Figure 1. Linear Regression Models. the Y-Axis Represents DEM Adjustments in (-)Meters

Figure 1. Linear regression models. The y-axis represents DEM adjustments in (-)meters. The x-axes represent the difference in surface water area in km2 calculated between landsat 5 TM imagery and a 1-Dimensional analysis with water gauge data. A simple linear regression model is displayed for each region and date by a red line. The y-value when x=0 for each graph is displayed in the top right corner. According to the linear model, this y-value is the estimated DEM adjustment needed for there to be no difference between derived surface water area (km2) between the two methodsfor each respective region and date.

Figure 2. Spline Interpolations. The y-axis represents DEM adjustments in (-)meters. The x-axes represent the difference in surface water area in km2 calculated between landsat 5 TM imagery and a 1-Dimensional analysis with water gauge data. A spline interpolation model (black line) is displayed for each region and date. The y-value when x=0 for each model is displayed in the top right corner. According to the spline model, this y-value is the estimated DEM adjustment needed for there to be no difference between derived surface water area (km2) between the two methodsfor each respective region and date.

Figure 3. 2nd Order Polynomial Models. The y-axis represents DEM adjustments in (-)meters. The x-axes represent the difference in surface water area in km2 calculated between landsat 5 TM imagery and a 1-Dimensional analysis with water gauge data. A 2nd order polynomial model (blue line) is displayed for each region and date. The y-value when x=0 for each model is displayed in the top right corner. According to the 2nd order polynomial model, this y-value is the estimated DEM adjustment needed for there to be no difference between derived surface water area (km2) between the two methodsfor each respective region and date.

Figure 4. 3rd Order Polynomial Models. The y-axis represents DEM adjustments in (-)meters. The x-axes represent the difference in surface water area in km2 calculated between landsat 5 TM imagery and a 1-Dimensional analysis with water gauge data. A 3rd order polynomial model (blue line) is displayed for each region and date. The y-value when x=0 for each model is displayed in the top right corner. According to the 3rd order polynomial model, this y-value is the estimated DEM adjustment needed for there to be no difference between derived surface water area (km2) between the two methods for each respective region and date.

Appendix 2 Table 1. Summary Table of y-values when x=0 for all models for each respective region and date. The best model from each region is highlighted in the “Best_Model” column. Averages and standard deviations are displayed in the last two rows.
LS location and serial date number / Date of gauge data with matching temporal resolution / DEM adjustment with smallest difference between LS and 1D derived surface water area (km2) / Linear model y-value when x=0 / Spline model y-value when x=0 / 2nd order polynomial model y-value when x=0 / 3rd order polynomial model y-value when x=0 / Best overall model y-value when x=0
SW_a732847 / 6/19/2006 / 3.25 / 3.3111554 / 3.31817 / 3.401011 / 3.319117 / 3.319117
SW_a733169 / 5/7/2007 / 2.25 / 1.8383977 / 2.180737 / 1.984587 / 2.185267 / 2.185267
SW_a734030 / 9/14/2009 / 2.25 / 2.0013984 / 2.323746 / 2.215591 / 2.261502 / 2.215591
SW_a734079 / 11/2/2009 / 1.5 / 1.4218735 / 1.427082 / 1.45626 / 1.487928 / 1.45626
S_a733302 / 9/17/2007 / 2.75 / 2.4791457 / 2.741727 / 2.725953 / 2.816174 / 2.816174
S_a734072 / 10/26/2009 / 1 / 1.1476429 / 1.037205 / 0.9322926 / 0.8831043 / 0.8831043
S_a734184 / 2/15/2010 / 0 / 1.177247 / 0.06812635 / 0.5927602 / 0.1568128 / 0.1568128
Sylhet_a732616 / 10/31/2005 / 3 / 2.5805002 / 2.88916 / 2.911954 / 2.99285 / 2.99285
Sylhet_a733064 / 1/22/2007 / 2 / 1.7961808 / 2.114003 / 1.768074 / 1.935161 / 2.114003
Sylhet_a733302 / 9/19/2007 / 3.25 / 3.1237504 / 3.133314 / 3.23576 / 3.148383 / 3.148383
Sylhet_a733547 / 5/19/2008 / 2.75 / 1.9740086 / 2.848702 / 2.198787 / 2.604903 / 2.604903
W_a732322 / 1/10/2005 / 0 / 1.165811 / -0.00310083 / 0.5618578 / 0.2718652 / -0.003100827
W_a733715 / 11/3/2008 / 2 / 1.6111128 / 2.094729 / 1.630376 / 1.815931 / 2.094729
W_a734051 / 10/5/2009 / 2.75 / 2.161433 / 2.786042 / 2.531911 / 2.842519 / 2.786042
Average / 1.916666667 / 1.8526438 / 1.930642835 / 1.876478307 / 1.91476782 / 1.918009018
Std Dev / 1.079434376 / 0.6919599 / 1.066782378 / 0.915291404 / 1.029696024 / 1.063657835