## Loading required package: airGR
## 
## Attaching package: 'airGRiwrm'
## The following objects are masked from 'package:airGR':
## 
##     Calibration, CreateCalibOptions, CreateInputsCrit,
##     CreateInputsModel, CreateRunOptions, RunModel

The example below is inspired by the semi-distributed model developed in the ClimAware project (Theobald et al. 2014), in which we used the daily rainfall-runoff model GR4J.

The aim of this vignette is to create the semi-distributed network necessary for the hydrological model.

Semi-distributed network description

The model is distributed according to the gauging stations described in Dorchies et al. (2014).

First, we must read the list of nodes and the associated metadata:

seine_nodes <- read.table(
  file = system.file("seine_data", "network_gauging_stations.txt", package = "seinebasin"),
  sep = ";", header = TRUE, fileEncoding = "UTF-8", quote = "\"", stringsAsFactors = FALSE
)
seine_nodes
##      id_sgl id_hydro lambert2.x lambert2.y     area
## 1  TRANN_01            766626.1    2369152  1557.06
## 2  GURGY_02 H2221010   689713.0    2320549  3819.77
## 3  BRIEN_03 H2482010   695313.0    2332549  2979.77
## 4  STDIZ_04 H5071010   791113.0    2407349  2347.53
## 5  PARIS_05 H5920010   602213.0    2427449 43824.66
## 6  BAR-S_06 H0400010   751913.0    2348349  2340.37
## 7  CHAUM_07            716518.4    2241747   216.50
## 8  CUSSY_08 H2172310   726013.0    2275149   247.99
## 9  STGER_09            718512.9    2266649   402.74
## 10 GUILL_10 H2322020   731013.0    2282349   488.71
## 11 AISY-_11 H2452020   742413.0    2298149  1349.51
## 12 CHABL_12 H2342010   709613.0    2314149  1116.27
## 13 NOGEN_13            685912.9    2389349  9182.39
## 14 EPISY_14 H3621010   633413.0    2371049  3916.71
## 15 MONTE_15            645112.9    2376849 21199.39
## 16 ALFOR_16 H4340020   606013.0    2420349 30784.71
## 17 NOISI_17 H5841010   620913.0    2428949 12547.72
## 18 MONTR_18 H5752020   638013.0    2431849  1184.81
## 19 LOUVE_19 H5083050   791613.0    2393949   461.74
## 20 LASSI_20 H1362010   759513.0    2385549   876.53
## 21 CHALO_21 H5201010   747713.0    2441349  6291.55
## 22 MERY-_22 H0810010   714913.0    2390949  3899.62
## 23 COURL_23 H2721010   660813.0    2370449 10687.35
## 24 ARCIS_24 H1501010   733313.0    2394749  3594.60
## 25 VITRY_25 H5172010   768513.0    2418849  2109.14
##                          description  id_aval distance_aval
## 1                   L'Aube à Trannes ARCIS_24         68100
## 2                    L'Yonne à Gurgy COURL_23         83612
## 3  L'Armançon à Brienon-sur-Armançon COURL_23         84653
## 4            La Marne à Saint-Dizier CHALO_21         85570
## 5                   La Seine à Paris                     NA
## 6           La Seine à Bar-sur-Seine MERY-_22         79766
## 7                 L'Yonne à Chaumard GURGY_02        153074
## 8       Le Cousin à Cussy-les-Forges GURGY_02         91378
## 9               La Cure à St-Germain GURGY_02         94152
## 10               Le Serein à Guillon CHABL_12         66026
## 11    L'Armançon à Aisy-sur-Armançon BRIEN_03        102428
## 12               Le Serein à Chablis COURL_23        111781
## 13       La Seine à Nogent-sur-Seine MONTE_15         63215
## 14                  Le Loing à Épisy ALFOR_16         89196
## 15              La Seine à Montereau ALFOR_16         94475
## 16            La Seine à Alfortville PARIS_05          9263
## 17                La Marne à Noisiel PARIS_05         39384
## 18           Le Grand Morin à Montry NOISI_17         37915
## 19             La Blaise à Louvemont CHALO_21         86165
## 20             La Voire à Lassicourt ARCIS_24         43618
## 21      La Marne à Châlons-sur-Marne NOISI_17        237937
## 22         La Seine à Méry-sur-Seine NOGEN_13         49933
## 23       L'Yonne à Courlon-sur-Yonne MONTE_15         26159
## 24           L'Aube à Arcis-sur-Aube NOGEN_13         70926
## 25      La Saulx à Vitry-en-Perthois CHALO_21         38047

Using that information, we must create the GRiwrm object that lists the nodes and describes the network diagram. It is a dataframe of class GRiwrm with specific column names:

  • id: the identifier of the node in the network.
  • down: the identifier of the next hydrological node downstream.
  • length: hydraulic distance to the next hydrological downstream node.
  • model: Name of the hydrological model used (E.g. “RunModel_GR4J”). NA for other types of nodes.
  • area: Area of the sub-catchment (km2). Used for hydrological models such as GR models. NA if not used.

The CreateGRiwrm function helps to rename the columns of the dataframe and assign the variable classes.

seine_nodes$id_aval[seine_nodes$id_aval == ""] <- NA
seine_nodes$distance_aval <- as.double(seine_nodes$distance_aval) / 1000
seine_nodes$model <- "RunModel_GR4J"
# Generate the GRiwrm object
griwrm <- CreateGRiwrm(seine_nodes,
                       list(id = "id_sgl",
                            down = "id_aval",
                            length = "distance_aval"))
griwrm
##          id     down  length     area         model    donor
## 1  TRANN_01 ARCIS_24  68.100  1557.06 RunModel_GR4J TRANN_01
## 4  STDIZ_04 CHALO_21  85.570  2347.53 RunModel_GR4J STDIZ_04
## 6  BAR-S_06 MERY-_22  79.766  2340.37 RunModel_GR4J BAR-S_06
## 7  CHAUM_07 GURGY_02 153.074   216.50 RunModel_GR4J CHAUM_07
## 8  CUSSY_08 GURGY_02  91.378   247.99 RunModel_GR4J CUSSY_08
## 9  STGER_09 GURGY_02  94.152   402.74 RunModel_GR4J STGER_09
## 10 GUILL_10 CHABL_12  66.026   488.71 RunModel_GR4J GUILL_10
## 11 AISY-_11 BRIEN_03 102.428  1349.51 RunModel_GR4J AISY-_11
## 14 EPISY_14 ALFOR_16  89.196  3916.71 RunModel_GR4J EPISY_14
## 18 MONTR_18 NOISI_17  37.915  1184.81 RunModel_GR4J MONTR_18
## 19 LOUVE_19 CHALO_21  86.165   461.74 RunModel_GR4J LOUVE_19
## 20 LASSI_20 ARCIS_24  43.618   876.53 RunModel_GR4J LASSI_20
## 25 VITRY_25 CHALO_21  38.047  2109.14 RunModel_GR4J VITRY_25
## 2  GURGY_02 COURL_23  83.612  3819.77 RunModel_GR4J GURGY_02
## 3  BRIEN_03 COURL_23  84.653  2979.77 RunModel_GR4J BRIEN_03
## 12 CHABL_12 COURL_23 111.781  1116.27 RunModel_GR4J CHABL_12
## 21 CHALO_21 NOISI_17 237.937  6291.55 RunModel_GR4J CHALO_21
## 22 MERY-_22 NOGEN_13  49.933  3899.62 RunModel_GR4J MERY-_22
## 24 ARCIS_24 NOGEN_13  70.926  3594.60 RunModel_GR4J ARCIS_24
## 13 NOGEN_13 MONTE_15  63.215  9182.39 RunModel_GR4J NOGEN_13
## 17 NOISI_17 PARIS_05  39.384 12547.72 RunModel_GR4J NOISI_17
## 23 COURL_23 MONTE_15  26.159 10687.35 RunModel_GR4J COURL_23
## 15 MONTE_15 ALFOR_16  94.475 21199.39 RunModel_GR4J MONTE_15
## 16 ALFOR_16 PARIS_05   9.263 30784.71 RunModel_GR4J ALFOR_16
## 5  PARIS_05     <NA>      NA 43824.66 RunModel_GR4J PARIS_05

The diagram of the network structure is represented below with in blue the upstream nodes with a GR4J model and in green the intermediate nodes with an SD (GR4J + LAG) model.

plot(griwrm)

Observation time series

The daily mean precipitation and potential evaporation at the scale of the intermediate sub-basins are extracted from the SAFRAN reanalysis (Vidal et al. 2010).

The daily naturalized flow is provided by Hydratec (2011).

These data are embedded in the R package ‘seinebasin’, which is not publicly available.

library(seinebasin)
data(QNAT)

Generate the GRiwrm InputsModel object

The GRiwrm InputsModel object is a list of airGR InputsModel objects. The identifier of the sub-basin is used as a key in the list, which is ordered from upstream to downstream.

The airGR CreateInputsModel function is extended in order to handle the GRiwrm object that describes the basin diagram:

InputsModel <- CreateInputsModel(griwrm, DatesR, Precip, PotEvap)
## CreateInputsModel.GRiwrm: Processing sub-basin TRANN_01...
## CreateInputsModel.GRiwrm: Processing sub-basin STDIZ_04...
## CreateInputsModel.GRiwrm: Processing sub-basin BAR-S_06...
## CreateInputsModel.GRiwrm: Processing sub-basin CHAUM_07...
## CreateInputsModel.GRiwrm: Processing sub-basin CUSSY_08...
## CreateInputsModel.GRiwrm: Processing sub-basin STGER_09...
## CreateInputsModel.GRiwrm: Processing sub-basin GUILL_10...
## CreateInputsModel.GRiwrm: Processing sub-basin AISY-_11...
## CreateInputsModel.GRiwrm: Processing sub-basin EPISY_14...
## CreateInputsModel.GRiwrm: Processing sub-basin MONTR_18...
## CreateInputsModel.GRiwrm: Processing sub-basin LOUVE_19...
## CreateInputsModel.GRiwrm: Processing sub-basin LASSI_20...
## CreateInputsModel.GRiwrm: Processing sub-basin VITRY_25...
## CreateInputsModel.GRiwrm: Processing sub-basin GURGY_02...
## CreateInputsModel.GRiwrm: Processing sub-basin BRIEN_03...
## CreateInputsModel.GRiwrm: Processing sub-basin CHABL_12...
## CreateInputsModel.GRiwrm: Processing sub-basin CHALO_21...
## CreateInputsModel.GRiwrm: Processing sub-basin MERY-_22...
## CreateInputsModel.GRiwrm: Processing sub-basin ARCIS_24...
## CreateInputsModel.GRiwrm: Processing sub-basin NOGEN_13...
## CreateInputsModel.GRiwrm: Processing sub-basin NOISI_17...
## CreateInputsModel.GRiwrm: Processing sub-basin COURL_23...
## CreateInputsModel.GRiwrm: Processing sub-basin MONTE_15...
## CreateInputsModel.GRiwrm: Processing sub-basin ALFOR_16...
## CreateInputsModel.GRiwrm: Processing sub-basin PARIS_05...

Save data for next vignettes

dir.create("_cache", showWarnings = FALSE)
save(seine_nodes, griwrm, InputsModel, file = "_cache/V01.RData")

References

Dorchies, David, Guillaume Thirel, Maxime Jay-Allemand, Mathilde Chauveau, Florine Dehay, Pierre-Yves Bourgin, Charles Perrin, et al. 2014. “Climate Change Impacts on Multi-Objective Reservoir Management: Case Study on the Seine River Basin, France.” International Journal of River Basin Management 12 (3): 265–83. https://doi.org/10.1080/15715124.2013.865636.
Hydratec. 2011. “Actualisation de La Base de Données Des Débits Journaliers ‘Naturalisés’ - Phase 2.” 26895 - LME/TL.
Theobald, S., K. Träbing, K. Kehr, V. Aufenanger, M. Flörke, C. Schneider, C. Perrin, et al. 2014. ClimAware: Impacts of Climate Change on Water Resources Management. Regional Strategies and European View. Final Report.” http://irsteadoc.irstea.fr/cemoa/PUB00040932.
Vidal, Jean-Philippe, Eric Martin, Laurent Franchistéguy, Martine Baillon, and Jean-Michel Soubeyroux. 2010. “A 50-Year High-Resolution Atmospheric Reanalysis over France with the Safran System.” International Journal of Climatology 30 (11): 1627–44. https://doi.org/10.1002/joc.2003.