Rainfall Type Research Articles

Development of quantitative precipitation estimation (QPE) relations for dual-polarization radars based on raindrop size distribution measurements in Metro Manila, Philippines

Quantitative precipitation estimates (QPE) can be further improved using estimation algorithms derived from localized raindrop size distribution (DSD) observations. In this study, DSD measurements from two disdrometer stations within Metro Manila during the Southwest monsoon (SWM) period were used to investigate the microphysical properties of rainfall and develop localized dual-polarimetric relations for different radar bands and rainfall types. Observations show that the DSD in Metro Manila is more distributed to larger diameters compared to Southern Luzon and neighboring countries and regions in the Western Pacific. This is reflected by the relatively higher mass-weighted mean diameter (Dm) and smaller shape (μ) and slope (Λ) parameters measured in the region. The average values of Dm and normalized intercept parameter (Nw) in convective rain samples also suggest that convective rains in Metro Manila are highly influenced by both continental and oceanic convective processes. Dual-polarimetric variables simulated using the T-matrix scattering method showed good agreement with disdrometer-derived reflectivity (ZH) values. The 0.5 dB and 0.3° km−1 thresholds for the differential reflectivity (ZDR) and specific differential phase (KDP) based on the blended algorithm of Cifelli (J Atmos Ocean Technol 28:352-364, 2011) and Thompson et al. (2017) are proven to be useful since the utility of the dual-polarimetric variables as rainfall estimators are shown to have dependencies on the radar band and rainfall type. Evaluation of the QPE products with respect to the C-band shows that R (KDP, ZDR) has the best performance among the dual-pol relations and statistically outperformed the conventional Marshall & Palmer relation [R(ZMP)]. The results show that dual-polarimetric variables such as ZDR and KDP can better represent the DSD properties compared to one-dimensional Z, hence providing more accurate QPE products than the conventional R(Z) relations.

Analysis of Flood Inundation Mapping Using the Weighting Method in Urban Floods

Floods are one of the most destructive natural disasters globally and are projected to increase in many regions of the world. One of the areas affected by the floods is Barito Kuala Regency in South Kalimantan. Flood hazard maps and flood inundation maps are one way to identify areas prone to flooding and to find out the area of inundated areas due to flooding. Methods of scoring and weighting the parameters that cause flood inundation to map an area that has the potential for flooding. Flood inundation maps can be generated using the Normalized Difference Water Index (NDWI) method. The purpose of these two analyzes is to determine the distribution of flood hazard levels in Barito Kuala District, to evaluate flood-prone areas with flood-prone maps, and to determine the effectiveness of the two methods in identifying flood-prone areas and to determine the accuracy of the resulting flood inundation maps. Flood-prone areas were identified using the scoring method and parameter weighting to determine the distribution of flood vulnerability levels in Barito Kuala District. Parameters of flood vulnerability level used include land cover, slope, rainfall, drainage density, and soil type. Flood vulnerability level parameters were obtained from NDWI analysis on ArcGIS and ENVI. Image data during the dry season and rainy season are thresholded at <0.3 to eliminate data that is considered non-water resulting in flood inundation. The results of processing the level of flood hazard in Barito Kuala Regency are divided into 4 classes, namely the safe class with 0.5%, the less prone class is 10.11%, the moderate class is 89.37 and the vulnerable class is 0.00% of the area of Barito Kuala Regency with the majority of the areas in the moderate class. Savings District. The results of the analysis of the flood inundation map and the flood hazard map show that the moderate class of flood inundation is 72.06% of the total area of flood inundation

ANALISIS KARAKTERISTIK SPASIAL DAN TEMPORAL HOTSPOT DI TAMAN NASIONAL SEBANGAU PROVINSI KALIMANTAN TENGAH

Sebangau National Park, in Central Kalimantan Province, is a wetland conservation area. In 2015, forest and land fires resulted in 455 hectares being burned. The identification of hotspots in this study is based on the number and distribution of hotspots based on satellite imagery data from the Moderate Resolution Imaging Spectroradiometer (MODIS) in 2001–2020. This study identifies hotspots by looking at the influence of rainfall and ENSO (El Nino Southern Oscillation) conditions. The method used is the method of spatial and temporal analysis. The aim of this study was to determine the characteristics of the hotspot distribution pattern in Sebangau National Park, Central Kalimantan Province, both spatially and temporally. There is a similarity between the temporal and spatial characteristics of hotspots in the number of significant additions to the number of hotspots in August, September, and October. The influence of monsoonal rainfall types and climates such as ENSO (El Nino Southern Oscillation) greatly influences the occurrence of hotspot events in Sebangau National Park, Central Kalimantan Province. The distribution pattern of hotspots in Sebangau National Park, Central Kalimantan Province, peaked in October, and the worst addition to the number of hotspots occurred in 2015, when these conditions occurred during the dry season and when the ENSO index (El Nino Southern Oscillation) showed +2.6, where these conditions included strong El Nino categories.

A Structured Graph Neural Network for Improving the Numerical Weather Prediction of Rainfall

AbstractThe current challenges of numerical weather prediction (NWP) of rainfall mainly stem from the complex and multiscale nature of rainfall. In recent years, as observation capability improved worldwide, there has been an increased feasibility to use data‐driven models to enhance forecasting performance with rainfall observation. Compared to traditional statistical and machine learning models, deep‐learning models show considerable promise in capturing the spatial‐temporal features of weather processes from multiple predictors, but the convolution‐based feature extractor is suboptimal due to the linear nature of convolution kernels. In this study, a multilevel forecasting model is proposed to forecast each rainfall level, in which each submodel adopts a graph neural network for feature extraction. Spatial and temporal propagation functions based on grid structure are designed to explicitly represent feature fusion and propagation of multiple predictors across multiple scales. On model training, a weight setting strategy that balances the impact of samples with different rainfall values on the total training loss is proposed, and a soft classification label is designed to convert observed rainfall into the probability of rainfall above each threshold. The proposed model was trained and validated on NWP data provided by European Center for Medium‐Range Weather Forecast, and results show significant improvement over the NWP in terms of threat score (TS) and Heidke Skill Score (HSS) scores. Analysis of the forecast results for two typical rainfall processes also illustrates that the proposed method can predict rainfall with more reasonable location and intensity.

Metal cation concentrations improve understanding of controls on soil organic carbon across a precipitation by vegetation gradient in the Patagonian Andes

Tephra-derived soils retain more organic carbon (C) than soils formed from any other parent material, but this C may be sensitive to changes in climate and land use. Here we evaluate the effects of precipitation, temperature, and afforestation on extractable metals and organic C storage in young tephra-derived soils in a temperate climate. We conducted our investigation across five sites in the Patagonian Andes that vary from 250 mm to 2200 mm mean annual precipitation, and 12 to 9.7 ℃ mean annual temperature from east to west. At each of the five sites are paired plots of natural vegetation, varying from grasses and shrubs at the dry sites to closed-canopy forest at the wet, and stands of Pinus ponderosa planted in monocultures 35 years prior to sampling. Previous research at these sites showed that aboveground net primary production and soil organic C increased with rainfall, but total soil organic C content was lower in pine plantations than natural vegetation. Here we assess whether variation in precipitation and vegetation type also affect soil mineral properties that promote soil C stabilization. Soils were collected to the depth of auger refusal and extracted with 0.5 M HCl for 24 h to target the combined exchangeable and adsorbed metals, including secondary short-range-ordered mineral phases and the plant available pools of Mg, Ca, and K. Pine afforestation lowered concentrations of HCl-extractable K (p < 0.1) and Ca (p < 0.01) within the top 0 – 30 cm. Other elements, while not affected by vegetation type, did respond to the rainfall gradient. Al, Si, P, and Mn all increased in the surface soils with increasing rainfall (p < 0.01), suggesting the development of short-range-order volcanic mineral phases that retain nutrients such as P and Mn. The addition of Al and Ca in the linear model to describe soil organic C explained more of the total variance than rainfall and vegetation type alone, indicating the importance of Al complexes and cation (Ca) bridging with secondary minerals to soil C retention. Importantly, the lower concentration of Ca in planted pine soils may signal a long-term decrease in the potential soil C stored in afforested soils due to a lower capacity for cation bridging. Our results show that the chemistry of these young tephra soils is dynamic, responding to both precipitation and afforestation in distinct ways with potential long-term impacts on nutrient cycling and C storage.

Tillage agriculture and afforestation threaten tropical savanna plant communities across a broad rainfall gradient in India

Abstract The consequences of land‐use change for savanna biodiversity remain undocumented in most regions of tropical Asia. One such region is western Maharashtra, India, where old‐growth savannas occupy a broad rainfall gradient and are increasingly rare due to agricultural conversion and afforestation. To understand the consequences of land‐use change, we sampled herbaceous plant communities of old‐growth savannas and three alternative land‐use types: tree plantations, tillage agriculture and agricultural fallows (n = 15 sites per type). Study sites spanned 457 to 1954 mm of mean annual precipitation—corresponding to the typical rainfall range of mesic savannas globally. Across the rainfall gradient, we found consistent declines in old‐growth savanna plant communities due to land‐use change. Local‐scale native species richness dropped from a mean of 12 species/m2 in old‐growth savannas to 8, 6 and 3 species/m2 in tree plantations, fallows and tillage agriculture, respectively. Cover of native plants declined from a mean of 49% in old‐growth savannas to 27% in both tree plantations and fallows, and 4% in tillage agriculture. Reduced native cover coincided with increased cover of invasive species in tree plantations (18%), fallows (18%) and tillage agriculture (3%). In analyses of community composition, tillage agriculture was most dissimilar to old‐growth savannas, while tree plantations and fallows showed intermediate dissimilarity. These compositional changes were driven partly by the loss of characteristic savanna species: 65 species recorded in old‐growth savannas were absent in other land uses. Indicator analysis revealed 21 old‐growth species, comprised mostly of native savanna specialists. Indicators of tree plantations (nine species) and fallows (13 species) were both invasive and native species, while the two indicators of tillage agriculture were invasive. As reflective of declines in savanna communities, mean native perennial graminoid cover of 27% in old‐growth savannas dropped to 9%, 7%, and 0.1% in tree plantations, fallows and tillage agriculture, respectively. Synthesis. Agricultural conversion and afforestation of old‐growth savannas in India destroys and degrades herbaceous plant communities that do not spontaneously recover on fallowed land. Efforts to conserve India's native biodiversity should encompass the country's widespread savanna biome and seek to limit conversion of irreplaceable old‐growth savannas.

The Effect of Doses of Cow Manure and NPK Fertilizer on the Growth and Yield of Purple Eggplant (Solanum Melongena L) Cultivars Mustang F1

The aim of this study was to determine the effect of doses of cow manure and NPK fertilizer on the growth and yield of purple eggplant plants (Solanum melongena L) Mustang cultivar F1, as well as to determine the relationship between the components of growth with components of purple eggplant plants (Solanum melongena L). The study was conducted in the village of Cigintung, Kuningan District, Kuningan Regency from September 07, 2019 to November 24, 2019. The location was at an altitude of 400 m above sea level (asl) with clay type, rainfall type C (Slightly wet). The method used was an experimental method with a factorial Randomized block Design (RBD), the treatment consisted of two factors that were repated three times. The first factor is cow manure consisting of three levels (K 1 = 10 tons/ha, K 2 = 15 tons/ha, K3 = 20 tons/ha). The second factor is NPK fertilizer consisting of three levels (N 1 = 100 kg/ha, N 2 = 200 kg/ha, N 3 = 300 kg/ha). The results showed that the different treatment dosages of doses of cow nanure and NPK fertilizer do not have a real effect on all ages observations on plant height, number of fruit plants, fruit length, fruit diameter, fruit weight per plant, fruit weight per plot.

In-field assessment of the variability in water and nutrient use efficiency among potato farmers in a semi-arid climate

Precise water management is imperative for sustainable crop production under irrigation in semi-arid regions with increasingly variable rainfall. Water use efficiencies achieved by farmers often differ widely, even within regions with homogenous agro-ecological conditions. To better understand the drivers of this variability and derive management recommendations, detailed measurements of water and associated nutrient dynamics were conducted on 20 potato farms in two regions of South Africa. Crop characteristics and typical growing conditions in South Africa make potato cultivation sensitive to water and nutrient losses. Water and nutrient inputs and losses through drainage and plant uptake were measured in potato and the follow-up crop, along with yield and weather variables. Seasonal mean irrigation and evapotranspiration were lower in winter crops (240 mm irrigation, 236 mm evapotranspiration) than in summer crops (598 mm irrigation, 608 mm evapotranspiration). Seasonal field water balances were often close to zero, indicating that estimations of evapotranspiration and drainage were representative for the greater field. Lysimeter observations however appeared more representative in sandy unstructured soils than in heavier structured soils. Rainfall during cropping reduced demand for irrigation and increased water use efficiency based on irrigation water, but caused substantial drainage. Leaching of N and K was considerable (on average 30 kg N, 55 kg K ha−1, much higher in some fields), while P leaching was negligible, with the exception of one field (51 kg P ha−1). Variation in water and nutrients use efficiencies was the result of management decisions and environmental factors, such as rainfall and soil type. Without substantial rainfall, application of irrigation scheduling tools can keep drainage and nutrient losses to a minimum, as was observed on almost half the fields, even on sandy soils with a low water holding capacity. Potato yields greatly varied among farmers (9.1–24.7 t dry matter tuber ha−1). Efficient farmers included those who used water sparsely and had minimal drainage, but also farmers who used inputs judiciously and obtained excellent productivity. The role of follow-up crops as users of surplus nutrients and water left behind by the potato crop was not always evident.

Rainfall characteristics of sediment connectivity activation from plot to watershed scales on the Loess Plateau

Sediment connectivity is a fundamental concept for understanding sediment dynamics within watersheds, serving as a crucial component in watershed management and soil and water conservation. However, quantifying sediment connectivity remains a challenging task due to its complexity and the difficulties associated with direct measurements of sediment flux at multiple temporal and spatial scales. Our research aims to address this challenge by monitoring functional sediment connectivity at various scales using two key indicators: sediment yield and sediment marks. Sediment yield is monitored at slope plots, slope-channel cascades, and watershed outlets, while sediment marks provide additional insight into functional sediment connectivity along the sediment transport path, particularly in slope-channel cascades and channels following rainfall events. To record sediment marks, we used wooden sticks wrapped with clean gauze as an alternative to assessing functional connectivity. Our results revealed that the activation of sediment connectivity was influenced by rainfall amount, intensity, and type, with the highest activation observed at the slope plot, followed by the outlet of the slope-channel cascade and the watershed outlet. Notably, strong sediment connectivity at slope plots, slope-channel cascades, and main channels exhibits a weak correlation with sediment connectivity at the watershed outlet. In upper contribution areas with lower vegetation coverage and higher human disturbance, rainfall amount and I60 values associated with sediment connectivity activation tend to be lower. Furthermore, our research indicates that medium-duration and moderate-intensity rainfall events have a more significant impact on sediment connectivity at slope plots, while rainfall types characterized by longer durations, lower intensity, and larger amounts have a more pronounced effect on sediment transport paths. This suggests that the identification of sediment connectivity switch nodes can be achieved by considering both rainfall characteristics and underlying surface features. Looking ahead, future research can leverage long-term observations and data-driven models to explore rainfall thresholds for sediment connectivity at various scales, ultimately improving sediment transport prediction within watersheds.

Comparisons of Rainfall Microphysical Characteristics between the Southeastern Tibetan Plateau and Low-Altitude Areas

Abstract The low air pressure and density over the Tibetan Plateau may have an impact on the microphysical features of rainfall. Using a two-dimensional video disdrometer (2DVD), a Micro Rain Radar (MRR), and a microwave radiometer (MWR), the features of the raindrop size distribution (DSD) on the southeastern Tibetan Plateau (SETP) are explored and compared with those in low-altitude regions. The falling speed of raindrops on the SETP is higher than that in low-altitude areas. Under different rainfall-rate categories, the number concentration and the maximum diameter of raindrops on the SETP are smaller than those in low-altitude regions. The convective rainfall on the SETP is more maritime-like because the South Asian summer monsoon brings water vapor from the ocean here. For stratiform and convective rainfall, the SETP has more small-sized raindrops than low-altitude locations. The mass-weighted mean diameters (Dm) on the SETP are the smallest among six sites. The generalized intercept parameter (Nw) of stratiform rainfall is balanced at a low rainfall rate, while that of convective rainfall is balanced at a high rainfall rate. Furthermore, for a given μ (the shape parameter of gamma distribution) value, the λ (the slope parameter of gamma distribution) value on the SETP is the highest of the six sites. Significance Statement For the occurrence and progression of rainfall, microphysical processes (for instance, collision, fragmentation, coalescence, and evaporation) that take place when rainfall particles descend are crucial. A key factor in the microphysical features of rainfall that varies with rainfall rates and types is the raindrop size distribution (DSD). The southeastern Tibetan Plateau (SETP)’s unique terrain ensures that there is enough moisture for rain to fall there, but little is known about the microphysical aspects of this type of precipitation. There has not been enough research done on how the high altitude affects the microphysical features of rainfall. The microphysical features of rainfall in this area must thus be studied.

Hillslope groundwater and river channel precipitation recharge to rivers in a continuous permafrost catchment of northeastern Tibetan Plateau

Climate-change driven degradation of permafrost and changes in precipitation have resulted in significant changes to hydrological processes in permafrost areas. Previous studies on hillslope-stream connectivity and associated runoff-recharge to rivers have mainly focused on the threshold conditions and processes. In contrast, there has been limited study on the capacity of the permafrost active layer to recharge rivers and the relationships between river channel precipitation and river runoff, needed to predict flood events. This study aimed to characterize river runoff generation processes in the Yakou Catchment, northeastern Tibetan Plateau. Continuous monitoring of meteorological variables (precipitation and air temperature) and hillslope hydrological elements (thaw depths, supra-permafrost groundwater, and the thickness of the saturated zone) was conducted between June–August 2021–2022. The results showed using the thickness of the saturated zone (TSZ) to determine wet and dry conditions yielded significantly higher low flow (average of 0.153 m3 s−1) and lower low flow (average of 0.049 m3 s−1) with average TSZ depths of 0.40 m and 0.12 m under wet and dry conditions, respectively. However, no significant difference was noted in quick flow. Precipitation during typical rainfall events determined the generation of quick flow, with low flow constituting the main component of river runoff. The application of a partial least squares path model showed that TSZ on the permafrost determined the generation of river low flow which mainly originated from hillslope lateral subsurface flow. Conversely, river channel precipitation determined the generation of quick flow, which can contribute up to 80 % of the peak runoff during extreme rainfall events. Specifically, this study enhances the understanding of the connectivity between hillslopes and rivers and the storage-discharge relationship in permafrost catchments. This study provides a new theoretical reference for simulations of hydrological processes in the permafrost region.

Effect of chronic and humped input of polystyrene microplastics on rice growth

The impact of microplastics (MPs) pollution on farmland is influenced by the type of rainfall and the hydrography of the site. However, it is not clear how the arrival of MPs to farmland through different input modes will affect plant growth. Here, we simulated the effects of polystyrene (PS) MPs chronic input (50 mg/L), humped input (0, 0, 0, 100, 250, 100, 0, 0, 0 mg/L) and without PS MPs input (control) on rice growth through hydroponic experiment. The results showed that the input mode of MPs had a significant effect on the growth of rice. Compared with the control, the chronic input reduced the fresh weight of rice roots, stems and leaves by 61 %, 60 % and 64 %, respectively. Humped input only had a significant effect on the fresh weight of rice roots and stems, which were reduced by 24 % and 17 %, respectively. Both PS MPs input modes significantly reduced the chlorophyll content of plants. However, the chronic input of PS MPs also stimulated the antioxidant system of rice, improved peroxidase (POD) activity, and changed the nutrient content in plant tissues. Overall, chronic input of PS MPs had a greater impact on rice growth. Therefore, it is crucial to consider the input modes of MPs when assessing their effects on plant growth. This study is the first to investigate the effects of different input modes of MPs on plant growth, providing new insights into the pathways through which MPs affect plants.

Isotopic signals of different rainfall types revealed by intra-event rainfall analysis

Isotopic signals of different rainfall types revealed by intra-event rainfall analysis

Seasonal variation of microphysical characteristics for different rainfall types in the Tianshan Mountains of China

Three-year (2020−2022) raindrop size distribution (DSD) measurements from a second-generation PARSIVEL disdrometer deployed at Zhaosu, which is located in the Tianshan Mountains of China, are analyzed to investigate the seasonal variability of microphysical characteristics of two types of rainfall. Rainfall at Zhaosu is classified as stratiform rainfall and convective rainfall in the normalized intercept parameter–median volume diameter (log10Nw–D0) and log10Nw–mass-weighted mean diameter (log10Nw–Dm) spaces, respectively. Both stratiform rainfall and convective rainfall samples in the log10Nw–D0 space are more than three times those in the log10Nw–Dm space, accompanied by smaller mean rainfall rate (R). Rainfall in summer (spring) has the lowest (highest) concentration of small-size raindrops, while rainfall in fall (summer) has the lowest (highest) concentration of mid- and large-size raindrops, accompanied by the largest (smallest) mean Dm and D0 values and the smallest (largest) mean log10Nw values in summer (spring). Convective rainfall exhibits more significant seasonal variation in microphysical parameters and DSD than stratiform rainfall, whether in the log10Nw–D0 space or the log10Nw–Dm space. The convective rainfall in spring is more like maritime cluster, whereas that in summer is more like continental cluster in the log10Nw–Dm space. Furthermore, in the log10Nw–D0 and log10Nw–Dm spaces, localized relationships of radar reflectivity factor – R (Z–R) and shape parameter – slope parameter (μ–∧) are derived across seasons for different rainfall types. The results indicate that there are significant seasonal variations in the microphysical characteristics of rainfall in the Tianshan Mountains of China for the two rainfall types. This study further emphasizes that different classification schemes for rainfall types can lead to significant differences in the characteristics of DSD, Z–R, and μ–∧ relationships for different rainfall types.

Mapping Landslide Susceptibility Areas Using GIS Analysis in Cilawu Sub-district, Garut, West Java

A landslide is the movement of soil mass down a slope. Landslides can be influenced by some factors including rainfall, soil type, land slope, land cover, and human activities. Cilawu Sub district, Garut, West Java is one of the most frequently experienced landslide areas which cause severe losses. This mapping aims to provide information about the landslide susceptibility areas in Cilawu Sub-district, Garut, West Java by using a Geographic Information System (GIS). This study used Digital Elevation Model (DEM) image, Landsat image, rainfall, geology, and soil types data which were then mapped using ArcGIS software. The analysis process used the overlay method, scoring method, and weighting method. The final result was a landslide map with 4 susceptibility levels covering low susceptibility, medium susceptibility, high susceptibility, and very high susceptibility. Based on this analysis, Cilawu District was dominated by the following classes: high susceptibility with an area of 5470.07 Ha, medium susceptibility with an area of 1627.78 Ha, very high susceptibility with an area of 515.96 Ha, and low susceptibility with an area of 366.16 Ha.

Flood Hazard Maping Using QGIS Spatial Analysis in Bangko and Masjid Watershed at Riau, Indonesia

Flooding is a natural occurrence hazardous to people and properties and produces environmental and economic losses, especially in flood-prone areas. This study will be used to assess flood risk in the Bangko and Masjid watersheds. To analyze it, flood hazard mapping is arranged by slope, land cover, elevation, rainfall, buffer zone, and soil type, which is done with the help of a Geographic Information System (GIS), specifically QuantumGIS (QGIS). This system tool assesses each variable utilizing satellite spatial data and categorizes the vulnerability being very high, high, medium, low, and very low. Each map arrangement value is combined using an overlay value to determine the flood susceptibility. According to the mapping results, the Bangko and Masjid watersheds are highly vulnerable to flooding. Based on the results of the mapping, in the Bangko watershed 61% of the total area is vulnerable to flooding, and 20% has high to very high vulnerability, while in the Mosque watershed 84% of the area is vulnerable to flooding and 11% of the total area has high vulnerability. to very high. After validation of areas that are often affected by floods, it is known that these areas are in vulnerable to very vulnerable areas. This is due to the low watershed elevation and flat slope and high rainfall, as well as residential areas close to the river in the watershed. This is due to the watershed's low elevation and flat slope and the high rainfall, and the residential area close to the river in the watershed area. Hence, it is vital to establish a convenient and straight-off understandable flood hazard map that emphasizes the management mitigation effects.

Geospatial Multi-Criteria Evaluation Using AHP–GIS to Delineate Groundwater Potential Zones in Zakho Basin, Kurdistan Region, Iraq

Groundwater availability in the Zakho Basin faces significant challenges due to political issues, border stream control, climate change, urbanization, land use changes, and poor administration, leading to declining groundwater quantity and quality. To address these issues, this study utilized the Analytic Hierarchy Process (AHP) and geospatial techniques to identify potential groundwater sites in Zakho. The study assigned weights normalized through the AHP eigenvector and created a final index using the weighted overlay method and specific criteria such as slope, flow accumulation, drainage density, lineament density, geology, well data, rainfall, and soil type. Validation through the receiver operating characteristic (ROC) curve (AUC = 0.849) and coefficient of determination (R2 = 0.81) demonstrated the model’s accuracy. The results showed that 17% of the area had the highest potential as a reliable groundwater source, 46% represented high-to-moderate potential zones, and 37% had low potential. Flat areas between rivers and high mountains displayed the greatest potential for groundwater development. Identifying these potential sites can aid farmers, regional planners, and local governments in making precise decisions about installing hand pumps and tube wells for a regular water supply. Additionally, the findings contribute to the development of a sustainable groundwater management plan, focusing on improving water usage and protecting water-related ecosystems in the region. Identification of the optimum influencing factors, arrangement of the factors in a hierarchy, and creation of a GWPI map will allow further planning for groundwater preservation and sustainability. This project can be conducted in other areas facing droughts.

Assessment of potential soil degradation on various land uses in Keduang Watershed

Keduang watershed is a catchment area in the Wonogiri and Karanganyar districts, contributing 38.33% of sedimentation to the Gajah Mungkur Reservoir. High value population pressure is present on agricultural land in the Keduang watershed, triggering increasingly serious land degradation. Degradation in the upstream sub-watershed has a strong effect on the downstream areas. Impacts of land degradation include a decrease in land productivity and farmers’ income, as well as the occurrence of critical land. Assessment of the potential soil degradation is important as an early indicator to determine the distribution of areas that have potential soil degradation for physical, chemical, and biological soil. This research was conducted in the Keduang watershed with the land use type consisting of paddy field, wood, moor, and plantation that overlayed through land use, rainfall, slope, and soil type map. The method used in this research is guided qualification. The result showed that the Keduang watershed has a soil degradation class from low to high. The medium class dominated the potential for soil degradation in Keduang watershed with the highest potential for degradation refers to moor with a slope of >40%, rainfall of 1908 mm/year, and Inceptisols soil type.

Evaluation of error components in rainfall retrieval from collocated commercial microwave links

Abstract. Opportunistic rainfall sensing using commercial microwave links (CMLs) operating in telecommunication networks has the potential to complement conventional rainfall monitoring; however, the diversity of sensors and their errors are difficult to handle. This analysis empirically evaluates errors in CML observations that manifest discrepancies between collocated sensors without reference to rainfall measurements. Collocated CMLs are evaluated as independent rainfall sensors and enable us to assess the effect of hardware homogeneity and measurement consistency using CML observations at 12 sites within a real telecommunication network in Prague. The evaluation considers 33 rainfall events distinguishing between stratiform and convective rainfall types in the period of 2014–2016, monitored at 1 min temporal resolution. Collocated CMLs of identical and different frequencies are evaluated, and different rainfall types are discussed. The collocated CMLs are in excellent agreement. The inherent error in rain-induced attenuation for paired independent CMLs is 0.4 dB. The high correlation of the rainfall intensity measurements between the collocated sensors was obtained in a range of 0.96 to 0.99, and the root mean square error ranges from 0.4 to 1.7 mm h−1. This confirms the homogeneous behaviour of the hardware in a real network. Therefore, the data of CMLs of the same characteristics can be processed with identical parameters for rainfall retrieval models.

Modeling Rainfall with Respect to Land Cover and Population in the Niger Delta Area Nigeria for the Period 1990-2040

Anthropogenic activities including oil exploration have led to environmental issues in the Niger Delta, Nigeria over the years, leading to the deterioration of aquatic and riparian ecosystems. This has affected health, fishing, subsistence farming, and the economy of residents of this region. The objectives of this study were to model rainfall with respect to the percentage land cover type and forecast the percentage land cover type in 2040 for the river Niger-Delta. The objectives were met by reviewing literature related to this study, data acquisition, and modeling. The data was accessed from Google Earth Engine and the World Bank climate websites. ArcGIS, Microsoft Excel and SPSS software were used to analyze the data. Land cover and rainfall data was modeled over ranges of time and data pairs from each variable for similar years were extracted and used to model the variation of rainfall versus land cover types. The land cover and rainfall data analyses are presented in the analysis section of this paper. The percentages of land cover in the study area under water and built-in were found to have increased while that under mangrove and vegetation were found to increase respectively between 1990 and 2040. Communities residing in the study region are highly vulnerable to the impacts of floods and water pollution by industries for half of each year. This study suggested several policies for the Niger-Delta well-being and protection of the region’s residents with respect to floods and related issues.