Sub-humid Regions Research Articles

Mapping of Sediment and Water Resources of Nadia District, West Bengal, India for Freshwater Aquaculture Management Practices

Present study relates to the fish growth, optimization and profitable fish production through pond sediment and water resources maps on sustainable basis. ALl blocks of Nadia district of West Bengal comprising of hot moist sub-humid agro-ecological region were thoroughly surveyed and physico-chemical characteristics of pond water and sediments were analysed. Based on the sediment and pond water resources an improved the fertilizer and manure management schedule, as well as maps have been prepared and demonstration of carp polyculture were carried out. All the fish species attained higher growth in the ponds of hot moist sub-humid agro-ecological regions (alluvial soils) following new nutrient management map over control. The average total fish production in experimental and control ponds was 5.184 and 3.095 tonnes/ha/yr, respectively.

A framework for identifying propagation from meteorological to ecological drought events

Drought severely affects vegetation growth owing to its multidimensional characteristics (e.g. duration and severity). However, current studies regarding the propagation of meteorological to ecological drought are not investigated well from an event-scale perspective. Therefore, a framework for identifying the propagation relationship between meteorological and ecological drought at an event scale is proposed. The gross primary productivity (GPP) and standardized precipitation evapotranspiration index are used to characterize ecological and meteorological drought, respectively. The pooling of ecological drought events (GPP anomalous events, GAs) and the exclusion of meteorological drought events (MDs) are considered in the framework. Matching events between these two types of droughts are identified, and their propagation characteristics are analyzed. The framework is tested in the Yangtze River Basin (YRB). The main results are as follows: (1) The propagation time from meteorological to ecological drought in the YRB varied from 1 to 48 months, with significant spatiotemporal heterogeneity; (2) Four propagation types from meteorological to ecological drought are identified: multiple MDs trigger a GA (MTO), an MD triggers multiple GAs (OTM), an MD triggers a GA (OTO), and multiple MDs trigger multiple GAs (MTM), which constituted 16.17%, 11.32%, 55.57%, and 16.94% of the total matching events, respectively. Most of these events occur in semiarid and subhumid regions. In addition, OTO typically occurs throughout the YRB. (3) For the four matching types, the average duration (or severity) of MDs (or GAs) is in the order of MTM > OTM > MTO > OTO. For MTM and OTM, the duration of MD is longer (more severe) than that of the GA caused by it, and a more significant linear relationship is indicated (R2>0.7), whereas the opposite is observed for OTM and OTO.

Modelling and Assessment of Climate Change Impact on Rainfed Rice Cultivation in a Sub-humid Subtropical Region

Modelling and Assessment of Climate Change Impact on Rainfed Rice Cultivation in a Sub-humid Subtropical Region

Loss of Net primary production of seasonal winter wheat due to multiple drought types in the main Grain-Producing area of China

Droughts have a severe impact on ecosystems and food security. Net primary production (NPP), a critical component of the carbon cycle of an ecosystem, is strongly associated with crop yield and serves as an indicator of drought impact. In the present study, the loss of NPP in seasonal winter wheat was evaluated through an analysis of the changes in frequency and probability of exceeding NPP loss. This study also analyzed the drought thresholds for various types of drought, namely meteorological drought (MD), natural agricultural drought (NAD), and actual agricultural drought (AAD), in the North China Plain (NCP). The standardized precipitation evapotranspiration index, Palmer Drought Severity Index, and Vegetation Health Index were used to define these drought categories. The study findings reveal that although the NCP has experienced increased dryness, the severity of AAD has decreased. Within the study period, the frequency of winter wheat NPP loss due to drought in the area was within the range of 30% to 40%, with higher sensitivity to drought occurring during the middle growth period of winter wheat and in the NCP’s dry subhumid region. The highest probability of NPP loss was observed in March in the humid and dry subhumid regions of the NCP and in April in the semiarid region. Farmers in the NCP can effectively cope with extreme loss caused by drought. However, they have less experience with handling mild and moderate losses, which were the primary forms of NPP loss during the study period, particularly in the semiarid region. To ensure NPP can be sustained at a normal level or increased, MD and AAD must be prevented during the growing period of winter wheat, and NAD in the semiarid region must be managed to ensure its effects remain mild. Furthermore, farmers’ management of AAD may lead winter wheat to have a higher tolerance to MD and NAD. Our results deepen the understanding of seasonal NPP loss in winter wheat due to different types of drought, providing practical assistance to farmers in the region.

Morphological characteristics and dynamic changes of typical climbing dunes on the Qinghai-Tibet Plateau

Climbing dunes are a form of topographic barrier dunes that feature in the aeolian landforms on the Qinghai-Tibetan Plateau. Topography fundamentally influences the spatial distribution and morphological characteristics of climbing dunes by modifying the near-surface airflow and creating space for sediment deposition. Previous studies have considered several aspects of the influence of topography on aeolian landforms. However, morphological differences between climbing dunes in different geomorphic contexts and dynamic changes in the area have received little attention. Therefore, topographic measurements, near-surface flow field measurements, dune morphology analysis, and remote sensing image analysis were combined to explore relationships between dune morphology and topography. Topographic obstacles can accelerate the near-surface airflow, particularly with a 25–35° slope gradient, which is beneficial for sand transport and deposition. Suitable accommodation space (concave slope morphology) and abundant sediment comprise the primary factors that control the scale and morphological diversity of climbing dunes, which are also influenced by a variable wind direction. In general, the morphology of the climbing dunes becomes progressively more complicated from the bottom to the middle of the windward slope, and the sand ridge lines of the dunes are perpendicular to the prevailing wind direction. Based on the influence of climate and human activities, the total area of climbing dunes in this region has decreased over the past 30 years. Despite general evidence of enhanced human-induced desertification in semi-arid and sub-humid regions, warming has not led to the rapid expansion of climbing dunes in these arid locations. This research offers new insights into the relationship between the terrain and dune morphology, enriching the theoretical basis for the plateau aeolian geomorphology. Furthermore, it allows us to consider the dynamic changes in climbing dunes area in the context of global warming.

Leguminous species at distinct planting densities and rainfed coconut intercropping for green manuring in sandy soil of sub-humid region

Leguminous species at distinct planting densities and rainfed coconut intercropping for green manuring in sandy soil of sub-humid region

Effect of eucalyptus on blue and green water availability and discharge in the tropical highlands: An interpretation of available literature

Abstract The highlands serve as water towers for the blue water in the surrounding area, with often insufficient rainfall for rainfed crops. The population is growing in the highlands, changing the hydrology and blue and green water availability. One of the changes that affect the highlands of Ethiopia is the rapidly expanding areas of small patches of eucalyptus on farmers fields. This manuscript aims to sort through the limited available literature and develop a water balance model as a starting point to discuss how hydrology is affected by increased acreage of eucalyptus in the highlands. We find some evidence in the literature that patches of eucalyptus during the dry phase may withdraw water from the subsoil up to twice the rate of evapotranspiration when the soil water is not limited. Since saturation excess generates surface runoff in the subhumid and humid highlands, water withdrawn during the dry phase should be made up before the area with eucalyptus becomes hydraulically active. The amount of water that can be removed from storage by eucalyptus is greater in areas with a long dry monsoon phase than in temperate climates for the same increase in trees. We also found, as expected, that the eucalyptus water balance model, as developed in this paper, was not valid for areas in semi-arid and arid regions. Soil crusting and water repellency might induce infiltration excess runoff. A tentative implication is that since most blue water is produced in the areas with the highest rainfall, eucalyptus in subhumid and humid monsoon regions will affect the blue water supply downstream but not the plant available green water although shading will decrease yield in the immediate surroundings of the eucalyptus trees.

Long-term effect of manuring-fertilization on nutrients availability and yield under rice (Oryza sativa)-lentil (Lens culinaris) system

Soil health degradation is a major threat in agricultural sustainability specially under rainfed agriculture. The purpose of this study was to assess the impact of long-term fertilization and manuring on soil organic carbon, nutrient status, uptake and yield trends under a rainfed rice (Oryza sativa L.)-lentil (Lens culinaris L.) cropping system situated at Agriculture Research Farm of Banaras Hindu University, Varanasi, Uttar Pradesh. Soil samples were collected in 2019 and 2021 after harvesting of rainy (kharif) season rice from 34 years old long-term experiment with rice-lentil cropping system of dry sub-humid region of India and analysed for various pools of SOC, nutrients availability, uptake and yield attributes. Results showed that 50% NPK+FYM treatment significantly influenced soil organic carbon pools and improved macronutrients (Nitrogen, Phosphorus, Potassium), microbial biomass carbon and dehydrogenase activity in soil as compared to the control. In addition, the integrated application of farmyard manure and inorganic fertilizers significantly enhanced the nutrient uptake, productivity of rice and lentil, and maintained the nutrient balance in the soil. Therefore, the balanced use of inorganic fertilizer along with organic manure may be recommended for maintaining soil health and crop productivity under subtropical India.

Seasonal variation and controlling factors of carbon balance over dry semi-humid cropland in Guanzhong Plain

A theoretical basis for optimizing mitigation and adaptation to future climate change can be obtained by determining the carbon balance and their control mechanism in agroecosystems. To better understand summer maize (Zea mays L.)/winter wheat (Triticum aestivum L.) agroecosystems in dry semi-humid carbon balance mechanism, we conducted an in-depth analysis of three-year (2019.6–2022.6) seasonal dynamics of carbon fluxes and their driving factors in summer maize/winter wheat cropland in the Guanzhong Plain combined with path analysis. The results showed that net radiation (Rn) was the main direct controlling factor of the net ecosystem exchange (NEE) in the summer maize growing season, followed by leaf area index (LAI). However, LAI was the main factor controlling the seasonal variation of NEE in the winter wheat growing season, followed by Rn. Furthermore, LAI was the dominant direct driving factor for the gross primary productivity (GPP) in the summer maize and winter wheat growing seasons. In addition, LAI was the dominant driving factor for the total ecosystem respiration (TER) in the summer maize season, while Rn (indirect effect) and LAI (direct effect) were the main controlling factors of TER in the winter wheat season. The NEE values of the summer maize system, winter wheat system, and summer maize/winter wheat system in the study area were from 119 to 221, − 601 to − 595, and − 433 to − 291 g C m−2, respectively (the net biological production (NBP) were − 709 to − 437, 220–303, and − 496 and − 260 g C m−2, respectively). Notably, the average carbon emission rate of the summer maize/winter wheat agroecosystem in the Guanzhong Plain, considering the carbon output at harvest is 386.2 g C m−2year−1. Therefore, this study may guide assessment of carbon balance of agroecosystems in dry sub-humid regions, and provide a strong reference for achieving carbon neutrality in local agroecosystems.

Phytoremediation of heavy metals (Cr and Pb) from sewage irrigated soil of tropical sub-humid region of Indo-Gangetic plain using Amaranthus viridis

This study was conducted to find out the potential of Amaranthus viridis for the phytoremediation of heavy metals (Cr and Pb) grown on sewage irrigated site. The status of heavy metals in sewage irrigated soil was observed as Pb 4.91±0.96 mg/kg and Cr 3.48±0.51 mg/kg maximum in Buxibandh site and minimum concentration 2.11 0.19 mg/kg and Cr 1.82±0.19 mg/kg in Phaphamau sites. A. viridis grown on a sewage irrigated soils recorded maximum accumulation of Cr ranging from 4.23 0.28-4.11 0.15 mg/kg and minimum concentration 2.52±0.05–2.34±0.05 mg/kg in Buxibandh and Phaphamau respectively and maximum accumulation of Pb 4.4±10.52–4.27±0.39 mg/kg and minimum accumulation 2.89±0.04–2.43±0.06 mg/kg in root and shoot, respectively. The result shows the maximum potential of accumulation Pb 4.41±0.52 mg/kg followed by Cr 4.23±0.28 mg/kg in Buxibandh sewage irrigated site. The maximum dry biomass yield of A. viridis plants was recorded in Phaphamau sewage irrigated site of Cr and Pb sewage irrigated soils ranging 3.8±0.5–4.9±0.7 g/plant and 36±5–39±4.4 g/plant, respectively, while the minimum dry biomass yield as 2.5±0.4–2.8±0.4 g/plant and 26±1.2–28±3.9 g/plant in shoot and root, respectively, at Buxibandh sewage irrigated site. The accumulation of heavy metals hampered plant development and nutrients bioavailability. Furthermore, their bioconcentration factor (BCF) and translocation factor (TF) greater than 1.0 indicated the hyperaccumulation efficiency of plants ranges of Cr and Pb was recorded 1.33±0.04–1.06±0.05 mg/kg and 1.03±0.02–1.12±0.1 mg/kg, respectively. The result proved that the A. viridis had a great potential to remove heavy metals from sewage irrigated soils.

Study on the Diversity of Genotypic Varieties of Durum Wheat (Triticum Durum Desf.) In the Sub-Humid Region of El Harrouch, Algeria

The study on the yield parameters and the morpho-biometric characterization of twenty genotypic varieties of durum wheat (Triticum durum Desf.) was carried out in the sub-humid region of El Harrouch of Algeria. A descriptive sheet according to the recommendations of UPOV (2014-2017) and the calculation of the Shannon and Weaver diversity index was prepared with 27 qualitative characters and one quantitative character relating to the different parts of the ear. The yield parameters, such as number of plants/m2, herbaceous tillers, ear tillers, number of ears/m2, number of grains/ear, weight of 1000 grains, grains yield, harvest index, areal biomass, economic yield and straw yield showed a great diversity among these varieties. The Shannon and Weaver index (H') revealed a great diversity of all the studied genotypes (H'=0.52). The high polymorphic characters were the shape of the shoulder of the lower glume (H'=1), the curvature of the beak of the lower glume (H'=0.9), the length of the rachis of the ear (H'=0.87), the disposition barbs (H'=0.86), the length of the hairs of the grain brush (H'=0.84), the hairiness of the first article of the rachis of the ear (H'=0.84) and the length of the first article of the ear (H'=0.81). Based on study result, the varieties suitable to this agro-ecological conditions could be chosen for this region. It is concluded that the creation of descriptive sheets, the knowledge of production and adaptation parameters could be considered as precursors of high yield for economic needs and mastery of production techniques in improvement programs. J. Biodivers. Conserv. Bioresour. Manag. 2023, 9(1): 41-60

Assessment of the impact of irrigation management on soybean yield and water productivity in a subhumid environment

As an effect of climate change, a considerable increase in irrigation demand is expected in subhumid regions. This poses a future challenge for agriculture, which often does not meet the requirements for highly efficient irrigation management. Field experiments in combination with modelling approaches can help in the development and evaluation of alternative irrigation strategies. The aim of this study was to parameterize the FAO AquaCrop model for soybeans in order to evaluate irrigation systems and strategies used by farmers in Austria. Moreover, this study aims at proposing a deficit irrigation strategy to increase irrigation water productivity (WPIrrig). Three irrigation methods were investigated: sprinkler, drip, and hose reel boom. Rainfed conditions were also assessed. Data sets from 2018 and 2019 were used for the parameterization of AquaCrop. Based on threshold values for the percentage of readily available water (RAW), full and deficit irrigation strategies were defined and tested for the years 1990–2019. The parameterization results showed good agreement between the simulated and observed canopy cover and yields from the four water management practices, with Nash-Sutcliffe efficiency coefficients between 0.76 and 0.96. Large errors resulted from the soil water content simulations, mainly due to poor sensor performance. It was concluded that a moderate deficit with RAW thresholds of 150% and 140% for the vegetative and reproductive stages, respectively, was an adequate strategy to improve yields and WPIrrig. Conversely, a severe deficit with an irrigation threshold of 180% RAW throughout the season considerably reduced yields, especially in years with high irrigation demand. Moreover, a significant improvement in WPIrrig was observed when drip systems were used compared to sprinklers, due to the higher efficiency of the former. These results can help scheduling irrigation for soybeans and increasing WPIrrig, thereby reducing pressure on limited water resources.

Prioritizing Tree-Based Systems for Optimizing Carbon Sink in the Indian Sub-Himalayan Region

Land use of the sub-Himalayan region is not that intensive like the intensively land-managed region of Punjab, India. Land resources of the sub-Himalayas must be managed effectively for sustainable development by preparing carbon inventories and data banks. Such macro-level studies have not been conducted yet in the present study area, and thus were conducted to suggest sustainable land use management options. To achieve the present study’s desired goal, 33 tree-based land uses were identified from forested and agricultural landscapes of the sub-humid tropical region of West Bengal, India. Stratified random nested quadrat sampling was adopted for the study. The SOC, biomass, and carbon accumulation significantly differed. Mixed forests had the highest soil primary nutrients and carbon stock. Positive correlations were observed between SOC, total standing biomass, litter production, and ecosystem carbon. The sequence of land uses based on carbon stock was mixed-species forest > sole tree species stands in a forest landscape > tea plantations > homegardens. This baseline information can be used for developing prediction models for future interventions towards sustainable land management. The study, however, could not estimate the carbon fluxes in and out of the systems due to the absence of detailed land use land-cover databases.

Observed Changes in Rainfall and Characteristics of Extreme Events in Côte d’Ivoire (West Africa)

This study evaluates how the characteristics of daily rainfall and extreme events in Côte d’Ivoire changed during 1961–2015 using the rain gauge observation network of the National Meteorological Service (SODEXAM). The results indicate that the northern and southern parts of Cote d’Ivoire experienced a change from a wet to a dry period, with cut-offs in 1982 and 1983, respectively. In the northern part, this dry period was marked by a decrease in rainfall intensity, the length of wet spells, and the contribution of heavy and extreme rainfall, as well as an increase in the number of rainy days and a decrease in the length of dry spells. Over the southern part, this dry period was marked by an increase in the maximum length of dry spells associated with an increase in the maximum 1-day and 5-day precipitation events. The western part of Côte d’Ivoire experienced a late cut-off from the wet to dry period in 2000; the dry period was associated with a decrease in the number of rainy days, rainfall intensities, and maximum length of wet spells. Changes in the central part of Cote d’Ivoire presented high variability, and trends were less marked, even though a cut-off from a wet to dry period was detected in 1991. This study shows that Côte d’Ivoire, which is located in a subhumid and humid region and has an economy dependent on agriculture (especially cash crops, which comprise 60% of the GDP), is experiencing dry spells that are increasing in frequency and length. Combined with deforestation to increase production, this situation could lead to desertification and compromise the sustainable development goals of the country. The contribution of heavy rainfall was found to increase during the last 15 years, increasing the overall risk of floods, especially in urban areas where city authorities and populations are not prepared, thereby threatening infrastructure and human security.

The Afrotropical breeding grounds of the Palearctic-African migratory painted lady butterflies (Vanessa cardui)

Migratory insects are key players in ecosystem functioning and services, but their spatiotemporal distributions are typically poorly known. Ecological niche modeling (ENM) may be used to predict species seasonal distributions, but the resulting hypotheses should eventually be validated by field data. The painted lady butterfly (Vanessa cardui) performs multigenerational migrations between Europe and Africa and has become a model species for insect movement ecology. While the annual migration cycle of this species is well understood for Europe and northernmost Africa, it is still unknown where most individuals spend the winter. Through ENM, we previously predicted suitable breeding grounds in the subhumid regions near the tropics between November and February. In this work, we assess the suitability of these predictions through i) extensive field surveys and ii) two-year monitoring in six countries: a large-scale monitoring scheme to study butterfly migration in Africa. We document new breeding locations, year-round phenological information, and hostplant use. Field observations were nearly always predicted with high probability by the previous ENM, and monitoring demonstrated the influence of the precipitation seasonality regime on migratory phenology. Using the updated dataset, we built a refined ENM for the Palearctic-African range of V. cardui. We confirm the relevance of the Afrotropical region and document the missing natural history pieces of the longest migratory cycle described in butterflies.

Future changes of dry‐wet climate regions and its contributing climatic factors in China based on CMIP6 models

AbstractUnderstanding future dry and wet changes under global climate change is of great regional significance in China. Based on six Global Climate Models (GCM) from the Coupled Model Intercomparison Project phase 6 (CMIP6), we project the changes of dry‐wet climate regions in China in the 21st century under the three SSP‐RCP (shared socioeconomic pathway‐representative concentration pathway) scenarios (SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5), and further identify the key climatic factors that lead to the transition of dry‐wet climate regions. The results show the area of humid and subhumid regions in China will show an upward trend in the future, while the area of semiarid and arid regions will show a downward trend. Especially under the SSP5‐8.5 scenario, the area of the subhumid region has the largest increase trend (0.042% per year), and the area of the arid region has the largest decline trend (−0.048% per year). The three main transfer directions of dry‐wet climate regions are from arid to semiarid regions, from semiarid to subhumid regions, and from subhumid to humid regions in the future. Due to the future extensive wetting trend in the north, the future dry‐wet climate regions will shift to wetter types in Tibet, North China, the Qinling‐Huaihe regions and the northeast. In addition, the key climatic factors for the transition of dry‐wet climate regions are mainly precipitation, maximum temperature and solar radiation. The increase of precipitation plays a dominant role for areas projected to change to wetter types, and the increase of potential evapotranspiration (PET) plays a dominant role for areas projected to change to drier types. The PET changes in changed areas of dry‐wet climate regions are mainly dominated by maximum temperature and solar radiation. Our research has important implications for future water resource management and reconsideration of climate mitigation and adaptation policies.

Temporal remote sensing based soil salinity mapping in Indo-Gangetic plain employing machine-learning techniques

Soil salinization is one of the most active land degradation processes, affecting predominantly arid, semi-arid, and dry sub-humid regions and leading to decreased agricultural yields. The Indo-Gangetic plain, which includes the irrigated command areas with arid and semi-arid climatic conditions are severely affected by secondary soil salinization. Assessing the spatial and temporal extent as well as the severity of salinization is an important step for adoption of proper reclamation measures to boost agricultural productivity in the salt affected areas. The study was conducted with this background to evaluate the extent and severity of soil salinization in alluvial plains of Mathura district of Uttar Pradesh, India. In this study, the satellite data of 6 months from January 2019 to June 2019 were pre-processed and various spectral indices were generated in Google Earth Engine. Remote sensing techniques provides an ideal platform for addressing this problem at larger scales and thus we employed Sentinel-2 derived vegetation and salinity spectral indices for distinguishing temporal change in severity of soil salinization and map the salinity as a function of these indices for the entire study area. The time series salinity analysis showed that among the various spectral indices Ratio Vegetation Index (RVI), Normalized Difference Vegetation Index (NDVI) and Normalized Difference Soil Index (NDSI) had a clear differentiation between slight, moderate and severe salinity class in the first three months of the study period and the Salinity Index II (SI_II) could differentiate for the first four months. Further, two machine learning algorithms namely Random Forest (RF) and Support Vector Machine (SVM), were used to create soil salinity prediction models making use of the soil Electrical Conductivity (EC) values of 115 ground-sampling sites as the predictand variable and the optimal spectral indices as the predictor variables. Further, we evaluated the prediction ability of different models using 12 and 24 variables combination using R2 and RMSE values. The prediction accuracy of the RF model was found to be slightly higher than that of the SVM model, and the spatial distribution pattern of soil salinity predicted by the two models were comparable. We concluded that spectral indices combined with machine learning techniques have the potential for low cost reliable spatial and temporal soil salinity distribution mapping for planning and implementation of salinity reclamation measures.

Soil quality index as affected by long-time continuous cultivation in a Mediterranean sub-humid region

Evaluating the Soil Quality Index (SQI affected by continuous and long-term cultivation operations to identify the threat of soil destruction and its controlling is a severe challenge. The current study has investigated the effects of cultivation operations on SQI in a wide area (37,524 ha), and with various types of soil (three soil orders including Inceptisols, Mollisols, and Vertisols) and the record of several decades of wheat cultivation. After determining the total data set (TDS) and minimum data set (MDS), the SQI was calculated using Integrated Quality Index (IQI) and Nemoro Quality Index (NQI) models. The results showed that most soil indicators (e.g., electrical conductivity, sodium adsorption ratio, organic carbon, and bulk density) were negatively affected by long-term cultivation operations. Compared to the control soils, the values of IQI-T, NQI-T, IQI-M, and NQI-M had been decreased ranging from 17 to 24%, 20 to 27%, 17 to 22%, and 21 to 26%, respectively, in the cultivated soils. The most significant decrease in the average SQI value was observed in the Vertisols (24% decrease), followed by Inceptisols (21% decrease) and Mollisols (19.5% decrease). The regression equations indicated that IQI-T, NQI-T, IQI-M, and NQI-M models could explain 59%, 39%, 53%, and 35% and 57%, 37%, 51%, and 33% of changes in the biological and grain yields of wheat, respectively. The current study provides a quantitative method for evaluating the soil quality at the soil type-scale and creatively analyzes the effects of long-term and continuous cultivation operations on the soil quality and product performance.

Spatial and temporal variations of gross primary production simulated by land surface model BCC_AVIM2.0

Gross primary production (GPP) is the largest flux and a crucial player in the terrestrial carbon cycle and has been studied extensively, yet large uncertainties remain in the spatiotemporal patterns of GPP in both observations and simulations. This study evaluates the performance of the second version of the Beijing Climate Center Atmosphere−Vegetation Interaction Model (BCC_AVIM2.0) in simulating GPP on multiple spatial and temporal scales in the Coupled Model Intercomparison Project Phase 6 (CMIP6) experiments. Model simulations driven by two meteorological datasets were compared with two observation-based GPP products covering 1982–2008. Spatial patterns of annual GPP show a significant latitudinal gradient in each dataset, increasing from cold (tundra) and dry (desert) biomes to warm (temperate) and humid (tropical rainforest) biomes. BCC_AVIM2.0 overestimates GPP in most parts of the globe, especially in boreal forest regions and Southeast China, while underestimating GPP in subhumid regions in eastern South America and tropical Africa. The four datasets broadly agree on the GPP seasonal cycle, but BCC_AVIM2.0 predicts an earlier beginning of spring growth and a larger amplitude of seasonal variations than those in the observations. The observation-based datasets exhibit slight interannual variability (IAV) and weak GPP linear trends, while the BCC_AVIM2.0 simulations demonstrate relatively large year-to-year variability and significant trends in the low-latitudes and temperate monsoon regions in North America and East Asia. Regarding the possible relationships between annual means of GPP and climate factors, BCC_AVIM2.0 predicts more extensive regions of the globe where the IAV of annual GPP is dominated by precipitation, especially in mid-to-high latitudes of the Northern Hemisphere and tropical Africa, while the observed GPP in the above regions is temperature- or radiation-dominant. The positive GPP biases due to earlier spring growth in boreal forest regions and negative GPP biases in off-equator tropical areas in the BCC_AVIM2.0 simulations imply that cold stress on biomes in boreal mid-to-high latitudes should be strengthened to restrain plant growth, while drought stress in low-latitude regions might be eased to enhance plant production in the future version of BCC_AVIM.

Predictive Modelling of Reference Evapotranspiration Using Machine Learning Models Coupled with Grey Wolf Optimizer

Mismanagement of fresh water is a primary concern that negatively impacts agricultural productivity. Judicious use of water in agriculture is possible by estimating the optimal requirement. The present practice of estimating crop water requirements is using reference evapotranspiration (ET0) values, which is considered a standard method. Hence, predicting ET0 is vital in allocating and managing available resources. In this study, different machine learning (ML) algorithms, namely random forests (RF), extreme gradient boosting (XGB), and light gradient boosting (LGB), were optimized using the naturally inspired grey wolf optimizer (GWO) viz. GWORF, GWOXGB, and GWOLGB. The daily meteorological data of 10 locations falling under humid and sub-humid regions of India for different cross-validation stages were employed, using eighteen input scenarios. Besides, different empirical models were also compared with the ML models. The hybrid ML models were found superior in accurately predicting at all the stations than the conventional and empirical models. The reduction in the root mean square error (RMSE) from 0.919 to 0.812 mm/day in the humid region and 1.253 mm/day to 1.154 mm/day in the sub-humid region was seen in the least accurate model using the hyperparameter tuning. The RF models have improved their accuracies substantially using the GWO optimizer than LGB and XGB models.