Low Rainfall Research Articles

Evaluating effects of selected water conservation techniques and manure on sorghum yields and rainwater use efficiency in dry region of Zimbabwe

Sorghum production in semi-arid areas of Zimbabwe is constrained by low and erratic rainfall, low fertility and soil moisture stress. Sorghum grain yields ranges from 0.2 to 0.4 t ha−1 in sandy-to-sandy loam soils respectively. The objective of the study was to assess cattle manure and rainwater harvesting techniques in improving sorghum grain yield in a semi-arid region of Zimbabwe. The experiment used a randomised complete block design with rainwater harvesting technique as a main treatment factor at three levels. Sub-plot factor was cattle manure at five levels (0, 2.5, 5, 10 and 15 t ha−1) and two sorghum varieties (Macia and SV1) as sub-sub plot factor. Sorghum grain yields were improved significantly (p < 0.05) for both varieties using tied contours. Increasing application rates of cattle manure, showed significant increase (p < 0.05) in sorghum grain yield over the control (0 t ha−1). Tied contour had higher grain yield (1.15 t ha−1) with the use of Macia variety. Stover yield was highly influenced by rainwater harvesting method of tied contour (p < 0.05) compared with infiltration pit and standard contour. Increase in application levels of cattle manure show significant (p < 0.05) increase in stover yields. Tied contour had the highest (3.11 kg ha−1 mm−1) rainwater use efficiency which show significant differences (p < 0.05) from infiltration pits and standard contour. Interaction of tied contour and different rates of cattle manure showed significant increments in rainwater use efficiency with increases in manure application rates. Tied contours, 15 t ha−1 cattle manure and Macia variety are potential strategy to achieve climate smart agriculture and improve food security in semi-arid areas. Sorghum production in marginalised areas can be productive with adoption of tested techniques.

Extreme wildfires in Canada and their contribution to global loss in tree cover and carbon emissions in 2023.

Canadian wildfires in 2023 were record breaking with wide-reaching impacts on people, nature, and climate. Extreme heat and low rainfall associated with climate change led to unprecedented forest fires that released enormous amounts of carbon as they burned. This study used data on fire-driven tree cover loss and forest carbon fluxes to estimate the total extent of stand-replacing forest fires and their associated carbon emissions. We found that the 2023 Canadian wildfires burned nearly 7.8 million hectares of forest and accounted for more than a quarter of all tree cover loss globally. Furthermore, forests impacted by wildfires emitted nearly 3 billion tons of CO2 or about 25% more carbon than all primary tropical tree cover loss that year. These results have important implications for global carbon budgets because emissions from these wildfires will largely be excluded from official greenhouse gas reporting.

Plant spatial configurations and their influences on phenological traits of cereal and legume crops under maize‐based intercropping systems

AbstractIntroductionIntercropping systems have a great potential for crop diversification thus increasing smallholder systems' resilience to climate change while improving soil health. However, optimal benefits associated with intercropping systems are rarely realised because of the interspecific competition for growth resources among the intercropped species.MethodologySix trials were established in the high and low rainfall agroecological zones of Babati district in Tanzania to assess how promising cropping systems with different plant spatial configurations would influence the phenological development of intercropped maize, bean and pigeonpea. Cropping systems under study included a sole maize system rotated with a pigeonpea‐bean intercrop dubbed Doubled‐up legume (DUL), maize‐pigeonpea system both with and without de‐topping, an innovation comprising double maize rows alternated with pigeonpea and beans (Mbili‐Mbili), maize‐pigeonpea system with two maize seeds sown within a 50 cm intra‐row space, a vertical‐architecture Meru H513‐pigeonpea system and a farmer practice.ResultsBranch formation was significantly higher in DUL than in maize‐based systems (p ≤ 0.05). Seasonal weather had upto 30% influence on pigeonpea flowering, with DUL having highest (p ≤ 0.05) flower production. The rate of pigeonpea branch and flower production in Mbili‐Mbili was stable across seasons relative to other maize‐pigeonpea systems. Doubled‐up legume and farmer practice had pigeonpea litter yield of between 1 and 2 t ha−1 which was at least 0.5 t ha−1 higher than in maize‐based systems (p ≤ 0.05). During the period preceding early maize reproductive stages, Mbili‐Mbili increased light interception by 30% and 63% compared to maize‐based systems and DUL, respectively. Maize toppings had higher (94%) P content than stover biomass that remained until harvest.ConclusionOverall, maize‐legume systems had higher intercropping efficacy than sole maize system, both in interception use efficiency, soil mulch cover, among other soil health benefits. Mbili‐Mbili and DUL also had increased phenological benefits on intercropped legumes however, the latter was prone to seasonal weather variability.

Characterization and Seasonal Dynamics of Tick Populations in Dairy Cattle Production Systems of Northwestern Colombian Amazon.

Cattle ticks are a significant health concern in tropical livestock production due to their hematophagous behavior and potential as vectors for human and animal pathogens. In this study, we investigated the tick population present in dairy cattle production, calves, and grazing areas of livestock systems in the northwestern Colombian Amazon. Identification was based on taxonomic keys and molecular markers. Phylogenetic relationships were established using mitochondrial COX1 and 16S genes. Population structure analysis was performed considering age, racial type (B. indicus vs. B. taurus), and the influence of environmental factors and the geomorphological landscape on tick population dynamics. Our findings revealed the presence of a single tick species, with a unique haplotype identified for each mitochondrial gene assessed. Phylogenetic analysis classified the found species within Clade A of the Rhipicephalus microplus complex. Ticks were more prevalent during periods of low rainfall and high temperature, and B. taurus cows exhibited the highest tick abundance. Thus, these results provide insights into the population characteristics and distribution of the tick species present in dairy cattle production systems in the northwestern part of the Colombian Amazon. This information is fundamental for developing targeted strategies based on seasonal variation and host characteristics to mitigate tick infestation severity in the region.

Studies on Crop Weather Calendar of Brinjal Crop in Eastern Uttar Pradesh, India

An investigation was carried out on studies of crop weather calendar on brinjal crop in Eastern Uttar Pradesh has been prepared with objectives to study climatic normal of past 21 years from 2000-21 at Department of Agricultural Meteorology, College of Agriculture, Acharya Narendra Dev University of Agriculture and Technology, Ayodhya, Uttar Pradesh. Climatic data for brinjal crop in Kharif season has been taken from 27th to 48th Standard Meteorological Week (SMW). From the crop weather calendar of brinjal, it was revealed that low temperatures are lethal for brinjal seedlings, so temperature should not be less than 18 °C before the transplanting of the brinjal seedlings into the field. Rainfall during vegetative stage was 140-150 mm found congenial for the better yield of the plant. The growth of the crops is severely affected when temperature falls below 17 °C. It can be successfully grown as a rainy season and summer season crop. It was revealed that, Tmax 23.3-31.8 °C, Tmin 8.4-25.1 °C, rainfall of 0.5-10 mm during 31st to 45th SMW with RHm 90.9-95.6% and RHe 52.1-79.6 were found conducive conditions for the infestation of shoot/fruit borer. It was observed that Fusarium wilt of brinjal was significant during October (41st week) to December (52nd week), when Tmax 23.5- 33.0 °C, Tmin 12.1-26.7 °C, RHm 83.9-87.8%, RHe 48.1-71.5% and rainfall of 0-0.75 mm. It has been found that the severity of fusarium wilt increases with decrease in temperature and high relative humidity and very low rainfall.

Influence of changes in solar activity on Nigerian Rainfall

This paper focuses on the impact of solar activity changes on rainfall in Nigeria. Rainfall data were got from Gridded Time Series (CRU TS v4) of the University of East Anglia, United Kingdom. Various statistical tools like Pearson rank correlation coefficient, regression analysis, covariance, skewness, and kurtosis are employed in the study. The results show that there are generally weak correlations between rainfall and solar activity in most seasons. However, low correlation coefficients (0.0424 and 0.1040, respectively for sunspot numbers and F10.7 mean a very weak positive relationship between early rainfall, main rainfall and annual rainfall and negative for dry season rainfall and Harmattan rainfall. Also, there is a negative time-series relationship between the rainfall amount in dry and Harmattan seasons, with the highest rainfall amount during low solar activity and vice versa. Therefore, it can be concluded that solar activity has little effect on Nigeria's annual and main season rainfall. However, during the dry season and Harmattan, heavy rainfall appears to be associated with low solar activity, while high solar activity appears to be associated with low rainfall. This study will be beneficial to farmers in Nigeria, majority of whom are peasant farmers that practice rain-fed farming.

Correlation between flood couplet-based sediment yield and rainfall patterns in a small watershed on the Chinese Loess Plateau

Understanding how rainfall patterns impact sediment yields during rainfall events is important to explore soil erosion changes and to prevent watershed flood disasters. However, few studies identified sediment yields variation affected by rainfall patterns at continuous deposited flood couplet scale. This study analyzed sediment yields under different rainfall patterns and correlated particle depositional features on the condition that the erosive environment was obviously changed by anthropogenic activities in a check dam-controlled small watershed on the Chinese Loess Plateau. Results showed that erosive rainfall events, having formed 40 flood couplets behind the check dam between 1978 and 2010, can be grouped into three rainfall patterns (i.e., rainfall patterns I, II, and III) according to changes in rainfall amount, erosivity, and duration. Rainfall pattern III, characterized by high rainfall amount and erosivity within a short duration (i.e., rainstorm) accounted for only 15.0 % of erosive rainfall events while yielding 44.7 % of the total sediment. Conversely, rainfall pattern I (the most common, 55.0 %), characterized by its long duration and relatively low rainfall amount and erosivity, only contributed 25.3 % of the total sediment. Both sediment yields and thickness proportions of coarse particle layer in flood couplets exhibited a decreasing trend under all three rainfall patterns. Meanwhile, the main factor that impacted sediment yields changed from rainfall in the 1980s and 1990s to the “Grain for Green” program dominated anthropogenic activities since 1999. For a small watershed with a few terraces and only one check dam at the outlet, artificial vegetation restoration significantly reduced coarse soil particle loss and sediment yield. Findings showed that sediment yield and deposition feature variations in flood couplets under different rainfall patterns are helpful in improving watershed soil and water conservation measures against flood disasters, particularly under rainstorms.

Constraint programming for reservoir operation optimization of Bhumibol dam

The modern constraint programming (CP) was adopted to minimize water scarcity and excessive water which are the critical issues in reservoir operation of Bhumibol Dam (BB) to solve consecutive droughts in the Chao Phraya River Basin (CPYRB), Thailand. The situations of the severe droughts have been frequently occurred in a broad area of CPYRB due to an extremely low rainfall leading to unusually low water levels and inflow in major reservoirs. Therefore, multi-objective optimization was conducted to characterize the actual operation and physical reservoir system of BB Dam. Two different CP models with seasonal and yearly constraints were manipulated using MiniZinc programming language and the constraint solver IPOPT to find the optimal daily release scheme from 2000 to 2018 of BB Dam. The potential of downstream flow conditions was also considered to partially supply downstream water demand and store savable water in a reservoir for subsequent use during possible future droughts. The results reveal that CP models can diminish some extent of yearly reservoir release, while daily long-term release scheme conforms well with the actual operation particularly during dry and wet seasons in specific drought years. These mean that amount of reservoir water of approximately 47.12–103.83 MCM/year can be saved and stored in reservoir for subsequent use in CPYRB when CP models are deployed. This results in a reservoir storage increase of 7.10–7.94% at the end of the wet season for seasonal and yearly CP models, respectively. When potential side flow is considered, the increase climbs up to 10.49%. This envisages the higher possibility of supplying reservoir water for agricultural water needs over the dry season in the Greater Chao Phraya Irrigation Scheme. As the potential hydraulic head is subject to increased reservoir water storage, therefore, the increase in hydropower production is definitely found of ranging from + 6.10% to + 13.79% by these two sorts of CP models. In addition, handling with huge volumes of flood and drought by CP models is well managed as the specific release constraints during refilled and drawdown periods are used to define the constraint satisfaction problem.

Long-term climate and hydrologic regimes shape stream invertebrate community responses to a hurricane disturbance.

Disturbances can produce a spectrum of short- and long-term ecological consequences that depend on complex interactions of the characteristics of the event, antecedent environmental conditions, and the intrinsic properties of resistance and resilience of the affected biological system. We used Hurricane Harvey's impact on coastal rivers of Texas to examine the roles of storm-related changes in hydrology and long-term precipitation regime on the response of stream invertebrate communities to hurricane disturbance. We detected declines in richness, diversity and total abundance following the storm, but responses were strongly tied to direct and indirect effects of long-term aridity and short-term changes in stream hydrology. The amount of rainfall a site received drove both flood duration and flood magnitude across sites, but lower annual rainfall amounts (i.e. aridity) increased flood magnitude and decreased flood duration. Across all sites, flood duration was positively related to the time it took for invertebrate communities to return to a long-term baseline and flood magnitude drove larger invertebrate community responses (i.e. changes in diversity and total abundance). However, invertebrate response per unit flood magnitude was lower in sub-humid sites, potentially because of differences in refuge availability or ecological-evolutionary interactions. Interestingly, sub-humid streams had temporary large peaks in invertebrate total abundance and diversity following recovery period that may be indicative of the larger organic matter pulses expected in these systems because of their comparatively well-developed riparian vegetation. Our findings show that hydrology and long-term precipitation regime predictably affected invertebrate community responses and, thus, our work underscores the important influence of local climate to ecosystem sensitivity to disturbances.

Predictive simulation of the water-energy-food nexus for the City of Cape Town

The City of Cape Town (CoCT), South Africa faced a critical situation between 2015 and 2018 in which the municipal water supply was almost completely exhausted. This situation, commonly referred to as Day Zero in South Africa emanated from a decline in rainfall, resulting in one of the most severe droughts in history. The crisis was also aggravated by rapid population growth and urbanization. CoCT was on the verge of becoming the first city in the past decade to experience a complete cessation of water supply for urban and agricultural purposes. In addition to the effects of low rainfall and population surge, urban energy consumption and increased food demand impacted directly the available water resources. To evaluate the interlinkages between water utilization, water production, energy supply and demand, and food production and demand, this study employed a system dynamics modeling (SDM) approach. The model was developed as a stock and flow diagram utilizing Stella Architect and encompassed five interconnected nodes: water, energy, food, land, and population. The findings revealed that by the end of the 20-year modeling period, the volume of accessible and stored water in all the major dams will be approximately 459 million cubic meters, with residential use accounting for about 85 % of urban water use and agriculture accounting for approximately30.37 % of total water demand. The model illustrates the impacts of precipitation rate, runoff, and evaporation on variables such as land-use change and population dynamics. It is anticipated that the outcomes of this study will serve as valuable inputs for decision-making processes, not only within the CoCT as it aims to mitigate or prevent the recurrence of Day Zero, but also for other cities facing similar challenges.

Wildfire susceptibility mapping by incorporating damage proxy maps, differenced normalized burn Ratio, and deep learning algorithms based on sentinel-1/2 data: a case study on Maui Island, Hawaii

ABSTRACT Climate change has contributed to the recent increase in wildfire occurrences, vegetation failures, human health risks, physical damage, and economic losses. Wildfire susceptibility mapping is an essential technique for assessing areas prone to wildfires. In this study, we proposed the combination of the damage proxy map (DPM) and differenced normalized burn ratio (dNBR) method to generate a precise wildfire inventory map and used it to predict areas susceptible to wildfire. The wildfire susceptibility maps were produced using frequency ratio (FR), convolutional neural network (CNN), and long short-term memory (LSTM)-based deep learning and their performances were compared. We implemented the proposed method on Maui Island, Hawaii, where wildfires frequently occur. We started the process by generating a wildfire inventory map from 2019 to 2023 based on the DPM method applied to Sentinel-1 synthetic aperture radar (SAR) data combined with a dNBR map retrieved from Sentinel-2 data. The wildfire inventory was randomly divided into a training dataset (70%) and a testing dataset (30%). Fifteen wildfire-related factors, including topographical, meteorological, land use, environmental, and anthropological factors, were selected to predict wildfires. The wildfire-related factors were selected by conducting study literature and considering spatial correlation analysis based on the FR method, information gain ratio analysis (IGR), and multicollinearity assessment using tolerance (TOL) and variance inflation factor (VIF) metrics. The level of susceptibility of an area to wildfire is divided into five, namely very high, high, moderate, low, and very low. The FR, CNN, and LSTM produced wildfire susceptibility maps with similar patterns, significantly influenced by land use and rainfall factors. The highly susceptible areas are located on gentle slopes covered by agricultural land and unhealthy vegetation, and these areas have low rainfall intensity but receive high levels of solar radiation. Meanwhile, areas with relatively low susceptibility occur in forests with high levels of wet canopy evaporation. The prediction results were evaluated using the area under the receiver operating characteristic (ROC) curve (AUC), and the CNN performed slightly better than the FR and LSTM, with AUC values of 0.879, 0.877, and 0.870, respectively. Hence, the use of the CNN algorithm in the proposed method is appropriate, specifically for the study area. In addition, the susceptibility map provides information on susceptible areas on Maui Island, Hawaii, to increase public awareness.

Projections of future streamflow for Australia informed by CMIP6 and previous generations of global climate models

Projections of streamflow under future climate are essential for developing adaptation strategies in the water and related sectors. This paper presents nationwide streamflow projections for Australia informed by climate change signals in CMIP6 GCMs and compares the projections with those from CMIP5 GCMs. The modelled future runoff projections driven by CMIP5 and CMIP6 GCMs are relatively similar for far southern Australia. The median projection is a 50% reduction in mean annual runoff in far southwest Australia and 20% reduction in far southeast Australia by 2046–2075 relative to 1976–2015 under the high SSP5-8.5/RCP8.5 global warming scenario. The vast majority of CMIP5 and CMIP6 GCMs project less winter rainfall across Australia. As most of the runoff in far southern Australia occurs in winter and spring, the lower winter rainfall translates to a significant reduction in annual runoff. It is therefore prudent to plan and manage for a reduction in future water resources, particularly in the densely populated and important agricultural regions in southeast Australia. There is less agreement between GCMs in the summer rainfall projection, with the CMIP6 GCMs generally projecting a wetter future (or smaller decrease in rainfall) than the CMIP5 GCMs. The modelled median projection for mean annual runoff is a 10% reduction in the south-east coast, 5% reduction in the north-east coast and little change in northern Australia. More GCMs project an increase rather than a decrease in the interannual variability of rainfall, and this would further amplify multi-year hydrological droughts.

Integrating remote sensing, GIS-based, and AHP techniques to delineate groundwater potential zones in the Moulouya Basin, North-East Morocco

Groundwater is a valuable shared resource in the Moulouya Basin, but it has been in decline due to recent years of low rainfall and rapid population growth. To support socio-economic development, there is increased demand for this precious resource. This paper presents a standard methodology for delimiting potential groundwater zones using geographic information systems (GIS), an integrated analytical hierarchy process (AHP), and remote sensing techniques. Seven parameters that monitor the presence and mobility of groundwater, including drainage density, lithology, slope, precipitation, land use/land cover, distance to river, and lineament density, were incorporated into a raster data model using ArcGIS software. AHP-based expert knowledge was used to prepare a groundwater potential index and assign weights to the thematic layers. The study classified the area into five zones of varying groundwater potential: very high (26%), high (51%), moderate (13%), poor (9%), and very poor (1%). The accuracy of the model was validated by comparing the Groundwater Potential Zones map with data from 96 wells and boreholes across the basin. The validity of the results was confirmed by comparing them with the specific yield of the aquifer in the study area, yielding a high correlation coefficient (R2) of 0.79. The analysis revealed that 89.5% of the boreholes were situated in the high and very high potential zones, demonstrating the reliability and robustness of the employed approach. These findings can aid decision-making and planning for sustainable groundwater use in the water-stressed region.

Influence of Growing Region on Targeted Anthocyanin Profile, Color, Phenolics, and Antioxidant Activity of Grape Juice

Influence of Growing Region on Targeted Anthocyanin Profile, Color, Phenolics, and Antioxidant Activity of Grape Juice cv. Manjari Medika (MM) were examined. The prevailing environmental conditions affect chemical composition or metabolites of grapes. The MM grape berries were harvested from three environmentally different locations in India i.e. Pune (MMJP), Vijayapura (MMJV), and Nashik (MMJN). MMJV, grown in region with high average temperatures and low rainfall showed higher levels of (393.65 ± 8.18 g/L) reducing sugar with lower levels of color intensity (49.69±0.55%), juice recovery (68.70±0.54%), and acidity (6.98±0.04 g/L) followed by flavonoids (0.023 g/L) than the regions with relatively low temperatures and high rainfall ((MMJP) and (MMJN)). In UHPLC-Oribitrap MS analysis, a total of 11 anthocyanins, which includes delphinidin-3-galactoside (Dp3Ga), cyanidin (Cy), peonidin-glucoside-4-Vinylphenol (Pn3Glu4VP), petunidin-3-glucoside (Pt3Glu), malvidin-3-glucoside (Mv3Glu), pelargonidin (Pg), petunidin-3-acetyl glucoside (Pt3ace), peonidin-3-acetyl glucoside (Pn3ace), malvidin-3-acetyl glucoside (Mv3ace), delphinidin (Dp) and petunidin (Pt) were detected in grape juice samples. MMJV. It is interesting to note that among the 11 anthocyanins detected, two compounds, petunidin-3-acetyl glucoside (Pt3ace) and peonidin-3-acetyl glucoside (Pn3ace), have been reported only in specific grape juice samples, i.e., Pt3ace in MMJV and Pn3ace in MMJN. Discriminatory compounds among the regions were petunidin-3-acetyl glucoside (Pt3ace), peonidin-3-acetyl glucoside (Pn3ace), and cyanidin (Cy) according to principal component analysis (PCA). UHPLC-MS results showed that the total anthocyanin content of the fresh juice in the cultivar tended to increase with altitude from sea level.

The Representation Of Arabian Identity Through Cultural Terms In Arabic Proverbs

One form of language that contains cultural elements is proverbs which in Arabic are called amtsal. This study aims to discover the identity of the Arabians which is represented in cultural terms in the amtsal. The research method used is descriptive qualitative, while data collection is done by reading and writing. The results show two things; the first, Arabic proverbs contain a number of cultural terms, which consist of three types, namely ecology, socio-culture, and artifacts. The second result shows the Arabic identity as seen from the amtsal, with a total of seven identities, namely the custom of war, fondness of traveling, low rainfall, palm trees and the fruit, gold, value time, and honoring science.

Impact of climate change and genetic development on Iowa corn yield

The vulnerability of corn yield to high temperature and insufficient rainfall in the US mid-west is widely acknowledged. The impact of extreme weather and genetic development on corn yield is less well known. One of the main reasons is that the multicollinearity in the variables can lead to confounding results. Here we model the impact of climate and genetic development by employing an elastic net regression model to address the multicollinearity issue. This allows us to develop a more robust multiple regression model with higher predictive accuracy. Using granular data for Iowa from 1981-2018, we find that corn yield is vulnerable to high mean summer temperatures particularly in July, a widening diurnal temperature range in June and dry summer conditions (due to extremely low rainfall) from June-August. We find that overall climate impact reduced average annual yield by 0.7%. We also find that genetic development which led to earlier planting dates, widening duration of the reproductive interval, higher growing degree day accumulation and larger net planted area had a beneficial impact on the Iowa corn yield during 1981-2018 resulting in an average annual yield improvement of 1.8% per annum. This provides a basis for optimism that these genetic developments and management practices will continue to adapt and improve in the future to counter the impact of climate change on corn yield. We have also modelled the impact of future climate change using the latest climate projections from the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR6). These climate projections show that the average temperature during the growing season (MayO-October) will increase by 2.4 -2.9 o C by mid-century while the average spring temperature (March and April) will increase by a relatively slower 1.9 -2.3 o C by mid-century. Additionally, climate projections show that both temperature and rainfall will also become more extreme in the future with the changes varying from spring to summer. Our results show that, just due to climate change alone in Iowa corn yield will decline between 1.4-1.7% per annum until mid-century (or 1.2-2.1% per annum until the late twenty first century).

Sugarcane leaf return and mixing significantly reduce slope runoff and soil loss

AbstractImproper management of sugarcane cultivation may cause severe soil erosion, especially in lateritic red soil hilly areas. Crop straw return to the field can effectively improve the soil structure, but there is a lack of evaluation studies of the soil and water conservation benefits of sugarcane leaf mixing and return to the field, and the underlying regulatory mechanism has rarely been described. Thus, we conducted a series of simulated rainfall experiments to investigate the impact of returning different mixed sugarcane leaf weights (0, 3, 6, 9, 12 and 15 t/ha) to the field on erodible lateritic red soil slopes that support sugarcane production under various slopes (5°, 10°, 15° and 20°) in different rainfall events (60 and 120 mm/h). The results indicated that returning sugarcane leaves into farmland could effectively regulate the process of runoff and sediment production on lateritic red soil slopes, and the optimal mixing amount was 9 t/ha. Under a low rainfall intensity, the erosion process was mainly affected by the slope, and the benefits of applying the sugarcane leaf mixing treatment to the slope to reduce runoff and sediment could reach 13.37–53.04% and 23.86–77.55%, respectively. However, under a high rainfall intensity, the sugarcane leaf mixing amount was the main influencing factor, the benefits for reducing runoff and sediment could reach 4.64–38.72% and 30.87–93.14%, respectively. The sugarcane leaf mixing amount exhibited a linear relationship with the Reynolds number (R2 &gt; 0.63), whereas the runoff velocity (R2 &gt; 0.96), Froude number (R2 &gt; 0.94) and drag coefficient (R2 &gt; 0.85) exhibited well‐fitting exponential function relationship with it. This study provides a reference for future endeavours regarding the inhibition mechanisms of sugarcane leaves mixed and returned to the field for decreasing slope erosion.

Tracking the nitrogen leaching from different sources in bioretention systems with a process-based model

Bioretention systems are a typical stormwater management technology intended to reduce runoff and non-point source pollution. Multiple sources can contribute to nitrogen (N) leaching from bioretention systems, including the current rainfall-runoff (i.e., immediate leaching), recent rainfall-runoffs (i.e., fast leaching) and long-ago legacy N (i.e., slow leaching), however, there is a lack of methods to quantify these contributions. Here, a process-based Bioretention System (BRS) model for N leaching simulations was verified with artificially-labeled 15N data besides N data to reduce predictive uncertainties. The BRS model was then coupled with an Nitrogen Source Apportionment (NSA) module for N leaching tracking to quantify the contributions from different sources. Results from a bioretention system showed that additional 15N data reduced the predictive uncertainty of total N (TN) concentrations by 23 %. Immediate leaching, fast leaching and slow leaching increased, decreased and remained steady during the leaching process and accounted for 79.54 ± 5.08 %, 2.80 ± 1.74 % and 17.66 ± 4.11 % of N leaching, respectively. The dominant immediate leaching can be significantly weakened by a submerged zone, a shorter antecedent dry period (ADP), a lower rainfall intensity or influent concentration. This study provides a framework to quantify N leaching from multiple sources with implications for long-term N leaching management.

Regionalization of environmental and economic performances of rainwater harvesting systems

Study regionBeijing Region Study focusLimited studies have yet been done on regionalization of multi-performances of rainwater harvesting systems (RHS). In this study, the daily rainfall records from 77 stations are used, and a hydro-economic model is adopted to examine regional water saving, stormwater control and economic performances of RHS by proposing a regionalization approach. New hydrological insights for the regionHigher water saving efficiency (WSE) and reliability (R) of RHS are linked with lower water demand, larger tank size and greater rainfall conditions. Differently, higher stormwater capture efficiency (SCE) is related to higher water demand, larger tank size and lower rainfall. The WSE and R of RHS demonstrate substantial regional differences; their maximized obtainable values closely depend on water demand scenarios and range from 9% to 99%, with smaller values in western mountain area but larger values in northeast suburban and central urban areas. The maximum obtainable values of SCE range from 61% to 100%, with higher values in western mountain area, but lower values in northeast suburban and central urban areas. A 10 m3 tank size can provide the highest benefit-cost ratio of RHS across the Beijing region. The regionalization approach proposed is a useful guidance for the implementation of RHS and sustainable urban water management, and thus it has the potential for wide uses in other regions with high rainfall gradients.

Adapting to climate disparities: Implications for fruit fly populations in citrus orchards

In the context of climate change, the agricultural sector faces the imperative of devising adaptive strategies to mitigate emerging challenges. This study aimed to know the relationship between climatic disparities and fruit fly populations in citrus orchards. Utilizing Steiner trap and Methyl Eugenol wooden blocks as monitoring, male annihilation controlling devices, and spraying protein bait, we conducted a comprehensive investigation across two distinct agroclimatic conditions. The main variations were monthly rainfall (mm), accentuating diverse agroclimatic dynamics. Surprisingly, an analysis comparing low rainfall (1-4 mm) to moderate rainfall (14-21 mm) periods did not affect fruit fly populations. Contrary to conventional assumptions, variations in only precipitation did not significantly impact fruit fly population dynamics. The critical factors were the dominant role of host plant availability and the efficacy of pest management practices in steering population trends. This study showed that climatic factors contribute to pest dynamics; however, they might not function as a single change factor. Instead, host plant availability and the implementation of effective pest control interventions held more significant influence. Based on the interconnected relationship between climate and pests, amid a continuously developing climate scenario, more careful management strategies are needed to increase the sustainability of citrus yields for food security and farmer welfare.