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Regional assessments of droughts are limited and meticulous assessment of droughts over larger spatial scales are often not substantial. Understanding drought variability on a regional scale is crucial for enhancing resiliency and adaptive ability of water supply and distribution systems. Moreover, it can be essential for appraising the dynamics and predictability of droughts based on regional climate across various spatial and temporal scales. The drought analysis of the past was carried out with the development of a high-resolution dataset (1km×1km) for three drought-prone regions of India between 1950 and 2016. In the study the monthly values of self-calibrating Palmer Drought Severity Index (scPDSI), incorporating Penman–Monteith (PM) approximation, which is physically based on potential evapotranspiration. Climate data were statistically downscaled using the delta downscaling method and was formulated to form a timeline for characterizing major drought events that occurred in the past. The downscaled climate data were validated with the station observations. Major severe drought events that occurred between 1950 and 2016 were identified and studied with greater emphasis to the drought situation in smaller spatial extent such as districts, villages or localities. A timeline of drought events within the period of study was also prepared to have an understanding of the severity of drought in all three regions.Likewise, the future drought durations are projected for droughts of different levels of severity and assessed in the same regions of India. Coupled Model Intercomparison Project Phase 6 (CMIP6) simulated precipitation and climate data were used for near‐future (2015–2044) for different shared socio-economic pathways (SSPs). scPDSI, was used again based on its fairness in identifying drought conditions which accounts for the temperature as well. Gridded rainfall and temperature data of spatial resolution of 1km were used to bias correct the multi-model ensemble (MME) mean of 7 Global Climatic Models (GCMs) from CMIP6 project. Equidistant quantile-based mapping was adopted to remove the bias in the rainfall and temperature data and were corrected at the monthly scale. The downscaled climate data exhibited good statistical agreement with station data with correlation coefficient (R) ranging from 0.83 to 0.93 for both precipitation and temperature. Drought analysis indicated several major incidences over the analysis time period considered in this work, which truly adheres to the droughts recorded in qualitative reports of meteorological institutions in those regions. The drought study of the past helped to understand the situation in local levels and understand the necessities that can be opted for the future by proper management of water resources. While the outcome of the future prediction of drought duration suggests multiple severe to extreme drought events in all three study areas of appreciable durations mostly during the mid-2030s under the SSP2-4.5 scenario. The severe drought durations under the SSP2-4.5 scenario were found to be ranging around 25 to 30 months in 30 years period of the near future. The high-resolution drought index proved to be key to assess the drought situation for both the past and the future in three different drought-prone regions of India.

Drought is one of the most widespread and least understood natural phenomena. Many indices using multiple data types have been created, and their success at identifying periods of extreme wetness and dryness has been well documented. In recent years, researchers have begun to assess the potential of total water storage (TWS) anomalies in drought monitoring method- ologies. The Gravity Recovery and Climate Experiment (GRACE) provides temporally and spatially consistent TWS measurements across the globe, and studies have shown GRACE TWS anomalies are suited to identify drought. GRACE TWS is used with MODIS-derived normalized difference veg- etation index (NDVI) and NOAA/NWS precipitation data to create a new drought index, the Merged-dataset Drought Index (MDI). Each dataset corre- lates with a different type of drought, giving robustness to MDI. MDI is based on dataset deviations from a monthly climatology and is objective and easy to calculate. MDI is studied across Texas, which is broken into five dataset- defined sub-regions. Multiple drought events are identified from 2002 - 2014, with the most severe beginning in October 2010. A new drought severity clas- sification scheme is proposed based on MDI, and it is organized to match the current US Drought Monitor Classification Scheme. MDI shows strong correlation with existing drought indices, notably the Palmer Drought Severity Index (PDSI). MDI consistently identifies droughts in different sub-regions of Texas, but shows better performance in regions with large GRACE TWS signals. MDI performance is enhanced through a weighting scheme that relies more on GRACE TWS. Even with this scheme, MDI and PDSI exhibit occasional behavioral differences. Drought analysis using MDI shows for the first time that GRACE data provides information on a sub-regional scale in Texas, an area with low signal amplitudes. Past studies have shown TWS capable of identifying drought, but MDI is the first index to quantitatively use GRACE TWS in a manner consistent with current practices of identifying drought. MDI also establishes a framework for a future, completely remote-sensing based index that can enable temporally and spatially consistent drought identification across the globe. This study is useful as well for establishing a baseline for the necessary spatial resolution required from future geodetic space missions for use in drought identification at smaller scales. / text

A seca que assola o norte de Minas Gerais é um desencadeante de severos impactos socioambientais. Mudanças na distribuição das precipitações, ou mesmo a redução no volume de chuvas é fator suficiente para a desorganização da atividade econômica regional. Neste contexto, este trabalho analisou a distribuição espaço-temporal da seca/estiagem no norte de Minas Gerais, entre 2003 a 2014. A metodologia consistiu na elaboração de série temporal de anomalia padronizada de NDWI utilizando imagens de reflectância MOD13Q1/MODIS. Para a realização das análises utilizou-se como base: os decretos de anormalidade por motivo de seca/estiagem, dados de perdas e danos, de precipitação e de variação de água da subsuperfície das soluções GRACE. Foram realizadas correlações entre NDWI e precipitação e entre anomalia padronizada de NDWI e anomalia de precipitação, considerando dados sem e com 30 dias de defasagem. Foi aplicado teste de médias, teste t de Student, para a anomalia padronizada de NDWI e a anomalia de precipitação, em um intervalo de confiança de 95%. Os resultados demonstraram que a anomalia padronizada de NDWI identificou de forma satisfatória três períodos de seca/estiagem na região. Estes corroboram com os dados de decretos de emergência e calamidade pública, sendo observado um maior número de decretos, principalmente, nestes períodos. Dois períodos identificados como de seca/estiagem foram noticiados como de estiagem severa no norte de Minas Gerais. Esse fato corrobora os dados de anomalia padronizada de NDWI com a situação ocorrida na região. O quantitativo de áreas afetadas por seca também evidencia o mesmo período de maiores números de ocorrências de seca/estiagem e deficiência na distribuição da precipitação. No entanto, o emprego de anomalia padronizada de NDWI na identificação seca/estiagem, por si só, pode não ser suficiente para essa identificação, uma vez que, o fenômeno pode ocorrer e causar danos e prejuízos, em meio a uma paisagem verde, como constatado para 2010. As análises estatísticas mostraram que existem correlações com graus de intensidade melhores entre o NDWI e a precipitação com uma defasagem de 30 dias. Fato também observado para os dados de anomalia padronizada de NDWI e anomalia de precipitação, todavia, foram observadas correlações de fraca a moderada. O teste de médias apresentou diferenças entre as médias apenas para o ano de 2014. Apesar de em todos os outros períodos as médias não serem estatisticamente diferentes entre si, foram verificados baixos valores de p-value, com excessão do período entre 2008 e 2011, onde são verificados p-value entre 0,4 a 0,9. Ainda que os testes estatísticos não apresentaram uma ótima significância, a variação temporal dos dados de anomalia padronizada de NDWI e de anomalia de precipitação evidencia uma relação similar entre esses dados. Por fim, a comparação com dados das soluções GRACE, identificou os mesmos períodos verificados com a anomalia padronizada de NDWI, sendo então, observado que estes dados corroboram entre si na identificação de seca/estiagem no norte de Minas Gerais. / The drought that affects the north of Minas Gerais State causes severe socio-environment impacts. Changes on the precipitation distribution or even the reduction of the raining amount is enough reason for regional disorganization. In this context, this work analyzed the drought spatial-temporal distribution in the north of Minas Gerais State, between 2003 and 2014. The methodology consisted on the elaboration of time series of standardized anomaly NDWI using images of reflectance MOD13Q1/MODIS. For the analysis it was used the following basis: the abnormality decrees caused by drought, damage and losses data, precipitation and the water subsurface range on GRACE solution. Correlations were conducted between NDWI and precipitation, as well as between standardized anomaly NDWI and precipitation anomaly, considering data with and without 30 days of gap. It was applied average test, the Student t-test, for the standardized anomaly NDWI and precipitation anomaly, with a confidence range of 95%. Results demonstrated that standardized anomaly NDWI satisfactorily identified three seasons of drought in this region. It corroborates with emergency decrees and public calamity data, in what it was observed a higher number of decrees, especially in these periods. Two seasons identified as drought were reported as severe drought in the north of Minas Gerais State. This fact validates the standardized anomaly NDWI data with the situation occurred in the region. The quantity of affected areas drought, also evidences the same period of larger numbers of occurrences drought and disability in the distribution of precipitation. However, the use of standardized anomaly NDWI by itself on the identification of drought may not be enough evidence for this association, since the phenomenon can occur and cause damages and losses among a green landscape, as seen in 2010. Statistical analysis demonstrated that there are correlations with better intensity degrees between the NDWI and the precipitation with a gap of 30 days. This fact was also observed for the standardized anomaly NDWI and precipitation anomaly data, however, mild to moderate correlations were observed. Student t-test demonstrated differences between the averages only for the year of 2014. Despite for all other periods averages were not statistically different, they were observed p-value low values, with the exception of the period between 2008 and 2011, which are verified p-value between 0.4 and 0.9. Although statistical tests did not demonstrated a great significance, the temporal variation of standardized anomaly NDWI data and precipitation anomaly evidenciate a similar relationship between these data. Lastly, the comparison with data from GRACE solutions, identified the same periods verified with the standardized anomaly NDWI, being then observed that these data corroborates between them in the identification of draught in the north of Minas Gerais State.

Farming communities in the United States and around the world lose billions of dollars every year due to drought. Drought Indices such as the Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI) are widely used by the government agencies to assess and respond to drought. These drought indices are currently monitored at a large spatial resolution (several thousand km2). Further, these drought indices are primarily based on precipitation deficits and are thus good indicators for monitoring large scale meteorological drought. However, agricultural drought depends on soil moisture and evapotranspiration deficits. Hence, two drought indices, the Evapotranspiration Deficit Index (ETDI) and Soil Moisture Deficit Index (SMDI), were developed in this study based on evapotranspiration and soil moisture deficits, respectively. A Geographical Information System (GIS) based approach was used to simulate the hydrology using soil and land use properties at a much finer spatial resolution (16km2) than the existing drought indices. The Soil and Water Assessment Tool (SWAT) was used to simulate the long-term hydrology of six watersheds located in various climatic zones of Texas. The simulated soil water was well-correlated with the Normalized Difference Vegetation Index NDVI (r ~ 0.6) for agriculture and pasture land use types, indicating that the model performed well in simulating the soil water. Using historical weather data from 1901-2002, long-term weekly normal soil moisture and evapotranspiration were estimated. This long-term weekly normal soil moisture and evapotranspiration data was used to calculate ETDI and SMDI at a spatial resolution of 4km ?? 4km. Analysis of the data showed that ETDI and SMDI compared well with wheat and sorghum yields (r > 0.75) suggesting that they are good indicators of agricultural drought. Rainfall is a highly variable input both spatially and temporally. Hence, the use of NEXRAD rainfall data was studied for simulating soil moisture and drought. Analysis of the data showed that raingages often miss small rainfall events that introduce considerable spatial variability among soil moisture simulated using raingage and NEXRAD rainfall data, especially during drought conditions. The study showed that the use of NEXRAD data could improve drought monitoring at a much better spatial resolution.

Drought, which is an important result of the climate change, is one of the most serious natural hazards globally. It has been agreed all over the world that it has adverse impacts on the production of agriculture, which plays a major role in the economy of a country. Studies showed that the results of the drought directly affected the crop yields, and it seems that this negative impact will continue drastically soon. Moreover, many researches revealed that, Turkey will be affected from the results of climate change in many aspects, especially the agricultural production will encounter dry seasons after the rapid changes in the precipitation amount. Insurance is a well-established method, which is used to share the risk based on natural disasters by people and organizations. Furthermore, a new way of insuring against the weather shocks is designing index-based insurance, and it has gained special attention in many developing countries. In this study, our aim is to model weather index based drought insurance product to help the small holder farmers in the Cental Anatolia Region under different models. At first, time series techniques were applied to forecast the wheat yield relying on the past data. Then, the AMS (AgroMetShell) software outputs, NDVI (Normalized Difference Vegetation Index) values were used, and SPI values for distinct time steps were chosen to develop a basic threshold based drought insurance for each province. Linear regression equations were used to calculate the trigger points for weather index, afterwards based on these trigger levels / pure premium and indemnity calculations were made for each province separately. In addition to this, Panel Data Analysis were used to construct an alternative linear model for drought insurance. It can be helpful to understand the direct and actual effects of selected weather index measures on wheat yield and also reduce the basis risks for constructed contracts. A simple ratio was generated to compare the basis risk of the different index-based insurance contracts.

Farming communities in the United States and around the world lose billions of dollars every year due to drought. Drought Indices such as the Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI) are widely used by the government agencies to assess and respond to drought. These drought indices are currently monitored at a large spatial resolution (several thousand km2). Further, these drought indices are primarily based on precipitation deficits and are thus good indicators for monitoring large scale meteorological drought. However, agricultural drought depends on soil moisture and evapotranspiration deficits. Hence, two drought indices, the Evapotranspiration Deficit Index (ETDI) and Soil Moisture Deficit Index (SMDI), were developed in this study based on evapotranspiration and soil moisture deficits, respectively. A Geographical Information System (GIS) based approach was used to simulate the hydrology using soil and land use properties at a much finer spatial resolution (16km2) than the existing drought indices. The Soil and Water Assessment Tool (SWAT) was used to simulate the long-term hydrology of six watersheds located in various climatic zones of Texas. The simulated soil water was well-correlated with the Normalized Difference Vegetation Index NDVI (r ~ 0.6) for agriculture and pasture land use types, indicating that the model performed well in simulating the soil water. Using historical weather data from 1901-2002, long-term weekly normal soil moisture and evapotranspiration were estimated. This long-term weekly normal soil moisture and evapotranspiration data was used to calculate ETDI and SMDI at a spatial resolution of 4km ?? 4km. Analysis of the data showed that ETDI and SMDI compared well with wheat and sorghum yields (r > 0.75) suggesting that they are good indicators of agricultural drought. Rainfall is a highly variable input both spatially and temporally. Hence, the use of NEXRAD rainfall data was studied for simulating soil moisture and drought. Analysis of the data showed that raingages often miss small rainfall events that introduce considerable spatial variability among soil moisture simulated using raingage and NEXRAD rainfall data, especially during drought conditions. The study showed that the use of NEXRAD data could improve drought monitoring at a much better spatial resolution.

A seca que assola o norte de Minas Gerais é um desencadeante de severos impactos socioambientais. Mudanças na distribuição das precipitações, ou mesmo a redução no volume de chuvas é fator suficiente para a desorganização da atividade econômica regional. Neste contexto, este trabalho analisou a distribuição espaço-temporal da seca/estiagem no norte de Minas Gerais, entre 2003 a 2014. A metodologia consistiu na elaboração de série temporal de anomalia padronizada de NDWI utilizando imagens de reflectância MOD13Q1/MODIS. Para a realização das análises utilizou-se como base: os decretos de anormalidade por motivo de seca/estiagem, dados de perdas e danos, de precipitação e de variação de água da subsuperfície das soluções GRACE. Foram realizadas correlações entre NDWI e precipitação e entre anomalia padronizada de NDWI e anomalia de precipitação, considerando dados sem e com 30 dias de defasagem. Foi aplicado teste de médias, teste t de Student, para a anomalia padronizada de NDWI e a anomalia de precipitação, em um intervalo de confiança de 95%. Os resultados demonstraram que a anomalia padronizada de NDWI identificou de forma satisfatória três períodos de seca/estiagem na região. Estes corroboram com os dados de decretos de emergência e calamidade pública, sendo observado um maior número de decretos, principalmente, nestes períodos. Dois períodos identificados como de seca/estiagem foram noticiados como de estiagem severa no norte de Minas Gerais. Esse fato corrobora os dados de anomalia padronizada de NDWI com a situação ocorrida na região. O quantitativo de áreas afetadas por seca também evidencia o mesmo período de maiores números de ocorrências de seca/estiagem e deficiência na distribuição da precipitação. No entanto, o emprego de anomalia padronizada de NDWI na identificação seca/estiagem, por si só, pode não ser suficiente para essa identificação, uma vez que, o fenômeno pode ocorrer e causar danos e prejuízos, em meio a uma paisagem verde, como constatado para 2010. As análises estatísticas mostraram que existem correlações com graus de intensidade melhores entre o NDWI e a precipitação com uma defasagem de 30 dias. Fato também observado para os dados de anomalia padronizada de NDWI e anomalia de precipitação, todavia, foram observadas correlações de fraca a moderada. O teste de médias apresentou diferenças entre as médias apenas para o ano de 2014. Apesar de em todos os outros períodos as médias não serem estatisticamente diferentes entre si, foram verificados baixos valores de p-value, com excessão do período entre 2008 e 2011, onde são verificados p-value entre 0,4 a 0,9. Ainda que os testes estatísticos não apresentaram uma ótima significância, a variação temporal dos dados de anomalia padronizada de NDWI e de anomalia de precipitação evidencia uma relação similar entre esses dados. Por fim, a comparação com dados das soluções GRACE, identificou os mesmos períodos verificados com a anomalia padronizada de NDWI, sendo então, observado que estes dados corroboram entre si na identificação de seca/estiagem no norte de Minas Gerais. / The drought that affects the north of Minas Gerais State causes severe socio-environment impacts. Changes on the precipitation distribution or even the reduction of the raining amount is enough reason for regional disorganization. In this context, this work analyzed the drought spatial-temporal distribution in the north of Minas Gerais State, between 2003 and 2014. The methodology consisted on the elaboration of time series of standardized anomaly NDWI using images of reflectance MOD13Q1/MODIS. For the analysis it was used the following basis: the abnormality decrees caused by drought, damage and losses data, precipitation and the water subsurface range on GRACE solution. Correlations were conducted between NDWI and precipitation, as well as between standardized anomaly NDWI and precipitation anomaly, considering data with and without 30 days of gap. It was applied average test, the Student t-test, for the standardized anomaly NDWI and precipitation anomaly, with a confidence range of 95%. Results demonstrated that standardized anomaly NDWI satisfactorily identified three seasons of drought in this region. It corroborates with emergency decrees and public calamity data, in what it was observed a higher number of decrees, especially in these periods. Two seasons identified as drought were reported as severe drought in the north of Minas Gerais State. This fact validates the standardized anomaly NDWI data with the situation occurred in the region. The quantity of affected areas drought, also evidences the same period of larger numbers of occurrences drought and disability in the distribution of precipitation. However, the use of standardized anomaly NDWI by itself on the identification of drought may not be enough evidence for this association, since the phenomenon can occur and cause damages and losses among a green landscape, as seen in 2010. Statistical analysis demonstrated that there are correlations with better intensity degrees between the NDWI and the precipitation with a gap of 30 days. This fact was also observed for the standardized anomaly NDWI and precipitation anomaly data, however, mild to moderate correlations were observed. Student t-test demonstrated differences between the averages only for the year of 2014. Despite for all other periods averages were not statistically different, they were observed p-value low values, with the exception of the period between 2008 and 2011, which are verified p-value between 0.4 and 0.9. Although statistical tests did not demonstrated a great significance, the temporal variation of standardized anomaly NDWI data and precipitation anomaly evidenciate a similar relationship between these data. Lastly, the comparison with data from GRACE solutions, identified the same periods verified with the standardized anomaly NDWI, being then observed that these data corroborates between them in the identification of draught in the north of Minas Gerais State.

A seca que assola o norte de Minas Gerais é um desencadeante de severos impactos socioambientais. Mudanças na distribuição das precipitações, ou mesmo a redução no volume de chuvas é fator suficiente para a desorganização da atividade econômica regional. Neste contexto, este trabalho analisou a distribuição espaço-temporal da seca/estiagem no norte de Minas Gerais, entre 2003 a 2014. A metodologia consistiu na elaboração de série temporal de anomalia padronizada de NDWI utilizando imagens de reflectância MOD13Q1/MODIS. Para a realização das análises utilizou-se como base: os decretos de anormalidade por motivo de seca/estiagem, dados de perdas e danos, de precipitação e de variação de água da subsuperfície das soluções GRACE. Foram realizadas correlações entre NDWI e precipitação e entre anomalia padronizada de NDWI e anomalia de precipitação, considerando dados sem e com 30 dias de defasagem. Foi aplicado teste de médias, teste t de Student, para a anomalia padronizada de NDWI e a anomalia de precipitação, em um intervalo de confiança de 95%. Os resultados demonstraram que a anomalia padronizada de NDWI identificou de forma satisfatória três períodos de seca/estiagem na região. Estes corroboram com os dados de decretos de emergência e calamidade pública, sendo observado um maior número de decretos, principalmente, nestes períodos. Dois períodos identificados como de seca/estiagem foram noticiados como de estiagem severa no norte de Minas Gerais. Esse fato corrobora os dados de anomalia padronizada de NDWI com a situação ocorrida na região. O quantitativo de áreas afetadas por seca também evidencia o mesmo período de maiores números de ocorrências de seca/estiagem e deficiência na distribuição da precipitação. No entanto, o emprego de anomalia padronizada de NDWI na identificação seca/estiagem, por si só, pode não ser suficiente para essa identificação, uma vez que, o fenômeno pode ocorrer e causar danos e prejuízos, em meio a uma paisagem verde, como constatado para 2010. As análises estatísticas mostraram que existem correlações com graus de intensidade melhores entre o NDWI e a precipitação com uma defasagem de 30 dias. Fato também observado para os dados de anomalia padronizada de NDWI e anomalia de precipitação, todavia, foram observadas correlações de fraca a moderada. O teste de médias apresentou diferenças entre as médias apenas para o ano de 2014. Apesar de em todos os outros períodos as médias não serem estatisticamente diferentes entre si, foram verificados baixos valores de p-value, com excessão do período entre 2008 e 2011, onde são verificados p-value entre 0,4 a 0,9. Ainda que os testes estatísticos não apresentaram uma ótima significância, a variação temporal dos dados de anomalia padronizada de NDWI e de anomalia de precipitação evidencia uma relação similar entre esses dados. Por fim, a comparação com dados das soluções GRACE, identificou os mesmos períodos verificados com a anomalia padronizada de NDWI, sendo então, observado que estes dados corroboram entre si na identificação de seca/estiagem no norte de Minas Gerais. / The drought that affects the north of Minas Gerais State causes severe socio-environment impacts. Changes on the precipitation distribution or even the reduction of the raining amount is enough reason for regional disorganization. In this context, this work analyzed the drought spatial-temporal distribution in the north of Minas Gerais State, between 2003 and 2014. The methodology consisted on the elaboration of time series of standardized anomaly NDWI using images of reflectance MOD13Q1/MODIS. For the analysis it was used the following basis: the abnormality decrees caused by drought, damage and losses data, precipitation and the water subsurface range on GRACE solution. Correlations were conducted between NDWI and precipitation, as well as between standardized anomaly NDWI and precipitation anomaly, considering data with and without 30 days of gap. It was applied average test, the Student t-test, for the standardized anomaly NDWI and precipitation anomaly, with a confidence range of 95%. Results demonstrated that standardized anomaly NDWI satisfactorily identified three seasons of drought in this region. It corroborates with emergency decrees and public calamity data, in what it was observed a higher number of decrees, especially in these periods. Two seasons identified as drought were reported as severe drought in the north of Minas Gerais State. This fact validates the standardized anomaly NDWI data with the situation occurred in the region. The quantity of affected areas drought, also evidences the same period of larger numbers of occurrences drought and disability in the distribution of precipitation. However, the use of standardized anomaly NDWI by itself on the identification of drought may not be enough evidence for this association, since the phenomenon can occur and cause damages and losses among a green landscape, as seen in 2010. Statistical analysis demonstrated that there are correlations with better intensity degrees between the NDWI and the precipitation with a gap of 30 days. This fact was also observed for the standardized anomaly NDWI and precipitation anomaly data, however, mild to moderate correlations were observed. Student t-test demonstrated differences between the averages only for the year of 2014. Despite for all other periods averages were not statistically different, they were observed p-value low values, with the exception of the period between 2008 and 2011, which are verified p-value between 0.4 and 0.9. Although statistical tests did not demonstrated a great significance, the temporal variation of standardized anomaly NDWI data and precipitation anomaly evidenciate a similar relationship between these data. Lastly, the comparison with data from GRACE solutions, identified the same periods verified with the standardized anomaly NDWI, being then observed that these data corroborates between them in the identification of draught in the north of Minas Gerais State.

<p>U ovoj disertaciji je definisan i predstavljen pristup monitoringu poljoprivredne su&scaron;e (SPEI-based approach to agricultural drought monitoring - ADM-SPEI) u Vojvodini koji objedinjuje vi&scaron;e poznatih i priznatih metoda i kritičko mi&scaron;ljenje eksperata zasnovano na njihovom znanju i iskustvu i pri tome uzima u obzir lokalne specifičnosti agroklimatskih uslova. Iako je kreiran za područje Vojvodine, predloženi pristup monitoringu poljoprivredne su&scaron;e baziran na SPEI indeksu opisan je generalno kroz tri faze i pripadajuće korake koji su detaljno opisani i obja&scaron;njeni &scaron;to omogućava da se ADM- SPEI pristup modifikuje i primeni u bilo kojim drugim agroklimatskim uslovima. Predstavljeni pristup baziran je na modifikovanom i &scaron;iroko prihvaćenom i kori&scaron;ćenom Standardizovanom Indeksu Padavina i Evapotranspiracije (SPEI). Ovom modifikacijom SPEI je povezan sa&nbsp; specifičnom kulturom &scaron;to omogućava da se su&scaron;a, odnosno uslovi vlažnosti analiziraju individualno za specifičnu ratarsku ili povrtarsku kulturu u agroklimatskim uslovima Vojvodine. Kreiranju pristupa monitoringu poljoprivredne su&scaron;e prethodilo je istraživanje koje se tiče uticaja referentne evapotranspiracije (ET0) na rezultate SPEI indeksa kako bi se potvrdila polazna pretpostavka da različiti metodi za izračunavanje ET0 u okviru SPEI indeksa daju u nekim slučajevima značajno različite vrednosti indeksa na području Vojvodine. Iz navedenih razloga je važno koristiti metod koji najvi&scaron;e odgovara specifičnom području od interesa. Modifikacija SPEI indeksa, odnosno zamena ET0 sa ETc (potencijalnom evapotranspiracijom kulture) izvr&scaron;ena je uključivanjem ekspertskog mi&scaron;ljenja odnosno intervjuisanjem vi&scaron;e stručnjaka različitih ekspertiza iz domena kori&scaron;ćenja i upravljanja vodama u poljoprivredi &scaron;to je omogućilo da se dođe do grupne odluke koja u najvećoj meri reprezentuje lokalne agroklimatske prilike. U tu svrhu upotrebljen je Analitički Hijerarhijski Proces (AHP metod) kao podr&scaron;ka odlučivanju kako bi se dobile individualne odluke stručnjaka i da bi se u narednom koraku dobila jedna grupna odluka o najpogodnijem metodu za izračunavanje ET0, odnosno ETc. U narednoj fazi predloženog pristupa, prateći dalju proceduru originalnog SPEI indeksa izračunati su klimatski vodni bilansi kultura. Analizom su obuhvaćeni podaci sa devet meteorolo&scaron;kih stanica na području Vojvodine, kao i jedanaest ratarskih i povrtarskih kultura. Zatim je statističkim metodama odabrana odgovarajuća teorijska distribucija za koju je potvrđeno najbolje slaganje sa empirijskim vrednostima klimatskog vodnog bilansa kultura i u narednom koraku dobijen modifikovani SPEI povezan sa specifičnom kulturom (agricultural drought SPEI - AD-SPEIcrop). Pristup omogućava i direktnu transformaciju indeksa u vrednosti klimatskog vodnog bilansa kulture, odražavajući potrebe useva za vodom. Sagledavanjem su&scaron;e i sa tog aspekta omogućava analizu mogućnosti sistema za navodnjavanje u borbi protiv su&scaron;e. U sledećoj fazi izvr&scaron;ena je validacija predloženog pristupa sa vi&scaron;e različitih aspekata koji podrazumevaju: ispitivanje povezanosti indeksa sa prinosima kultura, kako na lokalnom nivou op&scaron;tina tako i na nivou cele teritorije Vojvodine; poređenje stepena slaganja sa prinosima kultura u odnosu na originalni indeks SPEI; komparaciju sa op&scaron;te priznatim i prihvaćenim indeksima su&scaron;e (SPI, SPEI i SC-PDSI); i povratnu informaciju od strane eksperata. Bazirajući se na dobijenim rezultatima u fazi validacije može se zaključiti da predloženi pristup monitoringu poljoprivredne su&scaron;e na području Vojvodine baziran na SPEI indeksu može biti uspe&scaron;no primenjen i sa dobrim performansama, odnosno da indeks AD-SPEIcrop, dobijen kao rezultat ovog pristupa, predstavlja adekvatan pokazatelj poljoprivredne su&scaron;e na području Vojvodine.</p> / <p>In the doctoral dissertation, the SPEI-based approach to agricultural drought monitoring (ADM-SPEI) in Vojvodina has been defined and presented. While integrating several well-known and recognized methods and experts&rsquo; critical opinion based on their knowledge and experience, ADM-SPEI takes into account local specificities of agro-climatic conditions. Although it was created for the Vojvodina region, the proposed approach to agricultural drought monitoring based on the SPEI index has been described in three phases alongside the corresponding steps, for which a detailed description and explanation have also been provided. This allows for the ADM-SPEI approach to be modified and applied in any other agro-climatic conditions. The presented approach is based on the modified and widely accepted and used Standardized Precipitation and Evapotranspiration Index (SPEI). The modification enables relating the SPEI to a specific crop, thereby ensuring the possibility for the analysis of drought or moisture conditions separately for specific field or vegetable crops in the agro-climatic conditions of Vojvodina. The creation of the approach to agricultural drought monitoring was preceded by the research of the impact of reference evapotranspiration (ET0) on the results of the SPEI index. The aim of the research was to confirm the initial assumption that different methods for calculating ET0 within the SPEI index give in some cases significantly different index values in the Vojvodina region. For these reasons, it is important to use the most appropriate method for the specific area of interest. Carrying out the modification of the SPEI index, i.e., the replacement of the ET0 with the ETc (potential crop evapotranspiration) included the involvement of experts&rsquo; opinions by interviewing experts of various expertise in the domain of water use and water management in agriculture. This led to making a group decision representing the local agro-climatic conditions. For this purpose, the Analytical Hierarchy Process (AHP method) was used as a decision-making support in order to get experts&rsquo; individual decisions and, in the next step, to obtain a group decision on the most suitable method for calculating ET0 and ETc. In the next phase of the proposed approach, following the procedure of the original SPEI index, the cropspecific climate water balances were calculated. The analysis includes data from nine meteorological stations in the Vojvodina region, as well as eleven field and vegetable crops. Then, statistical methods were used to select the appropriate theoretical distribution which proved to best fit to the empirical values of the crop-specific climatic water balance. In the next step, the modified SPEI related to specific crops (agricultural drought SPEI - ADSPEIcrop) was obtained. The approach also enables the direct transformation of the index into the values of the climate water balance of crops reflecting the crop water needs. Examining drought from this perspective as well makes it possible to analyze the capabilities of irrigation systems to cope with drought. In the next phase, the validation of the proposed approach was carried out from several different perspectives including examining the correlation of the index with the crop yields, both at the local county level and at the level of the entire territory of Vojvodina; the comparison between the degree of the agreement of the AD-SPEIcrop and the original SPEI index with the crop yields, respectively; the comparison with the generally acknowledged and accepted drought indices (SPI, SPEI and SC-PDSI); and experts&rsquo; feedback. According to the obtained results in the validation phase, it can be concluded that the proposed approach to agricultural drought monitoring in the Vojvodina region based on the SPEI index can be applied successfully and with good performance, and that the ADSPEIcrop index obtained as a result of this approach is an adequate indicator of agricultural drought in the Vojvodina region.</p>