During normal operation in nuclear reactors, the nuclear fuel cladding corrodes as a result of exposure to high temperature cooling water. During this process, hydrogen can enter the zirconium-alloy of the fuel cladding, and under proper conditions, precipitate as brittle hydride platelets which can severely impact cladding ductility and fracture toughness. Hydrogen tends to migrate to and precipitate at colder spots. Because high local hydride concentrations increase the risk of cladding failure, it is important to predict the local hydrogen distribution. Hydrogen transport depends on different phenomena. Even though migration can only occur when the hydrogen is in solid solution, the cladding temperatures during operating condition allow a portion of the hydrogen to be in solid solution. Therefore, as hydrogen is picked up during the corrosion reaction between the cladding and the coolant, it can migrate following Ficks law and the Soret effect. Once the local hydrogen content reaches the terminal solid solubility for precipitation, the hydrogen will start precipitating as zirconium hydride. Previous work in our laboratory implemented a model that describes these different phenomena, into the 3D fuel performance code BISON. A first attempt to benchmark this model has been made in this study by comparing the results given by BISON to the hydrogen distribution measured in a nuclear fuel rod, which underwent a five cycle exposure at the Gravelines nuclear power plant. This was feasible because of the very detailed information about that reactor and fuel pin were available from the thesis of J.-H. Zhang in 1992. The benchmark performed with BISON showed very good agreement between the calculations experimental observation.The calculation above used a value of the precipitation kinetics parameter 2 based on a fit that ignored discrepancies in the early part of the precipitation process. The calculation was revised according to a new model. The new model, which assumes an initial dependence of the precipitation rate on (C_ss-TSS_p )^2 , provides a better fit for this date and we believe a more precise value of 2, which varies mildly with temperature.