Spectral relationships, reflecting the spectral dependence of water-leaving reflectance, rho(w)(lambda), can be easily implemented in current AC algorithms with the aim to improve rho(w)(lambda) retrievals where the algorithms fail. The present study evaluates the potential of spectral relationships to improve the MUMM (Ruddick et al., 2006, Limnol. Oceanogr. 51, 1167-1179) and standard NASA (Bailey et al., 2010, Opt. Express 18, 7521-7527) near infra-red (NIR) modeling schemes included in the AC algorithm to account for non-zero rho(w)(lambda(NIR)), based on in situ coastal rho(w)(lambda) and simulated Rayleigh corrected reflectance data. Two modified NIR-modeling schemes are investigated: (1) the standard NASA NIR-modeling scheme is forced with bounding relationships in the red spectral domain and with a NIR polynomial relationship and, (2) the constant NIR rho(w)(lambda) ratio used in the MUMM NIR-modeling scheme is replaced by a NIR polynomial spectral relationship. Results suggest that the standard NASA NIR-modeling scheme performs better for all turbidity ranges and in particular in the blue spectral domain (percentage bias decreased by approximately 50\%) when it is forced with the red and NIR spectral relationships. However, with these new constrains, more reflectance spectra are flagged due to non-physical Chlorophyll-a concentration estimations. The new polynomial-based MUMM NIR-modeling scheme yielded lower rho(w)(lambda) retrieval errors and particularly in extremely turbid waters. However, including the polynomial NIR relationship significantly increased the sensitivity of the algorithm to errors on the selected aerosol model from nearby clear water pixels. (C) 2013 Optical Society of America