diff --git a/workspace/R/non_dend.R b/workspace/R/non_dend.R
index fc3a2565de1e0f402314ce1c48c58a23dc13c089..2d2943ea2e9a1cd62192ec01e8fff2736bceb81a 100644
--- a/workspace/R/non_dend.R
+++ b/workspace/R/non_dend.R
@@ -82,7 +82,7 @@ assign_HUC12 <- function(divides_poi, HUC12_xwalk, nhd, CAC_num){
     ungroup() %>%
     group_by(FEATUREID, HUC_12_int) %>%
     summarize(n_NHD = n(),
-              NHD_area = mean(AreaSqKM),
+              NHD_area = mean(AREASQKM),
               HUC_12_area = sum(AreaHUC12),
               intarea = sum(intArea),
               CAC = intarea / ((NHD_area - intarea) + (HUC_12_area - intarea) + intarea)) %>%
@@ -118,7 +118,7 @@ assign_HUC12 <- function(divides_poi, HUC12_xwalk, nhd, CAC_num){
     ungroup() %>%
     group_by(HUC_12_int) %>%
     summarize(n_HUC12 = n(),
-              NHD_area = sum(AreaSqKM),
+              NHD_area = sum(AREASQKM),
               HUC_12_area = mean(AreaHUC12),
               intarea = sum(intArea),
               CAC = intarea / ((NHD_area - intarea) + (HUC_12_area - intarea) + intarea)) %>%
@@ -233,7 +233,7 @@ assign_HUC10 <- function(divides, HUC12_xwalk, nhd, CAC_num){
     ungroup() %>%
     group_by(HUC_10) %>%
     mutate(n_NHD = n(),
-           NHD_area = mean(AreaSqKM),
+           NHD_area = mean(AREASQKM),
            HUC_10_area = mean(AreaHUC10),
            intarea = sum(intArea),
            CAC = intarea / ((NHD_area - intarea) + (HUC_10_area - intarea) + intarea)) %>%
@@ -849,35 +849,46 @@ miss_term_assign <- function(term_outlets, divides_poi, nhd, elev){
       st_intersection(divides_lu_poi) %>%
       filter(!member_COMID == incomid)
     
-    # convert cat buf to format for extract input
-    buf <- st_as_sf(cats_buff)
-    
-    #**************************************************************
-    # Then do a zonal statitics type operation of the DEM within each 
-    #      buffered polygon to get the min cell value, this is a hard coded path to where the dems reside
-    
-    elev <- as.character(elev)
-    elev <- elev[grepl(unique(missing_cats$rpu), elev)]
-    
-    dem <- terra::rast(elev)
-    ex <- terra::extract(dem, terra::vect(buf), min)
-    buf_df <- as.data.frame(ex)[,2, drop = FALSE]
-    
-    # Attribute with values
-    buf_df$outlet_COMID <- incomid
-    buf_df$neighbor_COMID <- as.character(cats_buff$member_COMID)
-    buf_df$POI_ID = as.character(cats_buff$POI_ID)
-    
-    colnames(buf_df) <- c("Elev","outlet_COMID", "neighbor_COMID", "POI_ID")
-    buf_df2 <- buf_df[which.min(buf_df$Elev), ]
-    
-    return(buf_df2)
+    if(nrow(cats_buff) == 0){
+      miss_cat <- dplyr::select(st_drop_geometry(missing_cats), 
+                         outlet_COMID = member_COMID) %>%
+        dplyr::mutate(Elev = NA, neighbor_COMID = NA, POI_ID = NA) %>%
+        dplyr::select(Elev, outlet_COMID, neighbor_COMID, POI_ID)
+      return(miss_cat)
+    } else {
+      # convert cat buf to format for extract input
+      buf <- st_as_sf(cats_buff)
+      
+      #**************************************************************
+      # Then do a zonal statitics type operation of the DEM within each 
+      #      buffered polygon to get the min cell value, this is a hard coded path to where the dems reside
+      
+      elev <- as.character(elev)
+      elev <- elev[grepl(unique(missing_cats$rpu), elev)]
+      
+      dem <- terra::rast(elev)
+      ex <- terra::extract(dem, terra::vect(buf), min)
+      buf_df <- as.data.frame(ex)[,2, drop = FALSE]
+      
+      # Attribute with values
+      buf_df$outlet_COMID <- incomid
+      buf_df$neighbor_COMID <- as.character(cats_buff$member_COMID)
+      buf_df$POI_ID = as.character(cats_buff$POI_ID)
+      
+      colnames(buf_df) <- c("Elev","outlet_COMID", "neighbor_COMID", "POI_ID")
+      buf_df2 <- buf_df[which.min(buf_df$Elev), ]
+      
+      return(buf_df2)
+    }
   }
 
-  out_df <- do.call(rbind, 
-                    pbapply::pblapply(unique(term_outlets$outlet_COMID), 
+  out_df <- do.call(rbind,
+                    pbapply::pblapply(unique(term_outlets$outlet_COMID),
                                       assign_func, divides_poi, nhd, elev, cl = NULL))
-
+  
+  # out_df <- lapply(unique(term_outlets$outlet_COMID), 
+  #                                    assign_func, divides_poi, nhd, elev)
+  
   out_df <- out_df %>%
     left_join(dplyr::select(st_drop_geometry(divides_poi), HUC12_neighbor = HUC_12_int, member_COMID), 
               by = c("neighbor_COMID" = "member_COMID")) %>%