Modeling of GRACE-Derived Groundwater Information in the Colorado River Basin

Abstract

Groundwater depletion has been one of the major challenges in recent years. Analysis of groundwater levels can be beneficial for groundwater management. The National Aeronautics and Space Administration’s twin satellite, Gravity Recovery and Climate Experiment (GRACE), serves in monitoring terrestrial water storage. Increasing freshwater demand amidst recent drought (2000–2014) posed a significant groundwater level decline within the Colorado River Basin (CRB). In the current study, a non-parametric technique was utilized to analyze historical groundwater variability. Additionally, a stochastic Autoregressive Integrated Moving Average (ARIMA) model was developed and tested to forecast the GRACE-derived groundwater anomalies within the CRB. The ARIMA model was trained with the GRACE data from January 2003 to December of 2013 and validated with GRACE data from January 2014 to December of 2016. Groundwater anomaly from January 2017 to December of 2019 was forecasted with the tested model. Autocorrelation and partial autocorrelation plots were drawn to identify and construct the seasonal ARIMA models. ARIMA order for each grid was evaluated based on Akaike’s and Bayesian information criterion. The error analysis showed the reasonable numerical accuracy of selected seasonal ARIMA models. The proposed models can be used to forecast groundwater variability for sustainable groundwater planning and management.

Climatological Drought Forecasting Using Bias Corrected CMIP6 Climate Data: A Case Study for India

“…The risks of drought are rising as a result of the depletion of the available surface and subsurface water resources. The social and economic well-being of a country is highly impacted by the effects of drought [1][2][3]. In developing countries, this impact is severe since their economies are based on agricultural products [4].…”

Future Changes in Water Supply and Demand for Las Vegas Valley: A System Dynamic Approach based on CMIP3 and CMIP5 Climate Projections

“…This study assumes a constant groundwater contribution and evaporation loss in the future due to the difficulty in assessing the future groundwater condition in LVV under the changing climate. However, this assumption cannot be entirely justified, especially for long-term decision making, as it has been shown by previous studies that the change in precipitation trends, changes in subsurface conditions, and many other factors severely affect the status of groundwater [71,72]. Rise in temperature due to climate change in the future will tend to increase evaporation loss, resulting in reduced storage.…”

Spatio-Temporal Groundwater Drought Monitoring Using Multi-Satellite Data Based on an Artificial Neural Network

“…GRACE satellites provide an unprecedented opportunity to capture the variability of TWSC. Generally, the GRACE-based TWSC data comprises vertically integrated water storages of all columns of a region, which represents the sum of soil moisture, groundwater, surface water, snow, and ice (Equation 4; [7][8][9][10][11][34][35][36]). Vegetation effects (canopy, wetland, etc.)…”