Economic effectiveness of climate-smart agricultural practices for smallholder farmers: evidence from prioritized high-value crops in South Asia

1 Introduction

Climate change poses a serious threat to livelihoods of people not only in South Asia but also all over the world (World Bank, 2022a,b). South Asia encounters distinct challenges and heightened vulnerabilities to climate change while striving for food security. Increasing temperatures and changes in rainfall pattern lead to climate extremes such as heat waves, water scarcity, droughts, floods, typhoons, and glacier melting, consequently triggering disasters that threaten food production and security (IPCC, 2014; IPCC, 2022; Poudel et al., 2026). Over the past two decades, South Asia has been the region most impacted by extreme weather events (Germanwatch et al., 2025). Additionally, the IPCC Sixth Assessment Report also shed light on the fact that climate-related temperature extremes have an impact on food security, nutrition, and livelihoods in Asia, exacerbating the challenges faced by the region (IPCC, 2022). These threats are particularly serious in South Asia, where more than one billion people depend on monsoon-fed agriculture for their food and livelihoods. Monsoon dependency represents the region’s unique and defining vulnerability: Disruptions to seasonal rainfall can result not only in crop failures but it also leads to income shocks and long-term food insecurity for hundreds of millions of smallholder households. Effective management of these threats requires urgent, evidence-based interventions that both enhance livelihoods resilience and build adaptive capacity at the farm level.

These problems are particularly severe in Nepal, India, and Sri Lanka. The monsoon season, occurring from June to September, typically delivers approximately 80% of the region’s yearly rainfall (India Meteorological Department (IMD), n.d.; Poudel et al., 2023). However, climate change has destabilized monsoon patterns, undermining traditional agricultural cycles. These changes pose significant risks to agriculture and the overall sustainability of the South Asian region (IPCC, 2022). Furthermore, a report from the United Nations warns that advancing climate change could result in flooding, food shortages, and stagnant economic growth (IPCC, 2014). For instance, in 2024 and 2023, devastating floods struck Nepal (Lamichhane et al., 2025) and North India, highlighting this growing unpredictability (BBC News, 2023).

Smallholder farmers are the main food producers and land stewards in South Asia. Approximately 80% of the food consumed in Asia is produced on small farms, with approximately 350 million smallholder farmers across Asia (IFAD, 2013). They often face significant vulnerability to climate change risks, primarily due to their heavy dependence on rain-fed farming systems and have limited adaptive capacity due to low socio-economic status (Poudel and Shaw, 2016). In the agriculture sector, climate variations, including intense droughts, floods, cyclonic events, heat waves, altered rainfall patterns, and rising average temperatures, have posed a significant threat to agricultural productivity (Bibi and Rahman, 2023; Poudel et al., 2021). Higher temperatures reduce yields of major crops such as rice, wheat, and maize. In the Indo-Gangetic Plains, a 1 °C increase can decrease wheat yields by 4–6% and rice yields by 3–5% (Zhao et al., 2017). Erratic monsoons and reduced rainfall in some places lead to water scarcity, lowering irrigated crop yields, such as excessive rainfall in coastal areas causes flooding, damaging crops such as rice in Sri Lanka. Increased frequency of droughts and floods destroys crops and degrades soil. Cyclones in coastal areas further reduce production in the affected seasons. Higher temperatures and erratic rainfall exacerbate soil erosion and nutrient depletion, reducing long-term productivity, particularly in rain-fed areas of South Asia’s farmland. India’s northwest faces severe wheat yield decline and Sri Lanka’s tea, and rice are hit by droughts and floods. It is estimated reduction in yield by 2050 could range from 10 to 20% for rice, 12 to 25% for wheat, and 15 to 30% for maize under moderate emissions scenarios (RCP 4.5) in business-as-usual (BAU) situation (IPCC, 2022). Economic losses could exceed $50 billion annually, exacerbating food insecurity for 1.8 billion people. Smallholder farmers, reliant on rain-fed agriculture, are most vulnerable due to limited resources to cope with these changes. If current practices continue without change (business as usual), rain-fed agricultural systems may become unsustainable as climate change intensifies. These circumstances necessitate the development and implementation of adaptation solutions that can guarantee farmers’ livelihoods, assure food production, and, at the same time, mitigate climate change (Lal, 2024). A key policy solution to address these climate risks is promoting climate change adaptation through the adoption of climate-smart agriculture (CSA) practices. According to the Food and Agricultural Organization of the United Nations (FAO), CSA is an approach designed to develop agricultural strategies that ensure sustainable food security in the face of a changing climate (FAO et al., 2018). The projected losses by 2050 under moderate emissions (RCP 4.5) are as follows: rice: 10–20% decline; wheat: 12–25% decline; maize: 15–30% decline (IPCC, 2022). These losses could exceed USD 50 billion annually, jeopardizing food and livelihood security for 1.8 billion people across the region (World Bank, 2022a,b).

CSA is a sustainable strategy aimed at boosting agricultural productivity and incomes, enhancing resilience to climate change, and minimizing greenhouse gas emissions where feasible (Lizarazo et al., 2021). Beyond these core objectives, CSA adoption offers additional benefits, such as improved household nutrition security (Teklewold et al., 2019), reduced labor disparities for women (Khatri-Chhetri et al., 2020; Dabral et al., 2025), and enhanced conservation of biodiversity, soil, and water (Poudel et al., 2024; Udawatta et al., 2021; Thierfelder and Wall, 2012). CSA is defined by the FAO with three interdependent pillars: (1) Productivity indicates sustainably increasing agricultural output and incomes; (2) resilience focuses on reducing exposure and vulnerability to climate shocks, droughts, and variability; and (3) mitigation stresses on reducing and/or removing greenhouse gas emissions where possible (FAO, 2013). These three pillars together make CSA identical from conventional agricultural practices and frame the evaluation criteria used in this study. However, the adoption and expansion of CSA practices in South Asia (SA) remain limited. Smallholder farmers face barriers such as high initial and operational costs, limited access to technology and information, short-term yield gains, trade-offs between productivity, sustainability, and environmental goals, unreliable seasonal climate forecasts, and poor coordination across agricultural value chains. These challenges heighten smallholder vulnerability by hindering the adoption of CSA practices that could enhance food security, nutrition, and climate resilience.

However, the evidence of CSA benefits is growing, and there is still a critical knowledge gap. Traditional cost-benefit analysis (CBA) frameworks used in agricultural investment appraisal are not flexible: They fail to capture changes in investment under climate uncertainty and do not incorporate the social and environmental externalities that are central to the value of CSA. Yet, there is no study in South Asia that has applied an integrated framework that bring together CSA prioritization, financial CBA, externality valuation, and real option analysis (ROA) across multiple countries and high-value crop systems. This study aims to fill that gap. This study assesses the costs and benefits of prioritized climate-smart agriculture practices for smallholder farmers across selected high-value crops in three South Asian countries. Prioritizing CSA practices is critical for decision-making as it accounts for local and system-specific factors. Effective prioritization requires information on socio-economic impacts of CSA, yields, inputs, costs, and benefits (Lizarazo et al., 2021). It involves ranking practices based on criteria such as easy to implement, profitable, environmentally friendly, no or low greenhouse gas emission, and their role in boosting productivity. These criteria vary by crop, strategy, and country (Karki et al., 2024; Lizarazo et al., 2021). The prioritization process identifies high-impact strategies that enhance productivity, resilience, and greenhouse gas (GHG) mitigation in agriculture.

The study aims to create a portfolio of viable CSA practices to guide stakeholders, including policymakers, in selecting optimal options. While most climate-smart agriculture research overlooks economic feasibility, this study addresses this gap by incorporating CBA to evaluate CSA strategies. It achieves three objectives: (i) identifying prioritized climate-smart strategies for smallholders in three SA countries; (ii) quantify financial returns conducting a cost-benefit analysis (CBA) to assess the financial viability of prioritized CSA practices using NPV, IRR, BCR, and payback period indicators; and (iii) value social and environmental externalities applying contingent valuation and real option analysis (ROA) to capture externalities and investment flexibility under climate uncertainty, producing social NPV and social option values for each practice.

CBA is a decision-making tool that evaluates the economic viability of investments by comparing costs and benefits. In this study, financial CBA focuses on private profitability, while social net present value and real option analysis incorporate social and environmental externalities generated by CSA practices in SA regions. Key economic indicators included in the analysis are net present value (NPV), internal rate of return (IRR), benefit-cost ratio (BCR), and payback period (PP). Profitability is assessed through incremental benefits (yield increases multiplied by output price) and incremental costs (changes in machinery, inputs, services, and labor costs) compared to business-as-usual (BAU) practices.

2 Methodology

2.1 Study area description

The study was conducted across three countries in South Asia, namely, Nepal, India, and Sri Lanka (NIS). The sampling sites were selected based on two criteria: first, the prior information on the ongoing projects related to climate-smart agriculture, and second, to cover the diversity in climate and agriculture practice in the region. According to these selections scheme, we selected one site each from Nepal, India, and Sri Lanka to diversify the climatic condition and agricultural practices as shown in Figure 1. The study site profile summary of the selected countries is shown in Table 1.

Table 1. Study site profile summary for Nepal (Nawalpur), India (Champawat), and Sri Lanka (Anuradhapura).

Sources: DHM (2023), IMD (2023), DMC (2023), and World Bank (2022a,b).

In Nepal, the study focused on bean, bitter gourd, and cauliflower, while in India, it centered on tomatoes, capsicum, and cabbage, and in Sri Lanka, it identified paddy, mango, and chilli as the high-value crops. The research focuses to these specific value chains to prioritized CSA practices for CBA calculations.

2.2 Data collection and analysis

The data collection for this research started with collection of high-value crops suggested by smallholder farmers and experts in the selected countries. This study began with the participatory identification of high-value crop value chains through stakeholder consultations with smallholder farmers and agricultural experts in the selected countries. With these high-value crops already suggested, the next phase involved ranking of climate-smart agriculture practices under this high-value crops through prioritization process. The CSA prioritization process considered mainly three indicators of climate-smart agriculture such as easy to implement, profitable, environmentally friendly, and no or low greenhouse gas emission. This was followed by structured questionnaire survey with the purpose of household data collection from the smallholder farmers. The questionnaire was designed to obtain the information on general information of farming practices, socio-economic status, cost estimation (implementation, maintenance, and operation), crop production, and externalities generated by the adopted CSA practices. Before starting a questionnaire survey, two enumerators were trained from each country on managing the questionnaire, translating it, and recording farm locations and responses through mWater data collection portal. The enumerators also conducted a pre-test of the questionnaire to gain initial experience and refine the translation. Any unforeseen issues identified during this process were addressed and resolved. Additionally, prior to conducting the survey, oral consent was obtained from the respondents to ensure that the collected data would be used only for research purpose and kept confidential following the European Union General Data Protection Regulation (EU-GDPR). The household head was ideally chosen for the interview from each household. However, if the household head was unavailable or unable to participate, another adult who has been doing farming practices for at least 5 years was selected for the interview.

2.3 Sampling design

A purposive sampling technique was employed to select the study households, targeting smallholder farmers who had adopted CSA practices in the selected study areas. The total number of smallholder farmers adopting CSA practices was unknown. Hence, the sample size was kept at 68 after sample size calculation using Raosoft software for an unknown population size and a 90% confidence interval for each country. A total of 100 responses were obtained through the survey from each country. The study is based on a sample survey rather than a complete enumeration. Primary data collection covered the period of March to April 2024 and constituted cross-sectional data. All key variables used in the analysis, including implementation cost, operational and maintenance cost, discount rate, output price, input price, lifecycle, and yield, are defined in Table 2. Sites were purposively sampled based on agro-ecological diversity and the presence of established CSA pilot programs to ensure data reliability and representativeness across the varied climatic contexts of South Asia.

Table 2. Variables used in cost-benefit analysis.

The research applied both primary and secondary data. Primary data were collected from the household surveys and stakeholder workshops, whereas secondary data were obtained from relevant literature from national ministries, research institutes, and non-governmental organizations working in the studied areas of three countries. Primary data collection was conducted between March and April 2024, constituting cross-sectional data. Secondary data covered the period 2015–2024 and were used primarily for deriving baseline productivity figures, commodity prices, and literature-based shadow prices for externality valuation. Data analysis combined both qualitative and quantitative approaches, with surveys and interview responses entered a cost-benefit analysis Excel tool and using SPSS. To ensure data reliability, the findings were cross-checked with prior studies in South Asia and through validation workshops for consistency and reproducibility. Household served as the unit of analysis to compare profitability with CSA and business as usual (BAU), assessing net benefits and cost–benefit ratios.

2.4 Conceptual framework

The overall analytical framework of this study is structured around three integrated components: (i) CSA prioritization using the CSA prioritization framework (CSA-PF) tool to identify relevant practices through stakeholder engagement; (ii) financial and economic cost-benefit analysis (CBA) using NPV, IRR, BCR, and payback period to assess private profitability; and (iii) externality valuation and real option analysis (ROA) to capture social and environmental co-benefits and investment flexibility under uncertainty. These three components integrated into a composite evaluation of CSA viability, producing both financial and social net present values, enabling policy-relevant comparisons across practices and countries. The overall conceptual framework is depicted in Figure 2.

2.5 Prioritizing high-value crop climate-smart agriculture practices

The prioritization process of the high-value crops under CSA started with identifying existing and potential practices through stakeholders’ consultation in three countries. Then, a list of all practices mentioned by the workshop participants was made for each stage—input acquisition, production, post-harvest, and marketing based on criteria such as the intensity of climate hazards such as floods or droughts. A stated preference approach was applied to examine farmers’ choices of CSA technologies across the study areas. In this method, participants were asked to indicate their preferences among a list of technologies. These practices were ranked by their significance using indicators such as productivity, income, resilience enhancement, and mitigation benefits. Farmers’ preferences for climate-smart technologies were collected through a two-stage process. First, farmers were grouped into a team of 10 making three groups to discuss CSA technologies. The experts were the local government agriculture extension officers, representatives of local organizations working in the field of climate change and agriculture. Then, each participant scored the technologies on a scale from 1 to 4 (1 = no preference, 2 = low preference, 3 = moderate preference, and 4 = high preference). These scores were averaged based on the preference and selected the high scored technologies for the detail cost-benefit analysis, aiming to ensure economic efficiency and provide dependable data for value chain stakeholders to make informed choices (Table 3). The CSA-PF tool, developed by the International Centre for Tropical Agriculture (CIAT) and the CGIAR Research Program on Climate Change, Agriculture, and Food Security (CCAFS), was adopted in this study. This tool offers a detailed, step-by-step framework that assists stakeholders in refining an extensive list of climate-smart agriculture (CSA) practices into a concise set of practical options. Three CSA practices of high-value crops from each country were selected for economic feasibility analysis.

Table 3. Top prioritized CSA practices in Nepal, India, and Sri Lanka.

2.6 Cost-benefit analysis methodology

A cost-benefit analysis approach was applied to assess the effectiveness of implemented CSA practices in the studied areas. CBA is a decision-making tool that assess whether the benefits of the project policy exceed its associated costs over a defined period. CBA has been used not only in private sector but also is equally applied in public sector to assess the cost and benefit of the public policy and programs. A major indicator of conducting a CBA is clearly defining alternatives options and measuring their effects on the specific objective being analyzed (Morimoto and Hope, 2004). The CBA approach is not only strong and reliable but also straightforward to apply generating results that are robust and essential for guiding both current and future investment decisions. These decisions are crucial for various stakeholders including government planners, development agencies, non-governmental organizations, and farmers.

In this study, CBA combined both ex-ante and ex-post evaluations. This approach was imperative because some of the practices had already been implemented by farmers, while others have been initiated but their impacts were not yet visible due to timeframe which they were applied. The cost of implementing CSA practices includes all expenditures related to adoption, implementation, and ongoing maintenance, calculated per hectare of farmland. Although many farmers applied these practices on plots smaller than one hectare, all cost calculations were standardized to a per-hectare basis.

Four decision criteria were used under CBA. These were net present value (NPV), internal rate of return (IRR), benefit-cost ratio (B/C ratio), and payback period (PBP). The NPV is the value of the discounted future net benefits (Equation 1). A CSA practice with an NPV > 0 is deemed viable and should therefore be adopted. A project is rejected if otherwise (i.e., NPV < 0).

NPV = ∑ t = 0 T B t ( 1 + r ) t − ∑ t = 0 T C t ( 1 + r ) t (1)

Where NPV represents the value of the discounted future net benefits, B t represents the incremental benefit of the CSA practices in the tth period, C t represents the costs of the CSA practices in the tth period, r is the relevant discount rate, and T represents the lifecycle of the CSA practices. In this study, the changes in cost and benefits of the prioritized CSA practice were compared to the BAU practices. The incremental benefits were calculated in terms of the positive changes in yield multiplied by the price of the commodity in the specified crop. The incremental costs were evaluated as the changes in quantities used for inputs, services, labor and machinery, and equipment as they related to the implementation, maintenance, and operations cost multiplied by their respective unit costs.

Another decision-making criterion under cost-benefit analysis includes the internal rate of return (IRR). The IRR is the discount rate at which the NPV of the project becomes zero and it is compared against the discount rate (Equation 2).

IRR = LDR + ΔDR × NPV at LDR ∑ PV of INB at two DR , IRR > r (2)

Where LDR is the lower discount rate, ΔDR represents the difference between discount rates, and INB denotes the incremental net benefits. Unlike NPV, calculating IRR does not require cost of capital in advance. Once determined, IRR serves as a benchmark to evaluate various possible outcomes and helps assess the profitability of different scenarios. The IRR that is higher than the chosen discount rate indicates a profitable investment.

In the context of benefit–cost (B/C) ratio, a project or policy is considered viable if the benefit-cost ratio is greater than 1. The B/C ratio is the ratio of the present value of total benefits to the present value of total costs over the project’s lifetime, both discounted at the chosen discount rate. It means that the benefits gained from the implementing the CSA are sufficient to fully recover the associated costs with some surplus remaining. The B/C ratio is shown in Equation 3.

B / C = ∑ t = 0 T B t ( 1 + r ) t / ∑ t = 0 T C t ( 1 + r ) t (3)

Payback period is the duration needed for the net cash inflows to recover the initial investment in the business (Equation 4). The shorter the payback period, the acceptable is the project.

Payback period = Initial Investment Net Cashflow Period (4)

2.7 Sensitivity analysis

Sensitivity analysis explains how a change in a variable impacts the NPV. Addressing uncertainty is a crucial aspect of any cost-benefit analysis particularly amid of climate challenge. For this analysis, changes in discount rate were applied to observe the changes in NPV and B/C ratio with all selected CSA practices. The range of discount rate 3–30% for Nepal, 1–10% for India, and 2–20% for Sri Lanka was applied depending on the base rate. The sensitivity of NPV and BCR to discount rate was assessed independently, holding all other variables constant while modifying one at a time.

2.8 Externality parameters

Implementing climate agriculture practices generates benefit beyond financial profitability and increased agricultural productivity. These practices also generate external advantages. Research has shown that water management not only improves soil moisture but also increases water availability for crops during dry periods (Magombeyi et al., 2018; Nangia et al., 2018). Similarly, practices such as mixed cropping and crop rotation support ecosystem services by fostering biodiversity and limiting the accumulation of pests and diseases (Debie, 2025; Tamburini et al., 2020; Tiemann et al., 2015). Moreover, precision nutrient management enhances soil quality that contributes to greater resilience of cropping systems against climate stressors and helps reduce greenhouse gas (GHG) emissions from synthetic fertilizers (Sommer et al., 2016; Fairhurst, 2012). Although these environmental and social benefits are often not the primary focus of traditional CBA, they are essential for a comprehensive assessment of adaptation outcomes.

This study assessed on-farm externalities associated with 10 CSA practices applied across three study locations. Experts identified six key externalities deemed relevant for these contexts (Table 4). To quantify the economic value of these external benefits, the contingent valuation method (CVM) was used. This approach estimates the economic contribution of an externality by calculating the weighted change resulting from the intervention and applying a shadow price, representing the willingness to pay by the farmers and beneficiaries (Sain et al., 2017). The shadow prices were derived using market-based proxies, following established practices in literature (Lera-López et al., 2014; Bhattacharyya et al., 2019; Sain et al., 2017; Ng’ang’a et al., 2017). Data for the valuation of external effects were gathered through consultations with farmers, experts, researchers, and agricultural officers of the related field and from the relevant literature.

Table 4. Cost-benefit analysis of prioritized CSA practices per hectare across selected high-value crops in Nepal, India, and Sri Lanka.

In this study, contingent valuation method (CVM) was implemented following a structured four-step procedure. First, a hypothetical market scenario was developed for each externality, presenting respondents with a realistic description of the externality and its context within the CSA practice. Second, respondents were asked to state their willingness to pay (WTP) for the stated environmental or social benefit using a dichotomous choice format, where they indicated acceptance or rejection of a specified bid amount. Third, potential biases inherent to CVM were identified and mitigated: Strategic bias was addressed by ensuring respondents their response would be confidential and focusing that their answers would not affect actual payments; hypothetical bias was minimized through use of visual aids and pre-testing of the questionnaire with a pilot group. Fourth, the average WTP values calculated were aggregated and used as shadow prices to monetize the externalities, which were subsequently incorporated into the social net present value (SNPV) calculation. This approach follows the methodology established by Sain et al. (2017) and is consistent with best practices in environmental valuation for agricultural interventions in developing countries.

2.9 Social cost-benefit analysis

Social cost-benefit analysis was performed on the financial CBA described above by adding the discounted value of monetized externalities to the financial net benefit value, while holding the cost value unchanged, since the externalities valued here are additional social benefits rather than additional social costs (Equation 5).

Social net present value ( SNPV ) = ∑ [ ( B t + E t – C t ) / ( 1 + r ) t (5)

where E_t is the sum of monetized externalities in period t.

Social IRR (SIRR) is the discount rate at which SNPV = 0, calculated analogously to Equation 2. Following the same logic, a social benefit-cost ratio can be derived as Equation 6.

Social BCR = [ ∑ ( B t + E t ) / ( 1 + r ) t ] / [ ∑ C t / ( 1 + r ) t ] (6)

i.e., the ratio of the present value of total social benefits that is private financial benefits plus monetized externalities to the present value of total costs. Social BCR is ≥ financial BCR whenever externalities are net positive.

Women’s empowerment was defined as the reduction in women’s labor burden, time saving, and income productivity resulting from CSA adoption. CSA practices such as drip irrigation reduce the time women spend on manual field irrigation, while mixed cropping reduces weeding labor. This operational definition converted an intangible social benefit into a measurable unit: Hours of women’s labor saved per household annually. Through expert consultations, the average reduction in women’s labor time from each CSA practice was estimated. These estimates were averaged and calculated as a weighted change in labor hours per female household member standardized to one hectare. Since there is no market price for women’s time savings, a shadow price was derived using two complementary approaches following Sain et al. (2017): (i) a WTP-based approach, in which participants were asked through a contingent valuation question how much they would be willing to pay or accept as compensation for the labor time saved, with the average WTP used as the shadow price per unit of time; and (ii) a market wage proxy, in which the existing local agricultural daily wage rate for female labor (USD/day) in each country was used to convert hours saved into monetary equivalents, serving as an independent cross-check on the WTP-derived shadow price.

2.10 Real option analysis

The traditional CBA only deals with a static estimate of the economic feasibility of agricultural interventions, and it generally overlooks circumstances raised by uncertainty and the potential for future learning. This is especially relevant for CSA, where decisions must consider climatic uncertainty, technological and market changes, and socio-political movement. In such cases, real option analysis (ROA) offers a more dynamic and strategic valuation framework. In this study, Black–Scholes ROA (Equations 7–10) was applied to assess the economic resilience of selected climate-smart agricultural practices such as crop rotation, mixed cropping, precision nutrient management, drip irrigation, water management, polyhouse, short-term crops, and permanent crops across Nepal, India, and Sri Lanka. Each practice represents an investment under uncertainty, where future climate conditions, policy environments, and market responses are not fully known at the time of decision-making.

Real option analysis is superior to traditional CBA for CSA investments under climate uncertainty for three key reasons. First, ROA treats CSA investments as options rather than fixed commitments capturing the value of financial flexibility to invest, defer, scale up, or abandon a practice as new information about climate, markets, or policy emerges. Second, the Black–Scholes model, originally developed for financial options pricing, adapts well to agricultural investment contexts by quantifying the value of waiting and learning a critical advantage given the inherent uncertainty of climate projections in South Asia. Third, ROA generates a social option value which, when added to the SNPV, provides a fuller picture of the true economic worth of CSA practices, making it a more robust tool for guiding public investment decisions under uncertainty than NPV-based CBA alone.

Investment in these technologies involves irreversible costs, uncertain outcomes, and opportunities for modifying the implementation. ROA captures the value of flexibility in decision-making, allowing for delayed, abandoned, or adaptive deployment of CSA practices based on evolving climatic or economic information. That allows farmer and policymakers to postpone or scale investment based on the situation. For the social option values, risk free rate of 6.23, 3.47, and 8.78% were considered for Nepal, India, and Sri Lanka, respectively.

OV = SN ( d 1 ) – X / e − rt N ( d 2 ) (7)

d 1 [ ln ( S / X ) + ( r f + ½ σ 2 ) ∗ t ] / σ √ t (8)

d 2 = d 1 − σ √ t (9)

Where OV is the option value ($), S is the present value of cash flows from optional investment ($), d1 is the lognormal distribution of N(d₂), d2 is the lognormal distribution of N(d₂), X is the investment expenditure ($), rf is the annual risk free continuously compounded rate (%), σ is the annualized variance (risk) of the investment’s project, t is the period until investment (years), and e^-rt is the exponential term which is equal to 2,71,828.

The real options method accounts for uncertainty in optimal decision-making by modeling the stochastic behavior of an asset’s value. Mathematically, this stochastic process is characterized by two parameters: the annual risk-free continuously compounded rate and the annualized variance (risk) of the investment project. In the presented case, some of stochastic variables could be defined as risk and uncertainly variables too.

Option value OV = SN ( d 1 ) − present value of X times N ( d 2 ) (10)

where N(d₁) and N (d₂) represent the probability distributions. The values of N(d₁) and N(d₂) are obtained from normal probability distribution tables. They give us the probability that S or X will be below d₁ and d₂. In the BS model, they measure the risk associated with the volatility of the value of S. However, the strategic real options of the investment project are calculated using the Black–Scholes methodology and are calculated as follows Equation 11:

NPV SRO = NPV t + OV (11)

Where NPV_SRO is the strategic real option ($).

In sum up, the overall methodology of this study goes through a clear three stages. Stage 1—CSA-PF: Using the CIAT/CCAFS CSA prioritization framework, high-value crop CSA practices were identified, listed, and scored by farmers and experts through participatory workshops. Practices were ranked on a 1–4 preference scale and the top-ranked practices per crop and country were selected for economic analysis. Financial CBA was the Stage 2: In this stage, the selected practices were analyzed for financial CBA using NPV, IRR, BCR, and payback period, with sensitivity analysis across a range of discount rates (1–30%). This stage assesses private profitability from the smallholder farmer’s perspective. At last, social and environmental externalities were monetized using contingent valuation and shadow pricing to derive social NPV (SNPV) and social IRR (SIRR) to calculate social CBA and real option analysis (ROA). The Black–Scholes ROA model was then applied to generate social option values (SOVs), capturing the value of investment flexibility under climate uncertainty.

3 Results

While calculating CBA, integrating CSA-PF enables the effective identification of the most feasible CSA options. The input across the high-value crops provided by the farmers and stakeholders during the CSA prioritization workshops was incorporated to get the valuable insights for implementing CSA strategies at the farm level. This research provides a comprehensive CBA that is better than the conventional focus on NPV and IRR. It also includes detail assessment of the PBP, BC ratios, sensitivity analysis, and real option analysis that support risk evaluation through scenario-based approaches and provide the options especially relevant given the dynamic nature of climate and market conditions. Analyzing various high-value crops across three selected South Asian countries provides insights on comparative evaluation as each region has different climate conditions and varying degrees of climate risk impacts on crops. For instance, Champawat of India experiences a range of agroecological zones from tropical to cold climate, while Nawalpur of Nepal typically has a hot climate in summer and dry cold in winter but Anuradhapura, Sri Lanka, has a dry and hot climate with consistently high temperature. The results are presented in three parts, the most highly prioritized high-value crops, CSA practices by farmers and their standard ranking, are presented in the first part; second, the detailed CBA calculation along with indicators, sensitivity analysis, externalities, and real options analysis; and finally, with a synthesis of existing literature highlighting the findings of the study associated with CSA strategies.

3.1 Prioritized CSA among smallholder farmers in the selected value chains

Prioritization was based on how the CSA practices contribute to crop productivity, strengthened resilience, and mitigate climate change risks of the high-value crops. This process started in consultation with farmers, experts, and other stakeholders in the studied areas of three countries. The selected practices represent the most widely adopted and popular CSA technologies in the study regions. During the stakeholders’ workshop, participants were asked to rank each practice on a scale of 1 to 4. A score of 4 indicated a strong positive impact, while 1 indicated no perceived benefit (Table 3). In Nawalpur, Nepal, participants made a list of 14 CSA practices with high-value crops and then selected high ranked three practices, namely, crop rotation, mixed cropping, and precision nutrient management. Similarly, in Champawat district of India, three high ranked practices, namely, polyhouse, water management, and drip irrigation, out of 10 CSA practices were prioritized.

In the case of Anuradhapura, Sri Lanka, four practices, namely, mixed-cropping, water release timetable, short-term crops, and permanent crops, out of 16 CSA practices were prioritized. Distinct type of practices applied in each region was based on the local context. However, mixed cropping and water management-related practices were highly prioritized in all study areas. The mixed cropping in the context of this study refers to multiple crops that are grown in the same field at the same time. These practices are favored as they help minimize the risk of crop failure and yield loss. Over the time, it contributes to stabilizing food and nutrition security as well as household income.

Similarly, water management-related CSA practices such as rainwater harvesting, water storage facilities, alternate wetting and drying, water release timetable, and sprinkle irrigation help improve water efficiency minimizing climate variability and vulnerability enhancing resilience. Drip irrigation is also one of the water management technologies, but majority of the household applies drip irrigation, so it is kept separate in consultation with experts and farmers.

3.2 Cost-benefit analysis of prioritized CSA practices in selected high-value crops

Cost-benefit analysis was conducted for 10 CSA practices—crop rotation, mixed cropping, precision nutrient management, polyhouse, water management, drip irrigation, water release timetable, permanent crops, and short-term crops from all selected high-value crops. The main indicators of CBA used in the evaluation are IRR, NPV, B/C ratio, and payback period. The findings confirmed the profitability and feasibility of these prioritized CSA practices across all three selected countries. A discount rate of 15.3% was applied for Nepal, 7% for India, and 14% for Sri Lanka reflecting the local bank interest rate and local lending interest rate for investment loans, which differ by country. These discount rates were collected from the respective central bank lending rates and prevailing commercial bank interest rates on agricultural investment loans in each country. The discount rate serves as the opportunity cost of capital and reflects the rate at which future costs and benefits are discounted to their present values. The payback period, representing the time needed to recover initial investment costs, ranged from 3.1 to 6.5 years for most practices; however, polyhouse and drip irrigation for cabbage have 7.14 and 18 years of payback period. This short duration encourages acceptability among smallholder farmers, enabling them to quickly repay loans while reaping investment profits. While calculating, the CBA costs related to implementation, maintenance, and operations of the CSA practices were incorporated and standardized to 1 hectare over 1 year.

3.2.1 Financial cost-benefit analysis

The study considered on-farm activities while calculating the CBA of the CSA practices within high-value crops across the three countries of South Asia. Costs and benefits were assessed using one hectare of land as the unit of analysis. Data for the business-as-usual (BAU) scenario, reflecting input and output values prior to CSA implementation, relied on recall data and insights from key informants in each country. Each CSA practice was evaluated over a specific time horizon of 15 years to make consistency throughout the CBA. The analysis excluded fixed costs such as land value or depreciation. All analyzed CSA practices had a positive NPV except drip irrigation for cabbage in India (NPV—251.82), indicating their benefits. Crop rotation in Nepal’s cauliflower had the highest NPV ($1464.39), following by bean ($881.77). The highest NPV values of drip irrigation in India’s capsicum and water management in tomato were $636.25 and $610.50, respectively. Similarly, in the case of Sri Lanka, water release timetable in mangoes had the highest NPV ($384) (Table 4). The internal rate of return (IRR) results also confirmed profitability as all values exceeded their respective discount rates except drip irrigation in India’s cabbage (−3%).

Crop rotation in Nepal’s bean had the highest IRR (44%) followed by crop rotation (42%) and mixed cropping (41%) in bitter gourd. Permanent crop in Sri Lanka’s mangoes and water release timetable in chilli had IRR 30 and 29%. Similarly, drip irrigation in India’s capsicum and water management in India’s tomatoes had IRR 29 and 28%, respectively. The IRR disparity between these practices may stem from different cash flow patterns; for example, drip irrigation in India’s cabbage had the negative NPV (−$251.82). Benefit-cost ratio of the practices ranges from 1.14 in crop rotation of Nepal’s cauliflower to 0.99 in drip irrigation of India’s cabbage. Most of the practices showed B/C ratio more than 1, exhibiting those benefits over the costs. The negative returns for cabbage are probably because of the high initial capital cost of drip irrigation infrastructure for low market value vegetables such as cabbage which reduce the actual revenue. In contrast, capsicum has a significantly higher market price and generates higher benefits leading to higher benefit-cost ratio even under the same installation cost structure.

In this study, the BCR values for several CSA practices were close to unity despite comparatively higher NPV and IRR estimates, and this pattern indicates the absolute scale of smallholder cost–benefit structures. Because BCR is a ratio of the present value of benefits to the present value of costs, while NPV is absolute surplus and IRR reflects the timing of returns, practices with modest total costs can show thin benefit-cost ratios alongside higher NPV, particularly where benefits are front-loaded relative to the project lifecycle. Among the CBA profitability indicators (NPV, IRR, and B/C ratio), NPV emerged as the most reliable measure for determining a practice’s feasibility. IRR and B/C ratios fit with scenarios of only option, whereas NPV works when comparing multiple alternatives (Akinya et al., 2022, Asfaw and Branca, 2018). IRR can sometimes produce higher than actual values that are hard to interpret quantitatively; for instance, high IRR figures in this study (Table 4) suggest future cash flows tied to CSA practices may be undervalued. Consequently, NPV is often favored over IRR as a profitability metric.

3.2.2 Economic CBA of the prioritized CSA

All CSA practices have external effects, which can be either beneficial or harmful. In this study, externalities encompass the social and environmental costs and benefits. Although the analysis primarily focused on private profitability, information of externalities related to CSA technologies was drawn from experts’ consultation and existing literature. These externalities include impacts on soil biodiversity, air quality, carbon sequestration, and social effects such as quality of life, reduce in outmigration, and women empowerment.

The implementation of CSA practices led to additional environmental and social benefits, as outlined in Table 5. Table 6 presents the estimated average values of these external benefits, based on contingent valuation model and willingness to pay (WTP) Method. Most of the CSA practices have the externalities of enhanced quality of life, women empowerment, and curbing outmigration. Incorporating the externalities into the cost-benefit analysis reveals significant variation in economic viability and social returns across crops. Externalities are measured in the unit of per household, per hectare, per household member, or per ton CO₂e, reflecting the differing scale at which each benefit accrues. To incorporate these heterogeneous values into the social net present value, each externality was first standardized to an annual value per hectare, household, and person-level values were converted using average household size and farm size for each study site before being discounted and added to the financial net benefit flow. In Nepal, precision nutrient management generated relatively high social net present values (SNPVs), especially for beans (USD 2,836.65) and cauliflower (USD 2,348.40), with moderate social internal rate of return (SIRR) ranging from 43 to 52% (Table 7). The inclusion of externalities such as improved air quality and enhanced quality of life further increased returns, pushing the NPV for beans up to USD 3,024.70. For improved air quality, the WTP is estimated 20 per household during the expert consultation. For a Ghana case study, Ng’ang’a et al. (2017) calculated this at USD 15 per hectare per year, highlighting how practices such as mulching, agroforestry, and minimum tillage reduce GHG emissions and enhance air quality.

Table 5. External effects generated by CSA practices across three countries.

Table 6. Externality valuation.

NB: HH = household, H = hectare; Person = individual household member; ton CO₂e = ton of CO₂ equivalent.

Table 7. Social NVP, social IRR, and social benefit-cost ratio of prioritized CSA practices.

Crop rotation in Nepal, especially when linked with soil biodiversity and greenhouse gas (GHG) emission reduction, also showed high effectiveness. Crop rotation with cauliflower demonstrated the highest SNPV (USD 3,492.95) across all practices indicating that environmental co-benefits significantly strengthen economic viability. Mixed cropping for bitter gourd and cauliflower showed both high SNPV (USD 2,088.51 and USD 2,741.84, respectively) and SIRR (91.00 and 57.45%) proved impactful especially when linked with gender empowerment suggesting that inclusive agricultural practices generate strong socio-economic outcomes. In India, drip irrigation showed higher SNPV, with tomatoes and capsicum (USD 2,024.80 and USD 1,846.54, respectively) and SIRR exceeding 80%, particularly when combined with women empowerment and curbing out-migration as key externalities. This practice had the highest IRR (95.08%) among all for tomatoes under the women empowerment externality indicating its potential scalability.

In India, water management seemed as another high-impact practice, particularly when combined with externalities such as GHG emission reduction and curbing out-migration. Tomatoes and cabbage under this practice recorded SNPV of USD 1,961.00 and USD 2,020.41, respectively, with SIRR more than 90%, demonstrating water management has high potential in both climate adaptation and mitigation contexts. The feasibility of polyhouse in India to curb out-migration had moderate returns (tomato SNPV: USD 1,585.15; SIRR: 71.17%), reflecting its relevance in weak socio-economic environments.

On the other hand, short-term crops of Sri Lanka with paddy gained comparatively good returns showing SNPV of just USD 387.07 and low SIRR (39.69%). Across all crops assessed, highlighting that these practices may require additional support or integration with other practices to be economically sustainable. Overall, practices such as drip irrigation, crop rotation, and water management not only provide high economic returns but also generate substantial social and environmental co-benefits. CSA practices linked to women empowerment, curbing out-migration, and GHG emission reduction increased both SNPV and SIRR, emphasizing the importance of integrating externalities into CSA program design. The findings offer strong evidence in investing in CSA practices that boost both productivity and social resilience in South Asia.

Among all the externalities, greenhouse gas emission resulting from the implementation of the CSA practices had the highest benefits in Sri Lanka, with an average of US$35/ton CO₂e per hectare per year. This was followed by social benefits linked to women empowerment and enhanced quality of life, averaging US$25 per hectare per year in India and Sri Lanka, respectively. Improved air quality, improved soil biodiversity, and curbing out-migration provided average benefits of US$20 per household, per hectare, and per person per year for Nepal and India, respectively. Improved air quality was primarily attributed to drip irrigation and precision nutrient management, while social benefits were mostly linked to water management, crop rotation, mixed cropping, and polyhouse. Table 7 outlines the social externality of CSA adoption, assessed through changes in labor requirements. Using survey data from the CBA, it was assumed that implementing and maintaining CSA practices across the three countries and selected high-value crops demanded extra labor.

The change in labor needs was multiplied by country-specific labor market prices to determine the value shift (Table 8). High labor demands, particularly during harvesting and threshing, were notable; in resource-limited households, this was often met with family labor, creating a trade-off with off-farm activities.

Table 8. Estimated impact on labor due to CSA practices.

Agricultural practices such as intercropping, crop rotation, and mixed cropping demand increased labor input, thereby creating additional employment opportunities particularly benefiting vulnerable local populations such as women and youth. As a result, these practices contribute positively to the social net present value and the social internal rate of return.

These findings show the similar results consistent with other literature studies, where CSA strategies typically increase labor value (Sain et al., 2017; Ng'ang'a et al., 2021; Neher, 2018). Notably, CSA practices with higher profitability (greater NPV) tended to be less labor-intensive. For instance, in Kenya’s sweet potato value chain, Good Agriculture Practices (NPV US$28,044) required less labor (83 man-days) than improved seeds (NPV US$8,738, 277 man-days), suggesting Good Agriculture Practices’ superior efficiency in financial and resource terms. Similar conclusions were drawn by Mutenje et al. (2019) in their research in cost-benefit analysis of CSA in Southern Africa.

3.2.3 Sensitivity analysis

Sensitivity analysis plays significant role in CSA evaluation as it stands apart from standard analysis by relying on scenario-based analysis. In the analysis of economic indicators for various crop rotations, the net present value (NPV) and benefit-cost ratio (BCR) evaluated as the discount rate increases. The three crops (beans, bitter gourd, and cauliflower) under the crop rotations from Nepal which have higher NPV were analyzed. Each crop’s economic viability was assessed over a range of discount rates from 3 to 30%. The results indicate that cauliflower had the higher NPV and BCR than other crops. Cauliflower had the NPV of US$4,200 per hectare, higher than beans at US$2,500 per hectare and bitter gourd at US$1,900 per hectare at a 3% discount rate. Generally, all crops’ NPV decreased as the discount rate increased, but cauliflower remained the most economically feasible option in Nepal, with a positive NPV US$1,200 per hectare even at a higher discount rate of 30%. The BC ratio also followed the same trend, where cauliflower had BC ratio of 1.22 and remaining above the break-even point of 1.0 across the analysis (Figure 3). However, both beans and bitter gourd had their BCRs decreased to approximately 1.00 at higher discount rates, exhibiting a diminishing economic return. This showed that while all three crop under rotations could be economically acceptable (BCR > 1), their profitability is highly dependent on the discount rate. If the discount rate is higher, it makes the investment in these CSA practices less attractive, especially for making a long term. The cauliflower appeared not only the most profitable but also the most sensitive to changes in financial conditions.

In India, water management for tomatoes and drip irrigation for capsicum showed higher NPV of approximately US$1,200 at lower discount rate of 1%, while cabbage showed the lowest returns of NPV US$300 at 10%. The narrow margin of BCR = 1 across all CSA practices suggests that these technologies are economically feasible, showcasing modest to highly sensitive to investment. This highlights the need for financial support policies and subsidies to scale up CSA adoption and sustainable CSA in India.

The sensitivity analysis of water release timetable for mangoes and chilli and mixed cropping for paddy was conducted with different discount rates (2 to 20%) to evaluate the economic performance of these CSA practices in Sri Lanka. Among these practices, the water release timetable for mangoes had the highest initial NPV of over US$1,400/ha at 2% discount rate but also sharply declined and reached to less than USD 200 at 20% discount rate, indicating highly sensitivity to financing conditions. Chilli, under the same practice, had moderate profitability of approximately US$800/ha whereas a BCR remained marginally above 1 even at higher discount rate of 20%. On the other hand, mixed cropping with paddy had the lowest NPV at all discount rates dropping below US$50/ha at 16% discount rate and a BCR that also went below 1, highlighting low financial feasibility under existing scenarios.

While selecting an appropriate discount rate, there is difficulty to reach on the consensus because some researchers suggest for lower discount rates, focusing the importance of environmental protection and sustainability (Akinyi et al., 2022; Sterner and Coria, 2012). They suggest on choosing the discount rate within a range of 1 and 5%. In contrast, other warn that selecting discount rate very low could misguide the private investment decisions and overemphasizing the future benefits of adaptation projects (Mendelsohn, 2012). However, in the context of CSA planning and addressing the climate risks, applying a lower discount rate may be more suitable that may encourage a policy shift from adaptation efforts toward mitigation strategies.

3.2.4 Real option analysis

Black–Scholes real option analysis was applied to assess investment in CSA under uncertainty to facilitate the farmers to make a decision on which option can be delayed, adapted, expanded, or abandoned while more information is available. It is in contrary with a traditional CBA which provides a certain picture of whether to adapt or not. ROA considers flexibility particularly in the case of unpredictable climate, policy, and market condition. Figure 4 shows the social option value (SOV) of several CSA practices applying the real option analysis framework. This approach captures not only the static net benefits of an investment (as in traditional net present value models) but also the added value of flexibility under uncertainty which is a critical consideration in the context of climate change.

Precision nutrient management shows the highest social option value ($4,889), followed by crop rotation ($4,635) and mixed cropping ($3,979). These practices offer not only strong social returns but also greater strategic adaptability, making them attractive options for long-term investment. Mid-tier practices such as drip irrigation, water management, and polyhouse farming also demonstrate considerable option value, although to a lesser extent. Lower-ranked options such as short-term crops and mixed cropping SL (Sri Lanka) have modest option values, suggesting limited but context-specific utility.

This highlights the importance of incorporating uncertainty into decision-making frameworks. By accounting for future variability in costs, benefits, and climate risks, ROA helps prioritize CSA interventions that maximize both economic efficiency and resilience.

Figure 4 shows the comparative social option value of selected high-value CSA practices, derived from a Black–Scholes real option analysis (ROA) framework. This approach takes into consideration of investment flexibility and future uncertainty critical factors under climate variability. The bars represent the estimated social option value for each practice estimated time span from year 1 to 5, depending on the practice life with error bars indicating uncertainty in valuation. CSA interventions such as crop rotation, precision nutrient management, and mixed cropping are not only economically viable but also resilient and adaptable under uncertain and changing climate conditions. Practices with moderate or low option values may still be beneficial in specific ecological or socio-economic contexts but may require more specific support or risk mitigation strategies.

4 Discussion

This study comprehensively evaluated the economic feasibility of prioritized high-value climate-smart agriculture (CSA) practices applying cost-benefit analysis, externality valuation, sensitivity analysis, and real option analysis. The results highlight the economic viability and potential of CSA practices across diverse agroecological zones in Nepal, India, and Sri Lanka. Several studies have worked on prioritization within climate change adaptation; however, few studies have thoroughly assessed the financial and economic costs over benefits of the selected CSA practices (Sain et al., 2017; World Bank, 2022a,b). This research extends beyond prioritization by applying two decision-making tools across high-value agricultural crops in three south Asian countries. The CSA-PF tool was first used to pinpoint top climate-smart agriculture (CSA) technologies, ranked by their features to enhance productivity, resilience, and mitigation benefits (CIAT, 2015). Additionally, the study conducted household surveys in 2024 in all selected sites of three countries. Most CSA studies have focused on a single country, a single practice, or a single analytical tool (Khatri-Chhetri et al., 2017; Ng'ang'a et al., 2021). This study provides a more comprehensive and replicable evidence base by applying CSA-PF, financial CBA, externality valuation, and real option analysis simultaneously across three countries and multiple high-value crops. This is imperative because while making a CSA investments, there is a trade-off between private profitability, social equity, and environmental externalities that single-tool approaches cannot be justifiable. The multi-country, multi-crop analysis also provides cross-contextual learning: Practices that perform well across Nepal’s subtropical Terai, India’s humid sub-mountain zone, and Sri Lanka’s tropical dry lowlands are more likely to be robust CSA options than those validated in a single country context.

Then, a CBA tool developed by the International Centre for Tropical Agriculture (CIAT) was adopted to evaluate the economic viability and efficiency of these prioritized CSA strategies, focusing on indicators such as NPV, IRR, B/C ratio, and payback period (Sain et al., 2017). CBA results showed practices such as crop rotation, mixed cropping, and precision nutrient management positive net present values and internal rates of return across several high-value crops. These practices showed particularly successful in Nepal, where the integration of soil health, biodiversity, and input-use efficiency directly improved yields and household incomes. The findings from Nepal of the high return of low-input practices are consistent with the findings from Sain et al. (2017) in Guatemala and Ng'ang'a et al. (2021) in Ghana, where agricultural practices with minimum capital requirements have higher return than high capital and infrastructure interventions in resource-constrained smallholder contexts. Nepal’s fertile Terai soils and inherited crop diversification culture also lower the adoption barrier, making practices such as precision nutrient management particularly impactful (Tiemann et al., 2015). In India, capital-intensive practices such as drip irrigation and water management had strong financial returns and short payback periods, especially when applied to crops such as capsicum and tomatoes (World Bank, 2022a,b) which reflects high-value crops such as capsicum has higher market value comparing to other vegetables that may generate large revenue even modest yield gains from water management. In Sri Lanka, the CSA practices demonstrated moderate returns, with permanent crops and water release timetable contributing to long-term sustainability. Sri Lanka’s moderate and variable returns reflect the dual challenge of bimodal rainfall seasonality and long payback periods for perennial investments factors that reduce the net present value of benefits discounted at commercial rates, even when the undiscounted benefit stream is positive.

When externalities such as women empowerment, GHG reduction, and biodiversity conservation were included, the social net present value (SNPV) and social internal rate of return (SIRR) increased significantly sometimes by over 100%. This demonstrates that CSA practices are not only profitable from a private perspective but also generate substantial public benefits. CSA strategies require more labor create jobs, particularly for vulnerable groups such as youth and women. While this may increase costs for farmers (a welfare loss), it benefits society through employment gains (FAO, 2021). These effects are prominent and economically significant, but they are often excluded from farm-level investment decisions because individual farmers have no financial incentive to considering them. The finding that women’s empowerment externalities show the highest SIRR in the study further highlights that gender equity is not only an externality of CSA, it is rather a primary economic rationale for investment and should be at the center of CSA program design across South Asia (Khatri-Chhetri et al., 2020; Dabral et al., 2025).

The sensitivity analysis for Nepal indicates that all three crop rotation systems, such as beans, bitter gourd, and cauliflower, are economically viable at low-to-moderate discount rates as their benefit-cost ratios (BCRs) remain above 1. Net present value (NPV) declines with increasing discount rates across all crops, with cauliflower showing the highest initial returns but also the greatest sensitivity to rate changes. Beans and bitter gourd exhibit more stable BCRs, suggesting relatively better resilience under varying economic conditions. These findings highlight the importance of selecting the right crop rotations for maximizing economic returns, particularly in the face of increasing discount rates. The analysis suggests that cauliflower is the most resilient option, providing a more stable economic return compared to beans and bitter gourd. This information can guide farmers and agricultural planners in making informed decisions about crop selection to optimize profitability.

The sensitivity analysis for India examines the economic performance of three climate-smart agriculture interventions water management in tomato and cabbage cultivation, and drip irrigation for capsicum across a range of discount rates (1–10%). Across all cases, net present value (NPV) declines as the discount rate increases, while the benefit-cost ratio (BCR) remains only slightly above 1, showing minimal sensitivity. Two CSA practices with different crops, such as water management for tomato and cabbage, and drip irrigation for capsicum which had higher NPV in the CBA analysis, were chosen for the sensitivity analysis for India by changing the discount rate. Across two CSA practices, NPV decreased as the discount rate increased, indicating reduced long-term profitability with higher opportunity costs of capital. Similarly, BCR slightly decreased and remained above 1, suggesting that the CSA practices remain economically feasible even at higher discount rates. The small variation in BCRs from 1.012 to 1.028 depicts low sensitivity and sustainable cost-effectiveness, emphasizing the worthiness of these CSA practices for climate adaptation in India’s agricultural sector (World Bank, 2022a,b).

A BCR close to 1 indicates economic viability, but also sensitivity of the practices with any increase in input costs, decline in output prices, or adverse weather shock could bring these practices below break-even. This shows that water management practices in India require policy support such as crop insurance, or input subsidies to resist the price volatility and climate variability. The contrast with Nepal’s crop rotation systems, which has BC ratio above 1 across the full discount rate range, indicates the resilience of low-input, diversification-based practices than infrastructure-based water management. This is consistent with the other CSA research suggesting that agricultural practices yield higher than capital-intensive interventions on risk-adjusted returns in smallholder contexts (Sain et al., 2017; Ng'ang'a et al., 2021). In Sri Lanka, the NPV decline with rising discount rates for water management in mango and chilli combined with BC ratio falling below 1 for mixed paddy cropping demonstrates a structural constraint: The bimodal rainfall pattern (Maha and Yala seasons) concentrates cash flows in short windows, while high investment costs are spread over multi-year payback periods. Smallholders in Anuradhapura may face an affordability constraint without access to lower rates credit as the financial returns alone cannot overcome these barriers, irrespective of the positive social or environmental externalities.

Real option analysis assessed the flexibility under uncertainty which is often overlooked in conventional evaluations. The highest social option values (SOVs) were found in crop rotation, precision nutrient management, and mixed cropping, confirming their importance in long-term investment planning under climate variability and market fluctuations (Ng'ang'a et al., 2021). The option to delay, adapt, or expand the CSA investments provides additional information for both farmers and policymakers in uncertain climates.

The ranking of CSA practices such as crop rotation, precision nutrient management, and mixed cropping in the ROA analysis is practically significant. In the Black–Scholes model, social option value is determined by two key parameters: the expected social net benefit and the volatility. Practices such as crop rotation and PNM generate high SOVs because farmers have adopted these practices for a long time and have flexibility of adjusting species composition, input rates, and rotation sequences in response to changing rainfall patterns, pest pressure, or market prices without incurring substantial switching costs. This flexibility has a real economic value under changing climate that static NPV analysis fails to capture. In contrast, capital-demand practices such as drip irrigation and polyhouse have lower SOVs even when sometimes higher financial NPVs. Once these technologies are installed, farmers do not have other option value of waiting or adapting. This distinction between the value of flexibility and expected-value maximization has important policy implications.

5 Limitations

This study is not without limitations. First, the sampling design was purposive rather than random sampling, targeting smallholder farmers who have already adopted CSA practices at the selected sites. This approach was necessary where CSA adopters in Nepal, India, and Sri Lanka were unknown. The minimum sample size (68) was calculated using the Raosoft software, assuming an unknown population size and a 90% confidence interval for each country. To strengthen robustness, 100 households were surveyed per country. However, this relatively small sample limits the precision of country-level estimates and the extent to which findings can be generalized beyond the specific study sites and crop value chains examined. Second, the shadow prices were applied uniformly within each country rather than varying by household characteristics. Similarly, the Black–Scholes-based real option values rely on assumptions of log-normal returns and constant volatility that are conventional in financial option pricing but only an approximation of the more complex stochastic processes governing agricultural yields and climate risk. Future research could strengthen this finding by using random or stratified sampling frames alongside alternative stochastic models could better capture the heterogeneity and discrete climate shocks that the Black–Scholes framework assumes away.

6 Conclusion and policy recommendation

Climate change adaptation is not limited to only discipline rather it is interdisciplinary, demanding collaboration across sectors. As South Asia’s agricultural sector is one of the vulnerable sectors to climate change, adaptation is a critical response. Prioritization of the CSA practices plays a key role to choose the best options that are low-cost, highly productive, less GHG emission, and socially and technically feasible.

CBA analysis emphasizes their practicality, especially for resource-constrained smallholder farmers, helping them to take informed decisions to increase profitability. A clear identification and categorization of CSA options are thus essential. CSA practices such as precision nutrient management, crop rotation, and water-efficient technologies (e.g., drip irrigation) seem as economically viable, scalable, and resilient options. The study also highlights the importance of location and context-specific prioritization, participatory decision-making, and the integration of social and environmental co-benefits while evaluating CSA strategies.

The sensitivity analysis across Nepal, India, and Sri Lanka reveals both the economic viability and relative resilience of various climate-smart agricultural interventions under different discount rate scenarios. In Nepal, crop rotation systems particularly with cauliflower, beans, and bitter gourd seem economically viable at moderate discount rates, with cauliflower having the highest NPV but also showing the greatest sensitivity. In India, water management practices applied to tomato and capsicum show BCRs above 1.01, indicating modest profitability and lower sensitivity to discount rate. However, cabbage shows lower BCR and negative NPV. This suggests practical implications for farmers and policymakers. For farmers, the divergence between drip irrigation’s negative return for cabbage (NPV = –US$251.82, BCR = 0.99) and its viability for capsicum under an identical cost structure highlights the central role of crop value in determining the returns to capital-intensive technologies. From a policy perspective, the narrow BCR margins found in the sensitivity analysis suggest modest, targeted subsidies could push marginal practices above viability, while the cabbage case shows subsidies alone cannot resolve structural crop-technology mismatch and underscoring the need for complementary agronomic and extension support. In contrary, Sri Lanka has greater variability, with water management for mango and chilli exhibiting high returns in the beginning but NPV declines rapidly as discount rates increase. The mixed cropping system with paddy, however, displays low and diminishing returns, with BCRs falling below 1 raising concerns about its economic feasibility without additional support. Together, these findings emphasize the need for spatial and context-specific financial planning and policy support to ensure long-term sustainability and expansion of climate-smart agriculture practices across South Asia.

These results highlight that while water management interventions in perennial and high-value crops such as mango and chilli can be economically attractive, their feasibility is contingent on access to affordable financing. Meanwhile, the viability of mixed paddy systems appears limited unless supported by targeted subsidies or cost-reduction strategy.

Adaptation strategies are context-dependent, varying by region. Localized solutions are vital, for example, seasonal weather forecasts can inform decision-making. Integrated approaches that optimize resource allocation can drive economic growth and environmental sustainability. Planning should assess the needs of all sectors and stakeholders tied to agriculture, adaptation, and mitigation. To sustain agricultural systems, interventions should prioritize climate-smart, resilient practices, such as selecting appropriate crop varieties or systems, to maximize productivity.

While assessing the economic value of the CSA practices, incorporation of social and environmental externalities such as biodiversity conservation, women’s empowerment, and curbing out-migration can justify greater public investment and support for long-term sustainability. This study revealed that when externalities were included, the SNPV of crop rotation in Nepal increased to USD 3,492.94 (SIRR 46.47%) and precision nutrient management reached USD 3,024.70 (SIRR 56.24%), higher than private NPV. Therefore, policymakers should encourage the use of social cost-benefit analysis rather than financial CBA alone in evaluating public investments in CSA programs. Similarly, design CSA programs that enhance the meaningful participation of women and marginalized groups, recognizing their critical role in farm decision-making and resilience building can enable inclusiveness in the agriculture sector. The finding depicts that drip irrigation in India showed the highest SIRR (95.08%) incorporating women empowerment and out-migration curbing externalities and highlights the need for gender-sensitive extension and training programs. Another important aspect is governments should consider using lower discount rates (e.g., 3–5%) in CSA project evaluations to adequately reflect long-term environmental and social benefits, particularly for adaptation and resilience-building investments. The sensitivity analysis in this study demonstrates that all CSA practices in Nepal were economically viable (BCR > 1) at discount rates up to 15%, while Sri Lanka’s water management for mango showed rapid NPV decline beyond moderate discount rates reinforcing the need for lower public discount rates when assessing long-term CSA investments in risk-prone areas. Capital-intensive resource-conserving technologies require government pricing reform, targeted subsidies, and technical support to be financially viable for smallholders (Reddy, 2021).

Real option analysis reinforces the value of strategic flexibility allowing for investment, deferral, or abandonment based on evolving information which is essential in the face of climate uncertainty. This offers a powerful tool to guide adaptive planning in agriculture.

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Footnotes

Edited by: Steven Van Passel, University of Antwerp, Belgium

Reviewed by: A. Amarender Reddy, National Institute of Agricultural Extension Management (MANAGE), India

Pardeep Singh, National Institute for Agricultural Economics and Policy Research (NIAP), India

Hena Parween, Bihar Agricultural University, India