dataset · Zenodo (CERN European Organization for Nuclear Research)
A Python-based model was developed to assess dynamic crop water requirements and irrigation water demand in the Upper Genale River Basin, Ethiopia. This tool, part of the Integrated Climate-Water Allocation Decision Support Framework (ICWADSF), quantifies reference evapotranspiration, crop water requirements for wheat, maize, and sorghum, effective rainfall, and irrigation water requirements. It calculates demand for both existing and potential irrigation schemes, integrating these with other water uses. The model supports scenario-based planning under future climate pathways (SSP245 and SSP585) to aid sustainable water allocation and climate change impact assessment. A correction was implemented to ensure accurate basin-level estimates.
This model is crucial for managing water resources sustainably in the Upper Genale River Basin, where agriculture is a major water user. It provides a robust tool for understanding and planning for future irrigation needs and overall water allocation, especially under the pressures of climate change.
This Python-based model offers an applied research tool for water resource managers, agricultural planners, and policymakers. It can be used for irrigation planning, water allocation analysis, and assessing climate change impacts on water demand. As part of a larger decision support framework, it appears to be an early-stage development or research prototype, ready for use by specialists in planning and assessment.
AI-generated from the published abstract. Always read the original work before citing.
Dynamic Crop Water Requirement and Irrigation Water Demand Assessment ModelAuthor: Eliyas Abdi AliInstitution: Haramaya University / ACE Climate-Smart Agriculture & Biodiversity Conservation Study Area: Upper Genale River Basin, EthiopiaFramework: ICWADSF (Integrated Climate-Water Allocation Decision Support Framework) Introduction Agriculture is the largest consumptive water-use sector in the Upper Genale River Basin. Quantifying present and future irrigation water requirements is therefore essential for sustainable water allocation under climate variability and climate change. This Python-based model was developed to estimate: Reference evapotranspiration (ET₀) Crop water requirements (CWR) Effective rainfall (Peff) Irrigation water requirements (IWR) Gross irrigation requirements (GIR) Existing irrigation water demand Potential irrigation water demand Integrated basin water demand for both baseline and future climate scenarios. The model forms the irrigation component of the ICWADSF framework and supports scenario-based planning under SSP245 and SSP585 climate pathways. Objectives The model was developed to: Estimate monthly and annual reference evapotranspiration. Calculate crop water requirements for wheat, maize, and sorghum. Quantify effective rainfall and irrigation water requirements. Estimate gross irrigation requirements considering irrigation efficiency. Calculate water demand for existing irrigation schemes. Estimate future irrigation demand under potential irrigation development. Integrate irrigation demand with domestic, livestock, industrial, environmental, and hydropower water requirements. Support climate change impact assessment and water allocation planning. 3. Model Inputs Climate Variables Monthly climate data for each station including: Maximum temperature (°C) Minimum temperature (°C) Relative humidity (%) Solar radiation (MJ m⁻² day⁻¹) Wind speed (m s⁻¹) Precipitation (mm) Station Information Five representative stations: Station Elevation (m)Bor 2707 Has 2809 Ngl 1439 Kbr 1680 Dlm 1312 Crop Information Three representative crops: Crop Cropping RatioWheat 40% Maize 40% Sorghum 20% Irrigation Data Existing Irrigation Schemes Location Command area (ha) Potential Irrigation Schemes Location Command area (ha) 4. Methodology 4.1 Reference Evapotranspiration (ET₀) Reference evapotranspiration was estimated using the FAO-56 Penman-Monteith equation. ET0=0.408Δ(Rn−G)+γ900T+273u2(es−ea)Δ+γ(1+0.34u2)ET_0= \frac{ 0.408\Delta(R_n-G) +\gamma \frac{900}{T+273} u_2 (e_s-e_a) } { \Delta+\gamma(1+0.34u_2) }ET0=Δ+γ(1+0.34u2)0.408Δ(Rn−G)+γT+273900u2(es−ea) where: ET₀ = reference evapotranspiration Δ = slope vapor pressure curve Rn = net radiation G = soil heat flux γ = psychrometric constant u₂ = wind speed at 2 m es = saturation vapor pressure ea = actual vapor pressure 4.2 Crop Water Requirement (CWR) Crop evapotranspiration was estimated as: ETc=Kc×ET0ET_c = K_c \times ET_0ETc=Kc×ET0 where: ETc = crop water requirement Kc = crop coefficient ET₀ = reference evapotranspiration Dynamic monthly crop coefficients were used for wheat, maize, and sorghum. 4.3 Effective Rainfall Effective rainfall was estimated as: Peff=0.70PP_{eff}=0.70PPeff=0.70P where: Peff = effective rainfall P = precipitation The coefficient 0.70 accounts for runoff and other losses. 4.4 Irrigation Water Requirement (IWR) IWR=ETc−PeffIWR=ET_c-P_{eff}IWR=ETc−Peff Negative values were set to zero. Calculation was performed monthly before aggregation. 4.5 Gross Irrigation Requirement (GIR) GIR=IWREiGIR = \frac{IWR}{E_i}GIR=EiIWR where: Ei = irrigation efficiency Assumed: Ei=0.65E_i=0.65Ei=0.65 4.6 Basin Cropping Pattern To represent basin conditions: 40% Wheat40% \ Wheat40% Wheat 40% Maize40% \ Maize40% Maize 20% Sorghum20% \ Sorghum20% Sorghum Weighted basin GIR: GIRw=0.4GIRwheat+0.4GIRmaize+0.2GIRsorghumGIR_w= 0.4GIR_{wheat} + 0.4GIR_{maize} + 0.2GIR_{sorghum}GIRw=0.4GIRwheat+0.4GIRmaize+0.2GIRsorghum4.7 Existing and Potential Irrigation Demand Water demand was estimated using: Demand=Area×GIR×10106Demand= \frac{ Area\times GIR\times10 } {10^6}Demand=106Area×GIR×10 where: Area = irrigated area (ha) GIR = gross irrigation requirement (mm) Demand = MCM 5. Important Correction Applied During development, an overestimation issue was identified. The dataset contained: 12 months×5 stations=60 records12 \ months \times 5 \ stations = 60 \ records12 months×5 stations=60 records Initial calculations incorrectly summed crop water requirements across all five stations. This produced unrealistic results including: Weighted GIR > 6500 mm Irrigation demand > 2400 MCM The corrected approach averages monthly crop water requirements across stations before calculating basin irrigation demand: CWRbasin=CWR1+CWR2+CWR3+CWR4+CWR55CWR_{basin} = \frac{ CWR_1+CWR_2+CWR_3+CWR_4+CWR_5 } {5}CWRbasin=5CWR1+CWR2+CWR3+CWR4+CWR5 This method prevents double counting and produces physically realistic basin estimates. Results Gross Irrigation Requirement Indicator ValueGIR Wheat 1322.41 mm GIR Maize 1372.29 mm GIR Sorghum 1149.69 mm Weighted Basin GIR 1307.82 mm Irrigation Water Demand Existing Irrigation Indicator ValueDemand 13.39 MCM Potential Irrigation Indicator ValueDemand 415.55 MCM Integrated Basin Water Demand Integrated basin demand combines: Domestic Livestock Industrial Institutional Irrigation Environmental Hydropower Example scenario results: Year S2 (MCM) S3 (MCM)2023 62.09 49.39 2030 1335.84 1062.60 2040 1941.47 1544.35 7. Future Climate Scenario Assessment The workflow supports: SSP245 Near-Term (2021-2040) SSP245 Mid-Term (2041-2070) SSP585 Near-Term (2021-2040) SSP585 Mid-Term (2041-2070) For each scenario: ET₀ is recalculated using projected climate data. CWR is estimated dynamically. Effective rainfall is computed from projected precipitation. IWR and GIR are calculated. Existing and potential irrigation demand are estimated. Total basin demand is updated. 8. Outputs The model exports: Monthly Outputs ET₀ CWR Peff IWR GIR Annual Outputs Basin GIR Existing irrigation demand Potential irrigation demand Total water demand Scenario Outputs Baseline 2023 SSP245 Near-Term SSP245 Mid-Term SSP585 Near-Term SSP585 Mid-Term 9. Applications The model supports: Climate change impact assessment Irrigation planning Water allocation analysis Basin development planning Environmental flow assessment Hydropower planning ICWADSF scenario analysis 10. Key Baseline Findings Indicator ValueIrrigation Efficiency 65% Effective Rainfall Factor 70% Cropping Pattern 40% Wheat, 40% Maize, 20% Sorghum Weighted GIR 1307.82 mm Existing Demand 13.39 MCM Potential Demand 415.55 MCM Citation If this model is used in publications, cite: Ali et al., (2026). Integrated Climate-Water Allocation Decision Support Framework (ICWADSF): Dynamic Crop Water Requirement and Irrigation Demand Model for the Upper Genale River Basin, Ethiopia. PhD Research Framework, Haramaya University.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.5281/zenodo.22088417
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
