Plot two chart types (area and line) in one graph with separate legends

I've searched for a solution to my problem but haven't been able to find one that directly answers my question. For example, I've seen: Combining Bar and Line chart (double axis) in ggplot2 and Bar Chart + Line Graph on One Plot with GGPlot and a couple others, and while they get close, they don't quite hit what I'm getting at.
I am trying to create a chart with two plots, one area plot and one line plot. The two plots share the y-axis. I've been trying to use both long and wide data frame formats but I can't get the chart to work while also producing a legend. I know that to get a legend, one would normally want to use long format and to specify the variable key as color = or fill =, but because I want each variable in a separate plot type, I see no way to get this done.
I have successfully created the chart I want, but it does not include the legend, and the code seems clunky. Can anyone provide some guidance? See below for my attempts. Data below examples.
Attempt 1: Long Format
library(tidyverse)
growthUR_long %>% 
  ggplot(aes(x = Date)) + 
  geom_area(data = (. %>% filter(growthUR_long$Type == "Growth")), aes(y = value), fill = "blue", color = "black") +
  labs(x = "Date", y = "Percent") + 
  geom_line(data = (. %>% filter(growthUR_long$Type == "UR")), aes(y = value), color = "black")

Attempt 2: Wide Format
growthUR_wide %>%  
  ggplot(aes(x = Date)) + 
  geom_area(aes(y = Growth), fill = "blue", color = "black") +
  labs(x = "Date", y = "Percent") + 
  geom_line(aes(y = UR), color = "black")

Data
growthUR_long <- structure(list(Date = structure(c(16040, 16040, 16071, 16071, 
16102, 16102, 16130, 16130, 16161, 16161, 16191, 16191, 16222, 
16222, 16252, 16252, 16283, 16283, 16314, 16314, 16344, 16344, 
16375, 16375, 16405, 16405, 16436, 16436, 16467, 16467, 16495, 
16495, 16526, 16526, 16556, 16556, 16587, 16587, 16617, 16617, 
16648, 16648, 16679, 16679, 16709, 16709, 16740, 16740, 16770, 
16770, 16801, 16801, 16832, 16832, 16861, 16861, 16892, 16892, 
16922, 16922, 16953, 16953, 16983, 16983, 17014, 17014, 17045, 
17045, 17075, 17075, 17106, 17106, 17136, 17136, 17167, 17167, 
17198, 17198, 17226, 17226, 17257, 17257, 17287, 17287, 17318, 
17318, 17348, 17348, 17379, 17379, 17410, 17410, 17440, 17440, 
17471, 17471, 17501, 17501, 17532, 17532, 17563, 17563, 17591, 
17591, 17622, 17622, 17652, 17652, 17683, 17683, 17713, 17713, 
17744, 17744, 17775, 17775, 17805, 17805, 17836, 17836), class = "Date"), 
    Type = c("Growth", "UR", "Growth", "UR", "Growth", "UR", 
    "Growth", "UR", "Growth", "UR", "Growth", "UR", "Growth", 
    "UR", "Growth", "UR", "Growth", "UR", "Growth", "UR", "Growth", 
    "UR", "Growth", "UR", "Growth", "UR", "Growth", "UR", "Growth", 
    "UR", "Growth", "UR", "Growth", "UR", "Growth", "UR", "Growth", 
    "UR", "Growth", "UR", "Growth", "UR", "Growth", "UR", "Growth", 
    "UR", "Growth", "UR", "Growth", "UR", "Growth", "UR", "Growth", 
    "UR", "Growth", "UR", "Growth", "UR", "Growth", "UR", "Growth", 
    "UR", "Growth", "UR", "Growth", "UR", "Growth", "UR", "Growth", 
    "UR", "Growth", "UR", "Growth", "UR", "Growth", "UR", "Growth", 
    "UR", "Growth", "UR", "Growth", "UR", "Growth", "UR", "Growth", 
    "UR", "Growth", "UR", "Growth", "UR", "Growth", "UR", "Growth", 
    "UR", "Growth", "UR", "Growth", "UR", "Growth", "UR", "Growth", 
    "UR", "Growth", "UR", "Growth", "UR", "Growth", "UR", "Growth", 
    "UR", "Growth", "UR", "Growth", "UR", "Growth", "UR", "Growth", 
    "UR", "Growth", "UR"), value = c(0.0322086110094131, 0.0884577488042408, 
    0.0329947909338724, 0.0867061999760205, 0.0369791049661803, 
    0.0851919078232827, 0.0355169985403396, 0.0862978396964806, 
    0.0396692395382414, 0.0816915271432576, 0.0403342630003154, 
    0.08139558480318, 0.0353677807163653, 0.0801250617385394, 
    0.0348174892816639, 0.079246182084833, 0.0421586821845255, 
    0.0775132293815652, 0.045497159757506, 0.0762505497421263, 
    0.0479855163519212, 0.0756443010441955, 0.0431645807500451, 
    0.075679052359729, 0.0461836867149323, 0.0744676156513522, 
    0.0458201746505216, 0.0729279736217616, 0.0433054752282878, 
    0.0721403911270975, 0.0436767425553533, 0.070408204935737, 
    0.0405882652967209, 0.0703511470179263, 0.0391375049579188, 
    0.0690899407055714, 0.0393839156918634, 0.0690807060415389, 
    0.040776372038464, 0.0684442282747515, 0.0373001234501384, 
    0.0675339627652226, 0.0354219436836223, 0.0672348391519624, 
    0.0356159068524273, 0.0656551851245833, 0.039641088863388, 
    0.0647037939841651, 0.0399609996985248, 0.0635515287191864, 
    0.0317013278193472, 0.0630723444645541, 0.0328512011800204, 
    0.0620325823861175, 0.0327218554890207, 0.0614388558423061, 
    0.0334585785814081, 0.0609839998459472, 0.0308070913309046, 
    0.0597535514359257, 0.0338149386881423, 0.0591362192249516, 
    0.040317092357782, 0.0588051370066046, 0.034759613402543, 
    0.0566379922660853, 0.0394899239434814, 0.0563870883959305, 
    0.0314090340958895, 0.056679569373787, 0.0299952260614151, 
    0.0557285832378203, 0.0266744499962965, 0.054509993105507, 
    0.0356026530670595, 0.0541931717398106, 0.0342705188801191, 
    0.0539209138078119, 0.0357561213000237, 0.0534049405690803, 
    0.0282430112386445, 0.0538194547588392, 0.0320635214245448, 
    0.0535277334240149, 0.0294972674271483, 0.0532145449540054, 
    0.0254391816585626, 0.0521552584654269, 0.0251735156510164, 
    0.0514311178290782, 0.024173910868835, 0.0513899849245179, 
    0.0272327608151584, 0.0507680778938399, 0.0222257590529378, 
    0.0508044295844716, 0.0270204198555397, 0.0514736110118438, 
    0.0230437398194829, 0.0520862873603839, 0.0267092143066034, 
    0.0518027591652176, 0.0237249157033108, 0.0513989487830691, 
    0.0284997482684342, 0.0508771526917733, 0.0287893153050511, 
    0.0453979456228745, 0.0295347574671514, 0.045531549777798, 
    0.0385321606196869, 0.0454762717198563, 0.0394461559426129, 
    0.0471731715700883, 0.035513049515421, 0.0462938811890929, 
    0.0369998652281156, 0.0456567853126557, 0.0383561097442899, 
    0.0456830160674887)), row.names = c(NA, -120L), class = c("tbl_df", 
"tbl", "data.frame"))

growthUR_wide <- structure(list(Date = structure(c(16040, 16071, 16102, 16130, 
16161, 16191, 16222, 16252, 16283, 16314, 16344, 16375, 16405, 
16436, 16467, 16495, 16526, 16556, 16587, 16617, 16648, 16679, 
16709, 16740, 16770, 16801, 16832, 16861, 16892, 16922, 16953, 
16983, 17014, 17045, 17075, 17106, 17136, 17167, 17198, 17226, 
17257, 17287, 17318, 17348, 17379, 17410, 17440, 17471, 17501, 
17532, 17563, 17591, 17622, 17652, 17683, 17713, 17744, 17775, 
17805, 17836), class = "Date"), Growth = c(0.0322086110094131, 
0.0329947909338724, 0.0369791049661803, 0.0355169985403396, 0.0396692395382414, 
0.0403342630003154, 0.0353677807163653, 0.0348174892816639, 0.0421586821845255, 
0.045497159757506, 0.0479855163519212, 0.0431645807500451, 0.0461836867149323, 
0.0458201746505216, 0.0433054752282878, 0.0436767425553533, 0.0405882652967209, 
0.0391375049579188, 0.0393839156918634, 0.040776372038464, 0.0373001234501384, 
0.0354219436836223, 0.0356159068524273, 0.039641088863388, 0.0399609996985248, 
0.0317013278193472, 0.0328512011800204, 0.0327218554890207, 0.0334585785814081, 
0.0308070913309046, 0.0338149386881423, 0.040317092357782, 0.034759613402543, 
0.0394899239434814, 0.0314090340958895, 0.0299952260614151, 0.0266744499962965, 
0.0356026530670595, 0.0342705188801191, 0.0357561213000237, 0.0282430112386445, 
0.0320635214245448, 0.0294972674271483, 0.0254391816585626, 0.0251735156510164, 
0.024173910868835, 0.0272327608151584, 0.0222257590529378, 0.0270204198555397, 
0.0230437398194829, 0.0267092143066034, 0.0237249157033108, 0.0284997482684342, 
0.0287893153050511, 0.0295347574671514, 0.0385321606196869, 0.0394461559426129, 
0.035513049515421, 0.0369998652281156, 0.0383561097442899), UR = c(0.0884577488042408, 
0.0867061999760205, 0.0851919078232827, 0.0862978396964806, 0.0816915271432576, 
0.08139558480318, 0.0801250617385394, 0.079246182084833, 0.0775132293815652, 
0.0762505497421263, 0.0756443010441955, 0.075679052359729, 0.0744676156513522, 
0.0729279736217616, 0.0721403911270975, 0.070408204935737, 0.0703511470179263, 
0.0690899407055714, 0.0690807060415389, 0.0684442282747515, 0.0675339627652226, 
0.0672348391519624, 0.0656551851245833, 0.0647037939841651, 0.0635515287191864, 
0.0630723444645541, 0.0620325823861175, 0.0614388558423061, 0.0609839998459472, 
0.0597535514359257, 0.0591362192249516, 0.0588051370066046, 0.0566379922660853, 
0.0563870883959305, 0.056679569373787, 0.0557285832378203, 0.054509993105507, 
0.0541931717398106, 0.0539209138078119, 0.0534049405690803, 0.0538194547588392, 
0.0535277334240149, 0.0532145449540054, 0.0521552584654269, 0.0514311178290782, 
0.0513899849245179, 0.0507680778938399, 0.0508044295844716, 0.0514736110118438, 
0.0520862873603839, 0.0518027591652176, 0.0513989487830691, 0.0508771526917733, 
0.0453979456228745, 0.045531549777798, 0.0454762717198563, 0.0471731715700883, 
0.0462938811890929, 0.0456567853126557, 0.0456830160674887)), row.names = c(NA, 
-60L), class = c("tbl_df", "tbl", "data.frame"))

You can use wide format and specify fill, color within aes. Then to get wanted color ("blue", "black") you can scale_(fill/color)_manual.
ggplot(growthUR_wide, aes(Date)) + 
    geom_area(aes(y = Growth, fill = "Growth"), color = "black") +
    geom_line(aes(y = UR, color = "UK"), size = 1.5) +
    labs(x = "Date", 
y = "Percent", 
fill = NULL, 
color = NULL) +
    scale_color_manual(values = "black") +
    scale_fill_manual(values = "blue") +
    theme_classic()

More interesting solution (I'm maybe more correct from the data visualisation perspective) is to add annotation to your plot (I'm not that good with picking colors, you can decide yourself what goes best).
In this solution you annotate your layers with geom_text.
ggplot(growthUR_wide, aes(Date)) + 
    geom_area(aes(y = Growth), color = "black", fill = "thistle2") +
    geom_text(aes(growthUR_wide$Date[6], 0.02, label = "Growth"), 
data.frame(), size = 10, color = "navyblue") +
    geom_text(aes(growthUR_wide$Date[15], 0.08, label = "UK"), 
data.frame(), size = 10, color = "black") +
    geom_line(aes(y = UR), size = 1.5) +
    labs(x = "Date", 
y = "Percent") +
    theme_classic()