CIVE 634 Surface-water Hydrology, Fall 2022 Final Exam: Friday 221216 1530-1730

(a) Please answer only ten (10) questions.
(b) The exam should be typed. Use MS Word if appropriate.
(c) Clarity of presentation and appropriate grammar are required.
(d) Submit your completed exam in PDF format.
(e) Submit your exam to the course email by 17:30 the day of the exam.


  1. (a) What is deep percolation in the context of L'vovich's water balance? (b) What is its average value on a global basis? (c) Why is deep percolation usually neglected in practice?

    (a) Deep percolation is the amount of aquifer percolation which reaches deep enough to avoid the return to the surface waters by way of baseflow.

    (b) On a global basis, an average value of deep percolation is less than 1.5% of precipitation.

    (c) In practice, deep percolation is usually neglected because of the inability to estimate its value with enough precision.

  2. What is the difference between the psychrometric constants used in the Penman and Penman-Monteith evaporation methods?

    Unlike the psychrometric constant γ used in the Penman method, in the Penman-Monteith method the psychrometric constant γ* is also a function of the aerodynamic resistance ra and the stomatal resistance rs, as follows:

    γ* = γ [ 1 + (rs / ra)]

  3. (a) Describe Mockus' explanation of how he arrived at his rainfall-runoff relation. (b) What other sources of variability are implicitly included in the Antecedent Moisture Condition (AMC), other than soil type, land use, and hydrologic condition?

    (a) Mockus said that he arrived at the equation (P- Q) / S = Q / P one evening after dinner, seeing that it fitted the data very well, and after having tried many other alternative relations.

    (b) Other sources of variability implicitly included in the concept of AMC are: (i) spatial variability of storm and watershed properties; (ii) temporal variability of the storm, i.e., changes in rainfall intensity within the storm; and (iii) quality of the measured data.

  4. (a) In catchment flow, what is the difference between: (a) superconcentrated and concentrated flow? (b) concentrated and subconcentrated flow? Explain the differences in terms of the shape of the runoff hydrograph and the associated peak flow.

    (a) Superconcentrated flow features a flat hydrograph peak, while concentrated flow features a singular value of peak flow. The peak flow for both superconcentrated and concentrated catchment flow hydrographs is: Qp = Ie A, in which Ie = effective rainfall intensity, and A = catchment area.

    (a) Concentrated flow features a singular value of peak flow, equal to Qp = Ie A, while subconcentrated catchment flow features a flat peak, of value which is less than the maximum peak flow for full concentration. Effectively, the flow did not concentrate, i.e., attain its maximum possible value, because the rainfall duration is less than the time of concentration.

  5. (a) Explain how a tropical rainforest such as the Amazon is better able to recycle rainfall than a semiarid forest. (b) What demonstrable fact reveals that humid regions recyle moisture more effectively than arid regions?

    (a) Tropical rainforests feature a characteristically low albedo, tipically around 7%, and therefore, are subject to substantial amounts of cooling, by thermal lifting, of the lower atmosphere. This effect results in a relatively high recycling coefficient Kc of about 0.3.

    (b) The ratio of atmospheric moisture content between humid to arid regions is low, approximately 3. However, the ratio of mean annual precipitation between humid and arid regions may be quite large, often more than 100. This marked difference between atmospheric moisture content and precipitation flux is due to the greater precipitation recycling capacity prevalent in humid regions.

  6. (a) What is the value of the (mean) annual global terrestrial precipitation Pagt used in the conceptual model of drougnt intensity-duration-frequency across the climatic spectrum? (b) How is it determined?

    (a) The value is 800 mm.

    (b) A mean value of global terrestrial atmospheric moisture is estimated to be 25 mm, the average of a range of 2 mm (dry) to 50 mm (wet). The atmospheric moisture recycles every 11 days on the average, for a total of 33 cycles per year. The total average global terrestrial flux (precipitation) is: 25 × 33 = 825 mm. A round number of Pagt = 800 mm may be adopted for convenience.

  7. Why is the determination of regional aquifer parameters using baseflow recession data likely to be more accurate than conventional hydrogeologic determinations based of pumping tests?

    Determinations of aquifer parameters based on baseflow recession data comprise the entire aquifer, providing values which represent the totality of the aquifer. On the other hand, determinations based on pumping tests are perforce of local nature.

  8. (a) When using a linear reservoir in unit hydrograph determinations, why is the Courant number C limited to values less than or equal to 2? (b) Why does C = 2 effectively result in a hydrograph resembling the rational method?

    (a) For values of C > 2, the temporal interval Δt exceeds twice the time of storage K, resulting in negative diffusion, i.e., a numerical amplification effect, which renders the model unstable.

    (b) For C = 2, the outlow hydrograph of the linear reservoir has zero runoff diffusion; thus, it has the shape of an isosceles triangle, featuring equal rising and receding limbs. This hydrograph shape mimics the outflow hydrograph of the rational method, which ostensibly features only runoff convection, with zero runoff diffusion.

  9. What condition is necessary for the Muskingum-Cunge (M-C) method to improve on the classical Muskingum method? (b) What value of Courant number C assures numerical accuracy in the M-C method? Why?

    (a) The Muskingum-Cunge method will improve on the Muskingum method when the discrete geometric cross-sectional data on which to base the computation of the routing parameters is truly representative of the channel reach under consideration.

    (b) For Courant number C = 1, the Muskingum-Cunge method assures numerical accuracy and grid independence. This is due to the fact that for C = 1, the method minimizes numerical dispersion (third-order error).

  10. What is the reason for the documented increase in the number of glacial lakes in the White Range of Peru in the past 50 years?

    In the past 50 years, the documented increase in the number of glacial lakes in the White Range has been due to the global-climate-change induced increase in glacial melt in the presence of glacial till (moraine) geomorphology. The conjunction of glacial melt and glacial till is conducive to the formation of glacial lakes.


  11. Why do the Muskingum and Muskingum-Cunge methods become unstable and break down for values of X > 0.5?

    Because according to Cunge's portrait analysis, in the range X > 0.5, the R1 amplitude portrait becomes greater than 1 for all values of Courant number and spatial resolution. This fact produces a strong tendency for numerical instability.

  12. Why is the general dimensionless unit hydrograph (GDUH) better suited for unit hydrograph analysis than the conventional NRCS and Snyder unit hydrographs?

    Because unlike the NRCS and Snyder models, which are empirically based on regional data, the GDUH has a distinct conceptual basis and, it is, therefore, of global applicability.


  13. (Extra bonus question) (a) What is runoff diffusion in the context of modeling surface-water hydrology? (b) What physical parameter quantifies runoff diffusion? (c) How has this parameter evolved in the past sixty years of research in the modeling of surface-water hydrology?

    (a) Runoff diffusion entails the determination (calculation) of wave diffusion in surface-water flow in open channels and catchments.

    (b) The amount of runoff diffusion is quantified by the hydraulic diffusivity of Hayami (1951), which states that the diffusion coefficient is: ν = qo / (2So), in which qo = unit-width discharge, and So = bottom slope.

    (c) Recent research has shown that a more complete theoretical expression for hydraulic diffuxivity is: ν = ( 1 - V2 ) qo / (2So), wherein V = Vedernikov number.


221208 10:00