The dependence of hydropower planning in relation to the influence of climate in Northeast Brazil.

Water scarcity in Northeast Brazil has caused latent perturbations in hydropower generation, which is undesirable for Energy Planning. Thus, this study aims to identify the influence of climate on hydropower generation by Sobradinho Dam in Bahia by: (i) assessing the streamflow climatology (1964-2017) and rainfall (1964-2015) through time series analysis, hypothesis testing and cluster analysis; (ii) assessing hydropower generation (2000-2017) using climate and energy data, through principal component analysis and dynamic regression models. The results indicated reductions of up to 30% in the mean climatological streamflow patterns; and reductions in rainfall amounts of 22.9%, 13.3% and 12.4% at latitudes 9°, 12°and 13°South, respectively. Decreasing trends were found in simulations of hydropower generation under the influence of different climate variables. Thus, the hydroelectric system operates in contingency, due to the growing energy load demand resulting in more energy imports in Northeast Brazil.

Introduction

Northeast Brazil (NEB) has experienced a period of severe water shortage, as revealed by the historical series of streamflow and useful volume of the Sobradinho reservoir in the state of Bahia [1-4]. It is difficult to conceive a natural disaster with these characteristics in Brazil, but drought is in fact a recurring hazard in this region [5, 6]. Given that the Brazilian energy mix is mainly reliant on hydrothermal generation, which supplies 63.76% of the nation’s demand, climate is of the most importance for the energy sector and for energy planning (EP) [7].

Periods of prolonged and persistent drought [6, 8] usually lead to discussions, including of a legal nature, prompting the elaboration of instruments, such as, the Brazilian Energy Reallocation Mechanism (ERM—mechanism for sharing hydrological risks [9], associated with the optimization of the National Interconnected System—NIS). This was created in 1998 by Decree 2,655. Given the impacts of the hydrological crisis caused by water scarcity [2, 10, 11], this decree aimed to apportion the risk faced by hydropower generators, which amplifies commercial issues, especially when the ERM is lower than the generated Physical Guarantee (PG—maximum amount in MW of a power plant). However, this risk-sharing model does not seem reasonable given the critical water availability conditions in NEB, which is associated with changes in the water cycle, with rising energy demand during most of operational periods, causing the need to import energy from other submarkets (division of the NIS for which specific liquidation values are established and with boundaries defined based on the presence and duration of relevant transmission restrictions on power flow) [4, 12, 13].

An important parameter for hydrological risk management is the Generation Scale Factor (GSF), which measures the monthly ratio between energy produced by the ERM generators and the sum of their PG [12, 14]. This mechanism is very sensitive to water scarcity, since it increases the risk of energy supply to the system. This occurs due to probable misconceived assumptions of the initial climate analysis [15]. In the Sinu-Caribe basin in Colombia, for example, there was an 8.5% decrease in streamflow rate and a consequent reduction of 11% in the useful volume of reservoirs due to changes in climate of the basin [16]. Designing strategies in a broader sense is extremely relevant to the formulation of actions and mechanisms to mitigate the mentioned uncertainties [17].

Water cycle fluctuations, climate change and improper land use affect several regions of the world and are key factors associated with water scarcity [5, 10, 11, 13]. In this context, the analysis of satellite data from 2012–2016 retrieved by the Gravity Recovery and Climate Experiment (GRACE) over eastern Brazil indicated future annual water reduction from precipitation of 16 mm, a worrying result for EP in a country with an energy mix predominantly composed by hydropower [13]. There is increasing doubt about how the hydropower model and water scarcity in Brazil can coexist.

In the region of the Sobradinho Reservoir, located along the lower-middle part of the São Francisco River, the following meteorological systems act [18-21] throughout the annual seasonal cycle: Intertropical Convergence Zone (ITCZ), South Atlantic Convergence Zone (SACZ); Upper Tropospheric Cyclonic Vortices (UTCV); remnants of frontal systems (FS); and the moisture convergence zone during the austral summer in NEB. These atmospheric systems are present mainly in the Southern Hemisphere (SH) summer, due to the thermodynamic characteristics of this region. The ITCZ moves below the Equator in March and April. The UTCV is present in the same period (summer) together with the SACZ, from which it originates, due to the air masses coming from the Amazon region and stationary FS coming from Southern Brazil. Therefore, given the importance of rainfall and streamflow to the maintenance of reservoirs’ useful volumes, future projections indicating a decrease in these variables, threaten energy availability [2, 10, 15, 41] and impose additional challenges for the mitigation of hydrological risks. In recent years, the atmospheric systems seem to be acting less, causing less rainfall in the São Francisco River Basin.

Thus, the objective of this study was to estimate the energy generated by hydroelectric sources in NEB in light of climatic variables, by evaluating the criticality of water. Additionally, we aimed to: (i) describe streamflow and rainfall climatology; (ii) characterize the annual and interannual seasonality of the energy and climate variables and; (iii) define the impacts of climate variables on hydroelectric generation.

Materials and methods

Study area

The study area is located at the lower, middle and upper limits of the São Francisco River Basin (SFRB) in NEB, as shown in S1 Fig, encompassing Sobradinho Reservoir in the municipality of Sobradinho, Bahia [22]. Companhia Hidroelétrica do São Francisco (CHESF) started operating the Dam in 1979 [23], which is located 40 km upstream of the city of Petrolina, Pernambuco, between longitudes 40°5′W to 42°W and latitudes 9°S to 10°S. The dam was selected for study, because it is the most important dam in NEB. It accounts for 58.2% of the total energy storage of the Northeast subsystem, with a mean regulated streamflow of 2, 060 m3.s−1. Furthermore, NEB is the second most populated and energy-consuming region of Brazil, with a climate mainly classified as semiarid tropical.

Data

Around the turn of the century, the Brazilian power sector experienced recurrent blackouts and energy rationing due to water shortages. In this context, data comprising the period from 2000 to 2017 were used to analyze the behavior of energy generation in NEB. The datasets comprised: useful volume (%) of Sobradinho Dam; hydropower generated (MWaverage) by the Sobradinho facility; imported energy (MWaverage) by the North-Northeast submarket; energy load (MWaverage) in NEB; and incremental streamflow (m3.s−1) at the Sobradinho gauge 168. This information is monitored by the National Electric System Operator (ONS) [4]. Incremental streamflow measured by gauge 168 (Q) was calculated through Eq 1, expressing the difference between inflow (Q) in Sobradinho Reservoir and the sum of outflow (Q) from the Três Marias (TM) and Queimados (QM) hydropower plants, consumptive (C) use and evaporation (E) of Sobradinho Reservoir. Monthly accumulated rainfall data (mm) were obtained from the following weather stations of the Instituto Nacional de Meteorologia (INMET) for the period 2000–2017, according to S1 Table: Thus, all stations are located between the Três Marias, Queimados and Sobradinho hydroelectric plants, covering the lower, middle and upper portions of the São Francisco River Basin.

Data on monthly sea surface temperature anomaly (SSTA)(°C) in the Tropical South Pacific Ocean (El Niño 3+4) were obtained from the National Center for Environment Prediction (NCEP) and the National Oceanic and Atmospheric Administration (NOAA) for the period 2000–2017 [24]. This information was used to account for oceanic indices and to identify their influence on EP. Furthermore, standardized Atlantic dipole data provided by NOAA [25] were used for statistical modeling. These data were calculated as the difference between the Tropical Northern Atlantic Index (TNA) measured at latitudes 5°5′N to 23°5′N and longitudes 15° W to 57°5′W and the Tropical Southern Atlantic Index (TSA) measured at latitude 20°S and longitudes 10°E to 30°W [26-29].

For the climatological analysis of hydrological variables, monthly rainfall (1964–2015—mm) and streamflow (1964–2017—m3.s−1) data were used. Accumulated rainfall data were obtained from the mentioned INMET stations and the Global Precipitation Climatology Project (GPCP) dataset [30], which provides data in a horizontal grid with 2°5′latitude x 2°5′longitude spatial resolution, developed through a combination of observational and satellite data. Incremental streamflow data at the Sobradinho gauge 168 were provided by the ONS and the Energy Research Company (EPE), part of the Ministry of Mines and Energy.

Methodology

Rainfall and streamflow climatology analysis

The purpose of this analysis was to identify possible changes in incremental discharge, as expressed by Eq 1, observed at the Sobradinho gauge 168 in relation to the historical monthly series, comprising 54 years between 1964 and 2017. Descriptive statistics—mean, variance and standard deviation—were calculated for the series. Then, the hydro model is given by G = F ⋅ H ⋅ η ⋅ η ⋅ η ⋅ ρ, where G is hydropower generation; F is the gravitational constant; (H) is the height difference between inlet and outlet; (η) is the turbine efficiency; (η) is the hydraulic efficiency; (η) is the energy generation efficiency; and (ρ) is the density of water, which are all constants in this case. Thus, hydropower generation is directly related to streamflow. After this analysis, we tested the difference between streamflow series in the years 1964–1990 and 1991–2017, using the bilateral paired t-test (Student’s t) for equal means at a significance level of α = 0.05. The parameters mean, variance and standard deviation are presented by season. In addition, the same test was also performed for the rainfall variable, but in the periods 1964–1989 and 1990–2015. where: D is the difference between variables in the analyzed periods; Q is the variable sampled in the first period; and Q is the variable sampled in the second period. where: is the variance of the difference between variables in the distinct analyzed periods. The paired t-test statistic is given by Eq 4. where: T is the paired t-test statistic. This procedure was carried out in order to identify possible changes in the mean rainfall and streamflow, which are climate variables that influence power generation.

Cluster analysis

Additionally, cluster analysis was used with GPCP data to verify in which latitudes streamflow changes were more influenced by variations of rainfall, since the São Francisco River extends throughout latitudes 9°, 10°, 11°, 12°, 13°, 14°, 15°, 16° and 17° South, and longitudes 42°, 43°, 44°, 45°, 46° and 47° West, comprising the entire SFRB. The complete linkage method was used, i.e., groups were created based on the least similar Euclidean distance values, therefore considering dissimilarities between time series in each latitude x longitude pair. where: X is the rainfall variable.

Mann-Kendall test

When changes in the streamflow series were detected, we analyzed trends and seasonality of the following variables: streamflow , for Q = 1, 2, …, n; sea surface temperature anomaly , for SSTA = 1, 2, …, n; rainfall , for P = 1, 2, …, n; useful volume of Sobradinho Reservoir , for V = 1, 2, …, n; power generation , for G = 1, 2, …, n; and energy imports , for I = 1, 2, …, n. For this purpose, the Mann-Kendall test was used, to identify monotonic trends in the time series. The test statistic is given by the sign of S, expressed by: where: S > 0 = 1, or S = 0, or S < 0 = −1. The value of z for verification of the hypothesis test for trends is given by the following relationships: or, or, In addition to the Mann-Kendall test, we also plotted the annual time series at a monthly scale.

Principal component analysis

Principal component analysis (PCA) was used to create new orthogonal datasets of the climate variables that were independent of each other. These new datasets were used for the following independent variables: (i) incremental discharge at Sobradinho gauge 168 (Q); (ii) useful volume of Sobradinho Reservoir (V); (iii) mean rainfall in the cities of the lower, middle and upper São Francisco (Ra); (iv) Tropical Atlantic Dipole (Di) and; (v) sea surface temperature anomalies in the South Tropical Pacific (SSTA) (ENSO 3+4). These variables constitute the random vector of means , where X, j is the set of independent variables i in month j. A correlation matrix (R) was used, due to the different scales of the original variables.

Diagonal of the matrix ∀ r = 1.

where: R is a correlation matrix between independent variables. Through this matrix, it was possible to generate the eigenvalues: and the eigenvectors (e) which define the linear combinations according to the PCA model described by Eq 11. These linear combinations were used to explain power generation through a dynamic regression model by principal components. where: Y are the scores of the principal components, and e and z are the linear combinations of the standardized vectors of the means of the original variables. The number of variables k is defined according to the proportion of variance of the original variables. The new dataset (scores) calculated via PCA were used as exploratory variables in the dynamic regression model for the simulation of hydroelectric power generation, which is detailed in the next section.

Dynamic regression model

The main advantage of the dynamic regression model is that it allows the use of dependent time series, including their seasonality and trends, as independent variables. In the case of using the energy generation by hydroelectric sources, as the dependent variable, we verified its applicability regarding the lag of the series in the model. The dynamic regression model (DRM) is described in Eq 12 and its parameters were estimated by the least squares method. The model allows the construction of lagged arrangements between endogenous and exogenous variables, which will produce their response after several attempts through a bottom-up process that considers the relationships between dependent and lagged explanatory variables. where: Y is the power generation dependent variable, β0 is the intercept, y is the lagged dependent variable, β and x are the coefficients and the variables used in the dynamic regression, that is, the scores of the principal components; and ϵ is the residual or stochastic term. In addition to the application of the dynamic model, the accuracy and precision of the results were verified by calculating NSE—Nash-Sutcliffe coefficient, PBIAS—percent bias, MSE—mean square error and RMSE—root mean square error.

Results and discussion

The results refletc the analysis of streamflow, energy generation and energy imports, energy load, useful volume, rainfall, Atlantic dipole and SST anomaly in the South Pacific (ENSO 3+4) based on the PCA and dynamic regression model. Furthermore, criticality of water was verified by means of descriptive statistics and the hypothesis testing of streamflow and rainfall.

Analysis of criticality of water

S2 Fig shows the annual distribution of incremental streamflow at Sobradinho gauge 168 in the period from 1964 to 2017, which was calculated between the Três Marias, Queimados and Sobradinho dams. Three indicators were verified: regulated streamflow, and its means in 1964–1990 and 1991–2017. Furthermore, an extreme event was observed in the beginning of the 1980s, when a strong El Niño took place, which might have contributed to increase rainfall and streamflow in the upper and middle São Francisco Basin. Similar behavior was observed in 1991–1992, characterized by a moderate El Niño and a positive dipole in the Atlantic. In addition, according to National Institute of Space Research (INPE) [31], there were a total of 10 occurrences of El Niño, 6 occurrences of La Niña, and 11 neutral periods from 1964 to 1990. On the other hand, 3 La Niña events, 7 El Niño events and 17 neutral periods were observed between 1991 and 2017. Improper land-use and water-use practices also increased in this second period.

S2 Fig also shows that streamflow was lower 1994 in relation to previous periods. A possible explanation is related to the increase in temperature as recently reported by the IPCC, which indicates aggravation of the severity of water stress associated with global warming [5, 10, 32, 33]. Energy rationing took place at the beginning of the century due to regional changes influenced by the Atlantic dipole and the anomalous positioning of the UTCV [18]. Streamflow in the SFRB is influenced by precipitation events both in NEB and Southeast Brazil (SEB), since its source is located in SEB and its mouth is located in NEB. Water deficit was observed in 2011–2012, 2013–2014, 2014–2015 and 2015–2016, resulting in lower accumulated rainfall, besides a gradual increase in temperature [6]. Between 2014–2015, according [8], atmospheric circulation over SEB experienced severe changes at the regional scale, including atmospheric blocking, which drastically reduced rainfall and negatively impacted water storage in the basin. [3], also reported that alterations in the atmospheric circulation, detected by using a regional dynamic model, indicated a decrease in rainfall between 2012 and 2016.

The period from 1990 to 2017, stands out, due to the occurrence of more neutral periods and not as many (50% fewer) La Niña events, which can explain rainfall heterogeneity due to interannual variability and the decrease in rainfall and streamflow rates [34]. Overall, decreases in the mean, standard deviation and variance of these variables were observed in all seasons of the year, as shown in S3 Table. Such decreases were observed, when comparing the 1964–1990 and 1991–2017 periods at 5% significance level. Mean streamflow in the 1964–1990 period was 2, 027m3 s−1, while in 1991–2017 it was 1, 428m3 s−1 (p–value < 0.001). This configures a reduction of approximately 30% in streamflow (μ < μ0). Regarding hydropower generation, it is expressed as G = F ⋅ H ⋅ η ⋅ η ⋅ η ⋅ ρ, where G is hydropower generation; F is the gravitational constant; (H) is the height difference between inlet and outlet; (η) is the efficiency of the turbine; (η) is the hydraulic efficiency; (η) is the efficiency of the energy generator; (ρ) is the density of water, which are all constants in this case. Thus, hydropower generation is directly related to streamflow, so it also decreased in terms of mean values and presented a significant negative trend, according to the Mann-Kendall test (τ = −0.93 and p–value < 0, 002).

Hydrological changes in Sobradinho Reservoir were observed through remote sensing [1]. By using the normalized difference vegetation index (NDVI) and normalized difference water index (NDWI), the authors identified an increase in soil temperature of up to 7°C and a reduction in surface water of up to 50%, when comparing 2015–2016 to 2011. [2], also corroborated this critical finding by reporting a reduction of 40% to 60% in the reservoir, which might be directly associated with rainfall levels, streamflow and useful volume management. In this sense, cluster analysis was carried out using precipitation data in 9 positions varying from 9° to 17° South latitude and 42° to 47°25’ degrees West longitude, encompassing the entire SFRB. The analysis indicated changes in mean rainfall patterns at latitudes 9°, 12° and 13° South at 5% significance level. Furthermore, lower rainfall values were observed in 1990–2015, in comparison with 1964–1990 in all other latitudes. In addition, the Mann-Kendall test indicated decreasing trends in all groups. S2 Table shows the results in the cumulative column.

Rainfall time series between 1964–2015 at latitudes 9°, 12° and 13° South encompass the cities of Paulo Afonso-BA, Sobradinho-BA, Bom Jesus da Lapa-BA and Irecê-BA, indicating a decreasing trend in precipitation by the Student t-test. The Mann-Kendall test produced the following results: latitude 9° (τ = −0.899 and p–value < 0.013); latitude 12° (τ = −0.710 and p–value < 0.049); which indicate negative trends. Reductions in streamflow are strongly related to meteorological conditions and land use. For example, rainfall reductions of up to 35% proportionally impacted streamflow rates [10, 35]. Thus, cluster analysis suggests reductions in rainfall of 22.9% at latitude 9°, 13.3% at latitude 12° and 12.9% at latitude 13°, according to S3 Fig with highlighting to latitude 9°South.

Streamflow analysis presented similar behavior, with reductions in the mean streamflow value in all seasons of the 1991–2017 period compared to the 1964–1990 period. Furthermore, variance was also lower in the second period, especially during the wet season. According to S3 Table, ENSO conditions were neutral with 62% of the time in 1991–2017, while El Niño and La Niña events were 12% and 11% less frequent, respectively.

Hydropower generation time series

S4 Fig, shows that between 2000 and 2017, the hydropower generation in NEB presented a decreasing trend. On the other hand, energy imports from the North submarket gradually increased, as can be seen in S5 Fig with trend revealed by the Mann-Kendall test (τ = 1.03 and p–value < 0.051). In relation to energy load, it trended upward related to growing demand. This energy transition is associated with operational strategies that favor importing energy from the North region, due to lower rainfall and streamflow in NEB [36, 37]. The behavior of hydropower generation depends, among other factors, on streamflow rates, which as previously seen in S2 Fig, drastically decreased in the period from 1991 to 2017.

In this context, one should also observe additional information on the variables: generation, imports, load, rainfall, SSTA in the South Pacific, Atlantic dipole and useful volume. An increase in energy imports, energy load and a substantial decrease in hydropower generation and accumulated rainfall were observed in NEB, during the last decade. At the seasonal scale, energy imports are more necessary during the wet season, not only due to energy demand and meteorological conditions in NEB, but also because it is the wet season in the northern portion of the country, which allows attenuation of the usage of hydropower storage in NEB [4, 34].

With the increase in energy load in NEB, as shown in S4 Fig, there is an urgent need to expand generation in the region, and, hence to implement alternative strategies, such as importing energy from other submarkets, due to the reduction in hydropower generation. [38] reported an increase in demand and socio-environmental conflicts related to the hydroelectric matrix [39, 40]. The authors suggested the use of mixed energy sources as a strategy to mitigate these conflicts, given the apparently irreversible persistence of this type of matrix. Energy load increases linearly and behaves quite predictably. According to data from the ONS [4], it increased by approximately 0.35% per year from 2000 to 2017, resulting in an average maximum load of roughly 11, 000 MWaverage. Currently, it is not possible to fully meet this demand using hydropower alone. Energy is imported in the most favorable rainfall and streamflow periods, coinciding with their peak values.

Rainfall time series reduced in amplitude during the 18 year period analyzed, with a negative trend estimated by the Mann-Kendall test (τ = −0.37 and p–value <0.030). This condition was directly influenced by streamflow rates, which also presented negative trends, as estimated by the Mann-Kendall test (τ = −0.44 and p–value<0.009), impacting the control of Sobradinho Dam’s volume and hydropower generation. [13], also reported reductions in rainfall amounts of up to 17% between 2012 and 2016 by analyzing GRACE data. Observational data also indicated reductions up to 22% in the same period, and 60% in 2017, coupled with a reduction of approximately 62.8% in surface water in 2017 [2]. S6 Fig shows the behavior of the useful volume time series. It represents the energy storage throughout the years, which is an independent variable controlled by the ONS. It reached peak values of 40% between 2000 and 2005, 80% between 2005 and 2012, and below 40% in the last five years of the series, with an overall negative trend estimated by the Mann-Kendall test (τ = −0.59 and p–value <0.000).

The monthly boxplot illustrated in S7 Fig describes the annual variability of rainfall. It presents the same behavior as streamflow, with critical values during winter and spring. Its distribution indicates a wet season established in the summer and autumn and a dry season established in the winter and early spring, associated with the meteorological systems that act over the region, such as the SACZ [21]; UTCV [20], FS [19]; and ITCZ [34]. Peak values occur in February and March, as a result of rainfall, consumptive uses and outflow from the Três Marias and Queimados hydropower plants. Critical periods for the operation of the electric system are in June, July, August, September and October. The useful volume for energy storage is highest in April, when it is influenced by the need to assure energy security and hydroelectric operation throughout the year, making it necessary to adopt strategies according to demand such as the use of mixed energy sources [41].

There is natural seasonality in the Atlantic dipole time series, with more positive anomalies having occurred since 2012 [26, 29]. Thus, there is an increasing trend in sea surface temperatures over the Tropical Atlantic shifting the ITCZ northward, reducing rainfall south of the Equator [27]. Although not strong enough to completely overcome the influence of Pacific temperatures, it played a major role in recent water shortages observed in NEB, as shown by the positive Atlantic dipole trends estimated by the Mann-Kendall test (τ = 0.79 and p–value <0.010). This behavior influences the zonal circulation of the atmosphere, particularly Walker’s cell, impacting hydropower generation in NEB [42, 43].

Influence of climate on energy planning

The principal components were retrieved based on the variables: energy imports, rainfall, streamflow, useful volume, Atlantic dipole and SSTA in the Tropical South Pacific. Through the correlation matrix shown in S4 Table, it was possible to obtain the eigenvalues, which indicated that the first three components explain 76% of the total variance of the original matrix. The estimated eigenvalues were: λ1 = 1.6; λ2 = 1.18 and; λ3 = 1.02. According to Eq 11, component 1 represents mostly rainfall and streamflow, component 2 describes information related mostly to useful volume and anomalies in the SST in the Pacific, and component 3 represents the Atlantic dipole.

These linear combinations (loadings) originated the new dataset that was used in the analysis of energy generation, as shown in the following series of equations:

Influence of climate on energy generation

The following variables were used in the simulations of power generation by the dynamic regression models: rainfall, streamflow, useful volume, Atlantic dipole and SSTA in the South Pacific. The results of the simulations are shown in S8 Fig.

S5 Table shows the main results of the 18-year simulations by dynamic regression considering PCA scores. The mean square error (MSE) was 716, 883.1 and the root mean square error (RMSE) was 846.68. The model presented good fit, with residuals meeting the assumptions of normal distribution around zero, absence of outliers, independence and homoscedasticity. S8 Fig shows that the behavior of the model is similar to that of actual generation. The best fit was obtained using lagged generation data and components 1, 2 and 3 of the PCA, as shown in S9 Fig and S5 Table.

The estimated β0 parameter (intercept) was 5, 750, which is approximately the mean hydropower generated in the first five years of the time series. Endogenous parameters to the energy generation model were lagged G d6 and G d13 by six and thirteen months, with coefficients of 0.28 and 0.36 for each MW generated. The generation trend (Trend G) with a negative sign was also considered in the independent variables. Furthermore, the exogenous coefficients originated from the principal components PC1, PC2 and PC3 were also taken into consideration, balancing the equation at the predictor ŷ.

Given the simulations of the model, its seasonality, trends, coefficient of determination and F statistic, the results using climate as independent variable were satisfactory. It should be mentioned that the contribution of other factors such as thermal or wind energy sources were not taken into consideration.

Conclusion

This study identified climatological and seasonal changes in streamflow, resulting in future uncertainties regarding net hydropower generation. Streamflow analysis for the period between 1991 and 2017 revealed climatological reductions of 28% in summer, 29.4% in autumn, 31.5% in winter and 31.6% in spring. Therefore, an average reduction of 30% in streamflow was observed, which directly impacted hydropower generation. Regarding rainfall, time series analysis revealed reductions in accumulated values since 1990 of 22.9%, 13.3% and 12.9% at South latitudes 9° (where Sobradinho Dam is located), 12° and 13°, respectively [30].

In the period from 1991 to 2017, more neutral years were observed [31], which contributed to the remarkable interannual variability due to the occurrence of seven El Niño events, three La Niña events and 17 neutral events. Increasing trends were also observed for SSTA in the Pacific, energy loads and energy imports, while decreasing trends were observed for hydropower generation, rainfall, streamflow and useful volume. A statistically significant decreasing trend (p–value <0.05) with coefficient of determination 0.67 was found for the simulated energy generation between 2000 and 2017, as shown in S8 Fig which is crucial for modeling of hydropower generation. Therefore, we managed to incorporate climate aspects, when inferring energy generation by hydroelectric sources. Given the importance of these climate variables for energy modeling, the use of climate patterns in statistical models is recommended. In this specific case, contingency should be considered when operating the energy system, given the decreasing generation trends.

The incorporation and expansion of other energy sources, such as wind, solar, biomass and even conventional thermal plants are recommended to compensate the hydropower deficit, which was 5, 000 MW average in the beginning of the century and 2, 000 MW average in 2017, due to the gradual reduction of streamflow and precipitation, as observed in S3, S4 and S8 Figs, besides other parameters, to avoid energy rationing or blackouts like happened in 2001. Thus, based on the critical condition of water resources, there is a need for future changes in the operational strategy regarding network infrastructure. Thus, it is necessary to increase energy imports and to incorporate other sources in the energy mix to meet the growing demand observed in NEB and in other regions, considering variables, such as exchange of energy submarkets, population growth and industrial expansion, according to [44]. Currently, there is much debate about energy transitions and these possibilities seem to be increasingly real [39, 45]. Due to the relevance of this subject, discussions should be encouraged regarding the current uses of the dam. Multiple water uses should be considered and particularly for this region, other uses, such as human consumption and large-scale irrigation could be favored besides hydropower generation.

Sobradinho Dam in Northeast Brazil.

Source: Instituto Brasileiro de Geografia e Estatística (IBGE). (https://portaldemapas.ibge.gov.br/portal.phphomepage).

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Annual time series of incremental streamflow at Sobradinho gauge 168 in Northeast Brazil between 1964 and 2017.

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Dendrogram of rainfall at latitudes 9°to 17°South and longitudes 42°to 47°West from GPCP data 2.5°x 2.5°scale in Northeast Brazil between 1964 and 2015.

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Annual time series of generation of hydro, thermal and wind energy, besides energy load and energy imports between 2000 and 2017 in Northeast Brazil.

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Monthly distribution of (a) energy generation, (b) energy imports and (c) energy load in Northeast Brazil between 2000 and 2017.

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Annual time series of the useful volume and streamflow of Sobradinho Reservoir in Northeast Brazil between 2000 and 2017.

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Monthly seasonality of the variables a) precipitation, b) water streamflow and c) useful volume between 2000 and 2017 in Northeast Brazil.

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Simulation of energy generation by the dynamic regression model, using climate variables from PCA (scores—PC1, PC2 and PC3) between 2000 and 2017 in Northeast Brazil.

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Residual analysis of the simulations by the dynamic regression model of energy generation, using PCA between 2000 and 2017 in the Northeast Brazil.

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Weather stations of INMET.

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Descriptive statistic of rainfall in Northeast Brazil between 1964 and 2015 at latitudes 9° to 17° South and longitudes 42° to 47° West (2°.5’ x 2°.5’) with 5% significance level.

All average values are in mm.

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Descriptive statistic of incremental streamflow (m3.s−1) at gauge 168 of Sobradinho Dam between 1964 and 2017 in Northeast Brazil.

Q*: Quarter.

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Correlation matrix Rij of the original variables between 2000 and 2017 in Northeast Brazil and its weights.

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Summary of the dynamic regression model for energy generation, using the scores of the PCA between 2000 and 2017 in Northeast Brazil.

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18 Dec 2020

PONE-D-20-35122

Climate and hidropower planning in the Northeast Brazil.

PLOS ONE

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If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Juan A. Añel, Ph.D.

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

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2. We suggest you thoroughly copyedit your manuscript for language usage, spelling, and grammar. If you do not know anyone who can help you do this, you may wish to consider employing a professional scientific editing service.

Whilst you may use any professional scientific editing service of your choice, PLOS has partnered with both American Journal Experts (AJE) and Editage to provide discounted services to PLOS authors. Both organizations have experience helping authors meet PLOS guidelines and can provide language editing, translation, manuscript formatting, and figure formatting to ensure your manuscript meets our submission guidelines. To take advantage of our partnership with AJE, visit the AJE website (http://learn.aje.com/plos/) for a 15% discount off AJE services. To take advantage of our partnership with Editage, visit the Editage website (www.editage.com) and enter referral code PLOSEDIT for a 15% discount off Editage services.  If the PLOS editorial team finds any language issues in text that either AJE or Editage has edited, the service provider will re-edit the text for free.

Upon resubmission, please provide the following:

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A copy of your manuscript showing your changes by either highlighting them or using track changes (uploaded as a *supporting information* file)

A clean copy of the edited manuscript (uploaded as the new *manuscript* file)

3. During your revisions, please note that a simple title correction is required, 'Climate and hydropower planning in Northeast Brazil'. You may also consider making your title more specific to the study presented. Please ensure this is updated in the manuscript file and the online submission information.

4. We note that Figure 1 in your submission contain map/satellite images which may be copyrighted. All PLOS content is published under the Creative Commons Attribution License (CC BY 4.0), which means that the manuscript, images, and Supporting Information files will be freely available online, and any third party is permitted to access, download, copy, distribute, and use these materials in any way, even commercially, with proper attribution. For these reasons, we cannot publish previously copyrighted maps or satellite images created using proprietary data, such as Google software (Google Maps, Street View, and Earth). For more information, see our copyright guidelines: http://journals.plos.org/plosone/s/licenses-and-copyright.

We require you to either (1) present written permission from the copyright holder to publish these figures specifically under the CC BY 4.0 license, or (2) remove the figures from your submission:

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We recommend that you contact the original copyright holder with the Content Permission Form (http://journals.plos.org/plosone/s/file?id=7c09/content-permission-form.pdf) and the following text:

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In the figure caption of the copyrighted figure, please include the following text: “Reprinted from [ref] under a CC BY license, with permission from [name of publisher], original copyright [original copyright year].”

4.2.    If you are unable to obtain permission from the original copyright holder to publish these figures under the CC BY 4.0 license or if the copyright holder’s requirements are incompatible with the CC BY 4.0 license, please either i) remove the figure or ii) supply a replacement figure that complies with the CC BY 4.0 license. Please check copyright information on all replacement figures and update the figure caption with source information. If applicable, please specify in the figure caption text when a figure is similar but not identical to the original image and is therefore for illustrative purposes only.

The following resources for replacing copyrighted map figures may be helpful:

USGS National Map Viewer (public domain): http://viewer.nationalmap.gov/viewer/

The Gateway to Astronaut Photography of Earth (public domain): http://eol.jsc.nasa.gov/sseop/clickmap/

Maps at the CIA (public domain): https://www.cia.gov/library/publications/the-world-factbook/index.html and https://www.cia.gov/library/publications/cia-maps-publications/index.html

NASA Earth Observatory (public domain): http://earthobservatory.nasa.gov/

Landsat: http://landsat.visibleearth.nasa.gov/

USGS EROS (Earth Resources Observatory and Science (EROS) Center) (public domain): http://eros.usgs.gov/#

Natural Earth (public domain): http://www.naturalearthdata.com/

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors analyzed the influence of climate on hydropower generation in the Sobradinho-BA dam in Brazil, during the last decades. For that, different methodologies and statistical analysis, including the evaluation of rainfall and streamflow during the last decades, as well as the simulation of hydropower generation, were developed. Authors detected a significant reduction in the hydropower generation, caused by the decrease in rainfall, and therefore, in the associated streamflow, among others. Although the manuscript has wide interest for the scientific community due to the analysis of some important implications provoked by the climate change, some parts of the manuscript need an improvement before to be published in Plos ONE. Therefore, I recommend a major revision.

1. General comment:

The manuscript is sometimes difficult to read. Overall, English needs a revision. The authors should make an effort to be more concise in some parts of the manuscript. Some examples about this are listed below:

Lines 9-14: Sentence too long. Authors should be more concise.

Lines 14-20: The text should be rephrased.

Lines 20-26: The text should be rephrased.

Lines 297-299: The text should be rephrased.

In general, writing should be revised and improved throughout the manuscript.

2. Introduction:

Lines 43-47: “In the region of the Sobradinho-BA reservoir, located at the lower-middle Sao Francisco, the following meteorological systems act [17-20] throughout the annual

seasonal cycle: the South Atlantic Convergence Zone (SACZ); upper tropospheric cyclonic vortices (UTCV); remnants of frontal systems (FS); and moisture convergence

zone during the austral summer over the NEB”. Authors should briefly explain as these meteorological systems affect the area of study.

Lines 37-38. A reference is necessary.

Lines 47-50. A reference is needed.

3. Results and discussion

Since the study is focused on the impacts of climate change, it is important that authors provide some results and projections about how the climate change will affect the area under analysis in the future. For example, in lines 313-321 authors indicate that rainfall decrease in the last years, also play a key role in the reduction of streamflow rates. In the current context of global warming, it is of crucial importance to provide some information about will be expected in the next decades. Some information about the expected future evolution of some key variables analyzed in this study, will provide a very useful information. Authors could use some local databases and related bibliography to add this information. In addition, future projections of some key variables are also available in global scale databases, as for example, the Coordinated Regional Climate Downscaling Experiment (CORDEX) or CMIP5.

Respect to the simulation of energy generation, I have some comments. Did you use a period of calibration and other period to validate the simulation? This should be specified. In addition, other parameters should be used to verify the performance of the simulation, as for example, the Nash-Sutcliffe efficiency coefficient (NSE), percent bias (PBIAS) and the ratio of the root mean square error to the standard deviation of the observed data (RSR), in order to prove the robustness of the model results.

4. Figures

Figure 1 should be improved. In the graphic presented in this image there are several mistakes that should be corrected. In addition, authors should represent the watershed in the maps.

Figure 3 caption, just below the image, is the same than in figure 2. Authors should be careful with these details.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

14 Mar 2021

Dear Reviewers,

Follow my modest review. I hope it will answer all of your answers and wishes.

Reviewer correction

The point of reviewer: Topic 3: Title – “…title more specific to the study presented”.

Answer

New title. “The dependence of the hydropower planning in relation to the influence of Climate in the Northeast Brazil“. The change of the title intend to show a dependence between climate and hydropower generation.

Short title: Hydropower crisis and the climate.

Reviewer correction

The point of reviewer: Line 9-14: Sentence too long. Authors should be more concise.

Answer

The long sentence is due to the explanatory note of the acronym ERM – Energy Reallocation Mechanism. The idea is to consider and define how big problem of the dry period is in relation to the regulation of the electrical sector of ERM, when faced with drought. Also, because we can not to place footnote in the article (template). Anyway, we reduced.

Reviewer correction

The point of reviewer: Line 14-20: The text should rephrased.

Answer

This is the same case as the one previously mentioned. The text put the meaning of the both ERM and PG – Physical Guarantee, in parenthesis. Both terms could be in footnotes, but it is not allowed. Anyway, we reduced.

Reviewer correction

The point of reviewer: Line 20-26: The text should rephrased.

Answer

Considering the risks of ERM and the commitment to honor the physical guarantee, there is an inverse condition between water availability, the demand growth curve, in addition to the need to import energy and systemic restriction problems. The paragraph highlights the problem according to the context of the theme.

Reviewer correction

The point of reviewer: Line 297-299: The text should rephrased.

Answer

The text was rephrased.

Reviewer correction

The point of reviewer: Lines 37-38: A reference is necessary.

Answer

The references were placed.

Reviewer correction

The point of reviewer: Lines 43-47: Authors should briefly explain as these meteorological systems affect the area of study.

Answer

We made the summary about the meteorological systems between lines 49-53.

Reviewer correction

The point of reviewer: Lines 47-50: A reference is necessary.

Answer

The references were placed.

Reviewer correction – 3. Results and discussion

The point of reviewer:

1. To provide some information about will be expected in next decades.

2. Authors could use some local databases and relate bibliography to add this information.

3. To use NSE, PBIAS and RSR.

Answer

1. To provide some information about the future projection, we should make dynamic numeric model of the atmosphere-ocean to capture futures scenarios, but the aim of this paper was not make a projection, but a simulations with the past dataset, using dynamic regression model. Perhaps, it will be possible in a second step of the research.

2. This work did not aim to perform dynamic numerical simulation. Also, it did not have the character of exploring climate change.

3 . The NSE, PBIAS and RSR were incorporate into the study (Lines 202-205 and in table 4).

Reviewer correction – 4. Figures

The point of reviewer:

Point 4 – Figure 1: should be improved.

Point 4 – Figures: Figure 3 - About of the descriptive caption is the same of figure 2.

Answer

Figure 1 – The figure has been corrected and improved. The review figure is attached in the site.

Figure 3 - The figure caption has been corrected. The figure is attached in the site (Plos one).

Response to e-mail received on February 19, 2021 at 2:06 pm (FIGURE 1).

The clarifications regarding Figure 1:

Figure 1 was built through free software, which any researcher can use. The QGIS is an official Open Source Geospatial Foundation project. It is a free software with friendly work environment that can be used on Windows, Linux platforms, among others.

https://www.qgis.org/en_br/site/about/index.html

The database is from IBGE - Brazilian Institute of Geography. There is also no license required. The shapes (.shp files) are made available by this federal institution. From page 41 of your manual, it explains all procedures

In Brazil, there is a specific law for this as well. Decree No.8.777 of May 11, 2016 defines open data.

https://biblioteca.ibe.gov.br/visualization/livros/liv101675.pdf

The source of shapes used for construction of Figure 1 are also available on the IBGE website, which do not require a license.

https://www.ibe.gov.br/geociencias/downloads-geociencias.html

Submitted filename: Reviewer 1_PLOS ONE_Detailed Answers.docx

Click here for additional data file.

16 Apr 2021

PONE-D-20-35122R1

The dependence of the hydropower planning in relation to the influence of Climate in the Northeast Brazil.

PLOS ONE

Dear Dr. Santos,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process, and my own comments (see below):

Line 10 - please, include a citation, and link if possible, to the ERM document.

l20-22: A parenthesis is missing

l35-39: This part of the text is confusing. Please, explain it better.

l42-43: The ITCZ and the SACZ are climatological features, not meteorological systems. Please, fix it.

l47: March, April.

l50-53: You should make more explicit the link here between the exposed phenomena and water availability in the region of study (or rainfall). Values of correlations, percentage of water attributable to each phenomenon, etc. In general, I miss a complete introductory discussion here on this issue.

l69: water storage? I wonder how you translate the potential data to 'energy' stored.

The data section does not contain enough information on your data sources. During the submission, you have included in the 'Data availability section links to climatological indexes. However, there is no information about getting the rainfall data from the INMET or where a reader can access it. The same happens with the incremental streamflow data (line 121). Please, all the data must be accessible and available to anyone. Include the relevant links and, if possible, the DOI of the dataset. You could upload the data to Zenodo to make them available and get a DOI.

l234, l237, l240, l259, l294 (and any other along the manuscript): Avoid using the 'surname et al.' citation style. You could use 'According to existing research [34]'

In the conclusions: It is confusing how to move from a 5000 MW deficit to 2000 MW is a worse scenario. It is necessary a better explanation here. Also, the statement on the need to increase energy imports is out of scope here. Please, remove it. This manuscript is not about the socioeconomics of the issue, and recommendations on the best strategy to deal with deficits of a power system would be a different discussion, involving studies on other possibilities, technologies, etc.

In this version, you uploaded your figures in the wrong order. Please, be more careful when you submit a reviewed version.

==============================

Please submit your revised manuscript by May 31 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see:  http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at  https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols .

We look forward to receiving your revised manuscript.

Kind regards,

Juan A. Añel, Ph.D.

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors respond most of the comments, improving the quality of the manuscript. However, there are still some comments that need addressing. I recommend publication in Plos ONE if such comments are addressed.

1. Materials and Methods section

Equations corresponding to the NSE, PBIAS, MSE and RMSE parameters should be included.

2. Results and discussion section

Respect to the simulation of energy generation. Did you use a period of calibration and other period to validate the simulation? This should be specified. In addition, authors should discuss in the text the performance of the simulation based also in the results obtained for NSE and PBIAS parameters.

3.

Line 21 delete the “dash”.

4.

Line 374: delete “textit”.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

1 Jul 2021

All other answer about of the e-mail received in April 16th 2021 are in response to reviewers3.pdf.

1. Materials and Methods section

Equations corresponding to the NSE, PBIAS, MSE and RMSE parameters should be included.

Answer of author: Due to the fact that they are classic equations and additional checks, we only commented on the use of this verification in the methodology, being commented on in the topic of dynamic regression model.

2. Results and discussion section

Respect to the simulation of energy generation. Did you use a period of calibration and other period to validate the simulation? This should be specified. In addition, authors should discuss in the text the performance of the simulation based also in the results obtained for NSE and PBIAS parameters.

Answer of author: We considering in the table 4 the value of precision and accuracy. The table 4 considers the values of precision and accuracy. Due to the fact of the size of the article we explored this approche less.

3.

Line 21 delete the “dash”. This problem was fix.

4.

Line 374: delete “textit”. This problem was fix.

Answer in 2021, june 17th:

1) Please upload a copy of Supporting Information Figures S1-9 and Tables S1-4 which you refer to in your text on page 13-14. The figures had been uploaded. Please, could you check what might be going wrong with the upload. About to the tables, they are in the body of the text.

Answer of email - 2021-06-22.

Attached - SUPPORT INFORMATION_tables and figures.

Submitted filename: Response to reviewers_3.pdf

Click here for additional data file.

30 Jul 2021

PONE-D-20-35122R2

The dependence of the hydropower planning in relation to the influence of Climate in the Northeast Brazil.

PLOS ONE

Dear Dr. Santos,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. The reviewer is happy with the information that you present now, but I continue having several concerns on your work, mostly about how it is presented. Therefore, we invite you to submit a revised version of the manuscript that addresses the following points raised during the review process.

First of all, you must improve the English language use along the manuscript. Indeed, I strongly recommend that a professional service reviews the paper. I have picked a few examples of corrections necessary: The Abstract can be rewritten improving readability by a lot; some lines with awkward or wrong expressions: 46, 51, 261 (existing researchers?), 265 (this researchers), 314, 378.

Lines 88-105: This information would be better placed in a Table. Please, do it.

Table 1: You must discuss and focus in the text only on the trends statistically significative and choose a value for it (p < 0.1) should be the maximum reasonable. Under this criterium, at most, three bands seem to show significative results.

Line 320: You have mentioned GRACE before in the text without including the acronym. Therefore, you should include its explanation the first time it appears, and here (line 320), you should use only the acronym.

Line 351: Please, include evidence (references?) of this behaviour since 2012.

Lines 351-353: This statement on the link between the anomalies of the Atlantic dipole and the SST must be supported by citing relevant scientific literature.

Lines 417-419: The possibility of blackouts depends on many factors. Deficit of power production is only one of them, and others can be poor transport infrastructure, lack of interconnectivity, extreme weather, etc. However, assuming the problem of decreasing hydropower production, this would be a problem if it does not meet power demand. Here you cite a paper for Ireland to justify your statement for your region of study. This does not seem right. You should clearly state the future energy consumption scenarios for the area studied and how existing planning for 'energy security' fails by not addressing expected decreasing power production from hydropower.

Please submit your revised manuscript by Sep 13 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see:  http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at  https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols .

We look forward to receiving your revised manuscript.

Kind regards,

Juan A. Añel

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: (No Response)

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: (No Response)

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: (No Response)

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

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Reviewer #1: (No Response)

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16 Sep 2021

Dear editor, follow my comments.

English review: We request the review of writing in English for an experienced article reviewer.. The same is a Native American;

Lines 88-105: We compile the information in table format;

From(Table 1)/to(Table2): We made the comments only those that showed statistical significance T;

Line 320: we carried out the correction, as directed;

Line 351:Such scientific references are considered;

Lines 351-353: the article shows the best correlations between the sst and the atlantic dipole.

Lines 417-419: Although, the first part of comment is not understood, as the article strictly refers to the analysis of the natural water resource, and its relationship with hydroelectric generation, we tried to adjust or associate it in the conclusion to the ten-year energy plan, in order to improve the written with the energy transition.

Answer to e-mail of September 6th.

As recommended, the reference from table 1 was inserted in the body of the text.

Submitted filename: Response to reviewers_3.pdf

Click here for additional data file.

11 Oct 2021

27 Oct 2021

Dear editor,

We apologize for some basic mistakes. We did a careful review with the help of a native English speaker. We also fixed links and reference positions in the body of the text. We hope that the article is now ready for acceptance. Grateful for your attention.

Submitted filename: Response to reviewers_3.pdf

Click here for additional data file.

2 Nov 2021

The dependence of hydropower planning in relation to the influence of Climate in Northeast Brazil.

PONE-D-20-35122R4

Dear Dr. Santos,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Juan A. Añel

Section Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

9 Nov 2021

PONE-D-20-35122R4

The dependence of hydropower planning in relation to the influence of climate in Northeast Brazil

Dear Dr. Santos:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Juan A. Añel

Section Editor

PLOS ONE