Field‐based and spectral indicators for soil erosion mapping in semi‐arid mediterranean environments (Coastal Cordillera of central Chile)

The Coastal Cordillera of central Chile is naturally sensitive to soil erosion due to moderate to steep slopes, intense winter rains when the vegetation cover is scarce, and deeply weathered granitic rocks. In 1965, 60 per cent of its surface was moderately to very severely eroded. Today this process is still largely active, but no data are currently available to evaluate the real extent, distribution and severity of soil degradation on a regional scale. This information is vital to support efficient soil conservation plans. A multi‐scale approach was implemented to produce regional land degradation maps based on remote sensing technologies. Fieldwork has shown that the surface colour or ‘redness’ and the density of coarse fragments are pertinent erosion indicators to describe a typical sequence of soil degradation in the context of mediterranean soil developed on granitic materials and micaschists. Field radiometric experiments concluded that both factors influence the reflectance of natural surfaces and can be modelled using radiometric indices accessible from most satellites operating in the optical domain, i.e. redness index and brightness index. Finally the radiometric indices were successfully applied to SPOT images to produce land degradation maps. Only broad classes of erosion status were discriminated and the detection of the degradation processes was only possible when most of the fertile layer had already been removed. This technology provides decision‐making information required to develop regional soil conservation plans and to prioritize actions between catchment areas, especially in vast inter‐tropical regions where spatialized data are not always readily available. Copyright © 2006 John Wiley & Sons, Ltd.     

Use of multi‐platform,multi‐temporal remote‐sensing data for calibration of a distributed hydrological model: an application in the Arno basin,Italy

Images from satellite platforms are a valid aid in order to obtain distributed information about hydrological surface states and parameters needed in calibration and validation of the water balance and flood forecasting. Remotely sensed data are easily available on large areas and with a frequency compatible with land cover changes. In this paper, remotely sensed images from different types of sensor have been utilized as a support to the calibration of the distributed hydrological model MOBIDIC, currently used in the experimental system of flood forecasting of the Arno River Basin Authority. Six radar images from ERS‐2 synthetic aperture radar (SAR) sensors (three for summer 2002 and three for spring–summer 2003) have been utilized and a relationship between soil saturation indexes and backscatter coefficient from SAR images has been investigated. Analysis has been performed only on pixels with meagre or no vegetation cover, in order to legitimize the assumption that water content of the soil is the main variable that influences the backscatter coefficient. Such pixels have been obtained by considering vegetation indexes (NDVI) and land cover maps produced by optical sensors (Landsat‐ETM). In order to calibrate the soil moisture model based on information provided by SAR images, an optimization algorithm has been utilized to minimize the regression error between saturation indexes from model and SAR data and error between measured and modelled discharge flows. Utilizing this procedure, model parameters that rule soil moisture fluxes have been calibrated, obtaining not only a good match with remotely sensed data, but also an enhancement of model performance in flow prediction with respect to a previous calibration with river discharge data only. Copyright © 2006 John Wiley & Sons, Ltd.     

Large‐scale regional delineation of riparian vegetation in the arid and semi‐arid Pilbara region,WA

Multiscene Landsat 5 TM imagery, Principal Component Analysis, and the Normalized Difference Vegetation Index were used to produce the first region‐scale map of riparian vegetation for the Pilbara (230,000 km²), Western Australia. Riparian vegetation is an environmentally important habitat in the arid and desert climate of the Pilbara. These habitats are supported by infrequent flow events and in some locations by groundwater discharge. Our analysis suggests that riparian vegetation covers less than 4% of the Pilbara region, whereas almost 10.5% of this area is composed of groundwater dependent vegetation (GDV). GDV is often associated with open water (river pools), providing refugia for a variety of species. GDV has an extremely high ecological value and are often important Indigenous sites. This paper demonstrates how Landsat data calibrated to Top of Atmosphere reflectance can be used to delineate riparian vegetation across 16 Landsat scenes and two Universal Transverse Mercator spatial zones. The proposed method is able to delineate riparian vegetation and GDV, without the need for Bidirectional Reflectance Distribution Function correction. Results were validated using ground truth data from local and regional scale vegetation surveys.     

Evaluation of irrigation water use efficiency using remote sensing in the middle reach of the Heihe river,in the semi‐arid Northwestern China

Irrigation of agricultural oases is the main water consumer in semi‐arid and arid regions of Northwestern China. The accurate estimation of evapotranspiration (ET) on the oases is extremely important for evaluating water use efficiency so as to reasonably allocate water resources, particularly in semi‐arid and arid areas. In this study, we integrated the soil moisture information into surface energy balance system (SEBS) for improving irrigated crop water consumption estimation. The new approach fed with the moderate resolution imaging spectro‐radiometer images mapped spatiotemporal ET on the oasis in the middle reach of the Heihe river. The daily ET outputs of the new approach were compared with those of the original SEBS using the eddy correlation observations, and the results demonstrate that the modified SEBS remedied the shortcoming of general overestimating ET without regard to soil water stress. Meanwhile, the crop planting structure and leaf area index spatiotemporal distribution in the studied region were derived from the high‐resolution Chinese satellite HJ‐1/CCD images for helping analyse the pattern of the monthly ET (ET_monthly). The results show that the spatiotemporal variation of ET_monthly is closely related to artificial irrigation and crop growth. Further evaluation of current irrigation water use efficiency was conducted on both irrigation district scale and the whole middle reach of the Heihe river. The results reveal that the average fraction of consumed water on irrigation district scale is 57% in 2012. The current irrigation water system is irrational because only 52% of the total irrigated amount was used to fulfil plant ET requirement and the rest of the irrigation water recharged into groundwater in the oasis in 2012. However, in view of the whole middle reach of the Heihe river, the irrigation water use efficiency could reach to 66% in 2012. But pumping groundwater for reused irrigation wastes mostly energy instead of water. An improved irrigation water allocation system according to actual ET requirement is needed to increase irrigation efficiency per cubic meter water resource in an effort to save both water and energy. Copyright © 2014 John Wiley & Sons, Ltd.