DOI: 10.5061/dryad.zs7h44jgs
title: Time-series of groundwater recharge, Tiber Riber Basin, Italy from 801 CE to the present day

description: Groundwater, essential for water availability, sanitation, and achieving
 Sustainable Development Goals, is shaped by climate dynamics and complex
 hydrogeological structures. Here, we provide a time-series of groundwater
 recharge from 801 CE to the present day in the Tiber River Basin, Italy,
 using historical records and hydrological modelling. Groundwater drought
 occurred in 36% of the Medieval Climatic Anomaly (801-1249) years, 12% of
 the Little Ice Age (1250-1849) years, and 26% of the Modern Warming Period
 (1850-2020) years. Importantly, a predominant warm phase of the Atlantic
 Multidecadal Oscillation, aligned with solar maxima, coincided with
 prolonged dry spells during both the medieval and modern periods, inducing
 a reduction in recharge rates due to hydrological memory effects. This
 study enhances understanding of climate-water interactions, offering a
 comprehensive view of groundwater dynamics in central Mediterranean and
 highlighting the importance of the past for sustainable future strategies.
 Leveraging this understanding can address water scarcity and enhance basin
 resilience.
description: The dataset involves the
 collection of various climatic and hydrological data for the TRB, the
 application of Thornthwaite’s model for groundwater recharge estimation,
 and the development and validation of the HHydroREM historical model. The
 process includes calibration, delay consideration, and extensive
 statistical analysis to assess model performance. The
 dataset focuses on the Tiber River Basin (TRB) in central Italy, covering
 an area of over 17,000 km<sup>2</sup>. Data for the period
 1928–1974 were collected, including annual mean precipitation (P) and
 annual mean temperature (Tm) for the TRB. Surface runoff (Qon) data were
 obtained from the Annals Project, overseen by the Italian National
 Hydrological and Oceanographic Service. Soil-moisture storage capacity
 data were derived from statistical records (ISTAT, 2010).
 Thornthwaite’s water balance model was chosen for estimating
 groundwater recharge (GWR) rates. The model requires mean areal
 precipitation (P), mean areal temperature (T), direct runoff factor (DRO),
 and soil-moisture storage capacity (STC) as inputs. Specific parameters
 for the TRB were considered, along with adjustable parameters. The
 Thornthwaite-revised approach was calibrated by comparing its output with
 water equivalent thickness data from the GRACE-NASA MEaSUREs
 Program. The historical estimation of groundwater
 recharge (GWR(h)) was performed using a non-linear multivariate regression
 model (HHydroREM) tailored to the TRB. Monthly storm severity index
 (MSSI), snow severity index (SSI), and Palmer Drought Severity Index
 (PDSI) data were used as inputs. Model parameters were determined through
 statistical and physical evaluations, with iterative adjustments to
 achieve a meaningful correlation.<strong> </strong>The model
 was validated by comparing outputs with observed time-series data from
 specific locations in the TRB. To simulate the delay leading to
 groundwater recharge, a delayed drainage factor was estimated over the
 preceding three years. The model was validated using observed time-series
 data from the Boschetti well and Peschiera discharge in the TRB.
 Time-series data were normalized for statistical and graphical
 comparisons.  Model parameterization involved an iterative method and
 trial-and-error approach.<strong> </strong>Criteria for
 goodness-of-fit and error minimization were employed during
 parameterization.<strong> </strong>Metrics such as R2, mean
 absolute error (MAE), skewness, and kurtosis were used to assess model
 performance.<strong> </strong>Statistical and graphical
 software tools, including STATGRAPHICS, WESSA, and CurveExpert
 Professional, were used for data
 analysis.<strong> </strong>The Hurst exponent was calculated
 to estimate the rate of chaos and cyclical-trend patterns in the
 time-series data.
description: # Groundwater recharge, Tiber Riber Basin, Italy
 The dataset focuses on the
 Tiber River Basin (TRB) in central Italy and provides comprehensive
 information on groundwater dynamics from 801 CE to the present day. The
 study involves the collection of various climatic and hydrological data,
 including annual mean precipitation, annual mean temperature, and surface
 runoff, sourced from historical records and the Annals Project. The
 dataset employs Thornthwaite's water balance model to estimate
 groundwater recharge (GWR) rates in the TRB. The dataset introduces the
 HHydroREM historical model for groundwater recharge estimation,
 incorporating a non-linear multivariate regression approach. This model
 uses monthly storm severity index, snow severity index and Palmer Drought
 Severity Index data as inputs. It accounts for delayed drainage and
 simulates groundwater recharge patterns during dry spells and other
 climatic conditions. ## Description of the data and file structure The
 dataset is organized into five sheets within a spreadsheet file. The
 dataset provides a comprehensive view of the model structure and the model
 calibration and validation results, including the inputs, model
 parameters, and corresponding modeled groundwater recharge outputs in the
 first sheet. Additionally, it offers a reconstructed time-series of
 groundwater recharge values from 801 to 2020, with associated input
 variables starting from the year 789. This structure enables users to
 analyze the model's performance, understand the impact of different
 input variables, and explore the modeled groundwater recharge patterns
 over a long historical period. The 'GWR Calibration' and
 'GWR Validation' sheets compare the model estimates with the
 Thornthwaite groundwater recharge water balance (or Thornthwaite's
 surplus), while the 'GWR Extended Validation' sheet compares the
 model estimates with standardised mean values of groundwater level
 measurements made at two sites (Boschetti and Peschiera). In each sheet,
 each row corresponds to a specific year. Where necessary, specific months
 (from August to April of the following year) are represented by a column,
 each month with its corresponding values of the monthly storm severity
 index and hydrological weights in the 'GWR Modeling' and
 'GWR Reconstruction' sheets. Other factors are also shown in
 columns. The term 'n/a' used throughout the dataset indicates
 that certain information is not relevant for a particular data point.