Plants in water-controlled ecosystems: active role in hydrologic processes and response to water stress: III. Vegetation water stress

The reduction of soil moisture content during droughts lowers the plant water potential and decreases transpiration; this in turn causes a reduction of cell turgor and relative water content which brings about a sequence of damages of increasing seriousness. A review of the literature on plant physiology and water stress shows that vegetation water stress can be assumed to start at the soil moisture level corresponding to incipient stomatal closure and reach a maximum intensity at the wilting point. The mean crossing properties of these soil moisture levels crucial for water stress are derived analytically for the stochastic model of soil moisture dynamics described in Part II (F. Laio, A. Porporato, L. Ridolfi, I. Rodriguez-Iturbe. Adv. Water Res. 24 (7) (2001) 707–723). These properties are then used to propose a measure of vegetation water stress which combines the mean intensity, duration, and frequency of periods of soil water deficit. The characteristics of vegetation water stress are then studied under different climatic conditions, showing how the interplay between plant, soil, and environment can lead to optimal conditions for vegetation.     

Sampling of soil moisture fields and related errors: implications to the optimal sampling design

Adequate knowledge of soil moisture storage as well as evaporation and transpiration at the land surface is essential to the understanding and prediction of the reciprocal influences between land surface processes and weather and climate. Traditional techniques for soil moisture measurements are ground-based, but space-based sampling is becoming available due to recent improvement of remote sensing techniques. A fundamental question regarding the soil moisture observation is to estimate the sampling error for a given sampling scheme [G.R. North, S. Nakamoto, J Atmos. Ocean Tech. 6 (1989) 985–992; G. Kim, J.B. Valdes, G.R. North, C. Yoo, J. Hydrol., submitted]. In this study we provide the formalism for estimating the sampling errors for the cases of ground-based sensors and space-based sensors used both separately and together. For the study a model for soil moisture dynamics by D. Entekhabi, I. Rodriguez-Iturbe [Adv. Water Res. 17 (1994) 35–45] is introduced and an example application is given to the Little Washita basin using the Washita '92 soil moisture data. As a result of the study we found that the ground-based sensor network is ineffective for large or continental scale observation, but should be limited to a small-scale intensive observation such as for a preliminary study.     

Analytical solutions of tidal groundwater flow in coastal two-aquifer system

This paper presents a complete analytical solution to describe tidal groundwater level fluctuations in a coastal subsurface system. The system consists of two aquifers and a leaky layer between them. Previous solutions of Jacob [Flow of groundwater, in: H. Rouse (Ed.), Engineering Hydraulics, Wiley, New York, 1950, pp. 321–386], Jiao and Tang [Water Resour. Res. 35 (3) (1999) 747], Li and Jiao [Adv. Water Resour. 24 (5) (2001a) 565], Li et al. [Water Resour. Res. 37 (2001) 1095] and Jeng et al. [Adv. Water Resour. (in press)] are special cases of the new solution. The present solution differs from previous work in that both the effects of the leaky layer's elastic storage and the tidal wave interference between the two aquifers are considered. If the upper and lower aquifers have the same storativities and transimissivities, the system can be simplified into an equivalent double-layered, aquifer–aquitard system bounded by impermeable layers from up and down. It is found that the leaky layer's elastic storage behaves as a buffer to the tidal wave interference between the two aquifers. The buffer capacity increases with the leaky layer's thickness, specific storage, and decreases with the leaky layer's vertical permeability. Great buffer capacity can result in negligible tidal wave interference between the upper and lower aquifers so that the Li and Jiao (loc. cit.) solution applies.     

Cluster-based fuzzy models for groundwater flow in the unsaturated zone

In this paper fuzzy models are used as an alternative to describe groundwater flow in the unsaturated zone. The core of these models consists of a fuzzy rule-based model of the Takagi–Sugeno type. Various fuzzy clustering algorithms are compared in the data-driven identification of these Takagi–Sugeno models. The performance of the resulting fuzzy models is evaluated on the training surface on which they were identified, and on time series measurements of water content values obtained through an experiment carried out by the non-vegetated terrain (NVT) workgroup of the European Microwave Signature Laboratory (EMSL) (see [Mancini M, Hoeben R, Troch PA. Multifrequency radar observations of bare surface soil moisture content: a laboratory experiment. Water Resour Res 1999;35(6):1827–38] and [Hoeben R, Troch PA. Assimilation of active microwave observation data for soil moisture profile estimation. Water Resour Res 2000;36(10):2805–19]). Despite higher errors at the borders of high water content values in the training surface, good results are obtained on the simulation of the time series.     

From rainfed agriculture to stress-avoidance irrigation: I. A generalized irrigation scheme with stochastic soil moisture

With vast regions already experiencing water shortages, it is becoming imperative to manage sustainably the available water resources. As agriculture is by far the most important user of freshwater and the role of irrigation is projected to increase in face of climate change and increased food requirements, it is particularly important to develop simple, widely applicable models of irrigation water needs for short- and long-term water resource management. Such models should synthetically provide the key irrigation quantities (volumes, frequencies, etc.) for different irrigation schemes as a function of the main soil, crop, and climatic features, including rainfall unpredictability. Here we consider often-employed irrigation methods (e.g., surface and sprinkler irrigation systems, as well as modern micro-irrigation techniques) and describe them under a unified conceptual and theoretical framework, which includes rainfed agriculture and stress-avoidance irrigation as extreme cases. We obtain mostly analytical solutions for the stochastic steady state of soil moisture probability density function with random rainfall timing and amount, and compute water requirements as a function of climate, crop, and soil parameters. These results provide the necessary starting point for a full assessment of irrigation strategies, with reference to sustainability, productivity, and profitability, developed in a companion paper [Vico G, Porporato A. From rainfed agriculture to stress-avoidance irrigation: II. Sustainability, crop yield, and net profit. Adv Water Resour 2011;34(2):272-81].     

Modelling spatio-temporal soil moisture dynamics in mountain tundra

Soil moisture has a fundamental influence on the processes and functions of tundra ecosystems. Yet, the local dynamics of soil moisture are often ignored, due to the lack of fine resolution, spatially extensive data. In this study, we modelled soil moisture with two mechanistic models, SpaFHy (a catchment-scale hydrological model) and JSBACH (a global land surface model), and examined the results in comparison with extensive growing-season field measurements over a mountain tundra area in northwestern Finland. Our results show that soil moisture varies considerably in the study area and this variation creates a mosaic of moisture conditions, ranging from dry ridges (growing season average 12 VWC%, Volumetric Water Content) to water-logged mires (65 VWC%). The models, particularly SpaFHy, simulated temporal soil moisture dynamics reasonably well in parts of the landscape, but both underestimated the range of variation spatially and temporally. Soil properties and topography were important drivers of spatial variation in soil moisture dynamics. By testing the applicability of two mechanistic models to predict fine-scale spatial and temporal variability in soil moisture, this study paves the way towards understanding the functioning of tundra ecosystems under climate change.     

New equations for binary gas transport in porous media,Part 2: experimental validation

A previous study [Water Resour Res 39 (3) (2003) doi:10.1029/2002WR001338] questioned the validity of the traditional advection–dispersion equation for describing gas flow in porous media. In an original mathematical derivation presented in Part 1 [Adv Water Resour, this issue] we have demonstrated the theoretical existence of two novel physical phenomena which govern the macroscopic transport of gases in porous media. In this work we utilize laboratory experiments and numerical modeling in order to ascertain the importance of these novel theoretical terms. Numerical modeling results indicate that the newly derived sorptive velocity, arising from closure level coupling effects, does not contribute noticeably to the overall flux, under the conditions explored in this work. We demonstrate that the newly discovered “slip coupling” phenomenon in the mass conservation equation plays an important role in describing the physics of gas flow through porous solids for flow regimes of both environmental and industrial interest.     

Transport in chemically and mechanically heterogeneous porous media. II: Comparison with numerical experiments for slightly compressible single-phase flow

In this paper we compare the theory developed in Part I (Adv. Water Resour., 19 (1996) 24–47) with numerical experiments for transient, one-dimensional (in the large-scale averaged sense) flow in nodular and stratified systems. The comparison is limited to systems that are isotropic at the Darcy scale, and that are relatively simple when compared to the complex nature of most geological systems. Good agreement between theory and experiment is obtained, and this suggests that the simplifications made in the development of the three closure problems are acceptable. The closure problems have been used to calculate the permeability tensors and the exchange coefficient for a wide range of conditions of practical importance.     

Ecohydrology-a challenging multidisciplinary research perspective / Ecohydrologie: une perspective stimulante de recherche multidisciplinaire

Abstract

Ecohydrology is the science that studies the mutual interaction between the hydrological cycle and ecosystems. Such an interaction is especially intense in water-controlled ecosystems, where water may be a limiting factor, not only because of its scarcity, but also because of its intermittent and unpredictable appearance. Soil moisture is the key variable modulating the complex dynamics of the climate-soil-vegetation system and controlling the spatial and temporal patterns of vegetation. In this note the authors' perspective to the field is discussed and some open questions are outlined.     

Stochastic modelling of soil moisture dynamics in a grassland of Qilian Mountain at point scale

Stochastic modeling of soil moisture dynamics is crucial to the quantitative understanding of plant responses to water stresses,hydrological control of nutrient cycling processes,water competition among plants,and some other ecological dynamics,and thus has become a hotspot in ecohydrology at present.In this paper,we based on the continuously monitored data of soil moisture during 2002―2005 and daily precipitation date of 1992―2006,and tried to make a probabilistic analysis of soil moisture dynamics at point scale in a grassland of Qilian Mountain by integrating the stochastic model improved by Laio and the Monte Carlo method.The results show that the inter-annual variations for the soil moisture patterns at different depths are very significant,and that the coefficient of variance(CV) of surface soil moisture(20 cm) is almost continually kept at about 0.23 whether in the rich or poor rainy years.Interestingly,it has been found that the maximal CV of soil moisture has not always appeared at the surface layer.Comparison of the analytically derived soil moisture probability density function(PDF) with the statistical distribution of the observed soil moisture data suggests that the stochastic model can reasonably describe and predict the soil moisture dynamics of the grassland in Qilian Mountain at point scale.By extracting the statistical information of the historical precipitation data in 1994―2006,and inputting them into the stochastic model,we analytically derived the long-term soil moisture PDF without considering the inter-annual climate fluctuations,and then numerically derived the one when considering the inter-annual fluctuation effects in combination with a Monte-Carlo procedure.It was found that,though the peak position of the probability density distribution significantly moved towards drought when considering the disturbance forces,and its width was narrowed,accordingly its peak value was increased,no significant bimodality was observed in the soil moisture dynamics under the given intensity of random fluctuation disturbance.     

Structure in fluctuations of large-scale soil moisture climate due to external random forcing and internal feedbacks

Large-scale fields of soil moisture are forced by atmospheric precipitation and radiative forcing. When these forcing factors are themselves influenced by surface and soil moisture processes, the result is a nonlinear land-atmosphere system with inherent feedback mechanisms that may strongly modulate variability in climate. Given such feedbacks, simple randomness in the forcing factors may be manifested as a complex statistical signature in the surface hydrology. In this paper, we investigate the impacts of non-Gaussian and colored-noise on the probability distribution of soil moisture resulting from the statistical-dynamical land-atmosphere interaction model of Rodriguez-Iturbe et al. (1991). Persistence of hydroclimatologic anomalies as characterized by the correlation time scale of soil moisture is discussed.     

Stochastic analysis of bounded unsaturated flow in heterogeneous aquifers: Spectral/perturbation approach

This paper describes a stochastic analysis of steady state flow in a bounded, partially saturated heterogeneous porous medium subject to distributed infiltration. The presence of boundary conditions leads to non-uniformity in the mean unsaturated flow, which in turn causes non-stationarity in the statistics of velocity fields. Motivated by this, our aim is to investigate the impact of boundary conditions on the behavior of field-scale unsaturated flow. Within the framework of spectral theory based on Fourier–Stieltjes representations for the perturbed quantities, the general expressions for the pressure head variance, variance of log unsaturated hydraulic conductivity and variance of the specific discharge are presented in the wave number domain. Closed-form expressions are developed for the simplified case of statistical isotropy of the log hydraulic conductivity field with a constant soil pore-size distribution parameter. These expressions allow us to investigate the impact of the boundary conditions, namely the vertical infiltration from the soil surface and a prescribed pressure head at a certain depth below the soil surface. It is found that the boundary conditions are critical in predicting uncertainty in bounded unsaturated flow. Our analytical expression for the pressure head variance in a one-dimensional, heterogeneous flow domain, developed using a nonstationary spectral representation approach [Li S-G, McLaughlin D. A nonstationary spectral method for solving stochastic groundwater problems: unconditional analysis. Water Resour Res 1991;27(7):1589–605; Li S-G, McLaughlin D. Using the nonstationary spectral method to analyze flow through heterogeneous trending media. Water Resour Res 1995; 31(3):541–51], is precisely equivalent to the published result of Lu et al. [Lu Z, Zhang D. Analytical solutions to steady state unsaturated flow in layered, randomly heterogeneous soils via Kirchhoff transformation. Adv Water Resour 2004;27:775–84].     

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.     

Structure in fluctuations of large-scale soil moisture climate due to external random forcing and internal feedbacks

Large-scale fields of soil moisture are forced by atmospheric precipitation and radiative forcing. When these forcing factors are themselves influenced by surface and soil moisture processes, the result is a nonlinear land-atmosphere system with inherent feedback mechanisms that may strongly modulate variability in climate. Given such feedbacks, simple randomness in the forcing factors may be manifested as a complex statistical signature in the surface hydrology. In this paper, we investigate the impacts of non-Gaussian and colored-noise on the probability distribution of soil moisture resulting from the statistical-dynamical land-atmosphere interaction model of Rodriguez-Iturbe et al. (1991). Persistence of hydroclimatologic anomalies as characterized by the correlation time scale of soil moisture is discussed.     

A ground validation problem of remotely sensed soil moisture data

 As the use of space-based sensors to observe soil moisture is becoming more plausible, it is becoming necessary to validate the remotely sensed soil moisture retrieval algorithms. In this paper, measurements of point gauges on the ground are analyzed as a possible ground-truth source for the comparison with remotely sensed data. The design compares a sequence of measurements taken on the ground and from space. The authors review the mean square error of expected differences between the two systems by Ha and North (1994), which is applied to the Little Washita watershed using the soil moisture dynamics model developed by Entekhabi and Rodriguez-Iturbe (1994). The model parameters estimated by Yoo and Shin (1998) for the Washita `92 (relative) soil moisture data are used in this study. By considering about 20 pairs of ground- and space-based measure-ments (especially, for the same case as the Washita `92 that the space-based sensor visits the FOV once a day), the expected error was able to be reduced to approximately 10 of the standard deviation of the fluctuations of the system alone. This seems to be an acceptable level of tolerance for identifying biases in the retrieval algorithms.     

Year‐round estimation of soil moisture content using temporally variable soil hydraulic parameters

Soil moisture plays a key role in the hydrological cycle as it controls the flux of water between soil, vegetation, and atmosphere. This study is focused on a year‐round estimation of soil moisture in a forested mountain area using the bucket model approach. For this purpose, three different soil moisture models are utilised. The procedure is based on splitting the whole year into two complement periods (dormant and vegetation). Model parameters are allowed to vary between the two periods and also from year to year in the calibration procedure. Consequently, two sets of average model parameters corresponding to dormant and vegetation seasons are proposed. The process of splitting is strongly supported by the experimental data, and it enables us to variate saturated hydraulic conductivity and pore‐size characterisation. The use of the two different parameter sets significantly enhances the simulation of two (Teuling and Troch model and soil water balance model‐green–ampt [SWBM‐GA]) out of three models in the 6‐year period from 2009 to 2014. For these two models, the overall Nash‐Sutcliffe coefficient increased from 0.64 to 0.79 and from 0.55 to 0.80. The third model (the Laio approach) proved to be insensitive to parameter changes due to its insufficient drainage prediction. The variability of the warm and cold parameter sets between particular years is more pronounced in the warm periods. The cold periods exhibited approximately similar character during all 6 years.