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Effect of differing detail in dataset and model on estimation of water footprint of crops

Lassche, Teun (2013) Effect of differing detail in dataset and model on estimation of water footprint of crops.

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Abstract:The concept of water footprint analysis has been devisedby Professor Arjen Y. Hoekstrato assist with decision making for efficient, equitable and sustainable water use and its management. Thewater footprint can be calculated fordifferent countries, businesses, crops and other products. To calculate thewater footprints related to crop production the crop evapotranspirationand yield has to be known. Therequired variablescan be calculated by using different modelsand different data sources over different temporal and spatial scales. Theoretically,each combination of model and dataset of a specific crop on a specific place should give the same results. This study has been done to identifyif theuse of differentmodelsand/or datasetswill have effect on the estimationof the water footprint of crops. The study area is the Sirsa district in the Indian state Haryana. This district is characterized as a dry area, caused by extremely high temperatures and little rainfall. Two croprotationswere studied namely a wheat –rice and a wheat –cotton field, wherewheat is cultivated in the winter season and rice and cotton in the summer season. The study uses two different models, namely the CROPWAT model as being a simpler and commonly used model for water footprint studies and the SWAP model as being a complex agrohydrological model. The CROPWAT model usedtwo different datasets, namely a dataset from global available sources and a locallyavailable dataset. The SWAP model usedlocal datasets, which have beencollected on different times and places in the study area. With these models and datasets sixdifferent combinations have beenassessed. All these combinations are calculated in this study, only the evapotranspiration values of the SWAP modelcombinations are taken from previous studies. With the estimated crop evapotranspiration and yields calculated by the CROPWAT andSWAP modelsfromdifferent local and global data sources the water footprints of wheat, rice and cotton were calculated and compared to each other. The average water footprint in the Sirsa district for wheat is 0,84m3/kg, for rice 2,56m3/kgand for cotton 21,64m3/kg. The averagewater footprintsof rice and cotton are high, causedby the high values calculated by the combination of CROPWAT model and global available datain comparison with the other values for wheat and rice. The coefficient of variation inthe water footprints are largestwith rice, namely about 46%. This means the water footprint of rice is the most sensitiveto calculate, due to the preparation of the paddy fields. The evapotranspiration of wheat calculated by the different combinations are quite the same (ranging from342 mm to 392 mm) except for the combinationof CROPWAT model with global available data (237 mm). With this combination the evapotranspiration calculated for the different cropsis much different than the average, for instancefor wheat 237 mm by a mean value of 342mm, for rice 1031 mm bya mean value of 864mmand for cotton 1092mmby a mean value of 745mm. The coefficients of variation of the crop yields are quite large, namely 22% for wheat, 42% for cotton and 61% for rice.This is due to the manner of calculating the crop yields, which are different for almost all datasets, which all covers different time periods and different areas. This means therefore that the results show a discrepancy between practice and theory. This study shows that severalcombinations of model and dataset are possibleto estimate water footprints of crops, but the results are not the same. This is because of different data sources, different time periods considered, different methods used in models and different definitions of parameters. This means that it is very important that every parameter haveto be defined very well in calculating the water footprint of crops. In drawing conclusions researchers should be very careful. The differences between the different combinations of model and dataset are too large to drawfirm conclusions.
Item Type:Essay (Bachelor)
Faculty:ET: Engineering Technology
Subject:56 civil engineering
Programme:Civil Engineering BSc (56952)
Link to this item:http://purl.utwente.nl/essays/63848
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