Spatial-Temporal Characteristics and Climatic Responses of Water Level Fluctuations of Global Major Lakes from 2002 to 2010
Abstract
:1. Introduction
2. Materials and Methods
2.1. Lake Level Data
2.2. Watershed Data
2.3. Meteorological Data
3. Results
3.1. Temporal and Spatial Characteristics of Major Global Lakes
3.1.1. Time Characteristics of the Lake Water Level Changes
3.1.2. Spatial Characteristics of Lake Water Level Change
3.2. Global Climate Fluctuations
3.2.1. Temperature
3.2.2. Precipitation
3.3. Responses of the Lake Water Level Variation to Climate Fluctuation
3.3.1. Response of the Lake Water Level Variation to Climate Fluctuation
3.3.2. Response of Natural Lakes to Climate
4. Discussion
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
Appendix A
Sequence | Lake | Change Rate (m/a) | Sequence | Lake | Change Rate (m/a) |
---|---|---|---|---|---|
1 | Angostura * | 1.867 | 103 | Khanka * | 0.036 |
2 | Oahe | 1.03 | 104 | Nicaragua * | 0.036 |
3 | Tres Marias | 1.022 | 105 | Baikal * | 0.031 |
4 | Guri | 0.982 | 106 | Issykkul * | 0.03 |
5 | Tucurui | 0.802 | 107 | Great Bear * | 0.029 |
6 | Dogen-co * | 0.758 | 108 | Montreal * | 0.029 |
7 | Volta * | 0.68 | 109 | Vanerm * | 0.027 |
8 | Zeyskoye | 0.667 | 110 | Har Us * | 0.027 |
9 | Ziling * | 0.606 | 111 | Kainji | 0.026 |
10 | Sakakawea * | 0.604 | 112 | Tchad * | 0.019 |
11 | Dorsoidong-co * | 0.583 | 113 | Izabal * | 0.015 |
12 | Xuelian-hu * | 0.569 | 114 | Aru-co * | 0.015 |
13 | Sobradino | 0.554 | 115 | Hovsgol * | 0.013 |
14 | Dagze-co * | 0.552 | 116 | Huron * | 0.012 |
15 | Posadas | 0.505 | 117 | Kapchagayskoye | 0.01 |
16 | Cahora Bassa * | 0.482 | 118 | Dubawnt | 0.009 |
17 | Memar-co * | 0.474 | 119 | Erie * | 0.009 |
18 | Yanghu-co * | 0.467 | 120 | Balkhash * | 0.007 |
19 | Chapala * | 0.453 | 121 | Maracaibo | 0.007 |
20 | Krasnoyarskoye | 0.435 | 122 | Tana * | 0.006 |
21 | Hoh-xil-hu * | 0.434 | 123 | Kivu * | 0.004 |
22 | Kyeb * | 0.414 | 124 | Lesser Slave | 0.003 |
23 | Lumojangdong-co * | 0.364 | 125 | Ontario * | −0.001 |
24 | Xiangyang-hu * | 0.364 | 126 | Michigan * | −0.002 |
25 | Sevana * | 0.352 | 127 | Amadjuak | −0.004 |
26 | Caniapiscau | 0.345 | 128 | Athabasca * | −0.0077 |
27 | Xijir-hulan-hu * | 0.345 | 129 | Rinihue * | −0.008 |
28 | Saksak | 0.343 | 130 | Baker | −0.011 |
29 | Grande Trois | 0.343 | 131 | Logoa dos Patos * | −0.011 |
30 | Lisioidain-co * | 0.337 | 132 | Saint-Jean * | −0.014 |
31 | Ngoring-co * | 0.326 | 133 | Tanganika * | −0.015 |
32 | Aksayqin * | 0.325 | 134 | Logoa Gen Carrera * | −0.015 |
33 | Migruggwangkum * | 0.324 | 135 | Dabsan-hu * | −0.017 |
34 | Serbug-co * | 0.318 | 136 | Votkinskoye | −0.018 |
35 | Ulan-ul * | 0.314 | 137 | Superior * | −0.018 |
36 | Ayakkum * | 0.312 | 138 | Caspian Sea * | −0.019 |
37 | Bul-co * | 0.312 | 139 | Kyyvske | −0.021 |
38 | Gyeze-caka * | 0.307 | 140 | Tai * | −0.023 |
39 | Luotuo-hu * | 0.306 | 141 | Uvs * | −0.024 |
40 | Taro-co * | 0.297 | 142 | Nettiling | −0.024 |
41 | Sarykamish * | 0.291 | 143 | Chardarya | −0.026 |
42 | Ngangze * | 0.283 | 144 | Orba-co * | −0.026 |
43 | Zige-tangco * | 0.282 | 145 | Kremenchutska | −0.028 |
44 | Co-nyi * | 0.28 | 146 | Argentino * | −0.028 |
45 | Dawa-co * | 0.28 | 147 | Malawi * | −0.031 |
46 | Heishi-beihu * | 0.276 | 148 | Great Slave * | −0.032 |
47 | Aral(Nord) * | 0.243 | 149 | Todos los Santos * | −0.033 |
48 | Dogaicoring * | 0.23 | 150 | Hongze * | −0.034 |
49 | Kushuihuan * | 0.229 | 151 | Kara Bogaz Gol * | −0.037 |
50 | Tangra-yumco * | 0.216 | 152 | Edouard * | −0.038 |
51 | Iguazu | 0.215 | 153 | Uru-co * | −0.038 |
52 | Deschambault * | 0.21 | 154 | Great Salt | −0.04 |
53 | Bratskoye | 0.192 | 155 | Shala * | −0.043 |
54 | Namco * | 0.182 | 156 | Aylmer | −0.046 |
55 | Lagor-co * | 0.17 | 157 | Tchany * | −0.05 |
56 | Managua * | 0.166 | 158 | Har * | −0.055 |
57 | Yaggain-canco * | 0.155 | 159 | Llanquihue * | −0.056 |
58 | Aydarkul | 0.154 | 160 | Ulungur * | −0.057 |
59 | Winnipegosis * | 0.154 | 161 | Flathead | −0.062 |
60 | Caribou * | 0.148 | 162 | Beysehir * | −0.064 |
61 | Har-hu * | 0.147 | 163 | Victoria * | −0.066 |
62 | Chem-co * | 0.146 | 164 | Puma-yumco * | −0.072 |
63 | San Martin * | 0.145 | 165 | Kuybyshevskoye | −0.084 |
64 | Illmen * | 0.136 | 166 | Mapam-yamco * | −0.085 |
65 | Gozha-co * | 0.128 | 167 | Nahuelhuapi * | −0.121 |
66 | Balbina | 0.121 | 168 | Tsimlyanskoye | −0.124 |
67 | Tshchikskoye | 0.118 | 169 | Nasser | −0.128 |
68 | Zhari-namco * | 0.114 | 170 | Churumuco | −0.128 |
69 | Aong-co * | 0.109 | 171 | Okeechobee * | −0.128 |
70 | Kariba * | 0.106 | 172 | Aberdeen | −0.129 |
71 | pangong-co * | 0.101 | 173 | Khantaiskoye * | −0.145 |
72 | Nezahualcoyoti * | 0.1 | 174 | Asad | −0.146 |
73 | Ladoga * | 0.094 | 175 | Poopo * | −0.15 |
74 | Winnipeg * | 0.094 | 176 | Ranco * | −0.159 |
75 | Furnas | 0.089 | 177 | Pelkhu-co * | −0.168 |
76 | Cedar | 0.085 | 178 | Titicaca * | −0.189 |
77 | Opinaca | 0.083 | 179 | Albert * | −0.19 |
78 | Rybinskoye | 0.082 | 180 | Rukwa | −0.203 |
79 | Qinghai * | 0.078 | 181 | Kyoga * | −0.216 |
80 | Dore * | 0.073 | 182 | Viedma * | −0.22 |
81 | Manitoba * | 0.073 | 183 | Old Wives * | −0.232 |
82 | Vatern * | 0.072 | 184 | Hyargas * | −0.29 |
83 | Bangweulu * | 0.067 | 185 | Bosten * | −0.3 |
84 | Itaparica | 0.065 | 186 | Saysan * | −0.32 |
85 | Mweru * | 0.0625 | 187 | Williston | −0.333 |
86 | Nueltin | 0.062 | 188 | Hulun * | −0.338 |
87 | Des Bois | 0.061 | 189 | Cardiel * | −0.344 |
88 | Kasba | 0.06 | 190 | Chiquita * | −0.347 |
89 | Peipus * | 0.058 | 191 | Urmia * | −0.394 |
90 | Smallwood * | 0.058 | 192 | Hinojo * | −0.418 |
91 | Onega * | 0.056 | 193 | Razazah | −0.422 |
92 | Dongting * | 0.055 | 194 | Tharthar | −0.464 |
93 | Turkana * | 0.055 | 195 | Saravor * | −0.516 |
94 | Van * | 0.053 | 196 | Roseires * | −0.533 |
95 | Rinqiyubu-co * | 0.052 | 197 | Aral(Sud) * | −0.569 |
96 | Poyang * | 0.047 | 198 | Yamzho-yumco * | −0.599 |
97 | Powell | 0.0456 | 199 | Strobel * | −0.84 |
98 | Champlain * | 0.044 | 200 | Buyo | −0.954 |
99 | Nganga-ringko * | 0.042 | 201 | Qadisiyah | −1.608 |
100 | Sasykkol * | 0.04 | 202 | Mossoul | −1.8 |
101 | Yellowstone * | 0.039 | 203 | Mead | −2.356 |
102 | Ilha Solteira | 0.038 | 204 | Toktogul | −5.844 |
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The Change Rate of Lake Level | Accumulated Precipitation | Accumulated Temperature | ||
---|---|---|---|---|
the change rate of lake level | Pearson Correlation | 1 | 0.258 ** | −0.238 * |
Sig. (2-tailed) | 0.009 | 0.016 | ||
N | 103 | 103 | 103 | |
accumulated precipitation | Pearson Correlation | 0.258 ** | 1 | −0.201 * |
Sig. (2-tailed) | 0.009 | 0.042 | ||
N | 103 | 103 | 103 | |
accumulated temperature | Pearson Correlation | −0.238 * | −0.201 * | 1 |
Sig. (2-tailed) | 0.016 | 0.042 | ||
N | 103 | 103 | 103 |
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Tan, C.; Ma, M.; Kuang, H. Spatial-Temporal Characteristics and Climatic Responses of Water Level Fluctuations of Global Major Lakes from 2002 to 2010. Remote Sens. 2017, 9, 150. https://doi.org/10.3390/rs9020150
Tan C, Ma M, Kuang H. Spatial-Temporal Characteristics and Climatic Responses of Water Level Fluctuations of Global Major Lakes from 2002 to 2010. Remote Sensing. 2017; 9(2):150. https://doi.org/10.3390/rs9020150
Chicago/Turabian StyleTan, Chao, Mingguo Ma, and Honghai Kuang. 2017. "Spatial-Temporal Characteristics and Climatic Responses of Water Level Fluctuations of Global Major Lakes from 2002 to 2010" Remote Sensing 9, no. 2: 150. https://doi.org/10.3390/rs9020150
APA StyleTan, C., Ma, M., & Kuang, H. (2017). Spatial-Temporal Characteristics and Climatic Responses of Water Level Fluctuations of Global Major Lakes from 2002 to 2010. Remote Sensing, 9(2), 150. https://doi.org/10.3390/rs9020150