Data set for hydrodynamic lake model calibration: A deep prealpine case



[1] Hydrodynamic modeling of lakes requires an extensive amount of data that must often be measured far from the shore and throughout the water column. Accordingly, long-term comprehensive data sets for lakes are relatively rare. Lake Iseo is a deep prealpine lake, which we have monitored since 1995 on a monthly basis, collecting high-resolution data since 2011. These measurements were complemented with additional time series from surrounding meteorological stations and a comprehensive data set has been gathered for the period 1995–2012. This can be used, among other things, to test the capabilities of models to investigate the dynamics of a deep lake.

1. Introduction

[2] Eutrophication of lakes and reservoirs is one of the most widespread water quality problems both in developed and undeveloped countries [Organization for Economic Co-operation and Development, 1982; Rast et al., 1989]. Achieving good water quality targets is still a challenge in many sites worldwide. For this reason, a wide variety of lake ecosystem models have been developed and used to rationally support interdisciplinary ecosystem management strategies [e.g., Trolle et al., 2008]. Within physically based models, the hydrodynamic component is a prerequisite for the use of the ecological components.

[3] A substantial data set is needed to apply hydrodynamic models to specific study sites including: physical and chemical lake data; meteorological forcing such as wind, short-wave and long-wave radiation, air temperature and humidity; inflows and outflows discharges and temperature [Hodges, 2009]. If it is quite common that in the past decades several limnological research centers regularly conducted the physical and biogeochemical characterization of lake water, it is less common instead to find historical meteorological data to accomplish long-term simulations, as well as more recent high-resolution data for model calibration.

[4] This situation is present in Lake Iseo, a 256 m deep basin located in the northern prealpine part of Italy, which has been regularly monitored from the chemical point of view [Garibaldi et al., 1999]. No measurements, however, had ever been undertaken to investigate its internal hydrodynamics before 2009. Accordingly, we set up a gauging station network to fill this gap, collecting a full year of high-resolution data, that quantify all the heat and momentum fluxes at the lake boundaries, as well as the thermal response of the lake interior. These recent data are suitable to model the hydrodynamics of Lake Iseo over 1 year. Additionally, all the meteorological data that have been measured around the lake by a wide variety of institutional agencies since 1995 were collected, analyzed, and compared with the most recent ones. This resulted in a data set that allows the interseasonal and interannual lake thermal evolution to be modeled over a 17 year period and to be compared with the field data collected on a monthly basis at 13 depths. We are making this data set available to the scientific community in the expectation that they may be useful for testing the capability of models to reproduce the dynamics of a deep oligomictic lake [e.g., Perroud et al., 2009].

2. Data Availability, Acquisition, and Resolution

2.1. Field Site

[5] Lake Iseo is a deep, oligomictic, Italian lake located in the prealpine area of east-central Lombardy (45°44′N 10°04′E) at 185 m a.s.l., which represents well the features of other large lakes located south of the Alps. The lake covers a surface area of 60.9 km2, has a maximum depth of 256 m and is characterized by steep banks and a large island that separates the central plateau from the eastern 100 m deep channel (see Figure 1). At the southwest extreme, the Oglio River exits the basin (RL3 in Figure 1), and in the northern end two main inflows enter, the Oglio River and the “Industrial Canal” (respectively, RL1 and RL2 in Figure 1). The Oglio River drains a wide mountain catchment and the Industrial Canal is diverted from the Oglio River 10 km upstream from its mouth. On the south the Lake is open to a plain, while high mountains and several lateral valleys are present on both the eastern and western sides, strongly influencing the thermally driven wind field [Valerio et al., 2012]. Lake Iseo was historically classified as warm monomictic, but underwent a process of progressively deep deoxygenation starting from the end of the 1980s. Only two complete overturns have occurred in the last 20 years, as documented by the oxygen data here provided.

Figure 1.

Geographical setting of Lake Iseo (top left inset), bathymetry, represented with isodepth lines at 30 m spacing, and location of the measurement stations: thermistor chain (TC), wind stations (WS), land stations (LS), lake diagnostic system (LDS), river logger (RL), and sampling site (S1). The bottom left WGS84 coordinates are 573067 E, 5054053 N.

2.2. Lake Bathymetry

[6] The Regione Lombardia geological mapping program, in collaboration with the Istituto Nazionale di Oceanografia e Geofisica Sperimentale of Trieste, made a geophysical study in 2002 and 2004 of Lake Iseo, acquiring multibeam data of the lake bottom with a Simrad EM3000 Echo Sounder [Bini et al., 2007]. The original data, acquired with nominal accuracy of 5 cm RMS, have been averaged over a regular grid (20 m × 20 m) to create a digital elevation model of the lake bathymetry, which is here provided in an ASCII format.

2.3. High-Resolution Lake and Meteorological Data

[7] A Lake Diagnostic System (LDS) [Imberger, 2004] was moored in the northern part of the lake (see Figure 1), measuring the main thermal, radiative, and mechanical fluxes on the lake surface. This floating station consisted of meteorological sensors (wind speed and direction, net total (NR) and incoming short-wave (SWR) radiation, air-temperature and relative humidity) located 2.5 m above the water level. The temperature of the first 50 m of the water column was monitored with ±0.01°C accuracy by a submerged thermistor chain, equipped with 21 nodes whose depth ranged from 0.25 to 49.75 m. During summer 2011, an analogous thermistor chain monitored the temperature profile in the southern basin (TC in Figure 1) with 16 sensors located between 4 and 36 m of depth. Two additional wind stations, also measuring atmospheric pressure, were installed to account for the spatial variability of the wind field: WS1 on the lake shore close to the LDS and WS2 on the southern shore (see Figure 1). Regarding the inflows density, two river loggers have been placed near the inflow to the lake of the two main incoming tributaries (RL1 and RL2) to measure the water temperature and conductivity fluctuations at 1 min intervals. Details of the deployment and features of the measurement stations are synthesized in Table 1. Daily lake level, inflow and outflow discharge, as well as hourly outflow temperature, are available from Consorzio dell'Oglio, providing a full year (18 June 2011 to 18 June 2012) of hydro and thermodynamic high-resolution data for Lake Iseo.

Table 1. Measured Parameters, Instrumentation, and Record Lengtha
ParameterStationInstrumentModelRangeAccuracyLogging IntervalRecord Length
  1. a

    Abbreviations are as follows: T, temperature; DO, dissolved oxygen; Cond, conductivity (at a reference temperature of 25°C); WS, wind speed; WDIR, wind direction; APR, atmospheric pressure; SWR, short wave radiation; Net TR, net total radiation; and RH, relative humidity.

Lake water data
Water TS1T sensorWTW IDS 9250 to 50 °C 13 depths: 0 to 250 m±0.2 °Cmonthly02/95-06/12
Water TLDSThermistor chainPME T-chain0 to 36 °C 21 depths: 0 to 50 m±0.01 °C120 s01/11-present
Water TTCThermistor chainPME T-chain0 to 36 °C 16 depths: 4 to 36 m±0.01 °C20 s07/11-10/11
DOS1Optical DO sensorWTW IDS 9250 to 20 mg l-1± 0.5 %monthly02/95-06/12
CondS1RadiometerCDM 830.2 to 1.3 × 106μS cm-1 monthly02/95-06/12
Inflows and outflows data
Water TRL1T loggerRBR TR-1060-5 to 35 °C±0.002 °C60 s02/09-07/11
Water TRL2
Water TRL1T loggerYSI 600LS-5 to 50 °C±0.15°C180 s05/11-06/12
Water TRL205/11-present
Water TRL3T sensorCampbell 107-35 to 50 °C±0.2 °C30 min05/05-present
CondRL1Cond loggerYSI 600LS0 to 100 mS cm-1±0.5% or 1 μS cm-1180 s05/11-06/12
CondRL1RadiometerCDM 830.2 to 1.3 × 106μS cm-1 ∼15 d06/95-05/07, 01/00-12/00
Meteorological data
WSLS1Cup tacho-anemometerLastem C100S0 to 60 m s-1±0.1 m s-1 or 1%3600 s01/95-present
WSLS2DigitEco Vo0110 to 50 m s-1±0.1 m s-1 01/95-04/99; 06/01-present
WSLDSMechanical wind sensorYoung 051010 to 100 m s-1±0.3 m s-1 or 1%120 s06/11-09/12
WSWS160 s04/10-present
WSWS260 s05/10-present
WDIRLS1Gonio-anemometerLastem C100D0 to 360 °±2 °3600 s01/95-present
WDIRLS2DigitEco Vd0110 to 360 °±0.1 ° 09/08-present
WDIRLDSMechanical wind sensorYoung 051010 to 360 °±3 °120 s06/11-10/12
WDIRWS160 s04/10-present
WDIRWS260 s05/10-present
Air TLS1RH and T probeLastem DMA585-30 to 70 °C±0.2 °C3600 s01/95-present
Air TLDSVaisala HMP45A-40 to 60 °C±0.1 °C120 s01/11-09/12
Air TWS1T loggerCampbell 107-35 to 50 °C±0.2 °C60 s04/10-present
APRWS1BarometerSetra 278600 to 1100 mbar±0.5 mbar60 s04/10-present
SWRLS1PyranometerLastem DPA554300 to 3000 nm<5%3600 s01/95-present
SWRLDSCampbell LI200X-COR400 to 1100 nm±3%120 s04/11-10/12
Net TRLDSPyrradiometerMiddleton CN1-R-Net0,3 to 60 μm±5%120 s04/11-07/12
RHLS1RH and T probeLastem DMA5850 to 100 %±1.5% (5-95%), ±2% (<5% >95%)3600 s01/95-present
RHLDSVaisala HMP45A0.8 to 100 %±2% (0-90%), ±3% (90-100%)120 s01/11-09/12
RainLS1Rain gaugeLastem C101A 0.2 mm3600 s01/95-present

2.4. Past Lake Data

[8] The chemical characterization of lake water has been regularly conducted through monthly measurements at S1 (Figure 1), one of the deepest points of the lake. Since 1995 the Dipartimento delle Scienze dell'Ambiente del Territorio of the Università degli Studi di Milano has measured the Secchi depth, has collected samples through a Van Dorn bottle at depths 0, 1, 3, 5, 10, 20, 30, 50, 75, 100, 150, 200, and 245 m and has measured the samples' conductivity, oxygen, and temperature by an automatic probe (see Table 1), so providing a time series of these parameters over 17 years.

2.5. Past Meteorological Data

2.5.1. Radiation at the Lake Surface

[9] Several meteorological stations have been installed by government agencies around the lake to provide a general-purpose meteorological monitoring of the area. Among them, LS1 is a complete meteorological station (see details of the equipment in Table 1), located in Costa Volpino close to the lake's northern shore. This station has been used to build the 1995–2012 series of rain, air temperature, relative humidity, and short-wave radiation, because these variables are representative of the on-lake conditions. Since some data are occasionally missing, the time series was corrected and completed with data measured by analogous weather stations present in the surrounding areas (mainly LS2), after verifying the quality and compatibility of these data through a careful comparison. In absence of direct measurement, incoming long-wave radiation was calculated as a function of the cloud cover factor (CCF) data measured at the closest airport (Bergamo Orio al Serio) using standard correlations [e.g., Henderson-Sellers, 1984] as:

display math(1)

where math formula is the air temperature, math formula is the albedo for long-wave radiation, math formula the air emissivity, and math formula the Stefan-Boltzmann constant.

2.5.2. Wind

[10] With regard to the wind, care is needed when using land measurements for lake studies, especially in this site where a considerable spatial variability of the wind field has been observed to be induced by the topography [Valerio et al., 2012]. The LDS station clearly shows that the wind speed on the lake has a pronounced daily periodicity, characterized by two distinctive maxima, corresponding to the two preferential directions, north-north-east and south. Four conditions occur during a typical day: (1) wind blowing northerly from 22:00 h to 06:00 h, (2) calm between 06:00 h and 11:00 h, (3) wind blowing southerly from 11:00 h to 18:00 h, and (4) calm between 18:00 h and 22:00 h. Wind data measured over land strongly underestimate the wind speed on the lake and capture some wind flows better than others, depending on their position. LS1 station measures accurately the wind from the south, while it is sheltered from the northerly wind. LS2 station, instead, is exposed to the northerly wind only. Accordingly, in order to reproduce the wind on the lake surface where both southerly and northerly winds are present, an equivalent wind series has been produced by using the LS2 data for time band 1 and the LS1 data for the remaining time bands. Monthly wind multiplication factors (WMF) were calculated for each time bands (1–4) in 1 year long overlapping period (see Table 2). These factors were used as a basis for obtaining a whole time series of wind intensities fully representative of conditions over the lake. WMF values are consistent with similar analysis reported in the literature [e.g., Hornung, 2002; Shimizu et al., 2007]. These values may be of interest also for other lakes where no on-lake measurements are available. Here we provide both the original time series of the two stations and the modified wind intensities, which we used for lake modeling.

Table 2. Wind Monthly Multiplication Factorsa
  1. a

    The multiplication factors were calculated for the four time bands ((1) 22:00–06:00 h, (2) 06:00–11:00 h, (3) 11:00–18:00 h, (4) 18:00–22:00 h).

LS2 (1)
LS1 (2)
LS1 (3)
LS1 (4)

2.5.3. Inflows and Outflows

[11] The daily-averaged level of the lake surface and the discharges of the outflow and of the two main inflows are provided by Consorzio dell'Oglio, a private authority that manages the water released from Lake Iseo at the Sarnico Dam (see RL3 in Figure 1). The same authority has measured the outflow temperature at Sarnico since 2005, while the inflow temperature was not recorded before 2009, but only during occasional samplings. Accordingly, we used the data measured at RL1 and RL2 to supplement this missing information with air temperature correlations [e.g., Rueda et al., 2006]. Following the approach proposed by Smith [1981], air temperature Ta at the LS1 land station was found to be the variable with the strongest correlation with the mean daily water temperature Tw in Oglio (R2 > 0.9), especially when subdivided into 2 periods (I: 1/03–22/06 and II: 23/06–28/02). The temperature of the Industrial Canal (RL2), although very well correlated for the whole year with the temperature of the Oglio, is on average 2.2°C lower. Accordingly, we determined the coefficients of the linear equations to predict the Oglio (RL1) temperature from the daily-averaged LS1 air temperature, and then temperature of the Industrial Canal (RL2) from the Oglio's one:

display math(2)

[12] The standard deviation of the RL1 and RL2 temperature error was 0.66°C and 0.54°C, respectively.

[13] With regard to the inflows conductivity, before 2011 we had measured it twice a month for 3 years at RL1 and RL2 locations. These data provide a reasonable indication of the average conductivity of the inflowing water, as confirmed by the comparison with the more recent conductivity data.

[14] Following the explained procedure, we were able to build a complete meteorological data set suitable for lake modeling during the period when no on-lake data were available (1995–2010).

3. Example of Use of Data

[15] The primary use of the data set presented in this paper is the calibration of dynamic lake simulation models. Figure 2 summarizes some of the modeling results that we obtained using these data. The historical time series collected in RL, LS, and S1 are suitable for the 1-D modeling of the interseasonal and interannual lake temperature variability (see Figure 2c). In this context, the oxygen profiles collected in S1 may be used to verify the capability of the models in reproducing the interannual mixing variations in an oligomictic study case. Besides, the 1 year long, well-resolved data set allows for the 3-D simulations of more local phenomena with shorter time scales. RL, LDS, TC, WS, and S1 data may be used to reproduce the deepening of the thermocline in spring, the path of the Oglio River entering the lake (see Figure 2a) or the temporal and spatial structure of the basin-scale internal waves (see Figure 2b).

Figure 2.

Example of modeling results obtained by using the presented data set: (a) 3-D simulation (ELCOM model) of the path of Oglio River, compared with the results of a physical model (see Pilotti et al. [2013], for details); (b) 3-D simulation (ELCOM model) of the thermal structure at LDS and TC location, aimed to reproduce the basin-scale internal waves pattern (see Valerio et al. [2012], for details); and (c) 1-D simulation (DYRESM model) of the multiannual evolution of the average temperature in the upper 50 m of the lake water column.

4. Data Access

[16] Data are accessible in the internet, mainly as ASCII files downloadable at the following site (, where a detailed description of each file is also provided. Data are identified by the acronym of the measuring instrument as shown in Figure 1 and subdivided into four main categories: bathymetric data; inflows and outflow data; meteorological data; and lake data.

5. Summary

[17] This paper presents to the scientific community a comprehensive set of data for Lake Iseo, a deep, morphologically complex, prealpine lake. Meteorological, radiation, and discharge data allow the major forcings acting on the lake to be computed. Temperature, dissolved oxygen, and conductivity profiles allow an analysis of the interseasonal and interannual lake evolution. This data set can be used for scientific or teaching purposes because it allows a complete thermal and hydrologic balance of a lake. On the other hand, complex processes such as internal waves activity can be observed and analyzed. We believe that the main use of the data set can be that of providing a useful benchmark for hydrodynamic models of lakes. We hope that this effort will also foster additional interest and study of Lake Iseo.


[18] We gratefully acknowledge Consorzio dell'Oglio for providing the time series of water level, inflows discharge, and outflow discharge and temperature, Prof. Letizia Garibaldi for the historical series of lake data, Regione Lombardia for the lake bathymetry, and Charlie Hodge for his contribution in reviewing the manuscript. We also acknowledge the use of the models (DYRESM-ELCOM) developed by the Centre for Water Research, University of Western Australia. This research was partly funded by Kulturisk project.