# Bibliography - I. Rodriguez-Iturbe

- 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.

- 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.

- 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.

- 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.

- 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.

- 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.

- 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.

Direct link to page: http://cmi.princeton.edu/bibliography/results.php?author=3675