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The aridity index is an invaluable tool used for estimating how dry (or how humid) a location is based on the precipitation and evapotranspiration occurring in the area. It is useful for predicting the severity of droughts, studying water availability changes due to climate change, and determining the allocation of water in resource planning.

Although it has changed over the years, the aridity index is generally defined as the precipitation (P) received in an area divided by the potential evapotranspiration (PET). This provides a value that indicates whether water supply meets demand, with lower values (<1) indicating that a place is more arid and higher values indicating it is more humid.

Although this measure of aridity has been useful for understanding climate impacts on ecosystems, agriculture, and society, it does not provide a complete picture of water availability.

Some lowland areas, such as the Okavango Delta in Botswana, appear to receive more water than what is provided by precipitation alone. Areas like this are able to sustain more plant and animal life than what would be expected with the current definition of the aridity index.

In their recent study, in Nature, hydrologists Gonzolo Miguez-Macho and Ying Fan might have figured out the solution to this problem—lateral water flow. The current model only takes precipitation—vertical water flow—into account, which works well for highland areas, but it turns out that some lowland areas are actually receiving a significant amount of water from river and groundwater flow, explaining why these areas are less arid than they should be.

"As water also flows laterally across the land, from hills to valleys and from mountains to plains, through the river network above ground and the groundwater system below ground, a climate-only water balance does not fully reflect the water availability in the receiving lowlands.

"This lateral subsidy, sometimes exceeding local P in arid lowlands, enabled large civilizations to prosper in arid plains nourished by rivers sourced in remote highlands, allowed oases and riparian ecosystems to thrive in deserts and explains why savannahs and forests can coexist under the same climate but occupying different hydrologic positions," the study authors write.

In their paper, Miguez-Macho and Fan propose a new definition of the aridity index, which they prefer to refer to as the "global humidity index," since the calculation better reflects humidity than aridity. Their new definition takes on a more two-dimensional approach by incorporating the lateral flow of rivers and groundwater, which they define as a variable called "Q-lat."

In their calculation the global humidity index is defined as GHI_topo = (P + Qlat)/PET. If there is no lateral water flow in an area Q-lat is equal to zero and gives the value of aridity (or humidity) from the prior definition.

The researchers tested out their definition of the global humidity index in a series of simulations. The simulations, which compared both global humidity indices, used climate reanalysis data and satellite vegetation data from every hour for a period spanning 15 years (2003–2018) to determine which provides more accurate models.

They found that their updated global humidity index was more in line with the real world data. They explain, "We found that GHI_topo strongly reflects the land topography, with values identical to those of the conventional GHI in uplands where the only water supply is P, but with much higher values in lowlands that also receive lateral flow."

They also found that areas where water supply meets or exceeds demand, at GHI_topo ≥ 1 is 33% greater globally than with the traditional index, but even greater in the drier, summer Mediterranean climate, at 205%. As it turned out, around 16% of land areas were receiving more than 250 mm of water from lateral sources and 11% of land areas received more than 500 mm of water from lateral sources—a significant change from precipitation alone.

This model still does not take into account human activities impacting water availability, like irrigation, dams or diversions, and has some limitations when it comes to resolution of land features, but it appears to provide a more realistic view of water flow and availability. The researchers plan on continuing to put the model to use.

They say, "Next, we plan to explore the utility of GHI_topo in explaining global vegetation dynamics and how hydrologic subsidies might shape ecosystem responses to future global environmental change."

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