Mapping Drought Risk (Rice) of the World

Zhang, Xingming; Lin, Degen; Guo, Hao; Wu, Yaoyao; Wang, Jing’ai

doi:10.1007/978-3-662-45430-5_13

Cited by 3 publications

(2 citation statements)

References 3 publications

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“…In our previous studies, EPIC was used to simulate "Drought hazard-Crop yield loss" vulnerability curves to assess the drought risk of different crops (maize [67], wheat [68], and rice [69]). This study has proposed a new method for assessing vulnerability quantitatively and continuously by including the environment variable as an additional perspective on exposure.…”

Section: Discussionmentioning

confidence: 99%

Drought Risk Assessment Based on Vulnerability Surfaces: A Case Study of Maize

et al. 2016

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Abstract:Agriculture is a sector easily affected by meteorological conditions. Crop yield reduction, even regional conflicts, may occur during a drought. It is extremely important to improve the state of our knowledge on agricultural drought risk. This study has proposed a new method (vulnerability surfaces) for assessing vulnerability quantitatively and continuously by including the environmental variable as an additional perspective on exposure and assessed global maize drought risk based on these surfaces. In this research, based on the Environmental Policy Impact Climate (EPIC) model, irrigation scenarios were adopted to fit "Loss rate-Drought index-Environmental indicator (L-D-E)" vulnerability surfaces by constructing a database suitable for risk assessment on a large scale. Global maize drought risk was quantitatively assessed based on its optimal vulnerability surface. The results showed an R 2 for the optimal vulnerability surface of 0.9934, with coarse fragment content as the environmental indicator. The expected global average annual yield loss rate due to drought was 19.18%. The global average yield loss rate due to drought with different return periods (10a, 20a, 50a, and 100a) was 29.18%, 32.76%, 36.89%, and 38.26%, respectively. From a global perspective, Central Asia, the Iberian Peninsula, Eastern Africa, the Midwestern United States, Chile, and Brazil are the areas with the highest maize drought risk. The vulnerability surface is a further development of the vulnerability curve as a continuous expression of vulnerability and considers differences in environmental factors. It can reflect the spatial heterogeneity of crop vulnerability and can be applied in large-scale risk assessment research.

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Section: Discussionmentioning

confidence: 99%

Drought Risk Assessment Based on Vulnerability Surfaces: A Case Study of Maize

et al. 2016

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“…Spatially distributed modeling of the EPIC model, especially of the GEPIC model, has been successfully applied, calibrated, and validated in global gridded scale for wheat yield [44], maize [67], rice [68], crop water productivity, and drought risk assessment [44] in Sub-Saharan Africa [69], in country scale, in China [70], and in regional scale in Jordan River Basin [71], and in Karla Basin, Greece [53]. The PEPIC model has been also successfully applied in global scale for nitrogen losses [66].…”

Section: Nitrate Leaching Simulation Model Descriptionmentioning

confidence: 99%

An Integrated Modeling System for the Evaluation of Water Resources in Coastal Agricultural Watersheds: Application in Almyros Basin, Thessaly, Greece

Lyra

Λουκάς

Sidiropoulos

et al. 2021

Water

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This study presents an integrated modeling system for the evaluation of the quantity and quality of water resources of coastal agricultural watersheds. The modeling system consists of coupled and interrelated models, including (i) a surface hydrology model (UTHBAL), (ii) a groundwater hydrology model (MODFLOW), (iii) a crop growth/nitrate leaching model (REPIC, an R-ArcGIS-based EPIC model), (iv) a groundwater contaminant transport model (MT3DMS), and (v) a groundwater seawater intrusion model (SEAWAT). The efficacy of the modeling system to simulate the quantity and quality of water resources has been applied to the Almyros basin in Thessaly, Greece. It is a coastal agricultural basin with irrigated and intensified agriculture facing serious groundwater problems, such as groundwater depletion, nitrate pollution, and seawater intrusion. Irrigation demands were estimated for the main crops cultivated in the area, based on precipitation and temperature from regional weather stations. The models have been calibrated and validated against time-series of observed crop yields, groundwater table observations, and observed concentrations of nitrates and chlorides. The results indicate that the modeling system simulates the water resources quantity and quality with increased accuracy. The proposed modeling system could be used as a tool for the simulation of water resources management and climate change scenarios.

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Assessment of Irrigation Performance in Large River Basins under Data Scarce Environment—A Case of Kabul River Basin, Afghanistan

Akhtar

Awan²,

Tischbein

et al. 2018

Remote Sensing

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Abstract:The Kabul River basin (KRB) of Afghanistan, a lifeline of around 10 million people, has multiplicity of governance, management, and development-related challenges leading to inequity, inadequacy, and unreliability of irrigation water distribution. Prior to any uplifting intervention, there is a need to evaluate the performance of irrigation system on a long term basis to identify the existing bottlenecks. Although there are several indicators available for the performance evaluation of the irrigation schemes, we used the coefficient of variation (CV) of actual evapotranspiration (ET a ) in space (basin, sub-basin, and provincial level), relative evapotranspiration (RET), and temporal CV of RET, to assess the equity, adequacy, and reliability of water distribution, respectively, from 2003 to 2013. The ET a was estimated through a surface energy balance system (SEBS) algorithm and the ET a estimates were validated using the advection aridity (AA) method with a R 2 value of 0.81 and 0.77 at Nawabad and Sultanpur stations, respectively. The global land data assimilation system (GLDAS) and moderate-resolution imaging spectroradiometer (MODIS) products were used as main inputs to the SEBS. Results show that the mean seasonal sub-based RET values during summer (May-September) (0.37 ± 0.06) and winter (October-April) (0.40 ± 0.08) are below the target values (RET ≥ 0.75) during [2003][2004][2005][2006][2007][2008][2009][2010][2011][2012][2013]. The CV of the mean ET a , within sub-basins and provinces for the entire study period, has an equitable distribution of water from October-January (0.09 ± 0.04), whereas the highest inequity (0.24 ± 0.08) in water distribution is during early summer. The range of the CV of the mean ET a (0.04-0.06) on a monthly and seasonal basis shows the unreliability of water supplies in several provinces or sub-basins. The analysis of the temporal CV of mean RET highlights the unreliable water supplies across the entire basin. The maximum ET a during the study period was estimated for the Shamal sub-basin (552 ± 43 mm) while among the provinces, Kunar experienced the highest ET a (544 ± 39 mm). This study highlights the dire need for interventions to improve the irrigation performance in time and space. The proposed methodology can be used as a framework for monitoring and implementing water distribution plans in future.

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Mapping Drought Risk (Rice) of the World

Cited by 3 publications

References 3 publications

Drought Risk Assessment Based on Vulnerability Surfaces: A Case Study of Maize

Drought Risk Assessment Based on Vulnerability Surfaces: A Case Study of Maize

An Integrated Modeling System for the Evaluation of Water Resources in Coastal Agricultural Watersheds: Application in Almyros Basin, Thessaly, Greece

Assessment of Irrigation Performance in Large River Basins under Data Scarce Environment—A Case of Kabul River Basin, Afghanistan

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