WATER FLOW REGULATION AND

INCENTIVES FOR CONSERVATION: COCA

RIVER - ECUADORIAN AMAZON

REGULACIÓN HÍDRICA E INCENTIVOS DE

CONSERVACIÓN: RÍO COCA – AMAZONÍA

ECUATORIANA

María Cristina Torres

Departamento de Ingeniería Civil y Ambiental, Escuela Politécnica Nacional - Ecuador

Vanessa Fierro

Departamento de Ingeniería Civil y Ambiental, Escuela Politécnica Nacional - Ecuador

Sebastián Paez-Bimos

Departamento de Ingeniería Civil y Ambiental, Escuela Politécnica Nacional - Ecuador

Efraín Naranjo

Departamento de Estudios Organizacionales y Desarrollo Humano, Escuela Politécnica

Nacional - Ecuador

pág. 3232

DOI: https://doi.org/10.37811/cl_rcm.v8i6.15088

Water flow regulation and incentives for conservation: Coca river -

ecuadorian Amazon

María Cristina Torres

maria.torresg@epn.edu.ec

https://orcid.org/0000-0002-9005-2220

Departamento de Ingeniería Civil y Ambiental -

Escuela Politécnica Nacional

Ecuador

Vanessa Fierro

vanessafierro@yahoo.com

https://orcid.org/0000-0001-6656-507X

Departamento de Ingeniería Civil y Ambiental -

Escuela Politécnica Nacional

Ecuador

Sebastián Paez-Bimos

carlos.paezb@epn.edu.ec

https://orcid.org/0000-0003-4833-3923

Departamento de Ingeniería Civil y Ambiental,

(CIERHI) - Escuela Politécnica Nacional

Ecuador

Efraín Naranjo

efrain.naranjo@epn.edu.ec

https://orcid.org/0000-0001-6629-1101

Departamento de Estudios Organizacionales y

Desarrollo Humano - Escuela Politécnica

Nacional

Ecuador

ABSTRACT

Conservation and land use policies are key to regulating water in watersheds, influencing water

quantity, quality and storage, and mitigating risks such as erosion and flooding. In Ecuador, the Socio

Bosque Program (SBP), part of the Good Living Development Plan (2013-2017), focused on

conservation without fully considering water benefits. To optimize its implementation, the upper basin

of the Coca River, relevant for its hydroelectric potential, was evaluated by analyzing the inclusion of

water criteria in the SBP. Four scenarios of land cover and land use change were developed using the

Delphi method: Business as Usual (BAU), Strengthening of SPB (SBPS), National Incentive Plan

(NIP), and Degradation (DEG). Runoff rates were estimated for each scenario using a land cover and

land use model (TerrSet) and a hydrological model (SWAT). The results show that BAU and DEG

cause a decrease in lateral and base flow and an increase in surface runoff, while NIP is the only scenario

that maintains water regulation. This highlights the need for future incentives to prioritize strategic areas

for water regulation in line with watershed management objectives.

Keywords: land use/land cover change, conservation incentives, Socio Bosque Program, water

ecosystem services, water regulation

Autor principal.

Correspondencia: maria.torresg@epn.edu.ec

pág. 3233

Regulación hídrica e incentivos de conservación: río Coca - Amazonía

ecuatoriana

RESUMEN

Las políticas de conservación y uso de suelo son clave para la regulación hídrica de las cuencas,

influyendo en la cantidad, calidad y almacenamiento del agua, además de mitigar riesgos como la

erosión y las inundaciones. En Ecuador, el Programa Socio Bosque (PSB), en vigencia desde 2008, se

ha enfocado en la conservación sin considerar sus repercusiones en términos hídricos. Con el objetivo

de proponer mecanismos que optimicen la aplicación del PSB, se seleccionó la cuenca alta del río Coca,

relevante por su potencial hidroeléctrico, para evaluar la incidencia de incluir criterios hídricos en la

aplicación del PSB. Mediante el método Delphi se desarrollaron cuatro escenarios de cambio de

cobertura y uso de suelo: Business as Usual (BAU), Fortalecimiento del PSB (FSB), Plan Nacional de

Incentivos (PNI) y Degradación (DEG). A través de modelos de cobertura y uso de suelo (TerrSet) e

hidrológicos (SWAT), se estimaron caudales para cada escenario. Los resultados muestran que BAU y

DEG provocan disminución en la escorrentía subterránea y aumento de la superficial, mientras que el

PNI es el único escenario que preserva la regulación hídrica. Esto resalta la necesidad de que futuros

incentivos prioricen áreas estratégicas para la regulación hídrica, alineados con los objetivos de manejo

de cuencas.

Palabras clave: cambios de uso de suelo/cobertura de suelo, incentivos de conservación, Programa

Socio Bosque, servicios ecosistémicos, regulación hídrica

Artículo recibido 15 octubre 2024

Aceptado para publicación: 28 noviembre 2024

pág. 3234

INTRODUCTION

Integrated Water Resources Management (IWRM) ensures the coordinated development and

management of water in interaction with other natural, social and cultural systems, maximizing

economic well-being without compromising vital ecosystems (Tortajada, 2016). The watershed

approach is the most appropriate territorial unit for its application (Forero & Mosquera, 2014).

Land use and its degree of exploitation modify the hydrological functions of a watershed (Can et al.,

2015); thus, Land Use/Land Cover (LULC) changes affect the ecosystem service of water flow

regulation (Bonnesoeur et al., 2019; Brath et al., 2006; Costa et al., 2003; Crooks & Davies, 2001; Wang

et al., 2006). Inadequate soil management can lead to the loss of ecosystem services and biodiversity

(Can et al., 2015; Fernández & Prados, 2010; Li et al., 2009); therefore, to counteract these effects,

public policy instruments in the form of environmental incentives have been proposed in recent decades

to stimulate sustainable land use processes and actions (S. Ortega, 2008; Ramírez, 2006).

In 2008, following the ratification of the United Nations Framework Convention on Climate Change

(UNFCCC) and in line with the National Development Plan in force at the time, Ecuador established

the Socio Bosque Program (SBP), with the main objectives of conserving native vegetation, reducing

greenhouse gas emissions from deforestation and contributing to the improvement of the living

conditions of the rural population (MAE, 2008). In 2013, the National Incentive Program for the

Conservation and Sustainable Use of Natural Heritage (NIP) was established with the aim of integrating

all incentive initiatives (conservation, restoration, forest management, biotrade and financial

sustainability) into a single program (Acuerdo Ministerial 131, 2013; De Koning et al., 2011). With this

amendment, the SBP becomes part of the conservation and restoration chapters of this program.

According to the operating rules and internal procedures of the SBP, the applicant property must be

located within the areas identified as priority areas according to the criteria of deforestation risk,

provision of environmental services (water regulation, biodiversity habitat and climate change

mitigation) and poverty level (unsatisfied basic needs) (Manual Operativo Del Proyecto Socio Bosque,

2014).

The SBP has been consolidated as a valid strategy to promote the conservation of native vegetation

(Zurita & Cotacahi, 2019). This program works by providing annual financial incentives of USD$30.00

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per hectare to individual or collective landowners who voluntarily commit not to intervene in areas of

native vegetation (primary forest or páramo) for a period of 20 years (Granda & Yánez, 2017; Perafán

& Pabón, 2019). Although participation in the program is voluntary, membership is conditional on the

property being located within the areas identified as priority areas. In addition, each property that joins

the program must undergo a monitoring and control process to periodically verify that no changes in

land cover or land use are occurring (Braulete, 2012), but it is not necessary to measure the

environmental benefits generated (Farley & Bremer, 2017; Hansen et al., 2015; McAfee, 2016; Ponette-

González et al., 2015; Vanacker et al., 2018).

The Coca watershed, located in the northeastern Ecuadorian Amazon, is one of the most mega-diverse

regions in the world (Mittermeier et al., 2011), which is why 76% of its area is part of the National

System of Protected Areas (SNAP) (Torres et al., 2018). Due to its abundant river system and special

orography, it has a hydroelectric potential of 4640 MW, making it the second most important watershed

in the country (CONELEC, 2013), with 22 hydroelectric plants (five in operation, one under

construction and 16 in planning). Currently, the watershed produces 30% of the energy consumed by

the entire country, thanks to the NSPA operation of the Coca Codo Sinclair Hydropower Plant

(CCSHP), with 1,500 MW, according to the Ministry of Energy and Non-Renewable Natural Resources

(MERNNR, 2020). It also plays a key role in the current and future provision of water for the

consumption of around 40% of the population of the Metropolitan District of Quito (Jiménez & Terneus,

2019).

Although most of the watershed area belongs to the SNAP, according to the Ministry of the

Environment (MAE, 2015), since 2014 it has not been possible to stop the advance of pasture and arable

land (5.7% per year). In this context, the SBP is implemented as the only National Incentive Program

for the Conservation and Sustainable Use of Natural Heritage incentive present in the area, with a total

of 24,897 ha of private and communal forests and peatlands, distributed inside and outside the SNAP.

Despite the importance of this basin in terms of hydroelectric production and as indicated in the SBP

regulations, no studies were found on the relevance of focusing the incentives provided by the current

SPB regulations on areas whose conservation or restoration will have a positive impact on the

hydrological functions of the basin (Torres et al., 2018). In addition, the watershed presents a complex

pág. 3236

nature in terms of soils, geology, vegetation, which has recently been reflected in the process of

regressive erosion downstream, which became evident in 2020 with the loss of the iconic San Rafael

waterfall (Barrera Crespo et al., 2024). While water regulation is not explicitly identified as an objective

of the SBP, the selection of priority areas for its application does include water regulation criteria

(Acuerdo Ministerial 066, 2022; Consulado del Ecuador, 2012). Furthermore, the environmental policy

that supports the program recognizes the state's obligations in relation to aspects such as: a)

guaranteeing the conservation, recovery and integrated management of water resources and watersheds;

b) regulating changes in land use, ensuring the minimum impact and restoration of ecosystems in water

protection areas; and c) implementing environmental incentives that promote the conservation,

sustainable use and management, and restoration of ecosystems (A. Martínez, 2019).

This study focused on identifying and analyzing how the implementation of different conservation and

land-use policies, provided in current national legislation, would affect water flow regulation in the

upper Coca river watershed. To this end, the Delphi method was used to generate four land use scenarios

with a horizon of 2030 (J. Martínez et al., 2016; F. Ortega, 2008); then, the scenario approach was

applied as input to the hydrological modelling of the watershed (Marhaento et al., 2017; Mckenzie et

al., 2012), to obtain indicators to assess the impact of the scenarios on the water flow regulation. The

results of this study are expected to be an input for decision makers to consider mechanisms to optimize

the application of existing conservation incentives.

METHODOLOGY

Study area

The upper zone of the Coca river watershed (with outlet point at the confluence with Machacuyacu

river) is located in the northwest of the Ecuadorian Amazon, between the eastern Cordillera of the

Andes and the Amazon forest. Its altitude varies between 5,790 and 533 masl, and it has an approximate

drainage area of 4,597 km2, which includes part of three protected areas (Cayambe-Coca, Antisana and

Napo-Sumaco-Galeras) (López, 2016) (Figure 1). Its rivers originate in the foothills of the Antisana and

Cayambe volcanoes. The average rainfall is 2,950 mm/year, with the wettest period corresponding to

the months of May to July; the average annual temperature is 15.4°C, and relative humidity varies

between 84% and 93% (Horna, 2016). The soils are mainly Andisols (81%) and Inceptisols (8.2%)

pág. 3237

(Tamayo, 2017). Land use is distributed between natural forest (61%), páramo (27%) and pasture (10%)

(Figure 1) (Torres et al., 2018).

The soils in the watershed are fragile, with a shallow arable layer that is highly sensitive to leaching

due to high precipitation (Sánchez et al., 2018; Vargas et al., 2018). The conversion of natural forests

to pasture in this watershed results in reduced soil fertility and low crop productivity (Mainville et al.,

2006). Consequently, agriculture is a marginal activity, with most crops corresponding to pastures for

livestock maintenance.

Figure 1. Study area location and land use

In alignment with the objective of this research, we considered the areas of water importance identified

by Torres et al. (2018). On this basis the LULC was projected, assuming that the trend associated with

the conservation policies currently applied will remain constant over time. This analysis was used to

construct four land use scenarios based on the current legal framework and the Delphi method. These

scenarios were created to support the estimation of potential changes in vegetation cover and to assess

the impact of such changes on water flow regulation in the watershed. The study was conducted in

accordance with the steps presented in Figure 2.

pág. 3238

Figure 2. Study methodological framework. Notes: 1 Integrated Valuation of Ecosystem Services and

Trade-offs, 2 Soil & Water Assessment Tool

Scenario generation

The areas of water importance were established by identifying the sub-watersheds with the highest

water and sediment production (Torres et al., 2018). The water production was obtained by modelling

with the Soil and Water Assessment Tool (SWAT) model, represented by the total annual runoff. The

sediment production was obtained from sediment discharge of nine stations within the study area. A

qualitative assessment of water and sediment production was conducted using a scale ranging from low

to very high. Low corresponds to the lowest production, while very high corresponds to the highest.

Map algebra was then employed to sum the values assigned to each sub-watershed, identifying the areas

that met the characteristic of highest water and sediment production simultaneously (Figure 3). Further

details regarding the areas of water importance can be found in Torres et al. (2018).

pág. 3239

Figure 3. Areas of water importance (Adapted from Torres et al. (2018))

LULC scenarios describe possible situations of an uncertain future (Alpizar & Bovarnick, 2013). This

study developed four scenarios of LULC change under the current environmental legal framework and

defined using the approach of McKenzie et al. (2012). The scenarios were defined following the Delphi

method, with the aim of including the criteria of different actors and disciplinary fields (García, 2013).

To achieve this, the collaboration of seven experts in legal, economic, social, environmental, hydraulic

and hydrological issues was sought, with extensive knowledge of the socio-environmental dynamics of

the study area. These experts were consulted on the interaction of the variables that drive land use

change and the ideal conservation criteria for this watershed (Velázquez & Sánchez, 2021). The

outcome of this process was the identification of the underlying assumptions that inform the scenarios

and the set of variables that define the projected LULC.

The cartographic information available was aligned with the SBP assessment horizon (Torres et al.,

2018) and the Sustainable Development Goals 2015-2030 assessment period promoted by the United

Nations (ONU-CEPAL, 2016), with the year 2030 defined as the horizon for the land cover projections

for each scenario. Given that the populated area and crops represent only 0.20% of the watershed area,

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only the transformation of native forest, páramo and pasture cover was considered for the quantification

of LULC. Table 1 provides a summary of the assumptions and methods employed in the projection of

the four scenarios generated.

The starting scenario was the BAU, which was projected considering both the SBP coverage and the

loss of native vegetation for the period 2009-2014 as invariant. To project land use in this scenario, we

used the Land Change Modeler (LCM), a software tool integrated with the TerrSet framework

(Eastman, 2016). This incorporated explanatory variables and historical land cover data (1991, 2000,

2009 and 2014) provided by the MAE. The result of the projection of this scenario made it possible to

identify the areas that, due to their characteristics, should be incorporated into the different incentive

proposals of the SBPS and NIP scenarios.

Table 1. Scenario generation (assumptions and projection methodology

Scenario

Assumptions

Methodology

for Generating

the Land

Use/Land

Cover Use

Map to 2030

Business As

Usual

(BAU)

• The annual loss of native forest and páramo

throughout the watershed is presented by the

historical trend between 2009-2014 (Torres et al.

2018):

- Decrease of 0.7% in native forest per year

- Decrease of 0.05% in páramo per year

- Increase of 1.1% in pasture per year

• The same SBP coverage as in 2014 (24,987 ha) is

maintained in 2030.

Mathematical

model

(quantitative)

SIG – TerrSet

Strengthening

of SBP

(SBPS)

• It foresees the optimization of the conservation

incentive in terms of water regulation, by including

6250 ha defined as water significant outside the

SNAP that are under threat of degradation. Totaling

31147 ha under contract in the SBP.

• The annual loss of forest and páramo, as well as the

increase of pasture areas continues in the rest of the

watershed with the historical trend.

Expert

judgement

(qualitative)

National

Incentive

Program

(NIP)

• Extends the conservation of the areas defined in the

SBPS to areas that in the BAU scenario (2030) were

identified as areas of transition from native forest to

pasture, which are within protective forests,

correspond to areas of water importance and are

located outside the SNAP.

Expert

judgement

(qualitative)

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• Restoration of areas identified as degraded under the

following scheme:

- Degraded river slopes throughout the watershed.

- Degraded areas from 2009-2014, which are

outside the Salado River sub-watershed and

outside the river slopes.

- Degraded areas within the Salado River sub-

watershed (identified as being of high water

importance).

• Sustainable production by replacing pasture with

silvopastoral systems in degraded areas not under

other incentives.

Degradation

(DEG)

• Disappearance of the SBP

• Uncontrolled loss of natural vegetation due to road

growth and extensive expansion of livestock activities

is expected with the following annual trend:

• 1.1% decrease in native forest.

• 0.3% decrease in páramo

• 7% increase in grassland

Mathematical

model

(quantitative)

InVEST

((Sharp et al.

2018)

The SBPS scenario proposes the strengthening of the current SBP, with its application extended to areas

of water importance located outside protected areas and showing degradation in the BAU scenario. The

scenario is conceived as an intermediate situation between the current trend (BAU) and the ideal

situation represented by the NIP scenario. To check the projected land use for this scenario, the Delphi

methodology was once again employed.

The NIP scenario responds to the vision of an ideal situation of conservation and management of the

watershed, which includes the simultaneous application of three incentives contemplated in the National

Program of Incentives for the Conservation and Sustainable Use of Natural Heritage. In this study, these

incentives are grouped into three categories: conservation, restoration and sustainable production. The

latter category is represented by silvopastoral systems, which combine secondary forest, pasture and

livestock. The land use projection for this scenario was generated using the Delphi methodology. The

inclusion of silvopastoral systems is of great importance, as traditional livestock production systems in

the Ecuadorian Amazon region are based on pastures and monocultures that are extensively grazed.

This contributes significantly to the loss of fertility of naturally poor soils and has also become one of

the main drivers of landscape transformation and the loss of ecosystem services (Congo et al., 2018).

Faced with this situation, silvopastoral systems are a viable alternative for the area, as they are more

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respectful of biodiversity, make it possible to exploit the great diversity of tree species, increase soil

fertility and reduce the negative impact of a fundamental activity of the local economy (Fajardo et al.,

2012).

Finally, the DEG scenario simulates a critical situation in terms of conservation where the NIP is not

applied and the SBP disappears, thereby weakening the restrictions on anthropic activities within

protected areas. This, in turn, facilitates the advance of the agricultural frontier, which has the effect of

reducing the extent of natural vegetation cover. A mathematical model, InVEST (Sharp et al., 2018),

was employed to project land use to 2030.

Water Flow Regulation

• Hydrological modelling

The SWAT model was employed, which simulates the rainfall-runoff relationship over extended

periods of time, based on the biophysical characteristics of a river basin in a semi-distributed framework

according to Hydrological Response Units (HRU). This model is one of the most popular tools to assess

water related ecosystem services (Nedkov et al., 2022). It performs the analysis in a deterministic and

continuous manner, using a daily climate information base (Arnold et al., 1998). The selected modelling

period was 1976 to 1988, which corresponds to the time interval with the longest continuity of data

available at station H0714 – Coca in San Rafael (Figure 1). Station H0714 was employed as a calibration

point for the SWAT model. Three sub-periods were selected for each of the modelling stages. The data

were divided into three sub-periods: 1976-1978 (warm-up), 1979-1983 (calibration) and 1984-1986

(validation). The vegetation cover and land use applied to this modelling were those of 1990, as the

available information was closest in time to the period of the hydrological data used. Consequently, the

results obtained from this modelling are referred to as the ‘base model (1990)’. Further details on the

hydrological modelling can be found in the work of Tamayo (2017).

To perform the calibration, the SWAT-CUP (Calibration and Uncertainty Program) was employed. This

involved a sensitivity analysis that required 1000 iterations, which enabled the optimal parameterization

values to be determined. The model results were obtained at the daily level for the calibration-validation

periods (1979-1986) for stations H0714 and H0715 – Quijos AJ Bombón. The latter station was

employed to validate the spatial representation of the model, as it corresponds to the upper part of the

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study area (Figure 1). The statistical performance of the model was evaluated at a monthly scale by

calculating the Nash-Sutcliffe (NSE), Percent Bias (PBIAS) and coefficient of determination (R2),

using the criteria proposed by Moriasi et al. (Moriasi et al., 2007).

• Estimation of water flow by scenario

The representative water flows for each scenario were obtained by running the hydrological model,

calibrated and validated, using the land covers corresponding to each scenario projected to 2030 (López,

2016; Torres et al., 2018). In each run, the land cover of the scenarios was modified while all other

parameters were kept constant. To illustrate the impact of land use change on water flow regulation, the

mean annual flows, as well as the monthly surface runoff, lateral flow and base (return) flow of each

scenario were compared with those of their respective counterparts in the base model (Birkel et al.,

2012; Can et al., 2015; Marhaento et al., 2017; Zhang et al., 2020). The application of land covers in

hydrological modelling is detailed in the studies by López (2016) and Torres et al. (2018).

• Water flow regulation indices

The water flow regulation indices were obtained at an annual scale based on the hydrological

simulations of each scenario for the entire simulation period (calibration and validation) (Marhaento et

al., 2017). The following components of the SWAT model were used at the annual scale for the

calculation of the hydrological indices: surface runoff (Qs), lateral flow (Ql), base flow (Qb) and total

stream flow (Q).

Firstly, three water flow regulation indices were calculated for the base scenario (1990 cover) and for

the four land cover scenarios: the base flow index (BFI) = Qb/Q, lateral flow index (LFI) = Ql/Q and

surface runoff index (SRI) = Qs/Q. This was done following the procedure described by Marhaento et

al. (2017). Secondly, to analyze the effect of land cover change with respect to the base scenario, the

hydrological indices (BFI, LFI, SRI) of each scenario were divided by corresponding indices of the

base scenario. According to the data normalization criteria, a value close to 1 indicates a similarity of

the water flow regulation indices between the scenarios and the baseline scenario; a value less than 1

indicates a decrease of the water flow regulation indices of the scenarios with respect to the baseline

scenario, while a value greater than 1 indicates an increase of the hydrological indices of the scenarios

with respect to the baseline scenario.

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RESULTS AND DISCUSSION

Scenario projection

After obtaining the 2030 land cover projections, these were classified into three categories: páramo,

native forest and pasture. Figure 4 depicts the land cover and land use change maps generated for each

scenario, which served as the foundation for the hydrological modelling.

Figure 4. Projection of pasture, silvopastoril system and reforested forest by scenario a) BAU, b) SBPS,

c) NIP, d) DEG

It can be observed that three of the four scenarios demonstrate an increase in grassland in comparison

to the 2014 coverage, which was selected as a reference point due to its status as the most recent

cartographic information provided by the MAE at the time of the study.

Regarding native forest, the NIP scenario is the only one that maintains the same area of cover as in

2014. The BAU and SBPS scenarios indicate a loss of 10.7% and 7.5% respectively, while the greatest

loss corresponds to the DEG scenario, with a decrease of 16.9%.

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In comparison to the total increase in pasture that would occur in the BAU scenario, the SBPS scenario

projects a 29% smaller increase. However, it is important to note that this scenario alone is insufficient

to halt the advance of the agricultural frontier. The DEG scenario indicates an increase of approximately

127%. The combined application of the measures considered in the NIP scenario is the only one that

projects the total disappearance of the grassland identified in 2014. This is because a percentage is

transformed into reforested forest (sub-watersheds and banks of Cosanga and Salado rivers), while the

remainder is converted into silvopastoral systems (pasture combined with secondary forest). This

configuration is deemed appropriate for the area in question, given the limited suitability of the existing

soils for agricultural purposes. Consequently, an opportunity is created for farmers to explore other

possible sustainable alternatives (Congo et al., 2018; Murgueitio, 2009; Pattanayak et al., 2003; Sotelo

et al., 2017). It is crucial to emphasize that any policy designed to restore ecosystems in the region must

consider the dynamics of the human populations that have settled there. These populations must be

acknowledged as significant factors in the determination of land use and in the variability of

anthropogenic pressure (Rodríguez, 2021). This aligns with findings in other Andean basins, where the

importance of considering the participatory and social approach to solve anthropogenic effects and

socioeconomic disparities in IWRM has been highlighted (Mera-Parra et al., 2022).

The identified dynamics demonstrate that the páramo is highly susceptible to the removal of the forest

conservation incentive, with greater forest loss resulting in greater páramo loss (Espinosa & Rivera,

2016). In the DEG scenario, characterized by the greatest forest loss, the retreat of the páramo is

estimated to reach 20.3%. In contrast, in the BAU and SBPS scenarios, the retreat is less than 1%. Once

more, the NIP scenario shows no variation with respect to the 2014 coverage. These findings indicate

that the forest plays a protective role in this region, acting as a barrier against the loss of the páramo. It

is crucial to highlight that, based on existing knowledge, the loss of the páramo vegetation results in the

modification of the soil structure and associated hydrological functions (Patiño et al., 2021;

Podwojewski et al., 2002). Consequently, depending on the level of degradation achieved, it will be

necessary to allow the soil to rest for decades to achieve its recovery and the subsequent spontaneous

sprouting of vegetation (Hofstede et al., 2014; Torres et al., 2024).

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Water Flow Regulation

The performance evaluation criteria presented in Table 2 indicate that the SWAT hydrological model

at the monthly scale for the 1990 baseline scenario is within the established ranges of good to very

good, as defined by the classification of Moriasi et al. (2007). These results show that the model

represent adequately the hydrological variables for the vegetation cover considered within the

watershed at a monthly scale.

Table 2. Performance evaluation criteria at monthly scale at stations H0714 and H0715 for the base

model (1990)

NSEª = Nash Sutcliffe Efficiency, PBIAS b = Percent Bias, R2 c = Coefficient of Determination

Table 3 presents the values of the hydrological variables simulated in SWAT at a mean annual scale for

the period 1979-1986 in the watershed of station H0714, both for the 1990 base model and for the

scenarios with projected coverage to 2030. Furthermore, Table 3 illustrates the variation in percentage

of each variable with respect to the corresponding values generated from the base model.

Table 3. Annual mean hydrological variables for each scenario

Hydrological

Variable

Unit

BAU

SBPS

NIP

DEG

Base model

(1990)

Mean annual

discharge

403.08

403.01

402.52

403.20

402.79

Surface runoff (Qs)

863.85

838.73

715.63

911.27

734.84

Lateral flow (Ql)

559.23

563.89

589.11

548.57

588.01

Base flow (Qb)

1342.36

1362.35

1456.81

1306.41

1440.59

Changes to the base model (1990)

Mean annual

discharge

0.07

0.06

-0.07

0.10

Surface runoff (Qs)

17.56

14.14

-2.61

24.01

Lateral flow (Ql)

-4.89

-4.10

0.19

-6.71

Base flow (Qb)

-6.82

-5.43

1.13

-9.31

H0714

H0715

Period

NSE

PBIAS

NSE

PBIAS

Calibration

0.74

-5.11

0.51

0.81

1.83

0.43

Validation

0.62

-9.71

0.28

0.67

8.57

0.37

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The results presented in Table 3 demonstrate that, considering the projected land use changes, the mean

annual discharge of the scenarios remains largely unchanged in comparison to its reference in the base

model, with a difference of less than 0.1%. In contrast, the mean annual surface runoff, lateral and base

flow values exhibit a notable variation between the scenarios and the 1990 base model. The hydrological

simulations demonstrate that the land use policy applied in the BAU, SBPS and DEG scenarios results

in lower lateral and base flow (< -4%) and higher surface runoff (> +14%) in comparison to the 1990

base model. Conversely, NIP scenario results in higher lateral and base flows as well as lower surface

runoff compared to the 1990 base model.

Figure 5 illustrates the percentage change in the water flow regulation indices of base flow (BFI), lateral

flow (LFI) and surface runoff (SRI) over the annual period (1979 to 1986) for the four scenarios of land

cover change in comparison to the base model (1990 coverage). It is observed that the NIP scenario

projects a lower percentage change (close to 1) for all water flow regulation indices over the modelling

period. The similarity between the behavior of the projected runoff indices in the BAU and DEG

scenarios is remarkable. The percentage change in lateral and base flow is less than 1, with the greatest

reduction observed in base flow (between 0.84 and 0.90). This evidence suggests a reduction in this

type of flow with respect to the base model. Conversely, the percentage change in surface runoff for the

BAU and DEG scenarios show values greater than 1 (between 2.1 and 3.6), indicating that surface

runoff increases with respect to the 1990 model.

The results presented in Table 3 can be interpreted as indicative of water flow deregulation at the mean

annual level for scenarios BAU, SBP and DEG (Bonnesoeur et al., 2019; Francesconi et al., 2016;

Logsdon & Chaubey, 2013; Oliveira et al., 2018; Zhao et al., 2024). The DEG scenario presents the

most severe alterations to the hydrological response. In contrast, in the NIP scenario, water flows exhibit

a behavior that improves regulation in comparison to the base model. This is evidenced by the

maintenance of lateral and base flow (between +0.19% and +1.13%) and a decrease in surface runoff (-

2.61%). Likewise, in Figure 5 the same behavior is evidenced at annual scale.

pág. 3248

Figure 5. Percentage change scenario indices vs. 1990 base indices a) Base flow index (BFI) b) Lateral

flow index (LFI). c) Surface runoff index (SRI).

The results presented in Table 3 and Figure 5 provide evidence that the current conservation policy

(BAU) is not effective in maintaining the provision of the ecosystem service of water regulation.

Conversely, the SBPS scenario performs better than BAU; however, it does not reach the regulation

levels obtained in the NIP.

It can be seen that maintaining current conservation policies (BAU) does not guarantee the maintenance

of water regulation in this watershed. Indeed, conservation initiatives (BAU) applied in isolation from

restoration processes (SBPS) contribute to the maintenance of water regulation, but do not ensure it.

This is evidenced by similar watersheds (Konetter and Galmez 2017). This illustrates the necessity for

the creation of technical studies that align with the specific characteristics, potential, and objectives of

each watershed (Coral et al., 2021). As noted in similar studies, monitoring should include ways to

transfer knowledge to decision makers to ensure effective watershed management (Mera-Parra et al.,

pág. 3249

2022).

The findings of this study highlight the need for establishing a watershed management organization for

the Coca river watershed, as previously identified by Fierro (2017), who emphasized that the

fundamental issue in water resource management for this watershed is the absence of an articulating

entity with decision-making capacity. This aligns with successful experiences in Ecuador, such as the

Paute River Basin Council, which has demonstrated the effectiveness of watershed-based management

organizations in coordinating conservation efforts, water regulation, and hydroelectric production

(Molina, 2008). The creation of such an organization for the Coca watershed would be particularly

relevant given our results regarding water flow regulation under different scenarios, as it could facilitate

the coordinated implementation of conservation and restoration policies, while ensuring the

participation of multiple stakeholders in watershed management decisions.

In light of the findings from the NIP, it can be posited that the simultaneous implementation of

restoration, conservation, and sustainable production strategies represents the sole policy avenue that

exhibits the potential to positively impact the water infiltration and storage processes, which ultimately

regulate the water balance of a watershed (Guo et al., 2000; Núñez et al., 2006).

In a watershed with 22 hydropower plants, the projected deregulation in the BAU, SBPS and DEG

scenarios is a factor that should be considered, as the base and lateral flows could be significantly lower

than the design flows; whereas higher surface flows are associated to high sediment transport. This

water flow deregulation could represent the greatest impact for hydropower plants (Lin et al., 2022;

Nguyen et al., 2013; Vogl et al., 2016).

The primary limitation of the study pertains to the representativeness of the hydrological parameters of

the land covers provided by default in the SWAT model, which were assigned to the land covers of the

study watershed. A further significant limitation is the scarcity of data, which results in the

hydrometeorological series being discontinuous. It is also important to note that there is a lack of

socioeconomic data for the area, which limits the ability to fully assess the impact of the research

criteria. Moreover, the people who live in this watershed play a crucial role in the stewardship of natural

resources that benefit the entire country, yet there is a dearth of information on their socioeconomic

status and circumstances.

pág. 3250

CONCLUSIONS

The conservation policies currently in place in the Coca river watershed (NSPA and SBP) are

insufficient to halt the loss of native vegetation and the subsequent increase in pasture. However, despite

its limitations, the SBP plays a crucial role in the conservation of the watershed, as the area of pasture

would double by 2030 if this program were to disappear. The joint application of conservation,

restoration and sustainable production policies as outlined in the national environmental regulations

(NIP) and applied in areas of water importance is the only mean of ensuring the conservation of the

vegetation cover.

The results of this study have established the relationship between the application of conservation and

restoration policies and water flow regulation. This is expressed as the change in the flow components

of the watershed in each scenario with respect to the 1990 base model. The BAU and DEG coverage

scenarios result in a reduction in lateral and base flows and an increase in surface runoff. In contrast,

the NIP scenario is the only one that guarantees the permanence of water flow regulation in the

watershed. Furthermore, it was identified that the mean annual discharge is not affected by the

implementation of these policies.

The incentive foreseen in the BAU scenario have been applied without considering hydrological

analysis, which generates, in terms of water flow regulation, similar results to not applying any incentive

(DEG). Understanding that the SBP was not designed with water objectives in mind, it remains to

recommend that the creation and application of future conservation-oriented incentives prioritize the a

priori analysis of water flow regulation as the basis for ecosystem conservation and be based on the

identification of priority areas according to the specific objectives of each basin. For this purpose, the

methodology proposed in this study can be used as a starting point, and then be complemented with

socioeconomic studies to establish the viability of the planned incentives, both in terms of the openness

of landowners to join the programs, and in terms of their economic sustainability.

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