Frequency of occurrence of flow regime components: a hydrology-based approach for environmental flow assessments and water allocation for the environment

Abstract. As the water requirement for food production and other human needs grows, quantification of environmental flow requirements (EFRs) is necessary to assess the amount of water needed to sustain freshwater ecosystems. EFRs are the result of the quantification of water necessary to sustain the riverine ecosystem, which is calculated from the mean of an environmental flow (EF) method. In this study, five EF methods for calculating EFRs were compared with 11 case studies of locally assessed EFRs. We used three existing methods (Smakhtin, Tennant, and Tessmann) and two newly developed methods (the variable monthly flow method (VMF) and the Q90_Q50 method). All methods were compared globally and validated at local scales while mimicking the natural flow regime. The VMF and the Tessmann methods use algorithms to classify the flow regime into high, intermediate, and low-flow months and they take into account intra-annual variability by allocating EFRs with a percentage of mean monthly flow (MMF). The Q90_Q50 method allocates annual flow quantiles (Q90 and Q50) depending on the flow season. The results showed that, on average, 37% of annual discharge was required to sustain environmental flow requirement. More water is needed for environmental flows during low-flow periods (46–71% of average low-flows) compared to high-flow periods (17–45% of average high-flows). Environmental flow requirements estimates from the Tennant, Q90_Q50, and Smakhtin methods were higher than the locally calculated EFRs for river systems with relatively stable flows and were lower than the locally calculated EFRs for rivers with variable flows. The VMF and Tessmann methods showed the highest correlation with the locally calculated EFRs (R2=0.91). The main difference between the Tessmann and VMF methods is that the Tessmann method allocates all water to EFRs in low-flow periods while the VMF method allocates 60% of the flow in low-flow periods. Thus, other water sectors such as irrigation can withdraw up to 40% of the flow during the low-flow season and freshwater ecosystems can still be kept in reasonable ecological condition. The global applicability of the five methods was tested using the global vegetation and the Lund-Potsdam-Jena managed land (LPJmL) hydrological model. The calculated global annual EFRs for fair ecological conditions represent between 25 and 46% of mean annual flow (MAF). Variable flow regimes, such as the Nile, have lower EFRs (ranging from 12 to 48% of MAF) than stable tropical regimes such as the Amazon (which has EFRs ranging from 30 to 67% of MAF).

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Regionalization of natural flow regime: application to environmental flow optimization at ungauged sites

River Research and Applications ◽

10.1002/rra.1207 ◽

2008 ◽

Vol 25 (9) ◽

pp. 1071-1089 ◽

Cited By ~ 14

Author(s):

Jenq-Tzong Shiau ◽

Fu-Chun Wu

Keyword(s):

Flow Regime ◽

Environmental Flow ◽

Flow Optimization ◽

Natural Flow Regime ◽

Ungauged Sites ◽

Natural Flow

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Simulation–optimization model for optimum water allocation between environmental and agricultural demand using a coupled WEAP-MODFLOW model: Application in Miyandoab plain, Urmia basin, Iran

10.5194/egusphere-egu2020-3143 ◽

2020 ◽

Author(s):

Amirhossein Dehghanipour ◽

Gerrit Schoups ◽

Bagher Zahabiyoun

Keyword(s):

Optimization Model ◽

Water Allocation ◽

Deficit Irrigation ◽

Simulation Optimization ◽

Environmental Flow ◽

Objective Functions ◽

Trade Off ◽

Agricultural Demand ◽

Hydrologic Module ◽

Optimum Water

<p>In this study, we developed a simulation-optimization model for optimum water allocation to meet environmental flow requirements and agricultural demand. The simulation model consists of three modules: a hydrologic module, an agronomic module, and an economic module. The hydrologic module is based on a dynamic coupling of WEAP and MODFLOW, and includes water balances for the crop root zone, the surface water system, and the underlying aquifer. The agronomic module simulates the effect of deficit irrigation on crop yield response in each growth stage, while the economic module calculates the net benefit of crop production. The optimization model contains two objective functions, one related to agricultural production and the other related to environmental flows. These conflicting objective functions are maximized using the Multi-Objective Particle Swarm Optimization algorithm. Decision variables include crop acreages, minimum environmental flow requirements in the river, and the degree of deficit irrigation. We applied the simulation-optimization model to the irrigated Miyandoab plain in the semi-arid northwest of Iran, for the historical period 1984 to 2013. There is competition between irrigation demands in the plain and environmental flow requirements to downstream Lake Urmia, which has been shrinking in recent years due to decreased inflows. Our results quantify what the (Pareto) trade-off looks like between meeting environmental and agricultural water demand in the region. We find that historical water allocations were suboptimal and that both agricultural and environmental benefits can be increased by better management of cropping decisions, deficit irrigation, and environmental flow requirements. We further show that increased groundwater use for irrigation can partly alleviate the trade-off, but that it leads to significant declines in groundwater levels due to the relatively small specific yield of the aquifer.</p>

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