湖划分为东北、东南、西南、西北4个区域,采用传统统计学和地统计学相结合的方法对表层(0~20 cm)土壤盐分、含水量与p H的空间分异特征进行研究.结果表明:绕湖一周不同区域的土壤盐分均属中等变异强度;土壤含水量在西北部属强变异性,而东北、东南和西南部均属中等变异强度;土壤p H在不同区域内均属弱变异强度.绕湖一周除西北部土壤盐分的半方差理论模型较符合球状模型外,其它区域土壤盐分、含水量和p H均符合高斯模型;受结构性因素影响,不同区域土壤盐分、含水量和p H均具有较强的空间相关性;西南部土壤盐分、含水量和p H的Moran's I系数比其它区域的波动大,表明空间相关性较强.艾比湖湿地常年大风、干旱、缺水及沙化盐化的自然因素与引水围堰、种植耐盐碱植物的人为活动造成了采样区表层土壤盐分、含水量和p H的空间分布多呈现不规则条带状格局.艾比湖湿地土壤以盐土为主,重度盐化土次之,土壤盐渍化日益严重.     

基于光学与被动微波遥感的青藏高原地区土壤水分反演

青藏高原地区高精度的土壤水分反演对高原能水循环、全球大气循环研究有着极大的影响.因此,获取青藏高原土壤水分时空布信息是一个迫切需要解决的问题.温度植被干旱指数（TVDI）,是基于光学与热红外遥感通道数据反演土壤水分的重要方法,但在研究区域较大、地表覆盖格局差异显著时,TVDI模型反演精度会受到地表温度（Ts）等因素的影响.被动微波AMSR-E数据精确记录了像元内的土壤水分信息,但空间分辨率低.本文利用同时期的MODIS与被动微波数据,发展了针对青藏高原地区高精度土壤水分反演算法.首先,在TVDI模型中,利用修正型土壤调整植被指数（MSAVI）代替归一化植被指数（NDVI）,以改进NDVI易饱和的缺点;其次,利用ASTER GDEM数据,对地形高程和纬度差异引起的地表温度变化进行了校正;然后,通过神经网络训练建立基于TVDI、被动微波以及辅助气象数据的土壤水分反演模型,并应用该模型反演了青藏高原地区三个观测网（CAMP/Tibet、玛曲和那曲）的土壤水分;最后,利用实测土壤水分数据对反演结果进行验证,结果表明该模型的精度均方根误差（RMSE）数值可达到0.031~0.041 m³·m^-3.本文还应用该算法反演了青藏高原连续的土壤水分的空间分布,并比较了土壤水分的变化趋势与实测降水变化趋势,结果表明二者变化量的正负关系一致.

     

Soil moisture variation in relation to topography and land use in a hillslope catchment of the Loess Plateau, China

The profile characteristics and the temporal dynamics of soil moisture variation were studied at 26 locations in Da Nangou catchment (3.5 km²) in the loess area of China. Soil moisture measurements were performed biweekly at five depths in the soil profile (0–5, 10–15, 20–25, 40–45 and 70–75 cm) from May to October 1998 using Delta-T theta probe. Soil moisture profile type and temporal variation type and their relationship to topography and land use were identified by detrended canonical correspondence analysis (DCCA) and correlation analysis. The profile distribution of time-averaged soil moisture content can be classified into three types i.e. decreasing-type, waving-type and increasing-type. The profile features of soil moisture (e.g. profile gradient and profile variability) are influenced by different environmental factors. The profile type of soil moisture is only attributed to land use while profile gradient and profile variability of soil moisture is mainly related to land use and topography (e.g. landform type and slope). The temporal dynamics of layer-averaged soil moisture content is grouped into three types including three-peak type, synchro-four-peak type and lagged-four-peak type. These types are controlled by topography rather than by land use. The temporal dynamic type of soil moisture shows significant correlation with relative elevation, slope, aspect, while temporal variance displays significant relation with slope shape. The mean soil moisture is related to both the profile and dynamics features of soil moisture and is controlled by both land use and topography (e.g. aspect, position, slope and relative elevation). The spatial variability of soil moisture across landscape varies with both soil depths and temporal evolution.     

Temporal stability of soil moisture in an oasis of northwestern China

Temporal stability of soil moisture has been widely used in hydrological monitoring since it emerged. However, the spatial analysis of temporal stability at the landscape scale is often limited because of insufficient sampling numbers. This work made an effort to investigate the spatial variations of temporal stability of soil moisture in an oasis landscape. The specific objectives of the study were to explore the spatial patterns of temporal stability and to determine the controlling factors of temporal stability in the desert oasis. A time series of soil moisture measurements were gathered on 23 occasions at 118 locations over 3 years in a rectangular transect of approximately 100 km². The nonparametric Spearman's rank correlation coefficient, standard deviation of relative difference (SDRD), and mean absolute bias error (MABE) were used to quantify the temporal stability of soil moisture. Results showed that the temporal stability of soil moisture was depth dependent and season dependent. The spatial pattern of soil moisture in a deep soil layer and between two same seasons generally had a high temporal stability. SDRD and MABE were spatially autocorrelated and exhibited strong spatial structures in the geographic space. The concept of temporal stability can be extended to describe the time‐stable areas of soil moisture with geostatistics. There were great differences between SDRD and MABE in describing the temporal stability of soil moisture and in identifying the controlling factors of temporal stability. In this case, MABE was a better alternative to estimate the areal mean soil moisture using representative locations than SDRD. Land use type, soil moisture condition, and soil particle composition were the dominant controls of temporal stability in the oasis. These insights could help to better understand the essence of temporal stability of soil moisture in arid regions.     

Assimilation of streamflow and in situ soil moisture data into operational distributed hydrologic models: Effects of uncertainties in the data and initial model soil moisture states

We assess the potential of updating soil moisture states of a distributed hydrologic model by assimilating streamflow and in situ soil moisture data for high-resolution analysis and prediction of streamflow and soil moisture. The model used is the gridded Sacramento (SAC) and kinematic-wave routing models of the National Weather Service (NWS) Hydrology Laboratory’s Research Distributed Hydrologic Model (HL-RDHM) operating at an hourly time step. The data assimilation (DA) technique used is variational assimilation (VAR). Assimilating streamflow and soil moisture data into distributed hydrologic models is new and particularly challenging due to the large degrees of freedom associated with the inverse problem. This paper reports findings from the first phase of the research in which we assume, among others, perfectly known hydrometeorological forcing. The motivation for the simplification is to reduce the complexity of the problem in favour of improved understanding and easier interpretation even if it may compromise the goodness of the results. To assess the potential, two types of experiments, synthetic and real-world, were carried out for Eldon (ELDO2), a 795-km² headwater catchment located near the Oklahoma (OK) and Arkansas (AR) border in the U.S. The synthetic experiment assesses the upper bound of the performance of the assimilation procedure under the idealized conditions of no structural or parametric errors in the models, a full dynamic range and no microscale variability in the in situ observations of soil moisture, and perfectly known univariate statistics of the observational errors. The results show that assimilating in situ soil moisture data in addition to streamflow data significantly improves analysis and prediction of soil moisture and streamflow, and that assimilating streamflow observations at interior locations in addition to those at the outlet improves analysis and prediction of soil moisture within the drainage areas of the interior stream gauges and of streamflow at downstream cells along the channel network. To assess performance under more realistic conditions, but still under the assumption of perfectly known hydrometeorological forcing to allow comparisons with the synthetic experiment, an exploratory real-world experiment was carried out in which all other assumptions were lifted. The results show that, expectedly, assimilating interior flows in addition to outlet flow improves analysis as well as prediction of streamflow at stream gauge locations, but that assimilating in situ soil moisture data in addition to streamflow data provides little improvement in streamflow analysis and prediction though it reduces systematic biases in soil moisture simulation.     

Plant root traits affecting the resistance of soils to concentrated flow erosion

The effect of plant species on erosion processes may be decisive for long‐term soil protection in degraded ecosystems. The identification of functional effect traits that predict species ability for erosion control would be of great interest for ecological restoration purposes. Flume experiments were carried out to investigate the effect of the root systems of three species having contrasted ecological requirements from eroded marly lands of the French Southern Alps [i.e. Robinia pseudo acacia (tree), Pinus nigra austriaca (tree) and Achnatherum calamagrostis (grass)], on concentrated flow erosion rates. Ten functional traits, describing plant morphological and biomechanical features, were measured on each tested sample. Analyses were performed to identify traits that determine plant root effects on erosion control. Erosion rates were lowest for samples of Robinia pseudo acacia, intermediate in Achnatherum calamagrostis and highest in Pinus nigra austriaca. The three species also differed strongly in their traits. Principal components analysis showed that the erosion‐reducing potential of plant species was negatively correlated to root diameter and positively correlated to the percentage of fine roots. The results highlighted the role of small flexible roots in root reinforcement processes, and suggested the importance of high root surface and higher tensile strength for soil stabilization. By combining flume experiment to plant functional traits measurements, we identified root system features influencing plant species performance for soil protection against concentrated flow erosion. Plant functional traits related to species efficiency for erosion control represent useful tools to improve the diagnosis of land vulnerability to erosion, plant community resistance and the prediction of ecosystem functioning after ecological restoration. Copyright © 2012 John Wiley & Sons, Ltd.     

On the role of soil moisture in daytime evolution of temperatures

This paper explores the relationship between temperature, evaporation and soil moisture using a planetary boundary layer (PBL) model. It focuses on illustrating and quantifying the effect of soil moisture on the evolution of daytime temperatures. A simple convective PBL model coupled with the Penman–Monteith (PM) equation is used to estimate evapotranspiration. Following calibration and sensitivity analysis, the model was used to simulate the relative impact of dry and wet soil moisture conditions on daytime temperatures by changing the surface resistance parameter in the PM equation. It was found that the maximum temperature that can be reached during a day is constrained by the amount of soil moisture and the available net radiation, confirming previously published results. Higher temperatures can be reached with greater net radiation and dry soil moisture conditions. Copyright © 2012 John Wiley & Sons, Ltd.     

Controls of surface soil moisture spatial patterns and their temporal stability in a semi‐arid steppe

Temporal stability of soil moisture spatial patterns has important implications for optimal soil and water management and effective field monitoring. The aim of this study was to investigate the temporal stability of soil moisture spatial patterns over four plots of 105 m × 135 m in grid size with different grazing intensities in a semi‐arid steppe in China. We also examined whether a time‐stable location can be identified from causative factors (i.e. soil, vegetation, and topography). At each plot, surface soil moisture (0–6 cm) was measured about biweekly from 2004 to 2006 using 100 points in each grid. Possible controls of soil moisture, including soil texture, organic carbon, bulk density, vegetation coverage, and topographic indices, were determined at the same grid points. The results showed that the spatial patterns of soil moisture were considerably stable over the 3‐y monitoring period. Soil moisture under wet conditions (averaged volumetric moisture contents > 20%) was more stable than that under dry ( ) or moist ( ) conditions. The best representative point for the whole field identified in each plot was accurate in representing the field mean moisture over time (R² ≥ 0·97; p < 0·0001). The degree of temporal persistence varied with grazing intensity, which was partly related to grazing‐induced differences in soil and vegetation properties. The correlation analysis showed that soil properties, and to a lesser extent vegetation and topographic properties, were important in controlling the temporal stability of soil moisture spatial patterns in this relatively flat grassland. Response surface regression analysis was used to quantitatively identify representative monitoring locations a priori from available soil‐plant parameters. This allows appropriate selection of monitoring locations and enhances efficiency in managing soil and water resources in semi‐arid environments. Copyright © 2010 John Wiley & Sons, Ltd.     

1973-2018年青海湖岸线动态变化

青海湖独特的地理位置使得其不仅对环湖周边区域气候起着天然调节器的作用,而且还拥有丰富的湖岸线资源,准确、及时地掌握青海湖岸线动态变化对保护沿湖生态环境有重要意义.因此本文基于1973-2018年Landsat MSS/TM/OLI遥感影像和1961-2017年实测水位资料,对青海湖岸线动态变化及对鸟类栖息地的影响进行研究,同时结合面积、水位及气象数据讨论了影响岸线变化的主要因素.研究表明：1）近45年来青海湖岸线发生变化最大的区域是东岸的沙岛,西岸的鸟岛、铁布卡湾及北岸沙柳河入口区域.尤其自2004年以来,鸟岛地区岸线后退距离最大（5.52 km）,鸟类栖息地扩张约97.94 km²,为鸟类提供了较好的栖息环境.（2）1973-2018年青海湖岸线长度以0.88 km/a的速率逐渐延长.1997年之前岸线长度呈较为平稳的上升趋势,1997-2004年呈波动下降趋势,2004年之后呈剧烈波动增加趋势,岸线曲折性也表现出相同的变化趋势.（3）总体上岸线长度和曲折性受水位和面积的影响并不显著,但在不同的水位情况下,二者对青海湖动态变化做出不同的响应.尤其当水位小于3193.3 m或面积小于4249.3 km²时,岸线曲折性会随着水位和面积变化呈现相同的变化趋势,而水位高于3193.3 m时,岸线曲折性一直在增加,且水位上升速率越大则曲折性年际变化越大.（4）1973-2004年间青海湖水位下降和土地沙漠化是造成湖岸线变化的直接成因,人类活动及草场退化加速了湖泊岸线的变迁.2004年之后,随着青海湖水位回升与面积扩张,岸线逐渐后退,尤其在2017-2018年岸线后退距离最大.     

洞庭湖洲滩土壤种子库对土壤水分变化的响应

由于三峡大坝及上游水库群的运行,长江中下游水域水文节律随之发生了改变,导致洞庭湖枯水期提前,进而影响洞庭湖洲滩植被及其土壤种子库的分布格局.本研究在洞庭湖4个自然保护区内选取共11个典型洲滩湿地,沿由水到陆方向根据植被类型将洲滩分为泥沙洲滩、泥沙—湖草洲滩过渡带、湖草洲滩、湖草—南荻洲滩过渡带、南荻洲滩5种洲滩类型.通过样带—样方法调查和采样,并结合湿润和水淹两种条件下的土壤种子库萌发实验,分析了土壤水分变化对洲滩种子库萌发特征的影响及土壤种子库与地表植被的关系.结果显示:①土壤含水量沿水到陆方向由泥沙洲滩向南荻洲滩递减;②不同类型洲滩土壤种子库密度没有显著差异;③温室萌发实验中,水淹条件下土壤种子库物种丰富度和种子库密度显著降低,东洞庭湖自然保护区土壤种子库物种丰富度和种子库密度较高;④地表植被物种丰富度高于土壤种子库,泥沙洲滩土壤种子库与地表植被物种组成的Jaccard相似性指数最低.此外,虉草(Phalaris arundinacea)、芦苇(Phragmites communis)、南荻(Miscanthus sacchariflorus)等只在地表植被中存在,而陌上菜(Lin...     

On the importance of soil moisture in calibration of rainfall–runoff models: two case studies

Streamflow modelling results from the GR4H and PDM hydrological models were evaluated in two Australian sub-catchments, using (1) calibration to streamflow and (2) joint-calibration to streamflow and soil moisture. Soil moisture storage in the models was evaluated against soil moisture observations from field measurements. The PDM had the best performance in terms of both streamflow and soil moisture estimations during the calibration period, but was outperformed by GR4H during validation. It was also shown that the soil moisture estimation was improved significantly by joint-calibration for the case where streamflow and soil moisture estimations were poor. In other cases, addition of the soil moisture constraint did not degrade the results. Consequently, it is recommended that GR4H be used, in preference to the PDM, in the foothills of the Murrumbidgee catchment or other Australian catchments with semi-arid to sub-humid climate, and that soil moisture data be used in the calibration process.     

Role of time variant and invariant terms on soil moisture spatio-temporal variability in a subhumid coastal wetland

The knowledge of soil moisture spatio-temporal variability is highly relevant for water resources management. This paper reports an analysis of the spatial–temporal variability of soil moisture data for a small to medium-scale soil-sensors network in a coastal wetland of southwestern Spain. Measurements were taken from five sites located in the Doñana National Park over the time-period of one hydrological year from September 2017 to September 2018. The total area of the soil-sensors network shows an extension about 25 × 3 km. Soil moisture data was separated into time invariant (the temporal mean of the whole period at each site) and time-variant terms (the deviations of soil moisture from the mean, or anomalies). The time-invariant component was generally the main contributor to the total spatial variance of soil moisture and it was mostly controlled by the groundwater levels in the area. Nevertheless, the time variant terms have a huge effect on soil moisture variability in very dry states. Characteristic convex time-dependent patterns for this field site were found between spatially averaged soil moisture and its variability. This information could be used for the up and downscaling of soil moisture from satellite data. Those patterns of relation between spatial mean and variability of soil moisture were only affected by heavy rainfalls giving rise to hysteretic behaviour. This study shows that even though groundwater level is a time-variant variable, it significantly affects soil moisture's time-variant but also time-invariant terms due to the different average groundwater level depths at the different sites.     

Regional scale spatial and temporal variability of soil moisture in a prairie region

Understanding the dynamics of spatial and temporal variability of soil moisture at the regional scale and daily interval, respectively, has important implications for remote sensing calibration and validation missions as well as environmental modelling applications. The spatial and temporal variability of soil moisture was investigated in an agriculturally dominated region using an in‐situ soil moisture network located in central Saskatchewan, Canada. The study site evaluated three depths (5, 20, 50 cm) through 139 days producing a high spatial and temporal resolution data set, which were analysed using statistical and geostatistical means. Processes affecting standard deviation at the 5‐cm depth were different from the 20‐cm and 50‐cm depths. Deeper soil measurements were well correlated through the field season. Further analysis demonstrated that lag time to maximum correlation between soil depths increased through the field season. Temporal autocorrelation was approximately twice as long at depth compared to surface soil moisture as measured by the e‐folding frequency. Spatial correlation was highest under wet conditions caused by uniform rainfall events with low coefficient of variation. Overall soil moisture spatial and temporal variability was explained well by rainfall events and antecedent soil moisture conditions throughout the Kenaston soil moisture network. It is expected that the results of this study will support future remote sensing calibration and validation missions, data assimilation, as well as hydrologic model parameterization for use in agricultural regions. Copyright © 2016 John Wiley & Sons, Ltd.     

Analysis of soil moisture dynamics beneath olive trees

Olive cultivation is a widespread land use in Mediterranean climates. The proper implementation of soil and water conservation practices in groves requires detailed knowledge of the governing hydrological processes. In this work topsoil moisture dynamics under wet and dry conditions and across a small catchment was investigated in the inter row (IR) and directly under the olive tree canopies (UC). We do this using a sensor network (11 stations) and a simple bucket model which was calibrated (June, 2011–2012) and validated (June, 2012–2013). During most of the year the normalized soil moisture contents (s) were greater in the IR than under UC, with an average normalized soil moisture difference of 0.12. The difference between UC and IR normalized soil moisture followed a seasonal pattern, reaching a maximum near 0.30 during spring. An analysis of the normalized soil moisture probability density functions (pdfs) was bimodal, showing characteristic dominant wet and dry soil moisture states, with the highest probability densities for the dry state. Overall the spatial variability of soil moisture was lower UC than in the IR. This was a result of the soil moisture buffering capacity of the canopy with respect to rainfall and evaporation, in addition to observed differences in soil properties. Hourly soil moisture data were successfully modelled (R² > 0.85), both UC and in the IR, yet with the inclusion of a simple formulation for canopy interception for the former. The results provide insight into how olive trees change hydrological processes in their neighbourhood. Copyright © 2016 John Wiley & Sons, Ltd.     

Estimation of mean water transit time on a steep hillslope in South Korea using soil moisture measurements and deuterium excess

A method for estimating daily mean transit time (DMTT) within a soil layer was proposed using field measurements of soil moisture. Vertical profiles of soil moisture time series were used for storage estimation. Water fluxes were evaluated through matrix and bypass flow. Variations in soil moisture and soil thickness were used to evaluate matrix flow. Exponential decay in depth of macropores was also used for bypass flow approximation. DMTT evaluation was compared to results obtained from a stable water isotope model using two years of data acquired on a steep granite hillslope in the Sulmachun watershed, South Korea. Various uncertainties in transit time evaluation such as model structure, non‐stationary assumption and data acquisition of existing approaches can be accounted for in the proposed methodology, and the flowpath contribution can be further configured in conjunction with hydrometric measurements. Probability density functions of isotope analyses were partially explained by transit time distributions that were based on soil moisture measurements. Supplementary sensitivity analyses for uncertainty configurations indicate that matrix flow is the primary process in determining transit time distribution while the impact of bypass flow is minor. The feasibility of a DMTT approach over isotope‐based methodologies highlights not only the strength of this proposed method, both in cost and time, but also its further application potential for existing soil moisture measurements. Copyright © 2013 John Wiley & Sons, Ltd.     

A top–down soil moisture and sap flux sampling design of a rain–snow transition mountain watershed

This paper presents a top–down approach for soil moisture and sap flux sampling design with the goal of understanding ecohydrologic response to interannual climate variation in the rain–snow transition watersheds. The design is based on a priori estimates of soil moisture and transpiration patterns using a physical distributed model, Regional Hydro‐Ecologic Simulation System (RHESSys). RHESSys was initially calibrated with existing snow depth and streamflow data. Calibrated model estimates of seasonal trajectories of snowmelt, root‐zone soil moisture storage, and transpiration were used to develop five hydrologic similarity indicators and map these at (30 m) patch scale across the study watershed. The partitioning around medoids‐clustering algorithm was then used to define six distinctive spatially explicit clusters based on the five hydrologic similarity indictors. A representative site within each cluster was identified for sampling. For each site, soil moisture sensors were installed at the 30‐ and 90‐cm depths and at the five soil pits and a sap flux sensor at the averaged‐size white fir tree for each site. The model‐based cluster analysis suggests that the elevation gradient and topographically driven flow drainage patterns are the dominant drivers of spatial patterns of soil moisture and transpiration. The comparison of model‐based calculated hydrological similarity indicators with measured‐data‐based values shows that spatial patterns of field‐sampled soil moisture data typically fell within uncertainty bounds of model‐based estimates for each cluster. There were however several notable exceptions. The model failed to capture the soil moisture and sap flux dynamics in a riparian zone site and in a site where lateral subsurface flow may not follow surface topography. Results highlight the utility of using a hypothesis driven sampling strategy, based on a physically based model, for efficiently providing new information that can drive both future measurements and strategic refinements to model inputs, parameters, or structure that might reduce these errors. Future research will focus on strategies for using of finer scale representations of microclimate, topography, vegetation, and soil properties to improve models.