Horton Index: Conceptual Framework for Exploring Multi‐Scale Links Between Catchment Water Balance and Vegetation Dynamics

Groundwater evapotranspiration (GWET) is the principal component of groundwater budgets of arid basins with shallow aquifers (Loheide, 2008;Nichols, 2000), and plays an important role in the watershed-scale water balance when water table depth is comparable with the rooting depth of plants (Yeh & Famiglietti, 2009). Capillary forces move groundwater upward from the water table. Groundwater contributes to evapotranspiration (ET) through direct evaporation when the capillary zone intersects the land surface and through transpiration by root water uptake from plants (Lam et al., 2011). With the combined impacts of climate change (Mukherjee & Mishra, 2021) and increased anthropogenic groundwater withdrawal (Wada et al., 2014), the quantification of GWET becomes more crucial for sustainable groundwater management.GWET is usually estimated based on observed hydrologic variables such as streamflow and water table elevation since there is no direct measurement of GWET (Orellana et al., 2012). Daily GWET has been estimated based on base flow recession from observed streamflow (Daniel, 1976) and diurnal water table fluctuations (WTF) from observed groundwater level in unconfined aquifer (White, 1932). Particularly, the WTF method has been applied for estimating groundwater consumption by phreatophytic vegetation with shallow water table in the riparian zone of arid and semi-arid regions (e.g., Carlson Mazur et al., 2014;Diouf et al., 2020;Gribovszki et al., 2008). Besides the observed groundwater level, the WTF method requires specific yield of unconfined aquifer which depends on soil properties and water table depth, and therefore varies spatially and temporally (Orellana et al., 2012;Parajuli et al., 2019Parajuli et al., , 2020Sophocleous, 1985). The WTF method has been improved by capturing robust, diurnal WTF (Soylu et al., 2012) and by accounting for the dependence of specific yield on depth to water table (DWT;Nachabe, 2002). The estimated GWET from the WTF method is at the point or local scale, requiring a high density of observation wells to capture the spatial variability of GWET (Lautz, 2008).The estimated GWET from the WTF method provides insights into the controlling factors of GWET. These factors include meteorological variables (Kray et al., 2012), vegetation type (Butler et al., 2007

“…The black filled circles represent Horton index (

\mathrm{E}\mathrm{T}/W

), and the orange unfilled diamonds represent

{\mathrm{E}\mathrm{T}}_{G}/W

{\mathrm{E}\mathrm{T}}_{G}/W

decreases with WAI in the study watersheds, indicating that the contribution of

{\mathrm{E}\mathrm{T}}_{G}

to Horton index decreases with WAI in the water‐limited region.…”

Section: Resultssupporting

confidence: 91%

Section: Methodsmentioning

confidence: 99%

Climatic Control on Mean Annual Groundwater Evapotranspiration in a Three‐Stage Precipitation Partitioning Framework

Zhang

Yao

Geurink³

et al. 2023

“…Mean annual water balance has been an enduring research question in hydrology (Abeshu & Li, 2021; Koppa et al., 2021; Z. Li & Quiring, 2021; Meira Neto et al., 2020). Empirical equations have been developed for modeling mean annual evaporation as a function of mean annual precipitation and potential evaporation (Choudhury, 1999; Mezentsev, 1955; Ol'dekop, 1911; Pike, 1964; Schreiber, 1904; Turc, 1954).…”

Section: Introductionmentioning

confidence: 99%

Hydrological Basis of Different Budyko Equations: The Spatial Variability of Available Water for Evaporation

Yao

Wang

2022

Based on observations from a large number of catchments, Budyko (1974) hypothesized that climate aridity index (i.e., the ratio between mean annual potential evaporation and precipitation, 𝐴𝐴 𝐸𝐸 𝑝𝑝 𝑃𝑃 ) is the dominant controlling factor of evaporation ratio (i.e., the ratio between mean annual evaporation and precipitation, 𝐴𝐴 𝐸𝐸 𝑃𝑃 ). Thereafter, the function for the relationship between evaporation ratio and climate aridity index is named as Budyko curve or equation. The impacts of other factors on evaporation ratio have been studied based on this framework, such as vegetation (

“…(2019) proposed a relationship between evaporative fraction and aridity index, as an extension of the Budyko curve. In addition, Abeshu and Li (2021) developed an analytical framework of the related Horton Index to help understand the relationship between evapotranspiration, vegetation, and soil. Rajib et al.…”

Section: Introductionmentioning

confidence: 99%

“…With the help of remote-sensing data of energy fluxes, Yin et al (2019) proposed a relationship between evaporative fraction and aridity index, as an extension of the Budyko curve. In addition, Abeshu and Li (2021) developed an analytical framework of the related Horton Index to help understand the relationship between evapotranspiration, vegetation, and soil. Rajib et al (2020) explored the impact of topography and surface depressions on evapotranspiration and other hydrological processes.…”

mentioning

confidence: 99%

Data‐Guided Exploration of the Energy Partitioning at Land Surface in the Contiguous US

Chen

Wang

Sivapalan

2022

The energy and water cycles are interconnected in the Earth system and need to be represented accurately in Earth system models (Clark et al., 2015). Understanding the primary drivers of energy and water cycles is essential for hydrological studies. The fluxes of energy and water can be considered as a coupled problem (Koppa et al., 2021). This coupled water-energy system includes two partitioning relationships, namely the water partitioning of precipitation into runoff and evaporation and the energy partitioning of net radiation into sensible heat and latent heat over long timescales. Evaporation and the related latent heat flux are common to both the water and energy balance partitioning relationships, which are fundamental in hydrological systems and the Earth system in general.The water partitioning relationship has been extensively studied. One classic conceptual framework adopted for the study of long-term water partitioning is that of Budyko (1974). The Budyko curve indicates that the long-term water partitioning is primarily controlled by climate, represented by the aridity index. In the original study the Budyko framework was applied to large catchments (Budyko, 1974). In recent decades, the framework has been applied to medium sized catchments as well (e.g., Yang et al., 2006;Yin et al., 2019). Furthermore, the aridity index was originally described as a ratio between net radiation over latent heat of vaporization (R n /λ) and precipitation (P), where R n /λ represents energy supply and P represents water supply. In subsequent hydrological studies, aridity index has been usually described as a ratio between potential evaporation (E P ) and precipitation (P), in order to show the energy/water relationship explicitly in terms of water fluxes (e.g.,