Scaling up community participation in watershed management for food security improvement: the case of Qarsa woreda , East Haraghe zone, Ethiopia

Tena gobena; Amare Bantider; Messay Mulugeta; Ermias Teferi

doi:10.12688/f1000research.153669.1

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Research Article

Scaling up community participation in watershed management for food security improvement: the case of Qarsa woreda , East Haraghe zone, Ethiopia

[version 1; peer review: 1 approved, 1 approved with reservations]

Tena gobena ¹, Amare Bantider¹, Messay Mulugeta¹, Ermias Teferi¹

PUBLISHED 28 Feb 2025

Author details Author details

¹ Addis Ababa University College of Development Studies, Addis Ababa, Addis Ababa, Ethiopia

Tena gobena
Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Validation, Writing – Original Draft Preparation, Writing – Review & Editing

Amare Bantider
Roles: Conceptualization, Formal Analysis, Investigation, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

Messay Mulugeta
Roles: Conceptualization, Formal Analysis, Investigation, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

Ermias Teferi
Roles: Conceptualization, Formal Analysis, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

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This article is included in the Agriculture, Food and Nutrition gateway.

Abstract

Background

The watershed management approach has been well-acknowledged as an effective strategy for improving food security. However, the significance of community engagement, which is vital for the success of this strategy, has not been adequately acknowledged. The study examined the level of community involvement and the factors influencing their participation in watershed management.

Methods

A household survey of 337 household heads, focus group discussions, and key informant interviews were used to collect the data. Descriptive statistics, a people participation index, and a binary regression model were used for data analysis.

Result

The results of the people participation index indicated a moderate level of farmers’ participation in the planning, implementation, monitoring, and evaluation phases, with no significant differences observed between the three micro watersheds. However, there were variations in the indicator metrics within and across the micro watersheds, with participants from the Sustainable Land Management Program II (SLMPII), micro watershed showing significant differences compared to those from the Productive Safety Net Public work (PSNP_PW) and free mass mobilization at levels of 0.01 and 0.05, respectively. The results of binary logistic regression indicated that the overall level of farmer participation was significantly affected by the frequency of extension contact, livestock ownership, education level, family size, and group membership.

Conclusions

The study highlights the need to consider variability in indicator measurements for effective watershed management to improve food security. It stresses the importance of building farmers’ capacity and fostering ownership, rather than simply providing them with explícitas instructions to follow.

Keywords

Community involvement, farmers, micro watershed, rural development sustainability

Corresponding author: Tena gobena

Competing interests: No competing interests were disclosed.

Grant information: The author(s) declared that no grants were involved in supporting this work.

Copyright: © 2025 gobena T et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: gobena T, Bantider A, Mulugeta M and Teferi E. Scaling up community participation in watershed management for food security improvement: the case of Qarsa woreda , East Haraghe zone, Ethiopia [version 1; peer review: 1 approved, 1 approved with reservations]. F1000Research 2025, 14:244 (https://doi.org/10.12688/f1000research.153669.1) First published: 28 Feb 2025, 14:244 (https://doi.org/10.12688/f1000research.153669.1) Latest published: 28 Feb 2025, 14:244 (https://doi.org/10.12688/f1000research.153669.1)

1. Introduction

The use of watershed management has been widely acknowledged as an effective strategy for reducing poverty, improving food security, and increasing agricultural productivity while also protecting ecological resources (Iroye & Tilakasiri, 2015; Wang et al., 2016; Chimdesa, 2016). The approach gained attention especially after the 1992 Rio Earth Summit in many developing countries, including Ethiopia (Wani & Garg, 2009; Molle, 2009; FAO, 2017). Studies by Tefera et al. (2020) and Taye (2021) found that watershed management practices in Ethiopia has numerous benefits, such as increasing food production, preserving the environment, promoting gender equality, and addressing biodiversity concerns, all which are contributing to food security improbvement. However, the sustainability and the scaling up of this approach have not met the expected level of succes (Teressa, 2018; Gizaw et al., 2018).

According to Bantider et al. (2019), Ethiopia has made significant progress and dedicated significant resources to watershed management; however, the approach has not moved beyond basic conservation practices and has failed to incorporate comprehensive watershed management practices for sustainable livelihoods and food security improvement. The studies by Tesfahun and Chawla (2017), Ananga (2015), and Reed (2008) have demonstrated that the success or failure of watershed management relies on a comprehensive approach that takes into account economic, social, and environmental factors. Furthermore, Wang et al. (2016) argue that to address diverse concerns related to the economy, society, and environment, watershed management requires the active participation of the community in all phases of the watershed management process. A lack of comprehensive engagement by all stakeholders can lead to inconsistencies and the failure of the strategic plan (Mengistu & Assefa, 2021).

Furthermore, the shift in development ideology towards a human-centered approach emphasizes the significance of community participation as a fundamental element in rural development (Pimbert & Pretty, 1995; Wang et al., 2016). According Reed et al. (2018), Usadolo & Caldwel (2016), and Haregeweyn et al. (2015), community empowerment plays a critical role in ensuring inclusive progress and sustainable development at the local level. Bantider et al. (2019) indicated that the effectiveness of watershed management programs heavily relies on the active participation of the community as it directly affect their own lives. Community engagement can enhance various aspects in different contexts by promoting connections, resolving conflicts, and facilitating knowledge exchange (Reed et al., 2018; Usadolo & Caldwel, 2016). Yet, the importance of community participation in watershed management is often underestimated, as it is commonly seen only as a labor-intensive contribution (German et al., 2007; Snyder et al., 2014; Haregeweyn et al., 2015; Mengistu & Assefa, 2021).

The studies conducted by Tefera et al. (2020), Wang et al. (2016), Ayele et al. (2016), and Terefe et al. (2015) revealed that relying solely on technical solutions is inadequate in addressing the complex challenges faced of watershed management approach and extending beyond is imparative. Mengistu and Assefa (2021) further highlight sustainable watershed management, ultimately require more comprehensive community engagement for efficient solutions. However, studies in different parts of the country showed biased toward evaluating watershed management programs in terms of biophysical indicators, with less attention to livelihood improvement of people (Ayele et al., 2016; Tessema & Tibebe, 2017). Furthermore, studies conducted by Desta et al. (2005), Kidane et al. (2014), Teressa (2018), and Mengistu and Assefa (2021) have revealed that the top-down planning approach used in watershed management practices fails to take into account the valuable knowledge and input of the local community.

Furthermore, different people have different views on the concept of participation in watershed management (German et al., 2007). Indeed, multiple factors play a role in community participation in watershed management, including, institutional, sociological, technological, and logistical aspects. According to Botes and Van Rensburg (2000) proposed paradigm the external obstacles, such as financial and technological barriers, government encouragement for involvement, development experts, and selective engagement have an impact on community engagement. Nikkhah and Redzuan (2009) further argue that the local community’s ability to set its goals is affected when the development experts dominate decision-making processes. This lack of empowerment hinders the development of communities as they are not allowed to actively participate in shaping their future. Local political dynamics also play a role in limiting community participation by preventing them from having a voice in decision-making processes. Community participation is also impacted by low awareness, poverty, distrust in government programs, and village politics (Bekele et al., 2023; Sangchini, 2023).

Similarly, although Ethiopia has demonstrated a high commitment to community-based participatory watershed management, comprehensive research on the extent and factors influencing community involvement in watershed management was lacking. As a result, the management practices of watersheds suffer from a lack of comprehensive planning, implementation, and evaluation, thus falling short of addressing the distinct requirements and preferences of the community (Haregeweyn et al., 2015). Consequently, this has impacted the widespread adoption and recognition of watershed management strategies as a holistic approach. Therefore, this study aimed to examine the extent of farmers’ participation and the factors influencing their involvement in various stages of watershed management in the Qarsa woreda, East Harghe, Ethiopia, under diffirent program approach.to improve livelihoods and food security for the local community.

2. Conceptual framework of study

The complex and dynamic nature of watershed management requires the active involvement of the community in all stages of the process to attain food security. The active participation of the local communities in the planning, implementation, and monitoring of watershed management initiatives is crucial for improving agricultural productivity, water availability, horticulture, animal husbandry, and other vital services that support food security improvement (Vishnudas et al., 2008; Devi, 2015; Onyancha et al., 2022). However, the extent of community participation in watershed management intervention is influenced by varying perceptions, definitions, and approaches of participation (Alemu et al., 2023).

The concept of participation has been thoroughly analyzed and categorized by various scholars, each offering their perspectives. For instance, Pretty (1995) delineates levels of citizen engagement, ranging from non-participation to tokenism and ultimately to full citizen control. This classification allows for a better understanding of the varying degrees of engagement that individuals can have in participatory processes. Beierle (2002) examines the motivations and objectives behind participation, distinguishing between normative participation, driven by ethical considerations, and pragmatic participation, motivated by self-interest. Tippett et al. (2007) introduced an objective-based model for participation, categorizing it into instrumental, expressive, and deliberative types. These different perspectives provide valuable insights into the motivations, objectives, and outcomes of participation, ultimately contributing to more effective and inclusive participatory practices in development.

The study adopted a pragmatic approach to explore the practical implications of community participation in watershed management, emphasizing the importance of involving stakeholders in decision-making processes. The study also draws on the work of Reed (2008) and Tippett et al. (2007) to highlight the importance of participation rooted in empowerment, equity, and learning. This philosophy emphasizes the need for community members to have a voice in decisions that will significantly impact their daily lives. It also recognizes the importance of knowledge and technical skills of individuals in decision-making, seeking their input, and recognizing their contributions for successful watershed management (Alemu et al., 2023;Yusuf et al. 2020; Assefa et al., 2018). In this study, “participation” refers to the active involvement of the community in all stages of watershed management practices, allowing them to voice their opinions on developmental matters that will significantly affect their daily lives.

Thus, to ensure the success of watershed management programs, it is imperative to assess the level of community engagement using diverse strategies. One way to evaluate community engagement is by utilizing indicator measurements. These indicators can measure the level of community awareness and knowledge about watershed management practices, their level of involvement, and the impact of the community on watershed management (Roba et al., 2022; Bagdi & Kurothe, 2018). This allows for an objective evaluation of community involvement in watershed management practices. Community participation in watershed management is also influenced by various factors, including institutions, demographics, and individual attributes such as age, gender, family size, educational level, land holding, and income (Derkyi et al., 2021; Roba et al., 2022; Mengistu & Assefa, 2021). By assigning values to indicators in each stage of watershed management, researchers can quantitatively assess the level of farmers’ engagement at each stage of the approach. As a result, the level of participation by farmers in the planning, implementation, and evaluation stages serves as the variable that is influenced by other factors in this study. This level is determined by assessing indicators from each stage of watershed management and is assigned a value of 1 if a farmer participated and 0 if not. Figure 1 illustrates the representation of these dependent and explanatory variables.

Figure 1. Conceptual framework showing participation indicators and their explanatory factors.

(Sources: constracted by authours).

3. Methods

3.1 Description of the study area

The study was conducted in Qarsa Woreda of East Hararghe zone, Oromia region of Ethiopia. Geographically, the district lies between 9° 17′ and 9° 29′N latitudes and 41° 12′ and 41° 56′E longitudes to the west of the zonal capital, Harar town. The woreda is one of the food insecure in the East Haralrghe zone. The livelihood of the rural inhabitants is closely linked to the use of land resources for food production, energy sources, shelter constriction, and so on. Watershed management strategies have been applied in the area for a very long period through different initiatives and programs. However, the woreda continued to be the most affected by difficulties with chronic food and nutrition security, soil erosion, declining soil fertility, and water stress. This study focused on three micro watersheds that are part of the Free Mass Mobilization, Sustainable Land Management Program II, and Productive Safety Net Public Work initiatives, which are adjacent to each other (refer to Figure 2). The Free Mass Mobilization micro watershed is an initiative led by the government that does not rely on external funding, while the Sustainable Land Management Program II and the Productive Safety Net Program receive support from the World Bank. Despite the variations in approach and funding sources, all three micro watersheds share a common approach of utilizing watershed management as a fundamental strategy to improve food security and reduce poverty.

Figure 2. Map of the Study Area (Sources: constrcated by authours).

3.2 Study design, sample size and data collection methods

The study used a mixed research design. Quantitative data was collected through a household survey, while qualitative data was obtained from focus groups and key informant interviews (Creswell, 2003). The study area, Qarsa Woreda, was purposefully selected due to the presence of free mass mobilization, a sustainable land management program, and a productive safety net program simultaneously. The micro watershed was selected based on specific criteria, such as sites adjacent to each other, historical similarity of watershed management interventions, similar land use systems, and soil and water conservation practices. Based on this, one micro watershed from each program approach was selected. For the household survey, a list of household heads (the basic unit of the study) was obtained from kebele administration and development agents from the three micro watersheds, as indicated in Table 1. The respondent households were selected following the sample size determination by Kothari (2004) as follows

(1)

S = \frac{Z^{2} * P * (1 - P)}{C 2}

Table 1. A list of micro watersheds and the number of households located in each micro watershed.

N o	Name of micro watershed	Program approach	Area in Ha	Population
N o	Name of micro watershed	Program approach	Area in Ha	HH	Sample size
1	Andhura Kosum Micro watershed	Free Mass Mobilization	759.5	734	112
2	Baraka Micro watershed	PNSP-PW	565.7	639	107
3	Burqa Water micro watershed	SLMP-II	853.1	765	118
			2178	2138	337

Where: Z = Z-value (1.96) for 95 confidence level

P = is the percentage picking a choice, expressed as a decimal (0.5)

C = is the confidence interval expressed as a decimal (0.05 = ±0.05)

Subsequently, the actual sample size for the study area was determined as:

(2)

{SS}_{pk} = \frac{s}{1 + \frac{s - 1}{p_{k}}}

Where: SS_kp is the sample size for the known population size

S is the sample size for the unknown population calculated using Equation 1

P_k is the known population size from which the sample size is calculated

Accordingly, 118 (35%) from Baraka, 107 (31.8%) from Burka Watter, and 112 (33.2%) from Adhura Kosum were randomly selected ( Table 1).

Focus group discussions: Alongside the quantitative household survey, five focus group discussions were held to gain a deeper understanding of watershed management. Each discussion group, comprising 7 to 9 participants, included a variety of viewpoints from different levels within the community. The participants were local residents, community leaders, stakeholders, and government experts. The goal of these discussions was to capture local perceptions, evaluate community needs, and review current watershed management practices. The use of open-ended questions encouraged dynamic conversation, yielding valuable qualitative insights.

Key informant interviews: Additionally, key informant interviews were conducted to collect detailed information on watershed management. These interviews targeted specific areas such as challenges, existing practices, and potential strategic improvements. Stakeholders, including policymakers, practitioners, and community leaders with specialized expertise, were chosen for their in-depth knowledge. This combined approach provided a broad array of perspectives and a thorough understanding of both watershed management and community involvement issues.

Secondary data: Secondary data were acquired through online research and the review of existing documents, including journal articles, books, and reports from reputable databases related to watershed management. Furthermore, office reports from government levels—woreda, zone, and regional offices—provided valuable quantitative and qualitative information. Access to these resources was secured through an official request letter. This secondary data was instrumental in supplementing and validating the primary data collected for the study.

Indicators measurement: To systematically assess community participation in watershed management, a comprehensive set of 23 participation indicators was developed through a rigorous process. This development was informed by extensive consultations with a variety of stakeholders, including the Kebele watershed committee, local elders, development agents, and the Woreda watershed technical committee. The process also incorporated guidance from participatory community-based watershed management guidelines outlined by Desta et al. (2005) and the Ministry of Agriculture (2020), ensuring that the indicators were both contextually relevant and methodologically sound, as supported by theoretical foundations from Roba et al. (2022) and Tesfaye et al. (2018) which underscored the significance of aligning local practices with empirical evidence while maintaining strict scientific standards. Moreover, their research highlighted the importance of understanding the community’s cultural, social, and economic contexts to ensure that the indicators effectively address specific needs and values. The involvement of these diverse groups ensured that the indicators were grounded in local realities and reflective of practical experiences.

The indicators were structured to address three key stages of watershed management: planning, implementation, and monitoring and evaluation. Specifically, eight indicators were allocated to the planning phase, nine to the implementation phase, and six to the monitoring and evaluation phase. Each indicator was assessed using a five-point Likert scale, ranging from 1 (very low) to 5 (very high). This scale allowed for a nuanced evaluation of farmer participation, capturing variations in engagement levels across the different stages of the management process. To categorize participation levels, farmers’ scores were analyzed, with those scoring at or above the average classified as active participants, while those scoring below the average were categorized as non-participants. This approach provided a detailed understanding of community involvement and facilitated targeted improvements in watershed management practices.

3.3 Statistical data analysis

The structured questionnaire data were organized and entered into the Statistical Package for the Social Sciences (SPSS) version 26 in a systematic manner for the purpose of conducting data analysis (https://www.ibm.com/support/pages/downloading-ibm-spss-statistics-26). To provide an overview of the respondents’ characteristics, descriptive statistics such as frequencies, percentages, means, and standard deviations were utilized. The binary logistic regression model was employed to identify significant factors that influenced the level of participation. People’s Participation Index (PPI) was also designed to compute the extent of people’s participation. People’s Participation index (PI) was established through the use of a modified formula (Bagdi & Joshi, 2018) to precisely quantify the level of farmers’ participation at the each stage of watershed management as follows.

(3)

{PP}_{i} = \frac{mean participation Score (P)}{Maximam participation Score} \times 1000

(4)

P = \frac{\sum_{i}^{N} P_{i}}{N}

Where, N = the total number of respondent

(5)

P_{i} = \sum_{i}^{N} ({PP}_{i} + {PI}_{i} + {PM}_{i})

where: PP_i is the total scores obtained by a respondent due to participation in program planning; PI_i is the total scores obtained by a respondent due to participation in program implementation; PM_i is the total scores obtained by a respondent due to participation in program monitoring and evaluation; K is the total number of statements on which responses of the respondents were recorded; P_i is the total participation scores obtained by individual respondent in planning, implementation, and maintenance.

The overall PPI was created by adding values of participation at the three stages, and the classification of the participation index into three categories was adopted based on Roba et al. (2022), Bagdi and Joshi (2018), and the normal distribution curve and standard deviation (SD). The mean and standard deviation (SD) of marks were used to separate participants into low, moderate, and high levels of participation ( Table 2).

Table 2. Categorization of people’s participation according to normal distribution curve values.

Normal distribution curve range	PPI value	PI category
1. < Mean-SD	< ±38.93	Low level
2. Mean-SD, to mean+SD	38.94-75.72	Moderate level
3. >Mean+SD	> ±75.73	High level

3.4 Variables and model specification

To examine the factors that influence farmers’ participation in watershed management practices the binary logistic regression model was used. This model allowed for the assessment of the relationship between an independent variable and the binary response variable, which in this case was the level of farmers’ participation. To apply the logistic regression model, the overall participation score was transformed into a dummy variable. The scores were categorized by grouping them according to the average participation score. This categorization did not affect the size and significance of the main effects, types of associations, or interactive effects (Talaei et al., 2023). The response is a binary variable, with a value of 1 indicating active or high participation if the score in indicator metrics is equal to or higher than the mean. Conversely, a value of 0 is assigned if the respondents’ score is lower than the mean in indicator metrics, categorizing them as less active. The overall participation score is then converted into a binary variable, represented as a dummy variable in Table 3. The Cronbach’s alpha reliability coefficient, which ranges from 0 to 1, was used to assess the scale’s internal consistency. The higher the value, the stronger the scale’s reliability (above 0.7).

Table 3. Summary results of overall participation.

Respondent	Participation level
Overall level of farmers participation	Less/non participation = 0
Overall level of farmers participation	Active participation = 1

The likelihood of farmers actively participating in the practice of watershed management, denoted as P_r (Y_i = 1), can be determined by evaluating a cumulative density function at X_iβ. In this context, X_i represents a set of explanatory variables, while refers to the parameters that need to be estimated. To model this cumulative density function, a logistic probability function can be employed, as described by Getacher and Tafere (2013).

(6)

P_{r} (Y_{i} = 1) = \frac{\exp (X_{i} β)}{1 + \exp (X_{i} β)}

The estimation form of this logistic transformation for the probability that a respondent will express a higher perception, P_r (Y_i=1) is represented as (Greene, 2002);

(7)

Ln [\frac{P_{r} (Y_{i} = 1)}{1 - P_{r} (Y_{i} = 1)}] = β_{0} + β_{1} X_{1} + β_{2} X_{2} + \dots β_{n} X_{n}

where P_r denotes the probability that the ith respondent had for active participation; X_i is a vector of explanatory variables; β is the parameters to be estimated. The dependent variable of this study is the level of farmers’ participation in watershed management practices, which is coded as 1 if the respondent had actively participated in the program and 0 otherwise. The study chose several explanatory variables, including age, sex, educational attainment, family size, total number of animals held, farmland size, frequency of extension contact, group membership, and distance from plot to home, as predictor variables to explain the level of community participation. These variables were selected based on the available data and their expected influence on participation in the study area, as well as on previous empirical literature on participation in watershed management practice. Table 4 presents the hypothesized explanatory variables used in the logistic model, along with their expected direction of association with the response variables.

Table 4. Explanatory variables included in the logistic regression model influencing farmers' level of participation.

Variables	Description	Measurement procedure	Expected sign
SEX	Sex of the household head	1 if male, otherwise 0	(Men are expected to be more involved than women)
AGE	Age of household head	Year	(Older people are more engaged than younger)
EDU	The educational level of the household head	1 unable to read and write otherwise educated	Educational achievement is expected to have positive outcome
FSIZE	Family size of of the household head	Number	Increase in familywise has expected to have positive out come
DISTANCE	Walking distance in Minutes from farm to home	Min.	Nearest farm have expected positive impact on watershed activities
TOTALLAND	Total land holding of the household head as a proxy indicator of income	Ha	Have more land hold have expectation of active participation
TLULSK	Livestock holding in TLU as a proxy indicator of income	TLU	Have more livestock holding have expectation of active participation
EXTNSSEVIC	Extension service provided	0 Yes otherwise 1	Accessing extension services is expected to have a positive outcome
COMTMBR	Member community watershed committee	0 Yes otherwise 1	Being committee member have given more opportunity of participation

4. Results and Discussion

4.1 Socio-demographic characteristics of the household

Table 5 presents the socio-demographic characteristics associated with the level of farmers’ participation. Among the respondents included in this study, 294 (87.2%) were males, while the remaining respondents were females. Regarding age distribution, approximately 19.6% of the farmers fell within the 18-30 years age group, 144 (42.7%) were aged between 31 and 45 years, 114 (33.8%) belonged to the 46-64 years age category, and 13 (3.9%) indicated that farmers above the age of 64 were included in the study. This suggests that the sample captured a diverse range of ages within the farming population. The educational background of farmers plays a crucial role in their farming activities and overall productivity. In this regard it was found that 191 (56.7%) had no formal education, 52 (15.4%) were able to read and write, 29 (8.6%) had completed grades 1 to 4 in primary school, 43 (12.8%) had completed grades 5 to 8 in secondary school, and 22 (6.5%) had completed grades 9 to 12. The significant portion of farmers lack basic skill and this highlights a the need for targeted educational and extension programs to enhance their knowledge and skills in watershed management. Furthermore, the average size of livestock holdings was determined to be 2.58 tropical livestock units (TLU). Livestock production holds significant importance as one of the primary agricultural activities.

Table 5. Socio-demographic characteristics of households.

Variables	Categories	Frequency	Percent
Sex of the household	Male	294	87.2
Sex of the household	Female	43	12.8
Age of the household	18-30	66	19.6
	31-45	144	42.7
	46-64	114	33.8
	>64	13	3.9
Educational level	No formal Education	155	46.0
	Read and write	89	26.4
	Primer (1-4)	46	13.6
	Secondary (5-8)	30	8.9
	Complete (9-120	17	5.0
Family size	1-3	65	19.3
	4-6	90	26.7
	7-10	172	51.0
	>10	10	3.0
Livestock holding LUT	No livestock	155	46.0
	1-5	135	40.1
	6-10	32	9.5
	>10	15	4.5
Total land holding in Hectare	≤.025	214	63.5
	.26-.0.5	95	28.2
	0.6-.99	19	5.6
	≥1	9	2.7

4.2 Community participation in different stages of watershed management

Effective watershed management practices are vital for tackling complex environmental and food security challenges. A key aspect of this effort is the involvement of various stakeholders, particularly the active participation of local communities, which is essential for successfully implementing management strategies (Mengistu & Assefa, 2021). The People Participation Index (PPI) revealed differing levels of farmer engagement across three micro watersheds, with greater participation linked to more effective and sustainable management outcomes. In contrast, lower levels of participation led to less favorable results, highlighting the importance of increased community involvement in improving watershed management effectiveness. A thorough analysis was carried out at each stage to ensure a comprehensive evaluation and enhancement of management practices.

4.2.1 Level of community participation in the planning phase

Table 6 illustrates the extent of farmers’ involvement during the planning phase. The People Participation Index (PPI) indicates a significant disparity in indicators, ranging from a relatively low 43.9% in terms of incorporating farmers’ opinions and suggestions in the planning process to a high level of 82.3% in promoting farmers’ awareness in the planning of watershed management. These results emphasize the varying levels of farmer participation observed in the planning process for watershed management. Furthermore, a statistical analysis using the chi-square test reveals a significant difference between the indicator metric among the three micro watersheds, with p-values of 0.01 and 0.05. The SLMP II micro watershed participant found more participants in the indicator metrics when compared with the PNSP-PW and free mass mobilization participants ( Table 6).

Table 6. Level of community participation in the planning stage of watershed management practices.

Watershed management practices at the planning stage	PNSP _PW N=118	SLMP _II N=107	Free Mass Mobilization N= 112	Total N=337	Chi-Square	P-Value
Watershed management practices at the planning stage	Freq&(%)	Freq&(%)	Freq&(%)	Freq&(%)	Chi-Square	P-Value
I have participated in an awareness-creation meeting organized and provided before watershed management planning.	94 (79.4)	93 (86.9)	88 (78.6)	275 (81.6)	18.26	0.019**
I took technical training on the CBPWM guidelines for proper watershed planning	82 (69.49)	73 (68.22)	54 (48.21)	209 (62.02)	32.05	0.00**
I have participated participation in PRA techniques like resource mapping, social mapping, transect walks, etc., following CBPWM principles.,	57 (48.3)	64 (59.8)	55 (49.1)	172 (51.16)	27.55	0.001**
I gave my suggestions, and information and raised ideas during the planning of the watershed management in my locality	70 (59.3)	55 (51.4)	52 (46.4)	176 (52.38)	16.985	0.030**
I feel my suggestions were taken into consideration	53 (44.9)	45 (42.1)	50 (44.6)	148 (43.87)	12.359	0.136
I am a witness that the poor and marginalized members of the community participate in the micro watershed planning	56 (47.5)	62 (57.9)	57 (50.9)	175 (52.1)	9.858	0.275
I actively participated during the election of Kebele watershed committee members	50 (42.4)	46 (43)	60 (53.6)	156 (46.31)	5.551	0.697
I have been participating in the process of watershed plan approval	62 (52.5)	57 (53.3)	56 (50.0)	175 (51.93)	11.95	0.153
Overall PPI %	55.5	57.8	52.6	55.2		0.852

However, when considering the overall level of farmers’ participation, PPI showed that all three micro watersheds exhibited a moderate level, with no statistically significant difference. Specifically, the SLMPII program had a participation rate of 57.8%, the PNSP-PW program had a rate of 55.5%, and the free mass mobilization program had a rate of 52.6%. This finding implies that despite advancements in metric indicators, the inclusiveness of watershed management planning remains lacking in all three micro watersheds. During focus group discussions at the community level, participants revealed that development agents, experts, and government representatives had exerted influence over the planning process in each micro watershed. Furthermore, they expressed that professionals often impose their ideas and solutions without fully understanding the needs and concerns of the farmers. This suggested that a hierarchical planning approach, where decisions are made at higher levels and implemented at lower levels, may not effectively address the challenges of farmers in their specific local contexts. This is in line with a study by Mawhorter (2010), which showed that natural resource management planning is predominantly controlled by professional experts in government agencies, limiting public engagement. Similarly, a study conducted in West Harraghe by Teressa (2018) found that government officials at the organizational level have the authority to make the majority of decisions, with limited involvement from the community. According to Félix et al. (2015), the planning process is significantly impacted by the officials rather than the concerns of the local community involved. However, success comes when people’s ideas and knowledge are valued, and power is given to them to make decisions independently of external agencies. Desta et al. (2005) also noted that a comprehensive planning approach that values input from a wide range of stakeholders is essential for holistic watershed management. Darghouth et al. (2008) also argue that for watershed management to be successful, community participation should start from the planning stage. In light of these findings, it becomes evident that engaging farmers in the planning process can result in the development of more tailored and efficient strategies that effectively address the needs, limitations, and challenges in their specific local environments.

4.2.2 Level of community participation in the implementation phase

Table 7 presents data on the level of involvement of farmers during the implementation phase of watershed management practices. The People Participation Index (PPI) showed a wide range of values, with a high of 88.08% actively contributing resources and labor to physical conservation efforts and a low of 33.22% participating in off-farm activities, indicating a lack of diversity in their watershed management efforts. Field observation during the study confirmed farmers’ enthusiastic participation in implementing physical conservation measures in the three micro watersheds studied. However, their engagement in watershed management bylaws, forage development, crop production, and off-farm activities was comparatively lower, implying that these activities were not recognized and considered as the component of the comprehensive watershed management approach. Furthermore, the chi-square statistical analysis revealed a significant discrepancy among the indicator metrics across all three micro watersheds. The SLMP II micro watershed participation was found significant as compared to the PNSP-PW and Free Mass Mobilization micro watersheds, with a P-value of 0.001 and 0.03, respectively ( Table 7).

Table 7. Level of community participation at the implementation stage of watershed management practices.

Watershed management practices at the implementation stage	PNSP N=118	SLMP II N= 107	Free Mass Mobilization N=112	Total N=337	Chi-Square (X ²⁾	P-Value
Watershed management practices at the implementation stage	Score&%	Score&%	Score&%	Score&%	Chi-Square (X ²⁾	P-Value
I have participated in technical training that acquire the knowledge and skills required for practical implementation	51 (43.2)	74 (69.2)	49 (43.8)	174 52.60	1.07	0.001**
My family members a participants in the community's watershed management practices.	78 (66.1)	73 (68.5)	96 (85.7)	247 73.32	16.669	0.03*
I have participated in contributing resources such as labor, money, and so on during watershed implementation	107 (90.7)	94 (87.9)	96 (85.7)	297 (88.08)	11.891	0.152
I have participated in physical soil and water conservation both on my own farm/common land in the watershed	99 (83.9)	91 (85.0)	93 (83.0)	283 (83.9)	11.276	1.87
I have participated in and practiced forage development or livestock development activities as part of the watershed	47 (39.8)	33 (30.8)	50 (44.6)	130 (38.44)	16.614	0.83
I have participated in and practiced crop production and improved crop varieties as part of the watershed management practice	40 (33.9)	38 (35.5)	39 (34.8)	117 34.74	52.79	0.00**
I have participated in off-farm income-generation activities as part of the watershed management practice	37 (31.4)	39 36.4	35 (31.3)	111 (33.02)	41.94	0.00**
I have participated in supervising the ongoing activities/works undertaken in the fields and community lands	49 (41.5)	41 (38.3)	41 (36.6)	131 (38.82)	34	0.90
I have participated in developing watershed management bylaws	50 (42.4)	46 (43)	57 (50.9)	153 (45.42)	5.55	0.69
Overall PPI %	52.80	55.12	53.00	53.30		0.893

However, throughout the implementation phase, the people participation index revealed that the overall level of farmers participation in all three micro watersheds had moderate levels, with no statistically significant variances (P= 0.852). The participation rate for SLMP II stood at 55.12%, PNSP_PW at 52.8%, and Free Mass Mobilization at 53.00%. These findings indicate that the level of involvement in implementing watershed management initiatives is relatively similar across all three micro watersheds. Discussions conducted with focus groups and key informants in the community have confirmed the tendency to prioritize physical conservation measures over a holistic approach in watershed management implementation. This inclination may be due to knowledge gaps that hinder the comprehensive implementation of watershed practices. This finding aligns with Sangchini (2023) who emphasizes the role of knowledge in facilitating effective participation in watershed management. Similarly, Akello et al. (2017) and Mutune & Nunow (2018) have highlighted the connection between community involvement in watershed management and their understanding of integrated watershed management. Additionally, Biswas et al. (2012) study demonstrated that knowledge-based entry-point activities significantly influenced the extent of community participation. The inclusive and active participation of farmers in all aspects of watershed management is crucial for the successful implementation of watershed management practices in practical situations, thus contributing to the improvement of food security (Roba et al., 2022; Brombal et al., 2018; Montemayor, 2023).

4.2.3 Level of community participation in the Monitoring and evaluation phase

Table 8 illustrates the level of farmer involvement in the monitoring phase of watershed management practices. Variability is observed in the monitoring and evaluation stage across different parameters, with some activities showing high participation levels and others showing lower levels. For instance, the People Participatory Index (PI) indicates a high level of engagement in maintaining physical aspects regularly (61.8), while there is moderate involvement in regularly assessing quantity and quality of work (46.5%) and low in the decision-making process is low (43.0%). Furthermore, the chi-square analysis reveals significant differences among the indicator metrics, with SLMP demonstrating better performance when compared to PNSP and Free Mass Mobilization. The results obtained from the Focus Group Discussions and Key Informant interviews also confirmed the assertion that SLMP II places a significant emphasis on the continuous monitoring of both the quantity and quality of work carried out. Moreover, the statistical analysis, specifically the F-test result of 6.763 and P= 001, provides additional evidence supporting the notion that SLMPII holds a statistically significant position when compared to the other two programs.

Table 8. Level of community participation in the monitoring and evaluation phase.

Watershed management practices at the planning stage	PNSP _PW N = 118	SLMP _II N = 107	Free Mass Mobilization N = 112	Total N = 337	Chi-Square (χ²)	P-Value
Watershed management practices at the planning stage	Freq&%	Freq&%	Freq&%	Freq&%	Chi-Square (χ²)	P-Value
I have actively participated in all stages of watershed management monitoring and evaluation based on existing community organizations and checked the overall performance	50 (42.4)	50 (46.7)	45 (40.2)	145 (43.1)	10.775	0.215
I attended regular meetings to discuss watershed management actions while in operation	56 (47.5)	48 (44.9)	47 (42.0)	151 (44.8)	14.83	0.062
I have participated in the protection of area closure and other rehabilitated watershed areas in the micro watershed	51 (43.2)	44 (41.1)	50 (44.6)	145 (43.0)	20.282	0.009**
I participated in the decision-making process for the micro watershed.	47 (39.8)	48 (44.9)	44 39.3	139 (41.3)	23.629	0.003**
I regularly checked the quantity and quality of work in line with the Community-based Watershed Management Guidelines.	50 (42.4)	57 (53.3)	49 (43.8)	156 (46.5)	34.599	0.000**
I have participated regularly in the maintenance of the physical conservation activities undertaken in the micro watershed	69 (58.5)	69 (64.5)	70 (62.5)	208 (61.8)	18.201	0.020**
Overall PPI %	45.6	49.2	45.4	46.7

However, the overall Farmers’ Participation Index (PPI) for all three program approaches was also calculated as (45.6%) for the PNSP, (49.2%) for the SLMPII, and (45.4%) for Mass Mobilization, indicating all of them fall under a moderate level of participation with statistically no significant difference between the three program approaches p-value = 0.590. The key informant interviews and focus groups also revealed that the kebele administrative structure did not consider monitoring and evaluation as part of the watershed management activities. They believed that monitoring and evaluation is tasks should be carried out by government officials, extension workers, or other professionals. The results of this study indicate that the lack of comprehensive monitoring and evaluation in all three micro-watersheds is the main factor contributing to the ineffectiveness of watershed management. This is in line with studies by Yusuf et al. (2020), who found that community participation in decision-making is essential for sustainable development. A study carried out in Nigeria by Tadesse et al. (2017) discovered a significant relationship between community participation in monitoring and evaluation and the sustainability of development projects. Gebregziabher et al. (2016) also suggest that many program failed as a result of a lack of community involvement in the monitoring and evaluation phase. This study’s findings higher-level government organizations did not fully recognize farmer engagement in monitoring and evaluation as key components of watershed management practice.

4.2.4 Overall People’s Participation in Watershed Development Programs

Table 9 illustrates the extent of farmers’ involvement at various stages of watershed management practice. The findings indicate that 55.2% of farmers participated in the planning stage, 53.6% in the implementation stage, and 46.73% in the monitoring and evaluation stage which is found to moderate. However, it was discovered that participation during the monitoring and evaluation phase was lower than the planning and evaluation phase that needs to be addressed. The finding also showed similarly moderate in overall level farmers participation in the three micro watershed 54.0 % for SLMP II, 51.3%, PNSP_PW and 50.3%, for Free Mass Mobilization. The study’s findings also showed that farmers in the three micro watersheds were more focused on physical conservation measures than comprehensive involvement in all indicator measurements. However, farmers’ participation in physical conservation alone would not be enough for effective watershed management for food security improvement. This is in line with studies by Bantider et al. (2019) and Biswas et al. (2012), who demonstrated that watershed management includes not only physical conservation but also integrated resource management targeted at lowering poverty and food insecurity. Furthermore, efforts must be made to increase farmers’ inclusive engagement at each stage of watershed management.

Table 9. Overall level of community participation in planning, implementation monitoring, and evaluation phases.

	PNSP-PW	SLMP II	Free mass mobilization	Total
Planning	55.5	57.8	52.6	55.2
Implementation	52.8	55.12	53	53.6
Monitoring and Evaluation	45.6	49.2	45.4	46.7
Overall PPI	51.3	54.0	50.3	51.8

4.3 Factors affecting level of community participation in watershed management

Table 10 presents the results of the binary logistic regression model, which investigated the influence of various factors on farmers’ involvement in watershed management practices at different stages. The regression analysis demonstrated that demographic, socioeconomic, and biophysical factors all played a significant role in farmers’ participation. The fitted model was statistically significant (x2 = 215.68, P = 0.00), indicating its strong explanatory capability. The Nagelkerke R Square value suggests that 82% of the variations in the level of participation can be explained by the explanatory variables examined in the study. Among the nine explanatory variables investigated in the binary regression model, all of them demonstrated statistical significance at both the 1% and 5% probability levels.

Table 10. Results of logistic regression model analysis.

Variables	B	S.E.	Wald	df	Sig.	Exp(B)	95% CI. for EXP(B)
Variables	B	S.E.	Wald	df	Sig.	Exp(B)	Lower	Upper
Sex of the household(1)	-1.027	0.352	8.512	1	0.004	0.358	0.18	0.714
Extension advice service (1)	9.13	1.16	61.957	1	0.000	9226.667	950.03	89609.05
Member community watershed committee(1)	2.733	0.312	76.564	1	0.000	15.38	8.339	28.369
Educational level			95.728	4	0.000
Educational level(1)	2.063	0.301	46.956	1	0.000	7.867	4.361	14.191
Educational level(2)	4.049	0.63	41.303	1	0.000	57.333	16.678	197.093
Educational level(3)	3.258	0.573	32.286	1	0.000	26	8.451	79.993
Educational level(4)	3.401	0.779	19.058	1	0.000	30	6.516	138.13
Distance from farm plot to home in Min.			54.655	3	0.000
Distance from farm plot to home in Min.(1)	3.904	0.765	26.042	1	0.000	49.593	11.073	222.114
Distance from farm plot to home in Min.	2.814	0.756	13.844	1	0.000	16.679	3.788	73.446
Distance from farm plot to home in Min.(3)	-1.478	1.247	1.404	1	0.236	0.228	0.02	2.629
Age of farmer			62.247	3	0.000
Age of farmer(1)	2.02	0.433	21.751	1	0.000	7.541	3.226	17.628
Age of farmer(2)	3.453	0.461	56.099	1	0.000	31.607	12.803	78.027
Age of farmer(3)	2.943	0.722	16.622	1	0.000	18.964	4.609	78.035
Constant	-2.132	0.4	28.433	1	0.000	0.119
family size			108.56	3	0.000
family size(1)	0.281	0.884	0.101	1	0.750	1.325	0.234	7.493
family size(2)	4.991	0.748	44.522	1	0.000	147.121	33.958	637.39
family size(3)	5.223	1.289	16.417	1	0.000	185.5	14.828	2320.652
Livestock holding			120.53	3	0.000
Livestock holding (1)	4.169	0.4	108.62	1	0.000	64.665	29.524	141.635
Livestock holding (2)	6.345	1.064	35.583	1	0.000	569.9	70.848	4584.294
Livestock holding (3)	23.835	10048.24	0	1	0.998	2.246	0

The results of the logistic regression analysis showed a significant and positive relationship between gender and the level of involvement. This suggests that male participants had a higher level of participation compared to females (b = 1.027, P = 0. 0.004; Table 10). Gender norms play a significant role in shaping the level of gender participation in development activities. It is observed that men tend to be more actively involved in such activities, whereas women are predominantly burdened with childcare and household chores. This finding aligns with the outcomes of a study conducted by Nasrabadi et al. (2013) revealed that the multitude of responsibilities shouldered by women significantly hinders their level of participation in development activities. The relationship between extension contacts and community participation in watershed management practices has been found to be significant and positive across all stages. This indicates that farmers who have access to extension services are more likely to actively participate compared to those who do not have access to such services (b = 9.13, P = 0.00; Table 10). Access to extension contacts can empower farmers with knowledge, skills, and resources, enabling them to actively contribute to the sustainable management of their local watersheds. This is in line with a study by Getacher and Tafere (2013),which found a significant and positive correlation between participation level and technical knowledge regarding watershed management. Being a member of a community-based watershed management program is a significant indicator of participation. The odds ratio for this predictor indicates that farmers who are part of the community watershed management and operate in the nearby area are 9.95 times more inclined to participate compared to those who are not engaged in the committee. This suggests that efforts should be made to encourage farmers to join community-based watershed management programs and to create an enabling environment that supports their active involvement. The binary logistic regression marginal effect analysis further confirms for every unit increase in the distance of farmland from the homestead, there is a 4.6% decrease in the likelihood of participation in watershed management. This could be due to various factors such as the inconvenience of traveling long distances to participate, lack of awareness or understanding of the importance of watershed management, or limited resources and capacity to engage in such activities. The result is consistent with research by Sangchini (2023) on forest management, which identifies distance as a significant factor influencing households’ participation.

Educational level of individuals is another important factor consistently and positively influenced community participation in all stages of watershed management methods. The odds ratio of 30.00 indicates a significant difference in participation rates between individuals with higher and lower educational attainment. Farmers with a higher level of education in the area are 30.00 times more likely to engage in participation compared to those with lower educational attainment. This suggests that education plays a crucial role in fostering a sense of responsibility and awareness among individuals, leading to increased involvement in watershed management initiatives. Sex of the household, Livestock holding (LUT), significantly contribute to farmers’ participation in watershed programs.However, the level of participation has not demonstrated any significant correlation with the coefficient of land holdings size. This is contradictory to Chala and Reddy (2014) and Mosisa et al. (2018) reported that farmers with larger plots have more opportunities to participate in conservation activities.

The results from Focus Group Discussions and Key Informant interviews also further confirmed that the level of participation was significantly impacted by the lack of strong local leadership that prioritizes farmers’ needs and interests at different decision-making levels as well as the inconsistent training provided to farmers in every aspect of the development of the watershed. The lesson learned from this study indicates that, despite achievements in some biophysical aspects of watershed management activities, the sustainability of the practices as a comprehensive approach to tackling the pervasive issues of food insecurity and poverty was not fully realized. As a result, to ensure the successful implementation of the watershed management practice, policymakers and extension workers need to focus on education and extension services.

5. Conclusions and recommendations

The study examined the extent and factors influencing farmers’ engagement in the execution of watershed management across three distinct program approaches. The result of the finding indicated that farmers’ involvement in all three micro watersheds was moderate, with no significant discrepancies in any phase of watershed management activities. However, variations were noted in indicators metrics with statistical significance in all three micro watersheds throughout various stages of watershed management. The study findings also revealed that the watershed management practices were biased toward physical conservation measures over comprehensive watershed management in all three micro watersheds. As a result, the strategy did not develop into a comprehensive approach to address the widespread problems of food insecurity and poverty.

Additionally, the findings indicated that the concerns and interests of the local communities were not taken into account in the planning process, with government officials and experts exerting a significant influence on the decision-making procedures. As a result, the comprehensive strategies for watershed management fell short of their intended effectiveness. Moreover, variables such as extension service, educational attainment, leadership qualities, and livestock ownership also influenced the extent of farmers’ engagement throughout all stages of watershed management. To ensure the inclusive and active participation of the farmers in sustainable watershed management, enhance knowledge, facilitate capacity development, and foster a sense of ownership rather than simply providing them with instructions or guidelines to adhere to is imperative.

Contribution of the author

Tena Gobena designed and carried out the research, gathered the data, examined and analyzed the results, and wrote the paper. Amare Bantider, Messay Mulugeta, and Ermias Teferi conducted the research, provided analytical tools, and edited and wrote the manuscript. All authors made substantial contributions to the conception of the work, analyses, and interpretation of data and approved the final version to be published.

Ethical considerations

This study was granted ethical approval consent from the Institutional Review Board (IRB) of College of Development Studies (CoDS) of Addis Ababa University on 30/12/2023 with Reference Number of 050/03/2023. Further detail on the letter can be requested from the IRB board via the email: cods.irb@aau.edu.et.

Informed verbal consent was obtained from all study participants to accommodate varying literacy levels. Many individuals faced difficulties with written consent, which could lead to misunderstandings. Verbal consent ensured that participants understood the study’s objectives and their rights, with approval from the ethical review board. Household respondents and focus group participants were informed about the study’s goals, their voluntary participation, and their right to refuse questions or withdraw at any time. Key informants received a detailed overview of the research objectives and benefits for the community, with assurances of no political or legal repercussions. They were also given contact information for research supervisors for any issues during interviews. Official letters of cooperation were sent to relevant bureaus and offices to communicate the research’s aims.

Consent for publication

Not applicable.

Data availability

Underlying data

This project contains the following underlying data:

Data verse: Scaling up community participation in watershed management for food security improvement: the case of Qarsa woreda, East Haraghe zone, Ethiopia, https://doi.org/10.6084/m9.figshare.26110306.v1 (Gobena et al., 2024).

Details of license: CC0

This data file contains three data files of which one is in the excel form, the second is in word form and the third data file deals with the PDF file. The excel file contains all necessary primary data about watershed and demographic data used to determine factors affecting watershed management effects on food security status of households in the study area, Qarsa woreda. While the word document consists of basic data collection tools used for household survey and qualitative data colection process. Besides this, the word document contains of the extended data transcripts of Focus Group Discussions (FGD) and Key Informant Interviews (KII) results.

Acknowledgments

First, let us give thanks to God for this day and time. Second, we thank all the respondents’ farmers and experts for their cooperation in providing the data for this study.

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Snyder KA, Ludi E, Cullen B, et al.: Participation and performance.:Decentralised planning and implementation in ethiopia. Public Adm. Dev. 2014; 34(2): 83–95. Publisher Full Text
Tadesse S, Woldetsadik M, Senbeta F: Forest users’ level of participation in a participatory forest management program in southwestern Ethiopia. For. Sci. Technol. 2017; 13(4): 164–173. Publisher Full Text
Talaei R, Salehpour A, Beyrami B: Prioritization of Factors Influencing People’ s Participation in Watershed Management Projects of Siyahposh Basin, Ardabil Province, Iran. Water Harvesting Rsearch. 2023; 6(1): 70–87.
Taye T: Evaluating Implication of Long Term Watershed Development on Plant Diversity Dynamics in Maybar Sub-Watershed, South Wello Zone, Ethiopia.2021. Publisher Full Text
Tefera M, Hailemichael A, Teshome A: Integrated Watershed Management (IWM) in Ethiopia: A baseline study in Dire Dawa, Deder and Zeway Dugdar (Issue September).2020.
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Tesfahun AA, Chawla PAS: People’s Participation in Development: The Actors and Factors Shaping People’s Participation in Environmental Conservation Initiatives in Eferatena Gidem District, Ethiopia. Public Police and Adiminstration Research. 2017; 7(3): 1–17. ISSN 2224-5731. Reference Source
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Author details Author details

¹ Addis Ababa University College of Development Studies, Addis Ababa, Addis Ababa, Ethiopia

Tena gobena
Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Validation, Writing – Original Draft Preparation, Writing – Review & Editing

Amare Bantider
Roles: Conceptualization, Formal Analysis, Investigation, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

Messay Mulugeta
Roles: Conceptualization, Formal Analysis, Investigation, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

Ermias Teferi
Roles: Conceptualization, Formal Analysis, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

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The author(s) declared that no grants were involved in supporting this work.

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gobena T, Bantider A, Mulugeta M and Teferi E. Scaling up community participation in watershed management for food security improvement: the case of Qarsa woreda , East Haraghe zone, Ethiopia [version 1; peer review: 1 approved, 1 approved with reservations]. F1000Research 2025, 14:244 (https://doi.org/10.12688/f1000research.153669.1)

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Reviewer Report 21 Apr 2025

Jesús López-Santiago, Universidad Politecnica de Madrid, Madrid, Community of Madrid, Spain

Approved with Reservations

https://doi.org/10.5256/f1000research.168591.r371731

I think that the research addresses a crucial and timely topic. The manuscript provides rich empirical data from Ethiopia’s Qarsa woreda and offers practical recommendations for scaling community-based approaches in watershed programs. In my opinion, the study is generally well-conceived, ... Continue reading

I think that the research addresses a crucial and timely topic. The manuscript provides rich empirical data from Ethiopia’s Qarsa woreda and offers practical recommendations for scaling community-based approaches in watershed programs. In my opinion, the study is generally well-conceived, with a clear conceptual framework and sound statistical methodology. However, some key limitations are noted below related to structure, novelty positioning, theoretical framing, and policy implications. So, I recommend some revisions.

Regarding my answers to reviewer question as “partly”, I must say that the manuscript is well-structured and presents its findings in a logical manner, but it suffers from repetitive phrasing, minor grammatical issues, and table formatting errors. The literature cited is generally relevant and includes foundational works and regional studies. However, the inclusion of more recent and globally current literature, post-2020, would enhance the scientific depth and context of the study. Besides, the conclusions are generally supported by empirical results, especially in identifying moderate levels of participation and key influencing factors. However, the discussion could better differentiate between findings across the three program types and offer more targeted recommendations. A stronger alignment between discussion and conclusion sections would help reinforce the study's implications.

The authors should better position their work within this existing body of literature by clearly stating what new insights this study provides, as triangulation of qualitative and quantitative methods or practical implications for program scalability.

About the methodology, the mixed method design is robust, and also, the use of binary logistic regression model and Cronbach’s alpha. However, sample selection, though statistically justified, should more clearly explain how generalizable the findings are to other woredas or regions with different agroecological or socio-cultural settings. And the PPI computation methodology should be detailed in an annex or supplementary material for reproducibility.

In Results sections, it´s important consider clarity and writing. Especially, the Tables 6, 7 and 8 contain incomplete or placeholder values ("I h…", "My…"), which compromise clarity and suggest formatting errors that should be corrected before publication.
In the Discussions section, it should be interesting to include more references to current watershed policy frameworks, for example, Ethiopia’s Green Legacy or climate-smart agriculture initiatives.
Regarding the Conclusions and Recommendations, I think that recommendations could be expanded with specific guidance for scaling, for example, how can extension systems be restructured? What incentives or institutional innovations are needed?

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Food safety, food security and environmental management

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

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Reviewer Report 28 Mar 2025

Molly Elizabeth Brown, University of Maryland at College Park, College Park, Maryland, USA

Approved

https://doi.org/10.5256/f1000research.168591.r369269

This paper reports the results of 337 household surveys, focus group discussions and key informant interviews. The data are used in a regression model to assess the level of community involvement in watershed management in Ethiopia.

The ... Continue reading

This paper reports the results of 337 household surveys, focus group discussions and key informant interviews. The data are used in a regression model to assess the level of community involvement in watershed management in Ethiopia.

The paper suffers from a significant number of typos and spelling issues, poor quality figures and some concerns with the presentation. However, with editing the paper can be strong and acceptable for indexing.
Specific comments:

Please use a spell checker throughout. Many of the typos are obvious and easy to fix with any word processing software. For example, the misspelled words in the abstract conclusions, Keywords and Figure 2 legend. There are many more.
The figures need to be much higher quality. Figure 1 is a screenshot where the authors leave the ‘select’ icons around it. A higher resolution is needed.
Figure 2 is fuzzy and of very low resolution. I would recommend having the ‘background’ be white and not the blue-green color. The watersheds should show on the Ethiopia map – although there is a legend entry that says ‘Boundary of study area’ it is not actually visible on the map. I also think you need to situate Ethiopia in the African continent, since not everyone knows where it is located.
Page 4, paragraph on ‘pragmatic approach’ the authors should state why it is important for communities to have a ‘voice’ in decisions that will affect their lives. It is not just a nice thing to do – it is the difference between an effective policy that will result in actual changes and one that is on paper only. You make this point in the subsequent paragraph (‘to ensure the success of watershed management programs’), but it should be made much more directly here too. Define ‘success’
Section 3.1 needs more description of the differences between the three watersheds – why not present the three together? Why do the authors expect differences between the three areas, although the results continually show that they are very similar? Perhaps describe the objectives of the three projects, the differences in environmental challenges, or the culture of the regions? More clear theory here will make the description of the results more comprehensible – currently the fact that the involvement of the community is very similar across the three watersheds seems to baffle the authors.
This idea from section 4.2.2:

‘Discussions conducted with focus groups and key informants in the community have confirmed the tendency to prioritize physical conservation measures over a holistic approach in watershed management implementation. This inclination may be due to knowledge gaps that hinder the comprehensive implementation of watershed practices.’

Should be introduced more explicitly in section 1 and be put in the abstract results.

I think the results could be trimmed significantly, moving some of the results to a supplementary section. However, the paper will be of interest to some readers as-is.

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: I am a quantitative social scientist, working to bring environmental and climate data together with household survey data to derive understandings of the impact of development, extreme weather events and economic change on human health.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

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Molly Elizabeth Brown, University of Maryland at College Park, College Park, USA
Jesús López-Santiago, Universidad Politecnica de Madrid, Madrid, Spain

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21 Apr 2025 | for Version 1

Jesús López-Santiago, Universidad Politecnica de Madrid, Madrid, Community of Madrid, Spain

3 Views Cite this report Responses(0)

Approved With Reservations

I think that the research addresses a crucial and timely topic. The manuscript provides rich empirical data from Ethiopia’s Qarsa woreda and offers practical recommendations for scaling community-based approaches in watershed programs. In my opinion, the study is generally well-conceived, with a clear conceptual framework and sound statistical methodology. However, some key limitations are noted below related to structure, novelty positioning, theoretical framing, and policy implications. So, I recommend some revisions.

Regarding my answers to reviewer question as “partly”, I must say that the manuscript is well-structured and presents its findings in a logical manner, but it suffers from repetitive phrasing, minor grammatical issues, and table formatting errors. The literature cited is generally relevant and includes foundational works and regional studies. However, the inclusion of more recent and globally current literature, post-2020, would enhance the scientific depth and context of the study. Besides, the conclusions are generally supported by empirical results, especially in identifying moderate levels of participation and key influencing factors. However, the discussion could better differentiate between findings across the three program types and offer more targeted recommendations. A stronger alignment between discussion and conclusion sections would help reinforce the study's implications.

The authors should better position their work within this existing body of literature by clearly stating what new insights this study provides, as triangulation of qualitative and quantitative methods or practical implications for program scalability.

About the methodology, the mixed method design is robust, and also, the use of binary logistic regression model and Cronbach’s alpha. However, sample selection, though statistically justified, should more clearly explain how generalizable the findings are to other woredas or regions with different agroecological or socio-cultural settings. And the PPI computation methodology should be detailed in an annex or supplementary material for reproducibility.

In Results sections, it´s important consider clarity and writing. Especially, the Tables 6, 7 and 8 contain incomplete or placeholder values ("I h…", "My…"), which compromise clarity and suggest formatting errors that should be corrected before publication.
In the Discussions section, it should be interesting to include more references to current watershed policy frameworks, for example, Ethiopia’s Green Legacy or climate-smart agriculture initiatives.
Regarding the Conclusions and Recommendations, I think that recommendations could be expanded with specific guidance for scaling, for example, how can extension systems be restructured? What incentives or institutional innovations are needed?

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Food safety, food security and environmental management

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

Respond to this report

Responses (0)

Back to all reports

Reviewer Report

2 Views

28 Mar 2025 | for Version 1

Molly Elizabeth Brown, University of Maryland at College Park, College Park, Maryland, USA

2 Views Cite this report Responses(0)

Approved

This paper reports the results of 337 household surveys, focus group discussions and key informant interviews. The data are used in a regression model to assess the level of community involvement in watershed management in Ethiopia.

The paper suffers from a significant number of typos and spelling issues, poor quality figures and some concerns with the presentation. However, with editing the paper can be strong and acceptable for indexing.
Specific comments:

Please use a spell checker throughout. Many of the typos are obvious and easy to fix with any word processing software. For example, the misspelled words in the abstract conclusions, Keywords and Figure 2 legend. There are many more.
The figures need to be much higher quality. Figure 1 is a screenshot where the authors leave the ‘select’ icons around it. A higher resolution is needed.
Figure 2 is fuzzy and of very low resolution. I would recommend having the ‘background’ be white and not the blue-green color. The watersheds should show on the Ethiopia map – although there is a legend entry that says ‘Boundary of study area’ it is not actually visible on the map. I also think you need to situate Ethiopia in the African continent, since not everyone knows where it is located.
Page 4, paragraph on ‘pragmatic approach’ the authors should state why it is important for communities to have a ‘voice’ in decisions that will affect their lives. It is not just a nice thing to do – it is the difference between an effective policy that will result in actual changes and one that is on paper only. You make this point in the subsequent paragraph (‘to ensure the success of watershed management programs’), but it should be made much more directly here too. Define ‘success’
Section 3.1 needs more description of the differences between the three watersheds – why not present the three together? Why do the authors expect differences between the three areas, although the results continually show that they are very similar? Perhaps describe the objectives of the three projects, the differences in environmental challenges, or the culture of the regions? More clear theory here will make the description of the results more comprehensible – currently the fact that the involvement of the community is very similar across the three watersheds seems to baffle the authors.
This idea from section 4.2.2:

‘Discussions conducted with focus groups and key informants in the community have confirmed the tendency to prioritize physical conservation measures over a holistic approach in watershed management implementation. This inclination may be due to knowledge gaps that hinder the comprehensive implementation of watershed practices.’

Should be introduced more explicitly in section 1 and be put in the abstract results.

I think the results could be trimmed significantly, moving some of the results to a supplementary section. However, the paper will be of interest to some readers as-is.

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

I am a quantitative social scientist, working to bring environmental and climate data together with household survey data to derive understandings of the impact of development, extreme weather events and economic change on human health.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Respond to this report

Responses (0)

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[45] Sangchini EK: Evaluation of watershed management projects implemented in terms of improving the spirit of public participation in Rimeleh Watershed, Watershed Enginering and development Lorestan Province.2023; 15(3): 452–466. Publisher Full Text

[46] Snyder KA, Ludi E, Cullen B, et al.: Participation and performance.:Decentralised planning and implementation in ethiopia. Public Adm. Dev. 2014; 34(2): 83–95. Publisher Full Text

[47] Tadesse S, Woldetsadik M, Senbeta F: Forest users’ level of participation in a participatory forest management program in southwestern Ethiopia. For. Sci. Technol. 2017; 13(4): 164–173. Publisher Full Text

[48] Talaei R, Salehpour A, Beyrami B: Prioritization of Factors Influencing People’ s Participation in Watershed Management Projects of Siyahposh Basin, Ardabil Province, Iran. Water Harvesting Rsearch. 2023; 6(1): 70–87.

[49] Taye T: Evaluating Implication of Long Term Watershed Development on Plant Diversity Dynamics in Maybar Sub-Watershed, South Wello Zone, Ethiopia.2021. Publisher Full Text

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[53] Tesfahun AA, Chawla PAS: People’s Participation in Development: The Actors and Factors Shaping People’s Participation in Environmental Conservation Initiatives in Eferatena Gidem District, Ethiopia. Public Police and Adiminstration Research. 2017; 7(3): 1–17. ISSN 2224-5731. Reference Source

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Scaling up community participation in watershed management for food security improvement: the case of Qarsa woreda , East Haraghe zone, Ethiopia

Abstract

Background

Methods

Result

Conclusions

Keywords

1. Introduction

2. Conceptual framework of study

Figure 1. Conceptual framework showing participation indicators and their explanatory factors.

3. Methods

3.1 Description of the study area

Figure 2. Map of the Study Area (Sources: constrcated by authours).

3.2 Study design, sample size and data collection methods

(1)

Table 1. A list of micro watersheds and the number of households located in each micro watershed.

(2)

3.3 Statistical data analysis

(3)

(4)

(5)

Table 2. Categorization of people’s participation according to normal distribution curve values.

3.4 Variables and model specification

Table 3. Summary results of overall participation.

(6)

(7)

Table 4. Explanatory variables included in the logistic regression model influencing farmers' level of participation.

4. Results and Discussion

4.1 Socio-demographic characteristics of the household

Table 5. Socio-demographic characteristics of households.

4.2 Community participation in different stages of watershed management

Table 6. Level of community participation in the planning stage of watershed management practices.

Table 7. Level of community participation at the implementation stage of watershed management practices.

Table 8. Level of community participation in the monitoring and evaluation phase.

Table 9. Overall level of community participation in planning, implementation monitoring, and evaluation phases.

4.3 Factors affecting level of community participation in watershed management

Table 10. Results of logistic regression model analysis.

5. Conclusions and recommendations

Contribution of the author

Ethical considerations

Consent for publication

Data availability

Underlying data

Acknowledgments

References

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