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Table 7.1. Stations and data periods. Nº Station Real evaporation trends Southern West Record latitude longitude period 1 Mariscal Estigarribia 22º 02' 60º 37' 1968-1999 2 Puerto Casado 22º 17' 57º 56' 1964-1999 3 Concepción 23º 25' 57º 18' 1960-1999 4 Asunción 25º 15' 57º 31' 1960-1999 5 Ciudad del Este 25º 32' 54º 36' 1966-1999 6 Encarnación 27º 20' 55º 50' 1951-1999 7 Santiago del Estero 64º 18' 27º 46' 1965-2001 8 Santa Fe 31º 36 60º 42' 1960-2001 9 Junín 34º 33' 60º 55' 1959-2001 Fig. 7.1. Geographic location of the stations. The water balance model calculates the RET and losses or gains of water in the soil, in a serial manner for every month since the beginning of the data series. Input data are monthly precipitation and potential evapotranspiration (PET). Although it is a strong simplification, the maximum water capacity (W) was assumed at 100 mm for the whole region. Depending on the Precipitation (P) and the Potential Evapotranspiration (PET) values, two situations are considered: 89
Real evaporation trends a) PET > Pi; then the water “availability” is estimated as Pi + Wi-1. If the water availability is enough, RETi = PETi. If not, RETi = Pi + Wi-1 and the difference RETi - PETi is saved as a deficit. In this case, either the atmosphere or the vegetable cover can only spend what entered as precipitation plus the quantity that they can take from the soil, which had been stored before. This can happen only up to the moment when the humidity content in the soil turns to zero. Once arrived this point, the RETi acquires the precipitation value for that month and the difference RETi - ETPi is saved as the new deficit. b) PET < Pi; in this case there is water enough, so the RETi acquires the PET value for that month, and the difference between the precipitation and RET (P - ETRi ) will storage in the soil adding to the former value: Wi = Wi-1 + (P - RETi). This happens up to the moment when the soil humidity content reaches its maximum value, which in this case was defined as 100 mm. Once arrived that moment, the difference P - RETi is saved as an excess. Figure 7.2 shows an example of the application of this methodology for one particular year. a) b) Fig. 7.2. (a) Example of the results of the model of water balance for a particular year at Junín, Argentina and (b) numeric results. 90
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CLIMATE CHANGE IN THE LA PLATA BASI
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INDEX FOREWORD . . . . . . . . . .
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7.3. Methodology . . . . . . . . .
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13.3. Regional validation of GCM fo
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1.1. Dropping the hypothesis of sta
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Introduction as they pour water ove
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A better understanding of the obser
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References Introduction Barros, V.
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ABSTRACT The hydrologic cycle of th
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La Plata basin climatology Within t
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in this last description, although
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warm season (October-April), in the
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La Plata basin climatology b. Upper
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La Plata basin climatology 2.3.3. R
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La Plata basin climatology Fig. 2.8
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2.3.7. West and South borders La Pl
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References La Plata basin climatolo
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La Plata basin climatology Robertso
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3.1. Introduction Interannual low f
Page 39 and 40: Interannual low frequency variabili
Page 41 and 42: 1989). This signal varies along eac
Page 43 and 44: Interannual low frequency variabili
Page 45 and 46: The main physiographic and hydrolog
Page 47 and 48: SUB-BASIN COUNTRY Argentina Bolivia
Page 49 and 50: the most important stretches of the
Page 51 and 52: Physiography and Hydrology The Para
Page 53 and 54: Physiography and Hydrology The Pant
Page 55 and 56: Physiography and Hydrology forcings
Page 57 and 58: Physiography and Hydrology It is no
Page 59 and 60: Physiography and Hydrology tion of
Page 61 and 62: Physiography and Hydrology INTERNAV
Page 63 and 64: 5.1. Introduction Precipitation and
Page 65 and 66: From 1956 to 1991, in most of the A
Page 67 and 68: -15 -20 -25 -30 -35 -40 -15 -20 -25
Page 69 and 70: Regional precipitation trends 5.3.2
Page 71 and 72: Regional precipitation trends and L
Page 73 and 74: trast, other regions suffer floodin
Page 75 and 76: ABSTRACT The main hydrological tren
Page 77 and 78: Following are the observed changes:
Page 79 and 80: In the case of the Paraná River th
Page 81 and 82: Hydrological trends In order to com
Page 83 and 84: Hydrological trends In table 6.1 it
Page 85 and 86: Hydrological trends On the other ha
Page 87 and 88: the central area of the high basin
Page 89: 7.1. Introduction Several authors,
Page 93 and 94: a) b) c) Mean Temperature Real evap
Page 97 and 98: The positive trends of the mean tem
Page 99 and 100: d) e) f) Mean Temperature Real evap
Page 103 and 104: 7.5. Discussion and final comments
Page 105 and 106: ABSTRACT The water, as resource, is
Page 107 and 108: puts in risk large number of person
Page 109 and 110: The main services and problems of w
Page 111 and 112: There are similar problems in diffe
Page 113 and 114: 8.3.3. Energy a. Hydroelectric depe
Page 115 and 116: (chapters 12 and 13), because of th
Page 117 and 118: The main services and problems of w
Page 119 and 120: 9.1. Introduction The emissions of
Page 121 and 122: 9.4. Greenhouse effect The atmosphe
Page 123 and 124: Temperature anomalies (°C) 0.8 0.6
Page 125 and 126: Global climatic change at a global
Page 127 and 128: In view of the unavoidability of th
Page 129 and 130: Background on other regional aspect
Page 135 and 136: Considering the non-linear interact
Page 137 and 138: SST anomalies also have influence o
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ABSTRACT The purpose of this chapte
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Global climate models Mid-1970’s
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Global climate models Table 11.1. B
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Global climate models Table 11.2. M
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Although changes in weather and cli
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Socio-economic variables and also s
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Applicability in impact assessments
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of the global climate system to the
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Climate scenarios B2: Assumes a wor
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Climate scenarios The reliability o
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Climate scenarios From Table 12.2 i
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Climate scenarios Fig. 12.5. The mu
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Climate scenarios this would be rel
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Results of global circulation model
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13.2.3. Statistical downscaling The
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La Plata basin are also considerabl
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10 N EQ 10 S 20 S 30 S 40 S 50 S 10
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Regional climatic scenarios Fig. 13
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a. Pre-industrial experiment: Initi
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Regional climatic scenarios Kalnay,
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Low-frequency variability 14.1. Bac
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egime occurred during the periods o
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Fig. 14.2. As Fig. 14.1, except for
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14.4. SST composites Low-frequency
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Low-frequency variability during th
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Fig. 14.10. As Fig. 14.9, except fo
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Low-frequency variability In genera
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Low-frequency variability Mantua, N
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15.1. Introduction Statistical anal
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Statistical analysis of extreme eve
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CURRÍCULA OF THE AUTHORS Vicente B
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Curricula of the autors Rubén Mari
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Proyect: SGP II 057: “Trends in t
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