| 03 Jul 2025
Groundwater storage dynamics and climate variability in the Lower Kutai Basin of Indonesia: reconciling GRACE ΔGWS to piezometry
Abstract. Groundwater is considered a climate-resilient source of freshwater yet its long-term response to climate variability remains poorly understood in environments with limited ground-based monitoring networks. In the Lower Kutai Basin (LKB) where Indonesia’s new capital (Nusantara) is under development, we examine evidence from Gravity Recovery and Climate Experiment (GRACE) satellite data, global-scale models, precipitation records, and in situ piezometric observations to investigate groundwater storage changes (ΔGWS) over the last two decades. GRACE-derived terrestrial water storage anomalies (ΔTWS) exhibit strong seasonal and interannual variability that are dominated by changes in soil moisture storage (ΔSMS). Statistical analyses reveal low to moderate correlations (r: -0.30 to -0.56) between ΔTWS, ΔSMS, ΔGWS and the El Niño-Southern Oscillation (ENSO), particularly during the 2015–2016 El Niño when ΔTWS declined at a rate of 3.8 cm/month. Downscaled ΔTWS (0.25° and 0.5°) are strongly correlated (r = 0.85 to 1) to ΔTWS at coarser spatial scales (3° mascon and the entire Borneo) despite GRACE’s native spatial resolution limitations. As a residual parameter, GRACE ΔGWS is subject to arithmetic uncertainties that arise primarily from uncertainty in GRACE products and simulated storage components. Across the 36 realizations employed in this study, ~30 % of the GRACE-derived ΔGWS estimates per realization are physically implausible, exhibiting positive values during dry periods and vice versa; main sources of uncertainty derive from estimates of ΔSMS and surface water storage anomalies (ΔSWS) in this tropical, data-sparse environment. Despite these limitations, plausible GRACE ΔGWS values generally align with groundwater-level dynamics and trends observed from available piezometric data. High-frequency (hourly) groundwater-level observations indicate that episodic, high-intensity rainfall events (>90th percentile) disproportionately contribute to groundwater recharge.
Arifin et al look at three different ways of measuring groundwater storage dynamics in the Lower Kutai Basin (LKB) of Indonesia: the GRACE budget residual approach, data from the existing (few) local piezometric sensors, and the possibility to use the sensors from pumping wells. The study is motivated by the fact that Indonesia’s new capital Nusantera is under development in the LKB which will lead to increased pressure on water resources.
The main message of the paper seems to me that currently neither of the three approaches can provide a reliable assessment of groundwater resource variability, and the government should think about rolling out a comprehensive measuring network. In my understanding the region is simply too small to be resolved well in GRACE (as the authors know very well), and there are too few in-situ sensors. The authors suggest that about 30% of their GRACE-derived dGWS ensemble timeseries are not usable since they provide unphysical results, and they discuss many timeseries with correlations about 0.3 as „weakly correlated“ – I think given that timeseries here are not very long on climate timescales we can say that such low correlation means nearly uncorrelated.
On balance, my judgement is that the topic is very relevant and there seems a pressing need to improve the monitoring system, however the quantitative evidence that is presented is a bit weak and the logic is not straightforward. It is clear that the region is not well suited for a thorough assessment of the GRACE data, or the GRACE residual approach for groundwater, since the basin is too small, the GRACE data are affected by ocean signals, and there are too few in-situ sensors. I am missing a discussion of related papers that discuss bigger inland regions of similar hydrogeophysics but better monitoring network with a similar approach. If I am right about the authors‘ intention, I am missing a much more extended discussion of how a monitoring network could look like, how many piezometers or observation wells would be needed, how could they be distributed to connect to the GRACE data. Without this I feel the paper misses a bit its mark.
Further issues
Overall, the error budgeting needs more detail and quantification. This is, as I said earlier, partly a consequence of the fact that the LKB region is a particularly challenging one for GRACE. That also means if the authors succeed to make their case, this could be a breakthrough in the application of GRACE data, so it is really worth to dig deeper. At the moment, results appear somewhat inconclusive and the message is not too clear. I suggest that the study logic – what is the underlying hypothesis, what exactly do we expect from GRACE at such small scales, why looking at the piezo-rainfall correlation, why looking at ENSO – is explained right at the start.
Best regards, Jürgen Kusche