Bibliography - I. Rodriguez-Iturbe

1. Nordbotten, Jan M., I. Rodriguez-Iturbe, and Michael Celia, 2007: Stochastic Coupling of Rainfall and Biomass Dynamics In , 43(W01408), doi:10.1029/2006WR005068
   [ Abstract ]

   A modeling scheme is presented to derive the probabilistic structure of plant biomass when subjected to stochastic precipitation conditions. Using the fact that soil moisture varies on a much shorter scale than plant biomass, analytical expressions are derived for the steady state probability distribution of the average plant biomass over a period T, which is expected to be of the order of 2 or 3 months. Analytical expressions are also given for the time-dependent mean and variance of the biomass over a period T. The analysis is based on a simple model linking the daily dynamics of plant growth and soil moisture. The derived analytical expressions reproduce the results obtained from a full simulation of the underlying model very well. The results allow the study of the impact of different climatic scenarios regarding changes in frequency and intensity of rainfall, as well as changes in the mean seasonal temperature, on the expected value and variance of plant biomass throughout time.

2. Puma, M. J., I. Rodriguez-Iturbe, Michael Celia, and A. J. Guswa, 2007: Implications of Rainfall Temporal Resolution for Soil-moisture and Transpiration Modeling. Transport in Porous Media, 68, doi:10.1007/S11242-006-9057-4 37-67
   [ Abstract ]

   Dimensionless groups of parameters characterizing an ecosystem are valuable indicators for the a priori assessment of the effect of rainfall data resolution on predictions of soil moisture and transpiration. Knowledge of these dimensionless groups enables identification of appropriate levels of rainfall data resolution, when using historical rainfall directly or when using it to derive rainfall model parameters for use in models of soil–plant–climate systems.Detailed simulation studies of the soil, plant, and climate systems in Colorado and Texas, highly resolved in time and vertical space, show that historical rainfall data resolved at the daily level allow accurate prediction of soil-moisture and transpiration dynamics for smaller time resolutions. These results support inferences based on the dimensionless groups. Furthermore, no significant improvement in the prediction of soil-moisture and transpiration dynamics is attained, when representing rainfall through a more complex Neyman–Scott model rather than the simple rectangular pulses Poisson model.

3. Nordbotten, Jan M., I. Rodriguez-Iturbe, and Michael Celia, 2006: Non-uniqueness of Evapotranspiration due to Spatial heterogeneity of Plant Species. Proceedings of The Royal Society of London, 462(2072), doi:10.1098/rspa.2005.1641 2359-2371
   [ Abstract ]

   Spatially averaged soil moisture dynamics are studied under seasonally fixed conditions. We consider rainfall as a marked Poisson process, uniformly covering a spatial domain consisting of multiple plant types. Each plant type is considered to have different characteristics in terms of evapotranspiration functions, root-zone depth and rainfall interception. Equations for the evolution of joint probability density functions for individual soil moistures associated with different plant types are developed, and the non-uniqueness of the spatially averaged evapotranspiration function as a function of the average soil moisture is demonstrated and quantified in an example.

4. Puma, M. J., Michael Celia, I. Rodriguez-Iturbe, and A. J. Guswa, 2005: Functional Relationship to Describe Temporal Statistics of Soil Moisture averaged over Different Depths. Advances in Water Resources, 28, doi:10.1016/j.advwatres.2004.08.015 553-566
   [ Abstract ]

   Detailed simulation studies, highly resolved in space and time, show that a physical relationship exists among instantaneous soilmoisture values integrated over different soil depths. This dynamic relationship evolves in time as a function of the hydrologic inputs and soil and vegetation characteristics. When depth-averaged soil moisture is sampled at a low temporal frequency, the structure of the relationship breaks down and becomes undetectable. Statistical measures can overcome the limitation of sampling frequency, and predictions of mean and variance for soil moisture can be defined over any soil averaging depth d. For a water-limited ecosystem, a detailed simulation model is used to compute the mean and variance of soil moisture for different averaging depths over a number of growing seasons. We present a framework that predicts the mean of soil moisture as a function of averaging depth given soil moisture over a shallow d and the average daily rainfall reaching the soil.

5. Guswa, A. J., Michael Celia, and I. Rodriguez-Iturbe, 2004: Effect of Vertical Resolution on Predictions of Transpiration in Water-limited Eosystems. Advances in Water Resources, 27, doi:10.1016/j.advwatres.2004.03.001 467-480
   [ Abstract ]

   Water-limited ecosystems are characterized by precipitation with low annual totals and significant temporal variability, transpiration that is limited by soil-moisture availability, and infiltration events that may only partially rewet the vegetation root zone. Average transpiration in such environments is controlled by precipitation, and accurate predictions of vegetation health require adequate representation of temporal variation in the timing and intensity of plant uptake. Complexities introduced by variability in depth of infiltration, distribution of roots, and a plant’s ability to compensate for spatially heterogeneous soil moisture suggest a minimum vertical resolution required for satisfactory representation of plant behavior. To explore the effect of vertical resolution on predictions of transpiration, we conduct a series of numerical experiments, comparing the results from models of varying resolution for a range of plant and climate conditions. From temporal and spatial scales of the underlying processes and desired output, we develop dimensionless parameters that indicate the adequacy of a finite-resolution model with respect to reproducing characteristics of plant transpiration over multiple growing seasons. These parameters may be used to determine the spatial resolution required to predict vegetation health in water-limited ecosystems.

6. Guswa, A. J., Michael Celia, and I. Rodriguez-Iturbe, 2002: Models of Soil-Moisture Dynamics in Ecohydrology: A Comparative Study. Water Resources Research, 38(9), doi:10.1029/2001WR000826
   [ Abstract ]

   An accurate description of plant ecology requires an understanding of the interplay between precipitation, infiltration, and evapotranspiration. A simple model for soil moisture dynamics, which does not resolve spatial variations in saturation, facilitates analytical expressions of soil and plant behavior as functions of climate, soil, and vegetation characteristics. Proper application of such a model requires knowledge of the conditions under which the underlying simplifications are appropriate. To address this issue, we compare predictions of evapotranspiration and root zone saturation over a growing season from a simple bucket-filling model to those from a more complex, vertically resolved model. Dimensionless groups of key parameters measure the quality of the match between the models. For a climate, soil, and woody plant characteristic of an African savanna the predictions of the two models are quite similar if the plant can extract water from locally wet regions to make up for roots in dry portions of the soil column; if not, the match is poor.

7. Rodriguez-Iturbe, I., 2000: Ecohydrology: A Hydrologic Perspective of Climate-Soil-Vegetation Dynamics. Water Resources Research, http://www.agu.org/journals/wr/v036/i001/1999WR900210/1999WR900210.pdf, 36(1), 3-9
   [ Abstract ]

   The hydrologic mechanisms underlying the climate-soil-vegetation dynamics and thus controlling the most basic ecologic patterns and processes are described as one very exciting research frontier for the years to come. In this personal opinion I have concentrated on those processes where soil moisture is the key link between climate fluctuations and vegetation dynamics in space and time. The soil moisture balance equation at a site is shown to be the keystone of numerous fundamental questions which may be instrumental in the quantitative linkage between hydrologic dynamics and ecological patterns and processes. Some of those questions are outlined here, and possible avenues of attack are suggested. The space-time links between climate, soil, and vegetation are also explored from the hydrologic perspective, and some exciting research perspectives are outlined.

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