Characteristics of droughts in Argentina's core crop region

Abstract

Abstract. This study advances the understanding and impacts of dry episodes on wheat, corn, and soybean yields over Argentina's core crop region. The production of these major crops is intense and is the main contribution to the country's gross domestic product. Our analysis focuses on the droughts' properties, including their magnitude, frequency at different timescales, duration, and severity. We analyzed 40 years of precipitation and soil moisture anomalies and their corresponding nonparametric standardized indices at timescales of 1, 3, and 6 months. The climate variables were complemented with 40 years of the crops' yield data. The percentage of drought occurrence in northeastern Argentina ranges between 12 % and 18 %, with the larger values located towards the core crop region's eastern–northeastern sector. An analysis of drought duration suggests that most cases tend to occur for periods shorter than 3 months, while a few can extend up to 1 year, and even fewer can last longer. More importantly, regardless of the duration, droughts have larger impacts during the crops' critical growth period. Corn and soybean have their critical growth periods during summer and are more sensitive to precipitation and soil moisture deficits than wheat, which has its critical growth period during spring. Quantification of the relation between the droughts' indicators during the crops' critical periods and detrended annual crop yields was performed. Large drought severity values during the crop-sensitive months result in significant crop yield losses. Results suggest that shorter-scale indicators during sensitive periods are more appropriate for predicting crop yield losses than the longer-scale indicators. This new approach can be helpful for regional decision-making systems that support planning by water managers and agricultural stakeholders.

Extreme precipitation events in the Austral Chaco region of Argentina

“…The outputs of Equation ( 1) are then transformed into SPI applying the inverse of the standard normal distribution function (;): Sen , 2003). SPI values on a 3-month time scale (SPI3) reflect wet or dry conditions for short to intermediate periods and provide climate estimates for critical growth stages of crops (Sgroi et al, 2021). SPI9 provides interseasonal information; it is useful to represent hydrological drought/wetness (Lloyd-Hughes and Saunders, 2002).…”

“…One of such regions is southeastern South America (SESA)-which includes northern Argentina, Uruguay, southern Brazil, and Paraguay (Magrin et al, 2014). In SESA, droughts and floods caused by extreme precipitation events produce large economic losses; two iconic examples have been the extraordinary flood of the Paran a River in 1983 Barros, 2000, 2003) and the extended and persistent drought of 2008(Müller et al, 2014Sgroi et al, 2021). Furthermore, extreme climate events have increased in frequency and intensity in SESA during the past decades (Cavalcanti et al, 2015;Carril et al, 2016;Avila-Diaz et al, 2020).…”

“…More frequent heavy precipitation events constitute a magnifying risk for urban settlements and agriculture, and cause significant infrastructure losses and decreased livestock productivity (Barros et al, 2015;Lovino et al, 2018a, b). On the other hand, longer dry events in recent decades suggest that more persistent short-term droughts affect agricultural activities (Llano and Penalba, 2010;Sgroi et al, 2021).…”

Genetic control of tolerance to drought stress in soybean

“…] is the most grown-high value legume crop, and delivers a large part of the increasing demand for protein and oil in the world [5]. Drought stress has been identified as one of the challenges limiting soybean production in different parts of the world [6][7][8][9]. Therefore, breeding soybean for drought tolerance is imperative to avoid yield losses [10].…”

Monitoring Meteorological Drought in Southern China Using Remote Sensing Data

“…This indicator is used in daily business by the departments of the China Meteorological Administration, and it can assess monthly, seasonal, and annual drought events. The anomalies of soil moisture, vegetation, and temperature are also widely used in many studies [27][28][29][30][31][32][33][34], and they are collectively referred to as the Anomalies Percentage (AP).…”