The prediction of water resource evolution is considered to be a major challenge for the coming century, particularly in the context of climate change and increasing demographic pressure. Water resources are directly linked to the continental water cycle, and the main processes modulating changes can be represented by global hydrological models. However, anthropogenic impacts on water resources, and in particular the effects of dams-reservoirs on river flows, are still poorly known and generally neglected in coupled land surface–river routing models. This paper presents a parameterized reservoir model, DROP (Dam-Reservoir OPeration), based on Hanasaki's scheme to compute monthly releases given inflows, water demands and the management purpose. With its significantly anthropized river basins, Spain has been chosen as a study case for which simulated outflows and water storage variations are evaluated against in situ observations over the period 1979–2014. Using a default configuration of the reservoir model, results reveal its positive contribution in representing the seasonal cycle of discharge and storage variation, specifically for large-storage capacity irrigation reservoirs. Based on a bounded version of the Nash–Sutcliffe efficiency (NSE) index, called
Dams are used to provide essential services to mankind in terms of economic, environmental and social impacts. They provide water supply for domestic, industrial and irrigation needs, enable hydroelectric power generation and river navigation and prevent extreme hydrological events. There are currently more than 58 700 large dams (heights
Several studies have demonstrated the significant impact of reservoirs on river flow regimes at not only local scales, but also at larger regional and global scales: reservoirs impact the magnitude of downstream river flows and alter the temporal pattern of river discharge over the continental surface
Models developed to date which represent reservoir releases at a large scale can be categorized as data-driven and process-based approaches. The first category of models is built on the basis of observed release data, water levels and volumes. These methods range from simplified representations of reservoir operation using linear or multilinear regression
Of all the studies which have been carried out with these models, very few have been focused on Iberian Peninsula basins, where the prevailing semi-arid climate leads to a greater necessity to store water in large-capacity reservoirs, which leads to larger reservoir effects on rivers
A large number of studies can be found in the literature focusing on the sensitivity analysis of various models, in various science fields, such as machine learning
This study proposes a global and parameterized reservoir model, DROP (Dam-Reservoir OPeration), built on the basis of the generic scheme by
This paper is organized as follows: Sect.
The parameterized DROP model has been developed based on the
In order to simulate dam releases,
Schematic representation of the DROP model showing its six parameters (in blue):
The operating rules are detailed below.
First, at the beginning of each operational year, an annual release coefficient
The following steps describe how reservoir releases are computed. The provisional monthly releases,
When the DPI is above the set threshold (
In this scheme, only irrigation demand is considered. Since dams provide water for the downstream demand within a certain distance, a maximum distance,
In all possible cases, regardless of the reservoir purpose, the water released over the operational year is equivalent to the long-term mean annual inflow.
The release computed so far is provisional. The real monthly release is calculated as follows:
The modifications brought to the model from the previous version of The starting month of the operational year, which was calculated in previous versions at the level of each reservoir based on observed inflows and dam releases, is considered in this model version as a parameter, denoted as The same applies to A more explicit parameterization of the demand-controlled release ratio
A description of the reservoir model parameters is given in Table
Description of the DROP model parameters.
The reservoir volume is derived at each time step from the water balance. Boundary conditions are defined considering two possible scenarios: (i) if the reservoir is full, the excess water is spilled. (ii) When reservoir storage falls below 10 % of the capacity, the reservoir reaches the dead storage zone and water release is prevented.
In order to run the model, reservoir characteristics, such as the storage capacity and main purpose, are needed. The model also requires continuous time series of inflow and water demands to compute releases. In the current study, all of the modeled reservoirs are located in Spain, where the physical characteristics, in situ observations of natural and anthropized flows, and storage volumes are publicly available. Section
The Sobol sensitivity analysis method
The sensitivity indices,
called Sobol indices, are computed as ratios between the component variances and total variance in order to measure the contribution of each single parameter and each parameter interaction. The first-order Sobol index,
Model parameter sampling and Sobol index estimation are performed here using the open-source Python library
Spain has an estimated area of 505 983 km
The data series required as inputs to the model and the ones used to validate the outputs are taken from the Spain database. Reservoir characteristics are taken from the global GRanD database. Irrigation demands are simulated by the ISBA irrigation module. The needed input data are detailed below.
Local (Spain) database. In situ observations of natural and anthropized flow and volume data are made publicly available by the Center for Hydrographic Studies of Spain (CEDEX, Ministry of Public Works and Ministry for Ecological Transition, Spain). The national database includes the location and daily time series of discharge for 1119 gauge stations and outflows from 347 reservoirs over the period 1900–2014. The Global Reservoir and Dam (GRanD) database, from which the general characteristics of dams are taken Simulated irrigation demands. The irrigation water demands are simulated by the new irrigation scheme implemented in the ISBA LSM
Out of the 263 reservoirs listed in GRanD, only 216 were kept after cross-referencing the two databases and for which both the characteristics and time series of release and volume could be identified. In fact, two reservoirs were doubly identified in GRanD v1.3 (the IDs were 2882 and 2844) because they were rebuilt and/or renamed; their most recent characteristics are those retained. The 45 remaining reservoirs, located mainly in the northwest and south of Spain, were not identified in the Spanish database since they were built after 2014.
The maximum storage capacity of the chosen reservoirs goes from 9.5 (the San Lorenzo Mongay dam, located on the Segre River in the Ebro basin) to 3200 hm
An initial analysis conducted on observed river flows upstream and downstream of the reservoirs has identified a common seasonal behavior among those with irrigation, which is that the peak dam release is shifted in time from the natural inflow. This is due to the typical operating mode of these reservoirs, which are designed to retain water arriving upstream during winter (wet season) and release it during summer (dry season) to meet irrigation needs.
The reservoir scheme requires reservoir net inflows and water demands as inputs to estimate volume variations and outflows. In existing studies, water demands are estimated and net inflows are either modeled by a river routing scheme or estimated from gauge observations in rivers and tributaries upstream the reservoir. Reservoir abstraction is also sometimes accounted for in the reservoir water balance. However, some processes are usually neglected, such as precipitation interception, direct runoff, evaporation or groundwater exchanges. This introduces a bias into the water budget and consequently increases the model uncertainties, especially when inflows are derived from land surface and river routing models
Note that, in a future work, the DROP model aims to be coupled to a series of models that can represent these different processes. In the ISBA-CTRIP land surface–river routing model, for example
For each of the selected reservoirs, the longest continuous common periods of daily observed outflows and volumes were first determined. At this stage, only reservoirs with more than 3-year time series were retained, which leaves 215 reservoirs to be simulated. The net inflows were then derived from outflows and volume variations at the daily scale (Eq.
Main characteristics of the chosen reservoirs.
We note a good distribution of management purposes and relative inflow capacities in the final selected reservoirs. Overall, half the reservoirs are primarily used for irrigation, which is mainly due to the semi-arid climate of the Iberian Peninsula and the high needs of irrigation in the country. The rest of the reservoirs are allocated to hydropower generation, water supply and different other purposes with respective percentages of 29 %, 16 % and 5 % and are grouped in the non-irrigation reservoir category.
A sensitivity analysis with respect to the six parameters was conducted on the performance of a Nash–Sutcliffe efficiency
Summary of the DROP model parameter default values and feasible ranges for the sensitivity analysis.
The default values for
The sensitivity analysis was performed on each of the 215 reservoirs separately, distinguishing between irrigation and non-irrigation reservoirs since the number of parameters involved depends on the main purpose of the reservoir (six and four, respectively, as
Using Saltelli's quasi-random sampling method
This section presents the main results of this study. First, simulation results of the reservoir releases using the default configuration of the model are displayed. Then, a sensitivity analysis of the model parameters is presented.
Using the default parameterization with the parameters listed in Table
Results of the DROP model contribution (default configuration) in river flow modeling at reservoir outlets:
Overall, with DROP, the river flow representation is clearly improved at nearly all the reservoirs' locations. The median
The results reveal the model's positive contribution in representing the seasonal cycle of river flow, specifically for irrigation large-storage capacity reservoirs, as the model reproduces the seasonal shift between inflows and outflows caused by irrigation management rules with reasonable accuracy. For these reservoirs, the correlation between simulated and observed discharge increases from 0.49 (reference simulation) to 0.75 in the median. Regarding storage volumes, correlation reaches 0.74 in the median.
As an example, the Gonzalez Lacasa reservoir located in the Ebro basin shows typical results in Fig.
Simulation results for the Gonzalez Lacasa irrigation reservoir within the Ebro River basin over the period [1979–1994]. The monthly time series of dam releases and storage volumes are shown in panels
The improvement of the
Distribution of river flow,
The distributions of first-order Sobol indices for each parameter calculated at each of the 107 irrigation and 108 non-irrigation reservoirs are shown in Fig.
Distribution of first (
To better illustrate how each parameter individually affects the model outputs, the Gonzalez Lacasa reservoir (GRanD ID 2699;
Example of seasonal pattern sensitivity of Gonzalez Lacasa reservoir outflow to three of the DROP model parameters:
Regarding the first parameter and for values of
The influence of
The parameter
The
An example of the seasonal pattern sensitivity of the Alcantara II hydroelectricity reservoir outflow to three of the DROP model parameters:
Distribution of first (
The distributions of total sensitivity indices ST (in grey), alongside
Distribution of second-order Sobol indices (
The distributions of second-order Sobol indices for each parameter couple for the irrigation and non-irrigation reservoirs considered separately are shown in Fig.
Since
Distribution of first- (“
For low values of
When using Sobol indices, the representation of model output uncertainty is limited to the variance only, which is not fully representative of all the statistical characteristics (or moments) of the
Shifts in
The large dispersion of the conditional PDFs (colored) shows the strong impact of
The DROP model outputs are affected by several uncertainties linked to the model inputs and the algorithm.
The parameterized model is based on a generic scheme of reservoir operation, which inevitably implies a simplification in terms of water release.
Concerning the representation of operational purposes, the algorithm fails to differentiate between other purposes than irrigation and considers that a constant release is expected by the rest of the reservoirs. In addition, only the main objective of the reservoir is represented, and the releases of the multi-purpose reservoirs are not entirely represented since their management rules are more complex to describe. This explains the poor performance of the model at the level of reservoirs that are used for irrigation, though it is not their main objective: DROP is very simplistic for the rest of its possible purposes, so that the seasonal shift in water discharge is not always well reproduced. This is the case of the reservoir “Los Bermejales”, for example, a multi-purpose reservoir located in the basin of the Guadalquivir River, southern Spain, which is mainly used for water supply, but it is also used to meet irrigation water demands (Fig.
Example of time series
In addition, the model computes releases independently on each reservoir. The cascades of reservoir operations, which can be coordinated with each other, are thus not captured. More specific studies on multi-objective reservoirs
Regarding the representation of releases from non-irrigation reservoirs more generally, the scheme remains very simplistic since release policy is not driven by physical processes. In fact, operation rules of these types of reservoirs involve complex socioeconomic and political factors that are different in each country. Simulating other management purposes is mainly based on optimization algorithms, as is the case for hydro-power dam releases, for instance, where the objective functions are economically oriented (i.e., to maximize energy production;
The model provides a relatively good performance in representing irrigation reservoir operations because of its physical approach that links water releases to crop water demands. However, some simplifications are to be noted which could be improved in the future. The irrigation water demand estimation is based on the irrigation scheme in ISBA LSM, which has its own limitations
Another aspect which is not explicitly simulated in the model is water abstraction. In this study, abstractions are taken into account indirectly since the inflow is reconstructed from observations at the inlet of each reservoir. However, once the DROP model is implemented in a hydrological model, the tributary inflows will correspond to river flows simulated by the routing model, and therefore there should be a deterioration of the performance index on discharge with an error spreading along the anthropized rivers. However, by coupling the above with a model that takes irrigation into account, such as the new version of the ISBA land surface model, for example
The sensitivity analysis has revealed the most influential parameters and those that can be set using predefined values without impacting the model output uncertainty distribution. It emerged that
Actually, the sensitivity analysis undertaken in this study focused on the model sensitivity in the average representation of releases rather than on the filling levels of reservoirs since the focus of the study is on flow representation and the effect of anthropogenic factors in altering the flow dynamics along the rivers. If we were to focus on water resource availability and water management issues, the sensitivity analysis should also focus on the uncertainty in representing water storage levels in the reservoirs, considering the
Distribution of first- (“
Both
Example of seasonal pattern sensitivity of Gonzalez Lacasa
In this paper, a global parameterized model, DROP, was reconstructed based on the
The sensitivity analysis, based on Sobol's method, was conducted on the
Overall, integrating this reservoir model into LSM RRMs, which are in turn coupled to climate and Earth system models (such as the CNRM-CM and CNRM-ESM;
The DROP model and the sensitivity analysis codes are available on Zenodo. Post-processing codes are also available. All information can be found in the following repository:
The supplement related to this article is available online at:
MS, SM, AB and SR designed the study and determined the methodology. MS and SM developed the reservoir model and the sensitivity analysis algorithm. MS performed the analysis and wrote the original draft. All the authors contributed to the editing and review of the paper.
The contact author has declared that none of the authors has any competing interests.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
We would like to thank Pere Quintana-Segui from Ebro Observatory for providing the SAFRAN-based meteorological dataset for Spain which was used to force the ISBA LSM and compute irrigation demands. We also thank him for providing pre-processed products of the in situ natural and anthropized flow and volume observations over Spain.
This study is part of Malak Sadki's thesis work, co-funded by the French National Center for Space Studies (CNES) and the Occitania Region in France.
This paper was edited by Min-Hui Lo and reviewed by three anonymous referees.