Using the space-borne NASA scatterometer (NSCAT) to determine the frozen and thawed seasons

We hypothesize that the strong sensitivity of radar backscatter to surface dielectric properties, and hence to the phase (solid or liquid) of any water near the surface should make space-borne radar observations a powerful tool for large-scale spatial monitoring of the freeze/thaw state of the land surface, and thus ecosystem growing season length. We analyzed the NASA scatterometer (NSCAT) backscatter from September 1996 to June 1997, along with temperature and snow depth observations and ecosystem modeling, for three BOREAS sites in central Canada. Because of its short wavelength (2.14 cm), NSCAT was sensitive to canopy and surface water. NSCAT had 25 km spatial resolution and approximately twice-daily temporal coverage at the BOREAS latitude. At the northern site the NSCAT signal showed strong seasonality, with backscatter around −8 dB in winter and −12 dB in early summer and fall. The NSCAT signal for the southern sites had less seasonality. At all three sites there was a strong decrease in backscatter during spring thaw (4–6 dB). At the southern deciduous site, NSCAT backscatter rose from −11 to −9.2 dB during spring leaf-out. All sites showed 1–2 dB backscatter shifts corresponding to changes in landscape water state coincident with brief midwinter thaws, snowfall, and extreme cold (Tmax\u3c−25°C). Freeze/thaw detection algorithms developed for other radar instruments gave reasonable results for the northern site but were not successful at the two southern sites. We developed a change detection algorithm based on first differences of 5-day smoothed NSCAT backscatter measurements. This algorithm had some success in identifying the arrival of freezing conditions in the autumn and the beginning of thaw in the spring. Changes in surface freeze/thaw state generally coincided with the arrival and departure of the seasonal snow cover and with simulated shifts in the directions of net carbon exchange at each of the study sites

The use and re-use of unsustainable groundwater for irrigation: A global budget

Depletion of groundwater aquifers across the globe has become a significant concern, as groundwater is an important and often unsustainable source of irrigation water. Simultaneously, the field of water resource management has seen a lively debate over the concepts and metrics used to assess the downstream re-use of agricultural runoff, with most studies focusing on surface water balances. Here, we bring these two lines of research together, recognizing that depletion of aquifers leads to large amounts of groundwater entering surface water storages and flows by way of agricultural runoff. While it is clear that groundwater users will be impacted by reductions in groundwater availability, there is a major gap in our understanding of potential impacts downstream of groundwater pumping locations. We find that the volume of unsustainable groundwater that is re-used for irrigation following runoff from agricultural systems is nearly as large as the volume initially extracted from reservoirs for irrigation. Basins in which the volume of irrigation water re-used is equal to or greater than the volume of water initially used (which is possible due to multiple re-use of the same water) contain 33 million hectares of irrigated land and are home to 1.3 billion people. Some studies have called for increasing irrigation efficiency as a solution to water shortages. We find that with 100% irrigation efficiency, global demand for unsustainable groundwater is reduced by 52%, but not eliminated. In many basins, increased irrigation efficiency leads to significantly decreased river low flows; increasing irrigation efficiency to 70% globally decreases total surface water supplies by backsim600 km3 yr−1. These findings illustrate that estimates of aquifer depletion alone underestimate the importance of unsustainable groundwater to sustaining surface water systems and irrigated agriculture

Adaptability of Irrigation to a Changing Monsoon in India: How far can we go?

Agriculture and the monsoon are inextricably linked in India. A large part of the steady rise in agricultural production since the onset of the Green Revolution in the 1960’s has been attributed to irrigation. Irrigation is used to supplement and buffer crops against precipitation shocks, but water availability for such use is itself sensitive to the erratic, seasonal and spatially heterogeneous nature of the monsoon. Most attention in the literature is given to crop yields (Guiteras, 2009; Fishman, 2012; Auffhammer et al, 2011) and their ability to withstand precipitation shocks, in the presence of irrigation (Fishman, 2012). However, there remains limited evidence about how natural weather variability and realized irrigation outcomes are related. We provide new evidence on the relationship between monsoon changes, irrigation variability and water availability by linking a process based hydrology model with an econometric model for one of the world’s most water stressed countries. India uses more groundwater for irrigation than any other country, and there is substantial evidence that this has led to depletion of groundwater aquifers. First, we build an econometric model of historical irrigation decisions using detailed crop-wise agriculture and weather data spanning 35 years from 1970-2004 for 311 districts across 19 major agricultural states in India. The source of agricultural data comes from the Village Dynamics in South Asia database at the International Crop Research Institute for the Semi-Arid Tropics (ICRISAT). Weather data is sourced from the only long term continental scale daily observationally gridded precipitation and temperature dataset called APHRODITE (Asian Precipitation- Highly Resolved Observational Data Integration Towards Evaluation of the Water Resources), that captures the spatial extent of the monsoon across the Himalayas, South and South-East Asia, and the Middle East in great detail. We use panel data approaches to control for unobserved and omitted variables that can confound the true impacts of weather variability on irrigation. Exploiting the exogenous inter-annual variability in the monsoon, our multivariate regression models reveal that for crops grown in the wet season, irrigation is sensitive to distribution and total monsoon rainfall but not to ground or surface water availability. For crops grown in the dry season, total monsoon rainfall matters most, and its effect is sensitive to groundwater availability but differentially so for shallow dug wells and deep tube wells. The historical estimates from the econometric model are used to calculate future irrigated areas using three different bias-corrected climate model projections of monsoon climate for the years 2010 – 2050 under the strongest warming scenario ( business as usual scenario) RCP-8.5 from the CMIP5 (Coupled Model Intercomparison Project) models. These projections are then used as input to a physical hydrology model, such as the Water Balance Model, that tracks water use and exchange between the ground, atmosphere, runoff and stream networks. This enables us to quantify supply of water required to meet irrigation needs from sustainable sources such as rechargeable shallow groundwater, rivers and reservoirs, as well as unsustainable sources such as non- rechargeable groundwater. Preliminary results show that the significant variation in monsoon projections lead to very different results. Crops grown in the dry season show particularly divergent trends between model projections, leading to very different groundwater resource requirements. By combining the strengths of the economic and hydrology components, this work highlights potential sustainable or unsustainable water use trajectories that different regions within India will face

Achieving sustainable irrigation water withdrawals: global impacts on food security and land use

Unsustainable water use challenges the capacity of water resources to ensure food security and continued growth of the economy. Adaptation policies targeting future water security can easily overlook its interaction with other sustainability metrics and unanticipated local responses to the larger-scale policy interventions. Using a global partial equilibrium grid-resolving model SIMPLE-G, and coupling it with the global Water Balance Model, we simulate the consequences of reducing unsustainable irrigation for food security, land use change, and terrestrial carbon. A variety of future (2050) scenarios are considered that interact irrigation productivity with two policy interventions— inter-basin water transfers and international commodity market integration. We find that pursuing sustainable irrigation may erode other development and environmental goals due to higher food prices and cropland expansion. This results in over 800 000 more undernourished people and 0.87 GtC additional emissions. Faster total factor productivity growth in irrigated sectors will encourage more aggressive irrigation water use in the basins where irrigation vulnerability is expected to be reduced by inter-basin water transfer. By allowing for a systematic comparison of these alternative adaptations to future irrigation vulnerability, the global gridded modeling approach offers unique insights into the multiscale nature of the water scarcity challenge

Impacts of drainage, restoration and warming on boreal wetland greenhouse gas fluxes

Northern wetlands with organic soil i.e., mires are significant carbon storages. This key ecosystem service may be threatened by anthropogenic activities and climate change, yet we still lack a consensus on how these major changes affects their carbon sink capacities. We studied how forestry drainage and restoration combined with experimental warming, impacts greenhouse gas fluxes of wetlands with peat. We measured CO2 and CH4 during two and N2O fluxes during one growing season using the chamber method. Gas fluxes were primarily controlled by water table, leaf area and temperature. Land use had a clear impact of on CO2 exchange. Forestry drainage increased respiration rates and decreased field layer net ecosystem CO2 uptake (NEE) and leaf area index (LAI), while at restoration sites the flux rates and LAI had recovered to the level of undrained sites. CH4 emissions were exceptionally low at all sites during our study years due to natural drought, but still somewhat lower at drained compared to undrained sites. Moderate warming triggered an increase in LAI across all land use types. This was accompanied by an increase in cumulative seasonal NEE. Restoration appeared to be an effective tool to return the ecosystem functions of these wetlands as we found no differences in LAI or any gas flux components (PMAX, Reco, NEE, CH4 or N2O) between restored and undrained sites. We did not find any signs that moderate warming would compromise the return of the ecosystem functions related to C sequestration. (C) 2018 Elsevier B.V. All rights reserved.Peer reviewe

Invisible water, visible impact: How unsustainable groundwater use challenges sustainability of Indian agriculture under climate change

India is one of the world’s largest food producers, making the sustainability of its agricultural system of global significance. Groundwater irrigation underpins India’s agriculture, currently boosting crop production by enough to feed 170 million people. Groundwater overexploitation has led to drastic declines in groundwater levels, threatening to push this vital resource out of reach for millions of small-scale farmers who are the backbone of India’s food security. Historically, losing access to groundwater has decreased agricultural production and increased poverty. We take a multidisciplinary approach to assess climate change challenges facing India’s agricultural system, and to assess the effectiveness of large-scale water infrastructure projects designed to meet these challenges. We find that even in areas that experience climate change induced precipitation increases, expansion of irrigated agriculture will require increasing amounts of unsustainable groundwater. The large proposed national river linking project has limited capacity to alleviate groundwater stress. Thus, without intervention, poverty and food insecurity in rural India is likely to worsen

Evaluation of the SeaWinds scatterometer for regional monitoring of vegetation phenology

Phenology, or the seasonality of recurring biological events such as vegetation canopy development and senescence, is a primary constraint on global carbon, water and energy cycles. We analyzed multiseason Ku-band radar backscatter measurements from the SeaWinds-on-QuikSCAT scatterometer to determine canopy phenology and growing season vegetation dynamics from 2000 to 2002 at 27 sites representing major global land cover classes and regionally across most of North America. We compared these results with similar information derived from the MODIS leaf area index (LAI) data product (MOD-15A2). In site-level linear regression analysis, the correspondence between radar backscatter and LAI was significant (p \u3c 0.05) at most but not all sites and was generally higher (R2 \u3e 0.5) for sites with relatively low LAI or where the seasonal range in LAI was large (e.g., \u3e3 m2 m−2). The SeaWinds instrument also detected generally earlier onset of vegetation canopy growth in spring than the optical/near-infrared (NIR) based LAI measurements from MODIS, though the timing of canopy senescence and the end of the growing season were more similar. Over North America, the correlation between the two time series was stratified largely by land cover class, with higher correlations (R ∼ 0.7–0.9) for most cropland, deciduous broadleaf forest, crop/natural vegetation mosaic land cover, and some grassland. Lower correlations were observed for open shrubland and evergreen needleleaf forest. Overall, the results indicate that SeaWinds backscatter is sensitive to growing season canopy dynamics across a range of broadleaf vegetation types and provides a quantitative view that is independent of optical/NIR remote sensing instruments