Abstract
The progressive desiccation of terminal lakes under global climate change represents an emerging environmental challenge with significant implications for regional climate and building energy demand. This study investigates the impact of Lake Urmia desiccation on building energy consumption across 13 cities in the Lake Urmia Basin in northwestern Iran during 2001–2023. Using MODIS land surface temperature, Landsat water-extent monitoring, MERRA-2 reanalysis, and GPM precipitation data, we generated 299 year-specific weather files for 13 cities across the Lake Urmia Basin. Year-by-year EnergyPlus simulations of representative residential and commercial building archetypes were conducted to quantify the progressive impacts of drought-induced climatic changes on heating and cooling demand. Results show that the 90% reduction in lake surface area coincided with a 1.8–2.4 °C rise in summer temperatures and a 0.8–1.2 °C increase in annual mean temperatures. A control-city analysis indicates that the majority of these temperature changes can be attributed to lake-desiccation-driven mesoscale forcing rather than generic urban or regional warming. Annual cooling energy increased by 18–35% for residential and 22–42% for commercial buildings, while heating demand declined by 8–15%, resulting in a net HVAC energy increase of 12–23%. Cities within 30 km of the former lakeshore experienced impacts 40–60% greater than those in more distant areas, confirming the spatial attenuation of lake-related climatic effects. Strong negative correlations between lake surface area and cooling energy (r = − 0.82 to − 0.91, p < 0.001) further demonstrate a robust association between lake desiccation and increasing cooling demand. The cumulative additional annual energy cost across the basin was estimated at $127–218 million, while peak cooling demand increased by 15–25%, potentially placing additional pressure on electricity-grid stability. These findings have important implications for regional energy-infrastructure planning, climate-adaptive building design, urban cooling strategies, and lake-restoration policies in semi-arid regions undergoing large-scale environmental degradation.
Abbreviations
- AOD:
Aerosol optical depth
- DTR:
Diurnal temperature range
- ETM+ :
Enhanced thematic mapper plus
- GES DISC:
Goddard Earth Sciences Data and Information Services Center
- GMAO:
Global Modeling and Assimilation Office
- GPM:
Global precipitation measurement
- GRACE:
Gravity recovery and climate experiment
- GRACE-FO:
Gravity recovery and climate experiment follow-on
- IMERG:
Integrated Multi-satellite Retrievals for GPM
- LAADS DAAC:
Level-1 and atmosphere archive & distribution system DAAC
- Landsat:
Land remote-sensing satellite
- LST:
Land surface temperature
- MERRA-2:
Modern-Era retrospective analysis for research and applications v2
- MODIS:
Moderate resolution imaging spectroradiometer
- MNDWI:
Modified normalized difference water index
- MYD11A2:
Aqua MODIS 8-day LST composite product (1 km)
- MOD04_L2:
MODIS Level-2 Aerosol product (10 km)
- MOD11A2:
Terra MODIS 8-day land surface temperature product (1 km)
- M2T1NXSLV:
MERRA-2 hourly single-level diagnostics collection
- NDWI:
Normalized difference water index
- OLI:
Operational land imager
- SWIR:
Short-wave infrared
- TM:
Thematic mapper
- TRMM:
Tropical rainfall measuring mission
- USGS:
United States Geological Survey
- CDD:
Cooling degree days
- GHI:
Global horizontal irradiance
- HDD:
Heating degree days
- PS:
Surface pressure
- QV2M:
2-Metre specific humidity
- RH:
Relative humidity
- RH2M:
2-Metre relative humidity
- SHGC:
Solar heat gain coefficient
- SWGDN:
Surface incoming shortwave radiation downward
- LWGDN:
Surface incoming longwave radiation downward
- T2M:
2-Metre air temperature
- U2M:
2-Metre eastward wind component
- V2M:
2-Metre northward wind component
- AC:
Air conditioning
- ACH:
Air changes per hour
- C1:
Commercial building archetype
- COP:
Coefficient of performance
- DOE:
U.S. Department of Energy
- EER:
Energy efficiency ratio
- EPW:
EnergyPlus weather file format
- EUI:
Energy use intensity
- HVAC:
Heating, ventilation, and air conditioning
- IAQ:
Indoor air quality
- IDF:
Input data file
- R1:
Residential Archetype 1 (pre-2000)
- R2:
Residential Archetype 2 (post-2000)
- SEER:
Seasonal energy efficiency ratio
- TMY:
Typical meteorological year
- VAV:
Variable air volume
- CV:
Coefficient of variation
- MBE:
Mean bias error
- MK:
Mann–Kendall (test)
- RMSE:
Root mean square error
- OLS:
Ordinary least squares
- R:
Pearson correlation coefficient
- R2
: Coefficient of determination
- ρ:
Spearman rank correlation coefficient
p
:P-Value
- SS:
Sen’s Slope
- AOI:
Area of interest
- DEM:
Digital elevation model
- GIS:
Geographic information system
- PM2.5
: Particulate matter ≤ 2.5 µm diameter
- PM10
: Particulate matter ≤ 10 µm diameter
- TWS:
Terrestrial water storage
- UTM:
Universal transverse mercator
- WGS 84:
World geodetic system 1984
- GEE:
Google earth engine
- GJ:
Gigajoule
- IPCC:
Intergovernmental panel on climate change
- kW:
Kilowatt
- kWh:
Kilowatt-hour
- NASA:
National Aeronautics and Space Administration
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sector.
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Maboudi Reveshti, A., Maroofiazar, R., Ebrahimpour, A. et al. Lake Urmia desiccation drives building heating and cooling energy demand in northwestern Iran.
Sci Rep (2026). https://doi.org/10.1038/s41598-026-73992-9
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DOI: https://doi.org/10.1038/s41598-026-73992-9
Keywords
- Lake desiccation
- Building energy simulation
- Urban microclimate
- EnergyPlus
- Remote sensing
- Cooling energy demand
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