Modeling water availability for trees in tropical forests

Abstract

Modeling soil water availability for tropical trees is a prerequisite to predicting the future impact of climate change on tropical forests. In this paper we develop a discrete-time deterministic water balance model adapted to tropical rainforest climates, and we validate it on a large dataset that includes micro-meteorological and soil parameters along a topographic gradient in a lowland forest of French Guiana. The model computes daily water fluxes (rainfall interception, drainage, tree transpiration and soil plus understorey evapotranspiration) and soil water content using three input variables: daily precipitation, potential evapotranspiration and solar radiation. A novel statistical approach is employed that uses Time Domain Reflectometer (TDR) soil moisture data to estimate water content at permanent wilting point and at field capacity, and root distribution. Inaccuracy of the TDR probes and other sources of uncertainty are taken into account by model calibration through a Bayesian framework. Model daily output includes relative extractable water, REW, i.e. the daily available water standardized by potential available water. The model succeeds in capturing temporal variations in REW regardless of topographic context. The low Root Mean Square Error of Predictions suggests that the model captures the most important drivers of soil water dynamics, i.e. water refilling and root water extraction. Our model thus provides a useful tool to explore the response of tropical forests to climate scenarios of changing rainfall regime and intensity.

Introduction

Despite annual precipitation that always exceeds 1500 mm year⁻¹, most of the Amazon’s neotropical forests experience some annual dry season (less than 100 mm per month), that is variable in both duration and intensity (Malhi and Wright, 2004, Sombroek, 2001, Xiao et al., 2006, Marengo, 1992).

The consequences of annual drought on tropical forest functioning include a decrease in growth primary production and ecosystem respiration (Goulden et al., 2004, Hutyra et al., 2007, Bonal et al., 2008), and a reduction in tropical tree fluxes for both carbon (Bonal et al., 2000, Miranda et al., 2005) and water fluxes (Fisher et al., 2006). Very recently, an analysis of tree responses to the intense 2005 dry season highlighted the vulnerability of neotropical forests to moisture stress, with the potential for positive feedbacks on climate change due to increased tree mortality (Phillips et al., 2009).

Climate modeling scenarios suggest that the dry season in north-eastern Amazonian forests might lengthen during the 21st century (Cox et al., 2000, Cox et al., 2004, Malhi and Wright, 2004, Malhi et al., 2009). The short-term effect of soil water availability deficits on tropical tree growth, mortality and carbon and water fluxes has recently been quantified under experimentally controlled conditions (Fisher et al., 2007, Nepstad et al., 2007). Long-term inventory plots with regular tree censuses (growth, recruitment, mortality) have been set-up widely in the past few decades throughout Amazonia (Phillips et al., 2010, Clark, 2004, Wagner et al., 2010). These plots offer an unexpected opportunity to analyze the impact of soil water availability on tropical forest dynamics on a large temporal and spatial scale (Clark, 2007). However, to the best of our knowledge, no soil water balance model explicitly accounting for tropical soil and climate characteristics, and able to compute available water for the trees on a plot scale, has ever been developed. The relation between amount of rainfall and water availability for trees is not straightforward and determined by various plant characteristics, such as the root distribution, and soil characteristics, such as the permanent wilting point and the field capacity. By contrast, other widely studied climatic variables such as light and temperature give a relatively direct indication on their effect on forest dynamics (Graham et al., 2003, Clark et al., 2010). Soil water availability to the trees, which can be characterized by Relative Extractable Water (REW, i.e. daily available water standardized by maximum available water), depends on soil characteristics such as structure, texture, composition and porosity, as well as on the rate of water uptake by the trees. Different soil water balance models have been used in Amazonian tropical forests to estimate drought implications for forest flammability and tree growth (Nepstad et al., 2004), to reproduce hydrologic processes (Belk et al., 2007), to evaluate soil water controls on evapotranspiration (Fisher et al., 2007), or to evaluate the importance of deep root uptake (Markewitz et al., 2010). However, none of these models aims to estimate REW. The nearest estimate of REW is so-called plant available water (PAW) described by Nepstad et al. (2004). The spatial resolution of PAW, i.e. 8 km, is too large for use in any precise modeling of the impact of soil drought conditions on tree growth, mortality and/or recruitment. Furthermore, the modeling framework never explicitly simulates the amount of water taken up by tree roots. Modeling approaches designed to estimate REW have already been developed for temperate forests and, for instance, were used to assess soil water control on carbon and water dynamics in European forests during the 2003 drought (Granier et al., 2007). Such temperate models are not suitable for tropical forests. For instance, the polynomial rainfall interception submodel is unsuited to the stand characteristics of tropical forests. Another limit is that water extraction is not modeled and field data is needed for root density, meaning that soil pits need to be dug to quantify vertical root distribution, also meaning that the strong assumption must be made that water absorption by roots is proportional to root distribution.

In this paper we introduce a locally parameterized soil water budget model inspired by the BILJOU temperate model (Granier et al., 1999). As performed by BILJOU, this model estimates soil water availability, stand transpiration and rainfall interception in tropical forests with a daily time step and for different soil types (Fig. 1). Model inputs are daily rainfall, annual means of potential evapotranspiration (PET) and solar radiation, and averaged plant area index (PAI). The soil is filled by rainfall water passing through the canopy. The amount of rainfall intercepted by the canopy is computed in a submodel adapted to tropical forests (Gash et al., 1995). In our model, the soil consists of a succession of fine layers, each of which has a unique field capacity and permanent wilting point. We developed a new method using a Bayesian framework to estimate these two parameters using only Time Domain Reflectometer (TDR) measurements. When the water in a given layer exceeds water content at field capacity, drainage occurs and water fills the next layer, etc. Water extraction from soil layers is due to tree transpiration in addition to soil and understorey evapotranspiration. Soil evaporation and understorey transpiration are computed based on equations developed by Granier et al. (1999), and are assumed to be proportional to the energy reaching the understorey; tree transpiration is computed using potential evapotranspiration. Both understorey and tree transpiration are extracted in accordance with estimated root distribution.

This paper has three specific objectives: (i) to present our water balance model and to describe the different submodels it contains; (ii) to present an original statistical method used to estimate permanent wilting point, field capacity, and root distribution based on Time-Domain Reflectometer (TDR) data only; and (iii) to parameterize and validate the model using TDR data collected on a soil topographic gradient in Paracou, French Guiana.