Environment | Reservoir 1 (Pimental Dam)
300 250 200 150
-106
2,000 1,000 0
-1,000 -2,000
2016 2017 2018
2019 Year
2020 2021 2022 1,000 0 -1,000 2016 2017 2018
2019 Year
2020 2021 2022
100 50 0
100 80 60 40
-106 Storage Reservoir 2 (Belo Monte Dam)
Surface Area
100 50 0
Above: Figure 6. Time series of surface area change (upper panel) and storage change (lower panel) for the two reservoirs based on Landsat data and SRTM-based AEC
j
Changes in reservoir storage Using such an AEC relationship and satellite data on
Right: Figure 7. An example artefact created by potential local ground issues of smoke pocket and fog causing the surface area estimate by satellite data in the visible and NIR band to drop unphysically (the example here is for Pimental Dam)
Below: Figure 8. A mass balance approach to estimating how much water the dams of Belo Monte project are diverting
surface water extent (from Landsat) we can compute the storage change patterns of the Belo Monte reservoirs. Figure 6 shows one such variation in storage change for the Pimental Dam (reservoir 1) and Belo Monte dam (reservoir 2). There is however one cautionary tale to be shared here. On close observation, one can notice the sudden drops in surface area for no apparent reason even during times when cloud cover is minimal (Figure 7). As already mentioned, local smoke pockets and fog could be the reason for such artefacts caused by the use of satellite data in the visible and NIR
bands that the end-user must be aware of. Fortunately, such issues are being tackled by the community by employing multiple sensors and more robust methods of surface area estimation (Das et al. 2022).
How much water is being diverted? A common method for tracking how much water a
reservoir is diverting or releasing, is to apply storage changes and the inflow in a mass balance. If we ignore all other flux components of a dam such as evaporation (which can be negligible for the Amazonian region) and seepage loss, then inflow is all that we need to know to understand what the reservoirs of Belo Monte dam project are doing to the Xingu River (Figure 8). Getting the inflow is however a challenge as the
250 200 50.13 150 12.14 0.18 83.54 60.69
80 60 40 20 0
Inflow – ΔStorage = Outflow
Upstream Flow
Evaporation losses excluded; Precipitation not included
Reservoir 1 (Primental)
• Assumption: 30% of outflow is diverted to the Xingu River (de Oliveira CARVALHO et al., 2004)
Reservoir 2 (Belo Monte)
Assumptions derived from the following study:
de Oliveira CARVALHO, N., Arruda CAFE´,F., de Oliveira MOTA, G., Costa de Barros FRANCO, H., Eng, C., & -Centrais Elétricas Brasileiras, E.S. (2004). Assessment of the Sedimentation in the Reservoirs of the Belo Monte Hydrocelectric Complex, Xingu River, Brazil.
https://www.iahr.org/library/infor?pid=17352
• Receives 70% of the flow from Reservoir 1
Xingu region, to the best of our knowledge, does not have an operational streamflow measuring network at the reservoir inlets that is publicly accessible. There are two ways to mitigate this issue. The first is to use any nearby gauge information with historical flow data and ‘transfer’ that information to the inlet location of interest. The other approach is to apply a hydrologic model forced with satellite data to estimate inflow. For the sake of simplicity, we show the example of the former method that is widely used in water practice. Here, we have assumed that 70% diversion of Pimental Dam outflow to the Belo Monte reservoir according to de Oliveira et al. (2004) (Figure 8). Figure 9 shows possible outflow scenarios for the two reservoirs. The inflow was derived from gauge data available from the Global Data Runoff Center (GRDC) at Altamira. However, this location had incomplete data for the period of interest and was therefore ‘recreated’ using a more complete record from another location at Boa Sirte and by applying regression analyses. The approach has limitations and will produce significant uncertainty. Nevertheless, it is one of the more feasible ways to derive a first peek into how the reservoirs may be diverting water.
Cooling or warming? One of the water quality parameters that satellite
remote sensing can derive using the thermal IR band 30 | February 2023 |
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