3rd International Electronic Conference on Water Sciences (ECWS-3) 15 – 30 November 2018 A modified IHACRES rainfall-runoff model for predicting hydrologic response of a river basin system with a relevant groundwater component Iolanda Borzì 1, *, Brunella Bonaccorso 1 and Aldo Fiori 2 1 Department of Engineering, University of Messina, Messina, Italy 2 Department of Engineering, Roma Tre University, Rome, Italy * Correspondence: iborzi@unime.it
A modified IHACRES rainfall-runoff model for predicting hydrologic response of a river basin system with a relevant groundwater component Iolanda Borzì 1, *, Brunella Bonaccorso 1 and Aldo Fiori 2 *iborzi@unime.it Introduction A flow regime can be broadly categorized as perennial, intermittent, or ephemeral. In perennial systems, there is a permanent connection between the stream and groundwater, and good results can be obtained from rainfall-runoff models that do not explicitly represent the groundwater store. On the contrary, instead, rainfall- runoff models often fail to simulate the hydrologic connection between streams and groundwater system where it tends to be variable in time and space, as for the spatial intermittent streams. This is the case of the Alcantara river basin in Sicily region (Italy), whose upstream is intermittent, while its middle valley is characterized by perennial surface flows enriched by spring water arising from the big aquifer of the Etna Volcano, Sicily, Italy Northern sector of the Etna Volcano.
A modified IHACRES rainfall-runoff model for predicting hydrologic response of a river basin system with a relevant groundwater component Iolanda Borzì 1, *, Brunella Bonaccorso 1 and Aldo Fiori 2 *iborzi@unime.it Case Study The Alcantara river catchment is located in North Eastern Sicily, encompassing the north side of Etna Mountain, the highest active volcano in Europe. The mountain area on the right side of the river is characterized by volcanic rocks with a very high infiltration capacity. Here, precipitation and snow melting supply a large aquifer whose groundwater springs at the mid/downstream of the river, mixing with surface water coming from the left side of the basin, whose contribution follows the rainfall annual variability typical of Mediterranean climate. Groundwater resources are mainly used to supply all the municipalities located within the river catchment through local aqueducts, as well as the small towns along the Ionian coast; in addition: the Alcantara river also supplies some industries, farms and two hydroelectric power plants. This area is also a beautiful environmental reserve. Mojo ojo Alcantara 260000 310000 360000 410000 460000 510000 560000 Main Informations Table Alcantara Bas asin in 4210000 4210000 Sub ub-Basin in 4160000 4160000 Area (km 2 ) 603 342 4110000 4110000 Mean elevation (m) 531 1142 4060000 4060000 260000 310000 360000 410000 460000 510000 560000 Max elevation (m) 3274 3274 Alcantara River Basin and Min elevation (m) 0 510 Mojo Alcantara Sub-Basin
A modified IHACRES rainfall-runoff model for predicting hydrologic response of a river basin system with a relevant groundwater component Iolanda Borzì 1, *, Brunella Bonaccorso 1 and Aldo Fiori 2 *iborzi@unime.it Objectives of the Study • Development and implementation of a model able to simulate the response of the system with its groundwater component explicitly modelled as well as interactions between aquifer and streamflow. • Building up of a useful instrument for enhancement of water resources management in a complex groundwater fed catchment, the Alcantara river basin in Sicily, under different climatic and water demand scenarios. “ Gole dell’Alcantara” – Alcantara Fluvial Park, Sicily, Italy
A modified IHACRES rainfall-runoff model for predicting hydrologic response of a river basin system with a relevant groundwater component Iolanda Borzì 1, *, Brunella Bonaccorso 1 and Aldo Fiori 2 *iborzi@unime.it The IHACRES Model Rainfall and In the original version of IHACRES , firstly described by Jakeman et al. (1990), the Temperature rainfall-runoff processes are represented by two modules: a non-linear loss module that transforms precipitation to effective rainfall considering the influence of the temperature, followed by a linear module based on the classical convolution between effective rainfall Non – Linear and the unit hydrograph to derive the streamflow. Module Main advantages and capabilities of the model: Effective • It is simple, parametrically efficient and statistically rigorous Rainfall • Inputs data requirements are simple too, requiring only precipitation, temperature and streamflow Linear Module • The model provides a unique identification of system response even with only a few years of input data • The model efficiently describes the dynamic response characteristics of catchments • The model allows to obtain time series of interflow runoff with over-day storage, runoff Streamflow from seasonal aquifers and catchment wetness index • The model can be run on any size of catchment Generic Structure of IHACRES model • Simulation are quick and computational demand is low (excerpted from Jakeman, 1990)
A modified IHACRES rainfall-runoff model for predicting hydrologic response of a river basin system with a relevant groundwater component Iolanda Borzì 1, *, Brunella Bonaccorso 1 and Aldo Fiori 2 *iborzi@unime.it The Modified IHACRES Model Rainfall Temperature For Effective Rainfall estimation INPUTS r(t) T(t) NON-LINEAR MODULE Hereafter a modified version of the above synthetically described IHACRES model is presented, able to better simulate the groundwater component of s(t) s(t-1) an aquifer system. r(t)/c The structure of the modified IHACRES model includes three modules: l (1) a non linear loss module that transforms precipitation to effective u(t) Effective Rainfall rainfall by considering the influence of temperature, after this (2) a linear module based on the classical convolution between effective rainfall and x 0 u(t) x 1 u(t) For Discharge and Groundwater the unit hydrograph able to simulate the quick component of the runoff and NON-LINEAR MODULE LINEAR MODULE (3) another non linear module that simulates the slow component of the SLOW Resource estimation QUICK Tank 1 𝜇 1 runoff and that feeds the groundwater storage. From the sum of the quick Soil and the slow components (except for groundwater losses that represents q 1 (t) q 0 (t) the aquifer recharge) the total streamflow is derived. y 2 q1(t) y 1 q1(t) GW Tank 2 The need of this further non-linear module (3) arises from the necessity to 𝜇 2 Groundwater properly describe the groundwater component of the aquifer system and to model and quantify spring discharges. OUTPUTS q s (t) q r (t) Structure of the modified IHACRES model Streamflow Discharge Springs Discharge
A modified IHACRES rainfall-runoff model for predicting hydrologic response of a river basin system with a relevant groundwater component Iolanda Borzì 1, *, Brunella Bonaccorso 1 and Aldo Fiori 2 *iborzi@unime.it Structure of the Model and Equations Rainfall Temperature For Effective Rainfall estimation INPUTS r(t) T(t) NON-LINEAR MODULE 𝒒 𝟐 1 𝒗 𝒖 = 𝒕 𝒖 + 𝒕(𝒖 − 𝟐 ሻ − 𝒎 ∙ 𝒔 𝒖 If 𝑡 𝑢 + 𝑡(𝑢 − 1 ሻ > 𝑚 s(t) 𝟑 2 s(t-1) r(t)/c 𝒗 𝒖 = 𝟏 otherwise 𝑠(𝑢 ሻ 1 𝑡 𝑢 = + 1 − ∙ 𝑡(𝑢 − 1ሻ 𝑑 𝜐 𝑥 𝑈 𝑢 Where: l 20−𝑈 𝑢 ∙𝑔 𝜐 𝑥 𝑈 𝑢 = 𝜐 0 ∙ 𝑓 u(t) Effective Rainfall x 0 u(t) x 1 u(t) For Discharge and Groundwater NON-LINEAR MODULE LINEAR MODULE 𝒚 𝟏 SLOW Resource estimation QUICK 𝒓 𝟏 (𝒖ሻ = 𝒖 ∙ ∆𝒖 ∙ 𝒗 𝒖 ∙ 𝑩 ∙ ∆𝒖 Tank 1 𝑦 0 + 𝑦 1 = 1 𝜇 1 Soil Where: 𝑧 1 + 𝑧 2 = 1 q 1 (t) q 0 (t) −𝒖 ∆𝒖 𝝁 𝟐 𝒓 𝟐 (𝒖ሻ = 𝒚 𝟐 𝟐 − 𝒇 ∙ 𝒗 𝒖 ∙ 𝑩 ∙ ∆𝒖 y 2 q1(t) y 1 q1(t) 𝒖 ∙ ∆𝒖 GW Tank 2 𝜇 2 Groundwater OUTPUTS − 𝒖 ∆𝒖 q s (t) q r (t) 𝝁 𝟑 𝒓 𝒔 (𝒖ሻ = 𝒛 𝟑 𝒓 𝟐 (𝒖ሻ 𝟐 − 𝒇 𝒓 𝒕 (𝒖ሻ = 𝒓 𝟏 (𝒖ሻ + 𝒓 𝟐 𝒛 𝟐 (𝒖ሻ ∙ 𝑩 ∙ ∆𝒖 Streamflow Discharge Springs Discharge 𝒖 ∙ ∆𝒖
A modified IHACRES rainfall-runoff model for predicting hydrologic response of a river basin system with a relevant groundwater component Iolanda Borzì 1, *, Brunella Bonaccorso 1 and Aldo Fiori 2 *iborzi@unime.it Calibration of the Model The model has been calibrated on a 4-year daily streamflow discharge time series (1984-1986) at Mojo Alcantara hydrometric station. For this case study, there are no spring discharge time series available, so to work around this issue, an “A Priori” condition has been used into the calibration process. Model Calibration has been carried out in R-Studio Software using the packages “ DEoptim ” and “ hydroGOF ” . Calibration of the Model (calibration period: 1984-1986)
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