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Sara Knox

Characterizing the geospatial features and hydrology of four pro-glacial valleys in the Cordillera Blanca, Peru

McGill University EPSC 480: Honors Research Project

Jeffrey McKenzie April 2009

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INTRODUCTION

Many large rivers throughout the world originate in mountainous regions. High

mountains and their glaciers, such as the Himalayas, the Andes, and the Alps, supply

water to hundreds of millions of people and assure water throughout the year (Coudrain

et al. 2005). In the outer-tropics, which experience highly seasonal precipitation patterns,

glaciers are significant water reservoirs that buffer river runoff by providing melt-water

throughout the year (Mark and Seltzer 2005). Many rivers draining glaciated basins,

especially in the Himalaya-Hindu Kush (HKH) region, the South-American Andes, New

Guinea, and East Africa, are sustained by glacier runoff during the dry season (IPCC

2007, Bradley 2006, Barnett et al. 2005).

Studies worldwide indicate an extensive retreat of mountain glaciers in the non-

polar regions of the world throughout the 20th century, with a marked increase in recent

decades (Coudrain et al. 2005, Kaser 1999). The retreat of tropical and subtropical

glaciers is of particular concern since this is where the majority of the world’s population

is located and where the greatest biodiversity is found (Mark and Seltzer 2005). As

glaciers retreat, there is an initial increase in discharge in the short term, but as they

continue to decrease in size they become less significant seasonal reservoirs (Mark and

McKenzie 2007, Coudrain et al. 2005, Mark et al. 2005). In the tropics, glacier recession

will likely result in more variable seasonal stream flow, with a loss of glacial buffering

during the dry season (Mark and McKenzie 2007, Mark et al. 2005). Droughts in the dry

season are therefore predicted for regions which rely heavily on glacial melt water as

their primary dry-season water supply (IPCC 2007).

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Peru is an example of a country which will suffer significantly from glacier

recession. Most of the country’s population lives along the Pacific coastal plains and

western slopes of the Andes, where the land is arid and heavily dependant on runoff from

the mountains (Vergara et al. 2007). Furthermore, Peru’s economically profitable

agricultural sector is highly water intensive, with large demands for irrigation water from

the desert coastal region which is already water stressed (Spang 2006). The majority of

Peru’s most glacierized mountain range, the Cordillera Blanca (Figure 1), drains to the

Pacific via tributary streams to the Rio Santa (Mark and McKenzie 2007). The Rio Santa

and its tributaries provide an important source of water for hydroelectric power

generation, irrigation, mining, industrial, and domestic purposes (Spang 2006). Modeling

tropical pro-glacial hydrology is therefore greatly important in predicting the future

impact of glacial retreat on water resources.

Several hydrological models have been developed to simulate pro-glacial

discharge across the Cordillera Blanca (Juen et al. 2007, Pouyaud et al. 2005). Although

these models have been generally successful in reproducing discharge in catchments

where melt water is the dominant input, they tend to highly simplify groundwater

contribution mechanisms. However, studies have shown that during the dry season,

groundwater often represents the largest hydrological input to stream discharge in some

glacierized basins (Baraer et al. 2009). Baraer et al. (2009) found that although

groundwater contributes just slightly over 10% to the total water budget of the

Querococha valley (Figure 1), during the dry season, groundwater is the largest

contributor to basin outflow; in 1999 and 2007, the relative contribution of groundwater

to dry season discharge was 68% and 79% respectively. Therefore, in modeling pro-

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glacial systems it is important to accurately incorporate groundwater contributions and

pathways in addition to glacial melt and runoff.

A potential location for the temporal storage of groundwater in the Cordillera

Blanca is pampas; treeless plains that are formed from paludified moraine-dammed lakes

(Mark and McKenzie 2007). The pampas are characterized by low permeability and

organic rich unconsolidated material (Mark and McKenzie 2007). Although very little

literature exists on such geomorphic features, similar formations are observed in other

regions of the South American Andes. “Bofedale” is the local name given to valley

bottom formations in the Cordillera Real, Bolivia which are composed of basal moraines

and fluvio-glacial deposits overlain by peat (Caballero et al. 2002). The precise

hydrologic role of the pampas is not entirely understood and merits further study.

To address the pressing concern posed by glacier recession, Baraer et al. (2009)

are developing hydrologic models that can include climate change related impacts on

water resources at the scale of the Cordillera Blanca. A major constraint in the model

development is the poor understanding of tropical pro-glacial hydrology in large (area

greater than 5000 km2), multi-valley, glacial fed catchments. To quantify and gain

insight into pro-glacier hydrology in the tropics, Baraer et al. (2009) used a three

component mixing model, called the hydrochemical basin characterization method

(HBCM), to quantify the contribution of glacier melt water, groundwater and surface

runoff to streams for four valleys and sub-basins within the Cordillera Blanca, Peru

(Figure 1). To interpret the results of the HBCM within the geographical context and

develop a better understanding of the factors that control the hydrological processes

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within and across catchments, the geospatial characteristics of the watersheds and their

sub-basins must be studied.

The objectives of this study are to 1) Map the total area of the pampas in the pro-

glacial valleys of the Cordillera Blanca due to the potential hydrological importance of

these features 2) Characterize the basins and sub-catchments selected for the HBCM

analysis by compiling geospatial data including watershed size, glacierized area, glacier

hypsometry, and pampa area 3) Correlate the geospatial data with the HBCM results for

the 2008 dry season in an attempt to explain the relative groundwater and melt water

contributions observed in each valley and nested watershed, and investigate basin

characteristics that could potentially be used to predict the hydrology of pro-glacial

valleys in the Cordillera Blanca.

STUDY AREA

The most glacierized tropical mountain range on Earth, the Cordillera Blanca,

spans over 130km between 8º-10º S latitude in Peru (Vuille et al. 2008). As described

above, the majority of the glacierized area within the Cordillera Blanca discharges to the

Pacific Ocean via tributary streams to the Rio Santa, which also receives runoff from the

nonglacierized Cordillera Negra mountain range. The Rio Santa originates at Lake

Conococha and flows northwest over 300km, draining a total watershed of 12 200km2.

The upper Rio Santa watershed, the Callejon de Huaylas, is 4900km2 and is delimited by

the hydroelectric power plant at Huallanca (1800 m.a.s.l.) (Figure 1). It is estimated that

10-20% of the total annual discharge, and 40% of the dry season discharge, in the

Callejon the Huaylas is comprised of glacial melt (Mark et al. 2005).

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The glacierized Cordillera Blanca has undergone a significant reduction in glacier

volume throughout the past century. The total glacierized area of the Cordillera Blanca is

presently estimated to be 570 km2 based on 2003 SPOT images, an overall loss of

glacierized area of 22.4% since 1970 (Racoviteanu et al. 2008a). In addition, since 1970

there has been an average rise in glacier terminus elevations of 113 m and an average rise

in the median elevation of glaciers of 66m. Finally, the number of glaciers has increased,

which is indicative of disintegration of ice bodies (Racoviteanu et al. 2008a).

Historical discharge records are available for about 40 years in some tributaries

that flow to the Rio Santa. Monthly average discharge from these gauged streams

discharging into the Callejon de Huaylas is higher during the months of October-April,

closely reflecting the seasonality of precipitation typical of the outer tropics (Mark and

Seltzer 2003). Over 80% of precipitation falls between October and May and the austral

winter months of June to September have nearly no precipitation (Mark and McKenzie

2007). Conversely, monthly averaged air temperature remains nearly constant

throughout the year, and the diurnal variation exceeds the annual variation as is

characteristic of the tropics (Kaser and Georges 1999).

The Cordillera Blanca is approximately 10Ma and sits on the magmatic Andean

arc caused by the subduction of the Nazca plate under the South American plate. The

western side of the Cordillera Blanca is underlain by bedrock exhumed by a NW-SE

trending normal fault, and consists of 80% to 90% batholith, the rest being isolated

regions of tonalite and diorite (Baraer et al. 2009). The lithology of the batholith is

characterized by high silicate contents. The eastern side of the Cordillera Blanca is

comprised of the Jurassic sedimentary Chicama formation composed of weathered rock

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structures including shale, argillite, and sandstone, and some areas are characterized by

extensive pyrite (Baraer et al. 2009).

To investigate the similarities and differences in the hydrology of pro-glacial

valleys in the Cordillera Blanca, the catchments of Llanganuco, Quilcayhuanca,

Querococha and Pumapampa (Figure 1) were selected for the HBCM analysis. They are

located across the geographical extent of the mountain range; Llanganuco is located at

the northern end of the Cordillera Blanca where the valleys are deeply incised and the

valley walls are very steep, and Pumapampa is situated at the southern end where the

valley walls have a gentler topography and there is a smaller elevation gradient between

the valley bottom and the watershed divide.

METHODS

Data Sources

To derive the total pampa area for the Cordillera Blanca and geospatial

parameters of the four catchments and selected sub-basins, a digital elevation model

(DEM), satellite imagery, georeferenced geology maps, and glacier shapefiles of the

Cordillera Blanca were processed within a geographic information system (GIS: ArcGIS

9.3). The DEM is an ASTER DEM product with 30m cell size. The projection for the

DEM and satellite imagery is Universal Transverse Mercator (UTM) Zone 18S. The

satellite imagery is also from the ASTER sensor which was launched in 1999 and

acquires high spatial resolution data in 14 bands, from the visible to the thermal infrared

wavelengths (NASA-JPL 2009). Nine scenes, acquired between 2000 and 2005, were

needed to cover the Cordillera Blanca. Bands 1 (520 – 600 nm) and 2 (630 – 690 nm) are

in the visible portion of the electromagnetic spectrum (VIS) and band 3 (760 – 860 nm) is

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in the near-infrared (NIR) (NASA-JPL 2009). The spatial resolution of the sensor for

these bands is 15m. Glacier shapefiles, derived from 2003 SPOT5 imagery, covering

90% of the Cordillera Blanca were obtained from the GLIMS Glacier Database

(Racoviteanu 2008b). The Pumapampa basin is located outside the SPOT5 imagery thus

glacier coverage for this watershed was digitized from a 2002 ASTER scene. Two

1:1000000 scale geology maps published by the Peruvian Insituto de Geologia y Mineria

were georeferenced and projected to UTM Zone 18S and used as the basis for the

geology analysis.

Pampa delineation

As noted above, pampas are treeless plains located in valley bottoms and thus are

characterized as regions with a low gradient. To determine regions of low grade, a slope

layer was derived from the DEM using grid-based modeling. A semi-automated method

was then used to delineate the pampas: Pampas represent regions with a slope less than or

equal to 10º, an elevation greater than 3500m, and which are found within glacierized

valleys surrounded by steep slopes. Determining the location of the pampas was further

refined by examining a false color composite of the ASTER scenes and excluding regions

where no vegetation was present.

Geospatial analysis

The hydrological tools of ArcGIS 9.3 were used to delineate the valleys and sub-

basins corresponding to those of the HBCM. The pour-points for catchments and sub-

basins were based on GPS mapped mixing point locations used for the HBCM analysis

(Figures 2-5). The glacierized area in each catchment and sub-basin was determined

from the GLIMS glacier shapefiles (and digitized 2002 ASTER scene for the Pumapampa

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basin) using the Analysis tools of ArcGIS 9.3. For glacierized area found in each

catchment, grid-based modeling and zonal functions were used to calculate its minimum,

maximum, mean, and median elevation, average slope and average aspect. The

hypsometric profiles of the glacierized areas were determined using the Spatial Analyst

toolbar. The Analysis tools were also used to determine the area of pampa in each basin.

The average length to width ratio of the pampas and the total river length flowing through

the pampas were determined using the Measure tool. The geologic characterization of

each catchment was digitized from the georeferenced geology maps.

The hydrological data on the contribution of groundwater and melt water to 2008

dry season discharge (June and July) for sub-basins in the Llanganuco, Quilcayhuanca,

Querococha and Pumapampa valleys was obtained from the HBCM analysis (Baraer et

al. 2009). The geospatial parameters for catchments and nested watersheds were then

correlated with the results from the HBCM analysis.

RESULTS AND DISCUSSION

Geospatial data

The geospatial data for the pro-glacial catchments of interest are summarized in

Table 1. The valleys differ considerably with regards to glacierized area and percentage

surface area covered by glaciers (Figure 6). The degree of glacierization is greatest in the

most northern catchment (35.6%) and decreases in the southern valleys, although

Querococha has the lowest percent watershed area glacierized (2.8%). Larger glacierized

areas have a higher maximum elevation and a lower minimum elevation (ie. greater

altitudinal range), as well as a higher median elevation (Table 1). The glacierized area in

the Querococha basin is found entirely below the snowline elevation of the Cordillera

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Blanca (~5200 m) (Klein et al. 1995; Mark and Seltzer 2005) (Figure 7). Conversely, the

majority of the glacierized area in the Llanganuco is located slightly above 5200 m

(Figure 7). The hypsometric curves for the Quilcayhuanca and Pumapampa basins show

that the majority of the glaciated area in these valleys is located around the same

elevation (just below 5200 m) but that a larger mass of ice is present at higher elevations

in the Quilcayhuanca valley. The glacierized areas within the basins also have varying

average slopes. Llanganuco has glaciers with the highest average slopes (31º),

Quilcayhuanca and Querococha contain glaciers with similar average slopes (~28º), and

the glacierized area in the Pumapampa basin has the lowest average slope (26º). These

results are similar to the average slope of all glaciers in the Cordillera Blanca (32º)

(Racoviteanu et al. 2008a). The average aspect for the glacierized area in most

watersheds is southwest for except for Llanganuco where the average aspect of the

glaciers is south (Table 1). This is consistent with Racoviteanu et al. (2008a) who found

that the average orientation of all glaciers in the Cordillera Blanca is 193º (southwest).

The total area of pampas, as defined above, in the glacierized valleys of the

Cordillera Blanca is 63.6 km2. The pro-glacial valleys located at the southern end of the

Cordillera Blanca have a greater area covered by pampas than those located at the

northern end (Figure 1). For instance, 11.6% of the Pumapampa basin is covered by

pampas versus 0.8% for the Llanganuco watershed (Figure 8). Basins with a higher

percentage of pampas also have a greater total river length flowing through the pampas

(Table 1). The geometry of the pampas differs between the basins; Quilcayhuanca has

the longest and most narrow pampas, followed by Llanganuco, whereas the length to

width ratio of the pampas in Querococha is the smallest (Table 1).

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Approximately 60% of the Llanganuco watershed is composed of the Chicama

formation and plutonic intrusion comprises the remainder of the basin (Figure 9). In the

Quilcayhuanca watershed, the Chicama formation underlies a much greater proportion of

the basin (86%) and the plutonic intrusion, mainly found in the southwest end of the

catchment, is present in the rest of the basin (Figure 9). In the Querococha watershed, the

Chicama formation makes up 69% of the basin, plutonic intrusion is present around the

southern boundary, comprising 22% of the basin, and 9% of the basin is underlain by

quaternary fluvial glacial sediments which are found along the southwest border of the

basin (Figure 9). The Pumapampa basin has a significantly different geological setting

than the three other basins; the Chicama formation underlies only 15% of the catchment,

the majority of the basin (66%) is composed of volcanic ignimbrite calipuy and the rest

of the watershed is comprised of cretaceous sedimentary rocks (Figure 9).

The valleys described above were sub-divided into nested watersheds

corresponding to the mixing points used in the HBCM (Figures 2-5). The geospatial data

for the sub-basins are presented in Tables 2 and 3.

HBCM results for the 2008 dry season

The HBCM was used for most of the mixing points within the partially glaciated

Llanganuco, Quilcayhuanca, Querococha and Pumapampa basins to determine the

absolute contribution of groundwater and melt water to 2008 dry season discharge. Due

to restricted water sampling throughout the Pumapampa and Llanganuco valleys and

limitations of the HBCM, the end-member analysis in these basins is restricted to a

limited number of sub-basins representing 30% and 38% of the total basin area

respectively. The absolute average groundwater and melt water contribution to total

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discharge at the outlet of each basin is summarized in Figure 10. Melt water contribution

is greatest in the Llanganuco valley (0.90 m3/s), and is considerably lower in the

Quilcayhuanca (0.41 m3/s) and Querococha (0.06 m3/s) basins. The HBCM analysis was

unable to quantify the melt water contribution to surface water in the Pumapampa basin.

Conversely, groundwater contribution is lowest in the Llanganuco basin (0.045 m3/s) but

greater in the other watersheds, contributing between 0.15 m3/s and 0.19 m3/s to the

discharge at the Pumapampa and Querococha outlets. The absolute groundwater and

melt water contribution to discharge at the sub-basin level is summarized in Tables 4 and

5.

Correlation between geospatial parameters and HBCM results

1. Melt water

At the sub-basin level, there are trends which can be observed between geospatial

parameters and melt water contribution to dry season discharge. Firstly, larger sub-basins

have a greater melt water contribution (Figure 11). Melt water discharge also increases

with larger amounts of glacier coverage (Figure 12). Additionally, there is a strong

positive correlation between the size of the ablation zone (roughly the glaciated area

below 5200 m) and melt water contribution (Figure 13). The elevation data for the

glaciated area in the nested watersheds is also correlated with melt water contribution;

basins whose glaciers have a higher maximum and median elevation, a greater elevation

range and a lower minimum elevation also have greater melt water discharge. However

these parameters are strongly related to glaciated area and thus the latter feature is likely

the predominant factor contributing to higher melt water production. The average slope

and aspect of the glaciated area is not correlated with melt water production. Based on a

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stepwise multiple regression analysis for various combinations of geospatial parameters,

only the glaciated area in each sub-basin significantly predicts melt water discharge (P <

0.01), explaining 84% of the variability in the minimum melt water production and 85%

of the variation in minimum melt water contribution.

At the catchment scale, the relationships between geospatial parameters and melt

water contribution are constrained by sample size, and trends which emerge at the sub-

basin level are not evident at the larger scale. For example, there is no apparent

relationship between basin area, glaciated area or ablation area and absolute melt water

contribution. This is likely explained by the fact that melt water discharge in the

Llanganuco basin could only be quantified for 38% of the entire catchment. However, at

the valley scale, melt water contribution increases with larger amounts of glacier

coverage (Figure 14). This can’t be assessed at the sub-basin level since melt water

originates from catchments that are assumed to be 100% glaciated. Again average slope

and aspect of the glaciers doesn’t appear to influence melt water production.

Kaser and Osmaston (2002) found that melting occurs predominantly in the

ablation zone below the equilibrium line altitude (ELA), thus the glaciated area below the

snow line, controlled by hypsometry, should be the predominant factor influencing melt

water contribution. However, total ice covered area in the nested watersheds is the only

parameter which was found to significantly predict melt water contribution. This

suggests that melting could potentially occur above the snow line. Conversely, the fact

that the glacierized area below the ELA isn’t the predominant factor controlling melt

could be due to the limited number of sub-basins and the resolution of the DEM. More

extensive sampling in the valleys would allow this analysis to be conducted for a larger

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number of sub-basins. Local topographic factors such as slope and aspect also influence

melting rates (Racoviteanu et al. 2008a). Slope and aspect were averaged for the entire

ice mass within the catchments and not for individual glaciers, thus there is considerable

variability within these parameters which likely explains why they are not significant in

predicting melt water discharge. It is important to acknowledge that the estimates of

glacier elevation, slope, aspect and hypsometry are highly sensitive to the quality of the

DEM used for this analysis.

Although physical parameters such as total ice covered area and glacier

hypsometry directly influence melt water contribution (Mark and Seltzer 2003), other

factors such as precipitation, humidity, cloud cover, and albedo greatly influence ablation

(Vuille et al. 2008, Mark and Seltzer 2005). This is further complicated by climate

variability at decadal time scales, such as El nino events which tend to result in enhanced

melt (Coudrain et al. 2005). Therefore both physical and climate parameters should be

considered when quantifying the contribution of melt water to total discharge.

2. Groundwater

The only geospatial parameter which is related to groundwater contribution at the

sub-catchment level is basin area (Figure 15a). When examining this trend within each

valley, sub-basin area appears to influence groundwater production to a differing degree

(Figure 15b). However this observation is limited by sample size and thus requires

further investigation. At the valley scale, groundwater contribution does not appear to

increase with increasing catchment area (Figure 16). This is likely explained by the fact

that groundwater contribution could only be quantified for a limited number of sub-basins

in the Llanganuco and Pumapampa valleys and thus groundwater discharge isn’t

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representative of the entire catchment area. A multiple regression analysis revealed no

geospatial parameter which significantly predicts groundwater contribution.

The absence of correlations between pampa parameters and groundwater

contribution to surface water suggests that pampas - defined as paludified moraine

dammed lakes - may not be temporal storage sites for groundwater. This is also

supported by their unique major ion chemistry which is inconsistent with surface water

and melt water hydrochemistry (Baraer et al. 2009), and their low hydraulic conductivity.

Potential sources of groundwater might be slope deposits, including lateral moraines and

talus slopes, and sand and gravel aquifers in valley bottoms. Rock faces are typically

made of massive batholiths and therefore are not a potential storage site.

CONCLUSION

The valleys of Llanganuco, Quilcayhuanca, Querococha and Pumapampa have

considerably different geospatial and hydrological characteristics. Notably, the more

northern catchments have a higher degree of glacierization, but a smaller pampa area than

the southern basins. Melt water production decreases from the most northern to the most

southern valley, whereas groundwater production is similar in the basins of

Quilcayhuanca, Querococha, Pumapampa, but considerably lower in the Llanganuco

catchment. However, melt water and groundwater contribution in the Llanganuco and

Pumapampa basins could only be quantified for 38% and 30% of the entire catchment

area respectively (Baraer et al. 2009). The geospatial parameters were analyzed in

conjunction with the HBCM results to investigate physical features which could explain

the differences in hydrology. Only the glaciated area in each sub-basin was found to

significantly predict melt water discharge. Ablation area, slope and aspect are known to

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influence melt water production, however these features were not found to significantly

predict melt water contribution presumably due to the limited number of sub-basins and

coarseness of the slope and aspect data. Future work should involve repeating this

analysis for a larger number of sub-basins in addition to determining slope and aspect

parameters at the glacier level rather than for the entire glaciated area in the sub-basins.

The hydrogeology of glaciated terrains is very complex and a key feature of pro-

glacial systems is the variability in hydraulic conductivity (Fetter 2001, p.285). Deposits

formed in association with glaciers range from till with mud-textured matrix to well-

sorted glacio-fluvial sands and gravels which are of particular hydrogeologic importance

(Robinson et al. 2008). Understanding the hydrogeology of valleys in the Cordillera

Blanca is further complicated by the numerous glacial advances and retreats since the last

glacial maximum and the heterogeneous geology of the Cordillera Blanca. Thus, since

no geospatial parameters significantly predict absolute groundwater contribution, further

hydrogeological investigations in these pro-glacial catchments are warranted to provide a

better understanding of the groundwater processes in these complex environments.

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Tables

Table 1. Summary of geospatial parameters for four valleys in the Cordillera Blanca including basin area (km2), degree of glacierization (km2 and %), elevation (m), slope (º), and aspect (º) of glaciated area, pampa area (km2), length to width ratio of pampas and total length of river flowing through the pampas (km).

Valley

Basin Area (km2)

Glaciated Area (km2)

% glaciated

area

Minimum elevation

of glaciated area (m)

Maximum elevation

of glaciated area (m)

Median elevation

of glaciated area (m)

Maximum-minimum elevation

of glaciated area (m)

Average slope (º)

of glaciated

area

Average aspect (º) of

glaciated area

Area of Pampa

in basin (km2)

% Pampa

area

Average length

to width ratio of pampas

Total river

length through pampa (km)

Llanganuco 91.05 32.43 35.6 4377 6577 5258 2200 30.7 182.0 0.74 0.8 4.65 3.67 Quilcayhuanca 87.66 17.98 20.5 4353 6180 5139 1827 27.9 217.2 3.55 4.1 13.17 15.42 Querococha 62.92 1.75 2.8 4647 5181 4946 534 28.1 208.1 2.54 4.0 1.64 9.64 Pumapampa 69.16 9.34 13.5 4704 5462 5128 758 25.6 222.2 8.00 11.6 4.20 19.97

Table 2. Summary of the glacier parameters in selected sub-basins of the valleys of interest. Glacier parameters include degree of glacierization (km2 and %), elevation (m), slope (º), and aspect (º) of glaciated area.

Valley Sub-basin

Basin Area (km2)

Glaciated Area (km2)

% glaciated area

Glaciated Area below

5200 m (km2)

Minimum elevation

of glaciated area (m)

Maximum elevation of

glaciated area (m)

Median elevation

of glaciated area (m)

Maximum-minimum

elevation of glaciated area (m)

Average slope (º)

of glaciated

area

Average aspect (º)

of glaciated

area Llanganuco Kinzl Up 17.35 12.00 69.2 4.76 4377 6577 5319 2200 32.8 214.4 Quilcayhuanca Laguna Cuchilla 4.16 2.46 59.1 1.03 4735 6063 5259 1328 33.5 202.1 Quilcayhuanca Laguna Tulipacocha 15.18 9.12 60.1 5.60 4353 6180 5138 1827 25.8 221.3 Querococha Yan out 1.50 0.76 50.6 0.76 4647 5128 4896 481 26.6 197.0 Querococha YOG up 1.81 0.91 50.0 0.91 4816 5181 4973 365 26.1 222.9

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Table 3. Summary of the pampa parameters in selected sub-basins of the valleys of interest. Pampa parameters include pampa area (km2), percentage of sub-basin covered by pampas, length to width ratio of pampas, total length of river flowing through the pampas (km) and area pampa in the above (upstream) sub-basin.

Valley Sub-basin Basin

Area (km2)

Area of Pampa in

basin (km2)

%Pampa area

Average length to

width ratio of pampas

Total river length

through pampa (km)

Area of pampa

(km2) in sub-basin

above

%Pampa area in

sub-basin above

Llanganuco Kinzl 6.29 0.00 0.00 Quilcayhuanca Casa de agua 7.56 0.38 3.37 1.69 1.35 0.49 16.38 Quilcayhuanca Cayesh Low 6.10 0.45 7.33 7.93 2.60 0.16 1.27 Quilcayhuanca Quilcay above Choco 2.98 0.49 16.38 3.48 1.61 1.11 7.85 Quilcayhuanca Quilcay Out 20.82 1.33 11.86 14.28 5.37 0.38 3.37 Quilcayhuanca Valley2 8.03 0.66 2.07 3.27 3.36 Querococha Q2-2 6.42 0.48 7.45 3.17 1.65 Querococha Q2-3 7.13 0.62 8.75 0.84 1.49 Querococha Q2-1 10.06 0.19 1.91 2.17 6.25 1.10 8.13 Pumapampa Above Huayllo 3.91 0.32 8.27 1.81 0.76 1.21 10.26 Pumapampa Puma Q stn 15.49 2.99 19.31 4.70 9.46 0.32 8.27 Pumapampa Pumapampa below Ruri 1.02 0.30 3.42 5.62 0.99

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Table 4. HBCM results for the 2008 dry season maximum and minimum melt water contribution (m3/s).

Table 5. HBCM results for the 2008 dry season maximum and minimum groundwater contribution (m3/s).

Valley Sub-basin

minimum groundwater

contribution (m3/s)

maximum groundwater

contribution (m3/s)

Llanganuco Kinzl 0.04 0.04

Quilcayhuanca Casa de agua 0.01 0.04

Quilcayhuanca Cayesh Low 0.02 0.03

Quilcayhuanca Quilcay above Choco 0.00 0.00

Quilcayhuanca Quilcay Out 0.06 0.11

Quilcayhuanca Valley2 0.03 0.03

Querococha Q2-1 0.10 0.11

Querococha Q2-2 0.04 0.04

Querococha Q2-3 0.05 0.05 Pumapampa Above Huayllo 0.02 0.09 Pumapampa Puma Q stn 0.06 0.07 Pumapampa Pumapampa below Ruri 0.03 0.03

Valley Basin minimum melt water contribution (m3/s)

Maximum melt water contribution (m3/s)

Llanganuco Kinzl Up 0.90 0.90

Quilcayhuanca Laguna Cuchilla 0.07 0.07

Quilcayhuanca Laguna Tulipacocha 0.32 0.35

Querococha Q2-2 0.02 0.03

Querococha Q2-3 0.03 0.03

20

FIGURES

Figure 1. Map of Callejon de Huaylas with catchments and pampas.

21

Figure 2. Map of sub-basins and mixing points in the Figure 3. Maps of sub-basins and mixing points in the

Llanganuco catchment. Quilcayhuanca catchment.

22

Figure 4. Map of sub-basins and mixing points in the Figure 5. Maps of sub-basins and mixing points in the

Querococha catchment. Pumapampa catchment.

23

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

Llanganuco Quilcayhuanca Querococha Pumapampa

Glaciated Area (km2)

% glaciated area

Figure 6. Glaciated Area (km2) and percentage glacierized area based on 2003 SPOT5 imagery (2002 ASTER imagery for the Pumapampa valley) for four pro-glacial valleys in the Cordillera Blanca, Peru.

4000

4400

4800

5200

5600

6000

6400

6800

0 10000 20000 30000 40000 50000 60000 70000

m

Llanganuco

Quilcayhuanca

Pumapampa

Querococha

Figure 7. Hypsometric curves for the glaciated area in four pro-glacial valleys in the Cordillera Blanca, Peru.

Area (m2)

24

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

Llanga

nuco

Quilc

ayhuan

ca

Quer

ococh

a

Pumap

ampa

Pampa Area (km2)

Pampa Area/Basin

Area (%)

Figure 8. Area of pampas (km2) and percentage of the basin covered by pampas for four pro-glacial valleys in the Cordillera Blanca, Peru.

Figure 9. Geological characterization of the A) Llanganuco B) Quilcayhuanca

D

15%

66%

19%

Chicama

Formation

Volcanic

Ignimbrite

Calipuy

Cretaceous

Sedimentary

Rocks

B

14%

86%

Plutonic

Intrution

Chicama

Formation

C

25%

40%

35%

Plutonic

Intrution

Chicama

Formation

Quaternary

Fluvial Glacial

Sediments

A

60%

40%

Plutonic

Intrusion

Chicama

Formation

25

C) Querococha D) Pumapampa valleys.

26

Figure 10. Absolute contribution (m3/s) of average melt water and groundwater to total 2008 dry season discharge at the outlet of the Llanganuco, Quilcayhuanca, Querococha and Pumapampa catchments.

y = 0.0378x

R2 = 0.7601

0

0.2

0.4

0.6

0.8

1

1.2

0 5 10 15 20 25 30

Sub-basin Area (km2)

Min

imu

m m

elt

wa

ter

con

trib

uti

on

(m

3/

s)

Figure 11. Relationship between sub-basin area (km2) and minimum melt water contribution (m3/s).

27

y = 0.0597x

R2 = 0.8371

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 2 4 6 8 10 12 14

Glaciated Area (km2) within sub-basin

Min

imu

m m

elt

wa

ter

con

trib

uti

on

(m

3/

s)

Figure 12. Relationship between glaciated area in sub-basin (km2) and minimum melt water contribution (m3/s).

Figure 13. Relationship between area (km2) below the ELA (~below 5200m) and minimum melt water contribution (m3/s).

28

Figure 14. Relationship between percent of basin glaciated and average melt water contribution (m3/s) and.

y = 0.0028x + 0.0167

R2 = 0.3336

0

0.02

0.04

0.06

0.08

0.1

0.12

0 5 10 15 20 25 30

Sub-basin area (km2)

Min

imu

m g

rou

dn

wa

ter

con

trib

uti

on

(m

3/

s)

Figure 15a. Relationship between sub-basin area (km2) and minimum groundwater contribution (m3/s).

29

Figure 15b. Relationship between sub-basin area (km2) within each valley and minimum groundwater contribution (m3/s).

0

0.05

0.1

0.15

0.2

0.25

0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00

Basin Area (km2)

Gro

un

dw

ate

r co

ntr

ibu

tio

n (

m3

/s)

Querococha

Quilcayhuanca

Llanganuco

Pumapampa

Figure 16. Relationship between total basin area (km2) and average groundwater contribution (m3/s).

30

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