The urgency of the problem is considerable. According to the UN Convention to Combat Desertification, roughly 28.6 percent of Uzbekistan’s territory is affected by land degradation, driven by erosion, salinization, and inefficient water use. In the Jizzakh Region, where irrigated cropland covers about 515,000 hectares and supports cotton, winter wheat, and horticultural production, agricultural viability depends on irrigation in a climate that is becoming steadily more arid. Previous studies have typically examined pieces of this puzzle in isolation, mapping salt-affected soils or modeling water balances, but few have integrated climatic, soil, and hydrogeological information into one landscape-scale assessment that decision-makers can actually use.

The new framework draws on data routinely collected by existing monitoring programs, which is central to its practicality. Meteorological records came from two long-running stations, Jizzakh and Dustlik, representing the piedmont-influenced central zone and the lowland irrigated plains respectively, with reference periods stretching back 88 and 52 years. District-level data on groundwater depth and mineralization, soil salinity, irrigation volumes, and drainage performance were supplied by Uzbek hydrometeorological and water-resource agencies. The researchers calculated a suite of established agroclimatic indices, including net radiation, vapor pressure deficit, the Budyko radiation aridity index, the natural moisture coefficient, the moisture index, Selyaninov’s hydrothermal coefficient, biological-climatic productivity, and the agroclimatic potential index, alongside soil and groundwater indicators derived from monitoring wells.

The climatic picture that emerges is stark. During the growing season, long-term average vapor pressure deficit reached 1.60 kilopascals at the Jizzakh station and 1.48 kilopascals at Dustlik, values that reflect severe atmospheric water stress for crops. The natural moisture coefficient, which expresses the balance between precipitation and potential evaporation, averaged just 0.12 during the vegetation period at Jizzakh and 0.10 at Dustlik, far below the threshold of 1.0 that would indicate adequate moisture. Annual values between 2021 and 2024 remained consistently below their long-term averages, pointing to a clear trend toward aridification. The hydrothermal coefficient, which fluctuated between roughly 0.4 and 1.1 over the study period, confirmed the region’s semi-arid character, with the wet year of 2022 providing only temporary relief.

Radiation balance measurements added a spatial dimension to this analysis. Net radiation on irrigated lands in districts represented by the Dustlik station ranged from 306 to 311 kilojoules per square centimeter per month, while districts associated with the Jizzakh station showed values between 271 and 359, following the region’s plain-to-mountain gradient. Districts such as Arnasay, Dustlik, and Paxtakor recorded the highest radiation fluxes and therefore the greatest evaporative demand and irrigation requirements, whereas the higher-elevation districts of Zomin, Zarbdor, and Sh. Rashidov showed lower energy inputs. Notably, 2024 saw a marked increase in radiation balance in several districts, reaching up to 359 kilojoules per square centimeter per month, a signal of elevated evaporative potential that the authors link to regional warming trends.

On the soil and groundwater side, the findings were more mixed. Groundwater mineralization during the vegetation period predominantly fell within the moderately mineralized 1 to 3 grams per liter range, accounting for nearly 90 percent of the monitored area in Dustlik and Sh. Rashidov districts. Encouragingly, the share of low-mineralized groundwater expanded from 2.2 percent in 2023 to 9.9 percent in 2024, while strongly mineralized waters above 5 grams per liter remained limited to less than 1 percent of the region. However, areas with moderately mineralized groundwater of 3 to 5 grams per liter increased in several districts, including Arnasay, Dustlik, Zafarabad, and Paxtakor, signaling localized deterioration of hydro-reclamation conditions that demands stricter control of groundwater depths.

Soil salinity showed a gradual but genuine improvement over the past decade. In 2011, 79 percent of irrigated lands were affected by salinity; by 2023 that figure had fallen to 73 percent, and to 71.4 percent in 2024. Strongly and very strongly saline areas remain small and concentrated in a handful of districts, with an overall decreasing trend from 2021 to 2024. The authors attribute much of this progress to the transition from traditional furrow irrigation to water-saving technologies, now implemented on more than half of the region’s irrigated land. Water-salt balance calculations revealed, however, that most districts still run a negative total water balance, with deficits reaching 2,807 cubic meters per hectare in Arnasay in 2021 and 2,692 cubic meters per hectare in Zomin in 2022, while positive salt balances in districts such as Zafarabad, Paxtakor, and Sh. Rashidov indicate ongoing salinization risk during the growing season.

The heart of the study is its integrated scoring system. Each indicator was normalized and assigned a score of 0, 1, or 2, corresponding to unfavorable, intermediate, or favorable conditions, with stress-indicating variables such as salinity and vapor pressure deficit scored inversely. The partial scores were summed into a composite index with a maximum of 28 points, classifying each district as good, satisfactory, or unsatisfactory. Across 2021 to 2024, district-level scores ranged from 11 to 16 points. Most districts were classified as unsatisfactory in 2021, but the majority attained satisfactory status during 2022 through 2024, though scores generally remained in the lower portion of the satisfactory range, indicating that favorable conditions were never consistently achieved across all indicators.

The framework’s practical value lies in its simplicity. Because it functions as a three-level traffic-light system, it translates complex agroclimatic, soil, and groundwater information into a format that farmers, water-management organizations, and regional authorities can interpret at a glance. Districts with the lowest integrated scores, particularly Zafarabad and, in some years, Sh. Rashidov, emerge as priorities for enhanced groundwater monitoring, improved drainage maintenance, and targeted reclamation. Districts facing elevated aridity and high atmospheric demand call for irrigation scheduling improvements, water-saving technologies, and drought-tolerant cropping systems, while areas with rising groundwater mineralization would benefit from controlled leaching operations and stricter management of water table depths.

The authors are candid about the limitations. The framework relies on seasonal and annual indicators that may miss short-term extremes such as heat waves or episodic droughts, and two meteorological stations cannot capture every microclimatic variation, particularly in mountainous terrain. Groundwater monitoring networks have heterogeneous spatial coverage, and the equal weighting of indicators may not reflect the true influence of each factor in every region. Future work should explore alternative weighting schemes, integrate higher-resolution remote sensing data, and validate the method in other irrigated drylands. Still, because the assessment depends almost entirely on data already collected through existing programs, it can be adopted without substantial new investment, offering a scalable model for climate-resilient agriculture across Central Asia and other arid regions where every drop of water, and every grain of salt, counts.

Subject of Research: Integrated agroclimatic, soil salinity, and groundwater assessment of irrigated agricultural landscapes in the Jizzakh Region, Uzbekistan

Article Title: An integrated framework for agroclimatic, salinity, and groundwater assessment in the Jizzakh Region, Uzbekistan

Article References: Amanov, B., Ghirardelli, A., Sherov, A., Gafarova, A., Gulomov, D., & Tarolli, P. (2026). An integrated framework for agroclimatic, salinity, and groundwater assessment in the Jizzakh Region, Uzbekistan. iScience, 29(11), Article 117582. https://doi.org/10.1016/j.isci.2026.117582

Image Credits: AI Generated

DOI: 10.1016/j.isci.2026.117582

Keywords: agroclimatic assessment, soil salinization, groundwater, irrigated agriculture, Uzbekistan, Jizzakh Region, water-salt balance, aridity index, land degradation, climate change adaptation, Central Asia, land reclamation

The research matters because sand has quietly become a global sustainability crisis. UNEP estimates that global construction sand consumption runs to 40–50 billion tonnes per year, a figure derived not from direct measurement but from a proxy: cement production. The logic seems sound, since sand and cement are typically consumed together in concrete. Cement is a high-value commodity, produced in capital-intensive plants and taxed on sales, so many countries track it carefully. Sand, by contrast, is often extracted with little state oversight, feeds largely local markets and supports a substantial informal sector with low barriers to entry. The result is chronic data blindness. Reported sand production in Vietnam, for example, falls well short of known consumption, and mismatches in import and export statistics are common worldwide.

The Malaysian study exposes just how fragile the cement proxy really is. In the United States, where both cement and sand-and-gravel production are well documented, the two track each other closely, with a regression R² of 0.76. But across other countries the relationship collapses. Germany shows almost no correlation at all, and no consistent pattern emerges when national pairs are compared, suggesting the link depends on industry structure, trade patterns and construction practices rather than any universal constant. When the researchers tested the proxy against Malaysia’s own official statistics, cement-based estimates of sand production came out far too high in some years and diverged sharply from reported production after 2012 — precisely the period when sand demand shifted away from buildings and toward roads and coastal land reclamation, sectors the cement proxy cannot see.

The team’s alternative approach works backwards from consumption. Using the Google Open Buildings dataset, generated by a U-Net deep learning model applied to high-resolution imagery from Maxar Technologies and CNES/Airbus, they mapped building footprints across the entire country with a detection confidence threshold of 0.75. Building heights came from a separate deep learning architecture, BHE-NET, which fuses optical data from Sentinel-2 and radar data from Sentinel-1 to produce height maps at 10-metre resolution — a considerable advance on the 90-metre World Settlement 3D product. Validated against roughly 1,000 buildings measured by the ICESat-2 satellite lidar, the height product showed a root mean square error of about 9 metres and a mean absolute error of about 5 metres.

Those error figures sound alarming, but the study’s authors explain why they matter less than they appear. Nearly 88 percent of Malaysian buildings stand below 6.6 metres — broadly one to two storeys — and fewer than 1 percent exceed 14 metres. Because the national total is dominated by low-rise structures, a 3-to-5-metre height error at the individual building level often represents less than a single storey, and with 9.1 million buildings in the sample, over- and under-estimations tend to cancel out. The net effect on national stock totals is therefore strongly reduced, even though uncertainty remains at the level of any single structure. It is a textbook illustration of how big data can tame noisy measurements.

To convert geometry into tonnage, the researchers needed to know what each building is made of. They classified buildings along two axes: urban versus rural setting, using a population density threshold of 500 persons per square kilometre from NASA’s Gridded Population of the World dataset, and residential-commercial versus industrial use, derived from land cover maps produced by a retrained U-Net model applied to Landsat composites from 1988 through 2018, achieving overall accuracies above 85 percent. The land cover time series also served a second purpose: by intersecting building footprints with the year built-up land first appeared, each building could be assigned an approximate construction decade. Material intensity coefficients — tonnes of sand, gravel, brick clay, tile and cement per unit of floor area — adapted from a comprehensive Chinese database were then applied, with floor heights of 3 metres for residential and commercial buildings and 3.5 metres for industrial ones.

Buildings alone, however, do not exhaust a nation’s appetite for sand. The team added nearly 1.5 million linear infrastructure elements from OpenStreetMap, covering almost 400 million kilometres of roads and railways, dated by intersecting each segment with the land cover time series and assuming a 20-year maintenance cycle for roads. They also accounted for land reclamation, a major sand consumer in a country actively expanding its coastline for ports and urban development. Between 1991 and 2021, Malaysia reclaimed or plans to reclaim 82.64 square kilometres of land, more than half of it in the final decade. Using a conservative loading of 2.25 tonnes per square metre and a sand density of 1.5 tonnes per cubic metre, the researchers folded these megaprojects into their national consumption model at decadal resolution.

The results reveal a country transformed. Built-up surface in 2020 covered roughly 1,830 square kilometres — less than 1 percent of Malaysia’s land area — but buildings now account for about 80 percent of that footprint, up from just 49 percent in 1988. Almost 40 percent of the entire building stock predates the 1990s, and nearly as much sand, gravel and crushed rock is locked into buildings erected after 1998 as in everything built before. Regional contrasts are sharp: in the urbanised state of Selangor, sand dominates consumption, while rural Sarawak, with older buildings, consumes proportionally more bricks and tiles. Across the country, brick and tile use has declined as concrete has taken over, and gravel and crushed rock use has risen — trends that only become visible with this kind of spatial and temporal resolution.

Perhaps the most consequential finding concerns the future. The model estimates that around 326 million tonnes of sand and 356 million tonnes of crushed rock are embedded in Malaysian buildings constructed before 1988 — structures now approaching the end of their typical 50-year lifespan. With annual production running at roughly 30 million tonnes of sand and 100 million tonnes of crushed rock, these ageing stocks could become a significant secondary resource if recycling and reuse policies are put in place. More than 680 million tonnes of sand and crushed rock sit in pre-1988 buildings in total, a latent urban mine waiting for the right infrastructure. The temporal dimension of the model, the authors argue, allows policymakers to forecast when materials will come back onto the market, supporting circular economy planning in a way that static national statistics never could.

The methodology is not without limitations. The material intensity coefficients, the largest source of uncertainty, are drawn from Chinese rather than Malaysian data — a defensible choice given documented similarities in modern concrete building typologies between the two countries, but one that could introduce errors for older and rural structures, where estimates can vary by 30 percent or more. The approach also captures only new construction on previously undeveloped land, which works for a country in an active phase of urbanisation but may not translate to mature cities building on brownfield sites. And some sand flows remain stubbornly opaque: Singapore’s reported imports of Malaysian sand in 2017 exceeded Malaysia’s entire reported production that year, hinting at unrecorded trade shrouded in political sensitivity. Even so, the study demonstrates that when the full value chain — buildings, roads, reclamation — is included, satellite-derived consumption estimates correlate well with official production figures, while cement-based proxies fail. For the dozens of countries where sand data simply does not exist, that is a genuinely scalable way forward.

Subject of Research: Earth observation-based dynamic material stock modelling of construction sand consumption in Malaysia from 1989 to 2020

Article Title: Using earth observation for national high resolution dynamic material stock modelling through time; assessing sand consumption in Malaysia from 1989 to 2020

Article References: Bide, T., Novellino, A., Watson, C. S., Cai, B., Holland, L., Shao, Z., Wang, S., & Othman, N. S. (2026). Using earth observation for national high resolution dynamic material stock modelling through time; assessing sand consumption in Malaysia from 1989 to 2020. Journal of Industrial Ecology. https://doi.org/10.1007/s44498-026-00109-w

Image Credits: AI Generated

DOI: 10.1007/s44498-026-00109-w

Keywords: sand consumption, earth observation, material stock modelling, Malaysia, deep learning, building footprints, construction materials, material flow analysis, land reclamation, cement proxy, circular economy, remote sensing