UGC NET Environmental & Agro-ecosystem Modelling: practice questions

UGC NET — Environmental Sciences (subject code 89) · India · National Testing Agency for the University Grants Commission

Original practice questions written to the published syllabus · not past papers

10worked here, free

70written to this exam in this subject

10syllabus units

What this subject covers

Building and using models of crops, soils, catchments and ecosystems: model types, calibration and validation, and the main open models used in sustainability research.

In the exams: UGC NET Unit 9 (environmental modelling); ICAR AICE subjects 60 and 71; PhD research

Systems analysis and model types
Mass-balance and box models
Population and ecosystem models
Crop simulation models
Soil carbon and nitrogen models
Catchment water-quality models
Ecosystem service models
Calibration, validation and sensitivity analysis
Uncertainty propagation and ensemble modelling
Coupling models with remote sensing and climate projections

Where the 70 questions fall

How our questions for UGC NET spread across the units of Environmental & Agro-ecosystem Modelling. Difficulty: 17 easy, 38 medium, 15 hard.

Population and ecosystem models	9
Calibration, validation and sensitivity analysis	9
Uncertainty propagation and ensemble modelling	9
Coupling models with remote sensing and climate projections	9
Systems analysis and model types	8
Soil carbon and nitrogen models	8
Ecosystem service models	8
Catchment water-quality models	5
Crop simulation models	3
Mass-balance and box models	2

10 practice questions, worked

Choose an answer, then open the working. Each explanation says why the right answer is right and why the others are not.

1 · Systems analysis and model types · medium

A catchment model divides the basin into sub-basins and hydrological response units (combinations of land use, soil and slope) without tracking their exact positions. It is:

Lumped
Fully distributed
Empirical and static
Semi-distributed

Answer and working

D. Semi-distributed

Hydrological response units group similar areas within sub-basins; a lumped model treats the whole basin as one unit, and a fully distributed model computes every grid cell.

Further reading: See the manual sources: Jørgensen and Fath; Wainwright and Mulligan; Chapra; Beven; Saltelli et al.; Moriasi et al. 2007; IPCC 2006 Vol. 1 Ch. 3

2 · Systems analysis and model types · hard

Why is a mechanistic model usually preferred over an empirical one for projecting crop yields under carbon dioxide concentrations never observed in the past?

It always fits historical yields more closely than any statistical model can
It needs fewer input data and parameters than any empirical regression model
It represents causal processes, so it can extrapolate beyond the observed data range more defensibly
It produces no uncertainty because its equations are derived from physical laws

Answer and working

C. It represents causal processes, so it can extrapolate beyond the observed data range more defensibly

Empirical relations hold only within the data used to fit them. Mechanistic models are not necessarily more accurate historically and need more data; their parameters are uncertain too.

Further reading: See the manual sources: Jørgensen and Fath; Wainwright and Mulligan; Chapra; Beven; Saltelli et al.; Moriasi et al. 2007; IPCC 2006 Vol. 1 Ch. 3

3 · Population and ecosystem models · medium

A fish stock follows logistic growth with r = 0.4 per year and K = 20,000 t. What is the maximum sustainable yield in this simple model?

8,000 t per year
10,000 t per year
2,000 t per year
4,000 t per year

Answer and working

C. 2,000 t per year

MSY = rK/4 = 0.4 × 20,000 / 4 = 2,000 t, taken at N = K/2. 8,000 = rK omits the 1/4; 10,000 is K/2, the stock size, not the yield.

Further reading: See the manual sources: Jørgensen and Fath; Wainwright and Mulligan; Chapra; Beven; Saltelli et al.; Moriasi et al. 2007; IPCC 2006 Vol. 1 Ch. 3

4 · Population and ecosystem models · medium

The dominant eigenvalue of a Leslie matrix for a threatened species is 0.94. This means the population is:

Declining by about 6% per time step in the long run
Growing by about 94% per time step in the long run
Stable, because the eigenvalue is close to one
Growing by about 6% per time step in the long run

Answer and working

A. Declining by about 6% per time step in the long run

λ < 1 means decline; λ = 0.94 implies a 6% loss per step once the stable age distribution is reached.

Further reading: See the manual sources: Jørgensen and Fath; Wainwright and Mulligan; Chapra; Beven; Saltelli et al.; Moriasi et al. 2007; IPCC 2006 Vol. 1 Ch. 3

5 · Soil carbon and nitrogen models · medium

Decomposition has Q₁₀ = 2. By what factor does the rate change when temperature rises by 5 °C?

1.41
1.00
2.00
1.50

Answer and working

A. 1.41

Factor = Q₁₀^(ΔT/10) = 2^0.5 = 1.41. 2.00 applies to a 10 °C rise; 1.50 assumes a linear response.

Further reading: See the manual sources: Jørgensen and Fath; Wainwright and Mulligan; Chapra; Beven; Saltelli et al.; Moriasi et al. 2007; IPCC 2006 Vol. 1 Ch. 3

6 · Soil carbon and nitrogen models · easy

In IPCC inventory guidance, a Tier 3 method for soil carbon uses:

Global default stock-change factors applied to reference soil carbon stocks
Process models or measurement systems with fine-resolution activity data
Country-specific emission factors that replace the global default values
Expert judgement in place of activity data where models are unavailable

Answer and working

B. Process models or measurement systems with fine-resolution activity data

Tier 1 uses defaults, Tier 2 country-specific factors and Tier 3 models or measurement-based systems verified against data.

Further reading: See the manual sources: Jørgensen and Fath; Wainwright and Mulligan; Chapra; Beven; Saltelli et al.; Moriasi et al. 2007; IPCC 2006 Vol. 1 Ch. 3

7 · Calibration, validation and sensitivity analysis · medium

Which method is designed for screening many parameters with relatively few model runs?

Morris elementary effects
Sobol variance decomposition
Full factorial Monte Carlo
Markov chain Monte Carlo

Answer and working

A. Morris elementary effects

Morris ranks parameters by the mean and spread of elementary effects with few runs; Sobol and MCMC need many more.

Further reading: See the manual sources: Jørgensen and Fath; Wainwright and Mulligan; Chapra; Beven; Saltelli et al.; Moriasi et al. 2007; IPCC 2006 Vol. 1 Ch. 3

8 · Calibration, validation and sensitivity analysis · easy

Calibration of a model means:

Testing the model against data that were not used to set the parameters
Tuning uncertain parameters to match observations
Checking that the computer code correctly implements the equations
Changing the model structure until it reproduces any desired output

Answer and working

B. Tuning uncertain parameters to match observations

Validation uses independent data; verification checks code; arbitrary structural changes are not calibration.

Further reading: See the manual sources: Jørgensen and Fath; Wainwright and Mulligan; Chapra; Beven; Saltelli et al.; Moriasi et al. 2007; IPCC 2006 Vol. 1 Ch. 3

9 · Uncertainty propagation and ensemble modelling · medium

Which ensemble type samples structural uncertainty?

Multi-model ensemble of different models
Initial-condition ensemble of one model
Repeated runs of one model with the same inputs
Perturbed-input ensemble of rainfall only

Answer and working

A. Multi-model ensemble of different models

Different models embody different process representations; initial-condition ensembles sample internal variability within one structure.

Further reading: See the manual sources: Jørgensen and Fath; Wainwright and Mulligan; Chapra; Beven; Saltelli et al.; Moriasi et al. 2007; IPCC 2006 Vol. 1 Ch. 3

10 · Coupling models with remote sensing and climate projections · hard

Assimilating 10 km satellite soil moisture directly into a field-scale crop model without adjustment is problematic because:

The satellite measures the top few centimetres averaged over many fields, a scale and depth mismatch
Satellite soil moisture is measured in different units that cannot be converted
Crop models cannot accept any external data while the simulation is running
Microwave soil moisture is unaffected by rainfall and so carries no information

Answer and working

A. The satellite measures the top few centimetres averaged over many fields, a scale and depth mismatch

Observation operators and bias correction are needed to relate a coarse surface retrieval to a field root-zone state.

Further reading: See the manual sources: Jørgensen and Fath; Wainwright and Mulligan; Chapra; Beven; Saltelli et al.; Moriasi et al. 2007; IPCC 2006 Vol. 1 Ch. 3

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