Create Env, Setup Notebooks, FIAT data

Data/damage_functions/flooding/JRC_damage_functions_linking.csv

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+Name,Link,Damage Type,type
+residential,residential,total,residential
+commercial,commercial,total,commercial
+industrial,industrial,total,industrial

Data/max_potential_damages/JRC_base_damage_values.csv

@@ -0,0 +1,249 @@
+Country,ISO A3 code,Construction Cost Residential (2010 €),Construction Cost Commercial (2010 €),Construction Cost Industrial (2010 €),GDP per capita (2010 US$)
+Afghanistan,AFG,275.790831,323.1586611,241.0331217,561.1976175
+Albania,ALB,597.450818,662.0776912,462.6412974,4175.121638
+Algeria,DZA,606.945797,671.8348045,468.835172,4349.569325
+American Samoa,ASM,0,0,0,
+Andorra,AND,0,0,0,
+Angola,AGO,599.8424625,664.5364111,464.2028853,4218.649126
+Antigua and Barbuda,ATG,925.8358632,994.0579546,669.4173335,13017.31039
+Argentina,ARG,881.5030426,949.8160048,642.2775019,11460.37615
+Armenia,ARM,534.3491473,596.9397752,421.0716996,3124.784854
+Aruba,ABW,1177.283822,1242.30466,819.8028211,24289.14152
+Australia,AUS,1576.098086,1628.49359,1048.521336,51800.93139
+Austria,AUT,1511.201454,1566.185027,1011.987128,46444.18444
+Azerbaijan,AZE,680.0220464,746.5730574,516.0173514,5842.805784
+"Bahamas, The",BHS,1132.084932,1197.989467,793.1745966,21941.8693
+Bahrain,BHR,1103.780434,1170.17358,776.414905,20545.96702
+Bangladesh,BGD,310.4029399,360.625262,266.308433,762.8037395
+Barbados,BRB,997.8679814,1065.620182,713.0866498,15812.27978
+Belarus,BLR,678.9469233,745.4778393,515.3291481,5818.854859
+Belgium,BEL,1484.68729,1540.673085,996.9904855,44358.26064
+Belize,BLZ,616.3835677,681.5222187,474.9767133,4527.336639
+Benin,BEN,298.6383882,347.9260805,257.7695017,690.0022811
+Bermuda,BMU,1934.767604,1969.723079,1246.474681,88207.32756
+Bhutan,BTN,467.7154928,527.5476903,376.3289318,2211.340513
+Bolivia,BOL,444.243464,502.9384002,360.3356987,1934.666067
+Bosnia and Herzegovina,BIH,608.6103253,673.544147,469.9194277,4380.604285
+Botswana,BWA,728.2528456,795.5798592,546.7199689,6980.361812
+Brazil,BRA,867.0295965,935.3378024,633.3712371,10978.26024
+Brunei Darussalam,BRN,1291.355959,1353.612025,886.3121928,30880.34486
+Bulgaria,BGR,711.9044621,778.995481,536.3496982,6580.813875
+Burkina Faso,BFA,281.6373864,329.510134,245.3358608,592.6074699
+Burundi,BDI,192.1160722,231.0636218,177.6806883,219.5297995
+Cabo Verde,CPV,552.8374016,616.079408,433.3271136,3413.26337
+Cambodia,KHM,313.4844445,363.945784,268.5366067,782.6188886
+Cameroon,CMR,363.0163506,417.0123338,303.9067621,1145.368992
+Canada,CAN,1523.914831,1578.406357,1019.163284,47465.34593
+Cayman Islands,CYM,0,0,0,
+Central African Republic,CAF,254.718351,300.1839723,225.4036291,456.5634087
+Chad,TCD,332.1348161,383.993383,281.9505512,909.2999069
+Channel Islands,CHA,0,0,0,
+Chile,CHL,916.5691459,984.8231166,663.7615377,12681.7652
+China,CHN,611.4222514,676.4310131,471.7500326,4433.340886
+Colombia,COL,694.8690263,761.6848526,525.5038566,6179.770329
+Comoros,COM,309.4612565,359.6100632,265.6268313,756.8106118
+"Congo, Dem. Rep.",COD,229.0934606,272.0590788,206.1207618,346.7042747
+"Congo, Rep.",COG,520.6060175,582.6815345,411.9187266,2920.406708
+Costa Rica,CRI,759.0653322,826.7646519,566.16709,7773.185487
+Cote d'Ivoire,CIV,382.4394043,437.6749266,317.5654555,1311.326565
+Croatia,HRV,938.9350803,1007.100749,677.3971539,13500.85443
+Cuba,CUB,673.6603667,740.0906478,511.9426519,5701.962671
+Curacao,CUW,0,0,0,
+Cyprus,CYP,1241.656317,1305.20806,857.4530452,27889.03718
+Czech Republic,CZE,1087.405517,1154.0579,766.6883148,19764.01554
+Denmark,DNK,1642.382404,1691.943646,1085.594448,57647.92502
+Djibouti,DJI,387.0973395,442.6187238,320.824687,1353.193028
+Dominica,DMA,726.0971561,793.3946024,545.3546531,6926.847597
+Dominican Republic,DOM,654.7359791,720.7808145,499.7855535,5295.39969
+Ecuador,ECU,622.0766024,687.360658,478.6742762,4636.693098
+"Egypt, Arab Rep.",EGY,512.4796597,574.2378458,406.4887842,2803.532963
+El Salvador,SLV,554.7780738,618.0857491,434.6097835,3444.456148
+Equatorial Guinea,GNQ,1017.629948,1085.186967,724.9797255,16638.13107
+Eritrea,ERI,234.5981433,278.1191478,210.2903648,368.7477582
+Estonia,EST,968.4306262,1036.421489,695.3020278,14629.64939
+Ethiopia,ETH,228.3242145,271.2113894,205.5368436,343.6901516
+Faeroe Islands,FRO,0,0,0,
+Fiji,FJI,567.2667272,630.9849618,442.8473691,3649.382362
+Finland,FIN,1508.166341,1563.266288,1010.272543,46202.41516
+France,FRA,1436.35291,1494.080603,969.5434816,40706.07833
+French Polynesia,PYF,0,0,0,
+Gabon,GAB,815.4430557,883.5900983,601.434557,9362.113583
+"Gambia, The",GMB,276.7630811,324.2155444,241.7496257,566.3481084
+Georgia,GEO,498.8281616,560.0314127,397.3364967,2613.756925
+Germany,DEU,1450.075218,1507.319721,977.3502816,41723.3659
+Ghana,GHA,384.0924639,439.4299309,318.7228352,1326.092033
+Greece,GRC,1223.830116,1287.812776,847.0581133,26861.4598
+Greenland,GRL,0,0,0,
+Grenada,GRD,743.4820588,811.0047431,556.3475655,7365.666529
+Guam,GUM,0,0,0,
+Guatemala,GTM,517.9847047,579.9589069,410.1686539,2882.386026
+Guinea,GIN,250.114583,295.1467169,221.9625409,435.448888
+Guinea-Bissau,GNB,270.592359,317.5030796,237.1953335,534.1475781
+Guyana,GUY,517.4003498,579.3518311,409.7783311,2873.952008
+Haiti,HTI,295.1353889,344.1378689,255.2168608,669.1869294
+Honduras,HND,456.6712768,515.979746,368.8197349,2078.32576
+"Hong Kong SAR, China",HKG,1317.816811,1379.327906,901.6060265,32549.99823
+Hungary,HUN,924.2232407,992.4513611,668.4337339,12958.53036
+Iceland,ISL,1449.7087,1506.966227,977.1419154,41695.99365
+India,IND,394.0367851,449.9761073,325.6689774,1417.073614
+Indonesia,IDN,522.4035424,584.5479623,413.1180146,2946.656061
+"Iran, Islamic Rep.",IRN,672.4280463,738.8344312,511.1526473,5674.923927
+Iraq,IRQ,613.5608975,678.626014,473.14144,4473.71044
+Ireland,IRL,1529.285536,1583.566984,1022.191997,47900.83929
+Isle of Man,IMN,0,0,0,
+Israel,ISR,1286.031985,1348.433368,883.2291431,30550.9204
+Italy,ITA,1368.137169,1428.129461,930.5586385,35875.72655
+Jamaica,JAM,636.3032182,701.9338614,487.8912838,4917.023202
+Japan,JPN,1468.555098,1525.134621,987.8454877,43117.82967
+Jordan,JOR,608.0810369,673.0006451,469.5747053,4370.721045
+Kazakhstan,KAZ,805.5689623,873.6586347,595.286063,9070.649972
+Kenya,KEN,341.5552543,394.0884321,288.6809109,977.7780694
+Kiribati,KIR,406.770906,463.452974,334.5239165,1539.047436
+"Korea, Dem. Rep.",PRK,432.0672802,490.1355459,351.9873315,1800
+"Korea, Rep.",KOR,1136.233273,1202.061951,795.6253707,22151.20912
+Kosovo,KOS,544.640388,607.5993904,427.9015587,3283.429596
+Kuwait,KWT,1407.040382,1465.76952,952.8278994,38584.4796
+Kyrgyz Republic,KGZ,327.9761899,379.5304071,278.9699811,880.0377751
+Lao PDR,LAO,360.2505816,414.063661,301.9526333,1122.852316
+Latvia,LVA,881.092001,949.4050662,642.0248841,11446.50818
+Lebanon,LBN,794.6826286,862.6988576,588.4935637,8755.849968
+Lesotho,LSO,355.2721427,408.7518639,298.4292267,1083.012065
+Liberia,LBR,223.8832668,266.3135253,202.1597549,326.6042804
+Libya,LBY,907.9771115,976.2546195,658.5095224,12375.44953
+Liechtenstein,LIE,0,0,0,
+Lithuania,LTU,892.9915407,961.2960566,649.3306751,11852.1696
+Luxembourg,LUX,2052.734797,2080.914052,1310.278866,102856.9717
+"Macao SAR, China",MAC,1590.582595,1642.374927,1056.64309,53045.87903
+"Macedonia, FYR",MKD,611.8979047,676.919248,472.0595594,4442.299972
+Madagascar,MDG,245.3277238,289.9020277,218.3740678,414.1427872
+Malawi,MWI,232.3339239,275.6277399,208.5771733,359.5795268
+Malaysia,MYS,794.6264382,862.6422601,588.4584662,8754.24282
+Maldives,MDV,710.7223976,777.7952946,535.5984431,6552.484491
+Mali,MLI,295.8996139,344.9645921,255.7741553,673.6946614
+Malta,MLT,1085.946695,1152.621327,765.8206764,19695.25572
+Marshall Islands,MHL,534.4631835,597.057974,421.1474927,3126.516365
+Mauritania,MRT,341.4708011,393.9980211,288.6207041,977.1505551
+Mauritius,MUS,752.0055697,819.6277895,561.7224544,7586.893454
+Mexico,MEX,800.4125209,868.4687473,592.070518,8920.689016
+"Micronesia, Fed. Sts.",FSM,514.928846,576.7836822,408.1267129,2838.448547
+Moldova,MDA,416.0184836,473.2208128,340.9271882,1631.535832
+Monaco,MCO,2344.468082,2353.968073,1465.68601,145229.8379
+Mongolia,MNG,473.7078907,533.8159787,380.3916466,2285.645378
+Montenegro,MNE,714.2011167,781.326934,537.8087674,6636.070538
+Morocco,MAR,513.8288217,575.640357,407.391207,2822.733739
+Mozambique,MOZ,247.5910579,292.3827458,220.0721313,424.134902
+Myanmar,MMR,377.7509832,432.6943819,314.2786109,1270
+Namibia,NAM,649.0906145,715.0127142,496.1483559,5177.681179
+Nepal,NPL,282.2156901,330.1378607,245.7606959,595.7716261
+Netherlands,NLD,1558.804244,1611.907838,1038.809007,50338.25483
+New Caledonia,NCL,0,0,0,
+New Zealand,NZL,1322.427218,1383.804681,904.265806,32846.45443
+Nicaragua,NIC,406.3781041,463.0377209,334.2514286,1535.192167
+Niger,NER,232.3890957,275.6884683,208.6189492,359.801242
+Nigeria,NGA,475.7141306,535.913304,381.7500316,2310.860518
+Northern Mariana Islands,MNP,0,0,0,
+Norway,NOR,1916.796979,1952.742448,1236.702354,86096.13602
+Oman,OMN,1111.53211,1177.796506,781.0114561,20922.65677
+Pakistan,PAK,347.5813879,400.5355391,292.970969,1023.195756
+Palau,PLW,825.0494476,893.243978,607.4051799,9651.133366
+Panama,PAN,761.3438091,829.0669876,567.6001738,7833.903551
+Papua New Guinea,PNG,390.2667108,445.9801458,323.0388349,1382.143749
+Paraguay,PRY,532.7678328,595.3005511,420.0204319,3100.835119
+Peru,PER,644.1248989,709.9360463,492.9449479,5075.47667
+Philippines,PHL,461.5050106,521.0451568,372.1097517,2135.918407
+Poland,POL,911.0387691,979.3085581,660.3818969,12484.07315
+Portugal,PRT,1143.847869,1209.534515,800.1203128,22538.65408
+Puerto Rico,PRI,1216.361923,1280.519692,842.6961812,26437.99218
+Qatar,QAT,1784.525908,1827.396678,1164.321909,71510.15575
+Romania,ROU,772.636806,840.4709292,574.6932186,8139.146673
+Russian Federation,RUS,858.7993592,927.0970961,628.2963785,10709.76936
+Rwanda,RWA,268.9663648,315.7325058,235.9925769,525.8549278
+Samoa,WSM,555.5411892,618.8745482,435.1139652,3456.76966
+San Marino,SMR,0,0,0,
+Sao Tome and Principe,STP,360.8836083,414.7386942,302.4000991,1127.981667
+Saudi Arabia,SAU,1078.070945,1144.863283,761.1333947,19326.58255
+Senegal,SEN,344.3388056,397.0674482,290.6640058,998.5995764
+Serbia,SCG,659.6547978,725.8036465,502.9506504,5399.29762
+Seychelles,SYC,862.8920742,931.1957262,630.8209406,10842.77306
+Sierra Leone,SLE,252.9154757,298.2121289,224.0572387,448.2215321
+Singapore,SGP,1512.773171,1567.696315,1012.874806,46569.68843
+Sint Maarten (Dutch part),SXM,0,0,0,
+Slovak Republic,SVK,1014.601583,1082.190305,723.1595686,16509.89667
+Slovenia,SVN,1160.829551,1226.186556,810.1278932,23417.64466
+Solomon Islands,SLB,380.5634073,435.6825729,316.2510383,1294.692732
+Somalia,SOM,212.14785,253.3365088,193.1844317,284
+South Africa,ZAF,736.0334895,803.4633501,551.6426293,7175.624804
+South Sudan,SSD,411.1219459,468.0507742,337.5395011,1582.150503
+Spain,ESP,1289.027494,1351.347305,884.9640521,30736.00228
+Sri Lanka,LKA,482.7017419,543.2131961,386.4742332,2400.015575
+St. Kitts and Nevis,KNA,931.5511801,999.7502804,672.9011663,13226.95231
+St. Lucia,LCA,729.6105529,796.9559492,547.5795542,7014.196449
+St. Martin (French part),MAF,0,0,0,
+St. Vincent and the Grenadines,VCT,697.1130351,763.9668472,526.934895,6231.713226
+Sudan,SDN,396.4297508,452.5110168,327.3363534,1439.523185
+Suriname,SUR,779.2555534,847.1491,578.8428506,8321.392197
+Swaziland,SWZ,543.2422879,606.1521047,426.9748931,3261.593263
+Sweden,SWE,1579.319664,1631.581807,1050.328746,52076.25591
+Switzerland,CHE,1810.809955,1852.35646,1178.769909,74276.71842
+Syrian Arab Republic,SYR,645.3219567,711.1601083,493.7175284,5100
+Tajikistan,TJK,306.7523615,356.6884442,263.6642858,739.7321918
+Tanzania,TZA,268.7374388,315.4831622,235.8231478,524.6937952
+Thailand,THA,630.5612984,696.0549175,484.1751854,4802.662758
+Timor-Leste,TLS,327.372186,378.8818605,278.536589,875.8365693
+Togo,TGO,264.4345572,310.7936467,232.6343396,503.161824
+Tonga,TON,561.0692414,624.5863264,438.7630607,3546.77782
+Trinidad and Tobago,TTO,993.4224002,1061.214673,710.4061679,15630.05045
+Tunisia,TUN,599.4428035,664.1255927,463.942002,4211.356086
+Turkey,TUR,840.7678195,909.0226081,617.1511737,10135.74889
+Turkmenistan,TKM,609.258149,674.2093209,470.3412876,4392.719583
+Turks and Caicos Islands,TCA,0,0,0,
+Tuvalu,TUV,541.7571852,604.6144612,425.9901528,3238.496111
+Uganda,UGA,257.9339136,303.6984072,227.8013233,471.6772799
+Ukraine,UKR,524.2653458,586.480644,414.3595076,2973.996481
+United Arab Emirates,ARE,1338.39364,1399.29964,913.4657812,33885.92544
+United Kingdom,GBR,1403.929998,1462.762918,951.0510097,38363.44144
+United States,USA,1535.128339,1589.179758,1025.485052,48377.39385
+Uruguay,URY,883.5808782,951.8931086,643.5542154,11530.6375
+Uzbekistan,UZB,389.7155571,445.3957364,322.6539974,1377.08214
+Vanuatu,VUT,523.7050483,585.8990684,413.9859612,2965.75223
+"Venezuela, RB",VEN,940.4940871,1008.652162,678.3457096,13559.1268
+Vietnam,VNM,384.9268446,440.3155609,319.3067255,1333.583526
+Virgin Islands (U.S.),VIR,0,0,0,
+West Bank and Gaza,WBK,477.9151691,538.2135379,383.2392798,2338.719877
+"Yemen, Rep.",YEM,391.6104795,447.4047457,323.9767516,1394.532356
+Zambia,ZMB,406.1834985,462.8319817,334.1164149,1533.284355
+Zimbabwe,ZWE,304.0875047,353.8125042,261.7309963,723.1646486
+Arab World,,688.4632967,755.1677558,521.4148354,6032.961957
+Caribbean small states,,790.1940967,858.176897,585.6887235,8628.040548
+Central Europe and the Baltics,,910.1484031,978.4205134,659.8374901,12452.42393
+East Asia & Pacific (all income levels),,747.1326956,814.69888,558.6508158,7459.925785
+East Asia & Pacific (developing only),,581.1203983,645.2701263,451.952199,3885.285375
+Euro area,,1396.099176,1455.191248,946.5747105,37810.39975
+Europe & Central Asia (all income levels),,1160.579708,1225.941692,809.9808238,23404.56246
+Europe & Central Asia (developing only),,695.6676619,762.497068,526.0132414,6198.226006
+European Union,,1333.40006,1394.454954,910.5902978,33558.68486
+Fragile and conflict affected situations,,385.0336564,440.4289233,319.3814569,1334.544411
+Heavily indebted poor countries (HIPC),,304.396205,354.1457495,261.9550863,725.0720456
+High income,,1370.68967,1430.60143,932.0227703,36049.74575
+High income: nonOECD,,1011.16617,1078.790074,721.0937306,16365.16378
+High income: OECD,,1436.538508,1494.259726,969.6491483,40719.73453
+Latin America & Caribbean (all income levels),,800.4477823,868.5042456,592.092518,8921.709283
+Latin America & Caribbean (developing only),,789.8817706,857.8621759,585.4934613,8619.190138
+Least developed countries: UN classification,,306.9202877,356.8696113,263.786024,740.783932
+Low & middle income,,550.2755514,613.4300903,431.6328016,3372.353103
+Low income,,278.0739669,325.6401173,242.7150655,573.3383774
+Lower middle income,,428.2373211,486.1031184,349.3538185,1758.870697
+Middle East & North Africa (all income levels),,731.6080402,798.9801455,548.8437391,7064.157652
+Middle East & North Africa (developing only),,587.8962986,652.2480899,456.3930076,4003.990437
+Middle income,,578.1200708,642.1784542,449.9832508,3833.423532
+North America,,1534.116169,1588.207548,1024.914724,48294.6308
+Not classified,,0,0,0,
+OECD members,,1365.472771,1425.548772,929.029866,35694.63064
+Other small states,,603.3144103,668.104474,466.4681079,4282.33261
+Pacific island small states,,519.2084856,581.2301108,410.9858615,2900.098166
+Small states,,651.8023465,717.7838518,497.896087,5234.023815
+South Asia,,380.9688613,436.1132346,316.5352054,1298.2767
+Sub-Saharan Africa (all income levels),,404.7294533,461.2945231,333.1073044,1519.075782
+Sub-Saharan Africa (developing only),,403.459255,459.9511318,332.2253196,1506.730202
+Upper middle income,,686.6152167,753.2867342,520.2340306,5991.009883
+World,,819.1951012,887.361663,603.7678544,9474.35556

Data/sea_level_projections/slr.csv

@@ -0,0 +1,15 @@
+year,units,ssp119,ssp126,ssp245,ssp370,ssp585
+2020,meters,0.049,0.049,0.049,0.049,0.05
+2030,meters,0.092,0.092,0.093,0.094,0.098
+2040,meters,0.128,0.136,0.142,0.145,0.157
+2050,meters,0.176,0.189,0.204,0.215,0.232
+2060,meters,0.21,0.232,0.262,0.282,0.31
+2070,meters,0.26,0.29,0.33,0.366,0.404
+2080,meters,0.301,0.338,0.403,0.458,0.509
+2090,meters,0.348,0.386,0.476,0.561,0.633
+2100,meters,0.384,0.436,0.556,0.679,0.766
+2110,meters,0.428,0.497,0.628,0.758,0.856
+2120,meters,0.466,0.545,0.702,0.868,0.98
+2130,meters,0.502,0.591,0.775,0.978,1.1
+2140,meters,0.536,0.637,0.848,1.086,1.214
+2150,meters,0.569,0.681,0.919,1.19,1.322

Data/sea_level_projections/slr_ippc.csv

@@ -0,0 +1,15 @@
+year,units,ssp119,ssp126,ssp245,ssp370,ssp585
+2020,meters,0.049,0.049,0.049,0.049,0.05
+2030,meters,0.092,0.092,0.093,0.094,0.098
+2040,meters,0.128,0.136,0.142,0.145,0.157
+2050,meters,0.176,0.189,0.204,0.215,0.232
+2060,meters,0.21,0.232,0.262,0.282,0.31
+2070,meters,0.26,0.29,0.33,0.366,0.404
+2080,meters,0.301,0.338,0.403,0.458,0.509
+2090,meters,0.348,0.386,0.476,0.561,0.633
+2100,meters,0.384,0.436,0.556,0.679,0.766
+2110,meters,0.428,0.497,0.628,0.758,0.856
+2120,meters,0.466,0.545,0.702,0.868,0.98
+2130,meters,0.502,0.591,0.775,0.978,1.1
+2140,meters,0.536,0.637,0.848,1.086,1.214
+2150,meters,0.569,0.681,0.919,1.19,1.322

FloodAdapt_database/Humber/FloodAdapt_Humber_catalog.yml

@@ -0,0 +1,33 @@
+
+meta:
+  root: C:\Repositories\DT-flood\Data\
+
+jrc_vulnerability_curves:
+    path: damage_functions/flooding/JRC_damage_functions.csv
+    data_type: DataFrame
+    driver: csv
+    meta:
+      category: vulnerability
+      description: JRC depth-damage functions for flooding, processed into a handy format for HydroMT-FIAT.
+      source_url: https://publications.jrc.ec.europa.eu/repository/handle/JRC105688
+      paper_ref: Huizinga, J., De Moel, H. and Szewczyk, W., Global flood depth-damage functions - Methodology and the database with guidelines, EUR 28552 EN, Publications Office of the European Union, Luxembourg, 2017, ISBN 978-92-79-67781-6, doi:10.2760/16510, JRC105688.
+      paper_doi: https://dx.doi.org/10.2760/16510
+
+jrc_vulnerability_curves_linking:
+    path: damage_functions/flooding/JRC_damage_functions_linking.csv
+    data_type: DataFrame
+    driver: csv
+    meta:
+      category: vulnerability
+      description: Default linking table for the JRC damage functions (e.g., the residential damage function links to residential buildings).
+
+jrc_damage_values:
+    path: max_potential_damages/JRC_base_damage_values.csv
+    data_type: DataFrame
+    driver: csv
+    meta:
+      category: vulnerability
+      description: Base damage values from the JRC publicated Excel from the tab "MaxDamage-Data", processed into a handy format for HydroMT-FIAT.
+      source_url: https://publications.jrc.ec.europa.eu/repository/handle/JRC105688
+      paper_ref: Huizinga, J., De Moel, H. and Szewczyk, W., Global flood depth-damage functions - Methodology and the database with guidelines, EUR 28552 EN, Publications Office of the European Union, Luxembourg, 2017, ISBN 978-92-79-67781-6, doi:10.2760/16510, JRC105688.
+      paper_doi: https://dx.doi.org/10.2760/16510

FloodAdapt_database/Humber/HumberDelta_large.geojson

@@ -0,0 +1 @@
+{"type":"FeatureCollection","features":[{"type":"Feature","properties":{},"geometry":{"coordinates":[[[-1.056816880256747,53.822483934713716],[-1.056816880256747,53.45678163473664],[0.17432842378539704,53.45678163473664],[0.17432842378539704,53.822483934713716],[-1.056816880256747,53.822483934713716]]],"type":"Polygon"}}]}

FloodAdapt_database/Humber/static/templates/overland/hydromt.log

@@ -0,0 +1,2 @@
+2023-09-28 12:12:56,448 - hydromt_sfincs.sfincs - model_api - WARNING - Replacing geom: region
+2023-09-28 12:12:56,491 - hydromt_sfincs.sfincs - model_api - WARNING - Replacing geom: region