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

Soil water content in southern England derived from a cosmic-ray soil moisture observing system - COSMOS-UK

Cosmic-ray soil moisture sensors have the advantage of a large measurement footprint (approximately 700 m in diameter) and are able to operate continuously to provide area-averaged near-surface (top 10-20 cm) volumetric soil moisture content at the field scale. This paper presents the application of this technique at four sites in southern England over almost 3 years. Results show the soil moisture response to contrasting climatic conditions during 2011-2014, and are the first such field-scale measurements made in the UK. These four sites are prototype stations for a UK COsmic-ray Soil Moisture Observing System (COSMOS-UK), and particular consideration is given to sensor operating conditions in the UK. Comparison of these soil water content observations with the Joint UK Land Environment Simulator (JULES) 10 cm soil moisture layer shows that these data can be used to test and diagnose model performance, and indicates the potential for assimilation of these data into hydro-meteorological models. The application of these large-area soil water content measurements to evaluate remotely-sensed soil moisture products is also demonstrated. Numerous applications and the future development of a national COSMOS-UK network are discussed

Inverse modelling of cosmic-ray soil moisture for field-scale soil hydraulic parameters

Summary: We used inverse modelling techniques and soil moisture measured by the cosmic-ray neutron sensing (CRS) to estimate root-zone soil hydraulic properties at the field scale. A HYDRUS-1D model was developed for inverse modelling and calibrated with parameter estimation software (PEST) using a global optimizer. Integral CRS measurements recorded from a sunflower farm in Germany comprised the model input. Data were transformed to soil water storage to enable direct model calibration with a HYDRUS soil-water balance. Effective properties at the CRS scale were compared against local measurements and other inversely estimated soil properties from independent soil moisture profiles. Moreover, CRS-scale soil properties were tested on the basis of how field soil moisture (vertical distribution) and soil water storage were reproduced. This framework provided good estimates of effective soil properties at the CRS scale. Simulated soil moisture at different depths at the CRS scale agreed with field observations. Moreover, simulated soil water storage at the CRS scale compared well with calculations from point-scale profiles, despite their different support volumes. The CRS-scale soil properties estimated with the inverse model were within the range of variation of properties identified from all inverse simulations at the local scale. This study demonstrates the potential of CRS for inverse estimation of soil hydraulic properties

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