CASE STUDY

Using Better Technology to Predict Drought and Increase Productivity Yields

Due to the water shortage caused by drought, companies and governments would need to search for alternative technologies, or even invent new technologies to substitute existing products and services with high water usage and lower water consumption. Worse still, there is arapid depletion of the groundwater sourceover the past years. The issue is especially severe in the agriculture industry since most crops rely on the use of groundwater. Therefore, agriculture is one of the two most vulnerable sectors to climate change risk.

Among all the weather hazards, droughts cause the highest economical loss.

“An ongoing drought in China Yunnan affected more than 273,000 hectares (675,000 acres) of cropland, causing $138 million in damages.”

To combat the issue, the most recent irrigation technology uses Artificial Intelligence and Cloud Computing to improve water use efficiency. By collecting data using soil and plant water status sensors, drones, and satellites, farmers can manage and optimize the amount of water used for each batch of crops, thus reducing the overall manual labour and water expenses.

A COUPLE OF FACTS ON CHINA’S WATER
  1. Over-extraction of groundwater and falling water tables are significant problems in China.
  2. Average annual groundwater depletion of more than 10 billion cubic meters.
  3. 60,000 square km of the ground surface has sunk with more than 50 cities suffering from severe land subsidence.
  4. Asia’s ten largest rivers, including the Yangtze, Yellow, Mekong and Ganges, are fed by seasonal melting.
  5. The third pole is the source of water for the main rivers in China.

1 Source: AON article June 10th, 2019 on Insurance Journal.

INTENSEL’S DROUGHT MODELS

Existing drought models are very simplistic and thus lead to wrong predictions. They only rely on rainfall data if available. Yet, rainfall data is not collected in most regions in Asia. It is, therefore, difficult to make any drought analysis on a meaningful grid case.

Intensel Limited is the Asia startup for Asian physical climate risk assessment and predictions, which models drought as a combination of several factors including snowmelt and other climate variables. Intensel’s dynamic climate models and AI technology can generate missing historical data, for example, rainfall data. The AI and NWP proprietary models can generate missing historical data at a granular level for 3 months, 12 months and 5 years interval. The main take away is that only by looking at historical past and recent past trends and only by incorporating climate change factors, we are able to generate reliable predictions and trends. Our recent analysis reveals that we are heading for a 5 to 7-year dry period with potentially large variations.

Third Pole Snow Cover is Declining at Alarming Rate

Source: Intensel Limited

Seasonal Rainfall Index

Source: Intensel Limited

Soil Moisture Content Decrease Has Clear Impact on Agriculture

Source:China Statistical Yearbook published by the National Bureau of Statistics of China in 2012

Source:China Statistical Yearbook published by the National Bureau of Statistics of China in 2012

Source: Intensel limited

The plot shows that grain production has increased the yield efficiency of half of what it should be, particularly for maize . The main culprit is climate and natural hazard. If we map grain to soil moisture as well as rainfall patterns, the answer to low productivity becomes apparent. To promote further agriculture productivity, there is a pressing need for better prediction of drought and better water management, along with other technological and other grain quality improvements.

Water availability affects various sectors of the economy, especially the water-intensive ones such as manufacturing, semi-conductors, and materials, etc. They share the available water with agriculture sectors while leaving enough for civilian use. Besides, these sectors are also the most polluting ones. As per one an incoming CWR publication on Water Risk, 40% of the water waste find its way on Yangtze Rivers and lakes. Cities around the Yangtze River contribute to 40%+ of national GDP.