The role of meteorological and hydrological uncertainties in the performance of optimal water allocation approaches

S. Anvari, Joong Hoon Kim, M. Moghaddasi

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Efficient reservoir operation and irrigation scheduling are important for the mitigation of water shortages in Iran. For more accuracy, the hydrological and meteorological uncertainties associated with reservoirs and farm levels should be considered. The major contribution of the current paper is to evaluate the uncertainties of evapotranspiration (ET) and inflow, and the issue of constant/variable agricultural demand (CAD/VAD) for optimal irrigation scheduling and reservoir operation. Some optimization approaches were employed and compared during a drought episode in the Zayandeh-Rud agricultural system. Approaches include: (i) DP-CAD: dynamic programming (DP), considering CAD and no inflow uncertainty; (ii) SSDP-CAD: sampling stochastic DP (SSDP) with CAD and inflow uncertainty; (iii) LP-NLP-VAD: implementing linear (LP) and non-linear programming (NLP) modelling for crop types, growing stages, and irrigation systems under deterministic conditions; (iv) SDP-NLP-VAD: similar to the third approach, but considers ET uncertainties using a stochastic DP (SDP) rather than an LP model, and uses stochastic crop yield functions in the NLP formulation. DP-CAD and SDP-NLP-VAD were the simplest and most complicated modelling processes, respectively. SDP-NLP-VAD was the most time-consuming to reach a steady state and a global optimal solution. The LP-NLP-VAD and SDP-NLP-VAD approaches, which account for variability in crop water requirements, conservatively consider water shortages and reservoir release.

Original languageEnglish
Pages (from-to)342-353
Number of pages12
JournalIrrigation and Drainage
Volume68
Issue number2
DOIs
Publication statusPublished - 2019 Apr 1

Fingerprint

water allocation
dynamic programming
computer aided design
uncertainty
water shortages
irrigation scheduling
inflow
evapotranspiration
water
water reservoirs
irrigation
water requirement
crops
crop
irrigation systems
sampling
crop yield
irrigation system
Iran
farming system

Keywords

  • DP
  • LP
  • NLP
  • optimization
  • SDP
  • SSDP
  • water requirement
  • yield function
  • Zayandeh-Rud

ASJC Scopus subject areas

  • Agronomy and Crop Science
  • Soil Science

Cite this

The role of meteorological and hydrological uncertainties in the performance of optimal water allocation approaches. / Anvari, S.; Kim, Joong Hoon; Moghaddasi, M.

In: Irrigation and Drainage, Vol. 68, No. 2, 01.04.2019, p. 342-353.

Research output: Contribution to journalArticle

@article{57f6aa2926c64091b5f8d20ef546122f,
title = "The role of meteorological and hydrological uncertainties in the performance of optimal water allocation approaches",
abstract = "Efficient reservoir operation and irrigation scheduling are important for the mitigation of water shortages in Iran. For more accuracy, the hydrological and meteorological uncertainties associated with reservoirs and farm levels should be considered. The major contribution of the current paper is to evaluate the uncertainties of evapotranspiration (ET) and inflow, and the issue of constant/variable agricultural demand (CAD/VAD) for optimal irrigation scheduling and reservoir operation. Some optimization approaches were employed and compared during a drought episode in the Zayandeh-Rud agricultural system. Approaches include: (i) DP-CAD: dynamic programming (DP), considering CAD and no inflow uncertainty; (ii) SSDP-CAD: sampling stochastic DP (SSDP) with CAD and inflow uncertainty; (iii) LP-NLP-VAD: implementing linear (LP) and non-linear programming (NLP) modelling for crop types, growing stages, and irrigation systems under deterministic conditions; (iv) SDP-NLP-VAD: similar to the third approach, but considers ET uncertainties using a stochastic DP (SDP) rather than an LP model, and uses stochastic crop yield functions in the NLP formulation. DP-CAD and SDP-NLP-VAD were the simplest and most complicated modelling processes, respectively. SDP-NLP-VAD was the most time-consuming to reach a steady state and a global optimal solution. The LP-NLP-VAD and SDP-NLP-VAD approaches, which account for variability in crop water requirements, conservatively consider water shortages and reservoir release.",
keywords = "DP, LP, NLP, optimization, SDP, SSDP, water requirement, yield function, Zayandeh-Rud",
author = "S. Anvari and Kim, {Joong Hoon} and M. Moghaddasi",
year = "2019",
month = "4",
day = "1",
doi = "10.1002/ird.2315",
language = "English",
volume = "68",
pages = "342--353",
journal = "Irrigation and Drainage",
issn = "1531-0353",
publisher = "John Wiley and Sons Ltd",
number = "2",

}

TY - JOUR

T1 - The role of meteorological and hydrological uncertainties in the performance of optimal water allocation approaches

AU - Anvari, S.

AU - Kim, Joong Hoon

AU - Moghaddasi, M.

PY - 2019/4/1

Y1 - 2019/4/1

N2 - Efficient reservoir operation and irrigation scheduling are important for the mitigation of water shortages in Iran. For more accuracy, the hydrological and meteorological uncertainties associated with reservoirs and farm levels should be considered. The major contribution of the current paper is to evaluate the uncertainties of evapotranspiration (ET) and inflow, and the issue of constant/variable agricultural demand (CAD/VAD) for optimal irrigation scheduling and reservoir operation. Some optimization approaches were employed and compared during a drought episode in the Zayandeh-Rud agricultural system. Approaches include: (i) DP-CAD: dynamic programming (DP), considering CAD and no inflow uncertainty; (ii) SSDP-CAD: sampling stochastic DP (SSDP) with CAD and inflow uncertainty; (iii) LP-NLP-VAD: implementing linear (LP) and non-linear programming (NLP) modelling for crop types, growing stages, and irrigation systems under deterministic conditions; (iv) SDP-NLP-VAD: similar to the third approach, but considers ET uncertainties using a stochastic DP (SDP) rather than an LP model, and uses stochastic crop yield functions in the NLP formulation. DP-CAD and SDP-NLP-VAD were the simplest and most complicated modelling processes, respectively. SDP-NLP-VAD was the most time-consuming to reach a steady state and a global optimal solution. The LP-NLP-VAD and SDP-NLP-VAD approaches, which account for variability in crop water requirements, conservatively consider water shortages and reservoir release.

AB - Efficient reservoir operation and irrigation scheduling are important for the mitigation of water shortages in Iran. For more accuracy, the hydrological and meteorological uncertainties associated with reservoirs and farm levels should be considered. The major contribution of the current paper is to evaluate the uncertainties of evapotranspiration (ET) and inflow, and the issue of constant/variable agricultural demand (CAD/VAD) for optimal irrigation scheduling and reservoir operation. Some optimization approaches were employed and compared during a drought episode in the Zayandeh-Rud agricultural system. Approaches include: (i) DP-CAD: dynamic programming (DP), considering CAD and no inflow uncertainty; (ii) SSDP-CAD: sampling stochastic DP (SSDP) with CAD and inflow uncertainty; (iii) LP-NLP-VAD: implementing linear (LP) and non-linear programming (NLP) modelling for crop types, growing stages, and irrigation systems under deterministic conditions; (iv) SDP-NLP-VAD: similar to the third approach, but considers ET uncertainties using a stochastic DP (SDP) rather than an LP model, and uses stochastic crop yield functions in the NLP formulation. DP-CAD and SDP-NLP-VAD were the simplest and most complicated modelling processes, respectively. SDP-NLP-VAD was the most time-consuming to reach a steady state and a global optimal solution. The LP-NLP-VAD and SDP-NLP-VAD approaches, which account for variability in crop water requirements, conservatively consider water shortages and reservoir release.

KW - DP

KW - LP

KW - NLP

KW - optimization

KW - SDP

KW - SSDP

KW - water requirement

KW - yield function

KW - Zayandeh-Rud

UR - http://www.scopus.com/inward/record.url?scp=85059945658&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85059945658&partnerID=8YFLogxK

U2 - 10.1002/ird.2315

DO - 10.1002/ird.2315

M3 - Article

AN - SCOPUS:85059945658

VL - 68

SP - 342

EP - 353

JO - Irrigation and Drainage

JF - Irrigation and Drainage

SN - 1531-0353

IS - 2

ER -