Search Results (5)

Accurately selecting an appropriate probability distribution model is a critical challenge when predicting extreme rainfall in arid and semi-arid regions, especially in countries with diverse climatic conditions. This study presents a comprehensive methodology for evaluating rainfall probability distributions across Pakistan, and aims to create a probabilistic zoning map that could serve as a valuable resource to inform the development of strategies for efficient water resource management and improved flood resilience in diverse climatic and geographic conditions. Precipitation data from the Pakistan Meteorological Department (PMD) over 42 years were compared with CHIRPS, confirming their accuracy. Nine probability distributions were assessed, with five models—log Pearson type-III (LP3), Weibull (W2), log normal (LN2), Generalized Extreme Value (GEV), and gamma (GAM)—deemed most suitable for the region’s climatic variability. The spatial applicability of these distributions was identified as follows: LP3 (30%), LN2 (30%), W2 (15%), GEV (10%), and GAM (15%). The central and southern regions of Punjab were predominantly characterized by LN2, while GAM was prevalent in the coastal areas of Sindh. Balochistan exhibited a heterogeneous distribution of W2, LP3, and LN2, while the mountainous Gilgit-Baltistan region was exclusively associated with GEV. Khyber Pakhtunkhwa demonstrated a mix of GEV and LP3 distributions. Beyond provincial variations, distinct patterns emerged: GEV dominated high-altitude, cold-temperate areas; LP3 was common in mountainous regions with variable temperature profiles; and W2 was prevalent along the flood-prone Indus River. This study provides a robust framework for region-specific disaster preparedness and contributes to sustainable development initiatives by offering tailored strategies for managing extreme rainfall events across Pakistan’s diverse climatic zones. Full article

Joint multivariate distribution and calculation of return period are essential in enhancing drought risk assessment and promoting the sustainable development of water resources. Aiming to address the increasingly serious drought situation in the Yellow River Basin, this study first utilized the Soil and Water Assessment Tool (SWAT) distributed hydrological model combined with the Standardized Precipitation Evapotranspiration Index (SPEI), the Standardized Soil Moisture Index (SSMI), and the Standard Water Yield Index (SWYI); the duration, peak, and severity of meteorological, agricultural, and hydrological droughts were analyzed. Based on the selected copula function, a three-dimensional joint distribution of drought duration (D), drought severity (S), and maximum severity (M) was constructed. The corresponding copula joint probability was calculated, leading to the three-dimensional joint return period and concurrent return period of meteorological drought, agricultural drought, and hydrological drought. The findings reveal several key trends: (1) Meteorological drought intensifies over time. Although drought areas eased after the 1990s, the overall drought trend continues to rise. Agricultural drought has intensified in arid regions but eased in semi-humid areas after the 2000s. Hydrological drought was severe in the upstream regions during the 1990s but eased in the 2000s, while it was particularly severe in the midstream and downstream regions during the 2000s. (2) Meteorological droughts are more severe in arid and semi-arid temperate regions and milder in semi-humid cold temperate regions. Agricultural droughts are extreme in arid and semi-arid cold temperate regions. Hydrological drought events are fewer but more severe in semi-arid temperate regions and have the lowest probability of occurrence in semi-humid cold temperate regions. (3) The overall probability of the occurrence of meteorological drought is between 55.7% and 69%; that of agricultural drought is between 73.1% and 91.7%, and that of hydrological drought is between 66.9% and 84%. Drought risk assessment provides scientific references for the analysis of the uncertainty of water supply in the basin and the formulation of effective risk management strategies. Full article

Conservation agriculture (CA) is becoming increasingly attractive to farmers due to advantages such as lower production costs and less destruction of soil structures compared to the conventional tillage. The cultivars introduced for the conventional systems may not be suitable under CA environments, and newly adapted cultivars need to be developed. Accordingly, four separate field experiments were conducted over two cropping seasons (2018–2019 and 2019–2020) to study the agronomic performance of seven barley genotypes under three tillage systems: conventional tillage (full tillage with residue removed), reduced tillage (chisel plowing with residue retained) and CA system (no tillage with residue retained on soil surface). The genotypes were grown under rainfed conditions in two different agro-ecological regions (Kamyaran and Hosseinabad locations) in the west of Iran. Significant genotypic differences were observed for grain yield and yield components except 1000-kernel weight. The results of this study showed that rainfed barley genotypes under a CA system produced yields equal to, or better (0.7%) than, the conventional tillage; while reduced tillage system decreased their performance by 4.9%. Regarding genotype × tillage interaction, the barley genotypes Catalhuyuk 2001 and Bulbule positively interacted with conventional tillage and showed higher performance than other genotypes, whereas genotypes Çumra 2001, Ansar and Abidar expressed highest performance under CA system. Consequently, genotypes Bulbule, Catalhuyuk 2001 and Gumharriyet 50 outperformed the domestic performance and the amount of grain yield and showed the highest adaptation to the tested environments. The results of the present study could be useful to improve the efficiency of a CA system in rainfed cultivation of barley and open new windows for the cereal production in arid and semi-arid regions with food security concerns. Full article

Jojoba (Simmondsia chinensis) is a semi-arid, oil-producing industrial crop that have been widely cultivated in tropical arid region. Low temperature is one of the major environmental stress that impair jojoba’s growth, development and yield and limit introduction of jojoba in the vast temperate arid areas. To get insight into the molecular mechanisms of the cold stress response of jojoba, a combined physiological and quantitative proteomic analysis was conducted. Under cold stress, the photosynthesis was repressed, the level of malondialdehyde (MDA), relative electrolyte leakage (REL), soluble sugars, superoxide dismutase (SOD) and phenylalanine ammonia-lyase (PAL) were increased in jojoba leaves. Of the 2821 proteins whose abundance were determined, a total of 109 differentially accumulated proteins (DAPs) were found and quantitative real time PCR (qRT-PCR) analysis of the coding genes for 7 randomly selected DAPs were performed for validation. The identified DAPs were involved in various physiological processes. Functional classification analysis revealed that photosynthesis, adjustment of cytoskeleton and cell wall, lipid metabolism and transport, reactive oxygen species (ROS) scavenging and carbohydrate metabolism were closely associated with the cold stress response. Some cold-induced proteins, such as cold-regulated 47 (COR47), staurosporin and temperature sensitive 3-like a (STT3a), phytyl ester synthase 1 (PES1) and copper/zinc superoxide dismutase 1, might play important roles in cold acclimation in jojoba seedlings. Our work provided important data to understand the plant response to the cold stress in tropical woody crops. Full article

Although the net primary productivity (NPP) of arid/semiarid ecosystem is generally thought to be controlled by precipitation, other factors like CO₂ fertilization effect and temperature change may also have important impacts, especially in the cold temperate areas of the northern China, where significant warming was reported in the recent decades. However, the impacts of climate and atmospheric CO₂ changes to the NPP dynamics in the arid and semiarid areas of China (ASA-China) is still unclear, hindering the development of climate adaptation strategy. Based on numeric experiments and factorial analysis, this study isolated and quantified the effects of climate and CO₂ changes between 1980–2014 on ASA-China’s NPP, using the Arid Ecosystem Model (AEM) that performed well in predicting ecosystems’ responses to climate/CO₂ change according to our evaluation based on 21 field experiments. Our results showed that the annual variation in NPP was dominated by changes in precipitation, which reduced the regional NPP by 10.9 g·C/(m²·year). The precipitation-induced loss, however, has been compensated by the CO₂ fertilization effect that increased the regional NPP by 14.9 g·C/(m²·year). The CO₂ fertilization effect particularly benefited the extensive croplands in the Northern China Plain, but was weakened in the dry grassland of the central Tibetan Plateau due to suppressed plant activity as induced by a drier climate. Our study showed that the climate change in ASA-China and the ecosystem’s responses were highly heterogeneous in space and time. There were complex interactive effects among the climate factors, and different plant functional types (e.g., phreatophyte vs. non-phreatophyte) could have distinct responses to similar climate change. Therefore, effective climate-adaptive strategies should be based on careful analysis of local climate pattern and understanding of the characteristic responses of the dominant species. Particularly, China’s policy makers should pay close attention to climate change and ecosystem health in northeastern China, where significant loss in forest NPP has been triggered by drought, and carefully balance the ecological and agricultural water usage. For wildlife conservation, the drought-stressed grassland in the central Tibetan Plateau should be protected from overgrazing in the face of dramatic warming in the 21st century. Full article