The papers in this issue represent a selection of the presentations made at the session entitled “Climate-soil and vegetation interactions in ecological–hydrological processes” of the European Geophysical Union General Assembly. The special issue “Coupled Ecological–Hydrological Processes” focuses on different aspects of Ecohydrology that can be summarized in the following topics: soil moisture dynamics, soil–plant interactions, vegetation modelling and effects of climate change on natural ecosystems.
How to cite: Salvatore Manfreda, Keith Smettem, Vito Iacobellis, Nicola Montaldo and Murugesu Sivapalan, Preface Coupled ecological –hydrological processes, ECOHYDROLOGY, 3, Pages 131–132 (doi: 10.1002/eco.131),2010. [pdf]
The description of soil moisture dynamics is a challenging problem for the hydrological community, as it is governed by complex interactions between climate, soil and vegetation. Recent research has achieved signiﬁcant advances in the description of temporal dynamics of soil water balance through the use of a stochastic differential equation proposed by Laio et al. (2001). The assumptions of the Laio et al. model simplify the mathematical form of the soil water loss functions and the inﬁltration process. In particular, runoff occurs only for saturation excess, the probability distribution function (PDF) of which is well represented by a simple expression, but the model does not consider the limited inﬁltration capacity of soil. In the present work, we extend the soil moisture model to include limitations on soil inﬁltration capacity with the aim of understanding the impact of varying inﬁltration processes on the soil water balance and vegetation stress. A comparison between the two models (the original version and the modiﬁed one) is carried out via numerical simulations. The limited inﬁltration capacity inﬂuences the soil moisture PDF by reducing its mean and variance. Major changes in the PDFs are found for climates characterized by storms of short duration and high rainfall intensity, as well as in humid climates and in cases where soils have moderate permeability (e.g. loam and clay soils). In the case of limited inﬁltration capacity, modiﬁcations to the dynamics of soil moisture generally lead to higher amounts of vegetation water stress. An investigation of the role of soil texture on vegetation water stress demonstrates that loam soil provides the most favorable condition for plant-growth under arid and semi-arid conditions, while vegetation may beneﬁt from the presence of more permeable soils (e.g. loamy sand) in humid climates.
How to cite: Manfreda, S., T.M. Scanlon, K.K. Caylor, On the importance of accurate depiction of infiltration processes on modelled soil moisture and vegetation water stress, Ecohydrology, 3, 155-165, (doi: 10.1002/eco.79), 2010. [pdf]
Society is facing growing environmental problems that require new research efforts to understand of the way that ecosystems operate and survive and their mutual relationships with the hydrologic cycle. This is fundamental to advance predictive models used by researchers, industry, and environmental managers. In this frame, Ecohydrology faces this task with the aim to provide improved forecasting and mitigation of flood and drought risk, better understanding of implications of land use changes on terrestrial ecosystems (such as deforestation or desertification), improved weather and climate predictions, better comprehension of climatic changes effects on terrestrial ecosystems. The scope of the present paper is to address the most challenging questions of ecohydrology providing a review of some of the most recent results in this emerging field.
How to cite: Salvatore Manfreda, Ecohydrology: A new Interdisciplinary Approach to Investigate on Climate – Soil – Vegetation Interactions, Annals of Arid Zone, Volume 48, Number 3 e 4, September and December, Pages 219-228, ISSN 0570-1791,2009.
Characterizing the spatial dynamics of soil moisture ﬁelds is a key issue in hydrology, oﬀering an avenue to improve our understanding of complex land surface–atmosphere interactions. In this paper, the statistical structure of soil moisture patterns is examined using modelled soil moisture obtained from the North American Land Data Assimilation System (NLDAS) at 0.125° resolution. The study focuses on the vertically averaged soil moisture in the top 10 cm and 100 cm layers. The two variables display a weak dependence for lower values of surface soil moisture, with the strength of the relationship increasing with the water content of the top layer. In both cases, the variance of the soil moisture follows a power law decay as a function of the averaging area. The superﬁcial layer shows a lower degree of spatial organization and higher temporal variability, which is reﬂected in rapid changes in time of the slope of the scaling functions of the soil moisture variance. Conversely, the soil moisture in the top 100 cm has lower variability in time and larger spatial correlation. The scaling of these patterns was found to be controlled by the changes in the soil water content. Results have implications for the downscaling of soil moisture to prevent model bias.
How to cite: Manfreda, S., M. McCabe, E.F. Wood, M. Fiorentino and I. Rodríguez-Iturbe, Spatial Patterns of Soil Moisture from Distributed Modeling, Advances in Water Resources, 30(10), 2145-2150, (doi: 10.1016/j.advwatres.2006.07.009), 2007. [pdf]
Recent work by Isham et al. and Rodrìguez-Iturbe et al. has characterized the space- time variability of soil moisture through its analytically derived covariance function which depends on soil properties, vegetation structure, and rainfall patterns typical of a region. This paper uses such characterization to address the strategies and methodologies for the sampling of soil moisture fields. The focus is on the estimation of the long-term mean soil moisture and the daily soil moisture averaged over a given area as a function of the network geometry, number of stations, number of sampling days and landscape heterogeneity. It is found that the spatial geometry of the network has a significant impact on the sampling of the average soil moisture over an area in any particular day, while it is much less relevant for the sampling of the long-term mean daily soil moisture over the region. In the latter case, the length of the record is a commanding factor in what concerns the variance of estimation, specially for soils with shallow rooted vegetation. Spatial vegetation heterogeneity plays an important role on the variance of estimation of the soil moisture, being particularly critical for the sampling of the average soil moisture over an area for a given day.
How to cite: Manfreda, S. and I. Rodrìguez-Iturbe, On the Spatial and Temporal Sampling of Soil Moisture Fields, Water Resources Research, 42, W05409, (doi:10.1029/2005WR004548), 2006. [pdf]
The present paper complements that of Isham et al. (2005), who introduced a space-time soil moisture model driven by stochastic space-time rainfall forcing with homogeneous vegetation and in the absence of topographical landscape effects. However, the spatial variability of vegetation may significantly modify the soil moisture dynamics with important implications for hydrological modeling. In the present paper, vegetation heterogeneity is incorporated through a two dimensional Poisson process representing the coexistence of two functionally different types of plants (e.g., trees and grasses). The space-time statistical structure of relative soil moisture is characterized through its covariance function which depends on soil, vegetation, and rainfall patterns. The statistical properties of the soil moisture process averaged in space and time are also investigated. These properties are especially important for any modeling that aggregates soil moisture characteristics over a range of spatial and temporal scales. It is found that particularly at small scales, vegetation heterogeneity has a significant impact on the averaged process as compared with the uniform vegetation case. Also, averaging in space considerably smoothes the soil moisture process, but in contrast, averaging in time up to 1 week leads to little change in the variance of the averaged process.
How to cite: Rodríguez-Iturbe, I., V. Isham, D.R. Cox, S. Manfreda, A. Porporato, Space-time modeling of soil moisture: stochastic rainfall forcing with heterogeneous vegetation, Water Resources Research, 42, W06D05, (doi:10.1029/2005WR004497), 2006. [pdf]
This paper examines the linkage between the drainage network and the patterns of soil water balance components determined by the organization of vegetation, soils and climate in a semiarid river basin. Research during the last 10 years has conclusively shown an increasing degree of organization and unifying principles behind the structure of the drainage network and the three-dimensional geometry of river basins. This cohesion exists despite the inﬁnite variety of shapes and forms one observes in natural watersheds. What has been relatively unexplored in a quantitative and general manner is the question of whether or not the interaction of vegetation, soils, and climate also display a similar set of unifying characteristics among the very diﬀerent patterns they presents in river basins. A recently formulated framework for the water balance at the daily level links the observed patterns of basin organization to the soil moisture dynamics. Using available geospatial data, we assign soil, climate, and vegetation properties across the basin and analyze the probabilistic characteristics of steady-state soil moisture distribution. We investigate the presence of organization through the analysis of the spatial patterns of the steady-state soil moisture distribution, as well as in the distribution of observed vegetation patterns, simulated vegetation dynamic water stress and hydrological ﬂuxes such as transpiration. Here we show that the drainage network acts as a template for the organization of both vegetation and hydrological patterns, which exhibit self-aﬃne characteristics in their distribution across the river basin. Our analyses suggest the existence of a balance between the large-scale determinants of vegetation pattern reﬂecting optimality in the response to water stress and the random small-scale patterns that arise from local factors and ecological legacies such as those caused by dispersal, disturbance, and founder eﬀects.
How to cite: Caylor, K.K., S. Manfreda, I. Rodríguez-Iturbe, On the Coupled Geomorphological and Ecohydrological Organization of River Basins, Advances in Water Resources, 28(1), 69-86, (doi: 10.1016/j.advwatres.2004.08.013), 2005. [pdf]
A simpliﬁed spatial-temporal soil moisture model driven by stochastic spatial rainfall forcing is proposed. The model is mathematically tractable, and allows the spatial and temporal structure of soil moisture ﬁelds, induced by the spatial-temporal variability of rainfall and the spatial variability of vegetation, to be explored analytically. The inﬂuence of the main model parameters, reﬂecting the spatial scale of rain cells, the soil storage capacity, the rainfall interception and the soil water loss rate (representing evaporation and deep inﬁltration) is investigated. The variabilities of the spatially averaged soil moisture process, and that averaged in both space and time, are derived. The present analysis focuses on spatially uniform vegetation conditions; a follow-up paper will incorporate stochastically heterogeneous vegetation.
How to cite: Isham, V., D.R. Cox, I. Rodríguez-Iturbe, A. Porporato, S. Manfreda, Representation of Space-Time Variability of Soil Moisture, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 461(2064), 4035 – 4055, (doi:10.1098/rspa.2005.1568), 2005. [pdf]
The spatial distribution of soil properties is directly involved in the fluctuation of soil moisture conditions and in the runoff generation mechanisms. In this work, the influences of the physical characteristics of the contributing area to the peak flow were widely investigated with the aim of understanding the influences of each physical parameter. The study was conducted by means of a hydrological distributed model (Manfreda et al. ), applied on the study area of the Agri river basin at Tarangelo (507 km2), in the region of Basilicata, Italy. Two different time scales were used: the first with higher temporal resolution (1-hour) dedicated to the superficial routing, the latter at daily scale used for local water balances and subsurface flow evaluation. Using the model at daily scale, daily soil moisture maps and the river discharge at the outlet are obtained. These results were used as input for the model at the hourly scale in order to describe the initial conditions in the watershed for event simulations. The simulation was carried on by using a synthetic hourly rainfall series generated by using the IRP model proposed by Veneziano & Iacobellis . By using the rainfall-runoff model it was possible to simulate a large number of extreme events and consequently evaluate the relative contributing area to the peak flow. Specifically, every cell of these areas was classified for its vegetational, pedological and morphological characteristics with the aim of interpreting the relationship between physical properties and potential contribute to flow peaks.
How to cite: Manfreda, S., D. Carriero, V. Iacobellis, A. Sole & M. Fiorentino, The Effects of Soil Properties on Floods in the Agri Basin (Southern Italy), River Basin Management II (edited by C.A. Brebbia), WITpress, pp. 321-330, (ISBN 1-85312-966-6), 2003.