Delectus copyright
Delectus - Scientific Journal, Inicc-Perú - [ISSN: 2663-1148]




Vol. 4 No. 1 (2021): January-June [Edit closure: 01/01/2021]

RECEIVED: 29/09/2020 | ACCEPTED: 24/12/2020 | PUBLISHED: 01/01/2021

Suggested quote (APA, seventh edition)

Arévalo Quijano, J. C., Barrial Lujan, A. I., Huamán Carrión, M. L., Delgado Laime, M. D. C., & Antay Ccaccya, R. (2021). Factors that Influence the Payment for Hydro-Ecosystem Services of The Chumbao River Micro-Basin. Delectus, 4(1), 107-118.

Factors that influence payment for hydro-ecosystemic services in the Chumbao River micro-basin











The objective of this work was to evaluate the factors that influence the availability of economic payment of irrigation users for hydro-ecosystemic services of provision to improve conservation actions of the Chumbao river micro-basin. For this analysis, the Contingent Assessment Method was used through logistic regression analysis. The procedure begins with the application of 310 surveys to irrigation users in the communities of the Chumbao valley - Apurímac region. The results were analyzed with the statistical test criterion P <0.05, finding 4 of 5 factors that affect the payment for hydro-ecosystem services; and in turn, with the 98.11% predictive model, it was determined that irrigation users are willing to pay a monthly fee of s / 2.00. Finally, the factors: hypothetical amount, level of education, water quality and quantity index, and number of members per family significantly influence the availability of payment.

Keywords: Willingness to Pay; Chumbao Micro-Basin; Water Ecosystem; Irrigation User.

Ecosystem services (ES) allow us to identify the direct and indirect ways in which we depend on the environment. The headwaters of the Chumbao River micro-basin represent one of the most important high Andean ecosystems in the district of San Jerónimo, Andahuaylas and Talavera, in the Apurimac region, because they generate multiple environmental services and/or benefits, economic and social, to the population of the city of Andahuaylas, and with greater influence of the agricultural and industrial production system (GOREAP, 2019).

ES are defined as benefits obtained from nature that satisfy human needs (MEA., 2005). Watersheds provide ES of great value to society, such as drinking water supply (provisioning services), soil erosion control (regulating services), wildlife habitat (support services), and aquatic recreation (cultural services) (Smith, De Groot, Perrot, & Bergkamp, 2006). On the other hand, the hydro-ecosystem services or also called water ecosystem services, date back to 2000 when the second World Water Forum was held in The Hague - Netherlands, event where the "economic value" of water was reinforced. And the concept of the Integrated Management of Water Resources was adopted, according to it. Given that water ecosystem services are directly linked to the availability of water resources (in terms of quality and quantity), the Ministry of the Environment identified MERESE by type of water resource user, so as to facilitate its management, regulation and development:

  1. For population use through drinking water operators.
  2. For agricultural use through users' (and/or agro-exporters') boards
  3. For energy, industrial, mining or fish farming use through the private sector (hydroelectric plants, agro-exporters, bottlers, producers of beer and carbonated or energy drinks, etc.) At the same time, it indicates, water users who share a surface or subway source and a common hydraulic system are obliged to organize themselves into committees, commissions and users' boards.

The users' committees are part of the commissions and these are the boards. For this reason, this study considers the ecosystemic water services of provision oriented to the fish farming production sector, who have the possibility of giving value. Likewise, they must promote the conservation of natural assets and ensure that water users comply with the payment of voluntary contributions agreed upon by their assemblies (MINAM, 2018).

In order to know the potential price of these water ecosystem service goods and services, the revealed preference method and the declared or expressed preference method are mainly used. In the revealed preferences method, the specific and most important method recognized by international institutions financing environmental projects, programs and policies is the Contingent Valuation Method, which consists of formulating a hypothetical market through a structured questionnaire. It consists of formulating a hypothetical market by means of a structured questionnaire. It is therefore a question of carrying out a survey of a representative sample of the population by means of which a non-real transaction is offered between the public good to be valued and a monetary amount. The objective of the questionnaire is to present a credible scenario where the individuals interviewed constitute the demand and the interviewer represents the supply (Riera, 1994). However, the preferences of rural communities for improvements in watershed ecosystem services, as well as the factors determining the valuation of these services, have not been sufficiently studied in developing countries. (Huenchuleo & De Kartzow, 2018).

The purpose of this study is to preserve the micro-basin of the Chumbao Valley and to improve the water supply ecosystem services provided by the Chumbado River. In this sense, the study aimed to determine the factors that influence the willingness to pay, in soles, of irrigation users for the ecosystem services provided by the micro-basin of the Chumbao River, so that, based on this study, the mechanisms for payment of ecosystem services for this place can be proposed. In this way, it can guarantee the fish farming activities that lead to the food security of the population.

The research was developed in the micro-basin of the Chumbao River, located between the coordinates 73° 41' and 73° 11' West longitude and between 13° 67' and 13° 34' South latitude. The altitudes vary from 2,000 to 4,800 m.a.s.l. covering an extension of 4,080.35 Km2. Politically it is located in the Southern Highlands of Peru in the Department of Apurimac, province of Andahuaylas. It includes the districts of Andahuaylas, San Jerónimo and Talavera. Sectorially it belongs to the Agrarian Region IX-Cusco, Agrarian Zone Apurímac and district of Irrigation Andahuaylas. The Chumbao River rises above 4,500 m.a.s.l. receiving the contributions of the Huachacocha, Pacococha, Antacocha and Pampahuasi lagoons; as well as numerous streams and creeks located on both sides of its course, downstream from the lagoon area until its mouth on the Pampas River. The valley in the districts of San Jerónimo, Andahuaylas and Talavera is elongated in a northeast-southeast direction, with an approximate length of 17 km and a variable width of 2 to 5 km (SENAMHI, 2010).

The study was carried out through a personalized survey of irrigation users of the Chumbao River, who are located in the rural areas of San Jerónimo, Andahuaylas and Talavera - Andahuaylas Province - Apurímac Department, Peru. SPSS version 25.0 statistical software was used for data processing.

In order to achieve the objective of this research, the Contingent Valuation Method was used. The questionnaire that was elaborated had the following characteristics

  • Type of question: Taking into account the recommendations of the NOAA panel, the Willingness to Pay was chosen.
  • Question format: The Referendum format was used.
  • Questionnaire structure: The survey used to extract the willingness to pay consisted of three blocks. The first contained information regarding the provision of ecosystem water services, which ensures that the respondent is aware of the problem being addressed. Fundamentally, the quantity and quality of water for use in crop irrigation. The second describes the willingness to pay, including the monthly rate. The last one collected information on the most relevant socio-economic characteristics of the respondent.
  • Administration of the questionnaire: The personal survey was chosen and applied in the same place that lasted 20 minutes on average for each respondent.
  • Pilot study: Following Arrow's (1993) recommendations, In order to evaluate the comprehension of the questions by the respondents (and thus the internal validity of the method), the time destined to answer the questionnaire, to define the items to be included and as part of the interviewer's training, a pilot questionnaire was elaborated. It was administered to 50 people who are users of the Chumbao River irrigation system. This questionnaire contained a series of preliminary questions divided into three blocks as mentioned above, which were later adjusted according to the results obtained. Along with the answers, observations and contributions were received from the respondents. The pilot study was applied during the months of November and December 2019.

Table l.
Description of the variables for the Willing to Pay

Dependent Variable Definition Units/scale
HPA Hypothetical Payment Amount S/ 0,50 =1; S/ 1.00 =2; S/ 2.00 =3; S/5.00 =4
MFI Monthly family income Less than 930 soles = 1; Between 930- 1500 soles = 2; Between 1500-2500 soles=3; Between 2500-3000 soles =4; More than 3000 soles =5
LIE Level of instruction or education No Instruction=1; Elementary Incomplete = 2; Elementary Complete=3; High School Incomplete=4; High School Complete=5; High School = 6
IAW Importance of the amount of water (1) Bad =1; Fair = 2; Good =3
NMF Number of members per family  single =1; 2 people =2; 3 to 5 people =3; 6 to 8 people =4, More than 8 people =5

Determination of the sample size

According to (Aguilar, 2005) the following formula is used to determine a population proportion when the population size is known:

……….Ec. 1


n: Sample size
P = Acceptance level =0.50
Q = Failure level = 0.5
N: Total population
E: Allowable sampling error 5 %.
Z: Critical value corresponding to 95% confidence = 1.96

The population for the survey was considered to be the users of the water service for irrigation of the Chumbao River, which includes the district of San Jerónimo (Poltocsa, Champaccocha, Lliupapuquio and Totoral), the district of Andahuaylas (Pochccota, Unión Chumbao) and the district of Talavera (Barrio Magisterial, Santa Rosa, Chumbibamba). The survey was conducted according to the percentage distribution of the population.

Main study: from the calculation of the above equation. The final questionnaire was administered to 310 people who were doing tourism in the place during the months of January to June 2020. The heads of the family, who were more than 18 years old, were surveyed, assuming that they had more knowledge about the importance of the water ecosystem for agricultural activities and the value that they give in money for the improvement and conservation of the environment of the micro-basin of the Chumbao River.

The viability of the hypothetical amount raised in the questionnaire depends on the value of the probability of being willing to pay.

Willing to Pay Method

The application of the Logit model will allow inferring the WTP and the variables that condition it. According to (Hanemann W. M., 1984), the Logit regression method is based on a function of cumulative logistic probability within the regression analysis framework. In general, the model can be expressed as follows:

…………Ec. 2

Where αo is the value of the intercept, Si is the vector of socioeconomic characteristics, α¡ are the respective parameters of the variables Si and β is the parameter of the variable amount offered by the interviewer. Both a and β are estimated using the Logit model.

If the errors are distributed as a logit model; the WTP will be given by the following expression:

Then if we include the socioeconomic variables, the marginal WTP is expressed:

 …………Ec. 4

In order to calculate the total WTP of the population, we extrapolate the marginal mean calculated per individual to the entire population studied.

Estimation of the willingness to pay

According to the variables that most affect WTP, the econometric model is proposed as follows:


α = Intercept
 = Coefficient of the variables
HPA = Hypothetical Payment Amount
FI= Family income
EL = Educational level
IEW = Importance of the ecosystem with respect to the provision of water
MF = Members per family

In table 2 and figure 1, the results on the willingness of irrigation users to pay for water ecosystem services provided by the Chumbao River are presented.

Table 2.
Willing to pay (WTP)
  Frequency Percentage Valid percentage Cumulative percentage
Valid NO 89 28,7 28,7 28,7
YES 221 71,3 71,3 100,0
Total 310 100,0 100,0  

Figure 1. Willing to Pay (WTP)

Table 3.
What amount would you be willing to pay to guarantee the quality and quantity of water in the Chumbao River in the future?


Frequency Percentage Valid percentage Cumulative percentage


S/0.50 40 18,1 18,1 18,1
S/1.00 63 28,7 28,7 46,8
S/2.00 93 42,3 42,3 89,0
S/5.00 24 11,0 11,0 100,0
Total 221 100,0 100,0  

From the 221 people surveyed who answered affirmatively, their willingness to pay for the improvement of the ecosystem services of the Chumbao River micro-basin; 11% revealed the amount of S/. 5,00 being the most representative, others revealed the amounts of S/. 0,50; S/. 1,00; S/. 2,00 representing 18,1% 28,7%, 42,2% of the people willing to pay respectively. So, the majority percentage of users willing to pay is the amount of S/. 2.00. However, through training programs within the framework of environmental education, it is possible to raise awareness and attract higher amounts of payment, which can allow for high impact investment projects in a short period of time.

Figure 2. Percentage distribution of amounts payable

Correlation of the dependent variable with the independent variables

According to the Logit model through the Nlogit 3.0 software with a significance level of α=0.05, in order to characterize the WTP as a function of the variables that condition it, a series of Logit regressions was performed, including all the variables. Then, those variables that best fit the model were chosen, which were considered significant at the time of capturing the WTP.

The hypothetical amount to be paid (HAP), monthly economic income (MEI), level of education (LE), number of members per family (NMF), and importance of the amount (IA) are not significant (at 95% confidence) in the model, however, for theoretical effects they remain in the model.

Table 4.
Evaluation of WTP variables

Variable ODDS RATIO (Coefficient) Standard Error b/St.Er P[|Z|>z]
HAP -671,223,121 0,8911 -5,232 0,000
MEI 0,892,355 0,512 1,125 0,1832
LE 178,281,32 130,589 1,131 0,0235
IA -0,712,342 0,211 -2,731 0,010
NMF 482,884,1 0,705 3,324 0,0102
Const 473,172,124 274,121 3,001 0,0367
  Pseudo R-square   0,7447  
  Pct. Correct prec.   98,107    

The variables: Hypothetical amount to be paid, level of instruction or education, importance of the amount of water and number of members per family have a significant relationship and affect the willingness to pay for a P< 0.05, however, the level of economic income does not have a significant relationship and therefore does not affect the dependent variable (willingness to pay).

From table 45 it is deduced. The model chosen presented a good fit (74.5%) as a function of Pseudo R square and the model correctly predicts 98.11% respectively.

As can be seen in table 45, the sign that accompanies the variable Hypothetical amount to be paid is negative, indicating the inverse relationship between the value of the amount to be paid for the conservation of the Chumbao River micro-basin and the possibility of responding positively to the payment question. This variable is statistically significant since the P<0.05. Therefore, an increase in the hypothetical price decreases the willingness to pay and a decrease increases the willingness to pay.

The sign that accompanies the economic income variable is positive (0.892), indicating a direct relationship between the family's economic income and the probability of answering affirmative to the payment question. However, its statistical probability is not significant (P> 0.05).

The positive sign that accompanies the LE variable, level of education of the interviewee, means that the higher the level of education of the interviewee, the greater the probability of responding positively to the question of willingness to pay. This variable is statistically significant since the P<0.05. Therefore, an improvement in education increases willingness to pay and a worsening of education reduces willingness to pay for hydrological ecosystem services in the Chumbao River microbasin.

The sign that accompanies the variable importance of the quantity of water is negative, which allows us to understand that the value of this variable has an inverse influence on the willingness to pay and is statistically significant given that the P<0.05. Therefore, an increase in the volume of water causes users to be less willing to pay.

The willingness to pay for the variable number of members per family is (482,884). This variable is statistically significant given that the P<0.05. This allows us to understand that when the number of family members increases there is a greater probability of willingness to pay at the global level; therefore, they are useful in the construction of the econometric model.

Estimate of willingness to pay

Once the econometric model was analyzed and validated with the variables that had the most impact, the WTP was estimated by adding the coefficients of the variables: Hypothetical amount HA, (KS) knows the source, (NMF) members per family, (EL) educational level multiplied by its value in each case (including the constant) and dividing that total by the coefficient of the variable amount (A) proposed. However, the (FI) family income is excluded.

The average of the WTP for the population using the water service through the Logit model is SI. 2,00 per month per family and extrapolating the total of families rises to an annual amount of S/ 38472,00.

The variables that significantly affect the willingness to pay (WTP) of the users of irrigation for water ecosystem services in the Chumbao River microbasin are: the hypothetical amount to be paid (MHP), the level of instruction and/or education (LIE), the importance of the amount of water (IAW) for crop irrigation, number of members per family (NMF). In their research, Bacalla and Goñas, (2016) identified the variables that condition WTP: amount offered (A), family income (FI), knowledge of the source (KS), members per family (NMF), educational level of the head of household (LIE); when comparing this study with the present research, the variables that affect WTP are similar, only deferring to the family income for the Chumbao River micro-basin. Hanemann et al. (1991) refer to the fact that WTP is a function of the economic income of the interviewee and maintains a positive direct relationship. However, it is related to the research of Tudela (2012) who points out that having an increasingly higher level of education increases the probability of responding positively to the proposed amount. Therefore, an improvement in education increases the willingness to pay and a worsening of education reduces the willingness to pay for hydrological ecosystem services in the Chumbao River micro-basin. According to studies conducted by Guzmán et al. (2014) on payments for hydrological ecosystem services in the department of Amazonas, the significant and unrelated variables in this research were (a) forest supply ratio and (b) water quality. Likewise, the studies of Tudela and Soncco (2014) the variables that are not related to the present research are (a) age, (b) gender, (e) presence of forests and vegetation, (d) knowledge of stories and legends and (e) participation in social organizations. However, when evaluating the similarities in terms of the variables that stand out as common, we found that the following variables are significant: the hypothetical amount of payment and level of education and/or training.

Riera et al., (2005), mentions that the family income increases by one nuevo sol (S/1.00) the resulting WTP, that is, the higher the income level, the greater the willingness to pay for the conservation and improvement of pastures program (PCIP). On the other hand, if the Payment Vectors or IDB's would increase by one new sol (S/1.00), the WTP would decrease by 0.90 nuevo soles, revealing that the higher the value of the IDB, the lower the willingness to pay for the PCIP. With respect to the socioeconomic variables (marital status, age and sex), when the respondents are married the WTP value decreases by S/. 0.64, when the age increases by one year the WTP decreases by 0.98 nuevos soles and when the people are male the WTP would increase by 1.13 nuevos soles.

On the other hand, in an attempt to estimate how much could be collected as a minimum to constitute a fund for the implementation of the PCIP for the Pasco Region, the value of the most conservative WTP and close to the median was used (Villena & La Fuente, 2012), that is, the WTP estimated using only the socioeconomic variables, amounting to S/. 3.94/family/month, which multiplied by 41,177 families residing in the provinces of Pasco and Daniel Alcides Carrión (INEI, 2011), would yield a monthly collection of S/. 162,237.38 and an annual collection of S/. 1,946,848.56 for the PCIP in the Pasco Region. This fund could be used to promote the generation of sustainable pasture management technologies, design of policies to stimulate conservation, technical capacity building and implementation of monitoring activities of pasture ecosystems (INRENA, 2005). While the users of the Chumbao River would collect an annual amount of S/ 38472,00 for water supply ecosystem services.

After applying the Contingent Valuation Method to the irrigation users of the Chumbao River, it can be concluded that, for the first time, there are basic elements involved in the process of valuing the water ecosystem services of the Chumbao River micro-basin (from the headwaters and the 17 km of the riverbed).

The econometric model of the willingness to pay for improvements and conservation of water services in the Chumbao River micro-basin is determined negatively by the hypothetical amount of payment and the importance of the quantity of water; and positively by the level of education and number of members per family. The four variables that affect WTP were determined through the Logit model with test criteria P<0.05. In addition, the average WTP for the irrigation user population was determined by the hypothetical Amount to be Paid of S/. 2.00 per month per family, and extrapolating the total number of users, it amounts to an annual amount of S/. 38472.00.

The statistical technique of binary logistic regression constitutes a very important tool to determine the variables that intervene in the final model of the disposition of the irrigation users by water ecosystem services provision of the Chumbao River micro-basin.

Bacalla, E., & Goñas, M. (2016). Disposición a pagar y mecanismo de retribución por servicios ecosistémicos hídricos para la capital del distrito de Magdalena, provincia de Chachapoyas, departamento de Amazonas. Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas.

GOREAP. (2019). Estudio de zonas de vida del proceso de meso zonificacion ecologica y economica de la región apurímac (p. 55). Gobierno Regional de Apurimac - Gerencia Regional de Recursos Naturales y Gestión del Medio Ambiente.

Guzmán, W., Arellanos, E., & Chávez, S. (2014). Pagos por servicios ecosistémicos hidrológicos en el departamento de Amazonas: determinación e incidencia de la disposición a pagar. En A. Diez, E. Raez, & R. Fort, Perú: el problema agrario en debate /SEPIA XV (p. 684-685). SEPIA.

Hanemann, W. M. (1984). Welfare evaluations in contingent valuation experiments with discrete responses. American Journal of Agricultura/ Economics, 66(1), p.332-341.

Hanemann, W. M., Loomis, J., & Kanninen, B. (1991). Statistical efficiency of double bound dichotomous choice contingent valuation. American Journal of Agricultura/ Economics, 73(4), l255-1263.

Huenchuleo, C., & De Kartzow, A. (2018). Valoración económica de servicios ecosistémicos en la cuenca del río Aconcagua, Chile. Tecnologia y Ciencias del Agua, 9(2), 58-84.

INEI. (2011). Instituto Nacional de Estadística e Informática – INEI. 2011. Reporte de población del Perú.

INRENA. (2005). Instituto Nacional de Recursos Naturales Santuario Nacional de Huayllay – Plan Maestro 2005- 2010. Ministerio de Agricultura.

MEA. (2005). Ecosystems and human well-being: a report on the conceptual framework working group of the Millenium Ecosystem Assessment. Millennium Ecosystem Assessment, 5(281).

MINAM. (2018). Mecanismos de retribución por servicios ecosistémicos hídricos con juntas de usuarios de riego (Primera edición ed.). M. d. Ambiente, Ed.
Riera, P. (1994). Manual de Valoración Comingenta Instituto de Estudios Fiscales.

Riera, P., García, D., Kriström, B., & Brännlund, R. (2005). Manual de economía ambiental y de los recursos naturales. Thomson.

SENAMHI. (2010). Caracterización agroclimática de la región apurimac. Servicio Nacional de Meteorología e Hidrología del Perú.

Smith, M., De Groot, D., Perrot, D., & Bergkamp, G. (2006). Pago : establecer pagos por servicios de cuencas. The World Conservation Union (IUCN).

Tudela, J. W. (2012). Valoración económica de los beneficios ambientales de políticas de gestión en la Reserva Nacional del Titicaca. Reseachgate, 2-9.

Tudela, J., & Soncco, C. (2014). Valoracion económica del servicio ambiental hidrológico de las lagunas del Alto Perú, Cajamarca: Una aplicación del método de valoración contingente y experimentos de elección. En A. Diez, E. Raez, & R.Fort, Perú: el problema agrario en dabate/SEPlAXV.

Villena, M., & La Fuente, E. (2012). Valoración económica de bienes ambientales por beneficiarios circundantes y no circundantes.Cuadernos de Economía, XXXI(56), 33.