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Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
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Mapping terrestrial water storage changes in Canada using GRACE and GRACE-FO.

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Updated: Apr 12, 2026

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
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Wavelet and Gaussian Approaches for Estimation of Groundwater Variations Using GRACE Data.

Farzam Fatolazadeh1, Behzad Voosoghi2, Mehdi Raoofian Naeeni

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This study estimates groundwater storage changes in Iran using GRACE satellite data and GLDAS models. Wavelet analysis refined GRACE data for more accurate groundwater variation assessments.

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Area of Science:

  • Hydrology
  • Remote Sensing
  • Geophysics

Background:

  • Groundwater storage variations are critical for water resource management.
  • Satellite gravimetry, like GRACE, offers a method to monitor terrestrial water storage.
  • Data assimilation models like GLDAS provide essential components of the water cycle.

Purpose of the Study:

  • To develop and validate a scheme for estimating groundwater storage variations in Iran.
  • To utilize Gravity Recovery and Climate Experiments (GRACE) observations and Global Land Data Assimilation Systems (GLDAS) model outputs.
  • To refine GRACE data using advanced signal processing techniques for improved accuracy.

Main Methods:

  • Combining GRACE-derived terrestrial water storage variations with GLDAS soil moisture, snow water equivalent, and canopy water storage.
  • Applying wavelet analysis and Gaussian filtering to refine GRACE data and mitigate stripping errors.
  • Validating the estimated groundwater storage variations against pisometric well data near Urmia Lake.

Main Results:

  • The wavelet analysis approach demonstrated superior signal localization and improved the signal-to-noise ratio in GRACE data.
  • The integrated approach successfully estimated groundwater storage variations across Iran.
  • The refined estimates showed favorable agreement with in-situ pisometric well measurements.

Conclusions:

  • Wavelet analysis is an effective method for enhancing GRACE data quality in hydrological studies.
  • The presented methodology provides a reliable approach for estimating groundwater storage variations in data-scarce regions.
  • Accurate groundwater monitoring is essential for sustainable water management in Iran.