The Alpine Drought Observatory

2020 ◽  
Author(s):  
Felix Greifeneder ◽  
Emilie Crouzat ◽  
Mario Fosatti ◽  
Gregor Gregoric ◽  
Klaus Haslinger ◽  
...  
Keyword(s):  
Case Studies ◽  
Meteorological Drought ◽  
Hydrological Drought ◽  
Agricultural Drought ◽  
Drought Indices ◽  
Drought Risk ◽  
Alpine Regions ◽  
The Alps ◽  
Set Up ◽  
Available Information

<p>Water scarcity and related conflicts are becoming a worrying topic in Alpine regions. Moreover, lowland regions far beyond the Alps suffer from missing water from the Alps. Thus, countries are urged to act on this topic with common strategies. To support this cause, the Interreg Alpine-Space project, Alpine Drought Observatory (ADO), aims to set up a virtual observatory for the monitoring of drought in the entire Alpine region and beyond this, to derive recommendations for improved risk preparedness and efficiency of drought management.</p><p>The ADO itself will be a transnational alpine-wide operational system with a web-interface (e.g. WebGIS, periodic reports) to access data and specific impact-oriented indices for monitoring droughts and their impacts. It will provide optimized observations and forecasts for mountainous areas, which could be integrated in existing EU-level monitoring systems (e.g. European Drought Observatory). Monitoring will be based on a fusion of existing approaches (e.g. meteorological drought indices, hydrological drought indices), and newly available information (e.g. remote sensing of snow and soil moisture), to provide an optimized set of drought indices and a common drought classification. One of the further project activities will be the collection and recording of specific drought impacts. This knowledge will help to relate meteo-hydrological indices to concrete, real world effects and thus significantly enhance their applicability for drought monitoring and management.</p><p>The ADO will be tested in six case studies in all alpine countries with local partners. The case studies represent different drought issues such as agricultural drought, hydrological drought or drought impact on ecosystems. Out of the case studies, guidelines for an improved drought risk management will be developed. Findings will be upscaled to recommendations for drought governance policies for the Alps. Main beneficiaries of project findings are institutions with decision-making capacities in the field of water management, energy production, and agriculture.</p>

scholarly journals Mapping the Spatial and Temporal Variation of Agricultural and Metrological Drought Using Geospatial Techniques, Ethiopia

2020 ◽  
Author(s):  
Abebe Senamaw ◽  
Solomon Addisu ◽  
K.V. Suryabhagavan
Keyword(s):  
Temporal Variation ◽  
Crop Yield ◽  
Meteorological Drought ◽  
Condition Index ◽  
Agricultural Drought ◽  
Spatial And Temporal Variation ◽  
Drought Indices ◽  
Drought Risk ◽  
Drought Condition ◽  
Gis And Remote Sensing

Abstract Background Geographic Information System (GIS) and Remote Sensing play an important role for near real time monitoring of drought condition over large areas. The objective of this study was to assess spatial and temporal variation of agricultural and metrological drought using temporal image of eMODIS NDVI based vegetation condition index (VCI) and standard precipitation index (SPI). To validate the strength of drought indices correlation analysis was made between VCI and crop yield anomaly as well as SPI and crop yield anomaly. The results revealed that the year 2009 and 2015 were drought years while the 2001 and 2007 were wet years. There was also a good correlation between NDVI and rainfall (r=0.71), VCI and crop yield anomaly (0.72), SPI and crop yield anomaly (0.74). Frequency of metrological and agricultural drought was compiled by using historical drought intensity map. ResultThe result shows that there was complex and local scale variation in frequency of drought events in the study period. There was also no year without drought in many parts of the study area. Combined drought risk map also showed that 8%, 56%, 35% and 8% of study area were vulnerable to very severe, severe and moderate drought condition respectively. Conclusion In conclusion, the study area is highly vulnerable to agricultural and meteorological drought. Thus besides mapping drought vulnerable areas, integrating socioeconomic data for better understand other vulnerable factors were recommended.

scholarly journals ANALISIS KETERKAITAN ANTARA KEKERINGAN METEOROLOGIS DENGAN INDEKS VEGETASI TERSTANDARISASI DI PULAU LOMBOK

2021 ◽  
Vol 22 (2) ◽  
pp. 41-49
Author(s):  
Siti Najma Nindya Utami ◽  
Rista Hernandi Virgianto ◽  
Dzikrullah Akbar
Keyword(s):  
Vegetation Index ◽  
Meteorological Drought ◽  
Agricultural Drought ◽  
Maximum Temperature ◽  
Drought Indices ◽  
Drought Risk ◽  
Observation Data ◽  
Standardized Precipitation Evapotranspiration Index ◽  
Length Of The Day ◽  
Lombok Island

Intisari Kekeringan merupakan bencana kompleks yang dapat menyebabkan kerugian masyarakat di berbagai sektor. Salah satu wilayah yang berisiko tinggi mengalami kekeringan adalah Pulau Lombok. Wilayah ini memiliki lahan yang berisiko terkena kekeringan seluas 405.985 ha. Tingkat keparahan kekeringan meteorologis dapat diukur dengan Standardized Precipitation Evapotranspiration Index (SPEI). Salah satu karakteristik kekeringan adalah kondisi vegetasi tanaman yang buruk, oleh karena itu Standardized Vegetation Index (SVI) digunakan sebagai acuan dalam monitoring kekeringan agrikultural. Penelitian ini bertujuan untuk mengetahui hubungan antara SPEI dengan SVI untuk setiap pos hujan di Pulau Lombok tahun 2001-2018. Penelitian ini menggunakan data bulanan tahun 2001-2018 yang meliputi data observasi curah hujan, suhu maksimum, suhu minimum, penginderaan jauh Normalized Differences Vegetation Index (NDVI) dengan resolusi 0,05°, model FLDAS kecepatan angin yang juga didapatkan dengan resolusi 0,5°, lama penyinaran matahari, lintang, dan elevasi. Metode yang digunakan yaitu menghitung indeks kekeringan SPEI dan SVI, kemudian menghitung korelasi dan signifikansi untuk kedua indeks kekeringan tersebut. Hasilnya menunjukkan bahwa SPEI1 lebih tinggi berkorelasi dengan SVI+1 dengan kategori cukup kuat. Untuk SPEI3, SPEI6, dan SPEI12 berkorelasi cukup kuat hingga kuat dengan SVI0. Hal ini menunjukkan bahwa kekeringan jangka panjang akan langsung mempengaruhi kekeringan agrikultural atau kekeringan vegetasi saat itu juga. Nilai korelasi yang lebih tinggi untuk setiap indeks tersebar di pos hujan yang terletak di tengah-tengah Pulau Lombok, karena pengaruh kondisi geografis dan demografis Abstract Drought is a complex disaster because it can cause loss to society in various sectors. One of the high-risk areas of drought is Lombok Island. This area has 405,985 ha of drought risk. The severity of meteorological drought can be measured by the Standardized Precipitation Evapotranspiration Index (SPEI). One of the characteristics of drought is the poor condition of plant vegetation, therefore the Standardized Vegetation Index (SVI) is used as a reference in monitoring agricultural drought. This study aims to determine the relationship of SPEI with SVI for each rainfall post in Lombok Island from 2001-2018. This study uses monthly data from 2001-2018, including observation data of rainfall, maximum temperature, minimum temperature, remote sensing Normalized Differences Vegetation Index (NDVI) 0.05 °, FLDAS model of wind speed 0.5 °, length of the day, latitude, and elevation. The use method is to calculate SPEI and SVI, then calculate the correlation and significance for the two drought indices. The result shows that SPEI1 is higher in correlation with SVI+1, which is in a strong enough category. For SPEI3, SPEI6, and SPEI12, the correlation is strong enough to strong with SVI0. This suggests that long-term drought will directly affect agricultural drought or immediate vegetation drought. The higher correlation values ??for each index are spread over the rain posts located in the middle of Lombok Island because geographic and demographic conditions influence them.  

scholarly journals Mapping the spatial and temporal variation of agricultural and meteorological drought using geospatial techniques, Ethiopia

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Abebe Senamaw ◽  
Solomon Addisu ◽  
K. V. Suryabhagavan
Keyword(s):  
Temporal Variation ◽  
Crop Yield ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Precipitation Index ◽  
Agricultural Drought ◽  
Spatial And Temporal Variation ◽  
Drought Indices ◽  
Drought Risk ◽  
Drought Condition

Abstract Background Geographic Information System (GIS) and Remote Sensing play an important role for near real time monitoring of drought condition over large areas. The aim of this study was to assess spatial and temporal variation of agricultural and meteorological drought using temporal image of eMODIS NDVI based vegetation condition index (VCI) and standard precipitation index (SPI) from the year 2000 to 2016. To validate the strength of drought indices correlation analysis was made between VCI and crop yield anomaly as well as standardized precipitation index (SPI) and crop yield anomaly. Results The results revealed that the year 2009 and 2015 was drought years while the 2001 and 2007 were wet years. There was also a good correlation between NDVI and rainfall (r = 0.71), VCI and crop yield anomaly (0.72), SPI and crop yield anomaly (0.74). Frequency of metrological and agricultural drought was compiled by using historical drought intensity map. The result shows that there was complex and local scale variation in frequency of drought events in the study period. There was also no year without drought in many parts of the study area. Combined drought risk map also showed that 8%, 56% and 35% of the study area were vulnerable to very severe, severe and moderate drought condition respectively. Conclusions In conclusion, the study area is highly vulnerable to agricultural and meteorological drought. There was also no year without drought in many parts of the study area. Thus besides mapping drought vulnerable areas, integrating socio-economic data for better understand other vulnerable factors were recommended.

scholarly journals Seasonal drought prediction for semiarid northeastern Brazil: verification of six hydro-meteorological forecast products

2018 ◽  
Vol 22 (9) ◽  
pp. 5041-5056 ◽  
Author(s):  
José Miguel Delgado ◽  
Sebastian Voss ◽  
Gerd Bürger ◽  
Klaus Vormoor ◽  
Aline Murawski ◽  
...  
Keyword(s):  
Rainy Season ◽  
Meteorological Drought ◽  
Skill Score ◽  
Hydrological Drought ◽  
Northeastern Brazil ◽  
Drought Indices ◽  
Monthly Precipitation ◽  
Seasonal Forecasts ◽  
Seasonal Drought ◽  
Drought Prediction

Abstract. A set of seasonal drought forecast models was assessed and verified for the Jaguaribe River in semiarid northeastern Brazil. Meteorological seasonal forecasts were provided by the operational forecasting system used at FUNCEME (Ceará's research foundation for meteorology) and by the European Centre for Medium-Range Weather Forecasts (ECMWF). Three downscaling approaches (empirical quantile mapping, extended downscaling and weather pattern classification) were tested and combined with the models in hindcast mode for the period 1981 to 2014. The forecast issue time was January and the forecast period was January to June. Hydrological drought indices were obtained by fitting a multivariate linear regression to observations. In short, it was possible to obtain forecasts for (a) monthly precipitation, (b) meteorological drought indices, and (c) hydrological drought indices. The skill of the forecasting systems was evaluated with regard to root mean square error (RMSE), the Brier skill score (BSS) and the relative operating characteristic skill score (ROCSS). The tested forecasting products showed similar performance in the analyzed metrics. Forecasts of monthly precipitation had little or no skill considering RMSE and mostly no skill with BSS. A similar picture was seen when forecasting meteorological drought indices: low skill regarding RMSE and BSS and significant skill when discriminating hit rate and false alarm rate given by the ROCSS (forecasting drought events of, e.g., SPEI1 showed a ROCSS of around 0.5). Regarding the temporal variation of the forecast skill of the meteorological indices, it was greatest for April, when compared to the remaining months of the rainy season, while the skill of reservoir volume forecasts decreased with lead time. This work showed that a multi-model ensemble can forecast drought events of timescales relevant to water managers in northeastern Brazil with skill. But no or little skill could be found in the forecasts of monthly precipitation or drought indices of lower scales, like SPI1. Both this work and those here revisited showed that major steps forward are needed in forecasting the rainy season in northeastern Brazil.

scholarly journals Commonly Used Drought Indices as Indicators of Soil Moisture in China

2015 ◽  
Vol 16 (3) ◽  
pp. 1397-1408 ◽  
Author(s):  
Hongshuo Wang ◽  
Jeffrey C. Rogers ◽  
Darla K. Munroe
Keyword(s):  
Soil Moisture ◽  
Time Scales ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Severity Index ◽  
Agricultural Drought ◽  
Weather Data ◽  
Drought Indices ◽  
Drought Severity ◽  
Better Than

Abstract Soil moisture shortages adversely affecting agriculture are significantly associated with meteorological drought. Because of limited soil moisture observations with which to monitor agricultural drought, characterizing soil moisture using drought indices is of great significance. The relationship between commonly used drought indices and soil moisture is examined here using Chinese surface weather data and calculated station-based drought indices. Outside of northeastern China, surface soil moisture is more affected by drought indices having shorter time scales while deep-layer soil moisture is more related on longer index time scales. Multiscalar drought indices work better than drought indices from two-layer bucket models. The standardized precipitation evapotranspiration index (SPEI) works similarly or better than the standardized precipitation index (SPI) in characterizing soil moisture at different soil layers. In most stations in China, the Z index has a higher correlation with soil moisture at 0–5 cm than the Palmer drought severity index (PDSI), which in turn has a higher correlation with soil moisture at 90–100-cm depth than the Z index. Soil bulk density and soil organic carbon density are the two main soil properties affecting the spatial variations of the soil moisture–drought indices relationship. The study may facilitate agriculture drought monitoring with commonly used drought indices calculated from weather station data.

Study on the correlation between meteorological and agricultural drought, based on remotely sensed indices

2020 ◽  
Author(s):  
Ruja Mansorian ◽  
Mohammad Zare ◽  
Guy Schumann
Keyword(s):  
Time Scales ◽  
Vegetation Index ◽  
Meteorological Drought ◽  
Lag Time ◽  
Irrigation Scheduling ◽  
Agricultural Drought ◽  
Standard Normal Distribution ◽  
Drought Indices ◽  
Landsat 8 ◽  
Drought Condition

<p>In this study, long-term time series of precipitation data were used for determining the drought condition using the standard precipitation index (SPI) for 3, 6 and 12 month time scales. The indicators were calculated with two methods: a) using a gamma distribution and transforming the probability of occurrence to standard normal distribution, b) using the non-parametric plotting position method. Then, the SPI values for two consequent years 2013-14 and 2014-15 were extracted from data to study on meteorological drought. The SPI index calculations showed that the first year had near normal, whereas the second year had extreme drought condition. In parallel, 34 Landsat 8 satellite images were downloaded during the indicated time period to determine normalized difference vegetation index (NDVI) and vegetation condition index (VCI) as agricultural drought indices. The mean values of VCI for each month were considered as representative value for drought condition of the area. When the agricultural and meteorological drought indices were determined, the correlation coefficient (r) were calculated for finding the relation between these types of droughts. the results show that the highest correlation between SPI-3,6 and 12-month time scales and VCI occurred in 4, 2 and 4 months lag time respectively, with corresponding r value of 0.67, 0.65 and 0.69. The best agreement between these indices with calculated lag time proves the hypothesis that agricultural drought occurs after meteorological drought. Therefore, the results could be applied by farmers to plan an appropriate irrigation scheduling for upcoming droughts, specially, in arid and semi-arid areas. It could be concluded that for having suitable planning in water scarcity condition, understanding the situation helps water planners have better insight about management polices to minimize the effects of this natural hazard on human. To sum up, finding a relation between different types of droughts is helpful for monitoring, predicting and detecting droughts to better prepare for drought phenomena and to minimize losses</p>

scholarly journals Finescale Evaluation of Drought in a Tropical Setting: Case Study in Sri Lanka

2009 ◽  
Vol 48 (1) ◽  
pp. 77-88 ◽  
Author(s):  
Bradfield Lyon ◽  
Lareef Zubair ◽  
Vidhura Ralapanawe ◽  
Zeenas Yahiya
Keyword(s):  
Sri Lanka ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Drought Indices ◽  
Drought Risk ◽  
Mitigation And Adaptation ◽  
Wide Range ◽  
Drought Relief ◽  
Drought Indicators ◽  
The Standardized Precipitation Index

Abstract In regions of climatic heterogeneity, finescale assessment of drought risk is needed for policy making and drought management, mitigation, and adaptation. The relationship between drought relief payments (a proxy for drought risk) and meteorological drought indicators is examined through a retrospective analysis for Sri Lanka (1960–2000) based on records of district-level drought relief payments and a dense network of 284 rainfall stations. The standardized precipitation index and a percent-of-annual-average index for rainfall accumulated over 3, 6, 9, and 12 months were used, gridded to a spatial resolution of 10 km. An encouraging correspondence was identified between the spatial distribution of meteorological drought occurrence and historical drought relief payments at the district scale. Time series of drought indices averaged roughly over the four main climatic zones of Sri Lanka showed statistically significant (p < 0.01) relationships with the occurrence of drought relief. The 9-month cumulative drought index provided the strongest relationships overall, although 6- and 12-month indicators provided generally similar results. Some cases of appreciable drought without corresponding relief payments could be attributed to fiscal pressures, as during the 1970s. Statistically significant relationships between drought indicators and relief payments point to the potential utility of meteorological drought assessments for disaster risk management. In addition, the study provides an empirical approach to testing which meteorological drought indicators bear a statistically significant relationship to drought relief across a wide range of tropical climates.

scholarly journals Impact of Meteorological Drought in Upper Blue Nile Basin on the Hydrological Drought of Nile River in Egypt

2020 ◽  
Vol 9 (6) ◽  
pp. 50-55
Keyword(s):  
Water Resources ◽  
Pearson Correlation ◽  
Meteorological Drought ◽  
Hydrological Drought ◽  
Drought Indices ◽  
Nile River ◽  
Nile Basin ◽  
Blue Nile ◽  
Blue Nile Basin ◽  
Upper Blue Nile Basin

Precipitation over the Upper Blue Nile Basin in Ethiopia contributes with 85% of the Nile river which provides 93% of Egypt’s conventional water resources. This study aims at assessing the meteorological drought in different locations in the Upper Blue Nile Basin and their relationship with the hydrological drought of Nile river in Egypt. The metrological drought was calculated by the Standard Precipitation Index (SPI) at five stations inside and close to the Upper Blue Nile Basin in Ethiopia, whereas the hydrological drought was calculated by the Streamflow Drought Index (SDI) at Dongola station at Nasser lake entrance. Both indices were calculated using the Drought Indices Calculator (DrinC) software. The selected study period was from 1973 to 2017 based on the availability of recorded data for meteorological stations in Ethiopia, and the streamflow for Dongola station. The data was categorized for each station by considering time periods of 1, 3, 6, 9, and 12 months based on their homogeneity. The correlation between SPI and SDI was evaluated using the Pearson correlation coefficient. The results showed a correlation between SPI for the five stations in the Upper Blue Nile Basin and SDI for Dongola station, where Gore station represented the highest frequency of significance at different time scales especially at the 3-months’ scale. The results confirm the relationship between SPI at Gore Station and SDI at Dongola Station, which means that the hydrological drought in Egypt is highly affected by the meteorological drought in the area surrounding Gore station. The paper recommends improving techniques for monitoring and overseeing drought hazards and assessing more meteorological stations to accurately predict climate change variations in Upper Blue Nile Basin and its effect on Egypt’s water resources.

scholarly journals Seasonal Drought Prediction for Semiarid Northeast Brazil: Verification of Six Hydro-Meteorological Forecast Products

2017 ◽  
Author(s):  
José Miguel Delgado ◽  
Sebastian Voss ◽  
Gerd Bürger ◽  
Klaus Vormoor ◽  
Aline Murawski ◽  
...  
Keyword(s):  
Rainy Season ◽  
Meteorological Drought ◽  
Skill Score ◽  
Hydrological Drought ◽  
Drought Indices ◽  
Monthly Precipitation ◽  
Northeast Brazil ◽  
Seasonal Forecasts ◽  
Seasonal Drought ◽  
Drought Prediction

Abstract. A set of seasonal drought forecast models was assessed and verified for the Jaguaribe River in semiarid northeast Brazil. Meteorological seasonal forecasts were provided by the operational forecasting system used at FUNCEME (Ceará's research foundation for meteorology) and by the European Centre for Medium-Range Weather Forecasts (ECMWF). Three downscaling approaches were tested and combined with the models in hindcast mode for the period 1981 to 2014. The forecast issue time was January and the forecast period was January to June. Hydrological drought indices were obtained by fitting a generalized linear model to observations. In short, it was possible to obtain forecasts for (a) monthly precipitation, (b) meteorological drought indices, and (c) hydrological drought indices. The skill of the forecasting systems was evaluated with regard to root mean square error (RMSE) and the relative operating characteristic (ROC) skill score. Forecasts of monthly precipitation had little or no skill considering RMSE. Still, the forecast of extreme events of low monthly precipitation showed skill for the rainy season (ROC skill score of 0.24 to 0.33). A similar picture was seen when forecasting meteorological drought indices: low skill regarding RMSE and significant skill when forecasting drought events of e.g. SPEI01 (ROC skill score of 0.53 to 0.61). Similar results were obtained for low regional reservoir storage forecasts. Regarding the skill in the forecasted months, it was greater for April, when compared to February and March (the remaining months of the rainy season). This work showed that a multimodel ensemble can forecast drought events of time scales relevant to water managers in northeast Brazil with skill. But no or little skill could be found in the forecasts of the whole range of monthly precipitation or drought indices (e.g. forecasting average years). Both this work and those here revisited showed that major steps forward are needed in forecasting the rainy season in northeast Brazil.

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