Irrigation-Induced Environmental Changes around the Aral Sea: An Integrated View from Multiple Satellite Observations

The Aral Sea basin (ASB) is one of the most environmentally vulnerable regions to climate change and human activities. During the past 60 years, irrigation has greatly changed the water distribution and caused severe environmental issues in the ASB. Using remote sensing data, this study investigated the environmental changes induced by irrigation activities in this region. The results show that, in the past decade, land water storage has significantly increased in the irrigated upstream regions (13 km 3 year -1 ) but decreased in the downstream regions (-27 km 3 year -1 ) of the Amu Darya River basin, causing a water storage decrease in the whole basin (-20 km 3 year -1 ). As a result, the water surface area of the Aral Sea has decreased from 32,000 in 2000 to 10,000 km2 in 2015. The shrinking Aral Sea exposed a large portion of the lake bottom to the air, increasing (decreasing) the daytime (nighttime) temperatures by about 1 °C year -1 (0.5 °C year -1 ). Moreover, there were other potential environmental changes, including drier soil, less vegetation, decreasing cloud and precipitation, and more severe and frequent dust storms. Possible biases in the remote sensing data due to the neglect of the shrinking water surface area of the Aral Sea were identified. These findings highlight the severe environmental threats caused by irrigation in Central Asia and call attention to sustainable water use in such dryland regions. Keywords: environmental issues; the shrinking Aral Sea; irrigation; desertification; dust storm; remote sensing; NDVI; GRACE; MODI

Irrigation-Induced Environmental Changes around the Aral Sea: An Integrated View from Multiple Satellite Observations

The Aral Sea basin (ASB) is one of the most environmentally vulnerable regions to climate change and human activities. During the past 60 years, irrigation has greatly changed the water distribution and caused severe environmental issues in the ASB. Using remote sensing data, this study investigated the environmental changes induced by irrigation activities in this region. The results show that, in the past decade, land water storage has significantly increased in the irrigated upstream regions (13 km3 year−1) but decreased in the downstream regions (−27 km3 year−1) of the Amu Darya River basin, causing a water storage decrease in the whole basin (−20 km3 year−1). As a result, the water surface area of the Aral Sea has decreased from 32,000 in 2000 to 10,000 km2 in 2015. The shrinking Aral Sea exposed a large portion of the lake bottom to the air, increasing (decreasing) the daytime (nighttime) temperatures by about 1 °C year−1 (0.5 °C year−1). Moreover, there were other potential environmental changes, including drier soil, less vegetation, decreasing cloud and precipitation, and more severe and frequent dust storms. Possible biases in the remote sensing data due to the neglect of the shrinking water surface area of the Aral Sea were identified. These findings highlight the severe environmental threats caused by irrigation in Central Asia and call attention to sustainable water use in such dryland regions

Open-source Monitoring und Wissen für ein Regional Nachhaltiges Wassermanagement in Zentralasien

Ungleich verteiltes Wasser in Zentralasien impliziert Konflikte in allen Bereichen der Wassernutzung. Eine effiziente Bewässerungslandwirtschaft ist ein wichtiger Beitrag zur regionalen Entwicklung. Fernerkundungsdaten können notwendige Informationen im Sinne eines Monitorings liefern. Satellitenbasierte Erdbeobachtung, insbesondere seit der Verfügbarkeit von frei zugänglichen Fernerkundungsdaten, bietet enormes Potenzial für die räumliche und zeitliche Bewertung einer Vielzahl sozioökonomischer und ökologischer Aspekte. Das nachhaltige Management von Wasserressourcen steht dabei im Fokus zahlreicher wissenschaftlicher und gesellschaftlicher Fragestellungen. Speziell im Kontext zwischenstaatlicher Wasserverteilungs- und Nutzungskonflikte wie in Zentralasien wird der Fernerkundung ein hoher Stellenwert bei der Analyse und Bewertung wesentlicher Prozesse und Faktoren zur Erfassung des water footprint in der Bewässerungslandwirtschaft beigemessen. Im Aralseebecken in Zentralasien, einem der global größten Trockengebiete, ist Wasser geographisch ungleich allokiert und muss zwischen sechs Staaten, deren Ökonomien stark von der Wasserverfügbarkeit abhängen, verteilt werden. Physio-geographische Gegebenheiten als auch konkurrierende Interessen bei der Wassernutzung (wie Bewässerungslandwirtschaft und Energiegewinnung) erfordern eine effektive nationale und vor allem grenzüberschreitende Koordination dieser Interessen unter Einbindung von Nutzern und lokalen sowie regionalen Entscheidungsträgern mit dem Ziel der langfristig ressourcenschonenden Wassernutzung. Dieser Beitrag widmet sich der Frage wie frei zugängliche Fernerkundungsdaten und daraus in GIS-basierten Analysen abgeleitete Geoinformationen sowie der Transfer generierten Wissens im Sinne eines Monitorings zur Erhöhung der Wassernutzungseffizienz in der regionalen Bewässerungslandwirtschaft beitragen können. Besonderer Fokus liegt auf der Anwendung von optischen Satellitenbildern (MODIS) für (1) das Monitoring der bewässerten Landnutzung und der Ernteabschätzung zur Ermittlung der Produktivität der bewässerten Landwirtschaft und (2) dem zeitlichen und räumlichen Vergleich der Produktivität der Bewässerungssysteme. Die wissenschaftliche Arbeit verortet sich im CAWa-Projekt („Regional Research Network Central Asian Water“) als wissenschaftlich-technische Komponente der vom deutschen Bundesaußenministerium geförderten Wasserinitiative für Zentralasien (“Berliner Prozess”)

Mapping Cropland abandonment in the Aral Sea Basin with MODIS time series

© 2018 by the authors. Cropland abandonment is globally widespread and has strong repercussions for regional food security and the environment. Statistics suggest that one of the hotspots of abandoned cropland is located in the drylands of the Aral Sea Basin (ASB), which covers parts of post-Soviet Central Asia, Afghanistan and Iran. To date, the exact spatial and temporal extents of abandoned cropland remain unclear, which hampers land-use planning. Abandoned land is a potentially valuable resource for alternative land uses. Here, we mapped the abandoned cropland in the drylands of the ASB with a time series of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2003-2016. To overcome the restricted ability of a single classifier to accurately map land-use classes across large areas and agro-environmental gradients, "stratum-specific" classifiers were calibrated and classification results were fused based on a locally weighted decision fusion approach. Next, the agro-ecological suitability of abandoned cropland areas was evaluated. The stratum-specific classification approach yielded an overall accuracy of 0.879, which was significantly more accurate (p < 0.05) than a "global" classification without stratification, which had an accuracy of 0.811. In 2016, the classification results showed that 13% (1.15 Mha) of the observed irrigated cropland in the ASB was idle (abandoned). Cropland abandonment occurred mostly in the Amudarya and Syrdarya downstream regions and was associated with degraded land and areas prone to water stress. Despite the almost twofold population growth and increasing food demand in the ASB area from 1990 to 2016, abandoned cropland was also located in areas with high suitability for farming. The map of abandoned cropland areas provides a novel basis for assessing the causes leading to abandoned cropland in the ASB. This contributes to assessing the suitability of abandoned cropland for food or bioenergy production, carbon storage, or assessing the environmental trade-offs and social constraints of recultivation

Mapping Cropland Abandonment in the Aral Sea Basin with MODIS Time Series

Cropland abandonment is globally widespread and has strong repercussions for regional food security and the environment. Statistics suggest that one of the hotspots of abandoned cropland is located in the drylands of the Aral Sea Basin (ASB), which covers parts of post-Soviet Central Asia, Afghanistan and Iran. To date, the exact spatial and temporal extents of abandoned cropland remain unclear, which hampers land-use planning. Abandoned land is a potentially valuable resource for alternative land uses. Here, we mapped the abandoned cropland in the drylands of the ASB with a time series of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2003–2016. To overcome the restricted ability of a single classifier to accurately map land-use classes across large areas and agro-environmental gradients, “stratum-specific” classifiers were calibrated and classification results were fused based on a locally weighted decision fusion approach. Next, the agro-ecological suitability of abandoned cropland areas was evaluated. The stratum-specific classification approach yielded an overall accuracy of 0.879, which was significantly more accurate ( p &lt; 0.05) than a “global” classification without stratification, which had an accuracy of 0.811. In 2016, the classification results showed that 13% (1.15 Mha) of the observed irrigated cropland in the ASB was idle (abandoned). Cropland abandonment occurred mostly in the Amudarya and Syrdarya downstream regions and was associated with degraded land and areas prone to water stress. Despite the almost twofold population growth and increasing food demand in the ASB area from 1990 to 2016, abandoned cropland was also located in areas with high suitability for farming. The map of abandoned cropland areas provides a novel basis for assessing the causes leading to abandoned cropland in the ASB. This contributes to assessing the suitability of abandoned cropland for food or bioenergy production, carbon storage, or assessing the environmental trade-offs and social constraints of recultivation

More people, more food, worse water? a global review of water pollution from agriculture

Current patterns of agricultural expansion and intensification are bringing unprecedented environmental externalities, including impacts on water quality. While water pollution is slowly starting to receive the attention it deserves, the contribution of agriculture to this problem has not yet received sufficient consideration. We need a much better understanding of the causes and effects of agricultural water pollution as well as effective means to prevent and remedy the problem. In the existing literature, information on water pollution from agriculture is highly dispersed. This repost is a comprehensive review and covers different agricultural sectors (including crops, livestock and aquaculture), and examines the drivers of water pollution in these sectors as well as the resulting pressures and changes in water bodies, the associated impacts on human health and the environment, and the responses needed to prevent pollution and mitigate its risks

Desertification

IPCC SPECIAL REPORT ON CLIMATE CHANGE AND LAND (SRCCL) Chapter 3: Climate Change and Land: An IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystem

Global assessment of sand and dust storms

The specific objectives of the assessment are to: 1) Synthesise and highlight the environmental and socio-economic causes and impacts of SDS, as well as available technical measures for their mitigation, at the local, regional and global levels; 2) Show how the mitigation of SDS can yield multiple sustainable development benefits; 3) Synthesize information on current policy responses for mitigating SDS and 4) Present options for an improved strategy for mitigating SDS at the local, regional and global levels, building on existing institutions and agreements

Durable Environmental Multidisciplinary Monitoring Information Network DEMMIN - Agricultural Research at the TERENO German Northeastern Lowlands Observatory

The Durable Environmental Multidisciplinary Monitoring Information Network (DEMMIN) is a calibration and Validation test site for remote sensing Technologies and derived Information products. The test site is located within the TERENO German Northeastern Lowlands Observatory. DEMMIN Objectives are: i) combination of in-situ data and remote sensing data analysis for: Crop parameter estimation (crop type, crop status, crop pattern) Soil parameter retrieval (soil moisture, organic matter) Evapotranspiration modelling, ii) high resolution data analysis (automatic data processing and analysis of multi sensor data (e.g. TSX, Sentinel-1 & 2, Landsat-8 + in-situ + modelling), and iii) Cal/Val site for new sensors and missions