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Working on new CREP and fallow program info

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Alex 2026-04-17 17:09:18 -06:00
parent 1bacd2467c
commit d388355373
4 changed files with 121 additions and 1 deletions
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12
1_Data_Proc.r
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@ -18,15 +18,25 @@ CROP_LEGAL
PARCEL_YEAR_WDID <- CROP_LEGAL %>% select(parcel_id,cal_year,gw_id1,gw_id2,gw_id3,gw_id4,gw_id5,gw_id6,gw_id7,gw_id8,gw_id9,gw_id10,gw_id11,gw_id12,gw_id13,gw_id14,gw_id15,gw_id16,gw_id17,gw_id18,gw_id19,gw_id20) %>% pivot_longer(-c("parcel_id","cal_year"),values_to="wdid") %>% select(-name) %>% filter(!is.na(wdid))
WELL_LIST <- PARCEL_YEAR_WDID %>% pull(wdid) %>% unique
WATER_RIGHTS <- WATER_RIGHTS %>% filter(wdid %in% WELL_LIST)
WATER_RIGHTS
WATER_RIGHTS %>% group_by(wdid) %>% summarize(rights_absolute=sum(rights_absolute),rights_apex=sum(rights_apex)) %>% filter(rights_absolute==0,rights_apex==0)
WATER_RIGHTS %>% filter(rights_absolute==0,rights_apex==0)
read_csv("https://dwr.state.co.us/Rest/GET/api/v2/waterrights/transaction/?format=csv&wdid=2005165",skip=2)
WATER_RIGHTS %>% filter(wdid=='2013695')
WATER_RIGHTS
WATER_RIGHTS %>% mutate(
WATER_RIGHTS %>% select(wdid,rights_absolute,rights_apex) %>% filter(rights_absolute==0,rights_apex==0)
WATER_RIGHTS %>% filter(wdid=='2013695')%>% select(wdid,rights_absolute,rights_apex)
WATER_RIGHTS %>% group_by(wdid) %>% mutate(total=sum(rights_absolute)+sum(rights_apex)) %>% filter(total==0) %>% arrange(wdid)
TRANSACT <- 'https://dwr.state.co.us/Rest/GET/api/v2/waterrights/transaction/?format=csv&division=3&pageSize=500000+&apiKey=PwevUQJCStcYZfqrOYbuyztmNPlUJWby'
TRANSACT <- read_csv(TRANSACT,skip=2)
colnames(TRANSACT )
TEMP <- TRANSACT %>% select(WaterRightNum,wdid,associatedWdid,planWdid,adjudicationDate,appropriationDate,totalVolumetricLimit,maxDecreedRate,comments,moreInformation)
TEMP %>% filter(wdid=='2005005')
TEMP %>% filter(WaterRightNum=='99984')
%>% filter(
WATER_RIGHTS
WATER_RIGHTS %>% select(rights_absolute,rights_apex)
WATER_RIGHTS

37
Data/CREP_and_Fallow/CREP_Perm.csv Normal file
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@ -0,0 +1,37 @@
wdid1,wdid2,wdid3,wdid4,wdid5
2013956
2005950,2005951,2005955
2014091,2006322,2006321,2014092
2006327,2006328
2006325,2006326
2006332,2006331
2006684,2006685,2006686
2014274,2014107,2005512,2005448
2705248
2005098
2008177,2008178,2013955
2006005,2006656,2005171,2006655
2006323,2006324,2014088
2008223,2008224,2008225,2014054
2005121,2008772
2005476,2005537,2005538,2014266
2005769,2005770,2005771,2014270
2005766,2005767,2005768,2014267,2014268
2008439
2008440,2208441
2009992
2009197,2014045,2014046
2006003,2006004,2006653,2006654,2014311
2005952,2005953,2005954
2014309,2006334,2014080,2006333
2006337,2006338,2014081,2014082
2008239
2705472
2010499,2010500,2013906,2014178
2006528,2006529
2014189,2009110
2008146,2008147,2013953
2005665,2005664,2005666
2005662,2005663
2008389,2014023
2705229
1 wdid1,wdid2,wdid3,wdid4,wdid5
2 2013956
3 2005950,2005951,2005955
4 2014091,2006322,2006321,2014092
5 2006327,2006328
6 2006325,2006326
7 2006332,2006331
8 2006684,2006685,2006686
9 2014274,2014107,2005512,2005448
10 2705248
11 2005098
12 2008177,2008178,2013955
13 2006005,2006656,2005171,2006655
14 2006323,2006324,2014088
15 2008223,2008224,2008225,2014054
16 2005121,2008772
17 2005476,2005537,2005538,2014266
18 2005769,2005770,2005771,2014270
19 2005766,2005767,2005768,2014267,2014268
20 2008439
21 2008440,2208441
22 2009992
23 2009197,2014045,2014046
24 2006003,2006004,2006653,2006654,2014311
25 2005952,2005953,2005954
26 2014309,2006334,2014080,2006333
27 2006337,2006338,2014081,2014082
28 2008239
29 2705472
30 2010499,2010500,2013906,2014178
31 2006528,2006529
32 2014189,2009110
33 2008146,2008147,2013953
34 2005665,2005664,2005666
35 2005662,2005663
36 2008389,2014023
37 2705229

54
Data/CREP_and_Fallow/CREP_Temp.csv Normal file
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@ -0,0 +1,54 @@
wdid1,wdid2,wdid3,wdid4,wdid5
2705126
2705519,2706148
2705342,2706196
2705341,2706195
2006478,2008677,2008678,2012887
2005857,2008391
2005642,2005643,2014474
2006153,2013962
2705318
2012537,2014288
2706253,2705317
2705186,2705328
2705054
2008155,2008156
2008129,2008130,2014244
2005921,2005941,2006283,2006525
2006335,2006336,2014086,2014087
2706014
2706246
2005886,2005868
2005595
2013377,2013618
2005133,2005533
2705344
2705067,2705068,2705523
2705069,2705070
2009113
2705293
2705290
2705224
2705225
2705225
2705224
2705197,2705359
2705246,2706237
2705006,2705790
2705184
2705185,2705356
2705327
2005774,2005775
2013784
2705259,2705021,2705020
2706194
2006376,2006375
2005127,2005168
2705347,2706258
2005116
2009940,2013577
2005038,2010590,2014490
2705247
2705080
2013928,2011009
2008191
1 wdid1,wdid2,wdid3,wdid4,wdid5
2 2705126
3 2705519,2706148
4 2705342,2706196
5 2705341,2706195
6 2006478,2008677,2008678,2012887
7 2005857,2008391
8 2005642,2005643,2014474
9 2006153,2013962
10 2705318
11 2012537,2014288
12 2706253,2705317
13 2705186,2705328
14 2705054
15 2008155,2008156
16 2008129,2008130,2014244
17 2005921,2005941,2006283,2006525
18 2006335,2006336,2014086,2014087
19 2706014
20 2706246
21 2005886,2005868
22 2005595
23 2013377,2013618
24 2005133,2005533
25 2705344
26 2705067,2705068,2705523
27 2705069,2705070
28 2009113
29 2705293
30 2705290
31 2705224
32 2705225
33 2705225
34 2705224
35 2705197,2705359
36 2705246,2706237
37 2705006,2705790
38 2705184
39 2705185,2705356
40 2705327
41 2005774,2005775
42 2013784
43 2705259,2705021,2705020
44 2706194
45 2006376,2006375
46 2005127,2005168
47 2705347,2706258
48 2005116
49 2009940,2013577
50 2005038,2010590,2014490
51 2705247
52 2705080
53 2013928,2011009
54 2008191

19
Data/CREP_and_Fallow/Create_CREP_Data.r Normal file
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@ -0,0 +1,19 @@
library(tidyverse)
library(janitor)
################Perm CREP contract
CONTRACT_NUMBER <- c('ALA#3','ALA#6','ALA#7','ALA#8','ALA#9','ALA#10','ALA#12','ALA#15','SAG#6','ALA#17','ALA#18','ALA#22','ALA#23','ALA#25','RG#4','ALA#26','ALA#27','ALA#28','ALA#29','ALA#30','ALA#31','ALA#32','ALA#33','ALA#34','ALA#38','ALA#39','SAG#33','SAG#34','ALA#40','ALA#41','ALA#42','ALA#43','ALA#44','ALA#45','ALA#47','SAG#39')
FIRST_FALLOW_YEAR <- c(2014,2014,2014,2014,2014,2014,2014,2014,2015,2015,2015,2015,2015,2015,2016,2016,2016,2016,2016,2016,2016,2016,2016,2016,2018,2018,2020,2020,2020,2020,2020,2021,2021,2021,2021,2024)
ACRES <- c(124.9,126,119.5,119.2,121.1,118.1,122.8,67,114.1,118.6,122,121,124.66,80,149.8,110,110,110,92.9,122.3,94,123,126,126,121.28,120.5,122.8,122,118,121.84,120,120,120.01,120.1,120.11,122.94)
CREP_PERM <- cbind(CONTRACT_NUMBER,FIRST_FALLOW_YEAR,ACRES,read_csv("CREP_Perm.csv")) %>% as_tibble %>% mutate(program='CREP',RETURN_YEAR=Inf,contract_type='Perm')
CREP_PERM
###############################Temp CREP contract
CONTRACT_NUMBER <- c('SAG#1','SAG#2','SAG#3','SAG#4','RG#1','RG#2','ALA#2','ALA#11','SAG#7','SAG#8','SAG#9','SAG#10','SAG#11','ALA#16','ALA#19','ALA#21','ALA#24','SAG#12','SAG#13','RG#3','RG#7','RG#8','ALA#35','SAG#14','SAG#15','SAG#16','ALA#36','SAG#17','SAG#18','SAG#19','SAG#20','SAG#21','SAG#22','SAG#23','SAG#24','SAG#25','SAG#26','SAG#27','SAG#28','ALA#37','SAG#29','SAG#30','SAG#31','RG#9','RG#10','SAG#32','RG#11','SAG#35','SAG#36','SAG#37','SAG#38','RG#12','RG#13')
FIRST_FALLOW_YEAR <- c(2014,2014,2014,2014,2014,2014,2014,2014,2015,2015,2015,2015,2015,2015,2015,2015,2015,2016,2016,2016,2016,2016,2016,2017,2017,2017,2017,2018,2018,2018,2018,2018,2018,2018,2018,2018,2018,2018,2018,2018,2019,2019,2019,2019,2019,2020,2022,2023,2023,2023,2023,2024,2024)
RETURN_YEAR <- c(2029,2029,2029,2029,2029,2029,2029,2029,2030,2030,2030,2030,2030,2030,2030,2030,2030,2031,2031,2031,2031,2031,2031,2032,2032,2032,2032,2033,2033,2033,2033,2033,2033,2033,2033,2033,2033,2033,2033,2033,2034,2034,2034,2034,2034,2035,2037,2038,2038,2038,2038,2038,2038)
ACRES <- c(144,144,210,60,130,120.4,120,121.5,172.09,113,191,116.5,120,124,120,129,120.97,120,124,139.9,122,123.32,122,120,122.4,123.4,113.92,120,120.35,114.32,124.78,125.58,119.3,123,125.15,126.1,126.3,125.5,53.6,106,112.81,126.95,118.9,118.36,120,120,100,120,130.02,114.54,120,121.92,126.15)
CREP_TEMP <- cbind(CONTRACT_NUMBER,FIRST_FALLOW_YEAR,RETURN_YEAR,ACRES,read_csv("CREP_Temp.csv")) %>% as_tibble %>% mutate(program='CREP',contract_type='Temp')
CREP_TEMP %>% full_join(CREP_PERM)
CREP_PERM