💧 WASH Investment Research Portal

The latest issue of our highly-respected peer-reviewed journal Water International is out, featuring new research and insights from across the global water community. This issue features a diverse selection of contributions, including […]

dc.title: Tharparkar Desert Flora: Resilient Ecological System dc.contributor.author: Gul, Nazar; Ashraf, Muhammad; Salam, Hafiz Abdul dcterms.abstract: Discover the unique flora of the Tharparkar Desert, a resilient ecological system that supports diverse plant species essential for soil conservation, dune stabilization, and the livelihoods of local communities. Learn how these plants provide food, medicine, fuel, and income. cg.contributor.programAccelerator: Policy Innovations

dc.title: Validating the Efficiency of the AquaCrop Model Under Full and Deficit Irrigation Regimes to Simulate Future Climate Impacts on Wheat Crop dc.contributor.author: Memon, Shamim Ara; Shaikh, Irfan Ahmed; Talpur, Mashooque Ali; Junejo, Abdul Rahim; Mangrio, Munir Ahmed; Gul, Nazar; Khan, Zaheer Ahmed; Salam, Hafiz Abdul; Ashraf, Muhammad dcterms.abstract: Wheat yield and water demand are affected by the ongoing disturbance of climatic factors and greenhouse gases (GHG). As a result, the AquaCrop model's ability to anticipate climate change impacts on wheat harvests under full and deficit irrigation regimes in Sindh, Pakistan, was evaluated using wheat trials conducted between 2018 and 2020. However, for its validation, the results of the deficit irrigation treatment ITS50 (50% controlled irrigation at the tillering stage) for both seasons were employed. The model efficiently estimated yield with a normalised root-mean-square error (NRMSE) of 13% and 17%, a Willmott's d-index of 98% and a Nash–Sutcliffe efficiency (NME) of 95% under full and deficit irrigation treatments, respectively. The simulation results revealed an adverse effect of climate change on the yield and water productivity of wheat. Over the century, the model predicted an increase of 6% to 7% in wheat yield under full (well-watered) irrigation and a decrease of 10 to 12% in 25% reduced water applied depth (RAD) and 21% to 24% under 50% RAD scenarios for both representative concentration pathway RCPs (4.5 and 8.5). The overall wheat water productivity increased under a well-watered irrigation regime by 16% in RCP8.5 compared with RCP4.5. cg.contributor.programAccelerator: Policy Innovations

dc.title: Sunlight to Sustenance: Early Implementation Insights from a Solar-Grid Lift System Pilot in Nepal’s Mid-Hills dc.contributor.author: Adhikari, Aashika; Karki, Darshan; Shrestha, Shisher; KC, Jibesh dcterms.abstract: This technical brief presents early insights from a pilot solar-grid lift system (SLS) implemented in Bisdeutar, a remote and marginalized Majhi community in Indrawati Rural Municipality, Nepal. The intervention addresses chronic water scarcity exacerbated by climate change, difficult terrain, and limited infrastructure. Designed as a multiple-use system, the SLS supplies both domestic and irrigation water, lifting over 90,000 liters daily and serving 55 households. The study highlights that strong community engagement, in-kind contributions, and continuous social mobilization are critical for successful adoption. Capacity-building, agricultural support, and stakeholder collaboration including local government involvement are essential for long-term sustainability. Early outcomes show improved water access, reduced workload for women, increased cropping intensity, and emerging livelihood opportunities such as vegetable farming and beekeeping. The intervention has also enhanced disaster preparedness and strengthened community initiative in accessing external support. Overall, the pilot demonstrates that integrated, context-specific water solutions can generate broader socio-economic and environmental benefits, emphasizing the importance of combining technological innovation with institutional support and local ownership. cg.contributor.initiative: NEXUS Gains; Mixed Farming Systems cg.contributor.programAccelerator: Climate Action; Policy Innovations

dc.title: Gender Action Learning System Assessment: Insights on How Inclusive Innovations Shape Gender Transformative Outcomes dc.contributor.author: Enokenwa Baa, Ojongetakah; Chinyophiro, Amon; Nortje, Karen dcterms.abstract: The Gender Action Learning System (GALS) is a household and community-led transformative tool that offers researchers and practitioners a guide to drive inclusive transformation across food systems. The GALS assessment conducted under the CGIAR Scaling for Impact (S4I) program in Malawi evaluates how inclusive innovations drive gender-transformative outcomes in scaling climate-smart agriculture. This study engaged 1,417 participants—78% women—representing 4,095 households trained under the CGIAR Initiative on Diversification in East and Southern Africa (Ukama Ustawi). Using mixed methods (household surveys and Most Significant Change stories), the assessment found that GALS fosters equitable decision-making, agency, and climate resilience. Results show 87% of participants improved visioning and goal setting, 64% strengthened gender equality awareness, and 62% enhanced financial management. Joint household decision-making rose from 74–82% across domains such as farming, finance, and education, while women’s leadership and participation increased markedly. Adoption of climate-smart practices was high—96% for manure use and tree planting, 95% for crop rotation, and 93% for irrigation—demonstrating GALS’ effectiveness in promoting sustainable agriculture. Despite strong household and community uptake, institutional adoption remains limited (24%), signaling the need for integration into governance and partner systems. The report recommends strengthening facilitation capacity, linking GALS to economic empowerment initiatives, and embedding it in local institutions. Overall, GALS provides a scalable, self-sustaining methodology for gender-equitable innovation and climate-smart transformation. cg.contributor.initiative: Diversification in East and Southern Africa cg.contributor.programAccelerator: Scaling for Impact

dc.title: Low-Cost and Labour-Efficient Innovations in Household Recycling of Organic Wastes for Soil Improvement dc.contributor.author: Smith, Jo; Naher, Umme Aminun; Dahal, Khem Raj; Hasan, Md Mahmodol; Rahman, Md Mizanur; Smith, Pete; Bhusal, Mukunda; Wardle, Jennifer; Bittner, Dominik; Chukwu, Vince; Adhya, Tapan; Adhikari, Raj Kumar; Akter, Masuda; Campbell, Grant A.; Gaihre, Yam Kanta; Hossain, A. T. M. Sakhawat; Islam, Md Nurul; Khan, Mehedi Hasan; Maharjan, Salu; Mekuria, Wolde; Mia, Ripon; Moges, Awdenegest; Nalavade, Rujuta; Namaswa, Timothy; Panhwar, Qurban Ali; Tumwesige, Vianney; Vista, Shree Prasad; Yakob, Getahun; Zuan, Ali Tan Kee dcterms.abstract: Organic matter plays an important role in the health and productivity of soils, but its depletion is a common problem in households in low-income countries. This is due to lack of and competing uses for organic resources, and limited information on recycling methods. Therefore, here we review low-cost and labour-efficient innovations to improve recycling of organic wastes, stabilising residues so that soil organic matter can be increased with less inputs and enhancing nutrient content to produce a more effective organic fertiliser. Composting, anaerobic digestion and pyrolysis are all processes that stabilise organic matter. Innovations in treatments are needed to improve stabilization and control the release of nutrients so that they are available to crops in the right amounts and at the right time. This can be achieved by maintaining appropriate treatment conditions: for composting, carbon to nitrogen ratio 25–35, carbon to phosphorus ratio ∼50, pH 5.5–8.5 and 50%–60% moisture content; for anaerobic digestion, carbon to nitrogen ratio 20–35, bulk density 0.6–0.8 g cm−3, lignin content < 7.5%, pH 6.8–7.4 and moisture content 85%–95%; and for pyrolysis, carbon to nitrogen > 40 and moisture content < 20%. Different methods to achieve these ideal conditions are discussed, including appropriate choice of treatment method, co-composting/co-digestion for ideal nutrient content, enhancing nutrients using collected urine, nitrogen-fixing plants, bioslurry or by inoculating with bacterial communities, absorbing excess nutrients on biochar, adjusting pH using wood ash or biochar, pre-treatment to break down lignin and cellulose, and designs to achieve ideal moisture and temperature. Innovations should also ensure that treatment processes do not overuse or compete with other important household resources, such as finances, water or labour. We draw together findings to identify methods with most potential to improve soils in low-income countries, providing decision tables to guide selection of approaches for different contexts.

dc.title: Mobile Weather Stations dc.contributor.author: International Water Management Institute dcterms.abstract: Low-cost weather stations help monitor the weather more closely, helping rural communities better prepare for floods and landslides. These devices automatically measure and transmit weather information — rainfall, temperature and wind speed data — every five minutes. They operate autonomously, powered by solar energy. The stations are locally assembled using off-the-shelf technology and open-source software, like Arduino boards and code. The data is stored in microSD cards, and can be accessed directly from the card or received via SMS text message alerts. Users can use additional sensors and reprogram the software, making these stations incredibly flexible for a variety of applications. The weather stations can last up to ten years and cost only $350 each. Given their potential to reduce damage from flooding, it is estimated that they will pay for themselves in only two and a half years. This project was funded by the World Bank, through its Challenge Fund and the Global Facility for Disaster Risk Reduction (GFDRR), and the CGIAR Research Programs on Water Land and Ecosystems (WLE) and Climate Change, Agriculture and Food Security (CCAFS).

dc.title: AI4WaterPolicy: AI-Assisted Qualitative Feedback for Community Water Security in Rajasthan, India dc.contributor.author: Bhattacharjee, Suchiradipta; Nicol, Alan; Parhi, K. R.; Papnoi, P.; Iyer, R.; Kettle, S. dcterms.abstract: AI4WaterPolicy is an action-research pilot implemented in Rajasthan, India, by IWMI in partnership with Centre for Microfinance (CmF), Colectiv, and the Institute of Development Studies (IDS). The initiative explored the feasibility of using AI-assisted interviewing via WhatsApp (voice and text) to collect timely, scalable qualitative feedback from frontline water governance actors. The study engaged 352 participants across four cohorts, including CmF staff, Pani Mitras, and Panchayat representatives, generating structured qualitative insights to complement routine monitoring systems. Findings reveal the multifaceted role of Pani Mitras, spanning community mobilization, technical promotion, and institutional liaison. Sustained engagement was driven by visible outcomes, training, stewardship, and recognition, while disengagement stemmed from trust deficits, process challenges, and competing responsibilities, particularly affecting women. A key contribution of the pilot was demonstrating the value of “closing the feedback loop,” which led to improved confidence among participants, stronger engagement with local governance institutions, and enhanced ability to navigate water-related schemes. The study also highlights that digital tools require active facilitation to ensure inclusion and must be complemented by human oversight to address risks in AI transcription and translation. As a feasibility pilot, the study underscores the potential of AI-enabled feedback systems to inform adaptive program design and strengthen community water security interventions. cg.contributor.programAccelerator: Policy Innovations

dc.title: India Has Built an Extraordinary Foundation of Groundwater Recharge Infrastructure over the Past 20 Years. The Task Now Is to Make It Work dc.contributor.author: Alam, Mohammad Faiz cg.contributor.programAccelerator: Policy Innovations

dc.title: Stakeholder Profiling and Innovation Scaling Demand Signaling in Nigeria dc.contributor.author: Osei-Amponsah, Charity; Minh, Thai Thi; Atampugre, Gerald; Oke, Adebayo; Cofie, Olufunke O. dcterms.abstract: This report analyzes demand signals for scaling innovations in Nigeria’s agri-food, water, and climate sectors, and is based on a workshop that took place on December 4, 2026 in Abuja. By profiling five key stakeholder groups—ranging from the public sector and private investors to farmers and donors—the study evaluates how these actors articulate priorities and constraints. The findings highlight a strong market pull for climate-smart agriculture, digital solutions, and improved supply chains. However, demand articulation is currently fragmented due to infrastructure deficits, weak coordination, and capacity gaps. Moving beyond a simple ‘technology push’, stakeholders emphasized systemic needs over purely technical ones. Successful scaling requires bundled solutions that integrate finance, policy support, and social legitimacy with the technology itself. The report concludes that to achieve meaningful impact, innovation design must be more demand-responsive, shifting toward integrated scaling pathways that address the complex, institutional realities of the Nigerian landscape. cg.contributor.programAccelerator: Scaling for Impact

dc.title: Contribution of the Use of Microbiologically Contaminated Water in Slaughterhouses to Food Safety Risks dc.contributor.author: Alegbeleye, Oluwadara; Mateo-Sagasta, Javier dcterms.abstract: Food animals can become contaminated with enteric pathogens during slaughter, with potentially significant consequences for food and public health safety. This overview examines the scientific evidence implicating slaughterhouses as critical points for microbiological contamination of meat, with particular focus on the role of process water as a potential source and vehicle for foodborne pathogens. Despite the extensive use of water—e.g., for carcass washing, equipment cleaning, and general hygiene, there is a notable lack of empirical data on how waterborne pathogens may contribute to food safety risks. This gap highlights the need to better characterize the potential for process water to act as a reservoir and a vehicle for foodborne pathogens. To address this, this overview proposes a framework for tracing, characterizing, and quantifying the food safety risks associated with water used during slaughter. It emphasizes the importance of generating experimental data on the survival, persistence, and fate of water-origin pathogens on or within meat. The ability of a pathogen to persist throughout processing and storage significantly influences its impact as a foodborne hazard, as it increases the likelihood that it reaches consumers at infectious doses. Establishing genetic relatedness among isolates recovered from slaughterhouse water, contaminated meat, and clinical cases of foodborne illness can confirm water as a contamination source. However, in general, robust microbiological and food chain surveys are needed to establish clearer links between water-mediated contamination in slaughterhouses and subsequent human illness. Addressing these research gaps is critical for designing effective interventions and ensuring meat safety from slaughter through distribution. cg.contributor.initiative: One Health cg.contributor.programAccelerator: Sustainable Animal and Aquatic Foods

IntroductionEcological resilience, which is the core capacity of ecosystems to withstand disturbances, maintain functions, and undergo adaptive transformation, is critical to ecological conservation and high-quality development in the Yellow River Basin.MethodsThis study examines 60 prefecture-level cities in the Yellow River Basin using 2006–2023 panel data. Adopting an evolutionary resilience perspective, we develop a three-dimensional ecological resilience framework—resistance, adaptation, and innovation—and combine boxplot analysis, GIS-based spatial analysis, and the Spatial Durbin Model (SDM) to reveal spatiotemporal patterns of ecological resilience and quantify local and spillover effects of natural and socio-economic drivers.Results(1) Ecological resilience in the Yellow River Basin followed a fluctuating upward trend between 2006 and 2023, with widening regional disparities and a distinct spatial pattern: high in the lower reaches, low in the middle, and volatile in the upper reaches. (2) SDM results reveal a U-shaped direct effect of economic development (PGDP) on ecological resilience; industrial structure (IS), government intervention (GOV), and population density (POP) significantly reduced local eco-logical resilience, while residents’ living standards (DPI) enhanced it. (3) Spatial spillovers highlight interregional complexity: PGDP’s indirect effect is also U-shaped; urbanization (UR), POP, and DPI positively influence neighboring areas.ConclusionThe study concludes with policy recommendations to implement differentiated basin-wide collaborative governance strategies, promote green industrial transformation, and leverage the positive spatial spillover effects of urbanization and improvements in residents’ living standards.

The tequila industry in Mexico generates large volumes of wastewater with high organic loads, making real-time monitoring of chemical oxygen demand (COD) essential for regulatory compliance and environmental protection. This study presents a case study employing internet of things (IoT) sensors and machine learning (ML) algorithms to predict COD from suspended solids, dissolved oxygen, turbidity and electrical conductivity. The data was collected over an 87-day period, with 4,038 records obtained and employed in model development and validation. Three ML models (random forest, XGBoost, and gradient boosting) were evaluated using R2, where gradient boosting yielded the best results (R2 = 0.9878). Results indicate that while the three models exhibit good accuracy (R2 > 0.95) and do not show signs of overfitting (explained using residual analysis) they struggle predicting extreme (i.e., exceedingly low or high) values. Additional analysis were conducted to ensure model robustness, and residuals exhibiting homoscedasticity and approximate normality. This highlights that integration of IoT and ML offers a scalable and cost-effective solution for real-time water quality monitoring.

Wildfires increase the fluxes of water, ash, sediment, nutrients, and carbon into streams and rivers. However, the unpredictable timing and location of wildfires have resulted in a lack of continuous water quality records prior to and following wildfires. This limits our understanding of how post-fire increases of material transport impact water quality and gross primary production (GPP). We explored water quality and GPP responses in two adjacent montane second-order streams in northern New Mexico that were similarly impacted by the Las Conchas wildfire (2011). We conducted a before-after paired trend analysis using a subset of measurements from each year from a period with the most complete water quality data to facilitate between-year comparison. The two streams exhibited similar temporal trends in pre- and post-fire water quality during this late-summer period for 3 years prior to, and 6 years following the wildfire. An immediate increase in specific conductance – SC (2x increase) and turbidity (10x increase) were observed, with a return to near pre-fire levels over 6 years. However, pre- and post-fire trends in GPP differed between streams. To investigate this variability, a mixed effect model was used to assess which environmental parameters were drivers of GPP pre- and post-fire. SC and turbidity had varying effects on GPP pre-fire and negative effects post-fire. The stream gradient of the first-order tributaries impacted by fire, which differed between streams, may have also contributed to the differential metabolic response. We found the impacts of wildfires on GPP were variable and emphasize the need for additional research to better understand how wildfire impacts ecosystem processes that regulate energy and material fluxes in lotic systems.

Freshwater scarcity and unequal exposure to water-related risks are increasingly recognised as constraints on sustainable development. However, most water footprint assessments remain primarily volumetric and spatially aggregated, limiting their ability to diagnose how hydrological pressure, environmental stress, and socially differentiated impacts are redistributed within interconnected regional economies. This diagnostic gap constrains the capacity of existing approaches to inform subregional and basin-level governance. This study develops a territorially coherent hydro-economic framework that integrates multi-regional input–output modelling with spatially explicit indicators of hydrological pressure, environmental stress, and social vulnerability. Applied to 48 Local Labour Systems in Tuscany (Italy), the approach jointly quantifies production- and consumption-based volumetric water demand, scarcity-weighted impacts, and socially differentiated exposure across intra-regional supply chains. The results reveal pronounced internal asymmetries. Production-oriented territories generate a substantial share of regional water demand while experiencing disproportionately high environmental stress and social vulnerability, even where total water use is comparable to neighbouring areas. Conversely, consumption-oriented territories act as net importers of virtual water, redistributing pressure and impact to more hydrologically constrained and socially fragile locations within the same regional economy. By explicitly tracing the internal redistribution of hydrological stress and social vulnerability through economic linkages, the framework extends conventional volumetric assessments and provides a diagnostic basis for governance strategies that address not only efficiency, but also equity and the territorial distribution of water-related risk.

That “magic” sponge under your sink may be hiding an environmental downside. While melamine sponges are famous for effortlessly scrubbing away stubborn stains, they slowly break down as you use them—shedding tiny plastic fibers that wash into water systems. Researchers estimate that globally, these sponges could release over a trillion microplastic fibers every month, potentially entering the food chain and affecting wildlife.

A hidden freshwater system deep beneath the Great Salt Lake has been revealed using airborne electromagnetic surveys. Scientists found that freshwater extends much farther under the lake than expected, reaching depths of up to 4 kilometers. The discovery began with mysterious reed-covered mounds formed by pressurized groundwater pushing upward. Researchers are now investigating whether this underground water could help control hazardous dust from the drying lakebed.

Spiders and insects may not be fan favorites, but they are vital to the health of ecosystems—and scientists barely know how they’re doing. Researchers found that nearly 90% of North America’s insect and arachnid species have no conservation status, leaving their fate largely unknown. Even more striking, most states don’t protect a single arachnid species. The study warns that these overlooked creatures are essential to planetary health and urgently need better monitoring and protection.

As deep-sea waters warm, scientists expected trouble for the microbes that help keep ocean chemistry in balance. Instead, researchers found that Nitrosopumilus maritimus can adapt to warmer, iron-limited conditions by using iron more efficiently. Because these microbes control key nitrogen reactions that support marine life, their adaptability could help sustain ocean productivity. In a warming world, they may play an even bigger role in shaping marine nutrient cycles.

Deep in the Congo Basin, vast peatlands quietly store enormous amounts of Earth’s carbon — but new research suggests this ancient vault may be leaking. Scientists studying Africa’s largest blackwater lakes discovered that significant amounts of carbon dioxide bubbling into the atmosphere come not just from recent plant life, but from peat that has been locked away for thousands of years.

A new 30-year analysis reveals that melting land ice is now the main force behind rising global sea levels. Researchers discovered that oceans rose about 90 millimeters since 1993, with most of the increase coming from added water mass rather than just warming expansion. Ice loss from Greenland and mountain glaciers accounts for the vast majority of this gain. Even more concerning, the rate of sea-level rise is accelerating.

Deep in the Arctic north, drained peatlands—once massive carbon vaults built over thousands of years—are quietly leaking greenhouse gases into the atmosphere. But new field research from northern Norway suggests there’s a powerful way to slow that loss: raise the water level. In a two-year study, scientists found that restoring higher groundwater levels in cultivated Arctic peatlands dramatically cut carbon dioxide emissions, and in some cases even tipped the balance so the land absorbed more CO₂ than it released.

Around 1550, life on Rapa Nui began changing in ways long misunderstood. New research reveals that a severe drought, lasting more than a century, dramatically reduced rainfall on the already water-scarce island, reshaping how people lived, worshiped, and organized society. Instead of collapsing, Rapanui communities adapted—shifting rituals, power structures, and sacred spaces in response to climate stress.