Agricultural Drought Indices - US Department of Agriculture

Water Balance—Tools for Integration in Agricultural Drought Indices
Paulo Cesar Sentelhas
AgMet Group, Department of Biosystems Eng., ESALQ, University of São Paulo
Piracicaba, SP, Brazil
Abstract
An overview of water balance models for integration with agricultural drought indices is presented
in this chapter. The basic concepts of water balance for agricultural purposes are discussed,
focusing on the complexity of the models used to simulate the soil water content. The models are
divided in two groups of complexity according to weather, soil, and plant data availability. Simple
models are those based on the computation of rainfall and evapotranspiration, whereas complex
models deal with soil water dynamics as a function of the interaction among soil-plant-atmosphere
systems. The basic errors associated with these different models are discussed and a clear
distinction is made between systematic and calibration errors. The water balance models currently
most used for agricultural drought index calculation are presented, with an emphasis on the
following models: Thornthwaite and Mather, MUSAG, Ritchie, and Gevaerd and Freitas. Some
examples are used to demonstrate both the potential and the limitations of each one of these
models and how their results, as actual evapotranspiration and soil moisture, are used to calculate
agricultural drought indices. Finally, strengths, weaknesses, and limitations of the water balance
models for drought monitoring are presented and discussed. Based on this review, it was
concluded that water balance is an indispensable tool for determining agricultural drought indices,
but choosing a given model will depend on input data availability, which is related to the complexity
of the models and errors associated with them.
Introduction
Agriculture is an economic activity that depends on several factors to be successful. According to
Diepen and Wall (1995), agricultural crop yield can be affected by factors such as abiotic (soil
water, soil fertility, soil type, and weather); crop management (soil tillage, soil depth, fertilization,
planting density, sowing date, weeding, pests, and disease control); land development (field size,
terracing, drainage, and irrigation); socio-economic (infrastructure, market, prices, and costs); and
catastrophic (flooding, frosts, hailstorms, and droughts). Among these factors, weather and
catastrophes associated with it are the most significant, since they affect crop growth, development,
yield, and quality.
Several weather parameters such as temperature, relative humidity, solar radiation, wind speed,
and rainfall can affect crop yield, but in general, temperature and rainfall are considered the most
significant (Boken et al. 2005). For a crop well adapted to a region, the interannual variability of
temperature can affect crop cycle duration, and when associated with solar radiation, relative
humidity, and wind speed, it can also affect crop water use or crop evapotranspiration. Rainfall is
the source of water for the soil, and consequently it affects water availability for crops, which
depends on the physical properties of the soil and also on the balance between water inputs and
outputs. This balance is called the water balance, and it is an accounting of all water that enters
and leaves a given volume of soil over a specified period of time, influencing the soil water content.
When the objective is to monitor and evaluate the effect of droughts on agriculture, the use of the
water balance data is essential, since it allows the determination of how much water is effectively
used by crops as a consequence of soil moisture and atmospheric demand. However, an
agricultural drought is very complex to quantify, considering several aspects from the soil-plantatmosphere
systems, such as soil water holding capacity, crop type, crop sensitivity to water stress,
crop water requirement for each one of its phenological phases, and management practices.
Moreover, taking all these aspects into account, the estimation of the water balance by models is
very complex and difficult to use in an operational system. On the other hand, very simple water
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