Towards Effective Drought Monitoring in the Middle East and North Africa (MENA) Region: Implications from Assimilating Leaf Area Index and Soil Moisture into the Noah-MP Land Surface Model for Morocco

Nie, Wanshu; Kumar, Sujay V.; Arsenault, Kristi R.; Peters‐Lidard, Christa D.; Mladenova, I. E.; Bergaoui, K.; Hazra, Abheera; Zaitchik, Benjamin F.; Mahanama, Sarith; McDonnell, Rachael; Mocko, David M.; Navari, Mahdi

doi:10.5194/hess-2021-263

Cited by 7 publications

(5 citation statements)

References 54 publications

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“…Our findings also showed how the Sentinel-1 γ 0 VV DA has a larger impact on the temporal dynamics of irrigation, whereas the VH polarization has a stronger influence in adjusting the bias, and one potential reason could be the high sensitivity of the vegetation to root-zone soil moisture and vice versa (Modanesi et al, 2021). Similar conclusions were obtained by Nie et al (2022) over Morocco. This recent study showed how the assimilation of MODIS LAI into Noah-MP v.4.0.1, with and without activating irrigation, provides critical information to improve the root-zone soil moisture and more generally water-energy-carbon fluxes.…”

Section: Data Assimilationsupporting

confidence: 82%

Challenges and benefits of quantifying irrigation through the assimilation of Sentinel-1 backscatter observations into Noah-MP

Modanesi

Massari

Bechtold

et al. 2022

Hydrol. Earth Syst. Sci.

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Abstract. In recent years, the amount of water used for agricultural purposes has been rising due to an increase in food demand. However, anthropogenic water usage, such as for irrigation, is still not or poorly parameterized in regional- and larger-scale land surface models (LSMs). By contrast, satellite observations are directly affected by, and hence potentially able to detect, irrigation as they sense the entire integrated soil–vegetation system. By integrating satellite observations and fine-scale modelling it could thus be possible to improve estimation of irrigation amounts at the desired spatial–temporal scale. In this study we tested the potential information offered by Sentinel-1 backscatter observations to improve irrigation estimates, in the framework of a data assimilation (DA) system composed of the Noah-MP LSM, equipped with a sprinkler irrigation scheme, and a backscatter operator represented by a water cloud model (WCM), as part of the NASA Land Information System (LIS). The calibrated WCM was used as an observation operator in the DA system to map model surface soil moisture and leaf area index (LAI) into backscatter predictions and, conversely, map observation-minus-forecast backscatter residuals back to updates in soil moisture and LAI through an ensemble Kalman filter (EnKF). The benefits of Sentinel-1 backscatter observations in two different polarizations (VV and VH) were tested in two separate DA experiments, performed over two irrigated sites, the first one located in the Po Valley (Italy) and the second one located in northern Germany. The results confirm that VV backscatter has a stronger link with soil moisture than VH backscatter, whereas VH backscatter observations introduce larger updates in the vegetation state variables. The backscatter DA introduced both improvements and degradations in soil moisture, evapotranspiration and irrigation estimates. The spatial and temporal scale had a large impact on the analysis, with more contradicting results obtained for the evaluation at the fine agriculture scale (i.e. field scale). Above all, this study sheds light on the limitations resulting from a poorly parameterized sprinkler irrigation scheme, which prevents improvements in the irrigation simulation due to DA and points to future developments needed to improve the system.

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Section: Data Assimilationsupporting

confidence: 82%

Challenges and benefits of quantifying irrigation through the assimilation of Sentinel-1 backscatter observations into Noah-MP

Modanesi

Massari

Bechtold

et al. 2022

Hydrol. Earth Syst. Sci.

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“…Therefore, irrigation is essential in the MENA region to sustain agricultural yield, land productivity, farmers' profit, and AVA. Irrigation is also a response to the growing worries about food and water securities, which are already strained (Nie et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

How to improve agricultural value-added in the MENA region? Implementation of Diamond Porter's theory in agriculture

Nugroho

Istvan²,

Fekete-Farkas³

et al. 2022

Front. Sustain. Food Syst.

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The global economy in recent decades has experienced frequent shocks. Many regions must improve their competitiveness and value-added to deal with this. One of them is in the Middle East and North Africa (MENA), where a rise in agricultural value-added (AVA) can produce more jobs than in other sectors. It is necessary to consider increasing AVA in the MENA region. Hence, the aim of this study is identifying the determinant factors of AVA in the MENA region. We employed 13 countries in the MENA region as samples in this study. The study's data spans 45 years, from 1975 to 2019. Static panel data regression analysis was employed in this study. AVA can growth by increasing the irrigated land, credit, and human capital. Meanwhile, growing inflation and economic globalization will reduce AVA. Therefore, we recommend that countries in the MENA region have to increase irrigation infrastructure, expand agricultural credit availability, encourage farmers to get a good education, improve research and development, control inflation, and find the best way to implement economic globalization.

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“…We used the dynamic phenology model within Noah-MP to account for plant processes that respond to cold, heat, and drought stresses 32 . The model simulates leaf area index due to senescence or herbivory.…”

Section: Methods and Data For CDI Productionmentioning

confidence: 99%

Development of a composite drought indicator for operational drought monitoring in the MENA region

Bergaoui,

Fraj,

Fragaszy

et al. 2024

Sci Rep

Self Cite

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This paper presents the composite drought indicator (CDI) that Jordanian, Lebanese, Moroccan, and Tunisian government agencies now produce monthly to support operational drought management decision making, and it describes their iterative co-development processes. The CDI is primarily intended to monitor agricultural and ecological drought on a seasonal time scale. It uses remote sensing and modelled data inputs, and it reflects anomalies in precipitation, vegetation, soil moisture, and evapotranspiration. Following quantitative and qualitative validation assessments, engagements with policymakers, and consideration of agencies’ technical and institutional capabilities and constraints, we made changes to CDI input data, modelling procedures, and integration to tailor the system for each national context. We summarize validation results, drought modelling challenges and how we overcame them through CDI improvements, and we describe the monthly CDI production process and outputs. Finally, we synthesize procedural and technical aspects of CDI development and reflect on the constraints we faced as well as trade-offs made to optimize the CDI for operational monitoring to support policy decision-making—including aspects of salience, credibility, and legitimacy—within each national context.

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Towards Effective Drought Monitoring in the Middle East and North Africa (MENA) Region: Implications from Assimilating Leaf Area Index and Soil Moisture into the Noah-MP Land Surface Model for Morocco

Cited by 7 publications

References 54 publications

Challenges and benefits of quantifying irrigation through the assimilation of Sentinel-1 backscatter observations into Noah-MP

Challenges and benefits of quantifying irrigation through the assimilation of Sentinel-1 backscatter observations into Noah-MP

How to improve agricultural value-added in the MENA region? Implementation of Diamond Porter's theory in agriculture

Development of a composite drought indicator for operational drought monitoring in the MENA region

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