M.S. Salama

Potential of using remote sensing techniques for global assessment of Water Footprint of crops.

Remote sensing has long been a useful tool in global applications, since it provides physically-based, worldwide, and consistent spatial information. This paper discusses the potential of using these techniques in the research field of water management, particularly for ‘Water Footprint’ (WF) studies. The WF of a crop is defined as the volume of water consumed for its production, where green and blue WF stand for rain and irrigation water usage, respectively. In this paper evapotranspiration, precipitation, water storage, runoff and land use are identified as key variables to potentially be estimated by remote sensing and used for WF assessment. A mass water balance is proposed to calculate the volume of irrigation applied, and green and blue WF are obtained from the green and blue evapotranspiration components. The source of remote sensing data is described and a simplified example is included, which uses evapotranspiration estimates from the geostationary satellite Meteosat 9 and precipitation estimates obtained with the Climatic Prediction Center Morphing Technique (CMORPH). The combination of data in this approach brings several limitations with respect to discrepancies in spatial and temporal resolution and data availability, which are discussed in detail. This work provides new tools for global WF assessment and represents an innovative approach to global irrigation mapping, enabling the estimation of green and blue water use.

Remote-sensing reflectance characteristics of highly turbid estuarine waters-a comparative experiment of the Yangtze River and the Yellow River

An outdoor tank experiment is carried out to analyse the interrelationships between remote-sensing reflectance and sediment characteristics in the highly turbid waters of the Yangtze River and the Yellow River estuaries. The results show that the sensitivity of remote-sensing reflectance to water turbidity is inversely related to suspended sediment concentration (SSC). SSC estimation in the highly turbid waters (SSC > 0.15 g l−1) is best achieved by using ocean colour ratios, especially the ratio at 810 nm: 700 nm. The effect of particle size of suspended sediment matter (SSM) on the observed remote-sensing reflectance is significant and depends on wavelengths and a SSC range. The mineral composition of SSM has a weak effect on observed reflectance in comparison to that of particle size.

Decadal variations of land surface temperature anomalies observed over the Tibetan Plateau by the Special Sensor Microwave Imager (SSM/I) from 1987 to 2008

In this paper, we analyze the standardized anomalies of land surface temperature (LST) retrieved from the Special Sensor Microwave Imager (SSM/I) vertically polarized 37 GHz (

Accelerated Changes of Environmental Conditions on the Tibetan Plateau Caused by Climate Change

T^v_{B,37~{\rm GHz}}

Medium resolution imaging spectrometer (MERIS) estimation of chlorophyll-a concentration in the turbid sediment-laden waters of the Changjiang (Yangtze) Estuary

) brightness temperature over the Tibetan Plateau for the period 1987 to 2008. A radiative transfer model is used to derive LST from SSM/I

Error decomposition and estimation of inherent optical properties

T^v_{Bv,37~{\rm GHz}}

Estimation of human‐induced changes in terrestrial water storage through integration of GRACE satellite detection and hydrological modeling: A case study of the Yangtze River basin

, which is calibrated and validated using time series of field measured soil surface temperatures. Additional Plateau-scale verification is performed with monthly LST products from the Moderate Resolution Imaging Spectroradiometer, the Noah land surface model and air temperature measured by Chinese Meteorological Administration. Trend analysis shows that the annual and monthly standardized anomalies are increasing at an averaged rate of 0.5 decade − 1. The highest positive trends are noted over the central part of the Plateau, which is on average 0.80 decade − 1 with a maximum of 1.44 decade − 1. Conversely, a negative trend in the anomalies is found for the Taklamakan desert and the Himalayan foothills with a rate of −0.27 decade − 1 and reaching a maximum of −1.4 decade − 1. In addition, we find that LST anomaly trends on the Plateau are seasonally dependent and increase with the elevation. These observed trends are in agreement with previous studies conducted with in-situ measurements, which demonstrates the use of long-term earth observation programmes for climate studies as has also been articulated in the 2007 IPCC report.

Analysis of long-term terrestrial water storage variations in Yangtze River basin

AbstractVariations of land surface parameters over the Tibetan Plateau have great importance on local energy and water cycles, the Asian monsoon, and climate change studies. In this paper, the NOAA/NASA Pathfinder Advanced Very High Resolution Radiometer (AVHRR) Land (PAL) dataset is used to retrieve the land surface temperature (LST), the normalized difference vegetation index (NDVI), and albedo, from 1982 to 2000. Simultaneously, meteorological parameters and land surface heat fluxes are acquired from the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) dataset and the Global Land Data Assimilation System (GLDAS), respectively. Results show that from 1982 to 2000 both the LST and the surface air temperature increased on the Tibetan Plateau (TP). The rate of increase of the LST was 0.26±0.16 K decade−1 and that of the surface air temperature was 0.29 ± 0.16 K decade−1, which exceeded the increase in the Northern Hemisphere (0.054 K decade−1). The plateau-wide annual m...

Stochastic inversion of ocean color data using the cross-entropy method.

Satellite estimation of chlorophyll-a (Chl-a) concentration in the Changjiang Estuary is challenging for ocean-colour retrieval algorithms. The Changjiang Estuary is characterized by suspended-sediment-dominated waters in the mouth and optically complex case 2 waters offshore of the mouth. Satellite ocean-colour products show that high-sediment loads of estuarine waters can cause overestimations or invalid flags of Chl-a concentration. A synthetic chlorophyll index (SCI) was designed for extracting chlorophyll information and for minimizing the influence of sediments on the remote-sensing reflectance spectrum. An SCI algorithm, a quadratic polynomial function of the SCI versus Chl-a concentration, was applied to the estimation of Chl-a concentration from Medium Resolution Imaging Spectrometer (MERIS) images. The overestimation of Chl-a concentration was corrected. The SCI algorithm has applications for MERIS estimation of Chl-a concentration in turbid waters with a moderate to high suspended-sediment concentration.

Ensemble uncertainty of inherent optical properties

We describe a methodology to quantify and separate the errors of inherent optical properties (IOPs) derived from ocean-color model inversion. Their total error is decomposed into three different sources, namely, model approximations and inversion, sensor noise, and atmospheric correction. Prior information on plausible ranges of observation, sensor noise, and inversion goodness-of-fit are employed to derive the posterior probability distribution of the IOPs. The relative contribution of each error component to the total error budget of the IOPs, all being of stochastic nature, is then quantified. The method is validated with the International Ocean Colour Coordinating Group (IOCCG) data set and the NASA bio-Optical Marine Algorithm Data set (NOMAD). The derived errors are close to the known values with correlation coefficients of 60-90% and 67-90% for IOCCG and NOMAD data sets, respectively. Model-induced errors inherent to the derived IOPs are between 10% and 57% of the total error, whereas atmospheric-induced errors are in general above 43% and up to 90% for both data sets. The proposed method is applied to synthesized and in situ measured populations of IOPs. The mean relative errors of the derived values are between 2% and 20%. A specific error table to the Medium Resolution Imaging Spectrometer (MERIS) sensor is constructed. It serves as a benchmark to evaluate the performance of the atmospheric correction method and to compute atmospheric-induced errors. Our method has a better performance and is more appropriate to estimate actual errors of ocean-color derived products than the previously suggested methods. Moreover, it is generic and can be applied to quantify the error of any derived biogeophysical parameter regardless of the used derivation.