Semi-arid Climate Zones Research Articles

Evaluating the Primary Macronutrients and their Correlations with pH, Electrical conductivity, Organic Carbon and Soil Nutrient index in the Arid and Semi-Arid Climatic Zones of Anantapur District, Andhra Pradesh, India

In the year 2022, the study was carried at Agricultural Research Station, Anantapur aimed to assess macronutrient levels and their correlation with soil physico chemical properties in the arid and semi-arid regions of Anantapur district, Andhra Pradesh. A total 42 samples were collected from farmers field under different land use. The soil analysis revealed a pH range of 6.53 to 8.94, with a mean pH of 7.89 and a majority of samples exhibiting alkaline properties. Soil electrical conductivity (EC) varied from 0.05 to 0.83 dS/m, with a mean EC of 0.22 dS/m, and most samples falling within the non-saline and very low salinity categories. Organic carbon content ranged from 0.07% to 1.15% with a mean of 0.38%, and a significant proportion of samples displayed low organic carbon levels. Available nitrogen content ranged from 50.4 to 264.6 kg/ha (mean: 139.44 kg/ha), mostly below the critical threshold. Phosphorus availability was medium (range: 16.1 to 44 kg/ha, mean: 29.97 kg/ha), while available potassium content varied widely (range: 15.68 to 311 kg/ha, mean: 129.65 kg/ha), with a substantial proportion of samples indicating low levels. The nutrient index categorized nitrogen and potassium as low in fertility and phosphorus as medium, reflecting values of 0.71, 1.37, and 1.09 (L, M, L) respectively. Correlations showed EC negatively related to pH (-0.056), while organic carbon positively correlated with EC (0.288*), and nitrogen displayed positive correlations with both organic carbon (0.283*) and pH (0.257). Phosphorus exhibited a positive correlation with organic carbon (0.224), and potassium displayed robust positive correlations with EC (0.592**) and moderate positive correlations with organic carbon (0.392**), nitrogen (0.311*), and a slight negative correlation with pH (-0.253). This result helps to understand nutrient status in the arid and semi-arid areas of Anantapur and recommended to incorporate compost, crop residues and green manure crops and use cover crops as live mulching helps to increase organic carbon, nitrogen and potassium and it also decrease nitrogen losses through volatilization.

Analysis of Vegetation Dynamics and Driving Mechanisms on the Qinghai-Tibet Plateau in the Context of Climate Change

The Qinghai-Tibet Plateau (TP) is susceptible to climate change and human activities, which brought about drastic alterations in vegetation on the plateau. However, the trends and driving mechanisms of vegetation changes remain unclear. Therefore, the normalized difference vegetation index (NDVI) was used to analyze the spatiotemporal distribution of vegetation and the consistency of dynamic trends in the TP from 2000 to 2020 in this study. The independent contributions and interactive factors of natural and human activities on vegetation changes were investigated through the Geodetector model. The drivers of vegetation under different dry–wet zones and precipitation gradients were quantitatively separated, and the internal mechanisms of vegetation changes were discussed from multiple perspectives. The results showed that from 2000 to 2020, the NDVI had an overall increasing trend, with an increasing rate of 0.0027 a−1, and the spatial pattern was different, increasing gradually from the northwest to the southeast. Consistent improvement occurred in the central and southeastern parts of the TP, while the western and northern parts consistently deteriorated. The annual mean precipitation had the greatest explanatory power for vegetation changes (0.781). The explanatory power of the integrated effects between two factors was greater than that of individual factors. The integrated effects between annual mean precipitation and other driving factors had the strongest explanatory power on vegetation variations. The driving mechanisms of vegetation dynamics varied among different dry–wet zones, and the vegetation growth was more sensitive to the response of precipitation in arid and semi-arid climate zones. This study enhances our understanding of the intrinsic mechanisms of vegetation changes on the plateau, which can provide a reference for ecological conservation, and has implications for further prediction and assessment of vegetation ecosystem stability.

A holistic digital workflow methodology to shifting towards net zero energy urban residential buildings in a semi-arid climate

Given the looming threats of climate change and the rapid worldwide urbanization, it is a necessity to prioritize the transition towards a carbon-free built environment. This research study provides a holistic digital methodology for parametric design of urban residential buildings with regard to the Mediterranean semi-arid climate zone of Morocco in the early design phase. The morphological parameters of the urban residential buildings, namely the buildings’ typology, the distance between buildings, the urban grid’s orientation, and the window-to-wall ratio, are evaluated in order to identify the key combinations of passive and active solar design strategies that determine the high energy performing configurations, based on the introduced Energy Performance Index (EPI), which is the ratio between solar BIPV production to maximum available installed BIPV capacity and the normalized thermal energy needs. Through an automated processing of 2187 iterations via Grasshopper, we simulate daylight autonomy, indoor thermal comfort and solar rooftop photovoltaic and building integrated photovoltaic (BIPV) energy potential. Then, we analyze the conflicting objectives of energy efficiency measures, active solar design strategies, and indoor visual comfort in the decision-making process that supports our goal of getting closer to net zero urban residential buildings. The digital workflow showed interesting trends in reaching a balanced equilibrium between performance metrics influenced by the contrasting impact of solar exposure on indoor daylight autonomy and thermal energy demand. Furthermore, the study's findings indicate that it is possible to achieve an annual load match exceeding 66,56 % while simultaneously ensuring an acceptable visual indoor comfort (sDA higher than 0.4). The findings also highlight the important role of the BIPV system in shifting towards the net zero energy goal, by contributing up to 30 % of the overall solar energy output and covering up to 20 % of the yearly self-consumption. Moreover, the energy balance evaluation on an hourly basis indicates that BIPV system notably enhances the daily load cover factor by up to 5.5 %, particularly in the case of slab SN typology, throughout the different seasons.Graphical representations of the yearly, monthly and hourly load matches and the hourly energy balance of the best performing configurations provide a thorough understanding of the potential evolution of the urban energy system over time as a result of the gradual integration of active solar electricity production.

Developing a satellite-based combined land degradation index for monitoring environmental change: A case study in Tana-Beles watershed, Upper Blue Nile, Ethiopia

Land degradation is one of the most pressing environmental challenges due to its effect on the people and ecosystem. Early detection of land degradation could help to avoid further deterioration and work on reversing the trend. This would require an integrated approach combining indicators such as vegetation condition, soil health (i.e., soil salinity), and soil exposure (i.e., albedo) to characterize land degradation comprehensively. Therefore, this study aims at developing a satellite image-based combined land degradation index to monitor the spatial extent of land degradation in the Upper Blue Nile Basin, Ethiopia. In addition, the study also evaluates the environmental change associated with land degradation across the Tana-Beles watershed. The combined land degradation index (CLDI) was developed by integrating multiple indicators, including normalized vegetation Index (NDVI), salinity index (SI), and albedo, for two periods spanning between 1990 and 2000 (1990s) and 2010 to 2020 (2010s). The individual indicators were combined with Principal Component Analysis (PCA) by assigning weights to the individual indicators. The analysis indicated that, in the 2010s, the vegetation condition deteriorated over 98.5% of the study area, while soil salinity and albedo increased by 82% and 97% in the 1990s, respectively. The combined land degradation index developed with the PCA indicated in the 2020s a fraction of the study area ∼2% is extremely degraded, while 18%, 43%, 27%, and 10% of the site is strongly, moderately, slightly, and not degraded, respectively. Monitoring land degradation is important for countries like Ethiopia, where most of the county are occupied by semi-arid and arid climate zones.

Determining the Adaptive Thermal Comfort and Preference Votes of Children in Public Primary Schools in the Hot Semi-arid Climatic Zone of Nigeria

Provisions for thermal comfort is important to childrens’ performance and health. The lack of good environmental comfort can greatly affect the learning capacity of pupils. An inherent research concern is that current thermal comfort approaches are predicated on the adult subjects. However, there is no certainty on the effect of these approaches towards children. This study is a research survey with experimental measurements using Kestrel 5500 indoor climate tracker on the effects of thermal comfort on the learning capacity of children. It adopted a cross-sectional approach using graphic questionnaires for data collection. The graphic comfort scale sought the pupils to make a subjective voting of their thermal sensations when they were in their classroom environment using the adapted ASHRAE thermal sensation 5 points scale. Concomitantly, measurements were taken with instruments with the records of Mclntyre preference 3 points scale. The result shows that a combined thermal discomfort percentage of about 68.86% (45.92% warm and 22.94% hot) of the students found the environment was not thermally satisfactory at a mean air velocity of 0.53m/s, air temperature of 35.38oC, radiant temperature of 37.33oC and relative humidity of 35.60%. The preference votes of the classes portray a clear preference of 62.30% of the pupils, requested for cooler environment at a mean air velocity of 0.53m/s, air temperature of 35.38oC, radiant temperature of 37.33oC and relative humidity of 35.60%. Consequently, the classroom environment is not thermally comfortable for the pupils. The research recommends that there is the inescapable need for further studies on the use of building materials, opening types and right orientation in construction that will bring down the temperature in the Hot Semiarid climatic zone of Nigeria that will ultimately enhance pupils learning environment.

A dataset of monthly VCI and TCI drought indices at a resolution of 1km in the Yellow River Basin (2003–2021)

The Yellow River Basin is located in the arid, semi-arid climate zone and semi-humid climate zones. According to the statistics of the Second National Comprehensive Water Resources Planning, its annual average water resources total 71.94 billion m3, accounting for 2.5% of the country's total water resources. However, it is the most severely affected by drought among the major river basins in China, and ecological protection faces severe challenges. With the global climate change, the drought problem in the Yellow River Basin has attracted more and more attention. Based on MODIS vegetation index products (MYD13A2, V6) and surface temperature radiation products (MYD11A2, V6). The dataset is obtained by approaches including projection conversion, cloud removal, mosaic clipping, time series interpolation and SG filter smoothing and other preprocessing. Using the calculation method proposed by Kogan in 1995, the VCI and TCI indices were calculated according to the corresponding MODIS products, respectively, and the monthly 1km resolution VCI and TCI drought index datasets in the Yellow River Basin from 2003 to 2021 were generated. Through data sharing, it is expected to provide important data support for drought monitoring and research in the Yellow River Basin under the background of global change.

Low-energy residential building optimisation for energy and comfort enhancement in semi-arid climate conditions

The application of energy-efficient strategies in buildings, such as the Green Building Concept, can significantly impact human comfort and resource consumption. However, due to the complexity of decision-making factors and the variety of available materials, computational models are necessary to identify the most effective solutions and optimise building energy performance. This study presents an integrated framework that uses machine learning algorithms and a Petri Net control system to optimise the thermal, comfort, and energy efficiency of both vertical and horizontal building envelopes in semi-arid climate zones. The framework incorporates several passive techniques for building energy parameters, including material thickness and melting point, window types, wall insulation thickness and thermal emissivity, wall solar absorbance, window wall ratio, fenestration position, air tightness, roof solar reflectance, roof insulation thickness and conductivity (W/(m·°C)), and floor insulation thickness. An experiment design was developed using Box-Behnken Design-Response Surface Methodology (BBD-RSM) for statistical optimisation, which was coupled with Design Builder simulation model. The methodology was demonstrated by applying it to a residential building in Mexico. Meta Additive Regression was used to analyse the output factors, which showed higher confidence compared to REP Tree and M5P Tree algorithms in green buildings. The results demonstrate that an annual energy reduction of 50 kW/m2 per household can be achieved by using an optimised building envelope.

Drought Assessment of Siirt using SPI and SPEI

Turkey is in the semi-arid semi-humid mid-latitude region. Therefore, drought, one of the destructive effects of climate change, is a fundamental problem for the country, part of which is in the semi-arid climate zone. To evaluate the drought of Siirt province in Turkey, a total of 792 time series were evaluated. In this study, meteorological drought analysis was carried out in Siirt province, located in the Southeastern Anatolia region, monthly and annual periods using the Standardized Precipitation Index (SPI) method and SPEI. Meteorological data (temperature, evaporation, and precipitation) from Siirt province between 1957-2022 were used. The results showed that the monthly and annual values of SPI and SPEI showed almost similar results at the selected stations for annual time scales. Although there were periods of severe drought, normal drought levels were observed in the overall average. The wet and dry periods were identified, and the results were presented graphically. As a result, the trend results in the region will contribute to the water resources planning management.

Comparison of Most Popular Buildings Performance Simulation Tools

A critical procedure in sustainable building design is the building energy performance assessment, which has significant implications for global energy consumption and climate change. This study compares three simulation software programs for a photovoltaic system on a building’s roof. The low-rise residential buildings in three East Mediterranean cities (Amman, Mafraq, and Aqaba) represent moderate drywarm, semiarid, and humid subtropical climate zones were compared using three simulation software programs (IES-VE, DesignBuilder, REVIT) for a typical building with PV on the roof and the second scenario without a PV system installed on the roof. This investigation aims to evaluate the shading effect of the PV system on a building’s roof structure by calculating the total electrical load required to maintain thermal comfort inside the building. The final results showed significant discrepancies between the three software for the base building design and the PV system on the roof, with a range of around 50 %. This highlights the importance of evaluating and calibrating different simulation tools and using them with a great deal of caution.

Predictive Model for Flood – Induced Collapse Phenomenon in Residual Soils of Northern Edo, Nigeria

Residual soils are in the category of questionable soils which have been experienced in the arid and semi-arid climatic zones of the world. The conditions in these zones favour the development of most unsafe collapsible soils. At their dry natural state, they possess awesome stiffness and high apparent shear strength, however upon flooding, may demonstrate a remarkable reduction in volume, consequently deteriorate in strength and collapse. In this research, the collapse phenomenon of residual soil collected from three locations in Auchi, Northern Edo, Nigeria has been investigated on undisturbed specimens by utilizing single Oedometer test. The results obtained from Oedometer tests were utilized to form the database to develop the Artificial Neural Network model for the prediction of collapse potential induced by flood. The influences of flood, flooding pressure, void ratio, dry density and porosity on soil collapse have been investigated. Six input parameters (i.e. Flooding Pressure, Initial void ratio, Initial water content, Initial dry density, Liquid limit and Initial porosity) are considered to have the most noteworthy influences on the degree of collapse and have been utilized as the model’s inputs while the model output will be the equivalent collapse potential. The proposed network was developed using Microsoft Visual Studio 2010 and the MS.NET Framework 4.0 and source codes were written in C-Sharp (C#). A supervised learning was utilized to train the Back Propagation feed forward multi-layer ANN algorithm with the momentum coefficient and learning rate as its parameters. The prediction performance of the Artificial Neural Network model was assessed by utilizing the primary statistical criterion proposed by Shahin, et al., [1] such as the coefficient of correlation, R2, and the root mean square error, RMSE. The model outcomes demonstrated that it has the aptitude to predict the collapse potential from single Oedometer test in residual soil samples with a good degree of precision with coefficient of correlation, R2 = 0.856 and root mean square error, RMSE = 166.199.

Evaluation of the adaptive potential of three non-native multipurpose species for soil rehabilitation

Soil rehabilitation involves restoring their capacity to provide goods and services; however, there is a lack of information regarding the survival and growth responses of individual species to local environmental variations. This study evaluated the adaptation capacity of three non-native multiple-use species in agroforestry design, in a degraded semiarid temperate climate zone located in the Tula watershed in Mexico, assessing their survival, growth of morphological variables, and death risk for use as soil restoration plants. According to the slope of the terrain, the species were planted in an agroforestry arrangement of lines and ridges. Plants were selected according to their multipurpose potential, including their taxonomy, form, function, and use, as well as their soil and climatic conditions. Survival rates for all three species were below acceptable levels (< 49%). Neither Senna multiglandulosa nor Sedum dendroideum adapted well to the soil and climate of the site, since their survival rates were below acceptable (sim 17<49mathrm{%}). Aloe sp. adapted to the edaphoclimatic conditions of the site because its survival rate was excellent (sim 97 ge 90%). Climate conditions during the autumn and winter affected growth rates of Senna multiglandulosa and Sedum dendroideum. Aloe sp. growth rates were only affected by climatic conditions during the winter months. Senna multiglandulosa's final height reduced death risk by 1.50%. Sedum dendroideum's final diameter, initial canopy cover and canopy growth rate reduced the risk of death by 55.1, 5.1 and 30.7%, respectively. The height growth rate of aloe and initial canopy cover reduced the risk of death by 93.9 and 2.4%, respectively. Plant species evaluated showed varying levels of adaptation. Aloe sp. was the species that adapted best to the site's soil and climate.

Rainfall and Temperature Variations in a Dry Tropical Environment of Nigeria

This study examines long-term rainfall and temperature variations over a dry tropical environment in Nigeria. An assessment of the variations of these weather variables showcases the extent of climate change limits and corresponding effects on the biotic environment. Rainfall and temperature data were obtained from Nigerian Meteorological Agency for a period of 31 years (1991-2020) for Kano and Katsina States. Descriptive statistics were used to determine the degree of variability of the weather variables across spatial domains. Results showed that there is a sharp contrast in mean annual rainfall amounts of 1154.1 mm and 569.6 mm for Kano and Katsina located in the dry continental and semi-arid climate zones of Nigeria respectively. It is revealed that the month of August had the highest mean monthly rainfall for both areas i.e. 359 mm and 194 mm with little or no trace during the dry season. The sharp difference in rainfall amount across spatial domains of the near similar climate zones shows that the Inter-tropical Discontinuity (ITD) does not completely overwhelm the northern band of Nigeria in August. The least variable monthly rainfall was in August and July with coefficient variations (CV) of 40% and 47% for Kano and Katsina. The months of February and March had the highest CV of 557% and 273% for the respective areas. In the examined areas the wet and dry seasons are from June-September and October-May respectively. The index of rainfall variability and drought intensity for the areas ranged from 0.85-0.95 and 45% indicating moderate variability and drought respectively. Mean annual temperature values are 33.4 °C and 33.8 °C for Kano and Katsina. The study recommends a proper climate observing scheme, most especially for agrarian practices so as to ensure profitable outputs for human sustainability.

Land Subsidence Susceptibility Mapping Using Interferometric Synthetic Aperture Radar (InSAR) and Machine Learning Models in a Semiarid Region of Iran

Most published studies identify groundwater extraction as the leading cause of land subsidence (LS). However, the causes of LS are not only attributable to groundwater extraction. Other land-use practices can also affect the occurrence of LS. In this study, radar interferometric techniques and machine learning (ML) models were used for the prediction, susceptibility zoning, and prioritization of influential variables in the occurrence of LS in the Bakhtegan basin. The LS rate was characterized by applying an interferometric synthetic aperture radar (InSAR). The recursive feature elimination (RFE) method was used to detect and select the dominant combination of indicators to prepare an LS susceptibility map. Three ML models, including random forest (RF), k-nearest neighbors (KNN), and classification and regression trees (CART), were used to develop predictive models. All three models had acceptable performance. Among the ML models, the RF model performed the best (i.e., Nash–Sutcliffe efficiency, Kling–Gupta efficiency, correlation coefficient, and percent bias metrics of 0.76, 0.78, 0.88, and 0.70 for validating phase, respectively). The analysis conducted on all three ML model outputs showed that high and very high LS susceptibility classes were located on or near irrigated agricultural land. The results indicate that the leading cause of land LS in the study region is not due to groundwater withdrawals. Instead, the distance from dams and the proximity to anticlines, faults, and mines are the most important identifiers of LS susceptibility. Additionally, the highest probability of LS susceptibility was found at distances less than 18 km from synclines, 6 to 13 km from anticlines, 23 km from dams, and distances less than 20 to more than 144 km from mines. The validated methods presented in this study are reproducible, transferrable, and recommended for mapping LS susceptibility in semiarid and arid climate zones with similar environmental conditions.

Influence of the ecosystem conversion process on the carbon and water cycles in different regions of China

Ecosystem conversion processes in different regions of China have different impacts on carbon and water cycle changes. Water use efficiency (WUE) is a key factor in coupling ecosystem carbon and water cycles, and it is important to quantify the effects of ecosystem conversional processes on the WUE in different regions of China to improve our understanding of the effects of ecological restoration projects and ecosystem conversional processes on carbon and water cycles in different regions. In this study, we proposed a dual–type extraction algorithm for ecosystem conversion processes (DTEA–ECP) to study the impact of ecosystem conversion processes on the WUE in different regions of China from 2001 to 2020. Our results showed that in the 2001–2020 period, the area of barren ecosystem conversion to grassland ecosystem increased at the fastest rate (4.29*103 km2 y-1). In the snow climate zone with dry winters and warm summers, projects returning cropland to forest were beneficial for improving WUE. In the northwestern part of the semiarid climate zone, returning cropland to grassland was beneficial for increasing the WUE of the ecosystem, while in northeastern China, the change in WUE after the conversion of grassland ecosystem to cropland ecosystem was not significant. WUE decreased after the conversion of forest ecosystems to grassland ecosystems, while WUE increased after the conversion of grassland ecosystems to forest ecosystems. This study identified where it was most suitable to plant each vegetation type and can help with the implementation of ecological projects such as afforestation, returning farmland to forest and grass, grassland protection and wind and sand management. The results provide information support for the in-depth development of national greening and low-carbon land restoration, improve vegetation carbon sink capacity, enhance carbon emission reduction and carbon sequestration, and help to achieve the goal of peak carbon and carbon neutrality.

Plasticity and coordination of branch and leaf traits in Ulmus pumila along a precipitation gradient

We compared branch and leaf functional traits of Ulmus pumila trees inhabiting different climatic zones (sub-humid, dry sub-humid and semi-arid zones), aiming to investigate the role of trait plasticity and coordination in tree acclimation to different water conditions. The results showed that leaf drought stress of U. pumila increased significantly from sub-humid to semi-arid climatic zones, as indicated by a 66.5% reduction in leaf midday water potential. In the sub-humid zone with less severe drought stress, U. pumila had higher stomatal density, thinner leaves, larger average vessel diameter, pit aperture area and membrane area, which could ensure the higher potential water acquisition. With the increases of drought stress in dry sub-humid and semi-arid zones, leaf mass per area and tissue density increased, and the pit aperture area and membrane area decreased, indicating stronger drought tolerance. Across different climatic zones, the vessel and pit structural characteristics were strongly coordinated, while a trade-off between xylem theoretical hydraulic conductivity and safety index was found. The plastic adjustment and coordinated variation of anatomical, structural and physiological traits may be an important mechanism contributing to the success of U. pumila in different climate zones with contrasting water environments.

Molecular genetics and phenotypic assessment of foxtail millet (Setaria italica (L.) P. Beauv.) landraces revealed remarkable variability of morpho-physiological, yield, and yield-related traits.

Foxtail millet (Setaria italica (L.) P. Beauv.) is highly valued for nutritional traits, stress tolerance and sustainability in resource-poor dryland agriculture. However, the low productivity of this crop in semi-arid regions of Southern India, is further threatened by climate stress. Landraces are valuable genetic resources, regionally adapted in form of novel alleles that are responsible for cope up the adverse conditions used by local farmers. In recent years, there is an erosion of genetic diversity. We have hypothesized that plant genetic resources collected from the semi-arid climatic zone would serve as a source of novel alleles for the development of climate resilience foxtail millet lines with enhanced yield. Keeping in view, there is an urgent need for conservation of genetic resources. To explore the genetic diversity, to identify superior genotypes and novel alleles, we collected a heterogeneous mixture of foxtail millet landraces from farmer fields. In an extensive multi-year study, we developed twenty genetically fixed foxtail millet landraces by single seed descent method. These landraces characterized along with four released cultivars with agro-morphological, physiological, yield and yield-related traits assessed genetic diversity and population structure. The landraces showed significant diversity in all the studied traits. We identified landraces S3G5, Red, Black and S1C1 that showed outstanding grain yield with earlier flowering, and maturity as compared to released cultivars. Diversity analysis using 67 simple sequence repeat microsatellite and other markers detected 127 alleles including 11 rare alleles, averaging 1.89 alleles per locus, expected heterozygosity of 0.26 and an average polymorphism information content of 0.23, collectively indicating a moderate genetic diversity in the landrace populations. Euclidean Ward's clustering, based on the molecular markers, principal coordinate analysis and structure analysis concordantly distinguished the genotypes into two to three sub-populations. A significant phenotypic and genotypic diversity observed in the landraces indicates a diverse gene pool that can be utilized for sustainable foxtail millet crop improvement.

Applicability of the HBV model to a human-influenced catchment in northern China

Abstract The Hydrologiska Byrans VattenbalansavdeIning (HBV) model is a catchment hydrological model that has been widely applied to hundreds of catchments worldwide. Taking the Nanjuma River Basin which is located in a semi-arid climate zone and has been highly regulated by human activities, as a case, the applicability of the HBV model to the basin was investigated. Results show that (1) due to environmental change, recorded stream flow of the Nanjuma River presented a significant decreasing trend, and the relationship between runoff and precipitation was changed as well, with the correlation coefficient decreasing from 0.58 in the natural period of 1961–1979 to 0.01 in a highly regulated period of 2000–2018. (2) The HBV model performs well on daily and monthly discharge simulation for the natural period with the Nash–Sutcliffe efficiency (NSE) coefficients in calibration and validation periods of 0.63 and 0.81 for daily discharge simulation. (3) The HBV model's applicability would like to decrease when the Nanjuma River Basin was moderately and intensively regulated by human activities. The daily-scale NSEs in moderate-disturbance and intensive-disturbance phases are 0.42 and −0.3, which means the HBV model almost lost its capacity in capturing hydrological features for a highly regulated catchment.

Quality Control and Homogeneity Analysis of Precipitation Time Series in the Climatic Region of Iraq

Non-climatic reasons, such as station replacement and changing the measurement device and calculation method, may make climate data unrepresentative of the actual variation of the regional climate. Data quality control and homogenization tests for climate data are critical. Thus, this study aims to evaluate the quality and homogeneity level of precipitation time series in arid and semi-arid climatic zones and specify the breakpoint in the datasets. The proposed methodology has been used to conduct arid and semi-arid representative case studies comprising 40 annual precipitation series for Iraq between 1979 and 2014. A Box-Cox transformation has been used to adjust the non-normally distributed datasets. Outliers have been censored by truncating extreme values. The results of the outliers indicate that they may be caused more by climate variability than by human-induced reasons. Homogeneity adjustments have been developed by applying these four homogeneity tests: Pettitt’s test, the Standard Normal Homogeneity method, Buishand’s test, and von Neumann’s check. Approximately 40% of the series (i.e., 16 stations out of 40) were homogeneous. Each homogeneity test was evaluated separately, and non-homogeneous stations were identified. Then, the series was classified into three groups that were assigned the labels “useful”, “doubtful”, and “suspect”. The results indicated that twenty-one stations were associated with the class ‘suspect’, three of the stations belonged to the class ‘doubtful’, and sixteen locations were within the class ‘useful’. Furthermore, the data analysis indicated no influence of the outliers on the results of the homogeneity tests. Accordingly, the study recommends further research on homogeneity tests that can be applied without considering outlier tests for similar case studies.

Skład frakcjonalny stożków gruzowych w kontekście zróżnicowanego klimatu peryglacjalnych stoków górskich (na przykładzie Spitsbergenu i środkowej Azji) = Grain-Size Composition on Talus Slopes in the context of disparate climatic conditions of periglacial mountain zones (exemplified by Spitsbergen and Central Asia)

Talus slopes origin is connected both with weathering and transport of the rock grain. The formation of these landforms is an effect of many climatological, morphological and geological factors. The grain size of the surface of the talus slope brings some information about the way of transport and deposition mechanisms. The main aim of the paper is to present different talus slope formation in two mountain locations - in arctic periglacial and semi-arid continental periglacial climate zones. Results from two study sites are presented. The first one was located on Spitsbergen Island, on its SW coast, near Polish Polar Station. The climate is arctic and periglacial, the average annual temperature is -3,2°C, annual precipitation is 494,6 mm. The slope is exposed to the west, rock face and talus slope are built with gneiss, crystalline shales with marbles intrusions. There is permafrost as well as an active layer noted on this study site. The second study site is in the Fann Mountains, part of Pamiro-Alay massive in Tajikistan. The annual temperature is about 1-2°C (meteo stations nearby: 6,6°C Iskanderkul 2204 m.a.s.l., 0,7°C Shahristan Pass 3143 m.a.s.l.), annual precipitation is about 300 mm. Slope is exposed to the south, rock material is a Devonian massive limestone. No permafrost was observed in this area. On both study sites, similar methods were used. Profiles with four measuring points were designated. On these points, 0,5 x 0,5 m square were marked and perpendicular photographs from a 1,5 m distance were made. Grain sizes were analyzed in BaseGRAIN software. In Asian periglacial high-mountain conditions lack of permafrost and low precipitation causes, that there is no factor of water. Domination of gravitational processes is sorting material when the heaviest rock fragments are transported longer and are deposited on lower positions on the slope.

Evaluating Shading Effects of PV Systems: Discrepancies in Simulation Software and Energy Consumption

Abstract A critical procedure in sustainable building design is that building energy consumption has significant implications for the global energy crisis and climate change. This study compares three simulation software programs for a photovoltaic system on a building’s roof. The low-rise residential buildings in three East Mediterranean cities (Amman, Mafraq, and Aqaba) represent moderate dry–warm, semi-arid, and humid subtropical climate zones were compared using three simulation software programs (IES-VE, Design-Builder, REVIT) for a typical building with PV on the roof and the second scenario without a PV system installed on the roof. This investigation aims to evaluate the shading effect of the PV system on a building’s roof structure by calculating the total heating and cooling loads required to maintain thermal comfort inside the building. The results showed significant discrepancies between the three software for the base building design and the PV system on the roof, with a range of around 50 %. This highlights the importance of evaluating and calibrating different simulation tools and using them with a great deal of caution.