Integral quantification of seasonal soil moisture changes in farmland by cosmic-ray neutrons

Soil moisture at the plot or hill-slope scale is an important link between local vadose zone hydrology and catchment hydrology. However, so far only a few methods are on the way to close this gap between point measurements and remote sensing. One new measurement methodology that could determine integral soil moisture at this scale is the aboveground sensing of cosmic-ray neutrons, more precisely of ground albedo neutrons. The present study performed ground albedo neutron sensing (GANS) at an agricultural field in northern Germany. To test the method it was accompanied by other soil moisture measurements for a summer period with corn crops growing on the field and a later autumn-winter period without crops and a longer period of snow cover. Additionally, meteorological data and aboveground crop biomass were included in the evaluation. Hourly values of ground albedo neutron sensing showed a high statistical variability. Six-hourly values corresponded well with classical soil moisture measurements, after calibration based on one reference dry period and three wet periods of a few days each. Crop biomass seemed to influence the measurements only to minor degree, opposed to snow cover which has a more substantial impact on the measurements. The latter could be quantitatively related to a newly introduced field neutron ratio estimated from neutron counting rates of two energy ranges. Overall, our study outlines a procedure to apply the ground albedo neutron sensing method based on devices now commercially available, without the need for accompanying numerical simulations and suited for longer monitoring periods after initial calibration

A global uncertainty and sensitivity procedure for the assessment of groundwater recharge distribution via hydrological models

Groundwater recharge is the key driver for groundwater flow and resulting transport at the catchment scale, but it is difficult to quantify. Hydrological models provide an option for evaluating an estimate of groundwater recharge. They can generally be used to estimate groundwater recharge rates over large spatial and temporal scales, and they can be applied for current or future scenario analysis as climate or land use changes. However, a serious limitation of current model applications is the non-availability of data and input parameters. In order to improve the reliability and the performance of hydrological models, in this study a general approach for the assessment of performance in the simulation of the groundwater recharge estimation is proposed. A so-called global uncertainty analysis is developed as a tool to evaluate the performance of the models. A global sensitivity analysis is defined and used as a complementary tool to find the most important sources of uncertainty. The procedure can take various sources of uncertainty into account, i.e. input data, parameters, either in scalar or spatially distributed form. This procedure is iterated in a loop for improving the performance of the models and to optimize the resource allocations. As a test example, the procedure is applied at an experimental site in northern Germany on a field scale, using the SWAP model, a ID physical-based hydrological model. Further research will involve other spatially distributed hydrological models of different complexity and application on larger spatial scales. Copyright © 2012 IAHS Press