scholarly journals Drought and households’ adaptive capacity to water scarcity in Kasali, Uganda

2020 ◽  
Vol 11 (S1) ◽  
pp. 217-232 ◽  
Author(s):  
Joseph Mukasa ◽  
Lydia Olaka ◽  
Mohammed Yahya Said
Keyword(s):  
Adaptive Capacity ◽  
Water Availability ◽  
Water Scarcity ◽  
Drought Index ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Seasonal Temperature ◽  
Average Maximum ◽  
June July ◽  
The Impact

Abstract The world is experiencing variability in precipitation, increased temperature, drought frequencies and intensities. Globally, approximately four billion individuals experience water scarcity due to drought. In Uganda about 10% of the population in the southern and northern parts of the country experience drought related water scarcity annually. This study aimed at assessing drought and households’ adaptive capacity (AC) to water scarcity during drought in Kasali. This was done through determining drought trends from 1987 to 2017, assessing the impact of drought on water availability and the AC of households to manage water scarcity. Droughts were assessed based on the Reconnaissance Drought Index (RDI). The results show a decrease in the average annual rainfall, and the seasons of March-April-May (MAM), January-February (JF) while the seasons of September-October-November-December (SOND) and June-July-August (JJA) show an increase in rainfall trend. The average maximum and minimum annual and seasonal temperature increased significantly by between 0.56 and 1.51 °C. The minimum temperature increased more than the maximum temperature. Kasali experienced one extreme dry year and four moderate ones between 1987 and 2017. Above 70% of the households spend longer hours collecting water during dry years than wet years. The AC of households to water scarcity was low and drought negatively impacted water availability.

scholarly journals Analyses of temperature and precipitation in the Indian Jammu and Kashmir region for the 1980–2016 period: implications for remote influence and extreme events

2019 ◽  
Vol 19 (1) ◽  
pp. 15-37 ◽  
Author(s):  
Sumira Nazir Zaz ◽  
Shakil Ahmad Romshoo ◽  
Ramkumar Thokuluwa Krishnamoorthy ◽  
Yesubabu Viswanadhapalli
Keyword(s):  
Climate Change ◽  
Statistical Tests ◽  
Wrf Model ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Seasonal Temperature ◽  
Western Himalayas ◽  
Jammu And Kashmir ◽  
Temperature And Precipitation ◽  
Average Annual Temperature

Abstract. The local weather and climate of the Himalayas are sensitive and interlinked with global-scale changes in climate, as the hydrology of this region is mainly governed by snow and glaciers. There are clear and strong indicators of climate change reported for the Himalayas, particularly the Jammu and Kashmir region situated in the western Himalayas. In this study, using observational data, detailed characteristics of long- and short-term as well as localized variations in temperature and precipitation are analyzed for these six meteorological stations, namely, Gulmarg, Pahalgam, Kokarnag, Qazigund, Kupwara and Srinagar during 1980–2016. All of these stations are located in Jammu and Kashmir, India. In addition to analysis of stations observations, we also utilized the dynamical downscaled simulations of WRF model and ERA-Interim (ERA-I) data for the study period. The annual and seasonal temperature and precipitation changes were analyzed by carrying out Mann–Kendall, linear regression, cumulative deviation and Student's t statistical tests. The results show an increase of 0.8 ∘C in average annual temperature over 37 years (from 1980 to 2016) with higher increase in maximum temperature (0.97 ∘C) compared to minimum temperature (0.76 ∘C). Analyses of annual mean temperature at all the stations reveal that the high-altitude stations of Pahalgam (1.13 ∘C) and Gulmarg (1.04 ∘C) exhibit a steep increase and statistically significant trends. The overall precipitation and temperature patterns in the valley show significant decreases and increases in the annual rainfall and temperature respectively. Seasonal analyses show significant increasing trends in the winter and spring temperatures at all stations, with prominent decreases in spring precipitation. In the present study, the observed long-term trends in temperature (∘Cyear-1) and precipitation (mm year−1) along with their respective standard errors during 1980–2016 are as follows: (i) 0.05 (0.01) and −16.7 (6.3) for Gulmarg, (ii) 0.04 (0.01) and −6.6 (2.9) for Srinagar, (iii) 0.04 (0.01) and −0.69 (4.79) for Kokarnag, (iv) 0.04 (0.01) and −0.13 (3.95) for Pahalgam, (v) 0.034 (0.01) and −5.5 (3.6) for Kupwara, and (vi) 0.01 (0.01) and −7.96 (4.5) for Qazigund. The present study also reveals that variation in temperature and precipitation during winter (December–March) has a close association with the North Atlantic Oscillation (NAO). Further, the observed temperature data (monthly averaged data for 1980–2016) at all the stations show a good correlation of 0.86 with the results of WRF and therefore the model downscaled simulations are considered a valid scientific tool for the studies of climate change in this region. Though the correlation between WRF model and observed precipitation is significantly strong, the WRF model significantly underestimates the rainfall amount, which necessitates the need for the sensitivity study of the model using the various microphysical parameterization schemes. The potential vorticities in the upper troposphere are obtained from ERA-I over the Jammu and Kashmir region and indicate that the extreme weather event of September 2014 occurred due to breaking of intense atmospheric Rossby wave activity over Kashmir. As the wave could transport a large amount of water vapor from both the Bay of Bengal and Arabian Sea and dump them over the Kashmir region through wave breaking, it probably resulted in the historical devastating flooding of the whole Kashmir valley in the first week of September 2014. This was accompanied by extreme rainfall events measuring more than 620 mm in some parts of the Pir Panjal range in the south Kashmir.

scholarly journals Sensitivity of wheat yields to rise in growing season temperature: Evidences from panel data analysis

2021 ◽  
Vol 22 (2) ◽  
pp. 191-197
Author(s):  
K. PHILIP ◽  
S.S. ASHA DEVI ◽  
G.K. JHA ◽  
B.M.K. RAJU ◽  
B. SEN ◽  
...  
Keyword(s):  
Climate Change ◽  
Panel Data ◽  
Growing Season ◽  
Maximum Temperature ◽  
Data Set ◽  
Impact Of Climate Change ◽  
Average Maximum ◽  
Wide Range ◽  
Potential Impact ◽  
The Impact

The impact of climate change on agriculture is well studied yet there is scope for improvement as crop specific and location specific impacts need to be assessed realistically to frame adaptation and mitigation strategies to lessen the adverse effects of climate change. Many researchers have tried to estimate potential impact of climate change on wheat yields using indirect crop simulation modeling techniques. Here, this study estimated the potential impact of climate change on wheat yields using a crop specific panel data set from 1981 to 2010,for six major wheat producing states. The study revealed that 1°C increase in average maximum temperature during the growing season reduces wheat yield by 3 percent. Major share of wheat growth and yield (79%) is attributed to increase in usage of physical inputs specifically fertilizers, machine labour and human labour. The estimated impact was lesser than previously reported studies due to the inclusion of wide range of short-term adaptation strategies to climate change. The results reiterate the necessity of including confluent factors like physical inputs while investigating the impact of climate factors on crop yields.

scholarly journals Future Impact of Climate Change on the Yield of Cocoa in Ondo State, Nigeria

2019 ◽  
pp. 467-476
Author(s):  
Femi S. Omotayo ◽  
Philip G. Oguntunde ◽  
Ayorinde A. Olufayo
Keyword(s):  
Climate Change ◽  
Climatic Variables ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Impact Of Climate Change ◽  
Projected Change ◽  
The Future ◽  
Ondo State ◽  
The Impact ◽  
Cocoa Yield

This study was carried to determine the trend of cocoa yield and climatic variables and assessment of the impact of climate change on the future yield of cocoa in Ondo State, Nigeria. Annual trend statistics for cocoa yield and climatic variables were analyzed for the state using Mann-Kendall test for trend and Sen’s slope estimates. Downscaled data from six Global Circulation Models (GCMs) were used to examine the impact of climate change on the future yield of cocoa in the study area. The results of trends analysis in Ondo State showed that yield decreased monotonically at the rate of 492.18 tonnes/yr (P<0.05). An increased significant trend was established in annual rainfall trend. While Maximum temperature, minimum temperature, and mean temperature all increased at the rate of 0.02/yr (P<0.001). The ensemble of all the GCMs projected a mid-term future decrease of about 9,334 tonnes/yr by 2050 and a long-term future decrease of 13,504 tonnes/yr of cocoa by 2100. The economic implication of these is that, if the projected change in the yield of cocoa as predicted by the ensemble of all the GCMs should hold for the future, it means that Ondo state may experience a loss of about $22,470,018.22 and $32,308,584.32 by the year 2050 and 2100 respectively according to the present price of the commodity in the world market. Measures are to be taken by the government and farmers to find a way of mitigating the impacts of climate change on the future yield of the cocoa study area. This research should be extended to other cocoa producing areas in Nigeria.

scholarly journals Trends in climatic variables and future reference evapotranspiration in Duero Valley (Spain)

2011 ◽  
Vol 11 (6) ◽  
pp. 1795-1805 ◽  
Author(s):  
R. Moratiel ◽  
R. L. Snyder ◽  
J. M. Durán ◽  
A. M. Tarquis
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Reference Evapotranspiration ◽  
Stomatal Resistance ◽  
Dew Point ◽  
Maximum Temperature ◽  
Net Radiation ◽  
Maximum Water ◽  
June July ◽  
The Impact

Abstract. The impact of climate change and its relation with evapotranspiration was evaluated in the Duero River Basin (Spain). The study shows possible future situations 50 yr from now from the reference evapotranspiration (ETo). The maximum temperature (Tmax), minimum temperature (Tmin), dew point (Td), wind speed (U) and net radiation (Rn) trends during the 1980–2009 period were obtained and extrapolated with the FAO-56 Penman-Montheith equation to estimate ETo. Changes in stomatal resistance in response to increases in CO2 were also considered. Four scenarios were done, taking the concentration of CO2 and the period analyzed (annual or monthly) into consideration. The scenarios studied showed the changes in ETo as a consequence of the annual and monthly trends in the variables Tmax, Tmin, Td, U and Rn with current and future CO2 concentrations (372 ppm and 550 ppm). The future ETo showed increases between 118 mm (11 %) and 55 mm (5 %) with respect to the current situation of the river basin at 1042 mm. The months most affected by climate change are May, June, July, August and September, which also coincide with the maximum water needs of the basin's crops.

Sustainability assessment of crops' production in India: empirical evidence from ARDL-ECM approach

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rita Rani Chopra
Keyword(s):  
Land Use ◽  
Error Correction ◽  
Sustainability Assessment ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Content Type ◽  
Irrigated Area ◽  
Long Run ◽  
Short Run ◽  
The Impact

PurposeThe study aims to evaluate the long- vs short-run relationships between crops' production (output) and crops' significant inputs such as land use, agricultural water use (AWU) and gross irrigated area in India during the period 1981–2018.Design/methodology/approachThe study applied the autoregressive distributed lag (ARDL) bounds testing approach to estimate the co-integration among the variables. The study uses the error correction model (ECM), which integrates the short-run dynamics with the long-run equilibrium.FindingsThe ARDL bounds test of co-integration confirms the strong evidence of the long-run relationship among the variables. Empirical results show the positive and significant relationship of crops' production with land use and gross irrigated area. The statistically significant error correction term (ECT) validates the speed of adjustment of the empirical models in the long-run.Research limitations/implicationsThe study suggests that the decision-makers must understand potential trade-offs between human needs and environmental impacts to ensure food for the growing population in India.Originality/valueFor a clear insight into the impact of climate change on crops' production, the current study incorporates the climate variables such as annual rainfall, maximum temperature and minimum temperature. Further, the study considered agro-chemicals, i.e. fertilizers and pesticides, concerning their negative impacts on increased agricultural production and the environment.

Implications of less tail end water on livelihoods of small farmers in Pakistan

2017 ◽  
Vol 46 (1) ◽  
pp. 36-43 ◽  
Author(s):  
Akhter Ali ◽  
Dil Bahadur Rahut ◽  
Muhammad Imtiaz
Keyword(s):  
Water Availability ◽  
Water Scarcity ◽  
Household Income ◽  
Water Source ◽  
Land Rent ◽  
Absolute Deviation ◽  
Canal Irrigation ◽  
Using Data ◽  
The Impact ◽  
Poverty Levels

In Pakistan, about 80% of the cropped area is irrigated using canal irrigation, and water availability is closely linked to the location of the farm. Using data collected from 950 farmers through a field survey covering four provinces (Punjab, Sindh, Khyber Pakhtunkhwa and Balochistan), this study aimed to assess the impact of location, that is, ‘head’ versus ‘tail’ on water availability and its impact on crop yield, household income, food security and poverty levels. The censored least absolute deviation was used to estimate farmer participation in water markets, and the propensity score matching was used to assess impacts on yield of wheat and rice, household income and poverty levels as well as land rent and water scarcity. The results show that farmers situated at the head of the water source have higher wheat and rice yields in the range of 2–3 maunds per acre. Household income levels are higher in the range of PKR 8455–14,673, and poverty levels are lower (+3% to 5%). The land rent at the head is higher compared to the tail while water scarcity is also less at the head. The study indicated that farmers’ status plays a major role in land location and access to irrigation water.

scholarly journals Low soil moisture predisposes field-grown chickpea plants to dry root rot disease: evidence from simulation modeling and correlation analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ranjita Sinha ◽  
Vadivelmurugan Irulappan ◽  
Basavanagouda S. Patil ◽  
Puli Chandra Obul Reddy ◽  
Venkategowda Ramegowda ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Root Rot ◽  
Disease Incidence ◽  
Maximum Temperature ◽  
Validation Dataset ◽  
Water Deficit Stress ◽  
Weather Factors ◽  
Rhizoctonia Bataticola ◽  
Average Maximum ◽  
The Impact

AbstractRhizoctonia bataticola causes dry root rot (DRR), a devastating disease in chickpea (Cicer arietinum). DRR incidence increases under water deficit stress and high temperature. However, the roles of other edaphic and environmental factors remain unclear. Here, we performed an artificial neural network (ANN)-based prediction of DRR incidence considering DRR incidence data from previous reports and weather factors. ANN-based prediction using the backpropagation algorithm showed that the combination of total rainfall from November to January of the chickpea-growing season and average maximum temperature of the months October and November is crucial in determining DRR occurrence in chickpea fields. The prediction accuracy of DRR incidence was 84.6% with the validation dataset. Field trials at seven different locations in India with combination of low soil moisture and pathogen stress treatments confirmed the impact of low soil moisture on DRR incidence under different agroclimatic zones and helped in determining the correlation of soil factors with DRR incidence. Soil phosphorus, potassium, organic carbon, and clay content were positively correlated with DRR incidence, while soil silt content was negatively correlated. Our results establish the role of edaphic and other weather factors in chickpea DRR disease incidence. Our ANN-based model will allow the location-specific prediction of DRR incidence, enabling efficient decision-making in chickpea cultivation to minimize yield loss.

scholarly journals Impact of seasonal climatic variability on rice yield in Bangladesh

2021 ◽  
Vol 22 (2) ◽  
pp. 165-171
Author(s):  
JAIONTO KARMOKAR ◽  
M. AMINUL ISLAM ◽  
M. RAKIB HASSAN ◽  
M.M. BILLAH
Keyword(s):  
Rice Yield ◽  
Climatic Variability ◽  
Vital Role ◽  
Least Square ◽  
Maximum Temperature ◽  
Negative Effects ◽  
Positive Effects ◽  
Average Maximum ◽  
The Impact ◽  
Boro Rice

In Bangladesh, 75% of the total cultivable area is under rice cultivation producing 25 million tons of rice and plays a vital role in the country’s GDP. The climatic variability is playing an important role in affecting the rice production. In this study, the impact of climatic variability (average maximum temperature (aMaxTemp), average minimum temperature (aMinTemp) and average rainfall (aRainfall)) on rice yield was determined in two different regions (northern and southern) of Bangladesh.The variability of rice yield and climate factors was determined by using the Ordinary Least Square (OLS) method. The data was analyzed over the 44-years period (1971 to 2014) in order to estimate the magnitude of these fluctuations statistically and graphically. We observed that the climate variables had significant effect on rice yield that varies among three rice crops (e.g., Aus, Aman, and Boro rice). We observed that, aMaxTemp has positive effects for Aus and Aman rice yield but negative effect on Boro rice yield. On the other hand, aMinTemp has negative effects on Aus and Aman rice yield but has positive effect on Boro rice yield. The aRainfall has a positive relationship with all rice yields in both the regions.

scholarly journals Climate Variability and Change Affect Crops Yield under Rainfed Conditions: A Case Study in Gedaref State, Sudan

Agronomy ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1680
Author(s):  
Maysoon A. A. Osman ◽  
Joshua Orungo Onono ◽  
Lydia A. Olaka ◽  
Muna M. Elhag ◽  
Elfatih M. Abdel-Rahman
Keyword(s):  
Linear Regression ◽  
Climate Variability ◽  
Crop Yield ◽  
Rainy Season ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Simple Linear Regression ◽  
Climate Variability And Change ◽  
Crops Yield ◽  
The Impact

It is projected that, on average, annual temperature will increase between 2 °C to 6 °C under high emission scenarios by the end of the 21st century, with serious consequences in food and nutrition security, especially within semi-arid regions of sub-Saharan Africa. This study aimed to investigate the impact of historical long-term climate (temperature and rainfall) variables on the yield of five major crops viz., sorghum, sesame, cotton, sunflower, and millet in Gedaref state, Sudan over the last 35 years. Mann–Kendall trend analysis was used to determine the existing positive or negative trends in temperature and rainfall, while simple linear regression was used to assess trends in crop yield over time. The first difference approach was used to remove the effect of non-climatic factors on crop yield. On the other hand, the standardized anomaly index was calculated to assess the variability in both rainfall and temperature over the study period (i.e., 35 years). Correlation and multiple linear regression (MLR) analyses were employed to determine the relationships between climatic variables and crops yield. Similarly, a simple linear regression was used to determine the relationship between the length of the rainy season and crop yield. The results showed that the annual maximum temperature (Tmax) increased by 0.03 °C per year between the years 1984 and 2018, while the minimum temperature (Tmin) increased by 0.05 °C per year, leading to a narrow range in diurnal temperature (DTR). In contrast, annual rainfall fluctuated with no evidence of a significant (p > 0.05) increasing or decreasing trend. The yields for all selected crops were negatively correlated with Tmin, Tmax (r ranged between −0.09 and −0.76), and DTR (r ranged between −0.10 and −0.70). However, the annual rainfall had a strong positive correlation with yield of sorghum (r = 0.64), sesame (r = 0.58), and sunflower (r = 0.75). Furthermore, the results showed that a longer rainy season had significant (p < 0.05) direct relationships with the yield of most crops, while Tmax, Tmin, DTR, and amount of rainfall explained more than 50% of the variability in the yield of sorghum (R2 = 0.70), sunflower (R2 = 0.61), and millet (R2 = 0.54). Our results call for increased awareness among different stakeholders and policymakers on the impact of climate change on crop yield, and the need to upscale adaptation measures to mitigate the negative impacts of climate variability and change.

scholarly journals Farmers’ perspectives

2018 ◽  
Vol 10 (4) ◽  
pp. 551-579 ◽  
Author(s):  
Winifred Chepkoech ◽  
Nancy W. Mungai ◽  
Silke Stöber ◽  
Hillary K. Bett ◽  
Hermann Lotze-Campen
Keyword(s):  
Climate Change ◽  
Annual Rainfall ◽  
Series Data ◽  
Maximum Temperature ◽  
Historical Trends ◽  
Chi Square ◽  
Content Type ◽  
Humid Zone ◽  
Mean Annual Rainfall ◽  
The Impact

Purpose Understanding farmers’ perceptions of how the climate is changing is vital to anticipating its impacts. Farmers are known to take appropriate steps to adapt only when they perceive change to be taking place. This study aims to analyse how African indigenous vegetable (AIV) farmers perceive climate change in three different agro-climatic zones (ACZs) in Kenya, identify the main differences in historical seasonal and annual rainfall and temperature trends between the zones, discuss differences in farmers’ perceptions and historical trends and analyse the impact of these perceived changes and trends on yields, weeds, pests and disease infestation of AIVs. Design/methodology/approach Data collection was undertaken in focus group discussions (FGD) (N = 211) and during interviews with individual farmers (N = 269). The Mann–Kendall test and regression were applied for trend analysis of time series data (1980-2014). Analysis of variance and least significant difference were used to test for differences in mean rainfall data, while a chi-square test examined the association between farmer perceptions and ACZs. Coefficient of variation expressed as a percentage was used to show variability in mean annual and seasonal rainfall between the zones. Findings Farmers perceived that higher temperatures, decreased rainfall, late onset and early retreat of rain, erratic rainfall patterns and frequent dry spells were increasing the incidences of droughts and floods. The chi-square results showed a significant relationship between some of these perceptions and ACZs. Meteorological data provided some evidence to support farmers’ perceptions of changing rainfall. No trend was detected in mean annual rainfall, but a significant increase was recorded in the semi-humid zone. A decreasing maximum temperature was noted in the semi-humid zone, but otherwise, an overall increase was detected. There were highly significant differences in mean annual rainfall between the zones. Farmers perceived reduced yields and changes in pest infestation and diseases in some AIVs to be prevalent in the dry season. This study’s findings provide a basis for local and timely institutional changes, which could certainly help in reducing the adverse effects of climate change. Originality/value This is an original research paper and the historical trends, farmers’ perceptions and effects of climate change on AIV production documented in this paper may also be representative of other ACZs in Kenya.

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