تهیه سامانه‌ی استانی حسابداری آب برای اراضی کشاورزی آبی استان فارس

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه زراعت، دانشکده تولید گیاهی، دانشگاه علوم کشاورزی و منابع طبیعی گرگان، گرگان، ایران

2 موسسه تحقیقات فنی و مهندسی کشاورزی، تهران، ایران

3 گروه اقتصادکشاورزی، دانشکده مدیریت کشاورزی، دانشگاه علوم کشاورزی و منابع طبیعی گرگان، گرگان، ایران

چکیده

تهیه و اجرای مناسب برنامه‌های سازگاری به کم‌آبی در سطح استانی نیازمند وجود اطلاعاتی متنوع، معتبر و یکپارچه مرتبط با منابع آب استان است. برای دستیابی به این اطلاعات به‌صورت یکپارچه و پویا، سیستمی تحت عنوان سامانه استانی حسابداری آب (SAWA) برای استان فارس تهیه شد. ابتدا با بررسی شرایط اقلیمی و خاک، کل اراضی کشاورزی آبی استان به 17 پهنه اگرواکولوژیک همگن تقسیم‌بندی شدند. سپس یک مدل ‌شبیه‌ساز گیاهی (SSM-iCrop2) که هسته اصلی سیستم را تشکیل می‌دهد برای شبیه‌سازی رشد، عملکرد و بیلان آب مزرعه 35 گیاه مهم در شرایط کشاورزان در 17 پهنه کالیبره و برپا (ست‌آپ) شد. شبیه‌سازی‌ها بر اساس داده‌های هواشناسی سال‌های 2011 تا 2021 در دو حالت شرایط کشاورزان و پتانسیل صورت گرفت. خروجی‌های سیستم مذکور به‌صورت روزانه و نیز انتهای فصل رشد گیاه تولید می‌شوند. علاوه بر این، سیستم قادر است خروجی‌های ماهانه نیز تولید کند. این برآوردهای ماهانه یکی از ضروری‌ترین اطلاعات در برنامه‌ریزی‌های سازگاری با کم‌آبی مثل تغییر الگوی کشت است. برخی از خروجی‌های سیستم عبارتند از تاریخ کاشت گیاهان زراعی و تاریخ بازشدن جوانه درختان، مراحل مهم فنولوژیک گیاهان، عملکرد بیولوژیک، شاخص سطح برگ و مؤلفه‌های بیلان آب یعنی رواناب، تبخیر، تعرق، زه‌کشی عمقی، برگاب، تعرق علف‌های هرز و آبیاری. خروجی‌های این سامانه برای هر گیاه و یا کل گیاهان به‌صورت پهنه، شهرستان و استان قابل دسترس هستند. ارزیابی صحت برآوردهای مدل نشان داد که برآوردهای شبیه‌سازی‌شده با اندازه‌گیری‌شده مطابقت رضایت بخشی دارند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Development of water accounting system for irrigated agricultural lands of Fars province

نویسندگان [English]

  • Abdolrahman Mirzaei 1
  • Afshin Soltani 1
  • Fariborz Abbasi 2
  • Ebrahim Zeinali 1
  • Shahrzad Mirkarimi 3
1 Department of Agronomy, Faculty of Plant Production, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran
2 Agricultural Engineering Research Institute: Karaj, Iran
3 Department of Agricultural Economics, Faculty of Agricultural Management, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran
چکیده [English]

Preparation and proper implementation of water scarcity adaptation programs at the provincial level requires diverse, reliable and integrated information related to the province's water resources. To obtain this information in an integrated and dynamic manner, a system called ‘System for regional Agricultural Water balance and water Accounting’ (SAWA) was prepared for Fars province. First, the irrigated agricultural lands of the province were divided into 17 homogenous Agro-Ecological-Zones (AEZ). Then, a crop model (SSM-iCrop2) was calibrated and set up to simulate the growth, yield and field water balance of 35 agricultural plants under potential and farmers’ conditions in the 17 AEZ. The simulations were done using weather data of 2011-2021. The outputs of the system are produced on a daily basis and for the end of the growing season. The system is also able to produce monthly outputs of water balance that are essential information for water scarcity adaptation programs such as cropping pattern. Some of the outputs of the system are crop planting date and the date of bud burst in trees, the time of occurrence of important phenological stages, total biomass, leaf area index and field water balance components such as runoff, evaporation, transpiration, deep drainage, weeds’ transpiration and applied irrigation water. The outputs of this system are available for each plant or all plants in each of the zones, counties and the whole province. The testing of the system showed that the simulated yields and applied irrigation water are in satisfactory agreement with the measured ones.

کلیدواژه‌ها [English]

  • Adaptation to water scarcity
  • irrigation water
  • modeling
  • SSM-iCrop2
  • water balance

Development of water accounting system for irrigated agricultural lands of Fars province

EXTENDED ABSTRACT

Introduction

Adapting to water scarcity in agricultural sector of Iran is a necessity and Fars province is no exception. Preparation and implementation of appropriate adaptation planning to water scarcity requires diverse, valid and integrated information on water resources. Models and software typically estimate this information for optimal growth conditions (potential) and then refine it based on empirical methods that may be subject to error. The main objective of this research is to develop a system that can provide this information directly, dynamically and in an integrated manner under farmer’s conditions. This information is essential for water scarcity adaptation planning.

Materials and Methods

In this research, the water balance accounting system was developed based on a scaling protocol, a plant simulation model and various input data. First, the irrigated agricultural lands of Fars province were divided into homogeneous agro-ecological zones (AEZ), and the cultivated area of each of the important plants of the province was determined in each AEZ. In the next step, one or more representative weather stations (RWS) were selected for each AEZ based on the size of the cultivated area. For these RWS points, required information and plant simulation model inputs such as management, soil, crop (variety), and weather data were prepared. The plant simulation model (SSM-iCrop2), which forms the core of the system, was set up and calibrated to simulate the water balance, yield and growth of the important plant(s) of the province under the conditions of farmers, and finally the system was developed. The system is able to simulate and produce the growth, yield and water balance components under the conditions of farmers or potential for the important plant(s) of the province.

Results

The results indicated that wheat, barley, and citrus have the largest area of irrigated plants among the 35 important plants of the province. 17 AEZ were identified to cover more than 95% of the irrigated agricultural lands of the Fars province, among which 6002Shrz AEZ had the largest cultivated area. The system produces important outputs such as information on water balance and growth, yield, and phenology of important plants in the province. These outputs can be generated monthly, annually (at the end of the growth season), or at any other time interval. Monthly water balance information is crucial for effective water scarcity adaptation planning. This information can be obtained for individual plants, all plants in each AEZ, or all plants in the entire province. Moreover, the system can provide this information in the form of counties. The system generates this information for farmers and potential conditions. The results indicated that the estimates of the potential conditions are different from the farmers. Therefore, it is necessary that the estimations of farmers conditions should be taken into account in water scarcity adaptation planning. The evaluation of the accuracy of the model estimates was satisfactory.

Conclusion

The system provides reliable and integrated information on yield, growth, and other water balance components for each plant or all plants monthly and annually (at the end of the growing season). The system produces estimates that can be used to calculate the volume of irrigation water and total water harvesting for agriculture on a monthly, yearly, or any time period basis. This information can be produced under farmers and potential conditions. This system is unique in its ability to provide the mentioned information directly under farmer’s conditions and does not require the use of experimental methods to modify estimates, unlike other systems. Estimates from this system can help reduce the difference in the volume of water consumed (volume of irrigation water) and water harvested for agriculture between government agencies. In addition, the estimates from this system are necessary for planning to adapt agriculture to water scarcity, such as optimizing cropping patterns.

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