a b s t r a c tRice agricultural practices and hydroperiod dates must be determined to obtain information on water management practices and their environmental effects. Spectral indices derived from an 8-day MODIS composite allows to identify rice phenometrics at varying degrees of success. The aims of this study were (1) to assess the dynamics of the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI(1) and NDWI(2)) and Shortwave Angle Slope Index (SASI) in relation to rice agricultural practices and hydroperiod, and (2) to assess the capability for these indices to detect phenometrics in rice under different flooding regimes. Two rice farming areas in Spain that are governed under different water management practices, the Ebro Delta and Orellana, were studied over a 12-year period (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012). The index time series autocorrelation function was calculated to determine index dynamics in both areas. Secondly, average indices were calculated to identify significant points close to key agricultural and flooding dates, and index behaviors and capacities to identify phenometrics were assessed on a pixel level. The index autocorrelation function produced a regular pattern in both zones, being remarkably homogeneous in the Ebro Delta. It was concluded that a combination of NDVI, NDWI(1), NDWI (2) and SASI may improve the results obtained through each index. NDVI was more effective at detecting the heading date and flooding trends in the Ebro Delta. NDWI(1), NDWI(2) and SASI identified the harvest and the end of environmental flooding in the Delta, and the flooding in Orellana, more effectively. These results may set strong foundations for the development of new strategies in rice monitoring systems, providing useful information to policy makers and environmental studies.

Terrestrial evapotranspiration (ET) is a central process in the climate system, is a major component in the terrestrial water budget, and is responsible for the distribution of water and energy on land surfaces especially in arid and semiarid areas. In order to inform water management decisions especially in scarce water environments, it is important to assess ET vegetation use by differentiating irrigated socio-economic areas and natural ecosystems. The global remote sensing ET product MOD16 has proven to underestimate ET in semiarid regions where ET is very sensitive to soil moisture. The objective of this research was to test whether a modified version of the remote sensing ET model PT-JPL, proven to perform well in drylands at Eddy Covariance flux sites using the land surface temperature as a proxy to the surface moisture status (PT-JPL-thermal), could be up-scaled at regional levels introducing also a new formulation for net radiation from various MODIS products. We applied three methods to track the spatial and temporal characteristics of ET in the World Heritage UNESCO Doñana region: (i) a locally calibrated hydrological model (WATEN), (ii) the PT-JPL-thermal, and (iii) the global remote sensing ET product MOD16. The PT-JPL-thermal showed strong agreement with the WATEN ET in-situ calibrated estimates (ρ = 0.78, ρ 1month-lag = 0.94) even though the MOD16 product did not (ρ = 0.48). The PT-JPL-thermal approach has proven to be a robust remote sensing model for detecting ET at a regional level in Mediterranean environments and it requires only air temperature and incoming solar radiation from climatic databases apart from freely available satellite products.The global water cycle is changing due to the combined effects of climate change and human interventions during the 21st century [1]. One of the greatest challenges is keeping water consumption at sustainable levels, which is more complex due to the increasing population in a context of climate uncertainty [2,3] and 3.5-4.4 billion people estimated under water scarcity conditions in 2050 [4]. Many regions of the world can expect a combination of increasing temperatures (largely increasing evaporative demand) and decreasing precipitation patterns, which leads to increased stress on tackling water demand [5]. A prime example of this is the Mediterranean region, which is consistently projected as a "hotspot" of drying trends and prolonged water scarcity conditions [6,7].The Iberian Peninsula is predicted to be among the most affected areas by severe droughts by the end of the 21st century [8]. In this region, where irrigated agriculture represents over 80% of the total extracted water [9], land use shifts towards higher market-valued crops represent a major driver of change, which will markedly increase water withdrawals [10]. In the Guadalquivir basin in Spain, irrigation water requirements are expected to increase between 15% and 20% by 2050 [11]. This may cause a redistribution of water between the surface and groundwater [12]. Monitoring the variations i...

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There is a growing need to map rice ecosystems and to develop methods for monitoring rice distribution in order to account for rapid land use changes worldwide. In this study, we evaluated a methodology based on Vegetation Indices time series derived from an 8-day MODIS composite to identify rice fields and develop rice maps that can be timely updated in the long term. We have assessed the potential of the Spectral Shape Index time series and compared its performance with the Normalized Difference Vegetation Index in two coastal locations and in an inland location in the Mediterranean Region for 2012. A profile similarity comparison method, the Spectral Angle Mapper, was accomplished between the reference rice annual profile and the annual profiles of both indices in a pixel basis in order to determine rice pixels. The resultant maps were validated with rice masks, where available, or ortophotos and crop surface statistics where not. The results obtained demonstrated the potential of both indices to provide accurate rice maps when applied together with spectral matching techniques. The overall accuracy was 92.8%, 98.1% and 90.1% for the Spectral Shape Index and 92.4%, 77.24% and 82.8% for the Normalized Difference Vegetation Index in each location. The excellent performance of the Spectral Shape Index in the three locations highlighted the importance of exploring angular indices to improve the identification of land cover dynamics.

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