Incorporation of Parameter Uncertainty into Spatial Interpolation Using Bayesian Trans-Gaussian Kriging

Quantitative precipitation estimation （QPE） plays an important role in meteorological and hydrological applications.Ground-based telemetered rain gauges are widely used to collect precipitation measurements.Spatial interpolation methods are commonly employed to estimate precipitation fields covering non-observed locations.Kriging is a simple and popular geostatistical interpolation method,but it has two known problems：uncertainty underestimation and violation of assumptions.This paper tackles these problems and seeks an optimal spatial interpolation for QPE in order to enhance spatial interpolation through appropriately assessing prediction uncertainty and fulfilling the required assumptions.To this end,several methods are tested：transformation,detrending,multiple spatial correlation functions,and Bayesian kriging.In particular,we focus on a short-term and time-specific rather than a long-term and event-specific analysis.This paper analyzes a stratiform rain event with an embedded convection linked to the passing monsoon front on the 23 August 2012.Data from a total of 100 automatic weather stations are used,and the rainfall intensities are calculated from the difference of 15 minute accumulated rainfall observed every 1 minute.The one-hour average rainfall intensity is then calculated to minimize the measurement random error.Cross-validation is carried out for evaluating the interpolation methods at regional and local levels.As a result,transformation is found to play an important role in improving spatial interpolation and uncertainty assessment,and Bayesian methods generally outperform traditional ones in terms of the criteria.

Ice thickness distribution and volume estimation of Burqin Glacier No.18 in the Chinese Altay Mountains

Information on the thickness distribution and volume of glacier ice is highly important for glaciological applications;however,detailed measurements of the ice thickness of many glaciers in the Chinese Altay Mountains remain lacking.Burqin Glacier No.18 is a northeast-orientated cirque glacier located on the southern side of the Altay Mountains.This study used PulseEKKO®PRO 100A enhancement ground-penetrating radar(GPR)to survey the ice thickness and volume of Burqin Glacier No.18 in summer 2018.Together with GPR surveying,spatial distributed profiles of the GPR measurements were concurrently surveyed using the real-time kinematic(RTK)global navigation satellite system(GNSS,Unistrong E650).Besides,we used QuickBird,WorldView-2,and Landsat TM to delineate accurate boundary of the glacier for undertaking estimation of glacier ice volume.GPR measurements revealed that the basal topography of profile B1-B2 was flat,the basal topography of profile C1-C2 presented a V-type form,and the basal topography of profile D1-D2 had a typical U-type topographic feature because the bedrock near the central elevation of the glacier was relatively flat.The longitudinal profile A1-A2 showed a ladder-like distribution.Glacier ice was thin at the terminus and its thickness increased gradually from the elevation of approximately 2620 m a.s.l.along the main axis of the glacier tongue with an average value of 80(±1)m.The average ice thickness of the glacier was determined as 27(±2)m and its total ice volume was estimated at 0.031(±0.002)km3.Interpretation of remote sensing images indicated that during 1989–2016,the glacier area reduced from 1.30 to 1.17 km2(reduction of 0.37%/a)and the glacier terminus retreated at the rate of 8.48 m/a.The mean ice thickness of Burqin Glacier No.18 was less than that of the majority of other observed glaciers in China,especially those in the Qilian Mountains and Central Chinese Tianshan Mountains;this is probably attributable to differences in glacier type and climatic setting.

Salinity assessment of groundwater for irrigation to prevent soil salinization

Electrical conductivity(EC)is considered as the most important indicator for assessment of groundwater quality.Determination of suitable interpolation method for derivation of groundwater quality variables map such as EC is dependent on region conditions and existence of enough data.For determining groundwater EC,341 groundwater samples were randomly collected from the central regions of Guilan province,paddy soils,in northern Iran.Interpolation methods including inverse distance weighting(IDW),global polynomial interpolation(GPI),local polynomial interpolation(LPI),radial basis function(RBF),ordinary kriging(OK)and empirical Bayesian Kriging(EBK)were used to generate spatial distribution of groundwater EC.The results indicate that EBK is a superior method with the least RMSE,MAE and the highest R 2.The generated maps can be used to identify the regions in the studied area where groundwater could be allowed to be extracted and utilized by farmers to reduce adverse effect of the scarcity of surface water.