Irrigation Water Requirements Research Articles

Penggunaan CROPWAT 8.0 untuk Menentukan Kebutuhan Air Irigasi Tanaman Tomat pada Tanah Regosol di Kawasan Ternate Utara, Provinsi Maluku Utara

Tomato is an important crop in Ternate, North Maluku Province, Indonesia. This study aimed to determine the irrigation water requirements for tomato cultivation on Regosol soil in the North Ternate region using the CROPWAT 8.0 model. Climate data, crop data, and soil data were collected and processed using the CROPWAT 8.0 program. The results showed that the irrigation water requirements varied significantly between the rainy and dry seasons. During the rainy season, the total irrigation water requirement ranged from 60 to 107 mm, while in the dry season, it was much higher, ranging from 130 to 187 mm. This difference was primarily due to the low rainfall during the dry season. Simulations of planting at different periods showed relatively minor variations in crop water requirements, reflecting the stable weather conditions throughout the year in Ternate. The findings of this study can assist local tomato farmers in managing irrigation water more efficiently and effectively, thereby improving crop productivity and reducing the risk of water shortage.

Examining Crop Yield Losses in Iğdır Plain Irrigation Systems in Türkiye Amidst Water Constraints

Water stands as a crucial component of agricultural production. This study aims to propose water efficiency measures in agriculture as an essential element for climate change adaptation. In this study, yield losses in staple crops in agricultural regions are analyzed by using the most suitable methodologies, particularly in agriculture-reliant developing nations. Furthermore, this study seeks to determine the financial consequences of such losses. The methodology applied for this purpose was implemented in Türkiye’s Iğdır Plain, selected as the study site. As the first step, the yields of the first three most cultivated products in each product group were assessed under normal climatic conditions in terms of their crop water requirements and irrigation water requirements. Subsequently, the irrigation water supply was reduced by 10%, and the resulting yield losses were calculated per hectare. Then, the overall crop losses after applying the 10% water constraint were determined in the total cultivation area. Among the crops cultivated in the region, the analysis reveals that clover from the field crops category exhibits the highest water dependence, while apricot demonstrates the least reliance on water resources. As a result, the recommended crop rotation for the Iğdır Plain under water constraints comprises wheat, apricot, watermelon, maize, melon, apple, tomato, peach, and clover. The following measures are proposed to ensure sustainable use of water resources and reduce exposure to climate change: increasing the water transmission efficiency and water use efficiency in irrigation areas, allocating more space to water-stress-resistant crops in the crop pattern in basins, and substituting crops requiring excessive water with less water-dependent crops.

Determination of irrigation requirement for tomato using FAO-CROPWAT model in the Arid Region

Food security presents a significant challenge in arid regions, exacerbated by water scarcity due to climate change. Tomato is one of the top agricultural crops around the world, in which it is needed to investigate its irrigation water requirements for each region, especially in the arid regions. This work mainly aims to estimate the irrigation water requirements and irrigation schedules for cultivating tomato in Ras Al Khaimah (RAK), United Arab Emirates (UAE). This would be done by utilizing the FAO-CROPWAT 8.0 Model and CLIMWAT 2.0. The findings of this research support efficient water use by utilizing the advanced modeling tools. The outcomes will inform and enhance irrigation water management practices for farmers, farm owners, and policymakers, contributing significantly to sustainable development goals and the resilience of agricultural systems in water-limited environments.

Determination of irrigation requirement for tomato using FAO-CROPWAT model in the Arid Region

Food security presents a significant challenge in arid regions, exacerbated by water scarcity due to climate change. Tomato is one of the top agricultural crops around the world, in which it is needed to investigate its irrigation water requirements for each region, especially in the arid regions. This work mainly aims to estimate the irrigation water requirements and irrigation schedules for cultivating tomato in Ras Al Khaimah (RAK), United Arab Emirates (UAE). This would be done by utilizing the FAO-CROPWAT 8.0 Model and CLIMWAT 2.0. The findings of this research support efficient water use by utilizing the advanced modeling tools. The outcomes will inform and enhance irrigation water management practices for farmers, farm owners, and policymakers, contributing significantly to sustainable development goals and the resilience of agricultural systems in water-limited environments.

Fuzzy rule–based control of multireservoir operation system for flood and drought mitigation in the Upper Mun River Basin

AbstractStrategic reservoir operation, a primary water management measures, plays a significant role in mitigating floods and droughts. Since the reservoir operation involves making complicated decisions on uncertain hydrological variables driven by climate variability, therefore, constructive tool for decision making like fuzzy logic is essential to optimize reservoir management and ensure water security. This study demonstrated fuzzy logic application to multiple reservoir operation in tropical region like Thailand. A Fuzzy Rule–Based Model (FRBM) exploiting FL approach was developed to control the upstream reservoir operation in the Upper Mun River Basin (UMRB) using the data from 2008 to 2021. Implementing FRBM for UMRB was conducted by identifying two key variables; available water storage and 7–day ahead predicted inflow, as fuzzy inputs. The fuzzy output of the system is the release fraction determined by three operational condition modules; flood, neutral, and drought. For flood module, fuzzy release is primarily determined by the predicted inflow. However, the determination of reservoir release for drought and neutral modules is influenced by the targeted water demand. The results of base case illustrate the capability of FRBM in increasing reservoir storages at the start of dry season by 123.56 MCM/yr in UMRB due to the new daily release schemes generated. This allows supplying water closer to the theoretical agricultural needs and gross irrigation water requirement potentially reducing the risk of water shortfall during consecutive dry years. Whereas, the maximum fuzzy release is constrained corresponding to safe channel capacity of tributaries and Upper Mun river, therefore, downstream flooding is accordingly prevented.

Assessing climate change impacts on irrigation water requirements in the Lower Mahanadi Basin: A CMIP6-based spatiotemporal analysis and future projections

ABSTRACT Climate change heightens India's agricultural risks, particularly in nations like India heavily reliant on farming. Previous studies focused on Coupled Model Intercomparison Project Phase (CMIP3) and (CMIP5) scenarios for large river basins, but the heightened risk of local climate changes poses a significant threat to smaller basins, notably affecting crops. This study investigates the spatiotemporal dynamics of climate change impacts on paddy crop irrigation in India's Lower Mahanadi Basin, utilizing the latest general circulation models (GCMs) from the CMIP6, focuses on two emission scenarios, SSP585 and SSP370. Thirteen models were analysed, top six were selected based on statistical criteria like PBIAS, NSE, R2, RSR, and RMSE. Models project climate changes for near- (2025–2050), mid- (2051–2075), and far-future (2076–2100) periods against a baseline (1981–2014), investigating spatiotemporal variations in rainfall, temperature, and irrigation water requirements (IWRs) in the region. In both scenarios, future mean seasonal rainfall is expected to increase compared with the baseline. SSP370 projects a 23.7% rise in minimum rainfall, while maximum rainfall varies by 11.5%. SSP585, on the other hand, projects a 9.53% decrease in maximum IWR and a 28.9% increase in maximum rainfall compared with the baseline. Both scenarios anticipate a 3–4 °C temperature increase in the far-future.

Agricultural Irrigation Water Requirement and Its Response to Climatic Factors Based on Remote Sensing and Single Crop Coefficient Method

Agricultural Irrigation Water Requirement and Its Response to Climatic Factors Based on Remote Sensing and Single Crop Coefficient Method

Representative concentration pathways (RCPs) used as a tool to evaluate climate change impact on maize crop production in the Woybo catchment of Ethiopia

ABSTRACT The research was conducted to assess the climate change impact on crop water requirements (CWRs) in the Woybo catchment of southern Ethiopia. The impact of climate change was assessed through climate models under RCP4.5 and RCP8.5 emission scenarios for the 2050s compared to 1971–2005. During the 2050s, the annual mean minimum temperature increased by 1.9–2.3 °C, while the maximum temperature over the catchment increased by 1.4–2.0 °C. The projected rainfall is expected to increase in autumn, summer, and annually by 3.7–16.8 and 8.7–12.2% in the 2050s under RCP4.5 and 8.5, respectively. But it is likely to decrease in winter and spring by 1.5–10.2% and 8.7–2.8%, respectively. The average annual potential evapotranspiration will rise by 0.1–6.8%. Under both RCPs, CWRs may increase from 6.2 to 17.2% during the growing season, while irrigation water requirements (IWRs) may rise from 4.6 to 16.4%. Future period projection results show that potential evapotranspiration and IWRs will increase for maize crops compared to the baseline period. The study will help water managers, users, and agricultural developers in preparing new water-saving strategies and achieving agricultural sustainability.

Integrating hydrologic modeling and satellite remote sensing to assess the performance of sprinkler irrigation

Integrating hydrologic modeling and satellite remote sensing to assess the performance of sprinkler irrigation

Vermicompost: Significance and Benefits for Agriculture

Vermicomposting is defined as the process of biodegradation and stabilization of organic materials, facilitated by the collaborative efforts of earthworms and mesophilic microorganisms. The activity of earthworms in vermicomposting results in the production of nutrient-rich vermicompost. This organic amendment is abundant in macro and micronutrients, vitamins, growth hormones, as well as enzymes like proteases, amylases, lipase, cellulase, and chitinase. Additionally, vermicompost harbors a diverse community of immobilized microflora. Even after being excreted by the worms, the enzymes in vermicompost persist in their ability to decompose organic matter, facilitating continued breakdown and nutrient release. The utilization of vermicompost in agricultural production brings forth a multitude of beneficial effects. These include decreased water requirements for irrigation, reduced susceptibility to pest and termite attacks, suppression of weed growth, and enhanced seed germination rates, accelerated growth and development of seedlings, as well as increased yield of fruits per plant in vegetable crops and a higher number of seeds per year in cereal crops. These advantages highlight the positive impact of incorporating vermicompost into agricultural practices, fostering sustainable and productive farming systems. The combination of earthworms and vermicompost presents a valuable opportunity to enhance horticultural production in a sustainable manner, reducing reliance on agrochemical inputs. Despite the numerous benefits associated with vermicompost, its widespread implementation and adoption are still relatively limited. This review aims to raise awareness and promote the understanding of this valuable local soil amendment.

Nutrient Composition of Detoxified Oil Cake from Simarouba glauca

Vermicomposting is defined as the process of biodegradation and stabilization of organic materials, facilitated by the collaborative efforts of earthworms and mesophilic microorganisms. The activity of earthworms in vermicomposting results in the production of nutrient-rich vermicompost. This organic amendment is abundant in macro and micronutrients, vitamins, growth hormones, as well as enzymes like proteases, amylases, lipase, cellulase, and chitinase. Additionally, vermicompost harbors a diverse community of immobilized microflora. Even after being excreted by the worms, the enzymes in vermicompost persist in their ability to decompose organic matter, facilitating continued breakdown and nutrient release. The utilization of vermicompost in agricultural production brings forth a multitude of beneficial effects. These include decreased water requirements for irrigation, reduced susceptibility to pest and termite attacks, suppression of weed growth, and enhanced seed germination rates, accelerated growth and development of seedlings, as well as increased yield of fruits per plant in vegetable crops and a higher number of seeds per year in cereal crops. These advantages highlight the positive impact of incorporating vermicompost into agricultural practices, fostering sustainable and productive farming systems. The combination of earthworms and vermicompost presents a valuable opportunity to enhance horticultural production in a sustainable manner, reducing reliance on agrochemical inputs. Despite the numerous benefits associated with vermicompost, its widespread implementation and adoption are still relatively limited. This review aims to raise awareness and promote the understanding of this valuable local soil amendment.

A comprehensive analytical and computational assessment of soil water characteristics curves in Atlantic Canada: Application of a novel SelectKbestbased GEP model

For sustainable agriculture, irrigation is one of the most important management practices in a semi-arid climate. Determining the site-specific soil type-based irrigation water requirements requires the development of a soil water characteristics curve (SWCC). This study focuses on exploring the suitability of analytical SWCC models based on the observed data of SWCC developed using the pressure membrane apparatus. A novel SelectKbest gene expression programming (GEP) model is used to create the generalized machine learning SWCC model for Atlantic Canadian soils. The composite soil samples with representative soil textures of loamy sand, loam, and sandy loam are collected from the selected locations in Prince Edward Island and New Brunswick provinces of Canada. The suitability of models at three regions shows that at all sites, including PEI-1 (loam soil) 1, PEI-2 (loamy sand), and NB-3 (sandy loam) if SWCC data has four measured suction potential levels, then McBee & Bomb and Tani exponential models may be selected. Van Genuchten, double exponential, Ruso, Kosuki, and Gardner's four parameters models should be a good choice for five-section potential. Similarly, for six measured suction potential values, the Fredlund & Xing, Omuto, and Van Genuchten models having parameters should be selected for determining the optimum soil hydraulic parameters. The HydroMe program with Brooks and Corey, four, and five parameters Van Genuchten models performed well. The HydroMe program is calibrated and validated with standard RETC for selected regions of Atlantic Canada, which suggests that the HydroMe program is flexible in developing efficient agricultural water management algorithms. Various performance metrics like R2 and RMSE are employed to assess the robustness of the model. A generalized SWCC model (R2=0.976 and RMSE=0.04) is developed using a novel SelectKbest-based GEP modeling approach for Atlantic Canadian soils. These novel approaches can significantly improve site-specific agricultural water management and decision support systems.

Hydrologic applicability of satellite-based precipitation estimates for irrigation water management in the data-scarce region

Reliable precipitation estimates are crucial for planning and managing water resources, monitoring hydrologic extremes, and fulfilling irrigation water requirements. Accurate precipitation estimates are particularly challenging in complex mountain terrains, where monitoring gauges are often sparsely distributed due to their remote locations, and high installation and long-term operation costs. Recent advances in satellite-based precipitation estimates offer promising opportunities to improve our understanding of hydrologic processes and their applications for irrigation water management. Several datasets are available varying considerably in terms of their data sources, quality control methods, estimation procedure, and spatiotemporal resolutions. Choosing the most suitable dataset for a particular application is a complex task. In this study, we (1) evaluate the performance of six satellite-based precipitation estimates (SPEs): i) CHIRPS v2.0, ii) CMORPH v1.0, iii) ERA5, iv) IMERG v6, v) MSWEP v2.8, and vi) PERSIANN-CDR against the gauge precipitation using continuous statistical and categorical indices, (2) integrate SPEs with a calibrated semi-distributed hydrologic model to predict streamflow, and (3) demonstrate practical implications of improved streamflow prediction for irrigation water management in the central Himalayan region, Nepal. Our results illustrate that satellite-based precipitation estimates have competitive performance in capturing a wide range of rainfall characteristics, with demonstrated variability across river basins and time scales. There are no significant discrepancies observed in satellite-based precipitation estimates for estimating irrigation water requirements for the three major crops (maize, wheat, and paddy) during the cropping period across the selected river basins, showing a greater promise for irrigation water management planning and decision making.

Ecosystem services of irrigated and controlled drainage agricultural systems: A contemporary global perspective

AbstractIrrigated agriculture provides 40% of the world's crop‐based foods but often with a negative impact on the environment. It is important to recognize that in addition to providing food and fibre, irrigation and controlled drainage systems can be optimized to provide additional ecosystem services and mitigate climate change by using resources in a more efficient way. Contemporary case studies were identified from around the world, including flood control by paddy fields in Japan, water quality enhancement and wastewater reuse in South Africa and Taiwan, micro‐/meso‐climate regulation in Ethiopia and Japan, controlled drainage and sub‐irrigation to maximize carbon sequestration and minimize leaching in Finland, and groundwater table management to reduce irrigation water and pumping requirements in Turkey. Irrigation infrastructure, such as rice paddy terraced landscapes (Japan) and large dams and canals (Australia), have also achieved notable additional ecotourism job creation. Case studies were analysed in terms of funding opportunities and compared using the Common International Classification of Ecosystem Services system. It is recommended that planning frameworks be developed that seek to optimize ecosystem services such as the ones discussed above. Policy should be updated to recognize these services and provide incentives to irrigators and water management entities accordingly.

Crop water requirement and irrigation scheduling under climate change scenario, and optimal cropland allocation in lower kulfo catchment

Crop water requirement and irrigation scheduling in Lower Kulfo Catchment of southern Ethiopia have not assessed under climate change scenarios, and the allocation of crop land also not optimal that signifcantly challenges to crop productivity.Therefore, this study was conducted to evaluate the effects of climate change on future crop water requirements, and irrigation scheduling, and to allocate cropland optimally. Bias of projected precipitation and temperature were corrected by utilizing Climate Model data with the hydrologic modeling tool (CMhyd). Alongside, crop water requirements and irrigation scheduling were assessed using Crop Water Assessment Tool. After estimating crop water requirement, crop land were allocated optimally using General Algebraic Modeling System programming with non-negativity constraints (scenario 1), and non-negativity constraints based on farmers adaptation (scenario 2). Average reference evapotranspiration from 2030 to 2050 and 2060 to 2080 was increased by 11.9 %, and 16.2 %, respectively compared with the reference period (2010–2022). The total seasonal crop water requirements were 4,529 mm, 4866.7 mm, and 5272.2 mm under 2010 to 2022, 2030 to 2050, and 2060 to 2080 climate change scenarios, respectively. The meean irrigation interval in 2010–2022, 2030 to 2050, and 2060 to 2080 climate change scenarios were 8 days, 7 days, and 5 days, respectively. This irrigation interval was decreased by 14 % (2030–2050), and 34 % (2060–2080) compared with the reference period. In 2030 to 2050 and 2026 to 2080 climate change scenarios, the required irrigation water at the inlet of main canal increased by 6.8 %, and 18 %, respectively. The optimal allocated area for tomato (60.4 %), maize (20.8 %), and watermelon (18.8 %) in scenario 1 with net benefit of 1.47*108 Ethiopian Birr. The allocated areas in scenario 2 were (48 %) for maize, (31.6 %) for tomato, and (20.4 %) for watermelon with 1.34*108 Ethiopian Birr net benefit it was reduced by 19.1 % compared with the net benefit in scenario 1. Fruit crops alone may not suffice for local food needs and to address this, small farmers should grow maize, tomato, and watermelon. This research aids policymakers in encouraging climate-resilient agriculture and improving small-scale farmers' awareness through conducting workshops and training.

Optimization of Tertiary Irrigation Network Using A Linear Program at D.I. Panggak Darat in Lingga District

The Panggak Darat Irrigation Area in Lingga Regency can irrigate 134.05 ha of rice fields. The problem that often occurs is that irrigation areas are not fully optimal for agricultural product productivity, so that an effort can be made to minimize the shortage of irrigation water and/or minimize the deviation of water release that can result from an optimal pattern of irrigation operations. The purpose of this study is to obtain an optimal operating pattern with better operating performance than the existing (planning). The analytical method used is an optimization technique using the LINDO program (linear programming). The objective function is to minimize the shortage of irrigation water. Evaluation of the operational performance of the optimized and existing reservoirs is carried out using simulation techniques. The results showed that the optimal operating pattern was obtained from the Objective Function with an average total release of reservoir water of 3.20 million m3, which can meet 100% of the irrigation water Requirements of an area of 134.05 ha of irrigation area that must be irrigated. The reliability of the optimization results is in the form of 100% irrigation reliability with a planting intensity of 300% with a rice-rice cropping pattern where the existing (planning) is a rice-rice-bero cropping pattern or a rice-bero cropping pattern with a cropping intensity of 200%. Optimization results from the objective function of minimizing the shortage of irrigation water provide better operating performance than the existing conditions, so as to increase agricultural productivity.

Effect of establishment methods in rainy season (kharif) and tillage practices in winter season (rabi) on yield and economics of rice (Oryza sativa)–maize (Zea mays) cropping system under coastal saline ecosystem

A field experiment was carried out during 3 consecutive rainy seasons (kharif) June–November and winter (rabi) December–May seasons of 2013–16 at Canning Town, West Bengal to evaluate 3 rice (Oryza sativa L.) es tablishment methods, viz. dry direct seeding (DSR), unpuddled transplanting (UNPT) and puddled transplanting (PT), followed by 3 tillage practices for sowing rabi maize (Zea mays L.), viz. zero tillage (ZT), conventional tillage (CT) and raised bed sowing (RBS). The DSR was done in the last week of May when the soil salinity was higher (12–15 dS/m); however, it reduced to 4–5 dS/m in the month of June due to leaching of salts by monsoon rain. The transplanting in the UNPT and PT plots was done during the first week of July using 40 days old seedlings. Submergence caused by the heavy rain, affected the transplanted rice (PT and UNPT) but not the DSR, as the plants with DSR were sufficiently above the standing water due to higher plant height. The mean grain yields in 3 establishment methods of rice (5,117; 4,477 and 4,740 kg/ha in PT, UNPT and DSR respectively) were statistically at par. However, net returns ( 36,000/ha) and benefit: cost ratio (2.2) were the highest in DSR owing to 24% re duction in cost of cultivation than PT rice. The positive effects of DSR also observed on the succeeding rabi maize crop in terms of 7.4 ha-cm less irrigation water requirement and 27% higher irrigation water productivity. Maize gave the highest yield (5,600 kg/ha), net returns ( 37,910/ha) and benefit: cost ratio (BCR) 1.86 with RBS tillage practices. The system rice-equivalent yield, net returns and BCR were 11,659 kg/ha, 77,470/ha and 2.05, re spectively, for dry direct-seeded rice-raised bed sown maize with higher mean irrigation water productivity (79 kg/ ha-cm) and energy productivity (461 kg/GJ) of rabi maize.

Comparative Analysis of Earth Observation Methodologies for Irrigation Water Accounting in the Bekaa Valley of Lebanon

This study extensively examines the estimation of irrigation water requirements using different methodologies based on Earth Observation data. Specifically, two distinct methods inspired by recent remote sensing and satellite technology developments are examined and compared. The first methodology, as outlined by Maselli et al. (2020), focuses on using Sentinel-2 MSI data and a water stress scalar to estimate the levels of actual evapotranspiration and net irrigation water (NIW). The second methodology derives from the work of D’Urso et al. (2021), which includes the application of the Penman–Monteith equation in conjunction with Sentinel-2 data for estimating key parameters, such as crop evapotranspiration and NIW. In the context of the Bekaa Valley in Lebanon, this study explores the suitability of both methodologies for irrigated potato crops (nine potato fields for the early season and eight for the late season). The obtained NIW value was compared with measured field data, and the root mean square errors were calculated. The results of the comparison showed that the effectiveness of these methods varies depending on the growing season. Notably, the Maselli method exhibited better performance during the late season, while the D’Urso method proved more accurate during the early season. This comparative assessment provided valuable insights for effective agricultural water management in the Bekaa Valley when estimating NIW in potato cultivation.

Green and Blue Water Footprints of Major Crops in the Wami/Ruvu Basin, Tanzania: Implications for Water Scarcity and Sustainability

Accurate estimation of the blue and green water requirements of the various crops cultivated in a water basin is essential for planning specific plant/crop irrigation schedules. In this study, the crop water requirements of the major crops grown in the Wami/Ruvu basin were determined using the FAO-CROPWAT model based on meteorological parameters: monthly maximum and minimum temperature, wind speed, mean relative humidity, sunshine hours, rainfall data, and effective rainfall for 23 hydro-meteorological stations distributed in the study area. The studied crops are rice, maize, beans, tomatoes, and sugarcane. The crop reference evapotranspiration (ETo) and actual evapotranspiration (ETc) for each crop were determined using crop coefficients (Kc) of various growth stages of crops. The results indicated that the total annual reference evapotranspiration (ETo) was 1604 mm, whereas an average ETo per month was 134 mm. The highest total irrigation water requirements were recorded in sugarcane, followed by rice, while the lowest water requirements were observed in beans and tomatoes. The results presented in this study may facilitate plant-specific water irrigation implementation and maximize crop production while conserving the environment.

EVALUATION OF NGABEAN SECONDARY CANAL IRRIGATION NETWORK, NGAWI DISTRICT PART OF SALURAN INDUK MADIUN IRRIGATION AREA

The SIM Irrigation Area has an area of 10,860 Ha and a primary canal length of 27,022 m, which passes through the Regencies of Madiun, Magetan, Ngawi, and Madiun City. One of the secondary canals in the D.I SIM is the Ngabean Secondary Canal, located in Ngawi Regency. This canal receives the main water supply from Jati Dam, 25% of the primary dam discharge and water withdrawal from the Ngabean Dam intake of 0.45 m3/ha. However, this value only meets the water needs of some of the irrigation areas. Due to the limited supply from the Jati Bendung, the government is working on rehabilitation work at the Jati Bendung. Apart from that, the Ngabean Secondary Canal also experienced a reduction in the irrigation area from 1840 ha to 1818 ha, to be precise in the NG3 Ki tertiary plot, which had an initial area of 120 ha to 98 ha. Therefore, an evaluation of the Ngabean Secondary Canal is needed to determine the value of water demand, water availability before and after rehabilitation and land reduction, and increasing agricultural profits.From the results of the analysis that has been carried out, it was concluded that the highest dependent flow at Ngabean Dam was 5.00 m3/s, and the lowest was 0.01 m3/s. Meanwhile, in conditions before rehabilitation, the highest dependent flow of Jati Dam was 1.01 m3/s, and the lowest was 0.00 m3/s with water withdrawal at the intake of 25%, able to fulfill the planting pattern of paddy (15%)-crops (75%)-crops (50%) generated a production profit of IDR 8.794.123.880,00. Meanwhile, after rehabilitation, the highest was 5.93 m3/s, and the lowest was 3.21 m3/s with an intake of 32%, able to fulfill the planting pattern of paddy (100%)-paddy (100%)-paddy (100%), resulting in a production profit of IDR 83, 564,115,480.00 with the highest irrigation water requirement value of 3.10 m3/sec. Apart from that, the existing canal dimensions still meet the requirements after land reduction, so no changes to the canal dimensions are required.