A Farmer-Centric Cost–Benefit Analysis of Climate-Smart Agriculture in the Gandaki River Basin of Nepal

Abstract

Climate-smart agriculture (CSA) is a climate-resilient practice that stands out globally as an important practice through which we can deal with emerging challenges through adaptation and mitigation to increase crop productivity and resilience. Despite its significance, a comprehensive cost–benefit analysis of the adoption of these practices has not yet been carried out. This study aims to bridge the knowledge gap between the cost and effectiveness of CSA practices adopted by small-scale farmers in growing rice, wheat and maize, the most staple crops in the Gandaki River Basin of Nepal. In this study, net present value (NPV), internal rate of return (IRR), benefit–cost (BC) ratio, net benefit investment (NK) ratio and payback period, along with the value of externalities (social and environmental), were employed to assess the profitability of CSA practices. The findings indicate that almost all the CSA practices analyzed were profitable, with the exception of solar water management in maize with very low IRR (6%) and a longer payback period. The outcome of this study offers valuable insights for farmers in choosing profitable CSA technology and for policy makers in promoting better CSA technology, upscaling CSA practices, and formulating new agricultural policies and programs in the context of the changing climate.

1. Introduction

The world is facing the consequences of climate change in various ways. The increase in temperature, unevenly distributed precipitation, flood, landslides, and drought spells have created a change in agricultural patterns [1,2]. Additionally, these events have resulted in crop failures, exacerbating food and livelihood insecurity, amplifying water shortages, and increasing the likelihood of poverty [2,3]. Although there might be several factors influencing the fluctuating yield, climate change is considered a major one [4,5]. The changing climate has brought massive challenges for smallholder farmers who rely on rain-fed agriculture. Projections indicate that under the prevailing conditions, climate change is expected to lead to a decline in rain-fed maize yield, ranging from 3.3% to 6.4% by the year 2030 and 5.2% to 12.2% by 2050. Similarly, for irrigated maize yield, the decrease in yield is projected to be between 3% and 8% in 2030 and 5% and 14% in 2050, based on the cultivation of current varieties in South Asia [6]. In Nepal, the impact of climate change (CC) is anticipated to have the most pronounced negative effects on yield levels for maize, potato, sugarcane, and lentils. These crop yields are expected to decrease by 16.1%, 8.9%, 8.0%, and 4.9%, respectively, under CC conditions compared to a scenario without climate change (NoCC) by 2050. Additionally, rice and vegetable yields are also expected to be lower under CC compared to NoCC, but the projected differences are relatively small, at −0.4% and −0.1%, respectively. The sustainability of rain-fed agricultural production systems may be jeopardized if we stay with business as usual (BAU) in the context of climate change. A sound policy recommendation for addressing the challenges posed by climate change involves promoting the adoption of climate-smart agriculture (CSA) practices as a means of adaptation. The Food and Agricultural Organization (FAO) of the United Nations defines CSA as a strategy through which to address the challenges of climate change and food security by sustainably increasing productivity, bolstering resilience, reducing GHG emissions, and enhancing achievement of national food security and development goals [7]. Adaptation, mitigation, and food security are the three pillars of CSA.

In Nepal, few villages from different ecological zones (Bardiya, Dang, Rupandehi, Nawalparasi, Gorkha, and Mahottari districts) have implemented CSA practices, which are vulnerable to changing climate and its possible effects. A study by Khatri-Chettri [8] on the benefits of implementing the CSA practices (including both experimental and in-field research) across South Asia revealed that the use of nutrient-supply- and irrigation-related technologies in rice led to an 83% and 23% increase in yield, respectively. Similarly, another study on the use of different irrigation-related CSA practices in winter maize reported an increased yield and significant improvement in the growth parameters [9]. Several studies suggest that the CSA practices could prove advantageous, but at the same time, the profitability of using different CSA practices in major crops grown by smallholder farmers needs to be ascertained. Therefore, by assessing the costs and benefits of agricultural investments, farmers and investors can adjust their decisions and prioritize the most effective techniques for successful adaptation [10]. The cost–benefit analysis (i) evaluates the impact of adopting specific CSA practices over time, providing farmers with information on the profitability of securing the necessary capital for the successful implementation and maintenance of CSA practices until profits are realized, and (ii) advises smallholder farmers on the potential of CSA practices to yield a return on invested capital. Assessment of CSA practices via discounted measures like net present value (NPV) and internal rate of return (IRR) not only provides a basis for choosing the most profitable practice but also indicates which practice should be chosen, considering long-term investment.

Similarly, a study reported that certain agricultural practices have a greater capacity to reduce greenhouse gas emissions (such as through carbon sequestration), enhance food security (for instance, by increasing productivity), and consequently contribute to the sustainability of the livelihoods of households [11]. CSA has the potential to provide environmental advantages that assist households in adapting to the impacts of climate change and variability [12]. The strategic selection of CSA practices plays a pivotal role in maximizing benefits while minimizing costs. However, this selection relies significantly on how farmers perceive these benefits. The farmers’ perception of these benefits is a crucial factor influencing their decisions regarding acquiring loans for investing in new technologies [13]. Therefore, the implementation of cost–benefit analysis (CBA) becomes imperative, offering farmers crucial insights into the anticipated benefits of investing in specific CSA practices. By comparing these benefits with the associated costs, smallholder farmers can determine the time frame required to reach a break-even point.

In this light, this research aims to determine the major costs and benefits of adopting chosen CSA practices; carry out a profitability assessment of practices using net present value, payback period, IRR, B/C ratio and NK ratio; determine the value of social and environmental externalities created by the CSA practices; and include the estimated value of those externalities in the cost–benefit analysis of the different CSA practices in major cereal crops. This study focuses on evaluating six CSA practices that smallholder farmers in the Gandaki River Basin of Nepal consider to have the most substantial impact on food security, productivity, and mitigation. As farmers bear the investment costs and directly experience the economic benefits of adopting CSA practices, the analysis presented in this paper adopts a farmer-centric viewpoint rather than a public one. The primary objectives of this paper include

• Prioritization of the implemented CSA practices;
• Evaluation of the costs and benefits associated with adopting six CSA practices recognized as climate-smart;
• Estimation of the value of externalities linked to the implementation of these six CSA practices.

This study covers an important research gap that exists in the financial and externality assessment of CSA practices, along with a valuation of the externalities created by the CSA practices. The findings from this study can be a great asset to cereal growers in the regions of Gandaki River Basin as they choose appropriate CSA practices for sustainable farming systems in the context of the changing climate, and they will also help policy makers to prioritize the CSA practices in their program that are financially sound and will create welfare for society and the environment. However, this study has some limitations. It relies on the existing literature to gather additional evidence on the valuation of externalities associated with CSA practices. Furthermore, due to a lack of comprehensive data or minimal impact, the study was unable to assess the value generated by reducing soil and water contamination through certain CSA practices. Lastly, the small landholding size of cereal producers in the region constrained the calculation of the carbon balance, which was excluded from this analysis.

The structure of this paper is outlined as follows: Section 2 provides an overview of the study, detailing the selection and ranking process of the six climate-smart agriculture (CSA) practices, along with an explanation of data collection and analysis methods. Section 3 presents the key findings of the study and their discussion, and Section 4 includes our conclusions and policy recommendations.

2. Research Methods

2.1. Conceptual Framework

The conceptual framework of the study is shown in Figure 1 below. CSA encompasses smart practices in terms of energy, knowledge and nutrition [14]. These practices can help in adaptation to and mitigation of climate change stress and play a significant role in ensuring food security [5].

In this study, economically efficient CSA practices that are financially sound and produce high-value externalities were determined. The adoption of such CSA practices can have a twofold effect—increased productivity and income (i.e., the welfare effect) and decreased emission of greenhouse gases through upscaling of these practices.

2.2. Study Area

In Nepal, CSA practices have been implemented in selected villages from different ecological zones of the Gandaki River Basin with the support of the Consultative Group for International Agriculture Research (CGIAR) and coordination with different partners [15]. The pilot study is being carried out in six districts: Bardiya, Dang, Rupandehi, Nawlapur (formerly Nawalparasi), Gorkha, and Mahottari. These selected villages are vulnerable to changing climate and its impacts [15]. For our study, we have chosen the Nawalpur district (Figure 2).

It is situated in Gandaki Province of Nepal centered at 27.32° N longitude and 83.40° E latitude. The district has a total population of 310,864 [16]. The altitudes vary from 91 m to 1936 m above mean sea level. Nawalpur is characterized by its tropical and sub-tropical climate zone. About half of the district is mainly populated by Brahmins, Magar, and Chhetri communities, while the Terai region is mainly populated by the Tharu community. The major occupation of the people in the district is farming. Nawalpur is a district vulnerable to the threats of the climate change [17], and it has relatively accessible sites in order to keep track of the agricultural farms. Furthermore, the future climate analog (2030), upon verification and evaluation at the Nawalpur site, has shown that the CSA areas for paddy and wheat will be appropriate for 1197 thousand hectares and 550 thousand hectares of land, respectively, across the country [8], which explains the rationale behind choosing the site.

2.3. Prioritization and Selection of CSA Practices

The CSA prioritization framework (CSA-PF) method involves consultation with experts and discussion with farmers and stakeholders to ascertain CSA practices and investment profiles. Farmers, agriculture officers and stakeholders of NGOs associated with climate-smart agriculture practices in the study sites were included in the CSA-PF process. The CSA-PF process encompassed the following steps: (a) in the first step, validation of the main farm typologies was carried out, as mentioned by [18]; (b) only small-scale subsistence cereal-growing farmers (referring to farmers with a small landholding size of less than 0.55 hectares) were selected [16]; (c) a list of existing and new CSA practices (specifically productivity, resilience, and low-emission development) that are adaptable to the varied typologies of the farms was made through focus group discussions with farmers and experts; (d) the listed practices were evaluated using the indicators in the CSA goals of productivity, resilience, and low-emission development. The major aim of the third step was to finally derive a shortlist which included the most applied and interested CSA practices for each type of farm; (e) we identified the most intriguing and applied practices prioritized by both farmers and experts; and (f) finally, we carried out an in-depth survey of farm households for the chosen CSA practices. In a nutshell, the first four steps involved 16 practices, among which only 6 practices were critically shortlisted in the priority ranking of CSA goals for CBA analysis. This paper specifically delves into the outcomes of step (d), conducting a comprehensive profitability assessment of the six high-priority CSA practices.

2.4. Data Collection

A structured questionnaire was prepared for the purpose of household survey data collection. The questionnaire aimed to obtain information on (1) general information about the study area; (2) the socio-economic characteristics and farming experience of household head; (3) field activities (no intervention); (4) adopted climate-smart practices; (5) yield, prices, inputs and costs of implementation of the practices (both before and after intervention); (7) household financial data; and (8) socio-economic and environmental impacts. Purposive sampling was carried out within the district, and a total of 100 farmers were selected who had practiced at least one of the six CSA practices in their farms for a period of at least two to five years (

Table 1. Distribution of the households by CSA practices and types of crops in Nawalpur (N = 100).

Farm Practice	Crops Grown in a Calendar Year	Number of Respondents
Conventional Agriculture Practice (CAP)	Rice	100 (100)
	Maize	93 (93)
	Wheat	20 (20)
Climate-Smart Agriculture Practices
Jab planter	Rice	N/A
	Maize	58 (62.36)
	Wheat	N/A
Improved seeds (Local seeds)	Rice	27 (27)
	Maize	35 (37.63)
	Wheat	4 (20)
Solar water management	Rice	36 (36)
	Maize	49 (52.68)
	Wheat	4 (20)
Biopesticides	Rice	2 (2)
	Maize	5 (5.37)
	Wheat	N/A
Organic fertilizers	Rice	1 (1)
	Maize	2 (2.15)
	Wheat	N/A
Zero tillage	Rice	N/A
	Maize	N/A
	Wheat	10 (50)

Note: Figures in parentheses are the relative percentages of respondents. N/A means not applicable due to non-adoption of the particular practice.

).

Prior to the data collection, two enumerators were given training on questionnaire management, translation, and recording of the farm location and responses. Pre-testing of questionnaire was carried out by the enumerators, which was used to gain their preliminary experiences along with translation. All clandestine issues were found out and resolved. Prior to the survey, verbal consent was obtained from the respondents, ensuring that the collected data would only be used for the research purpose and would not be shared anywhere else. In each household, the household head was preferred for the interview. However, in their absence/inability to take part, we chose another member (>20 years old) of the farm household who had been farming for at least five years. In this study area, almost all of the CSA practices were observed to have been implemented recently (i.e., their adoption took place with uneven frequency from 2015 to 2019).

Conventional agriculture practice (CAP) refers to the farmers who had not applied any CSA practice in their field and were working under business-as-usual conditions before implementing CSA practices (i.e., before 2015). The same farmers before 2015 who were classified as CAP farmers were CSA farmers, provided they adopted at least one of the practices. From Table 1, it can be observed that not all (100) farmers adopted CSA practices. The cropping system of farmers in the study area for cereals was R-W-M (rice–wheat–maize) in a calendar year, and hence it is possible that farmers grew rice, rice–maize, rice–wheat, maize–wheat or rice–wheat–maize; accordingly, the number of farmers growing particular crops were different. In the case of farmers adopting CSA practices, not all practices were applicable to all crops, and not all farmers adopted the particular CSA practices for that particular crop. For instance, jab planters are applicable to maize, and zero tillage is applicable to wheat only in this study area.

2.5. The Cost–Benefit Analysis Model

The CBA approach has a blended character of ex-ante and ex-post evaluation. It is an ex-post evaluation in a sense that practices were fostered and applied by the farmers, and ex-ante because their impact on yields or ecosystem services is not yet apparent, considering the span of the implemented practices. CBA is widely chosen for the evaluation of the benefits of expenditures in different sectors [19]. In this paper, the individual profitability of implementing CSA practices, i.e., the profitability for farmers who are implementing the practice, is determined by the CBA approach. The different CSA practices were appraised in terms of their relative profitability using the CBA approach, i.e., by comparing the differences between them in terms of the varying benefits and costs during the entire period of implementation. The cost incurred for the CAP was taken as the cost borne by the farmers for their regular agricultural activities prior to implementing the CSA practices. The cost incurred in adopting the CSA practices included the cost of the adoption, implementation, and maintenance of a given activity (per hectare of farmland). Thus, the calculations involve adoption, implementation and maintenance of the practices on a per-hectare basis, although farmers may have many activities taking place in an area of less than a hectare. Two popular discounted measures of CBA, (i.e., net present value (NPV) and internal rate of return (IRR) [20]) along with assessment of B/C ratio, net benefit investment ratio (NK ratio) and payback period (PBP) were applied for practices in rice, wheat and maize. Assessment of the individual profitability values can be determined by NPV, IRR, B/C ratio, NK ratio and the non-discounted measure; PBP (Formulas (1)–(5)) per hectare (ha) under CAP and CSA practices [21]. The comprehensive and multifaceted analysis of investment opportunities offers unique insights, and collectively, such insights ensure a thorough assessment of the financial viability and strategic value of the CSA practice under consideration.

$$\mathrm{NPV}={\sum }_{t=1}^n{\displaystyle \frac{B_t-C_t}{{(1+i)}^t}}$$

(1)

where NPV = net present value of implementing the CSA practice;

• B_t = incremental benefit of the CSA practice in the t^th period;
• C_t = incremental cost of the CSA practice in the t^th period;
• n = number of years;
• i = interest (discount) rate (%).

The NPV is defined as the summation of the present value of incremental net benefit over the time period considered [21]. The nature and description of the variables used for calculation of NPV is described in

Table 2. Variables used in the NPV model for CBA.

Variable	Nature	Description
Cost of CSA practice (installation, operation and maintenance)	Random	A random character of the cost is assumed so as to capture the differences in production technology amid the farms in the study area
Price of the crops	Non-random	The data from survey showed minimal variation in prices of the cereal crops (expressed in USD) across the farms
Crop yield response	Random	The magnitude of the impact of implementing the CSA practice can be measured by the crop yield response
Time horizon, time response parameters (t1 and t2), and discount rate	Non-random	A specific feature of the practice defines the time horizon of the analysis

Note: Random means values can vary unpredictably due to inherent uncertainty, variability in data, or differences in conditions. Non-random means values are fixed or exhibit minimal variation within the context of the study, often because they are controlled or standardized across the analysis.

. The respective values used in the classical equation were determined using MS Excel and used to obtain the average NPV.

$$\mathrm{IRR}=\mathrm{LDR}+\Delta \mathrm{DR} \ast {\displaystyle \frac{NPV at LDR}{\sum PV of INB at two DR }}$$

(2)

or the value of interest rate (i) at which NPV = 0.

Where LDR = lower discount rate; ΔDR = difference between discount rates; and INB = incremental net benefit.

The other indicator, IRR, can be defined as the interest rate that makes NPV zero, i.e., that which makes the present value of incremental net benefit zero. Unlike NPV, the cost of capital (interest rate) need not be specified for the calculation of IRR. Upon calculation, it can be used as a yardstick for different probable values, and can thus be used to ascertain the profitability of diverse cases. A greater IRR (more than the discount rate) suggests a profitable investment.

The discounted B/C ratio and NK ratio were used to validate the profitability of different CSA practices. The discounted B/C ratio was estimated by dividing the present value of incremental benefit with the present value of incremental cost. A B/C ratio of greater than 1 is considered profitable.

$$\mathrm{B}/\mathrm{C} \mathrm{ratio}={\displaystyle \frac{\sum _{t=1}^n\frac{B_t}{{(1+i)}^t}}{\sum _{t=1}^n\frac{C_t}{{(1+i)}^t}}}$$

(3)

where

• B/C = benefit–cost ratio of the CSA practice;
• B_t = incremental benefit of the CSA practice in the t^th period;
• C_t = incremental cost of the CSA practice in the t^th period;
• n = number of years;
• i = interest (discount) rate (%).

Similarly, an NK ratio of more than 1 is considered profitable for a business. It is the ratio of the sum of the positive value of incremental net benefit to the absolute negative value of incremental net benefit during the period considered [21].

$$\mathrm{NK} \mathrm{ratio}={\displaystyle \frac{sum of the incremental net benefit with positive value}{|sum of the incremental net benefit with negative values|}}$$

(4)

The payback period (PBP) refers to the time needed to recover the initial investment.

$$\mathrm{PBP}=\mathrm{E}+{\displaystyle \frac{B}{C}}$$

(5)

where

• PBP = payback period for implementing the CSA practice;
• E = year immediately preceding the year of recovery;
• B = amount left to be recovered;
• C = cash flow during the final year of recovery.

We used the average values of the farm for the calculation of NPV, IRR, B/C ratio, and NK ratio. Furthermore, we considered a time period of 25 years for NPV, IRR, discounted B/C, and NK ratio estimation and kept the discount rate at 12% (representing the opportunity cost of capital affecting banks and financial organizations) on the basis of data obtained from farm households and considering the bank interest rate during the time period. The calculation was performed using different functions and formulas available in MS Excel. Each of these values were obtained from the individual farmers, and ultimately, the average values of each of the indicators were assessed. In order to represent the statistical variation present within the calculation of NPV, IRR, B/C ratio, and N/K ratio, standard deviations were assessed.

2.6. Crop Yield Response to Adoption of CSA

CSA emphasizes systems in agriculture that bolster the ecosystem services in a sustainable manner [22]. We presumed that the CSA practices would mostly enrich soil nutrient status, decrease soil erosion, and decrease water shortage due to proper management of irrigation in the field, so as to exhibit the impact of CSA practices on productivity of crops [23]. CSA practices in association with their aftermath have a subsidiary effect on productivity through enriched soil nutrient status [24].

Thus, the considerably longer time required for the yield response of the crops could be attributed to the preliminary soil destruction and other issues relating to soil characteristics. In order to build a proper model for the physical response pattern of crop yields after implementing CSA practices, we assume that the curve of response takes the form of a linear plateau preceded by a lag amid the implementation of the practices and the onset of yield response, as shown in Figure 3.

Figure 3 represents a production function [25] popularly used to demonstrate the biological process on par with the Liebig’s law of the minimum. The discrepancy between Time 1 (t1) and Time 0 (t0) refers to the response lag. Similarly, Y_f is the highest possible increment in yield associated with the adoption of a CSA practice, and T refers to the entire time for which the practice is implemented. From the response survey among the farmers practicing CSA, both the yield response and maximum yield attainment took one year. T symbolizes the complete lifecycle of the practice, with the y-axis denoting productivity in quintal per hectare and the x-axis representing time in years.

The underlying principle of the Liebig production function is that at any given moment, only one factor, considered to be in minimal supply, constrains production (such as the level of nitrogen (N) in the soil) [26]. If the supply is augmented by using a nitrogen-rich fertilizer, production increases proportionally until it reaches a point at which a second factor, such as water availability, begins to constrain production. As depicted in Figure 3, there is a sudden shift from one limiting factor to another.

2.7. Environmental and Social Externalities

Every CSA practice creates external effects, which can be either positive or negative. In the context of this study, social and environmental externalities are considered to be generated upon application of CSA practices. Information on externalities was gathered from a survey of farmers and an experts’ workshop, as well as various literature sources discussing the ramifications of adopting climate change adaptation strategies. These externalities encompass effects on crop and soil biodiversity and on ecosystem services, as well as other external effects like biodiversity, greenhouse gas emissions, soil fertility, social harmony, and social impact. The strength of the effects of the adoption of CSA practices on these externalities was qualitatively ascertained, based on the discussion with CSA farmers, to be “high”, “non-significant” or “low”. For instance, use of bio-pesticides might have non-significant impact on fertility of soil but a high impact on productivity.

2.7.1. Valuation of Externalities, Change in Biodiversity and Labor Requirement

For the valuation of externalities, the weighted value of change in externalities generated by the introduction of CSA practices was applied along with the respective shadow price-marginal amount someone is willing to pay (WTP) or willing to accept (WTA) for given external effects, which may be positive or negative. The estimation of the shadow prices with respect to external effects can be performed using different methods [27]. The contingent valuation method (CVM) is applied for estimation of the value of the benefits corresponding to the externalities, since it is the most flexible method of valuation in the case of a stated preference, i.e., non-market-based. CVM is a stated preference for the valuation of resources that cannot have market value but have an impact, either positively or negatively, on the environment [27,28,29]. The respondents were asked their WTP values for the externalities created by the adoption of CSA practices, which were later averaged to obtain a value which reflected the adopters’ WTP for CSA practices at CAP, i.e., the amount they are willing to pay for an externality and to adopt a CSA practice within their conventional agriculture practices. Since not every farmer adopts every CSA practice, the valuation of externality was obtained from only the farmers associated with a particular CSA practice. For instance, the valuation of an externality created by the adoption of zero tillage (which in our case is wheat only) was obtained from the value of WTP obtained from farmers adopting the same.

The biodiversity index is an accurate and consistent measure of the richness of biodiversity in an area that allows for comparison of species’ abundance between two systems [30]. The change in the biodiversity after the introduction of CSA practices was calculated, taking into consideration the associated externalities (social and environmental) and their benefits. This system of valuation works on the principle that any changes in land use patterns indicate the amount of service provided to the environment [25]. For this purpose, a score was assigned in accordance with the type of land used to regulate or promote biodiversity. The topmost score of 1 was assigned to the forestland use pattern, owing to its greatest environmental services, whereas degraded land or intensive monoculture was assigned a score of 0 (at the bottom of the scale). To make the environmental service valuation proportionate, we considered a differential increment with respect to the base year 0. Furthermore, we assumed the price of alteration in biodiversity due to the implementation of a CSA practice. The distribution of prices was presumed to have a uniform nature, with a maximum value of USD 69/unit/year (USD 1 is taken to equal NPR 120.08 in our study, which is implied wherever the value is in USD, based on 4 December 2021) [31,32]. Ultimately, values were obtained by multiplying the change in biodiversity index due to the adoption of the respective CSA practice with the associated shadow price of the same level of biodiversity.

The societal impact or external consequences of implementing CSA strategies was assessed through their influence on changes in labor requirements. Furthermore, the calculation of the extra man days/ha/year for the practices was performed to assess the labor and employment as social externalities compared to the CAP. The value was obtained by asking the respondents about the additional labor required in adopting a particular CSA.

2.7.2. Soil and Water Conservation

The role of CSA practices in decreasing the effect of negative externalities like water pollution, particularly from agricultural chemicals, has been assessed [33,34]. Thus, this concept was incorporated by valuing the reduction in soil erosion and water pollution by using the opportunity cost. For this, we presumed an estimate of about USD 0.008/t of soil for the value of soil degradation due to land erosion [35]. The soil cover practice using mulch could effectively reduce loss of soil by about 91.1 t/Mz/year (1 Mz is equivalent to 0.7 ha) [36]. In the case of conservation tillage followed by mulching, an estimate of USD 1.04/ha was made [25]. This allowed us to consider the same value when using the jab planter and zero tillage.

2.8. Data Processing and Analysis

The collected data were carefully entered into MS Excel followed by data cleaning and curation. The collected data were arranged crop-wise, CSA practice-wise, and externality-wise (WTP) to prevent confusion upon further assessment. The collected data were analyzed using MS Excel and R Studio Version 4 for financial and economic analysis of the CSA practices.

3. Results

3.1. Prioritized Climate-Smart Practices

A list of CSA practices were developed and prioritized after consultation with experts, farmers, and stakeholders (

Table 3. Top prioritized CSA practices considered for cost–benefit analysis.

Practices	Descriptions
Jab planter	The use of a jab planter aims to reduce greenhouse gas emissions by avoiding the use of machinery, such as tractors, and soil disruption by ploughs.
Improved seeds	The adoption of hybrid seeds, as opposed to utilizing local or recycled seeds, increases production, while the application of other inputs like fertilizer, labor, and management remains constant.
Solar water management	Use of solar water management provides irrigation to replace the traditional petrol/diesel generator for irrigation, aiming to increase production and mitigate GHG emission.
Biopesticides	The use of biopesticides for controlling the pests aims to protect against the chemical contamination of the soil.
Organic fertilizers	Use of organic fertilizers like farmyard manure (FYM) compost minimizes the application of chemical fertilizers.
Zero tillage	Zero tillage and soil cover with straw as mulch minimize soil surface disruption and can occasionally replace the use of machinery, such as tractors or ploughs, on farms.

). The practices thus listed were the most commonly adopted and most popular CSA practices in the study area. CSA practices or technologies that support the three pillars of CSA—production, resilience, and mitigation of climate change in agriculture—could be considered CSA technology. For this purpose, farmers were asked to score each technology on a scale of 0 to 4 based on productivity, adaptability, and mitigation. If farmers perceived that these practices made a substantial contribution to increasing productivity, enhancing adaptation, and supporting greenhouse gas (GHG) mitigation, they assigned a rank of 4. Conversely, if they did not recognize these benefits, the practices were assigned a rank of 0. They were free to score between 0 and 4 for each of the practices they have been applying as CSA practices. The top six most highly ranked CSA technologies which were prioritized for the economic analysis are briefly discussed below.

3.2. Cost–Benefit Analysis of Prioritized Climate-Smart Practices

A cost–benefit analysis was conducted for six climate-smart practices: use of a jab planter, improved seeds, solar water management, biopesticides, organic fertilizers, and zero tillage, as outlined in

Table 4. Initial investment and operation and maintenance costs for different crops during different CSA practices.

Farm Practice	Crops	Initial Investment (USD/ha)	Operation and Maintenance Cost (USD/ha)
Conventional agriculture practice (CAP)	Rice	479.17	510.33
	Maize	458.33	247.82
	Wheat	458.33	167.68
Climate-smart Agriculture Practices
Jab planter	Rice
	Maize	204.17	411.21
	Wheat
Improved seeds	Rice	720.83	582.1
	Maize	720.83	369.11
	Wheat	720.83	152.2
Solar water management	Rice	1625	478.8
	Maize	1625	338
	Wheat	1625	240.7
Biopesticides	Rice	625	655.82
	Maize	625	304.54
	Wheat
Organic fertilizers	Rice	708.33	343.73
	Maize	708.33	247.63
	Wheat
Zero tillage	Rice
	Maize
	Wheat	875	168.55

Source: Field survey (2019).

. The key indicators considered included the NPV, IRR, B/C ratio, NK ratio, discount rate, and payback period. The findings demonstrated the profitability and viability of prioritized climate-smart technologies. The discount rate was kept at 12%. The payback period of the CSA practices ranged between 2.2 years (organic fertilizer) and 14.17 years (solar water management). However, most of the CSA practices have a payback period of 2 to 4 years, indicating favorable conditions for smallholder farmers. This shorter payback period allows them to repay credit and enjoy investment profit simultaneously. Costs used in CBA calculations were associated with implementing, maintaining, and operating CSA practices on one hectare for one year, with constant input and output prices. The nature of cost within the CBA approach two kinds of cost: installation costs and operation and maintenance costs, both of which constitute materials and labor. Installation costs are incurred by the farmers during adoption. Operation and maintenance costs are mandatory, incurred over the entire lifecycle of CSA practices. Initial investment and operation and maintenance costs for different crops during different CSA practices are shown in Table 4.

Private Profitability

In this study, a cost–benefit analysis was conducted to examine the economic implications of agricultural activities influenced by climate-smart agriculture (CSA). The assessment of costs and benefits considered the impact of a CSA practice on one hectare of land for analysis. Data regarding conventional agricultural practices or a business-as-usual scenario reflected input and output values before the implementation of the CSA; this relied on data recalled by the farmers. The jab planter was the most practiced (63%) CSA intervention, while households using biopesticides and organic fertilizer were minimal (7% and 3%, respectively).

From

Table 5. NPV, IRR, B/C ratio, NK ratio, and payback period for different crops during different CSA practices.

Farm Practice	Crops	NPV (in USD ha−1 at 12%)	IRR (%)	B/C Ratio	NK Ratio	PBP (Years)
Conventional agriculture practice (CAP)	Rice	655.62 (±83.63)	42 (±5.35)	1.15 (±0.15)	3.18 (±0.4)	3.35
	Maize	328 (±24.95)	26 (±1.98)	1.14 (±0.09)	2.016 (±0.15)	4.67
	Wheat	332 (±53.72)	26 (±4.21)	1.19 (±0.19)	2.03 (±0.33)	4.65
Climate-smart Agriculture Practices
Jab planter	Rice
	Maize	282 (±33.37)	42 (±4.97)	1.08 (±0.13)	3.21 (±0.38)	3.35
	Wheat
Improved seeds	Rice	530.4 (±118.58)	27 (±12.78)	1.10 (±0.52)	2.05 (±0.74)	4.66
	Maize	540.3 (±118.54)	27 (±7.96)	1.42 (±0.37)	2.07 (±0.49)	4.62
	Wheat	1029.5 (±850.56)	43 (±35.58)	2.44 (±1.16)	3.29 (±1.55)	3.30
Solar water management	Rice	1697 (±418.26)	33 (±8.53)	1.32 (±0.25)	2.56 (±0.47)	3.98
	Maize	−521 (±165.45)	6 (±1.61)	0.87 (±0.17)	0.61 (±0.12)	14.17
	Wheat	299.2 (±233.86)	15 (±11.50)	1.087 (±0.50)	1.24 (±0.56)	7.01
Biopesticides	Rice	330 (±325.63)	22 (±21.13)	1.06 (±1)	1.72 (±1.68)	5.28
	Maize	494 (±235.16)	28 (±13.76)	1.16 (±0.68)	2.14 (±1.21)	4.48
	Wheat
Organic fertilizers	Rice	1828 (±1801.88)	83 (±81)	1.54 (±1.50)	6.29 (±6.05)	2.20
	Maize	1034.5 (±1027)	45 (±44.1)	1.39 (±1.37)	3.38 (±3.32)	3.20
	Wheat
Zero tillage	Rice
	Maize
	Wheat	317.6 (±275.6)	26 (±21.70)	1.18 (±0.90)	1.53 (±1.17)	4.29

Note: Figure in parentheses are standard deviations representing statistical variations in measures among farms.

, it can be observed that almost all of the CSA practices were profitable, having positive NPV, an IRR higher than the discount rate, and a B/C ratio and NK ratio greater than 1, except for the practice of solar water management in maize. Among the profitability indicators discussed in the CBA, namely, NPV, IRR, B/C ratio, and NK ratio, NPV emerged as the most suitable measure for assessing the worthiness of a practice. While IRR and B/C ratio find applicability when there is only one alternative under consideration, NPV proves highly useful when multiple alternatives are available [10].

In the case of solar water management used on wheat, the IRR was found to be 15%, a few percent more than the discount rate (12%), proving it to be a marginally profitable practice. The use of organic fertilizers in rice showed the highest IRR amid all the CSA practices. Despite the highest initial investment (Table 5), use of solar water management on rice exhibited a relatively higher NPV (USD 1697), which was only slightly lower than the NPV of using organic fertilizer on rice, which had the highest value (USD 1828). The BC and NK ratio were higher than 1 for all the practices except for solar water management use in maize and wheat (0.87 and 0.61, respectively), indicating a non-profitable practice. Most practices required a huge investment during the initial phase and a significantly greater amount of time to exhibit their impact on the return and yield from the crops. This could be attributed to the payback period (PBP). The PBP was within the range of 2 to 4 years for most of the CSA practices. A shortest recovery period of 2.2 years was found for rice cultivation with the practice of organic fertilizer application. Unlike other practices, the use of solar water management in maize and wheat required 14 and 7 years, respectively, to cover the investment in the initial phase.

3.3. Environmental and Social Externalities

Despite the different sets of externalities obtained from some of the CSA practices, eight externalities were generated that were determined to be relevant and feasible for valuation of the concerned parameters, as shown in

Table 6. Externalities associated with different CSA practices in the Nawalpur district.

Practices	Externalities
	Carbon Sequestration	Productivity	Social	Soil Fertility	Biodiversity	Investment	Income	Natural Beauty
Jab planter	Low carbon emissions	High	Social harmony	Low nitrogen emissions	Balanced environment	Low	High income	Adds to natural beauty
Improved seeds	Low carbon emissions	High	Social harmony	Balanced	Eco-friendly	Low	High	No significant impact
Solar water management	Low carbon emissions	High	Social respect and harmony	Low nitrogen emissions	Balanced environment	Low	High	Adds to natural beauty
Biopesticides	Non-significant impact	High	Social harmony	Non-significant impact	Eco-friendly	Non-significant impact	High	Adds to natural beauty
Organic fertilizer	Non-significant impact	Non-significant impact	Non-significant impact	Balanced nitrogen	Eco-friendly	Non-significant impact	Non-significant impact	Non-significant impact
Zero tillage	Low carbon emissions	Low	Non-significant impact	Low nitrogen emissions	Eco-friendly	Low	Low	Non-significant impact

. Practices like use of a jab planter, improved seeds, solar water, and zero tillage were associated with carbon sequestration due to low carbon emissions. In the case of increased productivity, all practices except for the organic fertilizer contributed to productivity. The use of organic fertilizer and zero tillage did not contribute to social harmony as an externality. In the case of soil fertility, except for the use of biopesticides, other practices contributed positively to soil fertility. All the CSA practices created positive externalities with respect to biodiversity. The use of a jab planter, improved seeds, solar water, and biopesticides was associated with higher income and added natural beauty as externalities.

3.3.1. Willingness to Pay for Externalities and Change in Biodiversity

The willingness to pay (WTP) for the externalities of the farmers’ adopting CSA is shown in

Table 7. WTP for externalities of CSA farmers.

Externalities	WTP (USD/ha)
Low greenhouse gas emissions	33.51
Increased productivity	63.03
Social benefit	41.92
Soil fertility	16.22
Biodiversity	36.7
Investment	24.1
Income	69.27
Natural beauty	29.17

. The farmers had higher WTP for the externalities of increased income (USD 69.27/ha) and enhanced productivity (USD 63.03/ha) thanks to the adoption of CSA practices, compared to other externalities. The CSA farmers had the lowest WTP (USD 16.22/ha) for the soil fertility externality created by CSA practices. These statistics reveal that farmers are more concerned with increased income and productivity upon adoption of CSA practices. The average value of WTP for externalities created by the adoption of CSA practices was USD 39.24/ha.

The WTP for a unit change in biodiversity after the adoption of the CSA practices was between $8.75/ha and $51.3/ha (

Table 8. Estimated change in biodiversity index.

CSA Practices	Change in Biodiversity Index	WTP for Unit Change in Biodiversity (USD/ha)
Jab planter	0.64	51.3
Improved seeds	0.13	8.75
Solar water management	0.13	11.92
Zero tillage	0.64	29.6

Note: Biodiversity index adapted from [25].

). The average value of WTP for a unit change in the biodiversity index was estimated to be USD 25.4/ha for the selected CSA practices of jab planter, improved seeds, solar water management, and zero tillage. Although the biopesticides and organic fertilizers have an impact on the biodiversity, we could not assess their effects due to lack of information.

3.3.2. Social Externalities Due to CSA Intervention

The study showed that on average, labor increased by 1 man-day/ha in the first year of establishment of practices and by 2 man days/ha per year for maintenance of the practices (

Table 9. Estimated impact on the level of labor as a result of introducing CSA practices.

CSA Practice	Increase in Labor (Man days/ha)		Increase in the Value of Labor (USD/ha)
	Installation (Temporary)	Maintenance (Permanent)	Installation (Temporary)	Maintenance (Permanent)
Jab planter	0	3	0	30
Improved seeds	0	0	0	0
Solar water management	2	4	83.33	50
Biopesticides	4	1	33.33	8.33
Organic fertilizers	0	1	0	10
Zero tillage	0	3	0	200
Average	1	2	19.44	49.72

) compared to CAP. On average, the value of increased labor was USD 19.44/ha in investment in the initial year, and an annual increase of USD 49.72/ha/year for the lifecycle of the practices. The valuation of externalities arising from CSA practices was carried out based on the CVM, which was estimated from the response of the respondents.

3.3.3. Soil and Water Conservation

The valuation of the two CSA practices which fell under the category of conservation tillage (with mulch), i.e., zero tillage and the use of a jab planter, was USD 4.75/ha, which represents the value of potential soil erosion that was prevented by adoption of the conservation tillage practice. In the case of agrochemicals, the use of organic fertilizer led to a valuation of USD 51/ha/year from the survey; the consequent avoidance of chemical fertilizer resulted in a reduction of USD 9.33/ha in pollutants.

4. Discussion

4.1. Costs and Benefits in Implementing CSA Practices

For any agricultural planner or policy maker, decision making regarding investments and regulatory practices primarily revolves around two key considerations: (1) the profitability of practices for individuals, and (2) the overall benefits these practices bring to the public. Cost–benefit analyses (CBAs) emerge as the preferred tool for decision makers when evaluating investment options, factoring in policy considerations and planning dynamics [37]. Various studies have made use of the CBA approach for determining the viability of practices in the context of changing climate [38]. This study utilizes two decision-making tools to assess climate-smart agriculture from the perspective of smallholder farmers in Nepal. Initially, the CSA-PF was employed to pinpoint the most prioritized CSA strategies. This involved ranking their significance in enhancing productivity, resilience, and mitigation benefits. Then, a cost–benefit analysis was conducted based on the data collected from the questionnaire survey and experts’ workshops. The chosen practices not only provide social and economic benefit at the farm level under current conditions but also have the ability to build resilience to climate change in the near future, thus providing a stable option [39,40].

Almost all the assessed practices demonstrated a profitable nature, signified by a net present value (NPV) greater than zero (Table 5) and an internal rate of return (IRR) surpassing the considered discount rate of 12%. However, the implementation of solar water management exhibited a negative NPV and a low IRR for maize, indicating an unprofitable aspect of this particular CSA practice in maize cultivation. This can be attributed to the substantial initial investment required for the installation of solar water management [41], with returns failing to recuperate the initial investment within the assessed timeframe. Solar water management also impacted wheat cultivation, revealing a lower NPV and an IRR marginally exceeding the discount rate, primarily due to the significant initial investment. Conversely, the utilization of organic fertilizer as a CSA practice in rice showcased the highest NPV and IRR, followed by solar water management in rice cultivation. These findings concur with [20], who reported highest NPV in case of organic fertilizer application, in their study in Kenya. Moreover, the benefit–cost (BC) ratio and NK ratio for nearly all practices exceeded 1, affirming the profitability of the CSA practices. The exception was the use of solar water management in maize, which diverged from the profitable trend. While choosing CSA practices, careful consideration should be given to the statistical variation within the measures used in this study.

For the determination of a cost–benefit analysis of the practices, the time required to recover initial investments is crucial. In this study, most of the CSA practices had a PBP of 2 to 4 years, which could be considered a relatively longer period for the small producers targeted by the CSA-PF. Use of organic fertilizers in rice and maize, improved seed cultivation by wheat farmers, and solar water management in rice cultivation were the top three practices with respect to their IRR, and they had payback periods of 2 to 3 years, indicating their potential to enhance food security within households, increase incomes, and enhance adaptation, despite their high associated costs. These emerged as the strongest choices among the CSA practices considered for the farmers in the region, with improved seeds in wheat, solar water management and organic fertilizers in rice, and organic fertilizers used in maize proving to be the promising practices for the individual crops. The use of solar water management in wheat had a PBP of 7.01 years. The longer payback period of solar water management has been reported by a previous study [42] in Burkina Faso, suggesting potential support from microfinancing institutes to irrigate via solar water pump systems. Practices that have a long PBP could be applicable to systems with a favorable environment (like a secured tenancy and institutional and political support) and in which diversified short-term livelihood alternatives are accessible [25]. The statistical variation within the measures should also be considered prior to their implementation.

4.2. Externalities Corresponding to CSA Practices

In understanding the economics of an agricultural practice, measures beyond a financial basis are equally crucial for making an assessment [43]. CBAs that solely emphasize the financial analysis can create a dilemma related to the adoption of practices, due to an inability to address the critical externalities in their approach [25]. This is highly relevant when we consider the implementation of CSA practices both on the farm and within the associated system of agro-ecology. It is evident that the non-market values associated with different practices could prove argumentative [44], but an inability to include the estimated values of external effects means they could go undiscussed. Our study prioritizes these externalities so as to include external effects in the discussion with concerned stakeholders within the CSA prioritization framework. This will assist in the choice of CSA practices within investment portfolios. The identified externalities of increased productivity and increased income, for which the farmers’ willingness to pay was greater, are key in promoting CSA practices. Ref Anugwa et al. [45] reported that higher income and increased productivity due to adoption of CSA practices encourage a WTP of USD 115.63 per annum for adoption of CSA in rice cultivation in Nigeria. Decision makers can take into account the externalities that respondents were more willing to pay for. The findings of our study are in line with [20,25] in Kenya and Guatemala, respectively, where the authors reported similar societal and environmental benefits upon adoption of different regionally based CSA practices. The implications of findings related to externalities have been described in relation to farmers’ decision making. The valuation of externalities can help farmers and decision makers to make more holistic decisions regarding environmental benefits, risk reduction, and social co-benefits [46]. Most CSA practices have social benefits such as improved livelihoods for farmers, increased food security, and enhanced community resilience [47]. By valuing externalities related to social cohesion, decision makers can better understand the broader societal benefits of supporting CSA. This can inform policies and programs aimed at promoting sustainable agriculture. Similarly, CSA practices often enhance the resilience of agricultural systems to impacts of climate change such as droughts, floods, and extreme weather events. By valuing externalities related to risk reduction, such as increased water retention or improved pest management, decision makers can better assess the potential benefits of investing in CSA practices. This can also help farmers mitigate production risks and adapt to changing climatic conditions. CSA practices contribute to environmental conservation by reducing greenhouse gas emissions and preserving biodiversity. By valuing externalities related to environmental conservation, such as carbon sequestration or habitat restoration, decision makers can better assess the environmental impact of different agricultural practices. This can inform policies aimed at promoting sustainable land management and biodiversity conservation.

4.3. Potential Implementation and Adoption of CSA Practices

Although the approach of a cost–benefit analysis focuses on the determination of the profitability of individual farmers with respect to CSA practices, there were some constraints. One of the hindrances of the analysis is its inability to measure the degree of risk and uncertainty with respect to yields of cereal crops upon adoption of CSA practices compared with conventional farming. In order to overcome this restriction, we carried out a field survey of households who have implemented some CSA practices recently (in the last five years) but had undertaken conventional farming in the past. This tool could portray the difference in yield at the farm level. Furthermore, the price in real terms was averaged (between 2015–2020) so as to prevent any shortfalls with respect to short-term fluctuation in price. A mixed ex-ante and ex-post analysis was employed, as few CSA practices had been introduced very recently, thereby rendering it unfit for assessing the effectiveness of practicing CSA options.

CSA practices which could be cross-validated and evaluated were chosen along with policy makers, workshops, and farmers, thereby ameliorating constraints related to subjectivity [20]. In accordance with the findings of the study, most of the CSA practices had a positive NPV and a PBP of 4.21 years on an average; this presents an adequate justification for the Ministry of Agriculture and Livestock Development (MoALD), Nepal to encourage these promising CSA practices. The results provide convincing outcomes that can validate the government’s promotion of these practices along with further research on these practices. CBA offers an opportunity and a tool for assessing probable adoption niches and can be enhanced upon combination with some interdisciplinary decision support tools.

4.4. Policy Planning

The findings of this study were shared and presented with research institutions, farmers’ organizations, the agricultural ministry, non-government organizations working in climate change adaptation and mitigation, policy makers and concerned stakeholders in Kathmandu; then, the results were presented to concerned stakeholders. Furthermore, the different adjustments between the CSA goals (productivity, adaptation, mitigation) and the results of the economics of different practices used for the three crops were exhibited. Economic appraisal must be supplemented with other analyses of different conditions for prioritization of CSA practices. Thus, sufficient discussions to provide justification were carried out during the workshop on CBA, which created an enabling environment for the implementation of CSA practices of the most interest to the concerned stakeholders. Further action plans were created, which outlined the financial support, technical assistance, and local leaders’ roles required to scale up these practices. We hope that the findings of this study regarding climate-smart practices in the periphery of Gandaki River Basin can be scaled up via provision of our results to prospective researchers. This will create a favorable environment for potential research and provide a climate-smart path to upgrading farmers’ conventional practices in the context of our changing climate. Furthermore, this study envisions roles for local stakeholders within the CBA approach and fills gaps in the literature data so as to allow for replication of our approach to then recommend impending decisions on the policy level. A major constraint on practitioners and policy makers is the development of programs which focus on inferential analysis and that can be managed well along with proper integration of the novel threat of climate change and up-to-date CSA data.

Adopting a CSA practice will require a decision to be made on investment. For this purpose, how one practice compares to the other needs to be analyzed and clarified on an economic basis. The CBA approach provides a unique method of determining impact along with individual profitability. Furthermore, the approach can be bolstered by coupling it with analysis of social and environmental externalities. This research revealed that nearly all the practices were observed to be profitable in nature but with varied time periods required to recover initial investments. The findings provide a means of rethinking and considering the practices that are being implemented in accordance with the current agricultural policies by the MoALD, Nepal. Similarly, a better understanding of corresponding externalities (social and environmental) that are associated with farmers’ other policies and priorities is also provided by this study, which can have an impact on how these practices are adopted. Different practitioners, policy actors, and CSA-related stakeholders can modify the CBA approach so as to target investment activities to upscale novel practices in agriculture, which primarily focus on climate change adaptation, mitigation, resilience, and food security. Certain production systems will require a new approach that delimits the analysis, despite gaps in the data and uncertainty in measuring the impact of CSA practices. This study could not account for the valuation of carbon dioxide reduction, as the area under cultivation was too small to estimate the carbon balance using the FAO Ex-Act tool. The carbon balance could be calculated after a few years of CSA being practiced in a relatively larger land area. Similarly, the estimation of the reduction in cost of pesticides due to application of biopesticides as a CSA practice could not be addressed as an externality due to the practice being limited to very few households. The scope of this study is limited to smallholding farmers in the Gandaki River Basin of Nepal, given the similar climatic conditions, crop types, and farmers’ production levels in this region. The findings from this study can reinforce the promotion of CSA practices and motivate farmers to adopt such practices in different regions, considering their financial viability and generation of welfare, as observed in our study. However, to recommend that farmers of a particular region adopt a particular CSA practice, their CSA practices need to be evaluated for financial viability and welfare generation. In such cases, the methodology used in this study will be useful for researchers who aim to evaluate CSA practices in different regions and countries.

5. Conclusions

Climate-smart agriculture is emerging as a resilient and adaptive approach through which to address the challenges posed by climate change. There are several studies in the field of climate change adaptation strategies. However, only a limited number of these studies have taken a comprehensive approach by calculating the costs versus the benefits of climate-smart agriculture. To effectively invest in climate-smart agriculture (CSA) practices among smallholder farmers, a thorough assessment is essential to comprehend the costs, advantages, and payback periods associated with each of the six CSA practices. This evaluation has the potential to significantly influence decisions regarding the expansion, sustainability, and enhancement of food security for these practices. The current cost–benefit analysis (CBA) appraises CSA practices identified as optimal choices in terms of climate risk adaptation, financial returns, implementation costs, and the likelihood of investment loss. This study’s findings offer vital information that farmers can use to to reconsider their investment strategies.

The CSA practices of implementing organic fertilization for rice and maize, introducing improved seeds for wheat, and adopting solar water management in rice cultivation, despite their initially high costs, emerged as the top three practices based on their internal rate of return (IRR). Their relatively short payback periods of 2 to 3 years highlight their potential to enhance food security, increase household income, and facilitate adaptation efforts. These practices stood out as the most favorable options among the CSA techniques evaluated for farmers in the region. Policy makers can develop and implement tailored training programs for farmers in the Gandaki River Basin that focus on climate-smart agricultural practices identified as cost-effective in the analysis. Similarly, focus should be directed to ensuring that farmers have access to the necessary resources, inputs, and technologies required to adopt climate-smart agricultural practices. This may include providing subsidies or financial assistance for the purchase of climate-resilient seeds, organic fertilizers, and water-saving irrigation systems, etc. The Ministry of Agriculture and Livestock Development of Nepal can utilize this information to prioritize initiatives in the agricultural sector, particularly in projects where decisions and outcomes for adaptation are unclear. This study’s results provide insights into externalities and social benefits linked to the examined CSA practices, which are crucial for stakeholders to comprehend their true potential from the farmers’ perspective. The adoption of these CSA practices, if implemented, would result in positive environmental and social impacts, contributing to achieving the three CSA goals: food security, adaptation, and mitigation.

Considering externalities in economic valuation is crucial and should be incorporated into the economic analysis of adaptation options to ensure robust economic evaluations in future studies. Such consideration would facilitate decision making during the selection of CSA options and guide the efficient allocation of scarce resources in the future. In this study, it was challenging to quantify one of the externalities arising from CSA—specifically, carbon sequestration for mitigation purposes—due to certain limitations. We recommend that future studies consider the measurement of carbon sequestration as a valuable metric for consideration which has the potential to broaden the information used to select and invest in appropriate CSA practices and to enhance future planning and decision making processes.