top of page

By:

Rajendra Joshi

3 December 2024 at 9:20:26 am

A Dry Monsoon, A Bigger Water Challenge

A deficient monsoon is less a warning of immediate food scarcity than a test of how well India can manage a more volatile and uneven water regime. Kolhapur: India has ended the 2026 southwest monsoon season with rainfall 12.6 percent below the long-period average, making it the driest monsoon since 2015 and the fourth-driest since 2001. With El Niño influence strengthening, heatwaves becoming more intense and pressure on water resources mounting, the challenge is no longer simply how much...

A Dry Monsoon, A Bigger Water Challenge

A deficient monsoon is less a warning of immediate food scarcity than a test of how well India can manage a more volatile and uneven water regime. Kolhapur: India has ended the 2026 southwest monsoon season with rainfall 12.6 percent below the long-period average, making it the driest monsoon since 2015 and the fourth-driest since 2001. With El Niño influence strengthening, heatwaves becoming more intense and pressure on water resources mounting, the challenge is no longer simply how much rain India receives. It is how intelligently the country manages scarcity, volatility and the unequal distribution of water. The headline numbers are sobering. Between June and September, India received 759.4 mm of rainfall against the normal 868.6 mm. That is a substantial shortfall. Yet a deficient monsoon does not automatically mean drought, crop failure or food shortage. India today possesses several buffers that were considerably weaker during earlier periods of scarcity. Foodgrain stocks are substantial, the public distribution system provides a nationwide safety net, weather forecasting has improved and foodgrains can be moved relatively quickly from surplus to deficit regions. These mechanisms give the country a far greater capacity to absorb a poor rainfall season than it had decades ago. But the real test of those safeguards begins after the rains have stopped. The national average also conceals a more complicated picture. While parts of the country suffered rainfall deficiency, other regions experienced intense spells that damaged standing crops, triggered flooding and washed away soil. The emerging climate challenge, therefore, cannot be reduced to the simple question of whether the monsoon was “normal”. The more consequential questions concern when, where and how intensely the rain fell. Paradoxical Case Western Maharashtra illustrates the paradox particularly well. The region sits close to the Western Ghats, yet the rain-shadow areas to their east can move rapidly from a deficient monsoon to a serious water crisis. This year, the contrast has been striking: while parts of the Ghats received exceptionally heavy rainfall, Solapur recorded a deficit of more than 50 percent during much of the monsoon season. Sangli, too, experienced prolonged dry spells, while parts of Satara, Pune and Kolhapur have faced growing water stress. Western Maharashtra has a highly developed agricultural economy, with sugarcane, horticulture and other water-intensive crops competing with drinking-water and industrial requirements. When the rains fail or arrive in short, intense bursts, the consequences are magnified because groundwater, reservoirs and farm irrigation systems are placed under simultaneous pressure. The state government’s decision to declare drought in 265 of Maharashtra's 358 talukas, including substantial pockets of western Maharashtra, underlines the scale of the problem. For districts such as Solapur and Sangli, the immediate concern is the rabi season. A prolonged dry spell after the monsoon can rapidly drain the moisture left in the soil, making sowing more difficult and increasing dependence on irrigation. This is where Maharashtra’s experience offers a broader lesson: a monsoon can be deficient nationally, normal in one district and disastrous in another. Water policy therefore has to be designed around local hydrology and agricultural demand, not simply the national rainfall average. One region can face drought-like conditions while another is coping with excessive rainfall. The traditional classification of a monsoon as simply “good” or “bad” is becoming an increasingly inadequate measure of agricultural risk. The El Niño factor adds another layer of uncertainty. Warming of surface waters in the Pacific can alter atmospheric circulation and influence the Indian monsoon. But El Niño does not automatically produce drought in India. Conditions in the Indian Ocean, regional weather systems and the monsoon's own internal dynamics also matter. The lesson is that India's climate risk cannot be understood through one indicator alone. The immediate concern now is the rabi season. For the 2026-27 crop year, the Centre has set a foodgrain production target of 373.93 million tonnes, compared with estimated production of 376.56 million tonnes in the previous year. The rabi target has been fixed at 177.72 million tonnes. If reservoirs and groundwater remain under pressure, farmers may have to alter crop choices, reduce acreage or increase their reliance on costly irrigation. This is why water management must move beyond crisis response. It cannot begin only when reservoirs are depleted. Crop planning cannot wait until the rabi season is already underway. The 2026 monsoon should therefore be treated as a warning about India’s preparedness for a more volatile climate.

AI in Sperm Sorting: An Unbiased Decision for A Better Outcome

Writer: Dr. Ramnath Babu T J
Dr. Ramnath Babu T J
Nov 7, 2024
3 min read

Artificial Intelligence or AI is revolutionising fertility treatments of the future. The inclusion of AI enhances the accuracy, efficiency, and objectivity of sperm selection, hence potentially improving fertility outcomes by leaps and bounds. Traditionally, sperm sorting through manual methods is subjective to judgments. Processes like centrifugation and swim-up methods are used to separate sperm based on motility and morphology. Although they are effective, they have their limitations, leading to human errors that affect the success rates of fertility treatment. For instance, studies have shown that traditional sperm sorting techniques can have variability in success rates, with reported live birth rates ranging between 15 per cent to 25 per cent per cycle depending on the method and quality of sperm. Hence the introduction of AI helps in maintaining consistency in evaluations of sperm, using the same data set for every sample which leads to better judgments.


Automation and Standardisation- Automation of sperm selection and also introduction of AI in the process have improved the results in ART. AI-assisted sperm selection improves the accuracy in choosing high-quality sperm for fertilisation purposes, and also, pregnancy and live birth rates might be improved. Technologies like Intracytoplasmic Morphologically Selected Sperm Injection along with AI ensure the chances of pregnancies increase by about 10-20 per cent compared to the standard procedures. AI and Automation will decrease time taken to analyze sperm and increase opportunities to select better sperm with DNA integrity for better development and higher success rates in embryo selection. These processes ensure that the sperm selection process follows consistent criteria, reducing variability in outcomes caused by human error.


Analysing Complex Data for Better Outcomes- AI plays a crucial in improving IVF outcomes by analysing complex data and providing tailored recommendations. AI-driven tools and models such as those on SpOvum.ai point towards an opportunity to optimise ovarian stimulation decisions by assessing patient characteristics and follicle growth patterns. A study revealed that the use of AI in IVF improved egg yield and reduced medication costs. AI enables fertility specialists to make data-driven choices, improving overall IVF success rates and streamlining treatment processes.


Reducing Human Error- AI models can continuously learn and refine their performance by being trained on newer data. This adaptability ensures the technology remains unbiased and up-to-date with the latest scientific insights into sperm quality and fertility success rates. Studies have shown that AI-driven sperm sorting can decrease human-related errors by up to 25 per cent, improving sperm selection quality in terms of morphology and motility.


Reduction of Sperm Damage- The new AI-driven sperm sorting techniques also include microfluidic systems that are known to exhibit several advantages over the most commonly used conventional method, which is centrifugation. Traditional centrifugation methods, such as density gradient centrifugation, also cause severe oxidative stress and DNA fragmentation of the sperm because of the very high mechanical forces involved. The AI-infused microfluidic sorting minimises this damage significantly by involving gentler processes that mimic the natural pathway of sperm selection. The studies show that the process of microfluidic sorting decreases DNA fragmentation in sperm, which gives improved opportunities for success for IVF. For example, DNA fragmentation is 20 percent lower in sperm sorted using microfluidic processes than in traditional processing methods.


AI is bound to play an increasingly definitive role in fertility treatments, which will improve the outcomes for couples experiencing infertility.


(The author is a Co-Founder & CEO at SpOvum® Technologies. Views personal.)

Comments

bottom of page