The China Mail - Landslide-prone Nepal tests AI-powered warning system

USD -
AED 3.673042
AFN 63.503991
ALL 82.403989
AMD 368.150403
ANG 1.790403
AOA 918.000367
ARS 1465.449815
AUD 1.427684
AWG 1.8025
AZN 1.70397
BAM 1.705709
BBD 2.013483
BDT 122.708482
BGN 1.69088
BHD 0.37702
BIF 2985
BMD 1
BND 1.290663
BOB 6.90816
BRL 5.152304
BSD 0.999721
BTN 94.239742
BWP 13.585663
BYN 2.777729
BYR 19600
BZD 2.010527
CAD 1.417515
CDF 2280.000362
CHF 0.807865
CLF 0.02293
CLP 902.460396
CNY 6.769604
CNH 6.78349
COP 3452.68
CRC 453.506829
CUC 1
CUP 26.5
CVE 96.403894
CZK 21.091104
DJF 177.720393
DKK 6.516504
DOP 58.403884
DZD 133.34504
EGP 49.986489
ERN 15
ETB 158.37504
EUR 0.872353
FJD 2.235504
FKP 0.755711
GBP 0.757022
GEL 2.650391
GGP 0.755711
GHS 11.22504
GIP 0.755711
GMD 73.503851
GNF 8775.000355
GTQ 7.625892
GYD 209.119888
HKD 7.83688
HNL 26.68504
HRK 6.573199
HTG 130.583803
HUF 306.820388
IDR 17826.3
ILS 2.96854
IMP 0.755711
INR 94.330504
IQD 1310
IRR 1375000.000352
ISK 125.530386
JEP 0.755711
JMD 157.959917
JOD 0.70904
JPY 161.30504
KES 129.403801
KGS 87.450384
KHR 4010.00035
KMF 429.503794
KPW 900.00035
KRW 1527.650383
KWD 0.30793
KYD 0.833035
KZT 487.855928
LAK 22055.000349
LBP 89550.000349
LKR 333.641485
LRD 182.150382
LSL 16.405039
LTL 2.95274
LVL 0.60489
LYD 6.375039
MAD 9.225039
MDL 17.654036
MGA 4200.000347
MKD 53.732839
MMK 2099.479867
MNT 3580.422334
MOP 8.070939
MRU 40.060379
MUR 47.850378
MVR 15.450378
MWK 1737.000345
MXN 17.34565
MYR 4.137904
MZN 63.910377
NAD 16.403727
NGN 1360.440377
NIO 36.610377
NOK 9.70261
NPR 150.787532
NZD 1.743816
OMR 0.384983
PAB 0.999725
PEN 3.384039
PGK 4.38775
PHP 60.716504
PKR 278.325038
PLN 3.71375
PYG 6138.96617
QAR 3.640504
RON 4.568104
RSD 102.170373
RUB 73.103247
RWF 1464
SAR 3.74824
SBD 8.061424
SCR 13.683262
SDG 600.503676
SEK 9.589325
SGD 1.292404
SHP 0.746601
SLE 24.750371
SLL 20969.503664
SOS 571.503662
SRD 37.402504
STD 20697.981008
STN 21.4
SVC 8.747449
SYP 110.532098
SZL 16.403649
THB 32.890369
TJS 9.272075
TMT 3.5
TND 2.91175
TOP 2.40776
TRY 46.45903
TTD 6.779085
TWD 31.715038
TZS 2630.985038
UAH 44.909735
UGX 3638.520172
UYU 39.96965
UZS 12005.000334
VES 606.63266
VND 26310
VUV 118.132932
WST 2.751795
XAF 572.078806
XAG 0.015428
XAU 0.000241
XCD 2.70255
XCG 1.801643
XDR 0.703697
XOF 565.000332
XPF 104.250363
YER 238.603589
ZAR 16.454065
ZMK 9001.205044
ZMW 17.919703
ZWL 321.999592
  • CMSC

    0.0500

    22.37

    +0.22%

  • BCC

    3.8500

    74.66

    +5.16%

  • RBGPF

    -0.5300

    60.61

    -0.87%

  • RYCEF

    -0.0300

    18.4

    -0.16%

  • NGG

    -1.2400

    79.44

    -1.56%

  • BTI

    -0.5800

    58.91

    -0.98%

  • GSK

    -1.4800

    50.67

    -2.92%

  • RIO

    -2.5900

    100.08

    -2.59%

  • BCE

    0.0000

    23.28

    0%

  • CMSD

    0.0000

    22.29

    0%

  • JRI

    0.0500

    12.67

    +0.39%

  • BP

    -1.0400

    39.1

    -2.66%

  • VOD

    -0.2300

    14.3

    -1.61%

  • RELX

    -0.8300

    31.18

    -2.66%

  • AZN

    -2.9600

    174.93

    -1.69%

Landslide-prone Nepal tests AI-powered warning system
Landslide-prone Nepal tests AI-powered warning system / Photo: © AFP

Landslide-prone Nepal tests AI-powered warning system

Every morning, Nepali primary school teacher Bina Tamang steps outside her home and checks the rain gauge, part of an early warning system in one of the world's most landslide-prone regions.

Text size:

Tamang contributes to an AI-powered early warning system that uses rainfall and ground movement data, local observations and satellite imagery to predict landslides up to weeks in advance, according to its developers at the University of Melbourne.

From her home in Kimtang village in the hills of northwest Nepal, 29-year-old Tamang sends photos of the water level to experts in the capital Kathmandu, a five-hour drive to the south.

"Our village is located in difficult terrain, and landslides are frequent here, like many villages in Nepal," Tamang told AFP.

Every year during the monsoon season, floods and landslides wreak havoc across South Asia, killing hundreds of people.

Nepal is especially vulnerable due to unstable geology, shifting rainfall patterns and poorly planned development.

As a mountainous country, it is already "highly prone" to landslides, said Rajendra Sharma, an early warning expert at the National Disaster Risk Reduction and Management Authority.

"And climate change is fuelling them further. Shifting rainfall patterns, rain instead of snowfall in high altitudes and even increase in wildfires are triggering soil erosion," Sharma told AFP.

- Saving lives -

Landslides killed more than 300 people last year and were responsible for 70 percent of monsoon-linked deaths, government data shows.

Tamang knows the risks first hand.

When she was just five years old, her family and dozens of others relocated after soil erosion threatened their village homes.

They moved about a kilometre (0.6 miles) uphill, but a strong 2015 earthquake left the area even more unstable, prompting many families to flee again.

"The villagers here have lived in fear," Tamang said.

"But I am hopeful that this new early warning system will help save lives."

The landslide forecasting platform was developed by Australian professor Antoinette Tordesillas with partners in Nepal, Britain and Italy.

Its name, SAFE-RISCCS, is an acronym of a complex title -- Spatiotemporal Analytics, Forecasting and Estimation of Risks from Climate Change Systems.

"This is a low-cost but high-impact solution, one that's both scientifically informed and locally owned," Tordesillas told AFP.

Professor Basanta Adhikari from Nepal's Tribhuvan University, who is involved in the project, said that similar systems were already in use in several other countries, including the United States and China.

"We are monitoring landslide-prone areas using the same principles that have been applied abroad, adapted to Nepal's terrain," he told AFP.

"If the system performs well during this monsoon season, we can be confident that it will work in Nepal as well, despite the country's complex Himalayan terrain."

In Nepal, it is being piloted in two high-risk areas: Kimtang in Nuwakot district and Jyotinagar in Dhading district.

- Early warnings -

Tamang's data is handled by technical advisers like Sanjaya Devkota, who compares it against a threshold that might indicate a landslide.

"We are still in a preliminary stage, but once we have a long dataset, the AI component will automatically generate a graphical view and alert us based on the rainfall forecast," Devkota said.

"Then we report to the community, that's our plan."

The experts have been collecting data for two months, but will need a data set spanning a year or two for proper forecasting, he added.

Eventually, the system will deliver a continuously updated landslide risk map, helping decision makers and residents take preventive actions and make evacuation plans.

The system "need not be difficult or resource-intensive, especially when it builds on the community's deep local knowledge and active involvement", Tordesillas said.

Asia suffered more climate and weather-related hazards than any other region in 2023, according to UN data, with floods and storms the most deadly and costly.

And while two-thirds of the region have early warning systems for disasters in place, many other vulnerable countries have little coverage.

In the last decade, Nepal has made progress on flood preparedness, installing 200 sirens along major rivers and actively involving communities in warning efforts.

The system has helped reduce flooding deaths, said Binod Parajuli, a flood expert with the government's hydrology department.

"However, we have not been able to do the same for landslides because predicting them is much more complicated," he said.

"Such technologies are absolutely necessary if Nepal wants to reduce its monsoon toll."

N.Wan--ThChM