Remotely sensed soil moisture integration in an ecosystem carbon flux model. The spatial implication

While remote sensing is able to provide spatially explicit datasets at regional to global scales, extensive application to date has been found only in the reporting and verification of ecosystem carbon fluxes under the Kyoto Protocol. One of the problems is that new remote sensing datasets can be used only with models or data assimilation schemes adapted to include a data input interface dedicated to the type and format of these remote sensing datasets. In this study, soil water index data (SWI), derived from the ERS scatterometer (10-daily time period with a spatial resolution of 50 km), are integrated into the ecosystem carbon balance model C-Fix to assess 10-daily Net Ecosystem Productivity (NEP) patterns of Europe from the remote sensing perspective on an approximate 1-by-1 km² pixel scale using NDVI-AVHRR data. The modeling performance of NEP obtained with and without the assimilation of remotely sensed soil moisture data in the carbon flux model C-Fix is evaluated with EUROFLUX data. Results show a general decrease of the RRMSE of up to 11 with an average of 3.46. C-Fix is applied at the European scale to demonstrate the potential of this ecosystem carbon flux model, based on remote sensing inputs. More specifically, the strong impact of soil moisture on the European carbon balance in the context of the Kyoto Protocol (anthropogenic carbon emissions) is indicated at the country level. Results suggest that several European countries shift from being a carbon sink (i.e., NEP > 1) to being a carbon source (i.e., NEP < 0) whether or not short-term water availability (i.e., soil moisture) is considered in C-Fix NEP estimations.     

Drought propagation in the hydrological cycle in a semiarid region: a case study in the Bilate catchment,Ethiopia

Hydrogeology Journal - Drought is a temporal decrease in water availability and occurs in all climatic regions. Droughts propagate through the hydrological cycle, e.g., meteorological drought...     

Sub-pixel classification of SPOT-VEGETATION time series for the assessment of regional crop areas in Belgium

Global time series of low resolution images are available with high repeat frequency and at low cost, but their analysis is hampered by the presence of mixed pixels and the difficulty in locating detailed spatial features. This study examined the potential of sub-pixel classification for regional crop area estimation using time series of monthly NDVI-composites of the 1 km resolution sensor SPOT-VEGETATION. Belgium was selected as test zone, because of the availability of ample reference data in the form of a vectorial GIS with the boundaries and cover type of the large majority of agricultural fields. Two different methods were investigated: the linear mixture model and neural networks. Both result in area fraction images (AFIs), which contain for each 1 km pixel the estimated area proportions occupied by the different cover types (crops or other land use). Both algorithms were trained with part of the reference data and validated with the remainder. Validation was repeated at three different levels: the 1 km pixel, the municipality and the agro-statistical district. In general, the neural network outperformed the linear mixture model. For the major classes (winter wheat, maize, forest) the obtained acreage estimates showed good agreement with the true values, especially when aggregated to the level of the municipality (R² ≈ 85%) or district (R² ≈ 95%). The method seems attractive for wide-scale, regional area estimation in data-poor countries.     

Identification of the influencing factors on groundwater drought and depletion in north-western Bangladesh

Groundwater drought is a specific type of hydrological drought that concerns groundwater bodies. It may have a significant adverse effect on the socio-economic, agricultural, and environmental conditions. Investigating the effect of different climatic and anthropogenic factors on groundwater drought provides essential information for sustainable planning and management of (ground) water resources. The aim of this study is to identify the influencing factors on groundwater drought in north-western Bangladesh, to understand the forcing mechanisms. A multi-step methodology is proposed to achieve this objective. The standardised precipitation index (SPI) and reconnaissance drought index (RDI) have been used to quantify the aggregated deficit between precipitation and the evaporative demand of the atmosphere, i.e. meteorological drought. The influence of land-cover patterns on the groundwater drought has been identified by calculating spatially distributed groundwater recharge as a function of land cover. Groundwater drought is defined by a threshold method. The results show that the evapotranspiration and rainfall deficits are determining meteorological drought, which shows a direct relation with groundwater recharge deficits. Land-cover change has a small effect on groundwater recharge but does not seem to be the main cause of groundwater-level decline (depletion) in the study area. The groundwater depth and groundwater-level deficit (drought) is continuously increasing with little correlation to meteorological drought or recharge anomalies. Overexploitation of groundwater for irrigation seems to be the main cause of groundwater-level decline in the study area. Efficient irrigation management is essential to reduce the growing pressure on groundwater resources and ensure sustainable water management.     

Real time processing of Doppler data in a single station

Observations at a single station of the Doppler-shift of radio signals emitted by navigation satellites can be used to compute and update in real time the orbital elements of these satellites at the100 m level. This allows the immediate control of the observational quality and the computation of a better tracking schedule, as was done forSEASAT and could be used for theTOPEX experiment.