Bharat mein 1990-1999 ke dauraan shushkata visangatiyon ka kshetreey avem saamayik vishleshan

Aridity Anomaly Index (AAI), based on Thornthwaite’s water balance technique, has been used to identify the extent and persistence of aridity anomalies over 33 sub-divisions of India during a period of 10 years from 1990 to 1999. Regional and temporal analysis has been carried out to identify the areas and periods of intense and prolonged persistence. This study has shown that 1992 was worst hit by the aridity conditions, which emerged in 5 or more fortnights. All sub-divisions of north India were affected by moderate aridity during 1990, 1992-94 and 1999. Similarly, all sub-divisions of peninsular India were influenced by moderate aridity during 1991, 1993 and 1999. Severe aridity appeared in all sub-divisions of peninsular India during 1990. The duration of severe aridity was less than that of moderate aridity during all years. Moderate and severe aridity appeared simultaneously in 5 or more fortnights in maximum 9 sub-divisions in 1992 and occurred during maximum 5 years in Madhya Maharashtra. Moderate aridity in 5 or more fortnights emerged each year during 1990 to 1999 in coastal Andhra Pradesh. In 1991, maximum 55% sub-divisions were affected by severe aridity in 9th fortnight, whereas Saurashtra & Kutch was affected in 1996 and north Interior Karnataka in 1999 during maximum 7 fortnights. In the year 1992, maximum number of sub-divisions under moderate and severe persistence was 70% and 24% respectively. In north India, moderate persistence appeared in east Rajasthan in all nine years except 1996, with its longest duration of 8 fortnights in 1995. West Madhya Pradesh, in peninsular India, was affected by moderate aridity during 7 fortnights in each year during the period of study from 1990 to 1999.

Emprego do Índice de Anomalia de Chuva na Variabilidade Pluviométrica da Microrregião Do Curimataú Oriental no Estado da Paraíba

O estudo do clima vem se intensificando desde o século XX com o intuito de verificar as variações climáticas no espaço-tempo” em todo o território brasileiro. Deste modo é notório tentar entender como há uma grande variabilidade pluviométrica, principalmente nos estados do nordeste brasileiro. O objetivo principal deste trabalho é verificar e avaliar a variabilidade pluviométrica da microrregião do Curimataú Oriental no Estado da Paraíba, através da análise espaço-temporal mensal e anual da precipitação. Identificou-se assim os períodos secos e chuvosos da área estudada com o auxílio do Índice de Anomalia de Chuva (IAC). Os dados pluviométricos utilizados na pesquisa correspondem às séries mensais de precipitação no período de 1994 a 2017, fornecidos pela Agência Executiva de Gestões das Águas do Estado da Paraíba. A microrregião do Curimataú Oriental apresenta dois períodos distintos, um de sete meses chuvosos e outro com cinco meses secos. Completa-se ainda que o IAC é um instrumento de expressiva importância na análise desses dados, pois demonstra eficiência para averiguar os períodos extremos (úmidos e secos) e para realizar o monitoramento da precipitação de uma determinada região, município e/ou bacia hidrográfica. Employment of the Rain Anomaly Index in the Pluviometric Variability of the Micro-Region of the Oriental Curimataú in the State of Paraíba A B S T R A C T The study of climate has been intensifying since the 20th century to investigate space-time throughout the Brazilian territory. Thus, it is notorious to try to understand how there is a great climatic variability, mainly in the states of northeastern Brazil. The main objective of this work is to verify and evaluate the climatic variability of the eastern Curimataú microregion in the State of Paraíba, through the monthly and annual spatial-temporal analysis of its precipitation. Thus, the dry and rainy periods of the studied area were identified with the aid of the Rain Anomaly Index (IAC). The pluviometric data used in the research correspond to the monthly series of precipitation in the period from 1994 to 2017, provided by the Executive Agency for Water Management of the State of Paraíba. The Curimataú Oriental microregion has two distinct periods, one with seven rainy months and the other with five dry months. It is also completed that the IAC is an instrument of significant importance in the analysis of these data, as it demonstrates efficiency to ascertain the extreme periods (wet and dry) and to verify the monitoring of a certain region, municipality and / or hydrographic basin.Keyword: Precipitation anomalies, Periods, Variability.

A global dataset of standardized moisture anomaly index incorporating snow dynamics from 1948 to 2010

Drought indices are hard to balance in terms of versatility (effectiveness for multiple types of drought), flexibility of timescales, and inclusivity (to what extent they include all physical processes). A lack of consistent source data increases the difficulty of quantifying drought. Here, we present a global monthly drought dataset from 1948 to 2010 based on a multitype and multiscalar drought index, the standardized moisture anomaly index incorporating snow dynamics (SZIsnow), driven by systematic fields from an advanced data assimilation system. The proposed SZIsnow dataset includes different physical water‒energy processes, especially snow processes. Our evaluation of the dataset demonstrates its ability to distinguish different types of drought across different timescales. Our assessment also indicates that the dataset adequately captures droughts across different spatial scales. The consideration of snow processes improved the capability of SZIsnow, and the improvement is particularly evident over snow-covered high-latitude (e.g., Arctic region) and high-altitude areas (e.g., Tibetan Plateau). We found that 59.66 % of Earth's land area exhibited a drying trend between 1948 and 2010, and the remaining 40.34 % exhibited a wetting trend. Our results also show that the SZIsnow dataset successfully captured the large-scale drought events that occurred across the world; there were 525 drought events with an area larger than 500,000 square kilometers globally during the study period, of which nearly 70 % had a duration longer than 6 months. Therefore, this new drought dataset is well suited to monitoring, assessing, and characterizing drought, and can serve as a valuable resource for future drought studies.

Studi Perbandingan Metode Standardized Precipitation Index (SPI) dan Rainfall Anomaly Index (RAI) untuk Mengestimasi Kekeringan pada DAS Welang

Pada DAS Welang terdapat 20 desa di 5 kecamatan di Kabupaten Pasuruan serta 19 desa di 9 kecamatan di Kabupaten Malang yang termasuk daerah rawan kekeringan. Maka dari itu perlu dilakukan analisis kekeringan. Studi ini bertujuan untuk mengetahui hasil perbandingan indeks kekeringan meteorologi metode Standardized Precipitation Index (SPI) dan Rainfall Anomaly Index (RAI) serta kesesuaian metode apabila diterapkan di DAS Welang dalam mengestimasi kekeringan. Selain itu analisis spasial dengan bantuan software ArcGIS 10.3 bertujuan untuk mengetahui daerah yang berpotensi terdampak kekeringan pada DAS Welang. Hasil analisis kekeringan Metode SPI menghasilkan indeks kekeringan paling minimum pada stasiun hujan Purwodadi sebesar -4,09 pada periode 3 bulanan. Sedangkan metode RAI menghasilkan nilai indeks minimum sebesar -3,93 pada periode 1 bulanan. Setelah dilakukan analisis hubungan kesesuaian dengan indeks kekeringan hidrologi menggunakan metode Standardized Streamflow Index (SSI), didapatkan hasil korelasi yang bersifat lemah. Maka dari itu dipilih opsi perbandingan kualitatif dengan membandingkan pola debit dan data curah hujan bulanan dan metode RAI yang lebih sesuai. Hasil penggambaran peta sebaran kekeringan menggunakan metode IDW pada tahun dengan jumlah kejadian kering terparah yaitu tahun 2007 dan 2015, didapatkan sebanyak 42 desa berpotensi terdampak kekeringan dengan bulan kering yaitu bulan Agustus, September, dan Oktober.

Analysis of Agronomic Drought in a Highly Anthropogenic Context Based on Satellite Monitoring of Vegetation and Soil Moisture

This paper aims to analyze agronomic drought in a highly anthropogenic, semiarid region, the western Mediterranean region. The proposed study is based on Moderate-Resolution Imaging Spectroradiometer (MODIS) and Advanced SCATterometer (ASCAT) satellite data describing the dynamics of vegetation cover and soil water content through the Normalized Difference Vegetation Index (NDVI) and Soil Water Index (SWI). Two drought indices were analyzed: the Vegetation Anomaly Index (VAI) and the Moisture Anomaly Index (MAI). The dynamics of the VAI were analyzed as a function of land cover deduced from the Copernicus land cover map. The effect of land cover and anthropogenic agricultural activities such as irrigation on the estimation of the drought index VAI was analyzed. The VAI dynamics were very similar for the shrub and forest classes. The contribution of vegetation cover (VAI) was combined with the effect of soil water content (MAI) through a new drought index called the global drought index (GDI) to conduct a global analysis of drought conditions. The implementation of this combination on different test areas in the study region is discussed.

Soil moisture and streamflow deficit anomaly index: an approach to quantify drought hazards by combining deficit and anomaly

Drought is understood as both a lack of water (i.e., a deficit compared to demand) and a temporal anomaly in one or more components of the hydrological cycle. Most drought indices, however, only consider the anomaly aspect, i.e., how unusual the condition is. In this paper, we present two drought hazard indices that reflect both the deficit and anomaly aspects. The soil moisture deficit anomaly index, SMDAI, is based on the drought severity index, DSI (Cammalleri et al., 2016), but is computed in a more straightforward way that does not require the definition of a mapping function. We propose a new indicator of drought hazard for water supply from rivers, the streamflow deficit anomaly index, QDAI, which takes into account the surface water demand of humans and freshwater biota. Both indices are computed and analyzed at the global scale, with a spatial resolution of roughly 50 km, for the period 1981–2010, using monthly time series of variables computed by the global water resources and the model WaterGAP 2.2d. We found that the SMDAI and QDAI values are broadly similar to values of purely anomaly-based indices. However, the deficit anomaly indices provide more differentiated spatial and temporal patterns that help to distinguish the degree and nature of the actual drought hazard to vegetation health or the water supply. QDAI can be made relevant for stakeholders with different perceptions about the importance of ecosystem protection, by adapting the approach for computing the amount of water that is required to remain in the river for the well-being of the river ecosystem. Both deficit anomaly indices are well suited for inclusion in local or global drought risk studies.