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"Assessment the impact of climate change over sediments yields in the Cesar river basin M.Sc. Karen Milena Ch Advisor: Prof. Dr. Rer. nat. Manfred Koch Department of Geohydraulics and Engineering Hydrology University of Kassel 29.01.13 1

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Location of study area 2 Area Cesar District 22.925km2 Population: 43.94 Hab/Km2 Capital : Valledupar 365.548 Hab Temperature: 28C Location: 074116 105214 N 725327 740828 W Main ecosystems: Sierra Nevada de Santa Marta: (5300 -1230 m.a.s.l) Serrana de Perij:(750 -1350 m.a.s.l) Valley of River Cesar: (500- 950 m.a.s.l) Cienaga de la zapatosa: :(50 -200 m.a.s.l) Main characteristics of the Cesar region: Important roll for the economic in the region (cotton crop, mining, livestock) Intensive agricultural practices Existence of hydro meteorological and soil use information for the area. Table 1:Charactetistic of study area Serrania de Perija Sierra nevada de Santa Marta Valley of River Cesar Cienaga de la Zapatosa

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Stament of the problem For the district of Cesar, one of the most important water resources is the Cesar river. One of the major environmental problems in the region has been the massive deforestation of most of the forests to make way for agricultural uses that may lead to ecological imbalances. 3

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From the point of view of agriculture, inadequate use of natural resources, such as the use of mechanization without the prior classification of the agro-ecological zone. In an area, as the Cesar basin, which is rich in topographical and soil physiological conditions, erosion and sedimentation could occur in several ways. Schumacher T.E, et al. (1999), states that net soil loss from tillage erosion occurs on slope lands as a result of gravity acting on moving soil. 4

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According to a study of climate modeling in Colombia conducted by Pabn J.D, (2006), in the Cesar region the trend of air temperature might increase 0.17 C per decade, and the trend of precipitation 1.46% per decade for that region. From the agricultural point of view, the United Nations system in its review of risks and opportunities associated with climate change states that the effects associated with this phenomenon could be the aridity, soil erosion, desertification and changes in the hydrological regime as well as increased risk of flooding in agricultural production affecting crops. 5

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The main objective The main objective of this research is to assess the impact of climatic change over sedimentation yield in the Cesar basin, which is located in the Cesar district in northern of Colombia using SWAT (Soil Water Assessment Tool) model. Specific objectives: Establish the historical behavior of climatic and hydrological variables in the basin of the Cesar River. Evaluate sedimentation yield in the basin under climate change. 6

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SWAT Model 1 Soil Water Assessment Tool SWAT is a physically based, watershed-scale, continuous time, distributed-parameter hydrologic model that uses spatially distributed data on topography, land use, soil, and weather for hydrologic modeling and operates on a daily time step (Arnold et al., 1998; Arnold and Fohrer, 2005). Based on topography, this model subdivides a watershed into a number of subbasins for modeling purposes. In latina Amrica SWAT has been used in countries as: Mxico 2 ; Brasil 3, Colombia 4 ; Repblica Dominicana 5 Venezuela 6 7 1 http://swat.tamu.edu/software/swat-model/http://swat.tamu.edu/software/swat-model/ 2(Torres B. et al., 2005; Johannes,2004), 3(Machado, 2002; Machado et al., 2003; Neves et al., 2006), 4 (Millan and Isaza, 2002); (Oate and Aguilar, 2003) 5 (Camacho et al.,2003) 6 (Silva, 2004). The soilwater balance is the primary equation used in the SWAT model, which is represented as: SW :soil content, R, Q, ET, P and QR are daily precipitation, runoff, evapotranspiration, percolation and return ow, respectly. Sed :sediment yield on a given day (metric tons) Qsurf : the surface runoff volume (mm/ha) q : the peak runoff rate (m3/s), Khru is the Universal Soil Loss Equation (USLE), CUSLE, PUSLE, LSUSLE CFRG are factors as function of soil.

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The research design and methodology 1.Literature review 2.Training in SWAT model 3.Collection of information TYPE OF INFORMATIONCHARACTERISTIC OF INFORMATIONSOURCE Digital Elevation Model90m x 90mASTER GDEM Use of soilScale: 125.000IGAC Soil mapsScale: 125.000IGAC Physic and chemical Soil properties Soil type, Area ratio, Content of sand, Content of clay, Content of fine clay, Content of Organic carbon, Content of total nitrogen, Content of potassium, Content of total phosphorus. IGAC, ICA Climatic daily data (30 years) !!! Daily precipitation, Maximum temperature. Minimum temperature, Solar radiation. Wind speed, Relative humidity, Daily Stream. Sedimentation yield Hydrology, Meteorology and Environmental Studies Institute (IDEAM) 8

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4.Preparation of background information of entry for the application of the hydrological model. 5.Analysis of the series of time. 6.Modeling and calibration of the Cesar River basin hydrological validation. 7.Write final paper 9

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Partial results 3.Collection of information and arrangement of data 10 Macro

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Quality of available climatic data 11 Variable StationsYears Amount%fromto MaxT9619802010 MaxWs3219802009 MS211319702009 MRH9619802010 MT9619802010 MWs5319752009 mT9619802010 TSB8519802009 TE7419802009 TP734519802009 TWt9619852008 Max T: Maximun temperature, MaxWs: Maximun wind speed, MWs: Main wind speed, MS: Main Stream, MRH: Main relative Humidity, MT: Main temperature, mT: minimum temperature, TSB: Total solar brightness, TE: Total evaporation, TP: Total precipitation, TWt : Total wind track. Figure 1: Description of available data

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Delimitation of the basin with SWAT 12 Pte canoas Station (45 m.a.s.l) Area Cesar Basin: 12.500km2 Range of elevation: 40 and 5300 m.a.s.l.

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(Some Problems with soil information) 13

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FLOW Analysis 1.Annual Analysis 2.Monthly Analysis 3.Flow duration 4.Flood Frecuency 14 Pte canoas Station (45 m.a.s.l)

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1.Annual Analysis 15

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2.Monthly Analysis 18

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20 3.Flow duration

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4.Flood Frequency Analysis Log-Pearson Type III Distribution The Log-Pearson Type III distribution is a statistical technique for fitting frequency distribution data to predict the design flood for a river at some site. Once the statistical information is calculated for the river site, a frequency distribution can be constructed. The probabilities of floods of various sizes can be extracted from the curve. The advantage of this particular technique is that extrapolation can be made of the values for events with return periods well beyond the observed flood events. 21

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22 180 2

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Conclusions 24 Higher flow rates months are October and November and the lower flow are January and February. There is evidence that indicates that the discharge in the months of greater and lower discharge has been increasing in recent years.

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Thank you for your attention 25