The potential for land erosion due to primary tin mining in Bangka Island

In the context of primary tin mining by PT. Timah on the Bangka Island, an analysis of environmental impacts is needed concerning various related aspects. One of the potential impacts that need to be considered is erosion due to open land for mining activities. Rain and mining water triggers the process of erosion on open land with particular soil and topographic characteristics. This paper presents an analysis of the potential for erosion due to primary tin mining at five mining locations in Bangka Island. The soil erosion rate can be analyzed using the Universal Soil Loss Equation (USLE) and GIS. The environmental data used to predict the erosion rate include soil type, soil texture and structure, land cover, rainfall, slope, and soil management techniques. In this study, rainfall erosivity is taking into account based on average monthly rainfall from 2010-2019. The results showed that the erosion rates at the primary mining sites are relatively low, ranging from 4.72 to 683.47 tons/ha/year. The results showed that the erosion rate is more influenced by the topography (slope factor). Besides, the considerable land-use change will also contribute significantly to the amount of soil erosion.

Assessment of the rainfall exceedance in Nigeria

This study assessed rainfall extremes for agricultural overview in Nigeria using trend analysis and probability of exceedance expressed as normal for an average at 50% exceedance, wet for greater than average 20% exceedance and dry for lower than average 80% exceedance. The annual rainfall trend indicated variability in the six geopolitical regions with North-East having the lowest range and South-South area with highest. The average monthly rainfall exceedance showed that all part of the Nigeria experienced rainfall more than 100 mm at all levels of probability. The rainfall exceedance time series indicated extremes as well as critical values of 20% and 80% exceedance conditions at many stations during the study period. The critical values of exceedances in dry occurrences are in short-time scales in Northern region while, wet exceedances occurrences for long time scales in South-East, South-West, North-Central and North-West. The study revealed periods of extreme rainfall of significant magnitude susceptible to crop failure in the different regions if reliable cropping management plans is not put in place.

Spatial-Temporal Trend Analysis of Rainfall Erosivity and Erosivity Density of Tropical Area in Air Bengkulu Watershed, Indonesia

There have been many studies on rainfall erosivity and erosivity density (ED). However, it was not widely developed in Indonesia as a tropical country and has unique precipitation patterns. They are indicators for assessing the potential risk of soil erosion. The Air Bengkulu Watershed is undergoing severe land degradation due to soil erosion. This study aimed to analyze spatial-temporal in rainfall erosivity and ED based on monthly rainfall data (mm). The data used consisted of 19 weather stations during the period 2006–2020 and which are sparsely distributed over the watershed. The analysis was done by using Arnold's equation. Then, the trend was tested using parametric and non-parametric statistics, and analysed with linear regression equation, and Spearman's Rho and Mann Kendall's tests. The spatial distribution of both algorithms was analysed using the inverse distance weighted (IDW) method based on the geographic information system (GIS). Unlike previous research findings, The long-term average monthly rainfall erosivity and ED revealed a general increase and decreasing trend, whereas it was found to be non-significant when both indices were observed. However, these results indicate a range from 840.94 MJ · mm−1 · ha−1 · h−1 · a−1, 552.42 MJ · mm−1 · ha−1 · h−1 · a−1 to 472.09 MJ · mm−1 · ha−1 · h−1 · a−1 in that November month followed by December and April are the most susceptible months for soil erosion. Therefore, The upstream area of the region shows that various anthropogenic activities must be managed properly by taking into account the rainfall erosivity on the environment and that more stringent measures should be followed in soil and water conservation activities.

Variability and Trend Analysis of the Rainfall of the Past 119 (1901-2019) Years using Statistical Techniques: A Case Study of Uttar Dinajpur, India

The present study aims to identify and measure the impact of climate change on rainfall patterns in the Uttar Dinajpur district of West Bengal. The hydro-meteorological time series rainfall data was collected from the IMD and CHRS data portals and subsequently analysed using various statistical methods. Agriculture in this district is the main economic activity, but the rainfall propensity is very unpredictable and sporadic that has a significant impact on agriculture. The rainfall results (1901-2019) were examined and assessed using statistical techniques for Mann-Kendall’s Z-statistic and Sen’s slope estimators. From the estimation, it is understood that the pre-monsoon, monsoon, and winter seasons have positive trends in rainfall, whereas the post-monsoon rainfall shows a negative trend and both Mann-Kendall and Sen’s slope projections depict the same. Likewise, January, February, April, May, June, July, August, and December reflect upward positive change, while a downward trend (decline trend) was recorded in March, September, and October. The winter Kharif crops are more impacted by this negative or decreasing pattern of seasonal rainfall than other crops. The maximum average monthly rainfall in July (892.1 mm) and January showed the lowest average monthly rainfall of 63.3 mm. The results revealed that during the monsoon season the maximum rainfall (75.2%) occurred and the coefficient of variance value is 20.4%. In the winter season, the minimal rainfall (2.87%) with a coefficient of variance (CV) is 72.9%. The rainfall forecast using SMOreg and linear regression methods has been calculated. This research contributes greatly to adopting different strategies by the planners, researchers, numerous government institutions, and NGOs for the overall development of the study area. This study may also be effective in the management of water resources in the study region.

The Influence of Climate Factors on Cocoa Productivity in Sulawesi, 2019

Cocoa is one of the plantation commodities that has an important role in Indonesia's economic activity and is one of Indonesia's export commodities which is quite important as a source of foreign exchange and oil and gas. Sulawesi Island is one of the cocoa-producing islands in Indonesia. This study aims to determine a spatial regression model between the average cocoa productivity per month with the average drinking temperature per month, the average monthly rainfall and the average length of sunshine per month and the climatic factors that affect cocoa productivity in Sulawesi. The best model estimation uses the AIC value; the best model has the smallest AIC value. In this study, the SARMA spatial regression model is the best model with the specified criteria.

Analysis and Prediction of Meteorological Drought Area by Using Standardized Precipitation Index in Northeast, Thailand

The objectives of this work are: 1) to monitor the trend of rainfall data in in-season rice field period of Thailand (April to August). 2) to analyze meteorological drought by Standardized Precipitation Index : SPI in Northeast Thailand in in-season rice field period of Thailand and 3) to predict the rainfall data in in-season rice field period of Thailand of 2021. The average monthly rainfall data in April to August of 1990 – 2020 were gathered from 31 meteorological stations covered Northeast area of Thailand by Meteorological Department of Thailand. The data were used to draw trend of monthly average rainfall to track a change of rainfall in the period. Then, these were used to create distribution of meteorological drought characteristics maps under SPI criteria. Moreover, Single Moving Average model is used to predict the rainfall data with the lowest MAPE at 11.13 percentage. The results show that the higher meteorological drought risk area was always found in south-west side of the region in June to August. Moreover, average monthly rainfall increases from April and hit the peak in July and August. The trend of total monthly rainfall in in-season rice field period fluctuates along the study period with average value at 977.98 millimeters and its trend tends to be decreased at 0.1052 millimeters per year.

Relationship between climate variability and radial growth of Pinus montezumae Lamb. in Coyuca de Catalán, Guerrero

Introduction: Understanding the dendroclimatic potential of a species allows us to reconstruct the climate variability in the latitudes and altitudes of its distribution. Objective: To determine the potential of Pinus montezumae Lamb. to reconstruct climatic variables. Materials and methods: A total of 80 samples were extracted with a Pressler increment borer and dated, allowing growth rates to be generated. Average monthly rainfall and minimum and maximum temperature were obtained, and a response function analysis between growth rates and climate data was conducted. Results and discussion: Dated samples represented 75 % of the total. The COFECHA program indicated a correlation between series of r = 0.57 (P < 0.01) and a mean sensitivity of 0.31; P. montezumae is sufficiently sensitive to record climate variability. Three chronologies (standard, residual and arstan) covering 228 years (1790-2017) were generated for each of the three growth rates (total ring, early and latewood). The response function analysis showed that it is possible to reconstruct the spring rainfall and the May-July maximum temperature based on the total ring (r = 0.66; P < 0.01) and latewood (r = 0.35; P < 0.01) indices, respectively. Conclusion: Statistical parameters indicate that P. montezumae is an adequate proxy source for climate variability reconstruction studies.

PENENTUAN FAKTOR-FAKTOR POTENSIAL YANG MEMPENGARUHI KEJADIAN MALARIA DI PROVINSI PAPUA DENGAN EPIDEMIOLOGI SPASIAL

In Indonesia malaria is found to be widespread in all islands with varying degrees and severity of infection. Based on the Annual of Parasite Incidence (API) in Eastern Indonesia, Malaria is a disease that has a high incidence rate. The three provinces with the highest APIs are Papua (42.64%), West Papua (38.44%) and East Nusa Tenggara (16.37%). Spatial aspects are considered important to be studied because the spread of disease through mosquitoes is strongly influenced by fluctuating climate. The purpose of this study is to determine the potential factors that influence the incidence of Malaria disease in the province of Papua in 2013 by looking at aspects that are the focus of attention in spatial epidemiology. The methods used in analyzing the area are Simultaneous Autoregressive (SAR) and Conditional Autoregressive (CAR) models with a spatial weighting matrix up to second order. The result shows the average monthly wind velocity, average monthly rainfall, and malaria treatment with government program drugs by getting ACT drugs are substantial factors in determining the incidence number of Malaria in Papua based on the lowest AIC value for the second-order of CAR model. While the SAR model, in this case, has no spatial influence. By knowing the potential factors that influence the incidence of malaria, the Papua Province through the Health Office can take more effective preventive measures to reduce the number of malaria incidents.

A study of trend of incidence of dengue cases attending a tertiary care hospital in urban Maharashtra

Background: Presently, dengue is one of the most important mosquito-borne viral diseases in the world. The burden of the disease has drastically risen over the years with over 70% contributed by the Asia region. India is endemic to the disease and all four serotypes of the virus have been isolated from the country. This study aimed to describe the trends of incidence of dengue cases at a tertiary care hospital in urban Maharashtra.Methods: Retrospective data analysis with respect to admitted dengue cases in the preceding five years was carried out from the records available at the hospital. Year-wise trend as well as correlation with average monthly rainfall were also analysed.Results: The number of admitted cases of dengue showed a rising trend which was statistically significant. The study brought forth a change in the seasonality of occurrence of cases. The number of cases also showed a positive and statistically significant correlation with the monthly average rainfall in the Madhya Maharashtra region.Conclusions: There is evidence for an increase in the burden of dengue. With the overall number, there is also change in seasonality of the disease, indicating a requirement of control measures to be instituted earlier than the usual pre-monsoon period. The rising burden will pose a public health challenge and requires tailormade remedial activities taking into consideration various factors associated.