Abstract:In arid and semi-arid areas, unsustainable development of irrigated agriculture has reduced the water level of large lakes such as Aral, Urmia, Hamoon, and Bakhtegan. Urmia Lake, as a hyper saline and very shallow lake, located in the northwest of Iran, has water level reductions of about 40 cm each year over the past two decades. In this research, the indices of environmental and agricultural sustainability are evaluated using performance criteria influenced by climate change and water management strategies for the Zarrinehrud and Siminehrud River basins as the largest sub-basin of Urmia Lake basin. Modeling of hydrologic behavior of these basins is performed using WEAP21 model. The model is analyzed for three future emission scenarios (A2, A1B, and B1), for the period of 2015-2040 and five water management scenarios: (1) keeping the existing situation; (2) crop pattern change; (3) improving the conveyance and distribution efficiency; (4) combining the improvement of conveyance and distribution efficiency with improving the application efficiency using modern technology; and (5) the combination of crop pattern change with the improvement of total irrigation efficiency. The results show that the highest values of indices of environmental sustainability and agricultural sustainability are related to the scenario of combining the crop pattern change with improving the total irrigation efficiency under the B1 emission scenario (B1S4).

Abstract. Supplemental irrigation of rainfed winter crops improves and stabilises crop yield and water productivity. Although yield increases by supplemental irrigation are well established at the field level, its potential extent and impact on water resources at the basin level are less researched. This work presents a Geographic Information Systems (GIS)-based methodology for identifying areas that are potentially suitable for supplemental irrigation and a computer routine for allocating streamflow for supplemental irrigation in different sub-basins. A case study is presented for the 42 908 km 2 upper Karkheh River basin (KRB) in Iran, which has 15 840 km 2 of rainfed crop areas. Rainfed crop areas within 1 km from the streams, with slope classes 0-5, 0-8, 0-12, and 0-20 %, were assumed to be suitable for supplemental irrigation. Four streamflow conditions (normal, normal with environmental flow requirements, drought and drought with environmental flow) were considered for the allocation of water resources. Thirty-seven percent (5801 km 2 ) of the rainfed croplands had slopes less than 5 %; 61 % (3559 km 2 ) of this land was suitable for supplemental irrigation, but only 22 % (1278 km 2 ) could be served with irrigation in both autumn (75 mm) and spring (100 mm), under normal flow conditions. If irrigation would be allocated to all suitable land with slopes up to 20 %, 2057 km 2 could be irrigated. This would reduce the average annual outflow of the upper KRB by 9 %. If environmental flow requirements are considered, a maximum (0-20 % slopes) of 1444 km 2 could receive supplemental irrigation. Under drought conditions a maximum of 1013 km 2 could be irrigated, while the outflow would again be reduced by 9 %. Thus, the withdrawal of streamflow for supplemental irrigation has relatively little effect on the outflow of the upper KRB. However, if the main policy goal would be to improve rainfed areas throughout the upper KRB, options for storing surface water need to be developed.

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Supplemental irrigation of rainfed winter crops improves and stabilizes crop yield and water productivity. Although yield increases by supplemental irrigation are well established at the field level, its potential extent and impact on water resources at the basin level are less researched. This work presents a GIS-based methodology for identifying areas that are potentially suitable for supplemental irrigation and a computer routine for allocating stream flow for supplemental irrigation in different subbasins. A case study is presented for the 42 908 km² upper Karkheh River Basin (KRB) in Iran, which has 15 840 km² of rainfed crop areas. Rainfed crop areas within 1 km from the streams, with slope classes 0–5%, 0–8%, 0–12% and 0–20%, were assumed to be suitable for supplemental irrigation. Four stream flow conditions (normal, normal with environmental flow requirements, drought and drought with environmental flow) were considered for the allocation of water resources. Thirty-seven percent (5801 km²) of the rainfed croplands had slopes less than 5%. Sixty-one percent (3559 km²) of this land was suitable for supplemental irrigation, but only 22% (1278 km²) could be served with irrigation in both fall (75 mm) and spring (100 mm), under normal flow conditions. If irrigation would be allocated to all suitable land with slopes up to 20%, 2057 km² could be irrigated. This would reduce the average annual outflow of the upper KRB by 9%. If environmental flow requirements are considered, a maximum (0–20% slopes) of 1444 km² could receive supplemental irrigation. Under drought conditions a maximum of 1013 km² could be irrigated, while the outflow would again be reduced by 9%. Thus, the withdrawal of steam flow for supplemental irrigation has relatively little effect on the outflow of the upper KRB. However, if the main policy goal would be to improve rainfed areas throughout the upper KRB, options for storing surface water need to be developed

Scarce water resources present a major hindrance to ensuring food security. Crop water productivity (WP), embraced as one of the Sustainable Development Goals (SDGs), is playing an integral role in the performance-based evaluation of agricultural systems and securing sustainable food production. This study aims at developing a cloud-based model within the Google Earth Engine (GEE) based on Landsat -7 and -8 satellite imagery to facilitate WP mapping at regional scales (30-m resolution) and analyzing the state of the water use efficiency and productivity of the agricultural sector as a means of benchmarking its WP and defining local gaps and targets at spatiotemporal scales. The model was tested in three major agricultural districts in the Lake Urmia Basin (LUB) with respect to five crop types, including irrigated wheat, rainfed wheat, apples, grapes, alfalfa, and sugar beets as the major grown crops. The actual evapotranspiration (ET) was estimated using geeSEBAL based on the Surface Energy Balance Algorithm for Land (SEBAL) methodology, while for crop yield estimations Monteith’s Light Use Efficiency model (LUE) was employed. The results indicate that the WP in the LUB is below its optimum targets, revealing that there is a significant degree of work necessary to ameliorate the WP in the LUB. The WP varies between 0.49–0.55 (kg/m3) for irrigated wheat, 0.27–0.34 for rainfed wheat, 1.7–2.2 for apples, 1.2–1.7 for grapes, 5.5–6.2 for sugar beets, and 0.67–1.08 for alfalfa, which could be potentially increased up to 80%, 150%, 76%, 83%, 55%, and 48%, respectively. The spatial variation of the WP and crop yield makes it feasible to detect the areas with the best and poorest on-farm practices, thereby facilitating the better targeting of resources to bridge the WP gap through water management practices. This study provides important insights into the status and potential of WP with possible worldwide applications at both farm and government levels for policymakers, practitioners, and growers to adopt effective policy guidelines and improve on-farm practices.