Comparative Study of M5 Model Tree and Artificial Neural Network in Estimating Reference Evapotranspiration Using MODIS Products

<table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr class="thead"><td align="left">Station</td><td align="center">Model</td><td align="center"><span style="width: 13.7602ptpx;"><svg height="12.2911pt" id="M238" style="vertical-align:-0.2129993pt" version="1.1" viewbox="-0.0498162 -12.0781 13.7602 12.2911" width="13.7602pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.0135,0,0,-0.0135,0,0)"><path d="M610 18C585 26 567 34 540 68C517 97 499 128 476 171C452 215 425 276 413 304C496 332 570 394 570 494C570 555 545 595 509 619S419 650 364 650H139L133 622C216 615 219 612 203 527L129 132C112 40 105 36 23 28L17 0H279L285 28C199 34 194 40 211 132L239 284H284C320 284 334 275 351 236C374 182 394 140 420 93C459 23 495 -1 592 -8H600L610 18ZM480 485C480 424 449 372 403 342C374 323 338 316 293 316H245L291 562C296 589 301 601 311 608S337 618 358 618C432 618 480 575 480 485Z" id="g113-83"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="627" vert-adv-y="627"></glyph.data></g><g transform="matrix(.0095,0,0,-0.0095,8.495,-5.984)"><path d="M414 144C384 79 371 75 317 75H135L276 221C367 316 408 376 408 465C408 570 327 635 237 635C179 635 131 609 100 575L42 494L67 471C94 510 138 565 205 565C277 565 321 517 321 435C321 348 258 270 195 195C146 137 88 81 33 26V0H411C423 44 433 88 446 135L414 144Z" id="g50-51"></path><glyph.data ascent="3443" descent="-2856" horiz-adv-x="487" vert-adv-y="487"></glyph.data></g></svg></span></td><td align="center">RMSE (mm/d)</td><td align="center">MAE (mm/d)</td></tr><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr><td align="left" rowspan="2">Khazaei</td><td align="center">ANN</td><td align="center">0.79</td><td align="center">1.54</td><td align="center">1.14</td></tr><tr><td align="center">M5</td><td align="center">0.80</td><td align="center">1.49</td><td align="center">1.12</td></tr><tr><td align="center" colspan="5"><hr/></td></tr><tr><td align="left" rowspan="2">Shoeybie</td><td align="center">ANN</td><td align="center">0.86</td><td align="center">1.15</td><td align="center">0.90</td></tr><tr><td align="center">M5</td><td align="center">0.85</td><td align="center">1.17</td><td align="center">0.90</td></tr><tr class="table-tr"><td colspan="5"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Error statistics in estimating <svg height="12.5481pt" id="M237" style="vertical-align:-3.42776pt" version="1.1" viewbox="-0.0498162 -9.12034 23.5881 12.5481" width="23.5881pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.0135,0,0,-0.0135,0,0)"><path d="M517 162C503 123 484 88 467 68C445 42 417 34 341 34C291 34 256 34 237 47C219 59 213 81 213 128V317H308C395 317 402 311 415 240H444V431H415C403 364 398 356 307 356H213V584C213 613 215 616 246 616H322C394 616 421 609 435 587C448 566 458 544 467 502L496 506C493 557 488 625 488 650H42V622C120 616 128 612 128 523V125C128 43 120 35 29 28V0H511C520 31 540 125 546 158L517 162Z" id="g190-70"></path><glyph.data ascent="989" descent="-360" horiz-adv-x="568" vert-adv-y="568"></glyph.data></g><g transform="matrix(.0135,0,0,-0.0135,7.641,0)"><path d="M592 498C586 556 582 629 581 675H560C545 656 537 650 510 650H115C87 650 74 652 60 675H40C38 620 33 555 28 495H57C69 539 77 568 89 585C102 607 122 616 205 616H267V123C267 44 259 34 168 28V0H454V28C360 34 352 44 352 123V616H422C498 616 514 608 531 584C542 568 552 543 562 495L592 498Z" id="g190-85"></path><glyph.data ascent="989" descent="-360" horiz-adv-x="617" vert-adv-y="617"></glyph.data></g><g transform="matrix(.0095,0,0,-0.0095,16.06,3.264)"><path d="M750 359C750 550 603 667 427 667C199 667 24 499 24 287C24 100 166 -17 344 -17C573 -17 750 136 750 359ZM645 356C645 196 538 24 350 24C205 24 127 136 127 285C127 471 247 626 422 626C571 626 645 521 645 356Z" id="g50-80"></path><glyph.data ascent="3443" descent="-2856" horiz-adv-x="774" vert-adv-y="774"></glyph.data></g></svg> by ANN and M5 model tree using testing data.

Journal of Climatology

tab2

Table 2

Table 2: Comparative Study of M5 Model Tree and Artificial Neural Network in Estimating Reference Evapotranspiration Using MODIS Products 