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\begin{document}

\title{Using the Budyko framework to evaluate the human imprint on long-term
surface water partitioning across India}



\author[1]{Anav Vora}%
\author[1]{Riddhi Singh}%
\affil[1]{Indian Institute of Technology Bombay}%


\vspace{-1em}



  
  \date{May 08, 2024}


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\selectlanguage{english}
\begin{abstract}
The Budyko curve, relating a catchment's water and energy balance,
provides a useful tool to analyse how physio-climatic and socio-economic
characteristics may impact long-term runoff. Often a parametric form of
the curve, the Fu's equation, is used to represent the catchment's
long-term water partitioning behaviour. Fu's parameter \selectlanguage{greek}ω, \selectlanguage{english}typically
derived from observed climate and runoff data, can further be related to
catchments' physio-climatic characteristics to enable understanding the
main drivers of their water balance. At times, prior analyses have
reported potentially conflicting controls of characteristics on \selectlanguage{greek}ω. \selectlanguage{english}Based
on the rationale that several hydrological processes act across varying
spatio-temporal scales, we hypothesize that the impact of a
physio-climatic factor on \selectlanguage{greek}ω \selectlanguage{english}is driven by its broader regional setting.
We test our hypothesis by developing relationships between \selectlanguage{greek}ω \selectlanguage{english}and a
curated database of 33 physio-climatic and socio-economic
characteristics for 534 regional divisions of India. We employ two
related data-space splitting algorithms: classification and regression
trees (CART) and random forest (RF) to study the effects of potential
controlling factors within their regional context. The algorithms
diagnose a hierarchy of representative vegetation, climate, soil, land
use land cover, topography and anthropogenic controls. The most
important characteristics controlling \selectlanguage{greek}ω \selectlanguage{english}were found to be: long-term
temperature, percentage of short rooted vegetation, population density,
and long-term precipitation. We show the significance of considering the
regional context by highlighting contrasting effects of two factors:
long-term temperature and the proportion of sand to silt content on \selectlanguage{greek}ω.
\selectlanguage{english}Anthropogenic activities were found to be decisive in governing the
effect of long-term temperature, indicating their influence on
hydrological processes across the Indian subcontinent.%
\end{abstract}%



\sloppy


\textbf{Using the Budyko framework to evaluate the human imprint on
long-term surface water partitioning across India}

\textbf{Running Head:} HUMAN INFLUENCES WATER PARTITIONING BUDYKO INDIA

Anav Vora\textsuperscript{1}, Riddhi Singh\textsuperscript{1,2}

\textsuperscript{1} Department of Civil Engineering, Indian Institute of
Technology Bombay, Mumbai, India

\textsuperscript{2} Interdisciplinary Programme in Climate Studies,
Indian Institute of Technology Bombay, Mumbai, India

\textbf{Keywords} : Budyko; India; Fu's parameter; CART; random forest;
human impact

\textbf{Short Informative} :

\begin{itemize}
\tightlist
\item
  Use machine learning algorithms to identify dominant factors governing
  Fu's parameter \selectlanguage{greek}ω \selectlanguage{english}across landmasses of India.
\item
  Show that the influence of a physio-climatic factor, such as
  temperature, on \selectlanguage{greek}ω \selectlanguage{english}may be governed by the broader regional setting as
  governed by other factors such as population density and cultivation.
\item
  Highlight the significance of using a classification and regression
  (CART) tree based framework to identify nested controls on the
  hydrological processes governing surface water partitioning.
\item
  Show~that anthropogenic activities are decisive in governing the
  effect of long-term temperature on \selectlanguage{greek}ω \selectlanguage{english}in heavily cultivated landmasses
  of India
\end{itemize}

\textbf{Acknowledgement:} The data sets used in the study are freely
available for academic research in the public domain. The calibrated
omega values and associated characteristics values for each regional
division along with the codes are provided
at:\emph{https://riddhisingh.weebly.com/codeanddata.html} . We
acknowledge and thank Sai Veena and Ankit Deshmukh for their assistance
with data extraction and assimilation. A previous version of this paper
exists in a publicly accessible pre-print repository at:

\emph{https://www.authorea.com/users/348666/articles/473882-using-the-budyko-framework-to-evaluate-the-human-imprint-on-long-term-surface-water-partitioning-across-india}

\textbf{Data Availability Statement:} The calibrated omega values and
associated characteristics values for each regional division along with
the codes are provided
at:\emph{https://riddhisingh.weebly.com/codeanddata.html} . The data
used to estimate various physio-climatic and socio-economic
characteristics were derived from the following resources available in
the public domain:

\begin{enumerate}
\tightlist
\item
  Temperature and precipitation daily data, India Meteorological
  Department:
  http://imdpune.gov.in/Clim\_Pred\_LRF\_New/Grided\_Data\_Download.html\#
\item
  NDVI, Global Inventory Monitoring and Modelling System's (GIMMS):
  https://ecocast.arc.nasa.gov/data/pub/gimms/3g.v0/
\item
  Settlements, Anthropogenic Biomes of the World, Version 2: 2000:
  https://doi.org/10.7927/H4D798B9
\item
  PESWC, Global plant extractable soil water capacity maps:
  https://doi.org/10.3334/ORNLDAAC/545
\item
  Topographical data (Aspect, Elevation, Slope, and SlopeTan):
  https://earthexplorer.usgs.gov/
\item
  Saturated hydraulic conductivity, GLobal HYdrogeology MaPS (GLHYMPS):
  https://doi.org/10.5683/SP2/DLGXYO
\item
  Soil composition data, SoilGrids1km: https://soilgrids.org/
\item
  Land cover data, Global Land Cover (GLC2000) maps for South Asia:
  https://forobs.jrc.ec.europa.eu/products/glc2000/products.php
\item
  Data on existing dams, Global Reservoir and Dam Database (v1.01):
  https://doi.org/10.7927/H4N877QK
\item
  Population data, Census India, 2011:
  https://censusindia.gov.in/2011census/population\_enumeration.html
\end{enumerate}

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