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What is the most appropriate sampling scheme to estimate event-based average throughfall? A satisfactory answer to this seemingly simple question has yet to be found, a failure which we attribute to previous efforts' dependence on empirical studies. Here we try to answer this question by simulating stochastic throughfall fields based on parameters for statistical models of large monitoring data sets. We subsequently sampled these fields with different sampling designs and variable sample supports. We evaluated the performance of a particular sampling scheme with respect to the uncertainty of possible estimated means of throughfall volumes. Even for a relative error limit of 20%, an impractically large number of small, funnel-type collectors would be required to estimate mean throughfall, particularly for small events. While stratification of the target area is not superior to simple random sampling, cluster random sampling involves the risk of being less efficient. A larger sample support, e.g., the use of trough-type collectors, considerably reduces the necessary sample sizes and eliminates the sensitivity of the mean to outliers. Since the gain in time associated with the manual handling of troughs versus funnels depends on the local precipitation regime, the employment of automatically recording clusters of long troughs emerges as the most promising sampling scheme. Even so, a relative error of less than 5% appears out of reach for throughfall under heterogeneous canopies. We therefore suspect a considerable uncertainty of input parameters for interception models derived from measured throughfall, in particular, for those requiring data of small throughfall events.
Metabasites were sampled from rock series of the subducted margin of the Indian Plate, the so-called Higher Himalayan Crystalline, in the Upper Kaghan Valley, Pakistan. These vary from corona dolerites, cropping out around Saif- ul-Muluk in the south, to coesite-eclogite close to the suture zone against rocks of the Kohistan arc in the north. Bulk rock major- and trace-element chemistry reveals essentially a single protolith as the source for five different eclogite types, which differ in fabric, modal mineralogy as well as in mineral chemistry. The study of newly-collected samples reveals coesite (confirmed by in situ Raman spectroscopy) in both garnet and omphacite. All eclogites show growth of amphiboles during exhumation. Within some coesite-bearing eclogites the presence of glaucophane cores to barroisite is noted whereas in most samples porphyroblastic sodic-calcic amphiboles are rimmed by more aluminous calcic amphibole (pargasite, tschermakite, and edenite). Eclogite facies rutile is replaced by ilmenite which itself is commonly surrounded by titanite. In addition, some eclogite bodies show leucocratic segregations containing phengite, quartz, zoisite and/or kyanite. The important implication is that the complex exhumation path shows stages of initial cooling during decompression (formation of glaucophane) followed by reheating: a very similar situation to that reported for the coesite-bearing eclogite series of the Tso Morari massif, India, 450 km to the south-east.
Simulation of spatial sensor characteristics in the context of the EnMAP Hyperspectral mission
(2010)
The simulation of remote sensing images is a valuable tool for defining future Earth observation systems, optimizing instrument parameters, and developing and validating data-processing algorithms. A scene simulator for optical Earth observation data has been developed within the Environmental Mapping and Analysis Program (EnMAP) hyperspectral mission. It produces EnMAP-like data following a sequential processing approach consisting of five independent modules referred to as reflectance, atmospheric, spatial, spectral, and radiometric modules. From a modeling viewpoint, the spatial module is the most complex. The spatial simulation process considers the satellite-target geometry, which is adapted to the EnMAP orbit and operating characteristics, the instrument spatial response, and the sources of spatial nonuniformity (keystone, telescope distortion and smile, and detector coregistration). The spatial module of the EnMAP scene simulator is presented in this paper. The EnMAP spatial and geometric characteristics will be described, the simulation methodology will be presented in detail, and the capability of the EnMAP simulator will be shown by illustrative examples.
Map form information on forest biomass is required for estimating bioenergy potentials and monitoring carbon stocks. In Finland, the growing stock of forests is monitored using multi-source forest inventory, where variables are estimated in the form of thematic maps and area statistics by combining information of field measurements, satellite images and other digital map data. In this study, we used the multi-source forest inventory methodology for estimating forest biomass characteristics. The biomass variables were estimated for national forest inventory field plots on the basis of measured tree variables. The plot-level biomass estimates were used as reference data for satellite image interpretation. The estimates produced by satellite image interpretation were tested by cross-validation. The results indicate that the method for producing biomass maps on the basis of biomass models and satellite image interpretation is operationally feasible. Furthermore, the accuracy of the estimates of biomass variables is similar or even higher than that of traditional growing stock volume estimates. The technique presented here can be applied, for example, in estimating biomass resources or in the inventory of greenhouse gases.
Two types of electrical conductivity sensors were evaluated to prospect circular ditches surrounding former Bronze Age burial mounds, complementing aerial photography. The first sensor was based on the electrical resistivity (ER) method, while the second sensor was based on frequency-domain electromagnetic induction (FDEM). Both sensors were designed with multiple receivers, which measure several depth sensitivities simultaneously. First, the sensors were tested on an experimental site where a rectangular structure with limited dimensions was dug in a sandy soil. The structure appeared as a higher conductivity anomaly in the low-conductivity sand. Then, both methods were applied on two Bronze Age sites with different soil properties, which were discovered by aerial photography. The first site, in a sandy soil, gave only very weak anomalies. Soil augering revealed that the ditch filling consisted of the same sandy material as the surrounding, therefore this filling was not able to cause a high-conductivity contrast. Due to its lower sensitivity to noise in the low-conductive range, the ER-sensor produced a more pronounced anomaly than the FDEM-sensor. The second site was located on top of a ridge with a shallow substrate of Tertiary, coastal sediments. The ditch was very clearly visible on the sensor maps as a conductive low. At this location, the soil augering revealed that the ditch was dug through an alternating clay-sand layer and subsequently filled up with silty material from the topsoil. Overall, the shallow receiver separation produced anomalies that were both stronger and that corresponded better to the geometry of the ditches. The other receiver separations provided more information on the natural soil layering, and in the case of the ER-array they could be used to obtain a cross-section of the actual electrical conductivity with 2-D inversion modelling. The results of this study proofed that conductivity sensors can detect Bronze Age ditches, with varying contrast depending on the soil geomorphology. Moreover, the sensor maps combined with soil observations by coring provided insight in the environmental conditions that influence the contrast of the anomalies seen on the aerial photographs and the sensor maps.
In the humid tropics, continuing high deforestation rates are seen alongside an increasing expansion of secondary forests. In order to understand and model the consequences of these dynamic land-use changes for regional water cycles, the response of soil hydraulic properties to forest disturbance and recovery has to be quantified.At a site in the Brazilian Amazonia, we annually monitored soil infiltrability and saturated hydraulic conductivity (K-s) at 12.5, 20 cm, and 50 cm soil depth after manual forest conversion to pasture (year zero to four after pasture establishment), and during secondary succession after pasture abandonment (year zero to seven after pasture abandonment). We evaluated the hydrological consequences of the detected changes by comparing the soil hydraulic properties with site-specific rainfall intensities and hydrometric observations. Within one year after grazing started, infiltrability and K-s at 12.5 and 20 cm depth decreased by up to one order of magnitude to levels which are typical for 20-year-old pasture. In the three subsequent monitoring years, infiltrability and K-s remained stable. Land use did not impact on subsoil permeability. Whereas infiltrability values are large enough to allow all rainwater to infiltrate even after the conversion, the sudden decline of near-surface K-s is of hydrological relevance as perched water tables and overland flow occur more often on pastures than in forests at our study site. After pasture abandonment and during secondary succession, seven years of recovery did not suffice to significantly increase infiltrability and K-s at 12.5 depth although a slight recovery is obvious. At 20 cm soil depth, we detected a positive linear increase within the seven-year time frame but annual means did not differ significantly. Although more than a doubling of infiltrability and K-s is still required to achieve pre-disturbance levels, which will presumably take more than a decade, the observed slight increases of K-s might already decrease the probability of perched water table generation and overland flow development well before complete recovery.