Study of the Spatio-Temporal Variability of Rainfall in the Northern Region of Senegal

Senegal is a country of the Sahel. In this region, most of the populations live from agro-pastoral activities. The northern zone of Senegal is strongly influenced by river cultures. And the dynamics of the Senegal River are dependent on rainfall. The rainfall in the area is very closely linked to the dynamics of the atmosphere. The study of the spatio-temporal variability of rainfall in the northern region of Senegal requires quality rainfall observation data. It includes the Ferlo and the Senegal River valley, in particular the regions of Louga (department of Linguère included), Saint-Louis (departments of Dagana and Podor included) and Matam. These stations have been defined since Le Borgne (1988). The difficulty of having quality rain observation data can be resolved by using more accessible and good quality satellite data. Using satellite data, namely MSWEP, CRU, TAMSAT, ARC and PERSIANN, we showed the return of precipitation that appeared in 2000 and the unimodal cycle of precipitation in our study area. These data were validated using the correlation coefficient, the bias, the RMSE and the Nash index with observation data from the Regional Study Center for the Improvement of Adaptation to Drought (CERASS). The CRU data is then retained. Thus, this study made it possible to show the zonal distribution of rainfall in the northern zone of Senegal.

Spatio-temporal variability in sea surface wind stress near and off the east coast of Korea

Sea surface wind stress variabilities near and off the east coast of Korea, are examined using 7 kinds of wind datasets from measurements at 2 coastal (land) stations and 2 ocean buoys,satellite scatterometer (QuikSCAT), and global reanalyzed products (ECMWF,NOGAPS,and NCEP/NCAR). Temporal variabilities are analyzed at 3 frequency bands; synoptic (2-20 d), intra-seasonal (20-90 d),and seasonal (>90 d).Synoptic and intra-seasonal variations are predominant near and off the Donghae City due to the passage of the mesoscale weather system. Seasonal variation is caused by southeastward wind stress during Asian winter monsoon. The sea surface wind stress from reanalyzed datasets.QuikSCAT and KMA-B measurements off the coast show good agreement in the magnitude and direction,which are strongly aligned with the alongshore direction.At the land-based sites,wind stresses are much weaker by factors of 3-10 due to the mountainous landmass on the east parts of Korea Peninsula.The first EOF modes(67%-70%) of wind stresses from reanalyzed and QuikSCAT data have similar structures of the strong southeastward wind stress in winter along the coast but show different curl structures at scales less than 200 km due to the orographic effects.The second EOF modes (23%-25%) show southwestward wind stress in every September along the east coast of the North Korea

Spatio-temporal Variability of Northern Hemipheric Sea Level Pressure(SLP)and Precipitation over the Mid-to-Low Reaches of the Yangtze River

The spatio-temporal variability of Northern Hemisphere Sea Level Pressure （SLP） and precipitation over the mid-to-low reaches of the Yangtze River （PMLY） is analyzed jointly using the multi-taper/singular value decomposition method （MTM-SVD）. Statistically significant narrow frequency bands are obtained from the local fractional variance （LFV） spectrum. Significant interdecadal （i.e., 16-to-18-year periods） and interannual （i.e., 3-to-6-year periods） signals are identified. Moreover, a significant quasi-biennial signal is identified but only for PMLY data. The spatial joint evolution of patterns obtained for peaks in the LFV spectrum sheds light on relationships between SLP and PMLY： the Arctic Oscillation （AO） modulates the variability of the PMLY while the interannual variability of PMLY is in phase with the Northern Atlantic Oscillation （NAO） and the Northern Pacific Oscillation （NPO）.

Spatio-temporal Variability of Disastrous Convective Weather in China from 1961 to 2016

Based on the data of hail,gale,thunderstorm and lightning days in 2 481 stations in China from 1961 to 2016,the spatial and temporal distribution characteristics,periodicity and climate abruption characteristics of four kinds of disastrous convective weather in China were analyzed by various mathematical statistics methods. The results showed that in time,the days of four kinds of disastrous convective weather in China decreased,and the hail and thunderstorm days were characterized by " increasing firstly and then decreasing" from 1961 to 2016. The hail,gale,thunderstorm and lightning days in China had oscillation cycles of 3-5,2-3,1-2 and 1-4 a respectively,and the hail and thunderstorm days changed suddenly in 2002 and 1992 respectively. In space,the Qinghai-Tibet Plateau and western Sichuan were the highvalue distribution areas of hail,gale and thunderstorm days. The high-value distribution areas of thunderstorm days were also distributed to the south of the Yangtze River. South China and its southwestern regions at the same latitude were the high-value distribution areas of lightning days. In terms of trend,the hail days in China showed a decreasing trend mainly in the Qinghai-Tibet Plateau. The gale days in China decreased in the east,was unchanged in the central region,and increased and decreased alternately in the west. The thunderstorm days in China increased in Tibet,North China,Chongqing,Zhejiang and northwestern Heilongjiang. The lightning days in China decreased obviously to the south of the Yangtze River. In terms of the fluctuation,the hail days fluctuated greatly in the southeast. The gale days fluctuated greatly to the east of Hu Huanyong line. The thunderstorms days in China fluctuated greatly in the northwest and slightly in the southeast. In addition to the small fluctuation in northern Xinjiang and South China,the lightning days fluctuated greatly in other regions of China.

The Spatio-Temporal Variability of Rainfall over the Agro-Ecological Zones of Ghana

Rainfall variability plays an important role in many socio-economic activities such as food security, livelihood and farming in Ghana. Rainfall impact studies are thus very crucial for proper management of these key sectors of the country. This paper examines the seasonal and annual rainfall variability in the four agro-ecological zones of Ghana from the CHIRPS V2 rainfall time series spanning a period of 1981-2015. The rainfall indices were computed with the aid of the FClimDex package whereas the trends of these indices were further tested using the Mann Kendall trend test. The results show good agreement (r ≥ 0.7) between CHIRPS V2 and gauge in almost all portions of country although high biases were observed especially in DJF season over parts of the Northeastern (NE) portions of the country. The mean seasonal rainfall climatology over the country is observed to be in the range of 20 - 80 mm, 60 - 200 mm, 100 - 220 mm and 40 - 180 mm in DJF, MAM, JJA and SON seasons respectively with high intensities of rainfall dominating Southwestern portions of the country. The trend analysis revealed positive trends of consecutive dry days in the Transition, Forest and Coastal zones and negative trends in the Savannah zone of the country. Decreasing trends of consecutive wet days are observed over the Savannah, Transition and Coastal zones whereas increasing trends dominate the Forest zone. Savannah, Forest and Transition zones show weak increasing trends of the number of heavy rainfall days whilst weak decreasing trends are observed over the Coastal zone of the country. Similarly, weak increasing trends of the number of very heavy rainfall days are observed over all the agro-ecological zones except in the Transition zone. It is observed that the annual wet day rainfall total has increasing trend in the Savannah and Forest zones of the country whereas decreasing trends cover the remainder of the zones. The trends of these indices in the agro-ecological zones were all significant at a significant value of 0.05. This paper assessed the performance of the CHIRPS V2 rainfall data over the region and reports on the biases in seasonal rainfall amounts which are limited in previous studies. These findings have adverse impacts on rain-fed agricultural practices, water resource management and food security over the country.

Spatio-Temporal Variability of Shallow Groundwater Quality in a Hilly Red-Soil Agricultural Catchment in Subtropical Central China

Groundwater quality varies not only in space but also in time. In order to analyze the spatiotemporal variety of ground water quality, the concentration of ammonium nitrogen (NH4N), nitrate nitrogen (NO3N), total nitrogen (TN) and total phosphorus (TP) in very shallow groundwater were investigated in a red-soil catchment in subtropical central China, based on a three-dimensional kriging method. The spatio-temporal analysis demonstrated that NH4N, NO3N and TP presented strong spatio-temporal autocorrelation (with a nugget-to-sill ratio of <25%) and that TN presented a moderate spatio-temporal autocorrelation (with a nugget-to-sill ratio between 25% and 75%). According to the Chinese Groundwater Quality Standards, the ratio of areas contaminated by NH4N, NO3N, TN and TP to the whole catchment was 20.05%, 1.46%, 5.07%, 5.98%, respectively. The 3D delineation of continuously dynamic variation of contaminated area indicated that the catchment’s very shallow groundwater had a moderate contamination by NH4N, slight by TN and TP, and almost non by NO3N. Although the contaminated area was very small, only occurring in small dispersed patches, a close attention should be paid to the shallow groundwater quality because local farmers obtain their domestic drinking water directly from this shallow groundwater without any treatment prior to consuming and the potential health hazard is considerable. The findings from this study highlight the importance of surveillance of the contaminated area over time for decision making to protect public health and maintain sustainable development of the catchment.

Improved spatio-temporal alignment measurement method for hull deformation

In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Large misalignment angle and time delay often occur simultaneously and bring great challenges to the accurate measurement of hull deformation in space and time.The proposed method utilizes coarse alignment with large misalignment angle and time delay estimation of inertial measurement unit modeling to establish a brand-new spatiotemporal aligned hull deformation measurement model.In addition,two-step loop control is designed to ensure the accurate description of dynamic deformation angle and static deformation angle by the time-space alignment method of hull deformation.The experiments illustrate that the proposed method can effectively measure the hull deformation angle when time delay and large misalignment angle coexist.

Responses of Annual Variability of Vegetation NPP to Climate Variables Using Satellite Techniques in Gadarif State, Sudan

Plants play an essential role in matter and energy transformations and are key messengers in the carbon and energy cycle. Net primary productivity (NPP) reflects the capability of plants to transform solar energy into photosynthesis. It is very sensible for factors affecting on vegetation variability such as climate, soils, plant characteristics and human activities. So, it can be used as an indicator of actual and potential trend of vegetation. In this study we used the actual NPP which was derived from MODIS to assess the response of NPP to climate variables in Gadarif State, from 2000 to 2010. The correlations between NPP and climate variables (temperature and precipitation) are calculated using Pearson’s Correlation Coefficient and ordinary least squares regression. The main results show the following 1) the correlation Coefficient between NPP and mean annual temperature is Somewhat negative for Feshaga, Rahd, Gadarif and Galabat areas and weakly negative in Faw area;2) the correlation Coefficient between NPP and annual total precipitation is weakly negative in Faw, Rahd and Galabat areas and somewhat negative in Galabat and Rahd areas. This study demonstrated that the correlation analysis between NPP and climate variables (precipitation and temperature) gives reliably result of NPP responses to climate variables that is clearly in a very large scale of study area.

Spatio-Temporal Change of Dispersal Areas of Greater Kudu (Tragelaphus strepsiceros) in Lake Bogoria Landscape, Kenya

Decline in wildlife populations is manifest globally, regionally and locally. A wildlife decline of 68% has been reported in Kenya’s rangelands with Baringo County experiencing more than 85% wildlife loss in the last four decades. Greater Kudu (Tragelaphus strepsiceros) is endemic to Lake Bogoria landscape in Baringo County and constitutes a major tourist attraction for the region necessitating use of its photo on the County’s logo and thus a flagship species. Tourism plays a central role in Baringo County’s economy and is a major source of potential growth and employment creation. The study was carried out to assess spatio-temporal change of dispersal areas of Greater Kudu (GK) in Lake Bogoria landscape in the last four years for enhanced adaptive management and improved livelihoods. GK population distribution primary data collected in December 2022 and secondary data acquired from Lake Bogoria National Game Reserve (LBNGR) for 2019 and 2020 were digitized using in a Geographic Information System (GIS). Measures of dispersion and point pattern analysis (PPA) were used to analyze dispersal of GK population using GIS. Spatio-temporal change of GK dispersal in LBNR was evident thus the null hypothesis was rejected. It is recommended that anthropogenic activities contributing to GK’s habitat degradation be curbed by providing alternative livelihood sources and promoting community adoption of sustainable technologies for improved livelihoods.

The Influence of Climate Change and Variability on Spatio-Temporal Rainfall and Temperature Distribution in Zanzibar

Climate change has resulted in serious social-economic ramifications and extremely catastrophic weather events in the world, Tanzania and Zanzibar in particular, with adaptation being the only option to reduce impacts. The study focuses on the influence of climate change and variability on spatio-temporal rainfall and temperature variability and distribution in Zanzibar. The station observation datasets of rainfall, Tmax and Tmin acquired from Tanzania Meteorological Authority (TMA) and the Coordinated Regional Climate Downscaling Experiment program (CORDEX) projected datasets from the Regional climate model HIRHAM5 under driving model ICHEC-EC-EARH, for the three periods of 1991-2020 used as baseline (HS), 2021-2050 as near future (NF) and 2051-2080 far future (FF), under two representative concentration pathways (RCP) of 4.5 and 8.5, were used. The long-term observed Tmax and Tmin were used to produce time series for observing the nature and trends, while the observed rainfall data was used for understanding wet and dry periods, trends and slope (at p ≤ 0.05) using the Standardized Precipitation Index (SPI) and the Mann Kendall test (MK). Moreover, the Quantum Geographic Information System (QGIS) under the Inverse Distance Weighting (IDW) interpolation techniques were used for mapping the three decades of 1991-2000 (hereafter D1), 2001-2010 (hereafter D2) and 2011-2020 (hereafter D3) to analyze periodical spatial rainfall distribution in Zanzibar. As for the projected datasets the Climate Data Operator Commands (CDO), python scripts and Grid analysis and Display System (GrADS) soft-wares were used to process and display the results of the projected datasets of rainfall, Tmax and Tmin for the HS, NF and FF, respectively. The results show that the observed Tmax increased by the rates of 0.035℃ yr-1 and 0.0169℃ yr-1, while the Tmin was increased by a rate of 0.064℃ yr-1 and 0.104℃ yr-1 for Unguja and Pemba, respectively. The temporal distribution of wetness and dryness indices showed a climate shift from near normal to moderate wet during 2005 at Zanzibar Airport, while normal to moderately dry conditions, were observed in Pemba at Matangatuani. The decadal rainfall variability and distributions revealed higher rainfall intensity with an increasing trend and good spatial distribution in D3 from March to May (MAM) and October to December (OND). The projected results for Tmax during MAM and OND depicted higher values ranging from 1.7℃ - 1.8℃ to 1.9℃ - 2.0℃ and 1.5℃ to 2.0℃ in FF compared to NF under both RCPs. Also, higher Tmin values of 1.12℃ - 1.16℃ was projected in FF for MAM and OND under both RCPs. Besides, the rainfall projection generally revealed increased rainfall intensity in the range of 0 - 25 mm for Pemba and declined rainfall in the range of 25 - 50 mm in Unguja under both RCPs in perspectives of both NF and FF. Conclusively the study has shown that the undergoing climate change has posed a significant impact on both rainfall and temperature spatial and temporal distributions in Zanzibar (Unguja and Pemba), with Unguja being projected to have higher rainfall deficits while increasing rainfall strengths in Pemba. Thus, the study calls for more studies and formulation of effective adaptation, strategies and resilience mechanisms to combat the projected climate change impacts especially in the agricultural sector, water and food security.

Identifying the spatio-temporal variability of human activity intensity and associated drivers: a case study on the Tibetan Plateau

Human activities have significantly degraded ecosystems and their associated services.By understanding the spatio-temporal variability and drivers of human activity intensity(HAI),we can better evaluate the interactions between human and terrestrial ecosystems,which is essential for land-use related decision making and eco-environmental construction.As the“third pole,”the Tibetan Plateau(TP)plays a strong role in shaping the global environment,and acts as an important ecological security barrier for China.Based on land-use/cover change data,environmental geographic data,and socioeconomic data,we adopted a method for converting different land use/cover types into construction land equivalent to calculate the HAI value and applied the Getis-Ord Gi*statistic to analyze the spatio-temporal dynamics associated with HAI since 1980 on the TP.Thereafter,we explored the forces driving the HAI changes using GeoDetector software and a correlation analysis.The main conclusions are as follows:It was observed that HAI increased slowly from 3.52%to 3.65%during the 1980-2020 period,with notable increases in the western part of the Qaidam Basin and Hehuang Valley.Spatially,HAI was associated with a significant agglomeration effect,which was mainly concentrated in the regions of the Yarlung Zangbo and Yellow-Huangshui rivers.Both natural and anthropogenic factors were identified as important driving forces behind the spatial changes in HAI,of which soil type,gross domestic product,and population density had the greatest influence.Meanwhile,the temporal changes in HAI were largely driven by economic development.This information provides crucial guidance for territory development planning and ecological-protection policy decisions.

Leveraging Transfer Learning for Spatio-Temporal Human Activity Recognition from Video Sequences

Human Activity Recognition(HAR)is an active research area due to its applications in pervasive computing,human-computer interaction,artificial intelligence,health care,and social sciences.Moreover,dynamic environments and anthropometric differences between individuals make it harder to recognize actions.This study focused on human activity in video sequences acquired with an RGB camera because of its vast range of real-world applications.It uses two-stream ConvNet to extract spatial and temporal information and proposes a fine-tuned deep neural network.Moreover,the transfer learning paradigm is adopted to extract varied and fixed frames while reusing object identification information.Six state-of-the-art pre-trained models are exploited to find the best model for spatial feature extraction.For temporal sequence,this study uses dense optical flow following the two-stream ConvNet and Bidirectional Long Short TermMemory(BiLSTM)to capture longtermdependencies.Two state-of-the-art datasets,UCF101 and HMDB51,are used for evaluation purposes.In addition,seven state-of-the-art optimizers are used to fine-tune the proposed network parameters.Furthermore,this study utilizes an ensemble mechanism to aggregate spatial-temporal features using a four-stream Convolutional Neural Network(CNN),where two streams use RGB data.In contrast,the other uses optical flow images.Finally,the proposed ensemble approach using max hard voting outperforms state-ofthe-art methods with 96.30%and 90.07%accuracies on the UCF101 and HMDB51 datasets.

Relationship between spatio-temporal evolution of soil pH and geological environment/surface cover in the eastern Nenjiang River Basin of Northeast China during the past 30 years

To illuminate the spatio-temporal variation characteristics and geochemical driving mechanism of soil pH in the Nenjiang River Basin,the National Multi-objective Regional Geochemical Survey data of topsoil,the Second National Soil Survey data and Normalized Difference Vegetation Index(NDVI)were analyzed.The areas of neutral and alkaline soil decreased by 21100 km^(2)and 30500 km^(2),respectively,while that of strongly alkaline,extremely alkaline,and strongly acidic soil increased by 19600 km^(2),18200 km^(2),and 15500 km^(2),respectively,during the past 30 years.NDVI decreased with the increase of soil pH when soil pH>8.0,and it was reversed when soil pH<5.0.There were significant differences in soil pH with various surface cover types,which showed an ascending order:Arbor<reed<maize<rice<high and medium-covered meadow<low-covered meadow<Puccinellia.The weathering products of minerals rich in K_(2)O,Na_(2)O,CaO,and MgO entered into the low plain and were enriched in different parts by water transportation and lake deposition,while Fe and Al remained in the low hilly areas,which was the geochemical driving mechanism.The results of this study will provide scientific basis for making scientific and rational decisions on soil acidification and salinization.

Spatio-Temporal Pulsating Dissipative Solitons through Collective Variable Methods

A semi-analytical approach for the pulsating solutions of the 3D complex Cubic-quintic Ginzburg-Landau Equation (CGLE) is presented in this article. A collective variable approach is used to obtain a system of variational equations which give the evolution of the light pulses parameters as a function of the propagation distance. The collective coordinate approach is incomparably faster than the direct numerical simulation of the propagation equation. This allows us to obtain, efficiently, a global mapping of the 3D pulsating soliton. In addition it allows describing the influence of the parameters of the equation on the various physical parameters of the pulse and their dynamics.

Spatio-Temporal Analysis of Drought in the North-Eastern Coastal Region of Vietnam Using the Standardized Precipitation Index (SPI)

Spatio-temporal analysis of drought provides valuable information for drought management and damage mitigation. In this study, the Standardized Precipitation Index at the time scale of 6 months (SPI-6) is selected to reflect drought conditions in the North-Eastern coastal region of Vietnam. The drought events and their characteristics from 1981 to 2019 are detected at 9 meteorological stations and 10 Chirps rainfall stations. The spatio-temporal variation of drought in the study region is analyzed on the basis of the number, duration, severity, intensity, and peak of the detected drought events at the 19 stations. The results show that from 1981 to 2019 the drought events mainly occurred with 1-season duration and moderate intensity and peak. The number, duration, severity, and peak of the drought events were the greatest in the period 2001-2010 and were the smallest in the period 2011-2019. Among the 19 stations, the drought duration tends to decrease at 11 stations, increase at 7 stations, and has a slight variant at 1 station;the drought severity tends to decrease at 14 stations, increase at 4 stations, and has not a significant trend at 1 station;the drought intensity tends to decrease at 17 stations, increase at 1 station, and has a slight variant at 1 station;and the drought peak tends to decrease at 18 stations and increase at 1 station.

Dynamic Spatio-Temporal Modeling in Disease Mapping

Spatio-temporal models are valuable tools for disease mapping and understanding the geographical distribution of diseases and temporal dynamics. Spatio-temporal models have been proven empirically to be very complex and this complexity has led many to oversimply and model the spatial and temporal dependencies independently. Unlike common practice, this study formulated a new spatio-temporal model in a Bayesian hierarchical framework that accounts for spatial and temporal dependencies jointly. The spatial and temporal dependencies were dynamically modelled via the matern exponential covariance function. The temporal aspect was captured by the parameters of the exponential with a first-order autoregressive structure. Inferences about the parameters were obtained via Markov Chain Monte Carlo (MCMC) techniques and the spatio-temporal maps were obtained by mapping stable posterior means from the specific location and time from the best model that includes the significant risk factors. The model formulated was fitted to both simulation data and Kenya meningitis incidence data from 2013 to 2019 along with two covariates;Gross County Product (GCP) and average rainfall. The study found that both average rainfall and GCP had a significant positive association with meningitis occurrence. Also, regarding geographical distribution, the spatio-temporal maps showed that meningitis is not evenly distributed across the country as some counties reported a high number of cases compared with other counties.

“stppSim”: A Novel Analytical Tool for Creating Synthetic Spatio-Temporal Point Data

In crime science, understanding the dynamics and interactions between crime events is crucial for comprehending the underlying factors that drive their occurrences. Nonetheless, gaining access to detailed spatiotemporal crime records from law enforcement faces significant challenges due to confidentiality concerns. In response to these challenges, this paper introduces an innovative analytical tool named “stppSim,” designed to synthesize fine-grained spatiotemporal point records while safeguarding the privacy of individual locations. By utilizing the open-source R platform, this tool ensures easy accessibility for researchers, facilitating download, re-use, and potential advancements in various research domains beyond crime science.

A Stroke-Limitation AMD Control System with Variable Gain and Limited Area for High-Rise Buildings

Collisions between a moving mass and an anti-collision device increase structural responses and threaten structural safety.An active mass damper(AMD)with stroke limitations is often used to avoid collisions.However,a strokelimited AMD control system with a fixed limited area shortens the available AMD stroke and leads to significant control power.To solve this problem,the design approach with variable gain and limited area(VGLA)is proposed in this study.First,the boundary of variable-limited areas is calculated based on the real-time status of the moving mass.The variable gain(VG)expression at the variable limited area is deduced by considering the saturation of AMD stroke.Then,numerical simulations of a stroke-limited AMD control system with VGLA are conducted on a high-rise building structure.These numerical simulations show that the proposed approach has superior strokelimitation performance compared with a stroke-limited AMD control system with a fixed limited area.Finally,the proposed approach is validated through experiments on a four-story steel frame.

A novel variable-order fractional chaotic map and its dynamics

In recent years,fractional-order chaotic maps have been paid more attention in publications because of the memory effect.This paper presents a novel variable-order fractional sine map(VFSM)based on the discrete fractional calculus.Specially,the order is defined as an iterative function that incorporates the current state of the system.By analyzing phase diagrams,time sequences,bifurcations,Lyapunov exponents and fuzzy entropy complexity,the dynamics of the proposed map are investigated comparing with the constant-order fractional sine map.The results reveal that the variable order has a good effect on improving the chaotic performance,and it enlarges the range of available parameter values as well as reduces non-chaotic windows.Multiple coexisting attractors also enrich the dynamics of VFSM and prove its sensitivity to initial values.Moreover,the sequence generated by the proposed map passes the statistical test for pseudorandom number and shows strong robustness to parameter estimation,which proves the potential applications in the field of information security.

Remote Sensing Derived Phenological Metrics to Assess the Spatio-Temporal Growth Variability in Cropping Fields

Precision Agriculture (PA) recognizes and manages intra-field spatial variability to increase profitability and reduced environmental impact. Site Specific Crop Management (SSCM), a form of PA, subdivides a cropping field into uniformly manageable zones, based on quantitative measurement of yield limiting factors. In Mediterranean environments, the spatial and temporal yield variability of rain-fed cropping system is strongly influenced by the spatial variability of Plant Available Water-holding Capacity (PAWC) and its strong interaction with temporally variable seasonal rainfall. The successful adoption of SSCM depends on the understanding of both spatial and temporal variabilities in cropping fields. Remote sensing phenological metrics provide information about the biophysical growth conditions of crops across fields. In this paper, we examine the potential of phenological metrics to assess the spatial and temporal crop yield variability across a wheat cropping field at Minnipa, South Australia. The Minnipa field was classified into three management zones using prolonged observations including soil assessment and multiple year yield data. The main analytical steps followed in this study were: calculation of the phenological metrics using time series NDVI data from Moderate Resolution Imaging Spectroscope (MODIS) for 15 years (2001-2015);producing spatial trend and temporal variability maps of phenological metrics;and finally, assessment of association between the spatial patterns and temporal variability of the metrics with management zones of the cropping field. The spatial trend of the seasonal peak NDVI metric showed significant association with the management zone pattern. In terms of temporal variability, Time-integrated NDVI (TINDVI) showed higher variability in the “good” zone compared with the “poor” zone. This indicates that the magnitude of the seasonal peak is more sensitive to soil related factors across the field, whereas TINDVI is more sensitive to seasonal variability. The interpretation of the association between phenological metrics and the management zone site conditions was discussed in relation to soil-climate interaction. The results demonstrate the potential of the phenological metrics to assess the spatial and temporal variability across cropping fields and to understand the soil-climate interaction. The approach presented in this paper provides a pathway to utilize phenological metrics for precision agricultural management application.