Socioeconomic benefits of conserving Iran’s water resources through modifying agricultural practices and water management strategies

Karandish, Fatemeh

doi:10.1007/s13280-021-01534-w

Cited by 13 publications

(7 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To determine the variables' contribution, the co-variation of MAE with PET, P, and P+GW is calculated for the three global datasets (Figure 9). As mentioned before, GW is an important water source in semi-arid/arid regions such as in Iran and it cannot be assumed as zero due to relevant water withdrawals during recent decades [6,62,63]. The MAE, and RMSE of ET ERA5 has an inverse correlation with PET and a positive correlation with P and P+GW (Figure 9a-c, Figure S1a-c).…”

Section: Comparison Of Et Era5 Et Gleam and Et Gldas With Et Wb In ...mentioning

confidence: 89%

Spatio-Temporal Assessment of Global Gridded Evapotranspiration Datasets across Iran

et al. 2021

View full text Add to dashboard Cite

Estimating evapotranspiration (ET), the main water output flux within basins, is an important step in assessing hydrological changes and water availability. However, direct measurements of ET are challenging, especially for large regions. Global products now provide gridded estimates of ET at different temporal resolution, each with its own method of estimating ET based on various data sources. This study investigates the differences between ERA5, GLEAM, and GLDAS datasets of estimated ET at gridded points across Iran, and their accuracy in comparison with reference ET. The spatial and temporal discrepancies between datasets are identified, as well as their co-variation with forcing variables. The ET reference values used to check the accuracy of the datasets were based on the water balance (ETwb) from Iran’s main basins, and co-variation of estimated errors for each product with forcing drivers of ET. The results indicate that ETERA5 provides higher base average values and lower maximum annual average values than ETGLEAM. Temporal changes at the annual scale are similar for GLEAM, ERA5, and GLDAS datasets, but differences at seasonal and monthly time scales are identified. Some discrepancies are also recorded in ET spatial distribution, but generally, all datasets provide similarities, e.g., for humid regions basins. ETERA5 has a higher correlation with available energy than available water, while ETGLEAM has higher correlation with available water, and ETGLDAS does not correlate with none of these drivers. Based on the comparison of ETERA5 and ETGLEAM with ETwb, both have similar errors in spatial distribution, while ETGLDAS provided over and under estimations in northern and southern basins, respectively, compared to them (ETERA5 and ETGLEAM). All three datasets provide better ET estimates (values closer to ETWB) in hyper-arid and arid regions from central to eastern Iran than in the humid areas. Thus, the GLEAM, ERA5, and GLDAS datasets are more suitable for estimating ET for arid rather than humid basins in Iran.

show abstract

Section: Comparison Of Et Era5 Et Gleam and Et Gldas With Et Wb In ...mentioning

confidence: 89%

Spatio-Temporal Assessment of Global Gridded Evapotranspiration Datasets across Iran

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Regions with advanced agricultural practices, better infrastructure, and technology adoption tend to achieve higher productivity. Areas with lower yields might lack access to modern farming techniques or face limitations in implementing efficient agricultural methods [57] (Figures 13 and 14). Our study reveals that maize cultivation in Iran is influenced by factors like climate, soil, water, and farming practices, varying across regions.…”

Section: Discussionmentioning

confidence: 99%

Estimating Yield Response Functions to Nitrogen for Annual Crops in Iran

Aghabeygi,

Dönmez

2024

Agronomy

View full text Add to dashboard Cite

Nitrate is a crucial element for crop growth, and its optimal application is essential for maximizing agricultural yield. In Iranian agriculture, there is a substantial gap between recommended nitrate usage and what farmers actually apply. In this study, our primary objective is to determine the most effective utilization of nitrate for crop cultivation. Simultaneously, we aim to analyze the factors that contribute to the disparity between optimal and current nitrate application practices. Furthermore, our research explores the impact of these differences on regional variations in crop yields. This is achieved using a quadratic yield response function model based on unbalanced panel data spanning the years 2000 to 2016, which includes a total of 14 crop activities and encompasses 31 administrative regions. The results show that rice exhibits the highest nitrogen usage, while rain-fed wheat demonstrates the lowest utilization at the optimal point. Depending on whether random- or fixed-effects estimation is found to be the most suitable specification, average yields corresponding to the optimal level of nitrogen use are calculated by region, or the average across all regions. In Iran, the top-performing regions for cereals like rain-fed wheat and irrigated barley can achieve yields of 1.33 and 3 t/ha, respectively. These yields represent a 31% and a 9% increase from the levels observed in 2016. The outcomes derived from the estimated yield response function will be integrated into comprehensive agricultural, economic, and environmental optimization models. These integrated models will facilitate the assessment of various fertilizer policies on fertilizer use, land allocation, farm-household incomes, and environmental externalities, such as nitrate leaching and nitrate balance. This study holds substantial scientific promise, given its exploration of the policy implications surrounding fertilizer usage, making it crucial not only for Iran, but also for many developing nations grappling with inefficient and unsustainable agricultural practices. It represents the first of its kind in the literature, providing estimations of optimal nitrogen use and crop yield points across all regions in Iran. This is achieved through advanced visualization using GIS maps.

show abstract

“…Upon inferring that the freshness of the plants is insu cient, the farmer starts irrigation, so de cit irrigation is not considered. De cit irrigation is assumed to be an effective strategy for environmental conservation behavior (Montazar, 2021;UT et al, 2020), and can increase water productivity as well as farmers' pro t (Du et al, 2015;Fereres & Soriano, 2007;Karandish, 2021). While the extent of technical de cit irrigation can be assessed to nd out possible options for water conservation, it can be concluded that farmers do not incorporate de cit irrigation into their decision making process.…”

Section: Irrigation Decision Criteriamentioning

confidence: 99%

How do farmers' perceptions and attitudes toward agricultural water consumption behaviors can lead to unsustainability; evidence from Mahabad plain, Lake Urmia, Iran

Farahmand

Tajrishy

Isaai

et al. 2023

Preprint

View full text Add to dashboard Cite

There has been much attention paid to Lake Urmia's catastrophic desiccation by researchers and the government. An in-depth semi-structured interview and thematic analysis were used in this study to examine irrigation behavior and crop type selection decisions. 73% of farmers believe that there is no need to reduce their water consumption, 87% do not look for rain forecasts since they regard the government as responsible for water supply or have very few crop alternatives to choose from. In choosing the type of product, 77% only consider economics and do not consider environmental objectives, and 71% do not think drought conditions affect irrigation decisions. Educating farmers and increasing their collaboration role are therefore necessary. Therefore, these variables are the basis for extending psychological theories such as TPB to predict farmers' behavior to a much greater extent. While this study focused on one region, its findings are applicable to similar circumstances worldwide.

show abstract

Socioeconomic benefits of conserving Iran’s water resources through modifying agricultural practices and water management strategies

Cited by 13 publications

References 59 publications

Spatio-Temporal Assessment of Global Gridded Evapotranspiration Datasets across Iran

Spatio-Temporal Assessment of Global Gridded Evapotranspiration Datasets across Iran

Estimating Yield Response Functions to Nitrogen for Annual Crops in Iran

How do farmers' perceptions and attitudes toward agricultural water consumption behaviors can lead to unsustainability; evidence from Mahabad plain, Lake Urmia, Iran

Contact Info

Product

Resources

About