Course image IDR 3121: Watershed Management (20 credits)
Trimester 1

Welcome message 

This course is designed to equip you with the knowledge and skills needed to tackle the pressing challenges of water resource management in today's world. Through engaging lectures, group discussions, and hands-on projects, you will explore key concepts such as sustainable water practices, conservation strategies, and the impact of climate change on our water systems. The module consists of three key units: principles of land management, water harvesting techniques and  design of water storage structures.

Aim of the module

This module's objective is to provide students with a deeper understanding of watershed management, including catchment area management, water harvesting methods, and the design of buildings for both water harvesting and water storage

Learning outcomes 

Having successfully completed the module, students should be able to demonstrate knowledge and understanding of:

1. To learn about watershed degradation, land management, water harvesting methods, the design of water storage structures, and the planning, execution, and selection of these methods in this module.

2. To construct water storage structures, choose appropriate water harvesting methods, and create a strategy for managing a watershed. They will also be able to show these skills to farmers.

3. To communicate effectively, show that they are interested in managing watersheds, demonstrate that they are proficient in water harvesting, offer solutions, and present instances analytically.

4. To define and map watersheds, create land development reports, counsel stakeholders on development plans, and demonstrate field water harvesting methods after finishing the program.

Learning   and Teaching Strategies 

Development of the learning outcomes is promoted through the following teaching and learning methods:

1. Lectures are used throughout the program in order to impart essential knowledge relating to the above aims and outcomes.

2.  A student-centred approach is taken whereby most of the activities will be done by the students, facilitated by lecturers.

3. Independent study is necessary to both assimilate and further clarify material obtained from lectures, preparation for seminars, preparation for written assessments, and the broader development of knowledge of the field of study.

4 . Some exercises will be conducted to ensure group work. Group work is an important part of some modules in the program, and it provides an opportunity for teamwork participation, the development of interpersonal skills, and the reconciliation of different points of view.

5. Practical work to enhance the student’s programming productivity and skill development

Indicative Resources

Waterharvest Techniques, Principles of land Management, Groundwater water storage, storage Structures

Teaching Team

Mr. Valens Nkundabashaka , Email: v.nkundabashaka@ur.ac.rw, Tel: +250787843694

Mrs. Uwanyirigira Jeanine, Email: kanyirigira@gmail.com, ,Tel: +250788900817

Mrs. Ave Marie Therese, ,avemarietherese@gmail.com, Tel: +250784377071


Course image IDR3122 Extension and Communication
Trimester 1

Welcome Message

Dear Students,

You are welcome to the module IDR3122 Communication and Extension

Course image Statistics IDR3123
Trimester 1

Welcome Message

Dear Students,

You are welcome to the module IDR3123 Statistics

 

Aim of the module

This module teaches the Statistics and Introduction to research methodology. At the end of this module students would have clear understanding of statistics and research methodology and their applications in research and other domains of agriculture.

 

Module outline

 Module is comprised of two components as follows:

 1. Introduction to research methodology (5 Credits)

 2. Applied statistics  (5 Credits)

 

The module will offer a clear understanding and application of Statistics and Introduction to research methodology.

 

Assessment methods

The main principles underlying assessment are that understanding, interpretation and application are the crucial issues.  The assessment will be through

  • Continuous Assessment Test (CAT)  and Assignments,
  • Practical exercises,
  • Debates,
  • Seminar,
  • Group discussion.
  • Viva voce
  • Final written examination

Basically, assessment will balance the different aspects of knowledge, skills and attitude through above mentioned points.

 

Learning outcomes

A.    Knowledge and understanding

Having successfully completed the module, students should be able to demonstrate knowledge and understanding of:

A1. Descriptive and inferential statistics.

A2. The probabilities applied to Hydrology, irrigation structure designs and Irrigation water management.

A3. The Discrete random variables: Estimation random variables.

A4. The linear and logistic regression.

   B.   Cognitive/intellectual skills/application of knowledge

Having successfully completed the module, students should be able to:

B1. Apply descriptive and inference statistical in the economic and management context

      B2. Use the statistics in the random research and analyze of quantitative data.

C.  Communication/ict/numeracy/analytic techniques/practical skills

Having successfully completed the module, students should be able to:

C1. Analyze and interpret the quantitative and qualitative data.

C2. Formulate hypotheses and its verification in the economic and management context.

C3. Calculate simple and multiple regressions in the context of research.

    D   General transferable  skills

Having successfully completed the module, students should be able to:

D1. Use statistics in the every days life.

D2. Calculate different descriptive and inference statistics in the economics and management context.

D3. Verify hypothesis in the research by calculating different statistics.

 

Facilitators

Mr. Ruhumuliza Joseph – Introduction to research methodology

Email E-mail: ruhumulizason@yahoo.co.uk    Mobile: +250-0788569467

Mr. Niyigena Jean de Dieu - Applied statistics

 Email: jniyigena@aims.ac.tz   Mobile: +250-786258252

 

References

-       N. LARSEN and M. MARX (1986). An Introduction to Mathematical Statistics and Its Applications. Second Edition. Prentice-Hall, Englewood Cliffs, New Jersey, page 295.

-       W. PEARSON (1998), “Empirical statistical estimates for sequence similarity searches.” J. Mol. Biol. 276:71-84.

-       W. DAVID (1998), Introductory statistics: Concepts, models and application. Missouri University.

-       HARRISON A. (2000), Introduction to statistics. Cameron.

-       DAVIES G. R. & YODER D. (1937), Business statistics. New York: John Willey.

-       LIKERT R. (1932), A Technique for the measurement of attitudes. Archives of psychology. N0. 140.

-       Anirban DasGupta, (2010). Fundamentals of Probability: A First Course. Springer.

-       Douglas C. Montgomery and George C. Runger, (2003). Applied Statistics and Probability for Engineers. John Wiley & Son.

-       George Casella and Roger L. Berger, (2002). Statistical Inference 2nd Edition. Duxbury.

-       Hwei Hsu, (1997). Probability, Random Variables and Random Processes.  Schaum´s Outline Series.

-       Ilja N. Bronshtein, Konstantin A. Semendyayev, Gerhard Musiol and Heiner Muehlig, (2004). Handbook of Mathematics 4th Edition (Chapter 16). Springer-Verlag.

-       Merran Evans, Nicholas Hastings, Brian Peacock. Statistical Distributions 3rd Edition. John Wiley & Sons.

-       Mood A. M., (1974). Introduction to the Theory of Statistics. Mc Graw Hill.

-       Murray R. Spiegel, John Schiller and R. Alu Srinivasan, (2001). Probability and Statistics. Schaum´s Easy Outline.

-       Murray R. Spiegel and Larry J. Stephens, (2008). Statistics 4th Edition. Schaum´s Outline Series.

-       Murray R. Spiegel, John Schiller and R. Alu Srinivasan, (2009). Probability and Statistics 3rd Edition. Schaum´s Outline Series.

-       Norman L. Johnson, Samuel Kotz and Adrienne W. Kemp, (1992). Univariate Discrete Distributions 2nd Edition. John Wiley & Son.

-       Norman L. Johnson, Samuel Kotz and N. Balakrishnan. Continuous Univariate Distributions Vol. 1.

-       Norman L. Johnson, Samuel Kotz and N. Balakrishnan, (1995). Continuous Univariate Distributions Vol. 2. John Wiley & Son.

-       Poduri S.R.S. Rao, (2000). Sampling Methodologies with Applications. Chapman & Hall.

-       Sampath S., (2001). Sampling Theory and Methods. Norosa Publishing House, New Delhi.

-       Stephen Bernstein and Ruth Bernstein, (1999). Elements of Statistics I. Descriptive Statistics and Probability. Schaum´s Outline Series.

-       Stephen Bernstein and Ruth Bernstein, (1999). Elements of Statistics II. Inferential Statistics. Schaum´s Outline Series.

-       William G. Cochran, (1977). Sampling Techniques. John Wiley & Sons.

-       William W. Hines, Douglas C. Montgomery, David M. Goldsman and Connie M.

-       Borror, (2003). Probability and Statistics in Engineering. John Wiley & Son.

Websites for further reference

CAVM, Busogo and Nyagatare library collections

 

Course image Watershed management
Trimester 1

The  watershed management module includes land management, water harvesting techniques and design of water harvesting structures including water storage structures. The module gives an insight of integrated watershed management by judicious use of available land as per its capability, harvesting water resource by adopting appropriate techniques and designing water storage structures. The subject of water harvesting techniques is being given in details