Identification and Quantification of Runoff Generation · 2016-11-02 · Omar Munyaneza Umaru ......

Identification and Quantification of Runoff Generation

Processes During Floods and Droughts In Migina

Catchment, Southern Of Rwanda

By

Omar Munyaneza

Umaru Garba Wali

Christine Uzayisenga

Théoneste Nkurunziza

Ramazani Bizimana

Cyprien Ndayisaba

Coordinated by

Eng. Omar Munyaneza

National University of Rwanda

NBCBN Rwanda Node

Kigali Institute of Science and Technology (KIST)

Country Coordinator

Prof. Dr. Jean Baptiste Nduwayezu

2010

Produced by the Nile Basin Capacity Building network (NBCBN-SEC) office

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mailto:[email protected]

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Project Title

Knowledge Networks for the Nile Basin

“Using the innovative potential of Knowledge Networks and CoP’s in strengthening human and

institutional research capacity in the Nile region”

Implementing Leading Institute

UNESCO-IHE Institute for Water Education, Delft, The Netherlands (UNESCO-IHE)

Partner Institutes

Nine selected Universities and Institutions from Nile Basin Countries.

Project Secretariat Office

NBCBN-SEC office, Hydraulics Research Institute – Cairo - Egypt

Beneficiaries

Water sector professionals and institutions in the Nile Basin Countries

Short Description

The idea of establishing a Knowledge Network in the Nile region emerged after encouraging

experiences with the first Regional Training Centre on River Engineering in Cairo since 1996. In

January 2002 more than 50 representatives from all ten Nile basin countries signed the Cairo

Declaration at the end of a kick-off workshop was held in Cairo. This declaration in which the

main principles of the network were laid down marked the official start of the Nile Basin

Capacity Building Network in River Engineering (NBCBN-RE) as an open network of national

and regional capacity building institutions and professional sector organizations.

NBCBN is represented in the Nile basin countries through its nine nodes existing in Egypt,

Sudan, Ethiopia, Tanzania, Uganda, Kenya, Rwanda, Burundi and D. R. Congo. The network

includes six research clusters working on different research themes namely: Hydropower,

Environmental Aspects, GIS and Modelling, River Morphology, flood Management, and River

structures.

The remarkable contribution and impact of the network on both local and regional levels in the

basin countries created the opportunity for the network to continue its mission for a second phase.

The second phase was launched in Cairo in 2007 under the initiative of; Knowledge Networks for

the Nile Basin. New capacity building activities including knowledge sharing and dissemination

tools, specialised training courses and new collaborative research activities were initiated. The

different new research modalities adopted by the network in its second phase include; (i) regional

cluster research, (ii) integrated research, (iii) local action research and (iv) Multidisciplinary

research.

By involving professionals, knowledge institutes and sector organisations from all Nile Basin

countries, the network succeeded to create a solid passage from potential conflict to co-operation

potential and confidence building between riparian states. More than 500 water professionals

representing different disciplines of the water sector and coming from various governmental and

private sector institutions selected to join NBCBN to enhance and build their capacities in order

to be linked to the available career opportunities. In the last ten years the network succeeded to

have both regional and international recognition, and to be the most successful and sustainable

capacity building provider in the Nile Basin.

List of Figures

List of Tables

1 INTRODUCTION ....................................................................................................................................................... 1

1.1 OBJECTIVE OF THE STUDY.................................................................................................................................... 1 1.2 SCOPE OF THE RESEARCH ..................................................................................................................................... 1 1.3 CONTRIBUTIONS OF THE RESEARCH AND REPLICATION ACTIONS ........................................................................ 2

2 RESEARCH METHODOLOGY ................................................................................................................................. 3

2.1 THE MIGINA CATCHMENT AND KADAHOKWA MARSHLAND DESCRIPTION .......................................................... 3 2.2 EXPERIMENTAL INVESTIGATIONS AND SAMPLING ............................................................................................... 5 2.3 HYDROMETRIC AND TRACER METHODS .............................................................................................................. 5

3 RESEARCH ACTIVITIES .......................................................................................................................................... 6

4 RESEARCH ACHIEVEMENTS ................................................................................................................................. 7

4.1 THE DEVELOPMENT OF LOCAL ACTION RESEARCH PROPOSAL AND SETTING UP OF WORKING MEMBERS OF THE

RESEARCH TEAM .............................................................................................................................................................. 7 4.2 LITERATURE REVIEW ........................................................................................................................................... 8 4.3 ACQUISITION OF HISTORICAL DATA .................................................................................................................... 8 4.4 FIELD WORK ........................................................................................................................................................ 9

4.4.1 Instrumental Setup in the Migina Catchment .................................................................................................. 9 4.5 DATA COLLECTION ............................................................................................................................................ 11 4.6 DATA ANALYSIS/LAB WORK ............................................................................................................................. 13 4.7 PREPARATION/COMPILATION OF RESULTS ON RUNOFF GENERATION PROCESSES ............................................. 13

4.7.1 Hydrochemistry-Surface Water .................................................................................................................... 16 4.7.2 Spatial and Temporal Variability of Daily Rainfall in Migina Catchment ................................................... 16 4.7.3 Generation Rating Curve .............................................................................................................................. 18 4.7.4 Hydrochemical Analysis ............................................................................................................................... 20

4.8 RESEARCH REPORT ............................................................................................................................................ 20

5 CONCLUSIONS ........................................................................................................................................................ 21

6 REFERENCES .......................................................................................................................................................... 22

LIST OF RESEARCH GROUP MEMBERS

APPENDICIES

GROUP MEMBERS PHOTOS ............................................................................................................................................. 4

LIST OF FIGURES

Figure 1: Location of the Migina catchment in Rwanda and its hydrologic network ................................................... 4

Figure 2: Narrow stream passing through farmers’ crops fields; Spring with continuous flow (local people said flow

is available in all seasons); and wet areas with big trees on lateral sides of Kadahokwa marshland area ...................... 4

Figure 3: Spatial distributions of installed hydro-meteorological stations in the Migina catchment. .......................... 10

Figure 4: Instrumental setup in Migina Catchment: a) Weather station and evaporation pan; b) equipments for

hydrochemical analysis; c) Automatic rain gauge (Tipping bucket) and manual rain gauges; d) Staff Gauge (left),

automatic gauging station with diver (center) and Piezometer with diver inside the closed lock (right) ..................... 11

Figure 5: Relation between EC and water level of River: Staff gauge 1 means Mukura River and staff gauge 2

means Cyihene River at Kansi Bridge. ......................................................................................................................... 16

Figure 6: Temporal variability of rainfall at Murama station and in the whole Migina catchment .................. 17

Figure 7: Rating curve generation based on data collected from the Mukura River gauging station installed

in May 2009, fourteen discharge measurements were taken from May to Dec 2009. ....................................... 18

Figure 8: Mean daily rainfall and river discharge observed in the Migina catchment (May to Dec 2009) at a)

Mukura; b) Cyihene-Kansi; c) Munyazi-Rwabuye; d) Akagera; and e) Migina stations. ................................. 19

Figure 9: Hydrochemical parameters at Cyihene-Kansi River during 4 November 2009 event ...................... 20

LIST OF TABLES

Table1: Profile of Activities, Outputs and timeframe (from June to December 2009) ........................................ 6

Table 2: Rwanda group composition and their background ................................................................................ 7

Table 3: Selected stations used for hydro-climatic analysis ................................................................................ 9

Table 4: Hydrological and meteorological stations installed in Migina catchment and data records ................ 12

Table 5: Hydrochemistry results ........................................................................................................................ 14

LIST OF PHOTOS

Photo 1: Mukura River discharge measurement (picture taken by Harmen van den Berg on 06/05/2009) and

Akagera River discharge measurement (Picture taken on 10/08/2009 by Emille (BSc student) when NUR

Civil Engineering students were instructed how to measure discharge using a propeller). ............................... 18

This report is one of the final outputs of the research activities under the second phase of the Nile Basin

Capacity Building Network (NBCBN). The network was established with a main objective to build and

strengthen the capacities of the Nile basin water professionals in the field of River Engineering. The first

phase was officially launched in 2002. After this launch the network has become one of the most active

groupings in generating and disseminating water related knowledge within the Nile region. At the moment it

involves more than 500 water professionals who have teamed up in nine national networks (In-country

network nodes) under the theme of “Knowledge Networks for the Nile Basin”. The main platform for capacity

building adopted by NBCBN is “Collaborative Research” on both regional and local levels. The main aim of

collaborative research is to strengthen the individual research capabilities of water professionals through

collaboration at cluster/group level on a well-defined specialized research theme within the field of River and

Hydraulic Engineering.

This research project was developed under the “Local Action Research Modality” which has a main objective

to contribute to the capacity building process at local level and enhance the collaboration among the

researchers and institutions in the same country. This activity is the core activity of all NBCBN nodes and is

contributing to the establishment of the in-country network.

This report is considered a joint achievement through collaboration and sincere commitment of all the

research teams involved with participation of water professionals from all the Nile Basin countries, the

Research Coordinators and the Scientific Advisors. Consequently the NBCBN Network Secretariat and

Management Team would like to thank all members who contributed to the implementation of these

research projects and the development of these valuable outputs.

Special thanks are due to UNESCO-IHE Project Team and NBCBN-Secretariat office staff for their

contribution and effort done in the follow up and development of the different research projects activities.

This work was conducted in collaboration with a Team group of researchers of NBCBN

Rwanda Node members from different research Clusters like Hydropower, Flood

Management and Environmental Aspects. Researchers are also from different institutions

such as National University of Rwanda (NUR), Kigali Institute of Scientific and

Technology KIST), Institute of Scientific and Technological Research (IRST) and

Ministry of Agriculture (MINAGRI). The team members would like to recognize the

involvement of Dr. Jean Baptiste Nduwayezu, Coordinator of NBCBN Rwanda Node,

for his collaboration, encouragement and good working environment. The financial

support of Nile Basin Capacity Building for River Engineering (NBCBN-RE) is also

highly appreciated and further support is needed to encourage and motivate young

researchers.

ABSTRACT

Identification of hydrological processes is essential for the proper assessment of water resources availability

within catchments. The use of environmental isotopes in combination with hydrochemical tracers helped to

gain further insights into hydrological processes, in particular into flow pathways, residence times of water,

and the mixing of different runoff components. The aim of this research was to contribute to the

understanding of dominant hydrological process interactions in the meso-scale Migina catchment, southern

Rwanda. Specifically, the study emphasizes on identifying the dominant runoff generation processes during

floods and droughts and its spatio-temporal variability. Therefore, to investigate these processes, hydrometric

techniques using measurement of precipitation, discharge (at different scales) and shallow groundwater

piezometers were executed and supplemented with tracer studies. Dissolved silica (SiO2), major anions (Cl-,

P042- and S04

2-) and major cations (K+, Ca2+, Mg2+) were analyzed in order to quantify the contributions of

runoff components during different hydrological situations (floods and low flows) in the meso-scale Migina

catchment. Therefore, classical hydrometric techniques (measurement of precipitation, runoff discharge and

groundwater levels) were supplemented with tracer studies. Floods are available during the rainy seasons and

low flows in dry seasons; the variable contributions of groundwater to stream flow were quantified using the

tracer methods. These methods showed that the surface runoff is dominating the total discharge during floods

due to the observed suspended sediment in water samples. The response of the Migina catchment presents

slow surface runoff processes due to its topography (not steep) and land use. One flood event was investigated

during the rainy season of October–December 2009 and analysed for dissolved silica and major anions and

cations. This is for the event of 4 November 2009 observed at Cyihene-Kansi River located in Migina sub-

catchment. During the period from May to December 2009, the maximum rainfall of 52.5 mm d-1 was

observed in November at Mpare rainfall station (1691 m a.s.l.). The highest peak flow was observed on 19

November 2009 at the outlet of the Migina catchment at Migina River (4.8 m3 s-1), and the lowest flow was

observed on 8 August 2009 at Munyazi-Rwabuye River (0.0002 m3 s-1), which is located at upstream of the

Migina catchment.

Keywords: Hydrological processes; runoff generation processes; hydrometric and tracer methods; meso-scale;

Rwanda

Local Action Research-Rwanda 2010

Nile Basin Capacity Building Network ( NBCBN ) 1

1 INTRODUCTION

In many parts of the world catchments are not or poorly gauged. In particular in developing countries,

catchments are predominantly ungauged, as a result of lack of adequate resources (Mazvimavi, 2003). This

report provides the achievement of Rwanda Local Action Research in determining runoff generation processes

and quantifying runoff components at an event and seasonal timescale in a meso-scale Migina catchment (214

Km2), Southern of Rwanda. The study covered the dry season of June to August for drought events and low

flows, and the rainy season of October to December for flood events. Kadahokwa marshland which is one out

of five sub-catchments located in Migina catchment was understudy for instrumental set up for groundwater

monitoring (installation of piezometers) since May to July 2009.

Different key persons from different research clusters in Rwanda with different background skills were

actively involved in this local action research. This report outlines the various activities that have been

achieved. The use of isotopic tracers in combination with hydrochemical tracers was necessary to complete

this study. However, understanding hydrological processes, in particular water flow pathways, source areas

and residence times, are very essential for predicting water quantities (including floods and low flows) and

water quality in a catchment as found by Uhlenbrook, et al., 2008.

Hydrological processes within a catchment define how precipitation reaches the catchment outlet, how long

water is stored in the surface water, soil water and groundwater systems, as well as the hydrochemical

composition of these components (Uhlenbrook, et al., 2008 and Wenninger et al., 2008). To investigate these

processes, different types of field studies have been conducted in Migina catchment including comparison of

the hydrological responses.

This report is based on proposed activities during this local action research development as approved by

NBCBN Rwanda Steering Committee and NBCBN Secretariat. The planed activities were reminded in this

scientific report in order to give a clear picture of what Rwanda has achieved for local action research of 2009.

1.1 Objective of the Study

The overall aim of this research is to contribute to the understanding of dominant hydrological process

interactions in the meso-scale Migina catchment (214 km2), southern Rwanda.

The specific objectives of this study are:

To investigate the rainfall and runoff dynamics during the rainy and dry season in Migina catchment;

To separate and quantify different runoff components in the meso-scale Migina catchment of Rwanda;

To identifying the dominant runoff generation processes during floods and droughts events; and

To determine the spatio-temporal variability of dominant runoff generation processes.

1.2 Scope of the Research

The study investigated the instruments (climate and gauging stations) in meso-scale catchment for studying

the runoff generation processes in order to quantify the contributions of runoff components during different

hydrological situations (flood, drought and low flows). The study was focusing on a meso-scale Migina



catchment (214 km2) which is located in southern province of Rwanda (fig. 1). Kadahokwa marshland which

is one out of five sub-catchments located in Migina catchment, was understudy for instrumental set up

(installation of piezometers).

1.3 Contributions of the Research and Replication Actions

The research is a source of information on identification of runoff generation processes in the catchment. The

study contributes to a better understanding of dominant hydrological process interactions in the meso-scale

Migina catchment, southern Rwanda.

The knowledge generated in this research is essential to decision-makers for setting national water policies

and strategies, and should also help planers for sustainable water resources management and planning. The

study also provided a tool which should be helpful for farmers to optimize the crop production in the

marshlands in terms of agriculture production.

According to the types of microclimates and regions, similar study should be extended to other regions with

different characteristics like drought regions of Eastern part of Rwanda such as Bugesera and Umutara where

surface water is scarcity and groundwater studies is not yet developed. The study can be also extended to the

volcanic regions or high lands (Ruhengeri and Byumba) where groundwater is very limited and not yet

exploited as well.



2 RESEARCH METHODOLOGY

A list of group members was established to work on particular sections components of the catchment

hydrology. For instance, Hydrology and Water Resources, Environmental water Chemistry, Water

Management, Civil Engineering, Agricultural Engineering aspects require pertinent specialists dealing with

this particular aspects. Accordingly, six working members of the research team were identified to carry out

this research (Table 2).

Existing literature (especially previous studies done) on a meso-scale catchment using hydrometric and tracer

methods was collected and assessed by research group members to select appropriate methodology for this

specific topic.

Chemical hydrograph separation method was a selected to define the origin and composition of the runoff

during floods (Uhlenbrook et al., 2002). This method is based on the mixing of two or more water types with

known and distinct hydrochemical characteristics, where the ratio of mixing determines the concentrations in

the stream. Classical hydrometric techniques (measurement of precipitation, runoff discharge and groundwater

levels) were supplemented with tracer studies. For a better overview of the precipitation and runoff dynamics

during the investigation period, the time series of precipitation was divided into different events.

2.1 The Migina Catchment and Kadahokwa Marshland Description

The hydro-meteorological instrumentation took place in the meso-scale Migina catchment (214 km2), southern

Rwanda (Fig. 1). Approximately 56,500 inhabitants with a growth rate of about 3% (Nahayo, 2007) are living

within the catchment. The site is mountainous with elevation ranging from 1,434 m at the outlet of the Migina

River to 2,251 m at Huye Mountain. The topographic conditions are very variable and show slopes of the

valleys which varies from 5 to 10% in the upstream and 1 to 15% in the downstream part (average slope is

between 2 and 3%) (see Nahayo, 2008). Land use is dominated by pasture and farm land where e.g. rice,

sorghum, maize, and sweet potato are cultivated.

The Migina catchment (2o32’S to 2o48’S and 29o42’E to 29o48’E) is divided into 5 sub-catchments

according to the main rivers draining the area. Two are located at the upstream (Munyazi and Mukura), two in

the center (Cyihene at Kansi and Akagera), and one is located downstream part (Migina River).



Figure 1: Location of the Migina catchment in Rwanda and its hydrologic network

In the Migina catchment the mean annual rainfall is approximately 1200 mm a-1 and the temperature is about

20oC. The annual average evaporation in the area is estimated to 917 mm a-1 (Nahayo, 2008). The annual

average of the relative soil moisture, calculated over the 11 years is 75.7% with minimum in June of 59.8%

and the maximum in April of 86.3% (Nahayo, 2007). The wind speed varies mostly between 1 to 3 m s-1 and

rarely exceeds 6 m s-1.

Kadahokwa marshland, which is located in the upstream part of the Migina catchment, was a focus of this

research for drilling activities. The Kadahokwa marshland is interesting site because there is no any other

activity instead of agriculture. Only field crops are observed in this marshland: Maize, corn, sweet potatoes, a

small rice field and vegetables. These are farmers own fields and no irrigations activities observed in this

marshland (Fig 2).

Figure 2: Narrow stream passing through farmers’ crops fields; Spring with continuous flow (local people

said flow is available in all seasons); and wet areas with big trees on lateral sides of Kadahokwa marshland

area



2.2 Experimental Investigations and Sampling

The instrumentation network includes hand auger to bedrock and shallow groundwater wells, as well as PVC

tubes in an upper and lower sub-catchment. Eleven piezometers with 2 transactions were installed in

Kadahokwa marshland. Samples from surface water runoff, rainfall and groundwater were taken and analysed

for natural tracers (i.e. silica and chloride).

2.3 Hydrometric and Tracer Methods

Hydrochemical tracers, such as Mg2+, SO2-4 and Cl- are relatively inexpensive to analyse and easy to use for

hydrograph separation (Ribolzi et al., 2000 and Tardy et al., 2004). The main challenge with using these

tracers is that the original concentrations can change along the specific flow path (non-conservative

behaviour). With a limited amount of time between rainfall and runoff, this can be neglected. Chemical

hydrograph separation has been mostly applied in humid temperate climates. This study also describes the

application of this method using hydrochemical tracers in a humid meso-scale Migina catchment.

During this research hydrochemical data and isotope data were collected in order to quantify the contributions

of runoff components during different hydrological situations (floods and low flows) in a mesoscale Migina

catchment. These data were measured biweekly or monthly at five rivers located at different sub-catchments

of Migina catchment (Munyazi at Rwabuye bridge, Mukura, Kagera, Cyihene at Kansi bridge and Akanyaru

at out let of Migina catchment).

The same study has been done by Uhlenbrook et al. (2002) using dissolved silica (SiO2) to investigate runoff

processes, flow pathways and to separate different runoff components. In his study, dissolved silica

concentrations (referred to as silica in the following text) were determined by photometric measurements,

using heteropoly acids produced by the reaction of ammonium molybdate with silica, according to the

German Institute for Standardization DIN 1981 (DEV D21; DIN 38405 part 21).

In this proposed research, monthly rainfall was collected from 5 different rain gauges which have been

installed in the catchment and samples were taken from those monthly collected water. Some hydrochemical

parameters like pH, EC, T were analyzed in the field as soon as earlier the water were sampled to avoid

oxidization and chemical properties changes. Other hydrochemical tracers were analyzed in the NUR

laboratory in Rwanda using an ion chromatograph and atomic absorption spectroscopy and the results are

given in the table 5.

Hydrograph separation techniques was also used in this study to determine runoff generation processes and to

quantify runoff components at an event and seasonal timescale in a meso-scale Migina catchment (from July

to December 2009). This method is based on the mass balance of water and tracer. The techniques have been

used by Mul et al. (2007) using hydrochemical tracers including electrical conductivity (EC), dissolved silica

(SiO2), and major anions and cations to separate and quantify different runoff components in the semi-arid

Makanya catchment in the South Pare Mountains of Tanzania.

In order to quantify the total amount of base flow for the hydrological year (July and August 2009) at the

lower piezometrs of the Kadahokwa sub-catchment, hydrograph separation using an additional runoff

separation technique was adopted (e.g. in Uhlenbrook et al., 2002; Mul et al., 2007; Wenninger et al., 2008).

The method is based on the assumption that the frequency spectrum of a hydrograph is built up by long waves

associated with base flow and high frequency waves caused by direct runoff (Wenninger et al., 2008).



3 RESEARCH ACTIVITIES

Activities realized during the year 2009 are summarized in the table below as planned during research proposal

development.

Table1: Profile of Activities, Outputs and timeframe (from June to December 2009)

Activities Expected Outputs Time

frame

1) Establishing a local action research team members from various field of

specialization related to water science (Hydrology and Water Resources,

Environmental water Chemistry, Water Management, Civil Engineering,

Agricultural Engineering), and developing a local action research proposal

-Local action research proposal developed

-Working members of research team established

and activities for each member set out

2 month

2) Literature Review : Runoff components during different hydrological

situations (floods, droughts and low flows), Dominant runoff generation

processes and Hydrograph separation techniques.

-All relevant documents for the establishment of

the research are collected and reviewed

6 months

3) Acquisition of historical data: Climatic data, hydrological data, Remote

sensing data, land use and cover data, Cropping pattern data

-Historical data on Migina catchment are

collected

2 month

4) Field Work: Field visit for catchment reconnaissance, Installation of

piezometers (Wells) in Kadahokwa Marshland, installation of rain gauges in

primary schools and staff gauges in rivers.

- Migina catchment visited for catchment

reconnaissance - 11 Piezometers

installed in Kadahokwa marshland

- 13 manual rain gauges including 3 automatic

raingauges and 5river (staff) gauges stations

installed in Migina catchment

2 months

5) Data collection: Groundwater and surface water samples, River discharges

measurement in 5 gauging stations in Migina catchment; Stream water samples

at 5 sites in the catchment (biweekly or monthly intervals), Catchment

precipitation from 5 Rain collectors installed in the Migina catchment (monthly

average intervals)

- Groundwater/surface water and rain water,

river discharges, water chemistry collected

5 months

6) Data analysis/Lab Work: Identification and quantification of runoff

generation processes [Major anions (Cl-, N03-, S04

2-,); Dissolved silica (SiO2);

and Major cations (Mg2+, Ca2+, K+); were analysed in the NUR laboratories;

Hydro-chemical parameters like pH, EC and T were analyzed in the field.

Hydrograph separation techniques were also exploited].

- Rainfall and runoff dynamics during the rainy

and dry season investigated

- Hydro chemical data and isotope data analysed

- Dominant runoff generation processes

identified and quantified

4.5 months

7) Preparation/Compilation of results on runoff generation processes -All research results obtained and compiled 3 weeks

8) Research report Research report elaborated and submitted to

NBCBN Rwanda Node Secretariat

1 week



4 RESEARCH ACHIEVEMENTS

4.1 The Development of Local Action Research Proposal and Setting up of

Working Members of the Research Team

A list of group members was established to work on particular sections components of the catchment

hydrology. For instance, Hydrology and Water Resources, Environmental water Chemistry, Water

Management, Civil Engineering, Agricultural Engineering aspects which required pertinent specialists dealing

with this particular aspects were identified. Accordingly, 6 working members of the research team were

identified to carry out this research regarding to their background or specialization (Table 2).

Table 2: Rwanda group composition and their background

No Name* Background/Specialization E-mail Post and Institution

1 Eng. Omar

Munyaneza

PhD Researcher in Hydrology and

Water Resources (MSc in Water

Resources and Environmental

Management (WREM); and BSc in

Civil Engineering)

[email protected] Lecturer at National

University of Rwanda

(NUR)

2 Mr. Théoneste

Nkurunziza

MSc in Water Resources and

Environmental Management

(WREM) (BSc in

Environmental Chemistry)

[email protected] Lecturer in Kigali

Institute of Scientific and

Technology (KIST)

3 Dr. Umaru Garba

Wali

PhD in Hydraulics and Engineering

Hydrology (MSc in Irrigation,

Drainage, Land Development and

Water Supply; BSc in Agricultural

Mechanization)

[email protected] Lecturer at National

University of Rwanda

(NUR)

4 Eng. Christine

Uzayisenga

BSc in Agricultural Engineering [email protected] Engineer in Rwanda

Agricultural

Development Authority

(RADA) in the Ministry

of Agriculture

(MINAGRI) 5 Eng. Ramazani

Bizimana

Post-Graduate Diploma in Water

Management

(BSc in Agricultural Engineering)

[email protected] Rural Engineer in

Rwanda Rural Sector

Support Project (RSSP)

in MINAGRI

6 Mr. Cyprien

Ndayisaba

Post-Graduate Diploma in Natural

Resources and Environmental

Management (BSc in Chemistry)

[email protected] Researcher in the

Institute of Scientific and

Technological Research

(IRST)

*Team Group is composed by NBCBN Rwanda Node members from different Research Clusters.






4.2 Literature Review

All relevant documents for the establishment of this research were collected. This part was constituted to

review an existing baseline information and literature material which could be undertaken to conduct the

research. The previous studies related to the present research were consulted (e.g. Rodgers et al., 2005; Mul et

al., 2007; Didszun and Uhlenbrook, 2008; Uhlenbrook et al., 2002 and 2008; Wenninger et al., 2008; and

many others). To facilitate this step, some of the important literature with regard to existing literature

(especially previous studies done) on a meso-scale catchment (1–1000 km2) using hydrometric and tracer

methods was collected, consulted and assessed by research group members to select appropriate methodology

for this specific topic.

Main points were focused (targeted) during this part like runoff components during different hydrological

situations (floods, droughts and low flows), dominant runoff generation processes, hydrograph separation

techniques, hydrological source areas, flow pathways and catchment residence times. Additional materials

acquired are listed down in the list of references which is presented at the end of this local action research

report.

4.3 Acquisition of Historical Data

Historical data available in Migina catchment as used in this study were provided by the Ministry of

Environment and Lands (MINELA), former Ministry of Natural Resources (MINIRENA) and Rwanda

Meteorological Office. Some additional data like topographic map, DEM map, land use and land cover were

obtained from other institutions like National University of Rwanda (NUR-CGIS Center).

The period of available data records in Migina catchment is given in Table 3. Within the period of data

availability, the data set exhibit some significant discontinuity. In many cases the missing values ranges from

several months to several years. Because of that, a manual screening method was used to select as set of

dataset with reasonably long period of time series with minimum missing values (Munyaneza et al., 2009).

The locations of these selected stations are presented in Fig. 3. Kigali airport is not located in Migina

catchment but was just used to show stations where minimum missing values are available. Kigali airport is a

referenced meteorological station in Rwanda. These historical data were used to check the accuracy of data

collected recently in Migina catchment for this local action research (only for 7 months).



Table 3: Selected stations used for hydro-climatic analysis

Parameter

Station

No Station name Period of data availability

Time series

length

Altit

ude

(m)

Rainfall 1 Butare Mission 1934-1963; 1967 31 years 1750

2 Nyakibanda 1937-1993 57 years 1750

3 Butare airport 1969-1993 25 years 1768

4 Kansi ENT 1977-Feb 1994 20 years 1650

5 Kansi Parish 1940-Feb 1994 54 years 1670

6 Save ETI 1974-Feb 1994 20 years 1750

7 Rubona Hill 1958-1980; 2000; 2004-2005 26 years 1675

8 Save Parish 1910-1916; 1930-1948; 1981-1992 31 years 1775

9 Kigali Airport

1964- Feb 2008 ; Only data from

May to Sept 1994 are missing 45 years 1475

Temperature 1 Kigali Airport 1971-2008 38 years 1495

2 Butare Airport 1971-1993 23 years 1768

Stream flow

Station

No

River/Former

Province Period of data availability Time series

Alt.

1 Mwogo 1/Butare

1970; 1972-1982; 1984-1989; 1995-

2000 24 years 1525

2 Akanyaru 1/Butare

1955-1961; 1963; 1971-1991; 1995-

2000 34 years 1406

3 Migina/Butare 1970-1990 21 years 1547

4.4 Field Work

4.4.1 Instrumental Setup in the Migina Catchment

The filed work was taken place in the meso-scale catchment called Migina with surface area of 214 km2. The

catchment is located in the Southern Province of Rwanda (former Butare Province) in current districts of

Huye, Nyaruguru and Gisagara (Fig. 1). This study describes the setup of hydrological and meteorological

stations in Migina catchment and presents the hydro-climatic data collected from May to December 2009. All

maps were produced by using ArcGIS. All rainfall and climatic stations have been installed near Primary

Schools for security reasons and for getting accurate readings done by teachers. Local people were trained on

how to carry out data collection and on the important benefits of the installation and setup of hydro-

meteorological stations in the catchment.

Rainfall stations were built using PVC tubes grounded with concrete. The height is 50 cm to 1 m; on average

around 70 cm above the surface (Fig. 4). Funnels and plastic cylinders were used for some stations and



manual rain gauges were used at other stations. Daily rainfall and evaporation data were collected at 7AM

using trained local people. Rainfall intensity was measured using tipping buckets. Gauging stations have been

installed in the main 5 rivers at the outlet of each sub-catchment of Migina catchment (Fig. 3). PVC tubes

were used and iron stills were fixed with concrete for protection. A pressure transducer (mini diver, Van Essen

Instruments) was installed inside the PVC tube for automatic water level measurements. Instantaneous river

discharge measurements were taken once a week or bi-weekly according on the change in water level using

area-velocity method (Photo 1; Waterloo et al., 2007). Daily water level measurements were collected by local

people as a back-up for the diver data. Rating curves are generated and daily river discharges were prepared,

see below.

Shallow piezometers were installed in the upstream part of the Migina catchment in Kadahokwa marshland

for groundwater level monitoring. A gravel pack (highly permeable) around the screen was made, filter

stocking to leave the (bigger) soil particles outside and to avoid clogging of the piezometers were used. Clay

to close the top part of the soil surrounding the piezometer was used to avoid (preferential) infiltration

alongside the tube. An iron still was fixed with concrete on top of the piezometer for protection. Continuous

groundwater level measurements with an interval of 5 to 15 minutes were collected using pressure transducers

(Mini Diver, Van Essen Instruments). The stations installed and period of available data records are given in

Table 4. The pictures of some of hydrological and meteorological stations during their installation are shown

in Fig. 4.

After the field visit for catchment reconnaissance, a detailed hydrological and meteorological instrumentation

of Migina catchment (214 km2) was carried out (Fig. 3). This includes: 13 rain gauges including three

automatic tipping buckets, 2 evaporation pans, 1 weather station, 5 river gauging stations and 11 piezometers

(shallow wells).

Figure 3: Spatial distributions of installed hydro-meteorological stations in the Migina catchment.

These equipments were installed partly for local action research and another part for PhD and MSc researches.

This was in collaboration with UNESCO-IHE and National University of Rwanda (NUR) where one PhD



student (Omar) and 2 MSc students from Vriije University Amsterdam (Harmen and Rutger) were doing their

field research in the same catchment (Migina catchment). The field work achievement is shown bellow in

figure 4.

a) b)

c)

d)

Figure 4: Instrumental setup in Migina Catchment: a) Weather station and evaporation pan; b) equipments for

hydrochemical analysis; c) Automatic rain gauge (Tipping bucket) and manual rain gauges; d) Staff Gauge

(left), automatic gauging station with diver (center) and Piezometer with diver inside the closed lock (right)

4.5 Data Collection

After installation of the above equipments, different data were collected including Groundwater, surface and

Soil water samples, river discharges measurement (Photo 1) from 5 river gauging stations (Munyazi, Mukura,

Cyihene, Akagera and Migina); stream water samples at 5 sites in the catchment (weekly or biweekly



intervals), monthly catchment precipitation from rain collectors in 5 stations according to geographical

position (North, south, west, center and eastern of Migina catchment). Water samples from about 10 springs

located in Migina were also collected for hydrochemistry analysis (Table 5c).

The hydro-meteorological stations installed and period of available data collected are given in Table 4 and the

locations of these installed stations are presented in Fig. 3. River discharge measurements were taken using

area-velocity method (propeller) and the rating curve was generated referring to Show (2004).

Table 4: Hydrological and meteorological stations installed in Migina catchment and data records

Parameter

Station

No Station name Period of data

Coordinates

(UTM Zone) Altitude

availability X (m) Y (m) 35M (m)

Steam flow 1 Mukura From May to Dec 2009 804606 9707366 1618

2 Cyihene-Kansi From May to Dec 2009 806555 9702617 1577

3

Munyazi-

Rwabuye From May to Dec 2009 806263 9713884 1662

4 Akagera From Jul to Dec 2009 801597 9699935 1575

5 Migina From Jul to Dec 2009 801454 9692989 1520

Rainfall 1 Murama From May to Dec 2009 80129 9699128 1720

2 Vumbi From May to Dec 2009 800382 9709831 1824

3 Mpare From May to Dec 2009 803030 9711007 1691

4 Sovu From May to Dec 2009 800824 9717176 1764

5 Save B From May to Dec 2009 808328 9718265 1770

6 Muyira From May to Dec 2009 809227 9708819 1725

7 Kibilizi From May to Dec 2009 809300 9706476 1712

8 Gisunzu From June to Dec 2009 805956 9701364 1684

9 Rwasave From May to Dec 2009 806184 9712510 1665

10 Kansi A From May to Dec 2009 02041’55’’ 29045’05’’ 1685

11 Rango From May to Dec 2009 805464 9707671 1708

12 Mubumbano From May to Dec 2009 803144 9705574 1808

13 CGIS* From Jan 2006 to Dec 2009 801485 9713790 1726

Temp., RH,

Wind, 1 Gisunzu From Jun to Dec 2009 805956 9701364 1684

Soil moisture, 2 CGIS* From Jan 2006 to Dec 2009 801485 9713790 1726



Solar

radiation

Evaporation 1 Rwasave From May to Dec 2009 806184 9712510 1665

2 Gisunzu From Jun to Dec 2009 807902 9700518 0586

Groundwater

level Piezometers

at Kadahokwa

1 Piezo 1 From Jun to Dec 2009 802224 9708159 1645






7 Piezo 7 From Jul to Dec 2009 802232 9708165 1645





4.6 Data Analysis/Lab Work

Hydro-meteorological data collected during this research have been analysed and the results are shown in the

compilation section bellow (Table 5).

Hydrochemistry analysis was done during this study. Direct measurements have been done in the field (pH, T

and EC parameters) as soon as earlier the water was sampled to avoid oxidization and chemical properties

changes (Table 5). Titration has been conducted for Cl-, Mg2+ and Ca2+ parameters using equipments of PhD

student (Omar) and/or 2 MSc students (Harmen and Rutger). We have done also colorimetry for dissolved

silica (SiO2); S042-and P04

2- (see Table 5). Dissolved silica (SiO2) results helped to investigate runoff processes

and to separate different runoff components. Further measurement to complete anions, cations and isotope

analysis was done at the laboratory of NUR to identify the dominant runoff generation processes (e.g. Didszun

and Uhlenbrook, 2008).

4.7 Preparation/Compilation of Results on Runoff Generation Processes

During this research hydrochemical data and isotope data was collected and compiled in the same file in order

to quantify the contributions of runoff components during different hydrological situations (floods and low

flows) in a meso-scale Migina catchment. River discharges were measured biweekly or monthly at five main



rivers located at different sub-catchments of Migina as explained in previous section. The hydrochemistry

results are compiled in Table 5. Land use and geology have been described in Appendix 1.

Table 5: Hydrochemistry results

a) Monthly rainfall water analysis

Date

Aug-

09 Sep-09

Oct-

09 Nov-09 Dec-09

Parameter

(mg/l) PO42-

SO42-

PO42-

SO42-

PO43-

SO42-

PO42-

SO42-

PO42-

SO42-

Station

Rwasave 0.01 3 0.6 7 0.24 0 0.32 0 0.51 7

Murama 0.82 0 0.34 2 1.62 1 0.97 0 0.32 3

Mubumbano 0.16 3 0.65 0 0.33 0 0.47 0 0.4 0

Kibirizi 0.18 0 1.49 0 0.29 0 0.06 0 0.04 4

Gisunzu 0.22 0 0.4 2 0.05 4 0 0 0.07 7

b) Kansi Stream water events analysis

Kansi River on 4th

Nov 2009

Parameter (mg/l) PO42-

SO42-

SiO2

Hours

1h 0.41 10 3.9

2h 0.1 6 2.2

3h 0.14 5 6.1

4h 0.2 12 5.7

5h 0.31 11 9.4

6h 0.3 8 4.7

7h 0.16 11 4.7

8h 0.33 12 4.5

9h 0.21 10 11.8

10h 0.18 9 5.7

11h 0.18 9 12.5

12h 0.23 9 10

13h 0.16 9 11.7

14h 0.32 10 4.4

15h 0.41 9 15.5

16h 0.47 9 9.9

17h 0.29 10 12.3

18h 0.2 10 11.5

19h 0.16 10 7.8

20h 0.23 10 9.2

21h 0.21 10 11.0



22h 0.22 9 6.4

23h 0.19 11 5.3

24h 0.23 11 4.2 c) Surface water from five main Rivers and 8 springs and Groundwater from 11 piezometers analysis

Site or well ID Date Time Alt Field

pH

Field

EC

Field

Temper

Alkalinity Cl- Ca

2+ Mg

2+ PO4

2- SiO2

m

a.s.l.

uS

cm-1

°C mg l-1 mg

l-1

mg

l-1

mg

l-1

mg l-

1

mg

l-1

Spring Staffgauge

1

2009-

06-06

11:38:00 1614 3.9 76.3 21.3 0.00 0.36 4.00 2.19 0.39 19.60

Staffgauge2_riverC 2009-

06-16

11:20:00 1577 7.9 109.8 20.1 34.16 3.91 9.20 2.67 0.36 11.80

Staffgauge 3 2009-

06-08

9:05:00 1662 6.8 96.2 18.4 21.96 7.10 6.80 4.13 >2.75 14.30


07-10

12:00:00

PM 1618 6.5 94.2 19.8 18.91 2.13 7.4 3.52 1.6 18.50

Staffgauge1_riverA 2009-

07-10

12:27:00

PM 1618 6.4 96.5 20.0 19.52 1.78 7.4 3.28 >2.75 19.90

Staffgauge1_riverB 2009-

07-10

12:45:00

PM 1618 6.7 90.8 19.3 28.06 3.91 7.4 4.25 0.2 9.80


07-10

5:10:00

PM 1577 5.5 110.7 19.5 28.06 5.33 8.8 4.37 >2.75 21.70

Staffgauge2_riverB 2009-

07-10

5:25:00

PM 1577 5.4 117.7 20.0 10.98 5.33 9 4.01 0.6 28.00

Staffgauge2_riverA 2009-

07-10

5:37:00

PM 1577 6.1 107.9 19.3 31.72 4.62 7.8 7.65 0.40 15.20

Piezo1 2009-

06-13

10:30:00 1645 5.3 163.5 26.8 62.22 2.49 19.60 4.37 0.00 36.00

Piezo2 2009-

06-13

11:04:00 1649 5.7 290.0 24.3 128.10 4.97 27.20 3.65 0.28 30.10

Piezo3 2009-

06-13

11:53:00 1643 5.3 190.3 23.7 36.60 5.33 17.20 3.65 0.70 24.80

Piezo4 2009-

06-27

2:17:00

PM 1634 6.8 282.0 22.5 125.70 1.10 8.00 3.20 0.20 26.60

Piezo5 2009-

06-20

2:15:00

PM 1633 5.3 207.0 22.1 84.20 8.50 10.40 1.70 0.59 21.00

Piezo6 2009-

07-04

4:45:00

PM 1627 6.3 193.6 22.1 82.96 3.91 21.20 4.86 >2.75 23.50

Piezo7 2009-

07-04

4:00:00

PM 1645 8.1 254.0 21.8 71.98 2.84 26.80 3.40 2.25 31.20

Piezo8 2009-

07-11

3:16:00

PM 1641 5.9 213.0 23.2 85.4 3.91 18.4 -9999 >2.75 39.30

Piezo9 2009-

07-11

4:12:00

PM 1649 9.4 450.0 26.2 -9999 -9999 -9999 -9999 -9999 -9999

Piezo10 2009-

07-11

4:00:00

PM 1647 7.1 277.0 22.1 133 2.49 32 -9999 0.07 25.30

Spring Sovu 2009-

06-03

14:22:00 1733 3.7 140.5 21.9 1.22 2.13 9.20 4.13 1.79 20.30

Spring

Kamugemge

2009-

06-06

9:30:00 1682 4.1 158.0 21.1 0.00 2.84 8.00 5.10 0.19 37.70

Spring Mjakariba

A

2009-

06-06

9:50:00 1652 4.6 85.3 21.3 0.00 2.49 4.40 2.67 0.10 23.40

Spring Mjakariba B 2009-

06-06

10:10:00 1644 4.8 106.4 21.4 0.00 2.13 6.00 2.67 0.21 17.30

Spring Nabagado 2009-

06-08

9:47:00 1652 4.7 146.7 21.3 0.00 9.23 8.40 4.62 >2.75 35.30

Spring Gahener 2009-

06-08

10:23:00 1671 5.4 132.0 22.1 2.44 7.81 8.00 3.40 >2.75 22.90

Spring Kadahokwa 2009-

06-13

12:33:00 1646 6.3 126.0 23.2 17.08 2.84 9.20 4.37 0.17 20.40

Spring Mayoga 2009-

06-25

11:10:00

AM 1575 6.3 156.1 20.7 12.20 11.72 12.00 4.86 0.30 25.70

Spring Rwasave 2009-

07-21

12:00:00 1665 4.9 137.4 22.3 0.00 -9999 -9999 -9999 -9999 -9999



4.7.1 Hydrochemistry-Surface Water

Figure 5: Relation between EC and water level of River: Staff gauge 1 means Mukura River and staff gauge

2 means Cyihene River at Kansi Bridge.

4.7.2 Spatial and Temporal Variability of Daily Rainfall in Migina Catchment

Figure 6 bellow shows the rainfall obtained from stations installed in Migina catchment with details at

Murama rainfall station which is located a little bit in downstream of Migina catch (see Fig. 3).

Murama: Rainfall in June 2009

02468

10121416182022242628

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Day (-)

Ra

infa

ll (

mm

)

Murama: Rainfall in July 2009

02468

10121416182022242628

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

Day (-)

Ra

infa

ll (

mm

)

Murama: Rainfall in August 2009

02468

10121416182022242628

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

Day (-)

Ra

infa

ll (

mm

)

Murama: Rainfall in September 2009

02468

10121416182022242628

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Day (-)

Ra

infa

ll (

mm

)



Figure 6: Temporal variability of rainfall at Murama station and in the whole Migina catchment

Figure 6 shows two main events: rainy season and dry season in Migina catchment. From the station taken as

sample (Murama rainfall station), the maximum total monthly rainfall was 132 mm in December and the

minimum was 0 mm in July. The total monthly rainfall in June was 4.5 mm, in August was 50 mm, in

September was 57 mm, in October was 92 mm and in November was 123 mm at the same station (Murama).

The average daily rainfall from all stations was 2.14 mm d-1 from June to December 2009 with maximum

daily rainfall of 52.52 mm d-1 which was observed on 18/11/2009 at Mpare rainfall station (see Tab. 4 and Fig.

3) and minimum of 0.0 mm d-1 observed at all stations, especially in the whole month of July.

Murama: Rainfall in October 2009

0.00

5.00

10.00

15.00

20.00

25.00

10/1

/09

10/2

/09

10/3

/09

10/4

/09

10/5

/09

10/6

/09

10/7

/09

10/8

/09

10/9

/09

10/1

0/0

9

10/1

1/0

9

10/1

2/0

9

10/1

3/0

9

10/1

4/0

9

10/1

5/0

9

10/1

6/0

9

10/1

7/0

9

10/1

8/0

9

10/1

9/0

9

10/2

0/0

9

10/2

1/0

9

10/2

2/0

9

10/2

3/0

9

10/2

4/0

9

10/2

5/0

9

10/2

6/0

9

10/2

7/0

9

10/2

8/0

9

10/2

9/0

9

10/3

0/0

9

10/3

1/0

9

Date

Pre

cip

itati

on

[m

m]

Murama: Rainfall in November 2009

0.005.00

10.00

15.0020.0025.0030.00

35.0040.0045.00

11/1

/09

11/2

/09

11/3

/09

11/4

/09

11/5

/09

11/6

/09

11/7

/09

11/8

/09

11/9

/09

11/1

0/0

9

11/1

1/0

9

11/1

2/0

9

11/1

3/0

9

11/1

4/0

9

11/1

5/0

9

11/1

6/0

9

11/1

7/0

9

11/1

8/0

9

11/1

9/0

9

11/2

0/0

9

11/2

1/0

9

11/2

2/0

9

11/2

3/0

9

11/2

4/0

9

11/2

5/0

9

11/2

6/0

9

11/2

7/0

9

11/2

8/0

9

11/2

9/0

9

11/3

0/0

9

Date

Pre

cip

itati

on

[m

m]

Murama: Rainfall in December 2009

0.00

10.00

20.00

30.00

40.00

50.00

12/1

/09

12/2

/09

12/3

/09

12/4

/09

12/5

/09

12/6

/09

12/7

/09

12/8

/09

12/9

/09

12/1

0/0

9

12/1

1/0

9

12/1

2/0

9

12/1

3/0

9

12/1

4/0

9

12/1

5/0

9

12/1

6/0

9

12/1

7/0

9

12/1

8/0

9

12/1

9/0

9

12/2

0/0

9

12/2

1/0

9

12/2

2/0

9

12/2

3/0

9

12/2

4/0

9

12/2

5/0

9

12/2

6/0

9

12/2

7/0

9

12/2

8/0

9

12/2

9/0

9

12/3

0/0

9

12/3

1/0

9

Date

Pre

cip

itati

on

[m

m]

Precipitation in Murama (Jun to Dec 2009)

0.005.00

10.0015.0020.00

25.0030.0035.0040.0045.00

6/1

/09

6/1

1/0

9

6/2

1/0

9

7/1

/09

7/1

1/0

9

7/2

1/0

9

7/3

1/0

9

8/1

0/0

9

8/2

0/0

9

8/3

0/0

9

9/9

/09

9/1

9/0

9

9/2

9/0

9

10/9

/09

10/1

9/0

9

10/2

9/0

9

11/8

/09

11/1

8/0

9

11/2

8/0

9

12/8

/09

12/1

8/0

9

12/2

8/0

9

Date

Pre

cip

itati

on

[m

m]

0.005.00

10.0015.0020.0025.00

30.0035.0040.0045.0050.00

6/1

/09

6/1

1/0

9

6/2

1/0

9

7/1

/09

7/1

1/0

9

7/2

1/0

9

7/3

1/0

9

8/1

0/0

9

8/2

0/0

9

8/3

0/0

9

9/9

/09

9/1

9/0

9

9/2

9/0

9

10/9

/09

10/1

9/0

9

10/2

9/0

9

11/8

/09

11/1

8/0

9

11/2

8/0

9

12/8

/09

12/1

8/0

9

12/2

8/0

9

1/7

/10

Dates

To

tal

dail

y r

ain

fall

(m

m)

Rango Mubumbano Murama Vumbi Mpare Sovu Save B



4.7.3 Generation Rating Curve

In order to establish a relationship between water levels and discharge for the five main rivers in the Migina

catchment, several discharge measurements were carried out at the gauging stations at different water levels.

The picture below shows how river discharge measurements were taken by propeller measurements using the

area-velocity method. The rating curve generated referring to the recommendations of Show (2004) and using

data collected from the Mukura station is shown in Figure 7. Mean daily discharges are shown in Fig. 8 after

considering data from all stations. The discharge was calculated using the average of 2 daily river depth

measurements that are taken at 7am and 5pm. That is why we called it mean daily discharge. However this

can also be replaced by daily discharge.

Photo 1: Mukura River discharge measurement (picture taken by Harmen van den Berg on 06/05/2009) and

Akagera River discharge measurement (Picture taken on 10/08/2009 by Emille (BSc student) when NUR

Civil Engineering students were instructed how to measure discharge using a propeller).

Figure 7: Rating curve generation based on data collected from the Mukura River gauging station installed in

May 2009, fourteen discharge measurements were taken from May to Dec 2009.

Figure 7 shows the rating curve generated from data collected at the Mukura River gauging station located in

the center of Migina catchment (see Fig. 3). Mukura station has been selected as one example sample but the

same method was used for all stations. The daily river discharges are shown in Figure 8.

y = 4.151x6.8843

R² = 0.8975

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1

Dis

ch

arg

e (Q

) in

m3s

-1

Water level (H) in m

Mukura

Power (Mukura)



a) b)

c) d)

e)

Figure 8: Mean daily rainfall and river discharge observed in the Migina catchment (May to Dec 2009) at a)

Mukura; b) Cyihene-Kansi; c) Munyazi-Rwabuye; d) Akagera; and e) Migina stations.

Figure 8 shows that during the period of data collection (May to December 2009) two significant events were

observed on 31 May 2009 and 31 December 2009 which had peak discharges of about 1.9 m3 s-1 and 3.7 m3 s-

1, respectively. High peak flow was also observed at the Migina River (4.8 m3 s-1) on 19 November 2009. The

lowest flow was observed on 8 August 2009 at Munyazi-Rwabuye River (0.0002 m3 s-1) which is located at

upstream of the Migina catchment. The Migina River is located in the downstream of Migina catchment

(outlet of the catchment) and has two main tributaries, Cyihene-Kansi and Akagera Rivers. The Migina River

which is the main river in the Migina catchment was the source of the name of this catchment.

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

5/1/

2009

5/16

/200

9

5/31

/200

9

6/15

/200

9

6/30

/200

9

7/15

/200

9

7/30

/200

9

8/14

/200

9

8/29

/200

9

9/13

/200

9

9/28

/200

9

10/1

3/20

09

10/2

8/20

09

11/1

2/20

09

11/2

7/20

09

12/1

2/20

09

12/2

7/20

09

Date

Mean

dail

y r

ain

fall

(m

m d

-1)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

Dail

y d

isch

arg

e (

m3 s

-1)

Rainfall Discharge at Mukura

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

5/1/

2009

5/16

/200

9

5/31

/200

9

6/15

/200

9

6/30

/200

9

7/15

/200

9

7/30

/200

9

8/14

/200

9

8/29

/200

9

9/13

/200

9

9/28

/200

9

10/1

3/20

09

10/2

8/20

09

11/1

2/20

09

11/2

7/20

09

12/1

2/20

09

12/2

7/20

09

Date

Mean

dail

y r

ain

fall

(m

m d

-1)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Dail

y d

isch

arg

e (

m3 s

-1)

Rainfall Discharge at Cyihene-Kansi

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

5/1/

2009

5/16

/200

9

5/31

/200

9

6/15

/200

9

6/30

/200

9

7/15

/200

9

7/30

/200

9

8/14

/200

9

8/29

/200

9

9/13

/200

9

9/28

/200

9

10/1

3/20

09

10/2

8/20

09

11/1

2/20

09

11/2

7/20

09

12/1

2/20

09

12/2

7/20

09

Date

Mean

dail

y r

ain

fall

(m

m d

-1)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Dail

y d

isch

arg

e (

m3 s

-1)

Rainfall Discharge at Munyazi-Rwabuye

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

5/1/

2009

5/16

/200

9

5/31

/200

9

6/15

/200

9

6/30

/200

9

7/15

/200

9

7/30

/200

9

8/14

/200

9

8/29

/200

9

9/13

/200

9

9/28

/200

9

10/1

3/20

09

10/2

8/20

09

11/1

2/20

09

11/2

7/20

09

12/1

2/20

09

12/2

7/20

09

Date

Mean

dail

y r

ain

fall

(m

m d

-1)

0.11

0.13

0.15

0.17

0.19

0.21

0.23

0.25

Dail

y d

isch

arg

e (

m3 s

-1)

Rainfall Discharge at Akagera

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

5/1/

2009

5/16

/200

9

5/31

/200

9

6/15

/200

9

6/30

/200

9

7/15

/200

9

7/30

/200

9

8/14

/200

9

8/29

/200

9

9/13

/200

9

9/28

/200

9

10/1

3/20

09

10/2

8/20

09

11/1

2/20

09

11/2

7/20

09

12/1

2/20

09

12/2

7/20

09

Date

Mean

dail

y r

ain

fall

(m

m d

-1)

0.0

1.0

2.0

3.0

4.0

5.0

6.0D

ail

y d

isch

arg

e (

m3 s

-1)

Rainfall Discharge at Migina



4.7.4 Hydrochemical Analysis

Figure 9: Hydrochemical parameters at Cyihene-Kansi River during 4 November 2009 event

Hydrochemical tracers may be readily used for hydrograph separation, however hydrochemical tracers are a

result of the processes that occur within the catchment, and therefore the assumption that the water quality of

the fast runoff is equal to that of rainfall could be wrong and may introduce some uncertainty. This may also

be the reason for the increase of some of the hydrochemical parameters at the beginning of the hydrograph.

The effect on the water quality of surface runoff processes will have to be investigated. Additionally, water

flowing through the unsaturated zone, diluting the sub-surface flow concentrations, may also obscure the

outcomes of a two-component hydrograph separation. Further study needs to be conducted regarding

hydrograph separation using isotopes as suggested by Mul et al, 2008.

4.8 Research Report

This report is a final report and is the product (outcome) of NBCBN-RE Rwanda Node hosted in the Institute

of Scientific et Technological Research (IRST) at Butare and will be submitted NBCBN-RE Secretariat based

in Egypt for the results of their support during Rwanda Local Action Research of 2009.

Dissolved Silica (SiO2)

0

2.5

5

7.5

10

12.5

15

17.5

4/10/09

21:36

4/11/09

0:00

4/11/09

2:24

4/11/09

4:48

4/11/09

7:12

4/11/09

9:36

4/11/09

12:00

4/11/09

14:24

4/11/09

16:48

4/11/09

19:12

4/11/09

21:36

4/12/09

0:00

4/12/09

2:24

Time [hrs]

Co

ncetr

ati

on

[m

g/l

]

Sulphate (SO4)

4

6

8

10

12

14

4/10/09

21:36

4/11/09

0:00

4/11/09

2:24

4/11/09

4:48

4/11/09

7:12

4/11/09

9:36

4/11/09

12:00

4/11/09

14:24

4/11/09

16:48

4/11/09

19:12

4/11/09

21:36

4/12/09

0:00

4/12/09

2:24

Time [hrs]

Co

ncetr

ati

on

[m

g/l

]

Phosphate (PO4)

0

0.1

0.2

0.3

0.4

0.5

4/10/09

21:36

4/11/09

0:00

4/11/09

2:24

4/11/09

4:48

4/11/09

7:12

4/11/09

9:36

4/11/09

12:00

4/11/09

14:24

4/11/09

16:48

4/11/09

19:12

4/11/09

21:36

4/12/09

0:00

4/12/09

2:24

Time [hrs]

Co

ncetr

ati

on

[m

g/l

]



5 CONCLUSIONS

Identification and quantification of runoff generation processes studies during floods and droughts events in

Rwandan catchments are very crucial and could help decision makers for water resources planning and

development. During the event of 4 November 2009, dominance of groundwater for flood formation was

demonstrated by hydrochemical parameters (dissolved silica and major anions) where the surface runoff is

dominating the total discharge during floods. This was due to the observed suspended sediment in water

samples. Dissolved silica (SiO2) is a good tracer to distinguish between sub-surface and surface runoff, which

was also found by Wels et al. (1991). This is the method for quantifying the contribution from Migina sub-

catchment that can also be used during flood events to generate a substantial amount of surface runoff. This

local action research will helpful in enhancing the observation capabilities by providing additional data and

variables complementing existing data in Rwanda. Data in Rwanda are in scarce and need to be developed.

The technique used for instrumental setup can be transferred to other catchments in Rwanda for better

understanding of the available water resources and efficient implementation of IWRM plans. One paper from

the part of this research has been published in the Journal of NBCBN (Nile Water Science and Engineering

Journal) in its 3rd volume published in April 2010 on Set up of Hydrological Instrumentation Network in a

Meso-scale Migina catchment and another paper can be produced on Hydrograph separation method using

hydrochemical tracers to define the origin and composition of the runoff during floods.



6 REFERENCES

1. Didszun, J. and Uhlenbrook, S., 2008. Scaling of dominant runoff generation processes: Nested

catchments approach using multiple tracers. WATER RESOURCES RESEARCH, VOL. 44, W02410,

doi:10.1029/2006WR005242.

2. FGDC., F.G.D.C., 1998. National Standard for Spatial Data Accuracy. In: F.G.D.C. FGDC. (Editor),

Geospatial Positioning Accuracy Standards, pp. 3-11.

3. Mazvimavi, D., 2003. Estimation of Flow Characteristic of Ungauged Catchments, Case study in

Zimbabwe. PhD Dissertation Wageningen University, The Netherlands.

4. McGuire, J. K., 2004. Water Residence Time and Runoff Generation in the Western Cascades of Oregon.

A PhD Dissertation, Oregon State University.

5. Mul, L.M., Mutiibwa, K. R., Uhlenbrook, S. and Savenije H.G. H., 2007. Hydrograph separation using

hydrochemical tracers in the Makanya catchment, Tanzania. Physics and Chemistry of the Earth 33

(2008) 151–156

6. Munyaneza, O., Uhlenbrook, S., Maskey, S., Wali, U. G. and Wenninger, J., 2009. Hydrological and

climatic data availability and preliminary analysis in Rwanda. Proceedings of the Hydrology, 10th

International WATERNET/WARFSA/GWP-SA Symposium, Enteebe, Uganda, 28-30 October 2009.

7. Nahayo, D., 2007. Irrigation practices and water conservation opportunities in Migina marshlands.

Proceedings of water resources management session, International 8th WATERNET/WARFSA/GWP-SA

Symposium, Lusaka, Zambia.

8. Oyebande, L., 2001. Water problems in Africa-how can sciences help? Hydrological Sciences Journal,

vol. 46, No. 6, 947-961.

9. Ribolzi, O., Andieux, P., Valles, V., Bouzigues, R., Bariac, T., Voltz, M., 2000. Contribution of

groundwater and overland flows to storm flow generation in a cultivated Mediterranean catchment.

Quantification by natural chemical tracing. Journal of Hydrology 233 (1–4), 241–257.

10. Rodgers, P., Soulsby, C., Waldron, S., and Tetzlaff, D., 2005. Using stable isotope tracers to identify

hydrological flow paths, residence times and landscape controls in a mesoscale catchment. Hydrol. Earth

Syst. Sci. Discuss., 2, 1–35, 2005

11. Savenije H.H.G. and De Laat P.J.M., 2002. Textbook of Hydrology. Delft, The Netherlands.

12. Shaw, M.E., 2004. Hydrology in Practice. Third edition, Department of Civil Engineering, Imperial

College of Science, Technology and Medicine, ISBN 0748744487.

13. Sklash, M. G. and Farvolden, R. N., 1979. The role of groundwater in storm runoff. J. Hydrol. 43, 45–65.

14. Soulsby, C., Rodgers, P., Malcolm, I.A. and Dunn, S., 2008. Nested tracer studies in catchment

hydrology: towards a multiscale understanding of runoff generation and catchment functioning.

University of Aberdeen, AB24 3UF.

15. Tardy, Y., Bustillo, V., Boeglin, J-L, 2004. Geochemistry applied to the watershed survey: hydrograph

separation erosion and soil dynamics: a case study: the basin of the Niger River, Africa. Applied

Geochemistry 19 (4), 469–518.

16. Uhlenbrook, S., McDonnell, J. J., and Leibundgut, C., 2001. Foreword to the special issue: Runoff

generation and Implications for river basin modelling, in Runoff Generation and Implications for River

Basin Modelling. Freiburger Schr. zur Hydrol. 13, edited by C. Leibundgut, S. Uhlenbrook, and J. J.

McDonnell, pp. 1 – 10, Univ. of Freiburg, Germany.

17. Uhlenbrook, S., Frey, M., Leibundgut, C. and Maloszewski, P., 2002. Hydrograph separations in a

mesoscale mountainous basin at event and seasonal timescales. WATER RESOURCES RESEARCH,

VOL. 38, NO. 6, 10.1029/2001WR000938.

18. Uhlenbrook, S., Didszun, J. and Wenninger, J., 2008. Sources areas and mixing of runoff components at

the hillslope scale – a multi-technical approach. In Press, Journal of Hydrological Sciences, 53(4).



19. UNEP, 2005. Connecting poverty and ecosystem services: A series of seven country scoping studies, focus

on Rwanda. United Nations Environmental Programme (UNEP) and the International Institute for

Sustainable Development (IISD), Nairobi, Kenya.

20. Wels, C., Cornett, R.J., Lazerte, B.D., 1991. Hydrograph separation: a comparison of geochemical and

isotopic tracers. Journal of Hydrology 122 (1–4), 253–274.

21. Wenninger, J., Uhlenbrook, S., Lorentz, S. and Leibundgut, C., 2008. Identification of runoff generation

processes using combined hydrometric, tracer and geophysical methods in a headwater catchment in

South Africa. Hydrological Sciences, 53(1).



List of Research Group Members

Name Organization E-mail

Eng. Omar Munyaneza National University of Rwanda [email protected]

Dr. Umaru Garba Wali National University of Rwanda [email protected]

Eng. Christine Uzayisenga RADA (Rwanda Agriculture

Development Authority) [email protected]

Mr. Théoneste Nkurunziza Kigali Institute of Science and

Technology KIST [email protected]

Eng. Ramazani Bizimana Ministry of Agriculture and Animal

Resources [email protected]

Mr. Cyprien Ndayisaba Kigali Institute of Science and

Technology KIST [email protected]

Full Profiles of Research Group Members are available on: The Nile Basin Knowledge Map

http://www.NileBasin-Knowledgemap.com







http://www.nilebasin-knowledgemap.com/

APPENDICIES


Nile Basin Capacity Building Network ( NBCBN ) A-1

Appendix 1: Piezometers installed in Migina catchment, southern of Rwanda

ID

UTM

Zone Easting North Elevation Depth

Rim

height

Rim

height Depth Diver Geological characteristics

[m] [m] [m a.s.l.]

[m

below

rim]

[m above

surface]

[m

above

PVC

tube]

[m below

surface]

[date of

installation]

Piezo 1 35M 802224 9708159 1645 2.95 0.15 0.01 2.80

12/06/2009

13:00

Red colored tropical soil, clayey. Filter in most sandy layer, impermeable clay

below

Piezo 2 35M 802247 9708163 1649 4.60 0.18 0.02 4.42

12/06/2009

13:00

Below top soil a 'gap' after which a sandy/gravel layer is present (290-370cm).

Underneath again a 'gap' and dark colored sandy clay, with real compact clay at

460cm.

Piezo 3 35M 802275 9708165 1643 3.30 0.21 0.06 3.09

12/06/2009

13:00

Brown colored top soil, followed by sand coarsening up to big gravels at 195-230

cm. Sand below and a 'gap' between 290 and 350cm, after which sandy gravel

returns.

Piezo 4 35M 802253 9708164 1634 3.07 0.16 0.07 2.91

20/06/2009

10:00

Brown colored top soil, followed by grey/black clay. From 220 more sandy with

gravels at 255 up to 345 (where black clays start again)

Piezo 5 35M 802282 9708167 1633 1.51 0.05 0.07 1.46

20/06/2009

10:00

Small topsoil layer, followed by brown clay with small gravels. From 60 to 140

cm grey sand coarsening upwards to gravel.

Piezo 6 35M 802211 9708156 1627 4.22 0.12 0.12 4.10

20/06/2009

10:00

Red/brown silty topsoil, followed by weathered rock (red clays with quartz and

pieces of 'rock') up to 380. Underneath more yellow and finer grained 'rotten rock'

with clay at 420

Piezo 7 35M 802232 9708165 1645 3.40 0.07 0.07 3.33

04/07/2009

14:00

Brown/red clayey dry top soil (0-60cm), becoming more wet and darker with

some small quartz grains (<1mm) from 60-120cm, followed by light grey clay

with small quartz grains (<1mm), at 220cm sharp boundary with yellow coloured

clayey gravel (1-5 mm with some 2cm pebbles) up to 330cm (impossible to go

deeper)

Piezo 8 35M 802199 9708217 1641 2.42 0.09 0.03 2.33

04/07/2009

14:00

Brown/red clayey dry top soil (0-60cm), followed by grey/black sticky clay with

organic material (60-160cm) that turns into dry real black 'peat' with a lot of

organic material at 200cm, at 210cm sharp boundary to gravels/coarse sand (1-

5mm) without finer material (='collapsing gravel') that change into real sand

(clayey) at 250cm. Impossible to go deeper than 260cm

Piezo 9 35M 802230 9708232 1649 2.36 0.13 0.02 2.23

04/07/2009

14:00

Very dry, gray, small grained sand (0.1mm), turning into brown/red 'top soil' until

100cm, followed by more clayey, wet and organic rich material with lots of mica,

becoming darker until 200cm. From 200cm-215cm clayey gravels with a big

'stone' at 215.

Piezo 10 35M 802214 9708225 1647 2.76 0.1 0.03 2.66

04/07/2009

14:00

Very dry, brown/red clayey top soil (0-80cm), followed by black sticky clay,

gradual changing into more grey and even white coloured clay. At 240cm grey

coarse sand (0.5mm) starts with some quartz pebbles (1-5mm)

Piezo 11 35M 802190 9708204 1649 1.22 0.1 0.05 1.12

28/07/2009

07:00

Brown/red clayey topsoil that becomes very wet at 20cm; saturated rotten rock

(clayey with quartz particles of 1-5 mm) with boulders up to 10cm (mainly quartz)



ID Land use

Piezo 1 At the knee-edge of agricultural field (downhill), with 'light forest' uphill

Piezo 2 Within an agricultural field (cassava)

Piezo 3 In between road and river, non-cultivated land with shrubs

Piezo 4 At the edge of agricultural field (cassava, beans and sunflowers), near the road

Piezo 5 In the riverbed, with some grasses

Piezo 6 Uphill of piezo 1, non cultivated and clayey with eucalyptus and shrubs

Piezo 7 Within an agricultural field (sweet potatoes)

Piezo 8 Within an bare agricultural field, 20m away from 'light forest' uphill

Piezo 9 At the edge of agricultural field (sweet potatoes) near the river (but 3m above)

Piezo 10 In the middle of a sweet potatoes field

Piezo 11 Bare land, full with shrubs, at the knee-fold of the hill-valley



Appendix 2: Geology description for piezometers installed at Kadahokwa marshland


Nile Basin Capacity Building Network A-4

Group Members Photos

Eng. Ramazani Mr. Cyprien Eng. Omar

Mr. Theoneste and Eng. Omar Eng. Christine Dr. Eng. Wali

Publisher: The Nile Basin Capacity Building Network, 2010

Identification and quantification of runoff generation processes studies during floods and droughts events in Rwandan catchments are very crucial and could help decision makers for water resources planning and development. During the event of 4 November 2009, dominance of groundwater for flood formation was demonstrated by hydrochemical parameters (dissolved silica and major anions) where the surface runoff is dominating the total discharge during floods. This was due to the observed suspended sediment in water samples. Dissolved silica (SiO2) is a good tracer to distinguish between sub-surface and surface runoff, which was also found by Wels et al. (1991). This is the method for quantifying the contribution from Migina sub-catchment that can also be used during flood events to generate a substantial amount of surface runoff.

This local action research was helpful in enhancing the observation capabilities by providing additional data and variables complementing existing data in Rwanda. Data in Rwanda are in scarce and need to be developed. The technique used for instrumental setup can be transferred to other catchments in Rwanda for better understanding of the available water resources and efficient implementation of IWRM plans. This work was conducted in collaboration with a Team group of researchers of NBCBN Rwanda Node members from different research Clusters like Hydropower, Flood Management and Environmental Aspects. Researchers are also from different institutions such as National University of Rwanda (NUR), Kigali Institute of Scientific and Technology KIST), Institute of Scientific and Technological Research (IRST) and Ministry of Agriculture (MINAGRI).

Identification and Quantification of Runoff Generation · 2016-11-02 · Omar Munyaneza Umaru ......

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