scholarly journals Modeling Dryness Severity Using Artificial Neural Network at the Okavango Delta, Botswana

2016 ◽  
Vol 18 (3) ◽  
pp. 463-481 ◽  
Keyword(s):  
Water Balance ◽  
Time Scales ◽  
Climatic Variability ◽  
High Variability ◽  
Okavango Delta ◽  
Annual Rainfall ◽  
Generalized Logistic Distribution ◽  
Artificial Neural ◽  
The Impact ◽  
Rainy Days

<div> <p>Water balance studies in the Okavango Delta indicate that more than 90% of inflow into the Delta is lost through evaporation. This coupled with high climatic variability threatens the ecohydrology of the Delta. Trends indicate decreasing rainfall amounts and increasing temperature at the area of the Delta. The main aim of this study was therefore to investigate long term trends and variability in rain onset, cessation, number of rainy days and their impact on the dryness index at the Delta. The impact of the above variables is expressed through the standardized precipitation and evaporation index (SPEI) quantified by aggregating the climate water balance and fitting monthly series to a generalized logistic distribution using L-Moments. The SPEI, determined at windows of different time scales of one, three and twelve months, provided an extensive evaluation of dryness severity and its impact on this sensitive ecosystem. Rain onset and cessation dates were generated from cumulative pentad rainfall&ndash;evapotranspiration relationships. Analysis of climatic data showed mean rain onset occurring in November and ceding in March with average of 44 rainy days between 1970/71 and 2013/14. The results revealed a decrease in the number of rainy days at a rate of 0.16 days/yr and of the duration of the rainy season at 0.25 days/yr with high variability. Annual rainfall was found to decrease at the rate of 1.60 mm/yr with 6.8% probability of failure in rainfall onset. Analysis further revealed that both extreme dryness and wetness are rare phenomena with probabilities of less than 1% and near normal conditions for 67% of the time for all SPEI time scales. Although gradual increase in dryness in the Delta is attributed to high climatic variability, simulations undertaken using Artificial Neural Networks did not predict any major changes in the next five years. However, vulnerability to severe droughts is not completely ruled out because of the high variability in rainfall and of the location of the Delta in a semi-arid zone.&nbsp;</p> </div> <p>&nbsp;</p>

scholarly journals Hydro-Climatic Variability: A Characterisation and Trend Study of the Awash River Basin, Ethiopia

Hydrology ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 35 ◽  
Author(s):  
Mahtsente Tibebe Tadese ◽  
Lalit Kumar ◽  
Richard Koech ◽  
Birhanu Zemadim
Keyword(s):  
River Basin ◽  
Climatic Variability ◽  
Management Strategies ◽  
Annual Rainfall ◽  
Sustainable Water Management ◽  
Mk Test ◽  
Awash River Basin ◽  
Research Findings ◽  
Droughts And Floods ◽  
The Impact

The objective of this study was to characterize, quantify and validate the variability and trends of hydro-climatic variables in the Awash River Basin (ARB) in Ethiopia using graphical and statistical methods. The rainfall and streamflow trends and their relationships were evaluated using the regression method, Mann–Kendall (MK) test and correlation analysis. The analysis focused on rainfall and streamflow collected from 28 and 18 stations, respectively. About 85.7% and 75.3% of the rainfall stations exhibited normal to moderate variability in annual and June to September rainfall, respectively, whereas 96.43% of rainfall stations showed high variability in March to May. The MK test showed that most of the significant trends in annual rainfall were decreasing except in two stations. These research findings provide valuable information on the characteristics, variability, and trend of rainfall and streamflow necessary for the design of sustainable water management strategies and to reduce the impact of droughts and floods in the ARB.

scholarly journals Hydrologic performance of bioretention in an expressway service area

2018 ◽  
Vol 77 (7) ◽  
pp. 1829-1837 ◽  
Author(s):  
Jianping Gao ◽  
Junkui Pan ◽  
Ning Hu ◽  
Chengzuo Xie
Keyword(s):  
Water Balance ◽  
Reduction Rate ◽  
Service Area ◽  
Annual Rainfall ◽  
Design Parameters ◽  
Effective Measure ◽  
Bioretention System ◽  
Runoff Reduction ◽  
The Impact ◽  
Hydrologic Performance

Abstract Bioretention can be an effective measure for stormwater treatment. However, there is a lack of systematic analysis of the impact of bioretention design parameters on hydrologic performance. Herein, SWMM and RECARGA models were applied to generate the typical annual rainfall runoff and simulate the water balance of the bioretention system in an expressway service area. The purpose of the investigation was to identify key design parameters for the bioretention system and delineate the priorities in developing the design. Results showed that the average groundwater recharge ratios for bioretention basins with and without an underdrain were 58.29% and 92.27%, respectively, the average overflow ratios were 4.13% and 4.19%, the average evapotranspiration ratios were 4.48% and 4.47%, and the average outflow ratio for bioretention with an underdrain was 33.94%. The ratio of the bioretention area to drainage area, and the saturated infiltration rates of planting soil and native soil were the main factors influencing water balance, while the underdrain diameter and gravel layer depth exerted little effect. Based on the impact analysis, multivariate nonlinear regression models of runoff reduction rate for two types of bioretention basin were established, which both exhibited high determination coefficients and acceptable Nash–Sutcliffe coefficients.

scholarly journals Livelihood diversification and climate change adaptation in Indo-Gangetic plains: implication of rainfall regimes

2015 ◽  
Vol 16 ◽  
pp. 77-94 ◽  
Author(s):  
Gopal D Bhatta ◽  
Pramod K Aggarwal ◽  
Amit Shrivastava
Keyword(s):  
Local Adaptation ◽  
Climatic Factors ◽  
Climatic Variability ◽  
Household Survey ◽  
Annual Rainfall ◽  
Rainfall Regime ◽  
Livelihood Diversification ◽  
Gangetic Plains ◽  
High Rainfall ◽  
The Impact

We investigate whether spatial variations in climatic resource such as rainfall have prompted livelihood diversification, local adaptation and household food availability in Indo-Gangetic Plains using data from a household survey of 2660 farm-families carried out in India, Bangladesh and Nepal. We found that on-farm livelihood sources are higher in high rainfall regime (1300-1800 mm) compared to medium (<1300 mm) and very high rainfall regime (>1800 mm). The off-farm sources are higher in medium rainfall regime. Although a large number of changes are attributed to harvest better yield, yet farmers made numbers of changes in response to climatic variability as well. Although agricultural livelihood and local adaptation are restrained by several climatic and non-climatic factors; the amount of annual rainfall significantly affects livelihood diversification, and the impact of climatic stressors becomes more pronounced when there is interaction with other non-climatic factors. The results imply that livelihood and adaptation strategies should be tailor made along the climatic and non-climatic resources.

Modeling Discharge of the Bangga Watershed under Climate Change

2015 ◽  
Vol 776 ◽  
pp. 133-138 ◽  
Author(s):  
I. Wayan Sutapa ◽  
Moh Bisri ◽  
Rispiningtati ◽  
Lily Montarcih
Keyword(s):  
Climate Change ◽  
Water Balance ◽  
Simulation Models ◽  
Balance Model ◽  
Effect Of Temperature ◽  
Annual Rainfall ◽  
Canopy Interception ◽  
Using Data ◽  
Monthly Water Balance ◽  
The Impact

The purpose of this research is to create a model of the discharge as the impact of climate change due to global warming. The study was conducted using data from the Bangga watershed. Monthly water balance model used is the development of a model FJ. Mock by entering the natural phenomena that occur at this time such as climate change, canopy interception, rainfall distribution based on land use, soil type and soil characteristics. Calibration of water balance is used to determine the performance of the models to variations in climate change. Then, analysis is conducted as the effect of rain and temperature on runoff at river Bangga. The conclusion of this research were: 1) Accuracy of discharge simulation models against observed discharge is quite good, which is characterized by the Nash coefficient (Ns) close to one except for a few periods and annual rainfall runoff ratio (RE) approaches one. 2) Changes in rainfall have a considerable influence on the runoff, while the effect of temperature on runoff is not too significant.

scholarly journals Assessing the impact of seasonal-rainfall anomalies on catchment-scale water balance components

2020 ◽  
Vol 24 (6) ◽  
pp. 3211-3227 ◽  
Author(s):  
Paolo Nasta ◽  
Carolina Allocca ◽  
Roberto Deidda ◽  
Nunzio Romano
Keyword(s):  
Water Balance ◽  
Rainy Season ◽  
Annual Rainfall ◽  
Water Yield ◽  
Implicit Assumption ◽  
Regression Equations ◽  
Catchment Scale ◽  
Water Balance Components ◽  
Rainfall Seasonality ◽  
The Impact

Abstract. Although water balance components at the catchment scale are strongly related to annual rainfall, the availability of water resources in Mediterranean catchments also depends on rainfall seasonality. Observed seasonal anomalies in historical records are fairly episodic, but an increase in their frequency might exacerbate water deficit or water excess if the rainy season shortens or extends its duration, e.g., due to climate change. This study evaluates the sensitivity of water yield, evapotranspiration, and groundwater recharge to changes in rainfall seasonality by using the Soil Water Assessment Tool (SWAT) model applied to the upper Alento River catchment (UARC) in southern Italy, where a long time series of daily rainfall is available from 1920 to 2018. We compare two distinct approaches: (i) a “static” approach, where three seasonal features (namely rainy, dry, and transition fixed-duration 4-month seasons) are identified through the standardized precipitation index (SPI) and (ii) a “dynamic” approach based on a stochastic framework, where the duration of two seasons (rainy and dry seasons) varies from year to year according to a probability distribution. Seasonal anomalies occur when the transition season is replaced by the rainy or dry season in the first approach and when season duration occurs in the tails of its normal distribution in the second approach. Results are presented within a probabilistic framework. We also show that the Budyko curve is sensitive to the rainfall seasonality regime in UARC by questioning the implicit assumption of a temporal steady state between annual average dryness and the evaporative index. Although the duration of the rainy season does not exert a major control on water balance, we were able to identify season-dependent regression equations linking water yield to the dryness index in the rainy season.

Assessing the impact of rainfall seasonality anomalies on catchment-scale water resources availability

2020 ◽  
Author(s):  
Nunzio Romano ◽  
Carolina Allocca ◽  
Roberto Deidda ◽  
Paolo Nasta
Keyword(s):  
Water Balance ◽  
Groundwater Recharge ◽  
Rainy Season ◽  
Annual Rainfall ◽  
Water Yield ◽  
Implicit Assumption ◽  
Water Balance Components ◽  
Annual Average ◽  
Rainfall Seasonality ◽  
The Impact

&lt;p&gt;Water balance components depend on annual rainfall amount and seasonality in Mediterranean catchments. A high percentage of the annual rainfall occurs between late fall and early spring and feeds natural and artificial water reservoirs. This amount of water stored in the mild-rainy season is used to offset rainfall shortages in the hot-dry season (between late spring and early fall). Observed seasonal anomalies in historical records are quite episodic, but an increase of their frequency might exacerbate water stress or water excess if the rainy season shortens or extends its duration, e.g. due to climate change. Hydrological models are useful tools to assess the impact of seasonal anomalies on the water balance components and this study evaluates the sensitivity of water yield, evapotranspiration and groundwater recharge on changes in rainfall seasonality by using the Soil Water Assessment Tool (SWAT) model. The study area is the Upper Alento River Catchment (UARC) in southern Italy where a long time-series of daily rainfall is available from 1920 to 2018. To assess seasonality anomalies, we compare two approaches: a &amp;#8220;static&amp;#8221; approach based on the Standardized Precipitation Index (SPI), and a &amp;#8220;dynamic&amp;#8221; approach that identifies the rainy season by considering rainfall magnitude, timing, and duration. The former approach rigidly selects three seasonal features, namely rainy, dry, and transition seasons, the latter being occasionally characterized by similar properties to the rainy or dry periods. The &amp;#8220;dynamic&amp;#8221; approach, instead, is based on a time-variant duration of the rainy season and enables to corroborate the aforementioned results within a probabilistic framework. A dry seasonal anomaly is characterized by a decrease of 241 mm in annual average rainfall inducing a concurrent decrease of 116 mm in annual average water yield, 60 mm in actual evapotranspiration and 66 mm in groundwater recharge. We show that the Budyko curve is sensitive to the seasonality regime in UARC by questioning the implicit assumption of temporal steady-state between annual average dryness and evaporative index. Although the duration of the rainy season does not exert a major control on water balance, we have been able to identify seasonal-dependent regression equations linking water yield to dryness index over the rainy season.&lt;/p&gt;

scholarly journals Spatio-temporal monitoring of vegetation phenology in the dry sub-humid region of Nigeria using time series of AVHRR NDVI and TAMSAT datasets

2018 ◽  
Vol 10 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Babatunde Adeniyi Osunmadewa ◽  
Worku Zewdie Gebrehiwot ◽  
Elmar Csaplovics ◽  
Olabinjo Clement Adeofun
Keyword(s):  
Time Series ◽  
Land Cover ◽  
Time Series Data ◽  
Anthropogenic Activities ◽  
Phase 1 ◽  
Climatic Variability ◽  
Annual Rainfall ◽  
Series Data ◽  
Vegetation Phenology ◽  
The Impact

Abstract Time series data are of great importance for monitoring vegetation phenology in the dry sub-humid regions where change in land cover has influence on biomass productivity. However few studies have inquired into examining the impact of rainfall and land cover change on vegetation phenology. This study explores Seasonal Trend Analysis (STA) approach in order to investigate overall greenness, peak of annual greenness and timing of annual greenness in the seasonal NDVI cycle. Phenological pattern for the start of season (SOS) and end of season (EOS) was also examined across different land cover types in four selected locations. A significant increase in overall greenness (amplitude 0) and a significant decrease in other greenness trend maps (amplitude 1 and phase 1) was observed over the study period. Moreover significant positive trends in overall annual rainfall (amplitude 0) was found which follows similar pattern with vegetation trend. Variation in the timing of peak of greenness (phase 1) was seen in the four selected locations, this indicate a change in phenological trend. Additionally, strong relationship was revealed by the result of the pixel-wise regression between NDVI and rainfall. Change in vegetation phenology in the study area is attributed to climatic variability than anthropogenic activities.

scholarly journals Assessing the impact of rainfall seasonality anomalies on catchment-scale water balance components

2019 ◽  
Author(s):  
Paolo Nasta ◽  
Carolina Allocca ◽  
Roberto Deidda ◽  
Nunzio Romano
Keyword(s):  
Water Balance ◽  
Rainy Season ◽  
Annual Rainfall ◽  
Water Yield ◽  
Dynamic Approach ◽  
Catchment Scale ◽  
Water Balance Components ◽  
Annual Average ◽  
Rainfall Seasonality ◽  
The Impact

Abstract. Water balance components at catchment scale are strongly related to annual rainfall amount. Nonetheless, water resources availability in Mediterranean catchments depends also on rainfall seasonality. Indeed, a high percentage of annual rainfall occurs between late fall and early spring and feeds natural and artificial water reservoirs. This amount of water stored in the mild-rainy season is used to offset rainfall shortages in the hot-dry season (between late spring and early fall). Observed seasonal anomalies in historical records are quite episodic, but an increase of their frequency might exacerbate water stress or water excess if the rainy season shortens or extends its duration, e.g. due to climate change. Hydrological models are useful tools to assess the impact of seasonal anomalies on the water balance components and this study evaluates the sensitivity of water yield, evapotranspiration and groundwater recharge on changes in rainfall seasonality by using the Soil Water Assessment Tool (SWAT) model. The study area is the Upper Alento River Catchment (UARC) in southern Italy where a long time-series of daily rainfall is available from 1920 to 2018. To assess seasonality anomalies, we compare two distinct approaches: a static approach based on the Standardized Precipitation Index (SPI), and a dynamic approach that identifies the rainy season by considering rainfall magnitude, timing, and duration. The former approach rigidly selects three seasonal features, namely rainy, dry, and transition seasons, the latter being occasionally characterized by similar properties to the rainy or dry periods. The dynamic approach, instead, is based on a time-variant duration of the rainy season and enables to corroborate the aforementioned results within a probabilistic framework. A dry seasonal anomaly is characterized by a decrease of 241 mm in annual average rainfall inducing a concurrent decrease of 116 mm in annual average water yield, 60 mm in actual evapotranspiration and 66 mm in groundwater recharge. We show that the Budyko curve is sensitive to the seasonality regime in UARC by questioning the implicit assumption of temporal steady-state between annual average dryness and evaporative index. Although the duration of the rainy season does not exert a major control on water balance, we have been able to identify seasonal-dependent regression equations linking water yield to dryness index over the rainy season.

Impact of changing rainfall conditions on surface and groundwater resources in an experimental watershed in Greece

2013 ◽  
Vol 12 (2) ◽  
pp. 119-125
Keyword(s):  
Groundwater Resources ◽  
Annual Runoff ◽  
Annual Rainfall ◽  
Rainfall Regime ◽  
Winter Rainfall ◽  
Rainfall Depth ◽  
Rainfall Volume ◽  
The Mean ◽  
Groundwater Reserves ◽  
The Impact

The present study concerns the impact of a change in the rainfall regime on surface and groundwater resources in an experimental watershed. The research is conducted in a gauged mountainous watershed (15.18 km2) that is located on the eastern side of Penteli Mountain, in the prefecture of Attica, Greece and the study period concerns the years from 2003 to 2008. The decrease in the annual rainfall depth during the last two hydrological years 2006-2007, 2007-2008 is 10% and 35%, respectively, in relation to the average of the previous years. In addition, the monthly distribution of rainfall is characterized by a distinct decrease in winter rainfall volume. The field measurements show that this change in rainfall conditions has a direct impact on the surface runoff of the watershed, as well as on the groundwater reserves. The mean annual runoff in the last two hydrological years has decreased by 56% and 75% in relation to the average of the previous years. Moreover, the groundwater level follows a declining trend and has dropped significantly in the last two years.

scholarly journals Artificial neural network, predictor variables and sensitivity threshold for DNA methylation-based age prediction using blood samples

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhonghui Thong ◽  
Jolena Ying Ying Tan ◽  
Eileen Shuzhen Loo ◽  
Yu Wei Phua ◽  
Xavier Liang Shun Chan ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Regression Model ◽  
Sensitivity Threshold ◽  
Ann Model ◽  
Blood Samples ◽  
Ann Models ◽  
Artificial Neural ◽  
The Impact ◽  
Age Prediction

AbstractRegression models are often used to predict age of an individual based on methylation patterns. Artificial neural network (ANN) however was recently shown to be more accurate for age prediction. Additionally, the impact of ethnicity and sex on our previous regression model have not been studied. Furthermore, there is currently no age prediction study investigating the lower limit of input DNA at the bisulfite treatment stage prior to pyrosequencing. Herein, we evaluated both regression and ANN models, and the impact of ethnicity and sex on age prediction for 333 local blood samples using three loci on the pyrosequencing platform. Subsequently, we trained a one locus-based ANN model to reduce the amount of DNA used. We demonstrated that the ANN model has a higher accuracy of age prediction than the regression model. Additionally, we showed that ethnicity did not affect age prediction among local Chinese, Malays and Indians. Although the predicted age of males were marginally overestimated, sex did not impact the accuracy of age prediction. Lastly, we present a one locus, dual CpG model using 25 ng of input DNA that is sufficient for forensic age prediction. In conclusion, the two ANN models validated would be useful for age prediction to provide forensic intelligence leads.

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