Groundwater in the Arab Middle East
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Cancel Flag comment. Subscribe to Independent Premium to debate the big issues Want to discuss real-world problems, be involved in the most engaging discussions and hear from the journalists? In one method, we sum them with equal weighting to give a true areal average of the total groundwater change in Iran. Because there are no well data from outside Iran, the final well estimates are missing those external contributions.
However, because the sensitivity kernel weights are small outside of Iran, we expect those contributions to be small. To isolate the groundwater contributions, we subtract the modeled SSCR, and show the results in Figure 3 a. This map, which represents the trend in total groundwater storage, still shows large negative values over western Iran and eastern Iraq, indicating that the contribution to the trend in TWS from the SSCR components is relatively small.
Though it should be noted that this statistical test assumes the errors are random, and normally distributed. The effects of systematic errors, due for example to errors in the hydrology model trend that has been subtracted from the GRACE results to generate Figure 3 a, are not included in this confidence level estimate. To separate the groundwater variations into naturally occurring and anthropogenic components, we subtract the CLM4.
The result, shown in Figure 4 b, represents anthropogenic groundwater variations. We note that some of the groundwater signal that's not in CLM4. We have lumped any such signal into the category of anthropogenic. Negative trends in total water storage and in naturally occurring groundwater storage are indications of drought. It is plausible that those negative trends would be accompanied by a negative anthropogenic trend, because when drought occurs in an already dry region, increased groundwater extraction can supply the precipitation deficit required to maintain agricultural productivity.
On the other hand, land surface models might not accurately reproduce changes in individual storage components, particularly in ground water, at regional scales. Therefore, it is prudent to question the accuracy of the anthropogenic groundwater trends shown in Figure 5 b. This will be discussed below. By fitting mascons to the GRACE Stokes coefficients, as described above, we derive monthly time series of mass variability for each Middle East region.
The black and red curves show results that have been smoothed to reduce subseasonal noise, by simultaneously fitting a constant, a trend, and 12 and 6 month periodic terms to the mass values across a 13 month sliding window. Note that the GRACE and model results agree well at seasonal periods, and they both show a sharp decrease in water storage that started with the onset of the drought, in The model results seem to have leveled off, and even recovered some, by Since CLM4. Figure 6 a shows our estimate of water storage variability, in gtons, for all Iran.
The black curve in Figure 5 a is the smoothed version of the blue curve in Figure 6 a. Because we have extrapolated the well data to the entire surface area of Iran, the trend from the well data represents an upper bound on the groundwater loss. We assume the GRACE measurement errors are largely uncorrelated from 1 month to the next, and estimate their contribution to the uncertainty as the 2 sigma formal error of the trend estimate. The land surface model errors are likely to have systematic components, and so are more difficult to assess.
We estimate the model uncertainty by comparing the CLM4. As mentioned above, of all the land surface models we considered, only CLM4. We estimate the hydrology uncertainty for the trend in each region as the absolute value of the difference between the CLM4. The model uncertainty and the measurement uncertainty are then added in quadrature to get the total uncertainty estimates given in Table 1.
So if the spatial pattern of the signal that is present in the in situ well data is a reasonably accurate representation of the true spatial pattern of groundwater loss, then the fact that the GRACE sensitivity kernel is not an exact kernel probably does not significantly impact the Iran results from GRACE, either. And it suggests, though does not prove, that the GRACE groundwater estimates for other countries in the region see below , where there are no in situ groundwater measurements to compare with, might be similarly unaffected by the fact that the GRACE sensitivity kernels differ from the uniformly weighted kernels.
The explanation is that the trend in total water loss in Iraq is dominated by water loss in Lake Tharthar. When the contributions from that lake are removed, the trend across Iraq is greatly diminished Figure 1 b , leaving the Iraq results shown in Figure 7 and Table 1. Anthropogenic trends during — are shown in Figure 4 b, computed by subtracting the total CLM4.
Anthropogenic groundwater loss is evident across most of the region, focused particularly in a band running across eastern Turkey, northern Iraq, and northern Iran. There are also positive trends running along the southern coastline of the Arabian Peninsula.
Groundwater in the Arab Middle East
It is reasonable to wonder if these positive features are caused by positive trends in the adjacent ocean, leaking into the solutions over land. This is of particular concern here, because we have added the ocean model predictions back to the GRACE gravity fields to remove the spurious Black Sea trend evident in Figure 1 a.
But when we compute the anthropogenic trends without adding back the ocean model predictions, the resulting map looks almost identical to Figure 4 b. Furthermore, when Figure 4 b is replotted so that the ocean is not blanked out, the positive features in Figure 4 b are seen to be centered over land. Anthropogenic increases in groundwater are certainly possible. Perhaps this is the explanation for the positive feature centered near the northern end of the Persian Gulf. Still, the presence of these apparent anthropogenic increases, combined with the difficulty of modeling the naturally occurring groundwater variability that has been subtracted from GRACE to produce the results shown in Figure 4 b, suggest caution when interpreting the apparent anthropogenic results in this region.
Trends for — are given in Table 2. The uncertainties in that table are computed in the same way as the uncertainties given in Table 1 , i. And for the model uncertainties, we use the same values used when constructing the Table 1 hydrology uncertainties, i. We are thus assuming that the level of uncertainty of the total CLM4. This would not be true if the model errors in the aquifer storage and the SSCR were correlated; due, for example, to errors in the atmospheric forcing variables. In that case, the total water storage would have larger uncertainties than the SSCR alone.
One the other hand, it is possible that errors in the aquifer storage and the SSCR could be anticorrelated; if, for example, the model erroneously put water into the soil layers instead of into the groundwater store; or vice versa. In that case, the errors of the total CLM4. So as a compromise, we assume the errors on the total CLM4.
From Table 2 , the only regions where the anthropogenic trend differs from zero by more than the uncertainty are Iran and North Saudi Arabia. Note that the GRACE water storage results decrease rapidly in , and recover slowly; but they do recover, in contrast to the results from the other regions.
Pennsylvania Water Science Center
The CLM4. One interpretation is that because eastern Turkey has a relatively high precipitation rate, its natural and anthropogenic groundwater losses can be replenished more rapidly than those in, say, Iran, where the average precipitation rates are lower. Irrigation is heavily used in the Middle East to increase agricultural productivity during times of drought. A recent drought occurring in highlighted the need for sustainable management of water resources.
When precipitation is insufficient, surface water stored in rivers, lakes, and reservoirs may provide additional water for irrigation. However, these resources are not available throughout the region, and in their absence, groundwater can be used to reduce water deficits. In many cases, groundwater resources are nonrenewable, and monitoring the rates at which they are utilized is important for planning purposes.
In this study, GRACE data are used to monitor monthly changes in total water storage groundwater plus soil moisture plus surface water and snow across the Middle East. Results from February to December show a prominent, negative trend in total water storage centered over western Iran and eastern Iraq.
This had been noted earlier by Voss et al. An analysis of in situ well data from across Iran further supports the conclusion of significant groundwater loss. These estimates represent the combined effects of natural climate variability e. Because CLM4. Although the relative uncertainty in the residual time series is higher, the results tentatively suggest that there was significant anthropogenic groundwater loss in Iran and eastern Turkey during —, much of which occurred during and after This work was conducted while G.
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Share Give access Share full text access. Share full text access. Please review our Terms and Conditions of Use and check box below to share full-text version of article. Figure 1 Open in figure viewer PowerPoint. Figure 2 Open in figure viewer PowerPoint. Figure 3 Open in figure viewer PowerPoint. Figure 4 Open in figure viewer PowerPoint. The naturally occurring trend is estimated from the CLM4. The anthropogenic trend is estimated by subtracting the CLM4. Figure 5 Open in figure viewer PowerPoint. Changes in water storage, in gton, for a all Iran and b Iraq, eastern Turkey, and northern and southern Saudi Arabia.
Figure 6 Open in figure viewer PowerPoint. Changes in water storage, for all Iran. Figure 7 Open in figure viewer PowerPoint. Changes in total groundwater storage, integrated across Iraq, eastern Turkey, and northern and southern Saudi Arabia. Lake Tharthar's variable mass is included on the Iraq time series plot, to illustrate the relative amplitude of that signal. Acknowledgments This work was conducted while G.
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