Payment for Ecosystem Services (PES) and Water ...1153233/...Payment for Ecosystem Services (PES)...
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Master’s thesis Physical Geography and Quaternary Geology, 45 Credits Department of Physical Geography Payment for Ecosystem Services (PES) and Water Resource Management of the tropical mountain ecosystem páramo A case study in the northern parts of Ecuador Ellinor Hallström NKA 178 2017
Transcript of Payment for Ecosystem Services (PES) and Water ...1153233/...Payment for Ecosystem Services (PES)...
Master’s thesisPhysical Geography and Quaternary Geology, 45 Credits
Department of Physical Geography
Payment for Ecosystem Services (PES) and Water Resource
Management of the tropical mountain ecosystem páramo
A case study in the northern parts of Ecuador
Ellinor Hallström
NKA 1782017
Preface
This Master’s thesis is Ellinor Hallström’s degree project in Physical Geography and
Quaternary Geology at the Department of Physical Geography, Stockholm University. The
Master’s thesis comprises 45 credits (one and a half term of full-time studies).
Supervisor has been Steve Lyon at the Department of Physical Geography, Stockholm
University. Examiner has been Stefano Manzoni at the Department of Physical Geography,
Stockholm University.
The author is responsible for the contents of this thesis.
Stockholm, 15 June 2017
Steffen Holzkämper
Director of studies
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Photos on front page: Ellinor Hallström
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ABSTRACT
Latin America has pioneered the concept of Payment for Ecosystem Services (PES) as a strategy to
improve the management of ecosystem services. Ecuador is not an exception, where many PES
schemes have been implemented to protect the tropical mountain ecosystem “páramo” and the
water resources these areas are generating for downstream societies. A successful PES scheme needs
to achieve both targeted bio-physical objectives and at the same time benefit local conditions while
not risking to sacrifice the local demand for ecosystem services. This balance is explored here in a
case study focusing on the Río Grande watershed in the highlands in the northern parts of Ecuador
by exemplifying community participation in the public PES scheme Socio Bosque (PSB) starting in
2009. The water resource distribution (precipitation, discharge, actual evapotranspiration and
potential evapotranspiration) in the watershed was evaluated over the last decades. The local
perception of the PSB and its impacts on local and regional water resources were also studied and
characterized. The results showed that the annual discharge in the Río Grande watershed has
decreased significantly from 1967-2014 and that the annual discharge was significantly lower
between 1997-2015 compared to 1979-1997. Since precipitation did not decrease significantly during
this period, the changes of the annual discharge are more likely depended on factors controlling the
seasonal distribution of discharge and evapotranspiration in the watershed. For example, large scale
land use changes coupled with a significantly warmer climate in the region could be a possible driver.
Of course, this would not exclude other important factors such as changes in water demand and the
supply of freshwater from the Río Grande watershed to downstream societies. The results of this
case study showed that it is likely too early to see any impacts in the water balance components as a
direct response to the implemented PSB scheme. Clearly, this motivates a need for continued
evaluation of the local perception and the water resources to ensure that the need and demand for
ecosystem services in a long-term perspective are maintained.
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RESUMEN
Latinoamérica ha sido pionera en el concepto de Pago por Servicios Ecosistémicos (PSE o PES en las
siglas en inglés) como estrategia para mejorar la gestión de servicios ecosistémicos. En Ecuador, se
han implementado muchos PSE para proteger el ecosistema montañoso tropical de El Páramo así
como los recursos acuíferos que dichas áreas generan para las sociedades que habitan cuenca abajo.
Un esquema de PSE exitoso requiere alcanzar los objetivos biofísicos y respetar las necesidades
locales de servicios ambientales. Este equilibrio se ha analizado tomando como objeto de estudio la
cuenca hidrográfica del Río Grande en las tierras altas del norte de Ecuador y la participación
comunitaria en el programa de PSE denominado Socio Bosque (PSB) iniciado en 2009. Se estudiaron
la distribución del agua (precipitación, descarga del agua, evapotranspiración actual y
evapotranspiración potencial) en la cuenca hidrográfica durante las últimas décadas. También se
estudiaron los impactos locales y regionales del PSB en los recursos hídricos y los percepción local
con respecto a la implementación de PSB. Los resultados muestran que la descarga anual de la
cuenca hidrográfica ha decrecido significativamente durante el período comprendido entre 1967 y
2014, particularmente, señalan un decrecimiento considerablemente mayor entre 1997 y 2015 con
respecto al período 1979-1997. La precipitación no se redujo durante el período estudiado y, en
consecuencia, los cambios en la descarga anual dependen presumiblemente de factores que
controlan la distribución estacional de la descarga y la evapotranspiración en la cuenca. Como
ejemplo, los intensos cambios en el uso del suelo junto a un clima regional marcadamente más cálido
pueden ser dos condicionantes del fenómeno. Esto no excluye otros factores como los cambios en la
demanda y abastecimiento de agua potable en la cuenca del Río Grande en las comunidades que se
encuentran distribuidas a lo largo del río. Los resultados muestran que es aún temprano para
observar impactos en los componentes del balance hídrico como resultado directo de la
implementación de un esquema de PSB. Esto motiva la necesidad de una evaluación continua de la
percepción local y un monitoreo los recursos hídricos para garantizar que las necesidades y
demandas de servicios ecosistémicos en la región se mantengan a largo plazo.
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ACKNOWLEDGEMENT
There are several incredible people who I have met during the time I have worked on this project and
each have contributed to make this project possible in different ways. I therefore would like to
warmly thank each of them. First of all, the community La Esperanza and all of you who participated
and were interviewed in this study. Thanks Edison Semanate for being an excellent driver and
assistant during the entire field visit. I would also like to thank Pablo Lloret, at the Empresa Pública
Metropolitana de Agua Potable y Saneamiento (EPMAPS) for welcoming me to Ecuador, being very
supportive throughout the whole project, and together with Ximena Fuentes, for giving me the
opportunity to explore and learn more about the different páramo ecosystems in Ecuador. I am also
grateful for the support I have received from Altropico, and the data and information provided from
the Instituto Nacional de Metrologia e Hidrologia (INAMHI) and the Gobierno Autónomo
Descentralizado de la Provincia Del Carchi. At the Department of Physical Geography at Stockholm
University, I want to thank Steve Lyon for your optimism, overall support throughout the whole
project and for being quick in response and assistance when needed. I am also very grateful for the
support received from Lowe Börjesson, at the Department of Human Geography. Thanks also to
Carol Hunsberger at the department of Geography University of Western Ontario in Canada for
inspiration to undertake the project. Thanks to the Department of Ecology, Environment, and Plant
Science at Stockholm University and the Swedish International Development Cooperation Agency
(SIDA) for financial support. I would also like to thank all the friends and families who have helped
and encouraged me along the way, especially Camilla Hallström, Stefan Johansson, Bengt Hallström,
Geoff Penhorwood, Imanol Rubio, Mariana Semanate, Maritza Cevallos, and Johanna Lundberg.
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TABLE OF CONTENTS
1. INTRODUCTION ................................................................................................................... 8
1.1. Payment for Ecosystem Services as a management approach of natural resources .......... 8
1.2. What is the “páramo”? ........................................................................................................ 9
1.3. A case study of Payment for Ecosystem Services in the páramo ...................................... 10
2. DATA AND METHODS ........................................................................................................ 11
2.1. Site description .................................................................................................................. 11
2.2. The characteristics of Río Grande watershed and the páramo vegetation ...................... 13
2.3. Climatological and Hydrological Data Considered and Data Quality Assessment ............ 14
2.4. Long-term water balance observations ............................................................................ 15
2.5. Potential impacts of the PSB scheme on the hydrological and climatological
parameters ........................................................................................................................ 16
2.6. Statistical hypothesis testing ............................................................................................. 17
2.7. Qualitative evaluation of the local people’s observations of the bio-physical conditions
and the PSB ........................................................................................................................ 17
3. RESULTS ............................................................................................................................. 19
3.1. Assessing Data Quality ...................................................................................................... 19
3.2. Long term water balance observations ............................................................................. 22
3.3. Short term water balance observations and impacts of the PSB ...................................... 25
3.4. Local observations of the bio-physical condition and the PSB scheme ............................ 28
4. DISCUSSION ....................................................................................................................... 34
4.1. Water balance analysis and local observations of the bio-physical conditions in the
watershed .......................................................................................................................... 34
4.2. Potential páramo and land use impacts on hydrological parameters in the watershed .. 34
4.3. The PSB scheme as a land-water resource management strategy ................................... 35
4.4. Uncertainties and limitations of the study ........................................................................ 37
5. CONCLUSIONS ................................................................................................................... 38
6. REFERENCES ...................................................................................................................... 39
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APPENDIX
APPENDIX A: THE RÍO GRANDE WATERSHED AND THE PÁRAMO VEGETATION .......................... 44
APPENDIX B: LIST OF RESPONDENTS............................................................................................. 47
APPENDIX C: INTERVIEW GUIDE ................................................................................................... 48
APPENDIX D: MATRICES USED FOR THE QUALITATIVE ANALYSIS ................................................. 49
APPENDIX E: DATA QUALITY ASSESSMENT; BOXPLOTS ................................................................ 51
APPENDIX F: DATA QUALITY ASSESSMENT; MEAN MONTHLY AVERAGES ................................... 52
APPENDIX G: ANNUAL OBSERVATIONS OF THE HYDRAULIC AND CLIMATOLOGICAL
PARAMETERS; BOXPLOTS .............................................................................................................. 53
APPENDIX H: STATISTICAL ANALYSIS; WATER BALANCE OBSERVATIONS (18 YRS) ...................... 55
APPENDIX I: STATISTICAL ANALYSIS; MONTHLY WATER BALANCE OBSERVATIONS (18 YRS) ...... 56
APPENDIX J: STATISTICAL ANALYSIS; WATER BALANCE OBSERVATIONS (12 YRS) ....................... 58
APPENDIX K: STATISTICAL ANALYSIS; WATER BALANCE OBSERVATIONS (6 YRS) ......................... 60
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1. INTRODUCTION
1.1. Payment for Ecosystem Services as a management approach of natural resources
Payment for Ecosystem Services (PES) have been the subject of increasing global popularity since the
early 1990s as a strategy to improve the management of ecosystem services (Grima, et al., 2016). PES
schemes are often referred to as a volunteer based management strategy, where an investor is
paying a seller to sustain the provision of a specific ecosystem service, often (but not always) through
conservation practices (Wunder, 2005). The concept of ecosystem services and PES schemes have
emerged as a response to the market and policy makers failure to value and consider non-monetary
resources of for example, air, water, forests, wetlands and local knowledge (McMichael, 2012;
Muradian, 2013). With economic compensation, the interests of landowners and external actors
regarding ecosystem services were expected to increase (Wunder, 2007; Grima, et al., 2016).
Even though economic preconditions have been developed for PES schemes (Börner, et al., 2010)
and many PES schemes are in place (Martin-Ortega, et al., 2013). Information and knowledge barriers
exist for implementing PES schemes because of long geographical and/or social distances between
the providers and investors (Muradian, 2013). An example of this would be highlighted in watershed
based PES schemes between upstream providers and downstream beneficiaries of ecosystem
services related to the supply of fresh water (Muradian, 2013). Other impediments for PES schemes
include institutional preconditions, land grabbing, insecure tenure, overlapping claims, and the lack
of information on private tenure (Börner, et al., 2010). The results and outcomes from a PES scheme
should therefore not be taken for granted and are typically considered to not be able to replace
regular command-and-control strategies of ecosystem services and natural resources (Wunder, 2007;
Börner, et al., 2010; Muradian, 2013). There is thus a risk that the “wrong” land managers or land
areas can be targeted due to a poor design of a PES scheme and that the desired hydro-ecological or
conservation benefits will not be received consequently (Porras, et al., 2013). Many small-scale
landowners, for example, in the Brazilian Amazon are struggling with soil fertility in traditional slash-
and-burn systems (Börner, et al., 2010). Due to unequal distribution of land, they would not benefit
from regular command-and-control environmental management strategies without compromising
with their welfare. Targeting instead the large-scale land owners, who contribute the most to
deforestation with PES schemes would be more beneficial (Börner, et al., 2010). However, many
ecosystem services are often treated as common-pool or public goods, and this could present a social
dilemma in terms of how best to manage (Muradian, 2013). In this case, PES schemes could be an
incentive for collective actions, where the effectiveness of the program depends much on the social
meanings (context and culture) of the PES scheme (Muradian, 2013). Most of the PES schemes that
are in place have only operated for less than 10 years and take shape only through a learning by
doing process (Martin-Ortega, et al., 2013). As such, the science (bio-physical and local
improvements), practices and theory behind PES schemes need to be explored (Martin-Ortega, et al.,
2013).
Latin America has pioneered the concept and the implementation of PES schemes (Martin-
Ortega, et al. 2013; Grima, et al. 2016). Costa Rica is a good example of this as it was the first country
in 1997 to implement a public PES scheme (FONAFIFO) (Pagiola, 2008). Since then, Colombia, Bolivia
and Brazil have all adopted PES strategies into their public conservation and environmental strategies
(Grima, et al., 2016). Ecuador is not an exception and many different types of PES schemes have been
implemented during recent years to protect the tropical mountain ecosystem “páramo” and the
water resources these areas generate to downstream societies (Southgate & Wunder, 2010). The
community based PES scheme in the Pimampiro society is one example where economic
compensation to upstream land owners to protect the water resources in the area has been
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conducted (Southgate & Wunder, 2010). In the Ecuadorian capital, Quito a larger PES scheme
(FONAG) works to sustain the quality of the fresh water provided from surrounding páramo areas
(Southgate & Wunder, 2010). The Program Socio Bosque (PSB) is another public PES scheme that the
state of Ecuador implemented in 2008. This PSB scheme is compensating land owners, both
individuals and different collectives such as communities and indigenous groups, with legal rights to
land areas of tropical forest, cloud forests, dry forest, high altitude forests and other ecosystems
including the páramo (Ministerio del Ambiente Ecuador, 2016). The objectives with the PSB are to
conserve the ecological, economic and cultural values of these ecosystems (like water resources);
significantly decrease the deforestation and consequences of global warming; and to improve the life
for the people living in rural areas, specifically indigenous and peasant communities (Ministerio del
Ambiente Ecuador, 2016) (Ministerio del Ambiente Ecuador, 2017). By 2015 in total 2775 contracts
had been signed, covering 1´500´000 ha of different vegetation types (Ministerio del Ambiente
Ecuador, 2016). Approximately, 273 contracts are covering 61’000 ha of páramo (Ministerio del
Ambiente Ecuador, 2015).
1.2. What is the “páramo”?
The word “páramo” has many different meanings and is typically used to describe an ecosystem,
geographic area or a climate condition as much as it is used to describe a zone of life and a
productive site (Hofstede, 2014). However, it is often used to refer to the vegetation zone above the
tree limit and below the snow limit in tropical mountain ecosystems that typify South America. This
area is dominated by shrubs, herbs and different grass types that are growing in tufts (Beltrán, et al.
2009; Sklenár, et al. 2005). Tropical mountain conditions, similar to the páramo, exist also in other
continents such as in the tropical eastern parts of Africa (Hedberg, 1964). Typically, the climate
variations over the year are small in these zones, but the temperature shifts can be large between
night and day (up to 20 °C) (Buytaert, et al., 2006; Hedberg, 1964). Such conditions are described as
“being summer during the day, but winter during the night” and days with high solar radiation and
cold nights with frost are common (Hedberg, 1964). In South and Central America, the páramo forms
an interrupted belt along the Andes mountain ridge from Peru to Venezuela with two divergent parts
in Panama and Costa Rica (Hofstede, 2014).
Despite the extreme climate conditions in the páramo, the plants have adopted and developed a
variety of different characteristics to survive. The genus Espeletia (Appendix A), for example, have
evolved super-cooling mechanism of the adult leaves to protect them from freezing and dead leaves
retained along the stem to give isolation (Rada, et al., 1987; Goldstein & Meinzer, 1983). The long
stems protect buds from the cold at ground level during the night (Smith, 1980). This evolution, also
improves the pith water storage capacity and allows for better survival during long periods of water
stress (Goldstein, et al., 1985). Due to this adaptation capacity, the flora of the páramo have formed
one of the World’s most unique high elevation mountain ecosystem with a rich biodiversity and
endemism. In total 3595 species have been found in these biotopes (Sklenár, et al., 2005), including a
total of 126 species of the genus Espeletia up to an elevation of 4500 m in the páramo of Ecuador,
Colombia and Venezuela (Sklenár, et al., 2005). Only in Ecuador, where the páramo covers
approximately 5 % of the land surface (1’337’119 ha) (Beltrán, et al., 2009) in total 404 genera and
1524 species of plants have been found and is to its size the country where the flora is most diverse
(Sklenár, et al., 2005). Apart from the biodiversity, the soils in the páramo (mostly Andisols and
Histosols) serve an important ecosystem function since they regulate (store) incoming precipitation
to generate a uniform base flow to connecting rivers, like the Amazon basin, throughout the year. In
addition, there are many urban areas downstream from the páramo that are dependent on the fresh
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water supplies from the páramo’s base flow sustaining soils, among those the cities Quito, Cuenca,
Bogata and Mérida (Buytaert, et al., 2004; Sklenár, et al., 2005).
Many of the people living in the páramo in Ecuador have marginalised income sources and are
dependent on the land for the cultivations of vegetables and potatoes for the household and/or to
sell on local and regional markets. Alternatively, sheep and cattle are kept and allowed to graze in
the páramo (Mena Vásconez & Hofstede, 2006). Current research agrees that intensification of these
types of land use practises increase the bare land and subsequently the erosion problems in the
páramo, this in turn affects the water retention capacity (Poulenard, et al., 2001; Podwojewski, et al.,
2002; Buytaert, et al., 2004; Buytaert, et al., 2005; Buytaert, et al., 2006), the slow hydraulic response
and the uniform distribution of water to connecting streams in the páramo. As a consequence this
could result in a smaller base flow and larger peak flows (Buytaert, et al., 2005). These research
efforts have taken place at such small scales that the extent to which large scale land use changes
affect the hydrodynamic nature of the páramo is still not completely understood. There are few
discharge stations in these high-altitude regions (Mosquera, et al., 2016). The dynamics of runoff and
the interactions with rainfall is therefore not well studied and far from completely understood
(Mosquera, et al., 2016). In addition, the topography in the tropical Andes is highly irregular and the
weather is influenced both by winds from the Atlantic and the Pacific Ocean. Evaluating changes in
the climate and its impacts on water resources is therefore difficult (Buytaert & De Bièvre, 2012).
However, due to these uncertainties there is a concern that the agriculture zone is expanding in the
páramo and the deforestation increasing (Vanacker, et al., 2003; Mena Vásconez & Hofstede, 2006),
while the potential impact of these changes are largely unknown for downstream populations.
The PES schemes like the public PSB scheme have been argued to be a good and effective
conservation strategy to protect natural ecosystems in Ecuador from deforestation (de Koning, et al.,
2011). The success with PES and PWS schemes in Latin America and in Ecuador have, however, not
been quantified to a large extent (Martin-Ortega, et al., 2013; Grima, et al., 2016). Most of the
criticisms of PES and PWS have been focusing on the schemes’ neoliberal approach of making nature
and ecosystem services a commodity for the benefit of commercial purposes in downstream areas
(Rodríguez de Francisco, et al., 2013; Boelens, et al., 2014). People in upstream areas, who are
dependent on the land and the ecosystem services from the páramo for their livelihood have been
argued to not benefit economically from participate in PES schemes (Boelens & Rodríguez de
Francisco, 2014; Boelens, et al., 2014). In several watersheds, for example, PES schemes in
combination with other general environmental laws have potentially made the life more restricted
for families living in upstream areas (Boelens & Rodríguez de Francisco, 2014; Boelens, et al., 2014).
The population size and poverty level of the people and communities participating in the PSB are not
considered in the PSB contracts, and it could as such be a challenge to combine poverty reduction
targets with the conservation objectives of the PSB (Krause & Loft, 2013).
1.3. A case study of Payment for Ecosystem Services in the páramo
Despite (or perhaps due to) the complexity whereby a PES scheme includes both bio-physical
conditions and social inference, few studies of the PES schemes in Ecuador have considered the bio-
physical aspects. Such as, for example, impacts on water resources, in combination with the
underlying conservation motivations for a PES scheme while assessing the participant’s perspective.
This current study aims to contribute to fill this lack of information by the evaluation of a páramo
land targeted with a PES scheme and by focusing on to evaluate potential impacts the PES scheme
could have on the provision of water the páramo land is generating to downstream societies. An
interdisciplinary approach has been used, which is advantageous when considering problems that are
increasingly complex and intertwined. Such an approach allows a problem to be studied from
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different angles (e.g. both the physical and the human dimension) and thereby can both contribute
to and challenge different perspectives (McNeill, et al., 2001). The study focuses on the Río Grande
watershed in the northern parts of Ecuador. This study site was chosen after an evaluation of
available hydraulic observations in the Ecuadorian páramo in combination to the location of different
implemented PES schemes. In the Río Grande watershed, the local community has legal rights to a
mountainous area with a páramo ecosystem. In August 2009, this community was among the firsts to
participate in the PSB. The distribution of water in the watershed over the last decades is evaluated
from a water balance approach. This was accomplished by analysing general trends and long-term
step changes in the precipitation (P), discharge (Q), actual evapotranspiration (AET), potential
evapotranspiration (PET) and temperature (T) in the watershed. Secondly, the study considers
potential impacts of the PSB scheme on the water balance components (P, Q, AET and PET) of the Río
Grande watershed. In addition, semi-structured interviews were conducted with a selected group of
people from the community to assess local perceptions of the PSB, and the impacts of the PES
scheme on both local and regional water resources. Taken together, such an interdisciplinary
approach will allow for a better understanding of the bio-physical conditions in the watershed, the
páramo and the PSB scheme as a land-water management strategy.
2. DATA AND METHODS
2.1. Site description
The river Río Grande in the northern parts of Ecuador (Figure 1), has its headwaters in the páramo of
the community “La Esperanza”, on the eastern side of the active stratovolcano Chiles (4748 m.a.sl)
(Instituto Geofísico, EPN, 2017). At lower elevations, the river meanders through a mosaic landscape
with potatoes cultivations and grasslands mixed with pastures. It then passes by the village Tufiño
with a population of approximately 2300 people (GAD Tufiño, 2015) before it converges with the
river Játiva o Alumbre and form the river Río Carchi. This is the river that makes up the border
between Colombia and Ecuador in this region. The watershed of Río Grande has an area of 54 km2
(INAMHI, 2016) and is the focus of this study both when it comes to the quantitative hydrological
analysis and the qualitative data collection. The water of Río Grande is lead through an open channel
system to one of the local power plants before the river converges with the river Játiva o Alumbre.
The Río Grande watershed is also supplying the communities downstream in the province with
freshwater, among those Tulcán, (Riascos, 2016) a city with a population of approximately 77 175
people (Gobierno Autónomo Descentralizado Provincial del Carchi, 2013). The community of La
Esperanza has about 350 families and received legal status on August 01, 1938 when it was
registered in the Registro Nacional de Comunas in the Ministerio de Previsión Social y Comunas. It
has legal rights to a mountainous land area of 14163 ha in the canton (Cantón) Tulcán between the
parishes (parroquias) Tufiño y Maldonado (Vásquez Narváez, 2008). Most of the people within the
community live downhill from the páramo land both on the western and eastern side of the
mountain ridge and the active stratovolcanoes Chiles and Cerro Negro. On the western side, in the
parish Maldonado, the people live in small villages in valleys. In these villages, the climate is
temperate to sub-tropical and the people are mainly dedicated to the production of granadilla,
blackberries and tamarillo fruit. On the eastern side, where this study is focused, most of the people
of the community live in the village Tufiño, located at an elevation of about 3120 m.a.sl. Here the
climate is colder and the people are mainly dedicated to the production of potatoes and milk
(Appendix A), which are sold at the local markets. Also, beans and “mellocos” (Ullucus tuberosus) are
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cultivated, but mainly for home/personal consumption (Vásquez Narváez, 2008). The temperature
shift is high between night and day in the village and the only available source to heat up their
houses is burning firewood. Since August 2009, the La Esperanza community has been participating
in the national conservation program Socio Bosque (PSB), with 8622 ha of land set aside for
conservation (Figure 1), most of which is páramo (Puetate, 2016). Approximately 40 % of the PSB
area is located within the watershed of Río Grande (Figure 1). A PSB contract covers a period of 20
years, which can be renewed after that time. For the first 50 ha registered, the PSB gives $ 30
US/ha/year. For larger land areas of 51-100 ha, the rate is $ 20 US/ha/year (Minesterio del Ambiente
de Ecuador, 2011).
Figure 1. Reference system: WGS 1984 UTM Zone 18N. Projection: Transverse Mercator. Data sources: Gobierno Autónomo
Descentralizado de la Provincia Del Carchi, Instituto Nacional de Metrologia e Hidrologia (INAMHI). Illustration of the sub
catchment of the rivers Río Grande (54 km2) and Játiva o Alumbre (72 km2) to the catchment Río Carchi. Of the total area of
the páramo La Esperanza included in the program Socio Bosque (PSB) (8622 ha) approximately 40 % is within the watershed
of Río Grande and Játiva o Alumbre. In the map the neighbour watersheds Río Carchi, Río Napo and Río Mira are highlighted
and also the metrological and hydrological stations of Precipitation (P), Discharge (Q) and Temperature (T) considered in this
study.
Content may not reflect National Geographic's current mappolicy. Sources: National Geographic, Esri, DeLorme, HERE,UNEP-WCMC, USGS, NASA, ESA, METI, NRCAN, GEBCO,NOAA, increment P Corp.
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2.2. The characteristics of Río Grande watershed and the páramo vegetation
Between the highest point of the volcano Chiles (4723 m.a.sl) (Instituto Geofísico, EPN, 2017) of the
watershed of Río Grande and the lowest point at the discharge station (H0091) (3120 m.a.sl) there is
a difference of 1603 m in altitude. The vegetation of the páramo changes spatially with different
climate conditions (Table 1). By Boada, et al. (2008) in total five different vegetation characteristics of
the páramo of La Esperanza were studied: high mountain evergreen forest, herbaceous páramo,
páramo of frailejones, dry páramo and montane grassland lakes (Appendix A). The high mountain
evergreen forest is the transition zone between forest and páramo vegetation and is generally found
at an elevation of around 3000 m.a.sl (Boada , et al., 2008). In the páramo of La Esperanza, 23 species
of trees, with a mean high of 3.51 m were found by Salgado (2008) in this zone including Escallonia
myrtilloides (Grossulariaceae), Polylepis sericea (Rosaceae), Oreopanax seemanianus (Araliaceae),
Miconia latifolia (Melastomataceae), Gynoxys sp. (Asteraceae) and Polylepis incana (Rosaceae). In
the herbaceous páramo of La Esperanza (3400-4000 m.a.sl), a total of 88 species of herbs were found
by Salgado (2008). These were dominated by grass types that are growing in tufts like Calamagrostis
intermedia (Poaceae), Carez muricata (Cyperaceae), Cortaderianitida (Poaceae) y Paspalum sp.
(Poaceae). In the vegetation zone páramo of frailejones (3500-3700 m.a.sl.) a total of 21 species of
plants were found by Salgado (2008) including Puya clava-herculis (Bromeliaceae), Loricaria
thuyoides (Asteraceae), Hyperium lancioides (Clusiaceae), Gynoxys fuliginosa (Asteraceae) and “El
Frailejón” Espeletia pycnophylla ssp. angelensis (Asteraceae) (Appendix A). “El Frailejón” forms big
fields of forests in the páramo of La Esperanza and is a plant that has only been found in these
northern parts of Ecuador (apart from a divergent population in Tungurahua) and in the Andes of
Colombia and Venezuela (Boada, et al., 2008). In the vegetation zone Montane grassland lakes
(>2100 m.a.sl.), lakes and lagoons are found and the flora are restricted to the related banks. Laguna
Verde is one example in the páramo of La Esperanza (Figure 1). Appendix A, illustrate some of the
plants identified at this site during the field visit in August 2016.
Table 1. Different vegetation zones of the páramo of La Esperanza (El páramo del Artesón) studied by Boada, et al. (2008).
Altitude (m.a.sl)
T min (°C)
T max (°C)
Annual P (mm)
Annual PET (mm)
Vegetation characteristic
High mountain evergreen forest
3000-3400 6 17 922 882 Transition zone between forest and páramo
Páramo of herbaceous
3400-4000 4 13 722 820 Herbs growing in tufts (Calamagrostis and Festuca)
Páramo of frailejones
3500-3700 5 13 983 805 “El Frailejon” Espeletia (Asteraceae)
Dry páramo ≥4200 3 12 754 766 Islands of grass and shrubs, a few mosses and lichens
Montane grassland lakes
>2100 - - - - Flora restricted to the banks of lakes and lagoons.
In total 39 species of birds of 17 families were found by Buitrón (2008) in the páramo of La
Esperanza. Among those are many of the families Trochilidae (hummingbirds) and Thraupidae
(tangaras). Few individuals of the condor (Vultur gryphus), which is a species nearing extinction in
Ecuador, have been seen in the páramo around the volcano Chiles but, but in the study by Salgado
(2008) none were found.
The páramo also constitutes the home for many mammals. According to Boada (2008) a total of
19 species were found in the páramo of La Esperanza. Among those were the “puma” Puma
concolor, “Lobo de páramo” Lycalopex culpaeus, “Zorrillo” Conepatus semistriatus, “Oso de anteojos”
Ellinor Hallström
14
Tremarctos ornatus, “Coatí andino” Nasuella olivacea, “Comadreja andina” Mustela frenata and the
“Gato de las pampas” Leopardus pajeros.
The soil of the páramo in Ecuador is composed of a parent material of ash from the Holocene
(younger than 10 000 years). Around Quito and on slopes of active volcanos the soil is younger,
coarser and richer in primary minerals. In contrast to these northern parts of Ecuador, where the
Andisols are older (300 BP) and richer in non-allophanic poorly ordered constituents. These soils are
more associated with organic matter (up to more than 15 %) (Poulenard, et al., 2001). For most
Andisols it is typical with an enrichment of organic matter averaging about 8 %. The degree of
organic matter can be higher if the volcanic soil develops a low pH and Al-humus complexes start to
form (Eriksson, et al., 2005). The permeability and water retention capacity is normally good in this
type of soil, since the bulk density (the total mass of the material of the total volume) is normally low
(less than 0.9 kg/dm3) (Eriksson, et al., 2005).
2.3. Climatological and Hydrological Data Considered and Data Quality Assessment
The input data, namely precipitation (P) from 1975-2015, discharge (Q) from 1967-2015 and
temperature (T) from 1963-2015 used in this study are all primary data generated by the Instituto
Nacional de Metrologia e Hidrologia (INAMHI) (Table 2), delivered as monthly averages with a
minimum of 20 days of measurements for each month. The discharge station (H0091) used is located
before the river Río Grande converges with the river Játiva o Alumbre, and before the water of Río
Grande is led through an open channel system to one of the local power plants. The discharge
observations at this station are based on daily measurements of the water level, every morning and
afternoon, and has been conducted by the same observer for the last 23 years (Trujillo Tupe, 2016).
This data has then been reported to INAMHI who have made the estimates of the discharge (m3/s) in
the river Río Grande (INAMHI, 2015).
There are several rain gauges in this northern highland region of Ecuador, installed according to
the norms of the World Metrological Organisation (WMO) (Figure 1). The precipitation at these
stations has been observed at three specific times per day (07, 13 and 19 h) and reported to INAMHI
(INAMHI, 2015). Only one of the rain gauges (M0308) is located in the watershed of Río Grande at
the altitude of 3418 m.a.sl. The annual P of this station was compared both graphically and with a
Kruskal Wallis statistical test to the average annual P calculated from five stations in the region (Table
2). This was done to assess potential variability due to the highly irregular topography in the region
and the potential for the added value of considering the P data available from stations that are
located in the neighbour catchments Río Napo and Río Mira. Based on this initial comparison of
regional rain gauge data and the uncertainties associated with wind patterns and the distribution of
P in the region, only data from the M0308 station were used for further analysis in this study.
For the temperature estimates in the region of the Río Grande watershed, the data from two
meteorological stations were used: M0102 (3000 m.a.sl.) and M0103 (2860 m.a.sl.). While these
stations are located in the neighbouring watershed of Río Míra, they are considered representative
since they are located at more or less the same altitude as the discharge station (H0091) (3120
m.a.sl.). As such, these were used on the assumption that the T in the region does not vary in the
same way the P patterns might do.
The input data was organised into hydrological years from dry period to dry period (August to
August) and the quality of the data was assessed graphically. This allowed for a better understanding
of the data and to identify possible patterns and trends. With the use of boxplots potential outliers
was identified. In all the original data series of P, T and Q, some months of data were missing. In the
discharge data, some of the gaps were larger. Over the entire period of observation, the years with
more than two months of monthly data missing were marked, including the hydrological years 1984-
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1986, 1992, 1994 and 2003-2004. The impact of including the years with the remaining gaps (≤ 2
months) in the measured observations of the P, Q and T data was assessed with a non-parametric
Wilcoxon Rank Sum test.
Annual actual evapotranspiration (AET) was estimated using the water balance approach
(Equation 1), where the change in storage (ΔS) was assumed to be zero for the analysis on an annual
scale:
P = Q + (AET + ΔS) (Equation 1)
The potential evapotranspiration PET was estimated using the Langbein (1949) equation (Equation
2). Where PET is the estimated potential evapotranspiration (mm/yr) and T is the annual average
temperature.
PET = 325 + 21T + 0.9T2 (Equation 2)
Table 2. Meteorological and hydrological stations measuring P, T and Q in the northern highland region of Ecuador, considered in this study.
Type Station Name Watershed Province Latitude Longitude Altitude (m.a.sl)
Data (years)
P M0102 El Angel Río Mira Carchi 0G 37' 8.2" N 77G 56'41.4" W
3000 1964-2015
P M0305 Julio Andrade
Río Mira Carchi 0G 39' 23.1" N
77G 43'13.2" W
2890 1964-2015
P M0103 San Gabriel
Río Mira Carchi 0G 36' 15" N 77G 49'10" W 2860 1964-2015
P M0101 El Carmelo
Río Napo Carchi 0G 41'3" N 77G 36'42" W 2955 1964-2015
P M0308 Tufiño Río Carchi Carchi 0G 48' 1.1" N 77G 51'19.7" W
3418 1975-2015
Q H0091 Grande Aj Jativa
Río Carchi Carchi 0G 48' 15" N 77G 50' 46" 3120 1967-2015
T M0102 El Angel Río Mira Carchi 0G 37' 8,2" N 77G 56'41,4" 3000 1963-2015
T M0103 San Gabriel
Río Mira Carchi 0G 36' 15"N 77G 49'10" W 2860 1963-2015
2.4. Long-term water balance observations
To get a better understanding for the water resource distribution in the Río Grande watershed the
water balance components P, Q, AET, PET and T were evaluated over a longer period of time. The
long-term general trend of the parameters was analysed using a regression analysis. All trends were
tested assuming the data was following a linear trend. As such, the resulting slope for each data
series was statistically tested using a t-test against the slope of 0 (the null hypothesis) and a
significant level of 5 %.
For the trend analysis for these years, the data series of P and Q were interpolated in the
statistical software JMP from SAS and all monthly gaps in the data was filled using a linear
relationship between the two surrounding monthly values around the missing value (Equation 3).
The impact of this interpolation method on the trend analysis was also explored to avoid any
spurious correlations.
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16
𝑥𝑛𝑒𝑤 = 𝑥𝑡2−𝑥𝑡1
𝑡2−𝑡1× (𝑡𝑛𝑒𝑤 − 𝑡1) + 𝑥2 (Equation 3)
xnew: new value
xt1: monthly average at time t1
xt2: monthly average at time t2
t1: month before xnew
t2: month after xnew
In addition to the regression analysis, step change analysis of the P, Q, AET, PET and T data were
conducted for the 18-years periods from 1979-1997 and 1997-2015. The break point of 1997 was
selected to allow for an even amount of data in both periods and to simplify comparison between
the different short-term step change analysis conducted to evaluate the impacts of the PSB. The
years with more than two months of data missing in the Q data (1984-1986, 1992, 1994 and 2003-
2004) were excluded in all the step change analyses. Considering the remaining years with missing
monthly data and the uncertainties these gaps bring to the interpretation of the results, in these step
change analysis, the data series of the hydraulic parameters including the years with gaps were
analysed. Additionally, the gaps in the data of the hydraulic parameters were filled using two
different strategies; a linear relationship between the two surrounding monthly data values around
the gap (Equation 3); and the average of the four surrounding monthly values around the gap. These
two data sets with filled gaps were also analysed. Overall, the goal of considering these variations in
gap filling vs. not gap filling of the data was to ensure a robust estimate of potential step-shift in
either forcing or response components of the water balance parameters.
Monthly averages of the P, Q, AET and T data were calculated and compared between the 18-
years periods 1979-1997 and 1997-2015. This was done to analyse whether or not the distribution of
the hydrologic parameters had changed over the seasons rather than on an annual scale. For these
analysis the data series with gaps filled (Equation 3) was used.
2.5. Potential impacts of the PSB scheme on the hydrological and climatological parameters
The PSB was implemented in August 2009 in the páramo ecosystem of the local community La
Esperanza. To monitor whether or not the PSB scheme has had an impact on the climatological and
hydrological parameters in the watershed, short-term step change analysis using 6-years periods and
12-years periods were conducted. In addition, this analysis tested for the robustness of the results
for the time periods considered when assessing change in the system. For these analysis, the years of
1979-2014 were used for the precipitation and evapotranspiration data. The discharge and
temperature data looked further back in time. As such the analysis of these parameters was
extended to include the years 1967-2014. The same data series (including gaps and gaps filled) that
were used in the 18-years step change analysis were also considered in this analysis. A
complementary data series of the annual estimates of each of the parameters was conducted from
the sum of the monthly averages of the P, Q, AET and T.
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2.6. Statistical hypothesis testing
The null hypotheses (H0), that the annual estimates of the hydraulic parameters P, Q, AET, PET and
annual average T were the same in the different time periods considered in the step change analysis
was statistically tested using the JMP software from SAS. The distributions of the data in the different
periods were checked using histograms and normal quantile plots. A normal distribution could not be
guaranteed for all periods. The non-parametric test Wilcoxon/Mann Whitney for two independent
samples was therefore used. In the short-term step change analysis, in the case with more than two
periods of data to test the nonparametric Kruskal Wallis test was used. From this test, it is only
possible to tell whether or not there is a significant difference between the different populations,
and not which populations are different. The multi comparison test Wilcoxon Method for Each Pair
was therefore used as a complement to these analyses if the H0 from the Kruskal Wallis test could be
rejected.
Non-parametric rank-based tests are often less powerful than a parametric approach, meaning
that it is easier to make a Type II error by not rejecting the H0 when it is false. The power of the tests
could be increased by increasing the significance level deemed acceptable, but that would in turn
increase the chance of making a Type I error of rejecting H0 when it is true (Weiss, 2014). For these
tests a significance level of 5 % was used. If a p-value resulted to be ≤ 0.05 in the tests, one of the
populations could be concluded, with 95 % confidence, to have a significant higher or lower annual
observation.
2.7. Qualitative evaluation of the local people’s observations of the bio-physical conditions and the
PSB
To get a better understanding of the physical conditions of the watershed of Río Grande and how
they were perceived, qualitative data and information were collected by key informant interviews
(Mikkelsen, 2005) with people in the community La Esperanza. The aim with these interviews was
also to characterize the local perception about the PSB as a land/water management strategy. The
target group of participants were middle age or older with experience in the land use of the
community and how it has changed over time, and with knowledge of the implementation of the PSB
scheme. Semi structured interviews were chosen, since this type of interview can be organised into
structured, but flexible interviews and gives an advantage for the researcher to identify issues that
could be unknown in advance (O'keeffe, et al., 2015; Mikkelsen, 2005). The interviews were
completed in August 2016, seven years after the implementation of the PSB.
In total, 13 interviews were completed that lasted between 15-45 minutes (Appendix B). Due to
confidentiality and ethical considerations all respondents participating in the study are presented
anonymously. The interviews were conducted with a volunteer approach in an undisturbed
arrangement, most of them (Nr. 1-7, 9-10, and 13) in connection to community meetings. The other
interviews were conducted with people that were met in the field. A pre-tested interview guide
(Appendix C) of questions was used during the interviews to structure the interviews and to be sure
that all topics were covered. Interviews started with a presentation of the purpose of the study and
by informing and checking if it was allowed to record the interview. The interviews covered a primary
section with questions about the area, its natural resources, ecosystem services and disservices and a
second section about the conservation program Socio Bosque. The interviews were flexible in their
construction and opened to add, skip or change the order of the questions depending on how the
interview was progressing and the different themes covered. All interviews were recorded except for
one, which took place outside in the páramo. Brief notes were taken during all interviews, but more
detailed notes were taken during the interview that was not recorded. These notes were reviewed
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and summarized the same day the interview was completed. A Spanish speaking assistant was
present during all interviews, who helped to record the interviews and to translate or sort out
potential misunderstandings. The interviews were transcribed word for word in Microsoft Word.
Each question and answer from this material was then sorted into larger themes covered in the
interview guide (Appendix D). This material was in turn sorted a second time and organised into a
matrix with more detailed themes, questions, and positive/negative/neutral responses (Appendix D).
The underlying material representing a summary of the results was translated into English and is
presented in this study. During this qualitative material work, it was decided that two of the
interviews would not be included in the final summary of the results. The location, where these
interviews took place was considered to have a negative effect on the structure of the interviews and
thereby on the resulting data. One of these interviews took place during a morning shift where the
respondent was milking cows. While potentially biased, this interview setting did provide important
information about the land use practises and life in Tufiño.
Additionally, two semi structured interviews were conducted as a follow up to the initial 13
interviews. The first was with Trujillo Tupe (2016), who is the individual that has been recording the
water level of the river Río Grande. The other interview was with Santiago Levy, who is working with
environmental issues in the province of Carchi. The same interview guide (Appendix C), was used as
the underlying structure for these interviews. These interviews are considered to target regional
experts with the water flows and environmental health in the watershed respectively.
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3. RESULTS
3.1. Assessing Data Quality
In Figure 2 of the annual P data from station M0308 (both data sets including and excluding years
with gaps) for the period 1975-2014 it is possible to recognize that there are highs and lows in the
precipitation that regularly repeat in the data series. For example, years with more than 1600 mm
seem to repeat every 6-10 years and years with less than 888 mm of precipitation every 8-13 year. It
also seems that the precipitation can shift drastically from year to year in the area. Between the
years 1988 (1606 mm) and 1991 (718 mm), for example, there was a drop of 888 mm, also between
the years 1998 (1671 mm) and 2001 (785 mm) there was a drop of 886 mm.
Of the P data that were covering the period Aug 1979 – Jul 2015 (used in the step-change
analysis) the data missed in total 1.6 % of the monthly observations (Table 3). In total, six of the years
were missing one month of data spread over the year, and one year was missing two months of data.
The data set of the annual P including the years with gaps was compared to a set of data excluding
these years. The statistical hypothesis test of this comparison resulted in that the H0 could not be
rejected. As such, no significant difference could be recognised between these data sets on the
significance level of 5 % (Table 3). In addition, the distribution of the monthly average P for the
period 1979-2014 of the two P datasets, including and excluding years with gaps, did not show any
difference over the year (Appendix F). June to September were the months with a lower monthly
average P (41 – 71 mm), while October until May, had a higher monthly average P (92-167 mm).
The annual P estimated from station M0308 and the mean annual P estimated from the five stations
in the region followed similar patterns over the period 1975-2014 (Figure 3). The mean annual P at
the station M0308 (incl. gaps; 1257 mm) was, however, higher than the regional mean annual P
(1106 mm) for the period 1975-2014. A significant difference was also found in the non-parametric
Kruskal Wallis statistical test of the annual P from the two data sets and on the significant level of 5 %
(Table 4). As such, there is a difference between the annual P estimated at the station located in the
watershed of Río Grande, compared to the regional mean annual P. The regional mean monthly
average P had a slightly lower distribution most notable during October to December and March to
May compared to the P from M0308 (Appendix F).
Table 3. Data quality assessment of the P data from station M0308 (Boxplots in Appendix E), using a Wilcoxon Rank Sum test of the annual P (2-Sample Test, Normal Approximation) (α = 0.05).
Period Data Data missing
Min Median Max Mean Std Dev
S Z P-value
Year % Mm mm mm mm mm
1975-2014
P (excl. gaps)
1.6 785.4 1217.4 1762.3 1250.4 235.7
P (incl. gaps)
784.6 1250.4 1762.3 1257.5 242.4 1205 -0.1774 0.8592
1979-2014
P (excl. gaps)
1.7 785.4 1202.3 1762.3 1256.4 236.8
P (incl. gaps)
784.6 1225.0 1762.3 1257.0 244.4 1205 -0.1774 0.8592
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Figure 2 of the annual Q (incl. gaps and excl. years with gaps) from 1967-1979 shows that there have
been highs and lows in the annual Q that have returned regularly. It is also notable that those years
with high flow (1974, 1982, 1988, 1999 and 2014) have decreased over the time. The data used for
the regression analysis and step change analysis of the annual Q (1967-2014) missed 12.7 % of all
monthly observations (Table 5). In total, 13 years of this data missed one or two months of
observations, and eight years missed more than two months of observations. In total, 20 years with
gaps appeared after 1979 and resulted in that the data used for the estimate of the annual AET
(1979-2014) for the step change analysis is missing 16.9 % of its data. No significant difference was
found between the annual Q calculated from the data including gaps and the data excluding the
years with gaps (Table 5). The distribution/patterns of the monthly average Q over the year was
similar for the different data sets (with and excluding the gaps) for the period 1966-1979, with a peak
monthly average Q in May (111-113 mm), and the lowest monthly average Q in September (39-46
mm) (Appendix F).
Table 5. Data quality assessment of the Q data from station H0091 (Boxplots in Appendix E); using Kruskal-Wallis Tests of the annual Q (1-way Test, ChiSquare Approximation) (α = 0.05).
Period Data Data missing
Min Median Max Mean Std Dev
Chi Square
DF P-value
Year % mm Mm mm mm mm
1967-2014
Q (excl. gaps)
12.7 651.0 1045.2 1678.5 1062.2 269.4
Q (excl. gaps > 2 months)
496.3 995.3 1678.5 1005.0 286.0
Q (incl. gaps)
99.7 941.0 1678.5 944.4 327.7 2.356 2 0.3079
1979-2014
Q (excl. gaps)
16.9 651.0 924.5 214.4 1398.9 946.1
Q (excl. gaps > 2 months)
496.3 996.2 286.3 1678.5 1012.2
Q (incl. gaps)
99.7 859.4 295.4 1471.0 856.4 4.7469 2 0.0932
Table 4. Mean annual P at the station M0308 and the mean annual average P in the region, and the results from the comparison of the annual P of these observations using a Kruskal Wallis test (α = 0.05).
DATA PERIOD MEAN (mm)
STDV. (mm)
P Region Aug 1975 - Jul 2015 1105.8 203.2
P M0308 (incl. gaps) Aug 1975 - Jul 2015 1257.5 242.4
P M0308 (excl. gaps) Aug 1975 - Jul 2015 1250.4 235.7
Kruskal-Wallis test p-value
One way, chi-square approximation
0.0017
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Figure 2. Precipitation data from the station M0308 from 1975 - 2014 (A); Annual Q at the station H0091 from 1967 – 2014
including and excluding years with monthly gaps of data missing (B); annual average T (°C) of the two metrological stations
M0103 and M0102 from 1963 – 2014 (C).
Figure 2 shows that the annual average T at both stations (M0103 and M0102) followed similar
patterns during the period 1963 – 2014. The T data between 1963-2014 (used for the regression
analysis) from the station M0102 missed in total 7.4 % of the monthly observations and 10.3 % of the
data for the period 1979-2014 (used for the step-change analysis) (Table 6). The T data from the
station M0103 missed 2.4 % of the monthly observations for the longer period, and 0.2 % for the
shorter period. The mean annual average T at the station M0103 (12.2 °C) was higher than the mean
annual average T at the station M0102 (11.9 °C). A statistically significant difference was also found
when the data series of the annual average T were compared (Table 6). The mean monthly average T
at the two stations M0103 and M0102 follow similar patterns over the year (Appendix F). The mean
monthly average T at both stations vary little over the year with the lowest T in July (11.2 – 11.4 °C)
and the highest in November for the station M0103 (12.8 °C) and in October for the station M0102
(12.2 °C) (Appendix F).
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010 2020
P (
mm
)A
P (incl. gaps) P (excl. gaps) Linjär (P (excl. gaps))
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010 2020
Q (
mm
)
B
Q (incl. gaps) Q (incl. gaps ≤ 2 months)
Q (gaps excluded) Linjär (Q (gaps excluded))
10
11
12
13
14
15
1960 1970 1980 1990 2000 2010 2020
T(°C
)
C
M0103 M0102 Linjär (M0103) Linjär (M0102)
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Table 6. Data quality assessment of the T data from station M0102 and M0103 (Boxplots in Appendix E), using a Wilcoxon Rank Sum Test of the annual average T (2-Sample Test, Normal Approximation) (α = 0.05).
Period Data Data missing
Min Median Max Mean Std Dev
Chi Square
DF P-value
Year % ° C ° C ° C ° C ° C
1963-2014
T M0102 7.4 11.1 11.8 12.7 11.9 0.3
T M0103 2.4 11.6 12.2 13.1 12.2 0.3 1928.5 -4.79 <0.0001
1979-2014
T M0102 10.3 11.1 11.9 12.7 12.0 0.3
T M0103 0.2 11.6 12.3 13.1 12.3 0.3 1928.5 -4.79 <.0001
3.2. Long term water balance observations
The trend of annual P between the period 1975 – 2014 estimated from station M0308 resulted to be
negative (-2.4 mm/year) (Figure 3). The regression analysis also resulted in a negative slope of -3.1
mm/year for the regional mean annual P estimated over the period 1963-2014 (Figure 3). The
statistical tests of these slopes resulted in high p-values (>0.05) of 0.5227, and 0.1310 respectively.
The H0 could therefore not be rejected and no significant linear trends of the data series were found.
The mean annual P at the station M0308 (gaps filled) was 1250 ± 213 mm for the 18 years-period
Aug 1979 – Jul 1997 and 1305 ± 244 mm for the period Aug 1997 – Jul 2015. In the statistical analysis
of the annual P of these two periods no significant difference was neither found in none of the data
series (incl. gaps vs. gaps filled) (Appendix G & H). The mean monthly average P had a similar
distribution over the year during the two periods 1979-1997 and 1997-2015 (Figure 5). No significant
differences between any of the months were found.
The regression analysis of the annual Q between 1967-2014 resulted in a negative trend of -9.85
mm/yr (Figure 3). The statistical hypothesis test of this slope resulted in a low p-value (<0.05) of
0.000492 and as such the negative trend was significant. The period 1979-2015 (885 ± 201 mm)
resulted in a lower mean annual Q compared to the period 1979-1997 (1109 ± 288 mm). The results
from the statistical testing of the annual Q of these two 18-years periods varied between the
different data sets (Appendix G & H). For the data series where the gaps had been filled the H0 could
be rejected, while not for the data series where the gaps had not been filled. The results from the
monthly analysis of the Q (gaps filled) (Figure 5) showed that all months had a lower mean monthly
average Q during the period 1997-2015 compared to the period 1979-1997. For the months between
August to October the differences of the monthly average Q were significant. In the 12-years analysis
of the annual Q, the two later periods 1991-2003 and 2003-2015 had a significantly lower annual Q
compared to the periods 1967-1979 and 1979-1991 (Appendix G & J). These results were consistent
for all the different tested data series (incl. gaps vs. gaps filled). As such, these results indicated that
the annual Q in the Río Grande watershed started to decrease significantly between 1991-2003.
Ellinor Hallström
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Figure 3. Annual P of the station M0308 from 1975-2014 and the mean annual average P in the region from 1964 - 2014 (A).
Annual Q of the station H0091 from 1967-2014 (B); Estimation of the annual AET from 1975 – 2014 and the annual PET from
1963 - 2014 in the Río Grande watershed (C).
P Region: y = -3.0876x + 1210.1R² = 0.0459
P M0308: y = -2.3889x + 1353.3R² = 0.0108
0
500
1000
1500
2000
19
60
19
62
19
64
19
66
19
68
19
70
19
72
19
74
19
76
19
78
19
80
19
82
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
20
02
20
04
20
06
20
08
20
10
20
12
20
14
20
16
20
18
20
20
BEFORE PSB PSB
P (
mm
)A
P Region P M0308 interp. Linjär (P Region) Linjär (P M0308 interp.)
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PET: y = 0.5336x + 693.32R² = 0.3447
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Ellinor Hallström
24
Figure 4. Annual average T from 1963-2014.
Figure 3 of the annual AET from 1975-2014 exhibited highs and lows with regular return. In the
regression analysis, the linear trend of the annual AET from 1975-2014 resulted in a positive slope of
+5.9 mm/year. The statistical test of this slope resulted in a low p-value (<0.05) of 0.004476 meaning
that there was a significant difference between this slope and the slope of zero. The period 1997-
2015 (389 ± 266 mm) had a higher mean annual AET than the period 1979-1997 (225 ± 185 mm). The
18-years step change analysis of the annual AET contradicted, however, the results from the
regression analysis, since the H0 could not be rejected for none of the tested data sets (incl. gaps vs.
gaps filled) (Appendix G & H). The mean monthly average AET (gaps filled) increased most notably
between September to February between these two 18-years periods (Figure 5). Only in July the
differences resulted to be significant. For the 12-year analysis of the annual AET the period 2003-
2015 resulted, however, to be significantly higher compared to the period 1979-1991 (gaps filled)
(Appendix G & J). As such, in this time perspective there was a significant change in the annual AET in
the watershed of Río Grande.
The results from the regression analysis of the annual PET in the region of the Río Grande
watershed were consistent with the results from the regression analysis of the annual AET. The
annual PET had a positive slope of +0.5 mm/year from 1963-2014 and resulted in a low p-value
(<0.05) of 6.3 x 10-6 in the statistical test (Figure 3). This indicated that there was a significant
increasing linear trend of the annual PET in the region for this period. The mean annual PET was
higher during the period 1997-2015 (722 ± 13 mm) compared to the period 1979-1997 (704 ± 9 mm).
The periods of the annual PET also proved to be significantly different under the statistical tests
(Appendix H). The same results that were achieved from the long-term analysis of the PET were
achieved for the analysis of the annual average T. For the period 1963-2014 the average annual T
resulted in a positive slope of +0.01 °C/year and a low p-value (<0.05) of 3.7 x 10-6 (Figure 4). The
mean annual average T for the period 1997-2015 (11.9 ± 0.2°C) increased with 0.4 °C compared to
the period 1979-1997 (12.3 ± 0.3 °C). A significant difference between these two periods of the
annual average T was also found in the statistical tests (Appendix G & H). For the 12-year analysis of
both the annual PET and the annual average T, significant differences between the period 2003-2015
and the two periods 1967-1979 and 1979-1991 were found, and as well between the two periods
1991-2003 and 1967-1979 (Appendix G & J). As such, these results indicate that the annual average T
and the annual PET started to increase significantly between 1991-2003 in the region of the Río
Grande Watershed. In the analysis of the mean monthly average T, all months except from August,
October and June resulted to be significantly warmer during the later period 1997-2015 compared to
the period 1979-1997 (Figure 5).
y = 0,0126x + 11,682R² = 0,3385
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Ellinor Hallström
25
Figure 5. Comparison of the monthly average P (a), Q (b), (AET+∆S) (c) and mean monthly average T (d) between Aug
1979 – Jul 1997 and Aug 1997 - Jul 2015. The striped columns refer to the months that resulted to be significantly
different in the statistical tests (p<0.05) (Appendix I). The error bars refer to the standard deviation of the data (mm).
3.3. Short term water balance observations and impacts of the PSB
Figure 6 shows the mean annual P (A), Q (B), AET and PET (C) of the 6-years periods before and after
the implemented management program Socio Bosque (PSB). The figure shows that the period 1979 –
1985 had a slightly higher mean annual P compared to the other periods between 1985 – 2015.
Figure 6 also shows that the mean annual Q was lower during the four latest 6-years periods
between 1991-2015 compared to the periods between 1967-1991, and that the mean annual AET
increased during these years. No changes in the hydraulic parameters in response to the
implemented PSB scheme in the Río Grande watershed are, however, visible in Figure 6. No
significant shifts (positive or negative response) were neither found in the statistical tests of the
annual observations (6-year and 12-year analysis) that could be related to the implemented PSB
(Appendix J & K). These results were consistent among the different data sets (including and
excluding gaps) and also for the analysis of the mean annual average T in the region (figure 7).
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Ellinor Hallström
26
Figure 6. Mean annual P Aug 1979 – Jul 2015 (A); Mean annual Q Aug 1967 – Jul 2015 (B), Mean annual AET Aug 1979 – Jul
2015; Mean annual PET Aug 1967 – Jul 2015 (C) of the 6-years periods before and after the implemented land use
management strategy Socio Bosque Program (PSB) in the páramo of the Río Grande watershed. Gaps filled (interp.) refers to
the linear relationship method used to fill the gaps, Gaps filled (SMA) refers to the average method used to fill the gaps.
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Ellinor Hallström
27
Figure 7. Mean annual average T for the different 6-years periods between Aug 1967 – Jul 2015 before and after the
implemented PSB scheme. “Seasonal” refers to the estimate of the mean monthly average T; “annual” to the mean annual
average T.
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Ellinor Hallström
28
3.4. Local observations of the bio-physical condition and the PSB scheme
3.4.1. Disservices in the watershed
According to the people of the community that were interviewed in this study, many of the
disservices (Figure 8) the community members who live in Tufiño has to deal with are related to
either the milk production or the cultivation of potatoes. When the summer (dry period) is long and
intense, the shortage of green grass for cattle can be a problem. Several times during the year, the
potatoes also need to be treated with pesticides to protect the harvest from pests and insects.
Another problem related to the cultivation of potatoes is the cold, especially during the dry period
when it can drop to such low temperatures that it destroys the whole harvest.
Figure 8. Local observations, Theme: Disservices and environmental problems in the zone of Tufiño, n=11.
3.4.2. Changes of the physical conditions in the watershed of Río Grande
Most of the respondents in this study mentioned during the interviews that the summer (dry period)
and the winter (wet season) have changed (Figure 9). The dry- and wet seasons used to be more
distinct, while now the respondents said that the weather is more unpredictable and that the
summer is beginning later or is barely notable. From the interview respondents: “Before it used to be
many days with sun, but not that hot ones, while now one barely notice the summer and when it is
sunny it burns a lot, and other days it rains heavily” (Nr. 8, 2016). 18 % of those interviewed also
mentioned that the volcano Chiles used to be more often covered and surrounded by zones of snow;
“Before el Cierro (the volcano) were snowing, there was zones of snow”…”some 20, 40 years, in these
times this exited, but not anymore. In this time the winter and summer were more distinct”… “There
used to be cycles of months, but now no. This is the change of the climate” (Nr 7., 2016). 18 % of the
respondents also mentioned that the problems with the freezing of the potatoes is not such a great
problem anymore and that they now can grow their potatoes with confidence since it has become
warmer. Even though the majority agreed that the weather has changed, when asked about when
these changes started to appear, the answers shifted from 3-5 years ago and up to 20-40 years ago.
1. Pests "mariposa" (butterfly/insect) in potatoes
2. White worms in potatoes
3. Potatoes turns yellow
4. Freezing of the potatoes
5. Heavy rains during the winter
6. Dry periods during the summer
7. Waste management
8. Illegal Fishing
9. There are no problems
10. Wild animals
0%
25%
50%
75%
100%
1 2 3 4 5 6 7 8 9 10
POTATOE PRODUCTION WEATHER OTHER
An
swer
s
Ellinor Hallström
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Figure 9. Local observations, Theme; changes in climate and seasons, n=11.
3.4.3. The páramo and land use practises before and after the PSB
According to the respondents, due to the low temperature in the páramo the only way the
community could use the páramo in any agriculturally productive way before the PSB was to produce
grass for their cattle (Table 7). For this they often would burn the páramo vegetation to stimulate
new green grass to grow. This management practice was something that, especially during the dry
period, could go uncontrolled and burn up several hectares. From the interview respondents, “One lit
a tuft of grass with a matchstick and it gave, but with an extent of four hectares. But before one said
that when the winter comes the grass will grow again. And this served as pasture, which we in turn
could give to the cattle. This is how it was, the alimentation for the cattle itself” (Nr 7., 2016). Today
they have permission from the Ministry of Environment to maintain wild bulls in the páramo. Besides
these wild bulls, any cultivation or grazing with cattle is forbidden in the páramo with the
implementation of the PSB. Instead, the community started to work to protect the páramo by having
five “gurada páramos”, guards that every day use horses or motorbikes to travel up into the páramo
to make sure that everything is controlled.
1.
The "summer" dry period is starting later
2. Extreme weather events are more frequent (eg. High solar radiation and intensive rainfalls)
3. The rainfalls used to be more prolonged
4. The seasons are no longer distinct
5. The water level in the rivers has decreased
6. There used to be zones of snow around the volcano
7. The freezing of the potatoes is not a big issue anymore
8. The quality and quantity of the water in the rivers are affected by sismic activities
Table 7. Local observations, Theme; usage of the páramo area before the start of the PSB in the community La Esperanza, n=11.
Category Cattle Burning Wood We did not use it
Sum I 64% 55% 9% 9%
0%
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50%
75%
100%
1 2 3 4 5 6 7 8
DRY SEASON WETSEASON
GENERAL
An
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Ellinor Hallström
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When the people of the community were asked about what function the páramo performs for the
community today, 90 % of the respondents mentioned the clean water the páramo is generating and
said the páramo acts like a living sponge that is regulating the water flow in their rivers (Figure 10).
According to the respondents, “The páramo regulates the water, the flows in our rivers. In my case
the river El Río Plata. On the other side in Chilma Bajo there is another river, but that also is provided
with water from the páramo” (Nr. 1, 2016). “To us it has the function of the environment that one is
taking care of, for what is our lungs. If not, if we destroy it we won’t have anything” (Nr. 3, 2016).
Many medicinal herbs are also grown in the páramo that have been used for generations in the
community to treat different health disorders. The páramo of the community also attracts both
national and international tourists, that come to hike in the páramo, to see the frailejones, the
volcano Chiles, or to visit the hot springs and spa complexes that exist in the area. Respondents
noted that; “First, they go up to the volcano, then to the “Lagunas Verdes” (the green lagoons). To all
what is páramo. This is because it is beautiful. Of course, it is cold as well but it is even better that
way because then they return content with the breeze it (the páramo) is giving the tourists, and when
coming down from the cold here I wait with the candle” (Nr. 11, 2016). Additionally, 36 % of the
respondents also described the páramo’s value as being a productive site, where the PSB now is
functioning and is generating an income source to the community.
Figure 10. Local observations, Theme: Ecosystem services of the páramo today, n=11.
1
Water resources & regulation of flows in rivers
2 Cattle (wild bulls)
3 Income source (PSB)
4 Flora and fauna
5 Tourism
6 Environment
7 Medicinal plants
0%
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1 2 3 4 5 6 7
An
swer
s
Ellinor Hallström
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3.4.4. The general opinion about the PSB
Most of the people interviewed expressed a gratitude for the PSB and that it has served the
community in many different ways (Figure 11). The compensation from the PSB has covered the
costs of the five guards of the páramo. The president of the community that is elected every year
also receives compensation from the PSB, and this role is no longer just a volunteer commitment.
The compensation has also directly helped the families in the community, since in 2013-2014 they
decided to support each family with $300 dollars in materials for construction such as iron, cement
blocks, seeds, spray-pumps for crop fumigation or other items the families said they needed to
improve their livelihood. In total 64 % of the respondents expressed a gratitude over the support.
From the respondents: “One project that benefitted me was when they gave me a breeding stock,
guinea pigs and chickens” (Nr. 3, 2016). With the remaining money, the community decided to buy a
small piece of land to be shared for cattle and milk production, something that 55 % of the
respondents thought was a good investment.
Figure 11. Local observations, Theme; positive aspects of the PSB, n=11.
Regarding the question of whether or not the people learned more about the environment via the
PSB, 64 % said that they had and that with the PSB the burning and grazing of the páramo had
stopped (Table 8). From the respondents: “There is a control now, for this I am thankful, now this
discrimination does not exist because we have learnt that the páramo is our colchon, they are living
sponges of water” (Nr. 11, 2016). Many of the older generation have not had any higher education
and 18 % of the respondents also mentioned the importance of courses and workshops as a source
of knowledge that has been established over the years through the support of different institutions
and organisations.
1
Contribution (eg. construction material, agricultural equipment, breeding stock, etc.) families livelihoods
2 More tourism
3 More work possibilities
4 More organization
5 Administration ex. "guarda parques"
6 Investment in land
7 An income source
8 Protecting the nature
0%
25%
50%
75%
100%
1 2 3 4 5 6 7 8
An
swer
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Ellinor Hallström
32
Relatively few of those interviewed had any negative critique of the PSB. However, 73 % of those
interviewed expressed a worry about that the PSB had stopped and that it will not continue (Table 9).
Further, 36 % of the interviewed expressed directly that they were worried that the people would
stop respecting the limits of the PSB if it is not supported and enforced (Table 9). From the
respondents: “Well, the opinions now are that it should continue. Let’s hope that it continues,
because they say that it has stopped. So let’s hope that it should continue, because the people now
have consciousness. Now they do not destroy for example. Because if it ended the people would say
that it has ended and they will continue the destruction. So let it continue.” (Nr 7., 2016).
Among the critique that was raised about the PSB (Figure 12), 18 % of the respondents expressed
that they did not approve of the environmental laws of the PSB area becoming so strict. Before the
program they at least had been free to decide what to do with their land. Today, locals need
permission from the Ministry of Environment if they want to cut down a tree or want to use any rock
material for construction. In addition, Nr. 6 (2016) expressed that he could no longer use his land
outside the PSB area in the way he had planned. He had invested in his land for both his own
livelihood and that of his children so they would have enough land to work on and firewood to heat
up their houses. He also mentioned that he had used his land to produce and sell timber, but that the
good, thick trees he wanted to save for the next generation. The stricter environmental laws have
therefore made every-day life harder and more restricted for his family. This he expressed in the
following sentences; “It irritates me that one for example is here (at home) at nine, ten in the night or
from six. The one who have his enclosure good, like before, one could have a dialog about the day or
whatever. In turn now come home to the bed to gather with the family, -another reason just to stand
the cold. The poor do not have anything to warm up himself with. In turn with the firewood one get
warmed up. But of course, it is a disadvantage to throw away the mountains like they say, that there
isn’t any oxygen. But to us it does not favour, but for the big companies yes” (Nr. 6, 2016).
27 % of the respondents expressed worry for those members of the community who do not have
enough land to work on, and for those members of the community who are supporting new families.
27 % of those interviewed were not satisfied with how the community had decided to spend the
compensation in 2013/2014, giving away 300 dollars to every family. They would have preferred to
invest the compensation in a productive project that could have also benefited the community in the
future. According to Respondent Nr. 10 (2016), the reason why the community had so much of the
compensation left in these years in order to split it among all the families was that the community
had saved the compensation for several years prior so that they could invest in a bigger productive
Table 8. Local observations, Theme/Question/Proposition: Have you learnt more about the environment with the PSB? n=11
Category Yes No Also, important with education/workshops
Sum I 64% 18% 18%
Table 9. Local observations, Theme: Worries about the PSB, n=11.
Category
"The program has stopped"
Worried that the destruction of the páramo will continue if the PSB stops.
Sum 73% 36%
Ellinor Hallström
33
project. One alternative idea was to invest the funds in purchase of a big hacienda in the lower areas,
outside the páramo area so that they could start a milk production collective and create work and
also sell pieces of land to people in the community that do not have any land to work. According to
Respondent Nr. 10 (2016) in 2014 the Ministry of Environment in Ecuador had sent a resolution to
the community telling they should invest the compensation they had received from the PSB, since
this was what other communities had done. According to Respondent Nr. 10 (2016) the community
had already found a hacienda, but due to complications with the paperwork for the purchase of the
hacienda, the deal was never completed. The community had looked for other projects to invest in,
among those a tourist spa complex near hot water springs in the páramo. Due to an earthquake, this
project was also delayed and the community ended up in splitting the money among the families.
This was both due to the fact that they felt pressure from the Ministry of Environment in Ecuador,
but also due to members of the community becoming impatient, and who felt that they should at
least benefit from the PSB somehow. The chance to invest in bigger productive projects for the
collective was lost. From the respondents: “What hurts me most is that we did not took advantage of
this money that came from the state, we did not take advantage and made big things. Like our
ancestors did with their breeding and selling of their cattle and bought 150 ha, -of what we today are
living and are surviving on” (Nr. 10, 2016).
18 % of those interviewed were directly questioned on the purpose and motivation of the PSB
and for whom it is really serving. From the respondents: “We are at least protecting the páramo, but
my question is; I am protecting, but for who? For who? Of course we all need this clean air, protect
the nature, but the one who is doing this need to get a recognition, a compensation” (Nr. 4, 2016).
Figure 12. Local observations, theme; Critique related to the PSB, n=11.
1 Strict land use regulations of the PSB area
2 Strict land use regulations outside the PSB area
3 Little info before entering PSB
4 Questioning the purpose of PES
5 The compensation is not enough
6 Not satisfied with the usage of the compensation
7 Need land to work on
8 Local authorities should care more about the case and help out
9 Difficult to start productive projects
0%
25%
50%
75%
100%
1 2 3 4 5 6 7 8 9
Land useregulations
Motivationto
participatein PSB
Compensation/Productiveprojects
An
swer
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4. DISCUSSION
4.1. Water balance analysis and local observations of the bio-physical conditions in the watershed
One of the objectives of this study was to get a better understanding for the water resources and the
bio-physical condition in the Río Grande watershed. The long-term analysis of the water balance
components in the Río Grande watershed showed that the annual Q decreased significantly between
1967-2014. Additionally, it was shown that the annual Q between 1997-2015 was significantly lower
than during the period 1979-1997. The results from the observation of the annual P did not indicate
significant change. Therefore, it is more likely that the changes of the annual Q depend on factors
that control the distribution of Q and AET in the watershed. This theory is supported by the long-
term analysis of the mean annual average T in this study, which the result show to have increased
significantly in the region.
During the interviews, a few of the local respondents in this study mentioned that the flow of the
rivers had decreased in the Río Grande watershed. Trujillo Tupe (2016), the observer of the water
level of Río Grande stated, however, that she made this observation. Some of the respondents gave
examples during the interviews that indicate that it has become warmer in the watershed. An
example of this is, the reports about that the zone of snow around the volcano Chiles has decreased
and that the problem with the freezing of the potatoes is not a very big problem anymore.
There is evidence that between 1950 and 1998 glaciers have retreated in the tropical Andes
(Vuille, et al., 2003). Vuille et al. (2003) suggested that this depended on increasing temperature and
humidity. They highlighted it was not due to changes in the distribution of precipitation, since the
cloud cover has changed minimally during previous decades. Vuille et al. (2003) also concluded that
the temperature has increased more on the western slopes of the Andes than on the eastern side.
One of the few climate predictions in the tropical Andes by Urrutia & Vuille (2009) emphasised the
significantly warmer temperatures at the end of the 21st century (2071-2100). They also predicted
that the precipitation will increase along the coast of Ecuador up to an elevation of 2000 m.a.sl. No
significant change in the precipitation is expected above this limit (Urrutia & Vuille, 2009). These
climate predictions and analysis are consistent with the results from this study. A warmer climate
would in turn cause a negative glacier mass balance in the Andes and in the páramo wetlands, that is
not offset by the precipitation (Urrutia & Vuille, 2009).
The local respondents in this case study of the Río Grande watershed reported frequently that
the wet and dry periods in the Río Grande watershed were no longer distinct. They explained that
the weather is now more unpredictable and that the summer is starting later than usual. These
changes in the weather patterns could likely be interlinked to the changes of the climatological and
hydraulic parameters found in this study. This linkage is important, even though it is difficult to do
any connections without further correlation analysis that includes other factors impacting the
weather such as wind, humidity, solar radiation or high and low rainfall events.
4.2. Potential páramo and land use impacts on hydrological parameters in the watershed
Many factors could have had an impact on the change and the decrease of the annual Q in the Río
Grande watershed. Excluding a warmer climate in the region, changes in the land use during previous
decades could have stimulated an increase to the AET in the watershed. The organic content in the
soil of the páramo in Ecuador has been found to be higher in the upper part of the soil horizon, and
that the water holding capacity was higher in these parts of the soil (Poulenard, et al., 2003). The soil
constitutes important but complex interactions between the hydrological cycle and ecosystems
Ellinor Hallström
35
(Porporato & Rodriguez-Itubre, 2002). Aside from the fact that the páramo vegetation is likely to be
important for soil properties and the content of organic matter (Eriksson, et al., 2005), it also reduces
evaporation into the atmosphere by shading the soil surface. It has been shown that the soil in the
páramo has a higher bulk density and a lower moisture content after long-term heavy grazing
(Hofstede, 1995). Large scale and intensive grazing of the páramo vegetation could therefore
contribute to increase the evaporation in the páramo.
According to the local respondents, the burning and grazing in the páramo ecosystem of the Río
Grande watershed stopped with the PSB implementation in 2009. No significant (positive nor
negative) change of the P, Q, AET and PET were found in response to the implemented PSB scheme
in this study. As such, it is likely too early to see if and what direct impacts the PSB scheme has had
on the distribution of water in the watershed. This implies that it is important to continue to follow
up and monitor the hydrological and climatological parameters in the watershed to evaluate if the
intended bio-physical targets with the PSB are achieved.
Trujillo Tupe (2016) commented that the trees in the lower parts of the watershed, downhill
from the páramo have decreased. Plants and trees consume water through evapotranspiration
processes (transpiration) (McElrone, et al., 2013). Changes and the stimulation of new vegetation
covers to a landscape dominated by pasture with a vegetation that might consume more water could
therefore be another factor to the “loss” of water in the watershed.
The results from this study have shown that the decrease in annual Q in the watershed have
occurred mainly during the late dry period between August to October. In a time of the year when
the water levels in the rivers might be low. It is possible that the withdrawl of fresh water from the
Río Grande watershed is not balanced by recharge from precipiation during these months. Therefore,
it is important to further evaluate and consider how the population, water demand and water usage
have changed in downstream areas during the previous decades and the impact this had on the fresh
water withdrawal from the Río Grande watershed. If this have had a significant impact, other water
management actions and strategies would be needed to improve the regional water resource
situation.
4.3. The PSB scheme as a land-water resource management strategy
The objectives of the PSB are, in addition to the protection of fresh water resources also to protect
the ecosystem values of the páramo and to decrease the deforestation in Ecuador. Except from the
provision of fresh water, provides the páramo several different other ecosystem services, such as the
vegetation itself and the rich biodiversity. It would be interesting to reflect upon what resilience and
retention capacity the flora of the páramo provides against burning. A full discussion of this is out of
the scope of this thesis. However, in a study by Suárez R. & Medina (2001) in the ecological reserve El
Angel showed that sites that had been exposed to intermediate damage by burning had the highest
density of adult stem rosettes (Espeletia sp.) (Suárez R. & Medina, 2001). Counter to this on the sites
that most recently and more intensively had been exposed to burning, there was a very low density
of stem rosettes, similar to the most undisturbed sites where shrubs instead had taken over the
vegetation (Suárez R. & Medina, 2001). Verweij & Kok (1992) have made similar observations, whom
noted that Espeletia populations survived a fire-frequency of 5-10 years. The mortality among
juvenile and adult individuals exposed to burning had resulted to be high, but this had been
compensated by the survival of seeds and a high juvenile growth (Verweij & Kok, 1992). These
studies show that it is likely that temporary small-scale burning is beneficial to the seed bank of the
Andean stem rosettes in the soil, while intensive and short-term repetitive burning might be a
disturbance that takes long time for the Espeletia populations to recover from. The overall results
Ellinor Hallström
36
from these studies confirm that the interconnection between human and the vegetation of the
páramo is complex, and is something that needs more research and understanding.
Based on the summary of the respondent’s answers, there exists recognition within the
community about the ecosystem services the páramo is providing. These outcomes are consistent
with the results from a broader study by Farley & Bremer (2017) on the perception of the páramo
among people and communities living in the Ecuadorian Andes and who are participating in the PSB.
According to most respondents from the community La Esperanza it was clear that the people had
learnt more about the environment from the PSB. As such, by participating in the PSB, the
community has not only opened their eyes to the concerns facing the status of the páramo, but also
to the supply of fresh water resources in the region. This awareness has also fostered collaboration
and helped the community to work together actively to create change. Another objective, with the
PSB scheme is to improve the life in rural areas and for peasant communities. For generations, the
people of La Esperanza have depended directly on the ecosystem services the area and the páramo
have produced, such as firewood, medicine, food, recreation, the potential for small-scale farming,
and not least fresh water. Despite this and stricter land use regulations of the páramo land that
followed with the PSB scheme, most of the respondents expressed a gratitude for the economic
benefits the PSB has had for the community. Many of the respondents expressed also a concern that
the PSB had stopped and that the destruction of the páramo would continue now without the
economic compensation.
It should be noted that few of the respondents had any critique to give about the PSB, which
could be due to the reputation that the PSB had stopped. However, one of the critical aspects that
was brought up among the respondents was regarding how the environmental laws in general have
become stricter in the area outside the PSB. This seems to have made the everyday life harder for
some of the families in the community. The main income sources in the páramo in Ecuador are
within the agriculture sector and the demand for land to work high (Mena Vásconez & Hofstede,
2006). Additionally, respondents gave examples how it has become difficult to start-up new
productive projects within the community that could have compensated the loss of areas for grazing
and management of cattle. Participating in the PSB is a volunteer commitment, but it should not
make life harder for the ones participating in the program and for people who directly depend on the
ecosystem services the site in question produces for their livelihood. This is especially the case if the
bio-physical and local conditions and the need for a PES scheme are not well evaluated beforehand.
Farley & Bremer (2017) conclude it is important to consider the local peoples knowledge and to
understand the local circumstances if one wants to implement a change of the land use practises in
an area. Research emphazises that the success of PES schemes depend on trust between providers
and service users, safe land tenure arrangements, good communication, social meaning of the PES
and the length of the PES scheme (Börner, et al., 2010; Muradian, 2013; Porras, et al., 2013). Not
least, that also the desired ecosystem services can continue to be provided or the quality of them
improved, while at the same time improve local conditions (Grima, et al., 2016). A such, a well
designed PES scheme requires a good monitoring and evaluation strategy that take all these aspects
into consideration (Porras, et al., 2013). Constructed on the fundamental condition that the rights to
the land of the ecosystem service in question belong exclusiveness to the provider (Börner, et al.,
2010). Being flexible to changing circumstances and learn from past experiences have, however,
been argued to be one important lesson learnt from Costa Rica in their progress and work with their
national PES scheme (Pagiola, 2008). In this specific case study of the Río Grande watershed the
demand for land or productive projects within the community and the need for different ecosystem
services at different levels and scales are important to consider. Only in this way it will be possible to
find a long-term sustainable and integrated land-water management strategy in the region that
works effectively and benefits all different partners involved.
Ellinor Hallström
37
4.4. Uncertainties and limitations of the study
There are many uncertainties and sources of errors in the work with the measuring of hydrological and climatological observations (World Meteorological Organization, 2008a). Such errors are hard to estimate if the data is not primary. One specific uncertainty impacting the P estimate in this watershed is the climate conditions in the páramo, where fog and dew is common. This, can add an unknown quantity of water to the hydrological system due to “horizontal rain” or “occult precipitation”. This is a problem especially in areas with arbustive species like Polylepis sp (Bruijnezeel & Proctor, 1995). This “error” could be compared to occult precipitation in lower montane cloud forests, where it typically adds up to 5-20% of ordinary rainfall (Bruijnzeel & Proctor, 1995). Errors in the P observation caused by wind deformation is likely the greatest source of errors in this case study, and this can vary between 2 - 10 % (World Meteorological Organization, 2008a). The high difference in altitude (1600 m) in the watershed of Río Grande between the lowest (Q station at 3120 m.a.sl) and highest point (volcano Chiles at 4723 m.a.sl), creates uncertainties in the wind patterns and distribution of P in the watershed. Basing the P estimates of this watershed on the observations from only one metrological station might therefore not be entirely accurate. An ideal situation would be to have several P stations spread throughout the watershed to better compensate for all these uncertainties. However, the data from station (M0308) followed the same patterns as the data of the average annual P estimated from the five metrological stations in the region. Station M0308 had a higher annual P, which confirmed speculations that the distribution of the P in the region is highly irregular, or that the P at station M0308 is overestimated. An overestimation of the P would in turn in this case give an overestimation of the AET, but not affect the Q.
For detailed climate and hydrological studies, daily observations are not sufficient. Hourly or
three-hourly observations are required (World Meteorological Organization, 2008). The data used in
this study was reported as monthly averages with a minimum of 20 days between observations each
month. Due to this the data, might not fulfil the criteria for any advance climate and hydrological
analysis. However, a completely accurate observation of the water balance components does not
exist since the uncertainties or errors in the measurements can never completely be eliminated
(World Meteorological Organization 2008b). This hydrological data was the only available in the
watershed and needs to be considered despite the intermediate quality. To be able to find
sustainable solutions on the bio-physical problems in the watershed and in the region. It is important
to continue to monitor and evaluate these variables.
There are many elements to a qualitative research method that can introduce uncertainties into the interpretation of the results, such as the location where the interviews take place and the selection of participants, to how questions are asked and understood, and how the material is transcribed and analyzed (Mikkelsen, 2005). This being the researcher’s first field study to include this type of research method increased the chances of making common mistakes described by Mikkelsen (2005). Despite this, it was a top priority to be as objective as possible during each of the field visits. Due to the limited number of participants in this part of the study the results from the respondents in the interviews should not be interpreted as a representative opinion from the whole community, but more as these individual’s local observations and experiences on the topic. A further more structured interview method would might have given better statistically analyzable data. A combination of these approaches would have been the optimal research method, but due to limited amount of time it was not possible.
Most often it is a specific problem, rather than a discipline, that motivates a researcher to undertake an interdisciplinary approach (McNeill, et al., 2001). This does not mean that it is easy, and in every step from the formulation of the research issue to the choice of methods, field studies, analyzing processes and presentation of the results, choices are (and need to be) challenged (McNeill, et al., 2001). Hopefully, this thesis will contribute to give insights towards the different disciplines that should be understood and considered to achieve a sustainable long-term land-water resource management strategy, such as PES schemes.
Ellinor Hallström
38
5. CONCLUSIONS The results from this study confirm the interdisciplinary complexity that the management of the páramo and fresh water resources of the Río Grande watershed are confronting. This is an area where the complexity of nature itself is high, the quality of the hydraulic data is intermediate and few studies of the páramo’s interconnection to the local population’s land use practices have been conducted. The study concluded, however, that it is important to consider both existing bio-physical data and local conditions in a case targeted for a PES scheme. Seeing that the people here rely directly on the land for their livelihood, the importance of designing land-water management strategies correctly, such that they achieve downstream goals without sacrificing upstream ecosystem services, is significant.
The long-term analysis of the water balance components in the Río Grande watershed showed
that the annual Q has decreased significantly between 1967-2014, and that the annual Q in 1997-
2015 was significantly lower than in the period 1979-1997. Since the annual P did not change
significantly, the decreased annual Q depended more likely on other factors controlling the
distribution of Q and AET in the watershed. One of many potential reasons that could have increased
the AET in the watershed is the annual average T that increased significantly in the region. Large
scale land use changes during the previous decades in the páramo, but also downhill from the
páramo could be potential drivers. Another aspect to consider is changes in population growth,
water demand and usage in downstream societies and how these demographical changes might have
affected the fresh water withdrawal from the Río Grande watershed during the previous decades.
The results from this study showed that it is likely too early to see any impacts on the
hydrological and climatological parameters due to the implemented PSB scheme. This is important to
continue to follow up and monitor to evaluate if the intended bio-physical targets with the PSB are
achieved. The objectives of the PSB scheme are not only to monitor fresh water resources, but also
to protect the páramo ecosystem, its biodiversity and to improve the life of the people living in rural
areas and peasant communities. The local awareness about the different ecosystem services the
páramo produces both locally and regionally were high among the respondents participating in this
study. The economic benefits of the PSB scheme seems to have been appreciated among the people
of the local community. To participate in the PSB is a volunteer commitment, except to evaluate if
the bio-physical objectives are met. It will, however, be important to follow up and evaluate what
improvements are needed with the PES scheme from the participant’s perspectives. For example,
how and what kind of incitements or support the participants would like to have from the program,
except from the direct economic compensation.
It would be interesting to follow up the results from this study in a few years to evaluate what happened over a longer period, if the PSB continued and what this imply for the community, the páramo and the region’s water resources.
Ellinor Hallström
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APPENDIX A: THE RÍO GRANDE WATERSHED AND THE PÁRAMO VEGETATION
Photos: Ellinor Hallström. Plants identified with help from Bertil Ståhl at the Department of
Organismal Biology, Uppsala University and Sklenár, et al. (2005).
Figure A 9. “El Frailejon I”, Espeletia
pycnophylla ssp. angelensis (Asteraceae),
Location: Laguna Verde, páramo of La
Esperanza. Orange arrow 1.63 m.
Figure A 2. “El Frailejon II”, Espeletia
pycnophylla ssp. angelensis (Asteraceae),
Location: The páramo of La Esperanza.
Figure A 5. Senecio chienogeton (Asteraceae).
Location: Laguna Verde, páramo of La Esperanza.
Figure A 4. Elaphoglossum sp. (Dryopteridaceae),
Location: Laguna verde, páramo of La Esperanza.
Figure A 3. “El Frailejon III”, Espeletia pycnophylla
ssp. angelensis (Asteraceae), Location: Laguna
verde, páramo of La Esperanza.
Figure A 1. “El Frailejon I”, Espeletia pycnophylla ssp.
angelensis (Asteraceae), Location: Laguna Verde,
páramo of La Esperanza. Orange arrow 1.63 m.
Ellinor Hallström
45
Figure A 10. Senecio canescens (Asteraceae) I, Location: páramo of La Esperanza.
Figure A 6. Puya sp. (Bromeliaceae) I, Location:
Laguna verde, páramo of La Esperanza.
Figure A 7. Puya sp. (Bromeliaceae) II, Location:
Laguna verde, páramo of La Esperanza.
Figure A 13. Lupinus sp. (Fabaceae), Location:
páramo of La Esperanza.
Figure A 12. Huperzia sp. (Lycopodiaceae),
Location: páramo of La Esperanza.
Figure A 16. Bartsia sp. (Orobanchaceae),
Location: Laguna verde, páramo of La
Esperanza.
Figure A 9. Diplostephium sp.(Asteraceae),
Location: Laguna verde, páramo of La Esperanza.
Figure A 11. Loricaria thuyoides (Asteraceae), Location: Laguna verde, páramo of La Esperanza.
Figure A 8. Bartsia sp. (Orobanchaceae),
Location: Laguna verde, páramo of La Esperanza.
Ellinor Hallström
46
Figure A 18. Páramo of herbaceous, with
Calamagrostis intermedia (Poaceae), páramo of
La Esperanza.
Figure A 16. Páramo of montane grassland lakes,
Location; Laguna Verde, páramo of La Esperanza.
Figure A 17. Páramo of frailejones, Location:
páramo of La Esperanza.
Figure A 19. Transition zone between the páramo
and the pasture land outside the village Tufiño.
Figure A 14. Watershed of Río Grande. View
downstream from the location Laguna Verde,
páramo of La Esperanza.
Figure A 2. Soil profile. Location: Laguna
Verde, páramo of La Esperanza. Orange
arrow: 1.63 m.
Figure A 20. Milking of cattle outside the village
Tufiño.
Figure A 21. Transition zone between the páramo
and the pasture land outside the village Tufiño.
Figure A 15. Soil profile. Location: Laguna Verde,
páramo of La Esperanza. Orange arrow: 1.63 m.
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47
APPENDIX B: LIST OF RESPONDENTS
Table B 1. List of participants in the qualitative study of the bio-physical condition and the PSB in the Río Grande watershed.
Reference number in text
Nr in field
Date Area of living
Gender Occupation Note
1 1 2016-08-06
Chilma Bajo
M Milk production and cultivation of blackberries, granadilla, tomate de arbol
2 2 2016-08-06
Tufino M Cultivation of potatoes
3 3 2016-08-06
Tufino F Household
4 4 2016-08-06
Tufino M Cultivation of potatoes and production of milk
5 5 2016-08-06
Tufino M Cultivation of potatoes and production of milk
6 6 2016-08-06
Tufino, M Cultivation of beans, monjoco. Pasture.
7 7 2016-08-06
Tufino M Cultivation of potatoes
8 8 2016-08-08
Tufino M Milk production, cultivation of potatoes, tourism
9 10 2016-08-13
Tufino F Household
10
12 y 13
2016-08-13
Tufino M Milk production
12 y 13
2016-08-13
Tufino M Construction
11 15 2016-08-15
Tufino F Milk production, cultivation of potatoes, catering, tourism
(12) 14 2016-08-14
Tufino F Milk production, household
Not included in results
(13) 11 2016-08-13
Tufino F Household
Not included in results
Trujillo Tupe, Nelli Cumanda
9 2016-08-12
Tufino F Measuring the water level of Río Grande
Levy, Santiago
16 2016-08-09
Tulcan M Environmental NGO
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APPENDIX C: INTERVIEW GUIDE
Basic information:
1. Origen:
2. Gender:
3. Occupation:
Information about the physical environment, ecosystem services and disservices
4. What function has the páramo vegetation?
5. Environmental services are services and products that the nature is producing and that we benefit from, for example fruits, food and clean water. It could also be a service that regulate the climate or the earth. What kind of ecosystem services exist in this zone?
6. The nature gives un many important products and services, but sometimes there can also be products and services, which are part of the nature, but are more of a problem for us. For example, mosquitos that spread diseases or birds that eat the fruits or plants in our cultivations. Are there any disservices in this zone, which are a problem for you or your family?
7. Are there any other environmental problems where you live and work?
8. Are there any environmental problems with the water in this zone? - Flooding, dry periods, dirty water? Indicators? Since when?
9. Have any of the environmental problems reduced or become worse with the implementation of the PSB?
Information about the program Socio Bosque (PSB)
10. What motivated the community to participate in the program Socio Bosque?
11. Before your participation in the PSB for what did the community used the land, the páramo?
12. From where did the community find information about the PSB?
13. In the community how did you decide to participate in the PSB?
14. What is your general opinion about the PSB? a. Positive aspects? b. Negative aspects? c. Is there something that could be improved with the PSB?
15. The contract of the PSB last for 20 years. Do you think that you had sufficient information about the program before you entered the PSB?
16. In what do the community spend the economic compensation that you receive every year form the PSB?
17. In comparison of what you earned on the land before participating in the PSB, do you think that the compensation you receive now per hectares is sufficient?
18. Have you learnt more about the environment and the nature with the PSB? a. Yes- what have you learnt?
19. Do you have any other comment or opinion that you would like to share?
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49
APPENDIX D: MATRICES USED FOR THE QUALITATIVE ANALYSIS
Table D 1. Matrix I; used for the analysis of the transcribed material
Theme Category Question Answers
Question x Answer nr x:
Physical Description
Páramo
Example: What función has the páramo in this área?
Example: Nr 1: El páramo recoge todo los que es el agua, para los cuadales nuestros en los rios. Por mi caso El Río plata. Por el otro lado por chilma bajo hay otro Río, pero que coge el agua del páramo mismo. Todos recoge el agua del páramo. Entonces el páramo sera una esponga para recoger el agua.
The volcano
Climate
Land use/PSB land
Water
Ecosystem Services
General
Earth
Water
Disservices General
Agriculture and pasture
Other Env. Problems
Water
Programa Socio Bosque (PSB)
General
Comuna La Esperanza
General
Other General
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Table D 2. Matrix II; used for the analysis of the transcribed material
Theme Category/Question/Proposition: Answers
Páramo function
Example: What function has the páramo? (today)
Nr interview
Inte
rvie
w
(fie
ld)
Wat
er
qu
alit
y,
regu
lati
on
of
the
wat
er
flo
w
Pas
ture
, wild
bu
lls
The
pro
ject
P
SB, A
n
inco
me
Flo
ra &
Fau
na
Tou
rism
Envi
ron
me
nt
al p
urp
ose
s
1 1 x x
2 2 x x
3 3 x x x x
4 4
5 5 x x
6 6 x x
7 7 x x
8 8 x x
9 10 x x
10
12 y 13
11
15
x
Sum: 6 3 3 3 2 2
Usage of the páramo before PSB?
Have you learnt more about the environment with the PSB?
PSB Opinion about PSB
Worries
Positive responses
Negative responses/critique
Usage of compensation
Motivation to enter the PSB
Climate Changes in climate/seasonal distribution
Changes in natural resources
Ecosystem Services
Ecosystem Services
Disservices and env. Problems
Disservices and environmental problems
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APPENDIX E: DATA QUALITY ASSESSMENT; BOXPLOTS
Figure E 1. Quality assessment of input data. Annual observations of P from station M0308 for 1975-2014 (mm) (a); annual
observations of Q from H0091 for 1967-2014 (mm) (b); and annual average T from M0102 and M0103
for 1963-2014 (°C) (c).
(a)
(b)
(c)
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APPENDIX F: DATA QUALITY ASSESSMENT; MEAN MONTHLY AVERAGES
Figure F 1. Mean monthly average P from station M0308 (including and excluding years with gaps), compared to the
monthly average P estimated on the five metrological stations located in the region for the period 1979-2014 (a). mean
monthly average Q (including and excluding gaps) (b): mean monthly average T for the period 1979-2014 (c).
0
50
100
150
200
250
P (
mm
)
a
P (incl. gaps) P (excl. gaps) P regional
0
50
100
150
Q (
mm
)
b
Q (incl. gaps) Q (excl. gaps) Q (excl. gaps >2 months)
10
11
12
13
14
15
T (°C)
c
M0103 M0102 T (average)
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APPENDIX G: ANNUAL OBSERVATIONS OF THE HYDRAULIC AND CLIMATOLOGICAL
PARAMETERS; BOXPLOTS
Figure G 1. Annual observations (mm) of P (a), Q (b), AET (c) and annual average T (ᵒC) (c) from Aug 1979 – Jul 1997 and Aug 1997 – Jul 2015 (gaps filled, linear relationship method).
Figure G 2. Annual observations (mm) of P (a), Q (b) and AET (c) and annual average T (°C) (d) in the region divided in
to 12-years periods (gaps filled, linear relationship method).
(c) (d)
(b) (a)
(a) (b)
(c) (d)
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Figure G 3. Annual observations of the hydraulic parameters (mm) P (a), Q (b) and AET (c) and annual average T (d) in the
region (°C) divided in to 6-years periods (gaps filled, linear relationship method).
(a) (b)
(c) (d)
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APPENDIX H: STATISTICAL ANALYSIS; WATER BALANCE OBSERVATIONS (18 YRS)
Table H 1. Results from the long-term step change analysis (18 years), Wilcoxon/Kruskal-Wallis Tests (Rank Sums), 2-Sample Test, Normal Approximation, data in mm.
Data Level Mean Min Median Max S Z p-value
Annual P (excl. gaps) 1979-1997
1286.4 888.5 1217.4 1762.3
1997-2015
1227.6 785.4 1181.5 1671.2 210 -0.9 0.3615
Annual P - gaps filled (interp.) 1979-1997
1305.1 989.1 1278.6 1753.3
1997-2015
1249.7 706.3 1269.4 1785.5 315 -0.6 0.5798
Annual P - gaps filled (average)
1979-1997
1300 989.1 1276.9 1753.3
1997-2015
1250 706.3 1269.4 1785.5 317 -0.5 0.6239
Annual Q (incl. gaps) 1979-1997
1014.1 610.0 998.1 1468.1
1997-2015
851.7 496.0 897.7 1316.9 233 1.6 0.1001
Annual Q (gaps filled interp.) 1979-1997
851.7 681.2 1033.4 1792.1
1997-2015
851.7 549.0 897.7 1316.8 243 2.1 0.0373
Annual Q (gaps filled average)
1979-1997
851.7 681.2 1044.4 1767.0
1997-2015
851.7 542.2 897.7 1316.8 244 2.1 0.0334
Annual AET (incl. gaps) 1979-1997
304.3 -64.9 264.4 685.1
1997-2015
393.9 34.3 404.2 942.0 172 -1.0 0.3238
Annual AET (gaps filled interp.)
1979-1997
225 -85.2 251.4 521.8
1997-2015
388.7 -39.4 371.9 1087.4 154 -1.8 0.0757
Annual AET (gaps filled average)
1979-1997
218.8 -174.6 251.4 516.1
1997-2015
390.4 -39.4 373.5 1087.4 154 -1.8 0.0757
Annual PET 1979-1997
704.2 685.5 705.5 715.0
1997-2015
721.5 698.8 716.5 752.0 458 3.9 <.0001
Annual average T (°C) 1979-1997
11.9 11.5 12.0 12.2
1997-2015
12.3 11.8 12.3 13.0 452 3.8 0.0001
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APPENDIX I: STATISTICAL ANALYSIS; MONTHLY WATER BALANCE OBSERVATIONS (18
YRS)
Table I 1. The results from the statistical hypothesis testing of the monthly average P (18 yrs), using a Wilcoxon/Mann Whitney test (α = 0.05).
MONTH
Mean monthly average
1979-1997 (mm)
Stdv (mm)
Mean monthly average
1997-2015 (mm)
Stdv (mm)
Wilcoxon test p-value
APR 166.2 56.6 162.0 63.1 0.8124
AUG 478.8 27.3 336.6 22.0 0.0536
DEC 126.3 54.2 131.6 57.2 0.9605
JAN 106.8 45.7 101.2 53.0 0.5798
FEB 96.5 36.1 102.7 60.8 0.8173
JUL 492.9 18.6 666.9 38.6 0.2681
JUN 656.4 26.7 789.2 37.2 0.3346
MAR 154.7 58.3 123.4 46.7 0.0713
MAY 138.8 48.4 132.7 66.4 0.4198
NOV 139.0 61.4 135.7 57.8 0.9874
OCT 141.6 61.0 128.7 58.4 0.6924
SEP 715.1 33.9 527.8 29.1 0.0791
Table I 2. The results from the statistical hypothesis testing of the monthly average Q (18 yrs), using a Wilcoxon/Mann Whitney test (α = 0.05).
MONTH
Mean monthly average
1979-1997 (mm)
Stdv (mm)
Mean monthly
average 1997-2015 (mm)
Stdv (mm)
P-value (two sided)
APR 118.5 36.8 104.4 26.2 0.1672
AUG 62.8 20.8 43.0 15.1 0.0097
DEC 100.1 42.4 87.5 34.1 0.4172
JAN 94.0 38.2 75.6 32.9 0.3238
FEB 81.9 34.5 71.5 34.1 0.4967
JUL 79.6 33.2 67.8 20.4 0.2826
JUN 96.0 36.3 86.7 30.0 0.3458
MAR 110.2 36.9 86.7 37.9 0.1303
MAY 123.1 29.3 107.3 37.2 0.1001
NOV 99.4 42.4 67.1 29.5 0.0564
OCT 85.0 32.8 52.6 19.1 0.0103
SEP 58.5 23.4 34.5 14.7 0.0061
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Table I 3. Results from the long-term step change analysis (18 yrs), of the monthly average AET using a Wilcoxon/Mann Whitney (α = 0.05).
MONTH
Mean monthly average 1979-1997
Stdv
Mean monthly average 1997-2015
Stdv P-value
mm mm mm mm (two sided)
APR 58.5 57.0 59.2 59.0 0.8780
AUG -13.2 41.0 -6.6 24.1 0.2278
DEC 36.9 36.2 51.1 57.4 0.6259
JAN 20.5 29.1 28.4 38.9 0.6770
FEB 18.4 43.0 34.2 45.7 0.5308
JUL -30.3 29.4 2.2 33.2 0.0190
JUN -24.3 35.4 -4.1 33.9 0.1811
MAR 49.6 52.6 40.8 47.8 0.5249
MAY 25.5 64.4 27.6 51.5 0.8094
NOV 40.7 39.5 66.4 48.8 0.2826
OCT 54.1 50.4 70.0 45.9 0.3925
SEP 2.5 24.8 17.0 30.1 0.4172
Table I 4. Results from the long-term step change analysis (18 yrs) of the monthly average T (18 yrs), using a Wilcoxon/Mann Whitney test (α = 0.05).
MONTH
Mean monthly average 1979-1997
Stdv
Mean monthly average 1997-2015
Stdv P-value (two sided)
mm mm mm mm
APR 12.3 0.3 12.8 0.52 0.0012
AUG 11.2 0.5 11.5 0.45 0.0963
DEC 12.3 0.3 12.6 0.47 0.0378
JAN 12.0 0.4 12.5 0.43 0.0034
FEB 12.0 0.4 12.5 0.57 0.0135
JUL 11.0 0.5 11.7 0.34 < 0.0001
JUN 11.8 0.4 12.0 0.37 0.0729
MAR 12.3 0.4 12.7 0.48 0.0199
MAY 12.3 0.2 12.7 0.45 0.0030
NOV 12.3 0.3 12.7 0.48 0.0081
OCT 12.3 0.4 12.6 0.47 0.0594
SEP 11.6 0.3 11.9 0.43 0.0361
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APPENDIX J: STATISTICAL ANALYSIS; WATER BALANCE OBSERVATIONS (12 YRS)
Table J 1. Results from the Short-term step change analysis (12 years), Kruskal-Wallis Tests (Rank Sums) (α = 0.05), 1-way Test, ChiSquare Approximation.
Data Level ChiSquare DF Prob>ChiSq
Annual P (excl. gaps)
- 1979-1991
1991-2003
2003-2015
3,1812 2 0.2038
Annual P - gaps filled (interp.)
- 1979-1991
1991-2003
2003-2015
0,4159 2 0.8122
Annual P - gaps filled (average)
- 1979-1991
1991-2003
2003-2015
0,3438 2 0.842
Annual Q (incl. gaps)
1967-1979
1979-1991
1991-2003
2003-2015
14,6058 3 0.0022
Annual Q (gaps filled interp.)
1967-1979
1979-1991
1991-2003
2003-2015
13,9636 3 0.003
Annual Q (gaps filled average)
1967-1979
1979-1991
1991-2003
2003-2015
14,3456 3 0.0025
Annual AET (excl. gaps)
- 1979-1991
1991-2003
2003-2015
3,6107 2 0.1644
Annual AET - gaps filled (interp.)
- 1979-1991
1991-2003
2003-2015
6,2797 2 0.0433
Annual AET - gaps filled (average)
- 1979-1991
1991-2003
2003-2015
6,3845 2 0.0411
PET 1967-1979
1979-1991
1991-2003
2003-2015
15,3146 3 0.0016
T 1967-1979
1979-1991
1991-2003
2003-2015
14,2077 3 0.0026
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Table J 2. Results from the Short-term step change analysis (12 years), Nonparametric Comparisons For Each Pair Using Wilcoxon Method (α = 0.05).
Annual P (excl. gaps) Annual P (gaps filled interp.) Annual P (gaps filled average)
Level - Level p-Value Level - Level p-Value Level - Level p-Value
2003-2015 1991-2003 0.302 2003-2015
1991-2003 0.931 2003-2015 1991-2003 0.931
2003-2015 1979-1991 0.4307 2003-2015
1979-1991 0.6236 2003-2015 1979-1991 0.7075
1991-2003 1979-1991 0.0905 1991-2003
1979-1991 0.5834 1991-2003 1979-1991 0.5834
Annual Q (incl. gaps) Annual Q (gaps filled interp.) Annual Q (gaps filled average)
Level - Level p-Value Level - Level p-Value Level - Level p-Value
2003-2015 1991-2003 0.7337 1979-1991
1967-1979 0.859 1979-1991 1967-1979 0.859
1979-1991 1967-1979 0.6441 2003-2015
1991-2003 0.6776 2003-2015 1991-2003 0.6776
1991-2003 1979-1991 0.0247 1991-2003
1979-1991 0.0305 1991-2003 1979-1991 0.0247
2003-2015 1979-1991 0.008 1991-2003
1967-1979 0.0161 1991-2003 1967-1979 0.0161
1991-2003 1967-1979 0.0062 2003-2015
1979-1991 0.0062 2003-2015 1979-1991 0.0048
2003-2015 1967-1979 0.0051 2003-2015
1967-1979 0.0041 2003-2015 1967-1979 0.0041
Annual AET (incl. gaps) Annual AET (gaps filled interp.) Annual AET (gaps filled average)
Level - Level p-Value Level - Level p-Value
Level - Level p-Value
2003-2015 1979-1991 0.0792 2003-2015
1979-1991 0.016 2003-2015 1979-1991 0.016
2003-2015 1991-2003 0.2413 1991-2003
1979-1991 0.1309 1991-2003 1979-1991 0.1309
1991-2003 1979-1991 0.4379 2003-2015
1991-2003 0.3447 2003-2015 1991-2003 0.3075
Annual average T Annual PET
Level - Level p-Value Level - Level p-Value
2003-2015 1967-1979 0.0011 2003-2015
1967-1979 0.0011
2003-2015 1979-1991 0.0063 2003-2015
1979-1991 0.0035
1991-2003 1967-1979 0.0249 1991-2003
1967-1979 0.0141
1991-2003 1979-1991 0.1595 1991-2003
1979-1991 0.126
2003-2015 1991-2003 0.2099 2003-2015
1991-2003 0.2145
1979-1991 1967-1979 0.43 1979-1991
1967-1979 0.5443
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APPENDIX K: STATISTICAL ANALYSIS; WATER BALANCE OBSERVATIONS (6 YRS)
Table K 1. Results from the short-term step changes (6 yrs), Kruskal-Wallis Tests (Rank Sums), 1-way Test, ChiSquare Approximation, (α = 0.05).
Data Levels ChiSquare DF p-value
Annual P (excl. gaps)
1979-1985
1985-1991
1991-1997
1997-2003
2003-2009
2009-2015
6.5 5 0.2583
Annual P - gaps filled (interp.)
1979-1985
1985-1991
1991-1997
1997-2003
2003-2009
2009-2015
3.5 5 0.6232
Annual P - gaps filled (average)
1979-1985
1985-1991
1991-1997
1997-2003
2003-2009
2009-2015
2.7 5 0.7393
Annual Q (incl. gaps)
1967-1973
1973-1979
1979-1985
1985-1991
1991-1997
1997-2003
2003-2009
2009-2015
16.9 7 0.018
Annual Q (gaps filled interp.)
1967-1973
1973-1979
1979-1985
1985-1991
1991-1997
1997-2003
2003-2009
2009-2015
15.6 7 0.0286
Annual Q (gaps filled average)
1967-1973
1973-1979
1979-1985
1985-1991
1991-1997
1997-2003
2003-2009
2009-2015
15.9 7 0.0262
Annual AET (incl. gaps)
1979-1985
1985-1991
1991-1997
1997-2003
2003-2009
2009-2015
5.3 5 0.377
Annual AET (gaps filled interp.)
1979-1985
1985-1991
1991-1997
1997-2003
2003-2009
2009-2015
7.9 5 0.1625
Annual AET (gaps filled average)
1979-1985
1985-1991
1991-1997
1997-2003
2003-2009
2009-2015
8.0 5 0.1589
Annual average T
1961-1967
1967-1973
1973-1979
1979-1985
1985-1991
1991-1997
1997-2003
2003-2009
2009-2015
24.4 8 0.002
Annual PET 1961-1967
1967-1973
1973-1979
1979-1985
1985-1991
1991-1997
1997-2003
2003-2009
2009-2015
27.485 8 0.0006
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Table K 2. Significant Results from the short-term step change analysis (6 yrs), Nonparametric Comparisons For Each Pair Using Wilcoxon Method, (α = 0.05).
Annual AET (incl. gaps) Annual AET (gaps filled interp.) Annual AET (gaps filled average)
Level - Level p-Value Level - Level p-Value Level -Level p-Value
1991-1997
1967-1973
0.0373 1991-1997
1973-1979
0.0304 1991-1997 1973-1979
0.0304
Annual Q (incl. gaps) Annual Q (gaps filled interp.) Annual Q (gaps filled average)
Level - Level p-Value Level - Level p-Value Level - Level p-Value
1991-1997
1979-1985
0.02 1991-1997
1979-1985
0.02 1991-1997 1979-1985
0.02
2003-2009
1979-1985
0.02 2003-2009
1979-1985
0.02 2003-2009 1979-1985
0.02
1991-1997
1967-1973
0.0142 1991-1997
1967-1973
0.0252 1991-1997 1967-1973
0.0252
2003-2009
1967-1973
0.0142 2003-2009
1967-1973
0.0252 2003-2009 1967-1973
0.0252
2009-2015
1967-1973
0.0202 2009-2015
1967-1973
0.0202 2009-2015 1967-1973
0.0202
2009-2015
1979-1985
0.0137 2009-2015
1979-1985
0.0137 2009-2015 1979-1985
0.0137
Annual average T
Annual PET
Level - Level p-Value
Level - Level p-Value
1997-2003
1967-1973
0.0062
1997-2003
1961-1967
0.0051
1997-2003
1991-1997
0.0076
1997-2003
1967-1973
0.0051
1997-2003
1961-1967
0.0078
2009-2015
1961-1967
0.0051
1997-2003
1973-1979
0.0154
1997-2003
1973-1979
0.0082
2009-2015
1967-1973
0.0152
1997-2003
1991-1997
0.0082
2009-2015
1961-1967
0.0127
2003-2009
1961-1967
0.0131
2009-2015
1991-1997
0.0232
2009-2015
1967-1973
0.0131
1997-2003
1979-1985
0.0275
1997-2003
1985-1991
0.0202
2003-2009
1973-1979
0.0289
2009-2015
1991-1997
0.0202
2003-2009
1961-1967
0.0263
1997-2003
1979-1985
0.0306
1997-2003
1985-1991
0.0334
2003-2009
1973-1979
0.0306
2003-2009
1967-1973
0.0354
2003-2009
1985-1991
0.0306
2009-2015
1973-1979
0.0357
2009-2015
1973-1979
0.0301
2003-2009
1985-1991
0.0409
2003-2009
1967-1973
0.0453
2003-2009
1991-1997
0.042
2003-2009
1979-1985
0.0453
2003-2009
1991-1997
0.0453
