A dynamical systems approach to optimizing irrigation strategy under the influence of land-atmosphere feedbacks.

<p><span>The soil-moisture feedback describes how precipitation amount, timing and intensity react to spatial anomalies in surface moisture. For heterogeneous moisture distributions with moist/dry patches on the scale of 10−</span><span> </span><span>50km, numerical studies supported by observations indicate a negative soil-moisture feedback, where it rains more over dry patches (Imamovic, 2018; Rieck et al., 2014). The circulation established by the heterogeneous soil-moisture patches not only modifies the spatial rain distribution but allows for more water to be extracted from the atmosphere, thereby increasing the domain mean precipitation. </span></p><p><span>We here suggest that the negative soil-moisture feedback can be exploited when irrigating agricultural land: if farmers cooperate by following a spatially heterogeneous irrigation pattern, they can increase both their collective time-mean precipitation and thus the total water available for growing crops. However, the spatially non-local nature of the feedback allows individual farmers to exploit this strategy, thereby saving their own resources; a typical ‘tragedy of commons’ situation. <br>We formulate this setup in terms of an optimisation problem and study its parameter phase space, both analytically and numerically, in order to understand optimal rules and the consequences of the players’ choice to cooperate vs. compete. Different constraints in terms of water availability (reservoir) and average soil moisture as defined by the evaporation timescale are explored. </span></p><p><span>Reducing the details of the land-atmosphere interaction into simple feedback parameters helps to elucidate the complex interactions between the precipitation, soil moisture and the human intervention by irrigation. Taking into account the negative soil-moisture feedback in irrigation models opens up new strategies to optimise water management and thereby increase crop yield.</span></p>

Role of Soil Moisture Feedback in the Development of Extreme Summer Drought and Flood in the United States

This study tackles the contribution of soil moisture feedback to the development of extreme summer precipitation anomalies over the conterminous United States using a regional climate model. The model performs well in reproducing both the mean climate and extremes associated with drought and flood. A large set of experiments using the model are conducted that involve swapped initial soil moisture between flood and drought years using the 1988 and 2012 droughts and 1993 flood as examples. The starting time of these experiments includes 1 May (late spring) and 1 June (early summer). For all three years, the impact of 1 May soil moisture swapping is much weaker than the 1 June soil moisture swapping. In 1988 and 2012, replacing the 1 June soil moisture with that from 1993 reduces both the spatial extent and the severity of the simulated summer drought and heat. The impact is especially strong in 2012. In 1993, however, replacing the 1 June soil moisture with that from 1988 has little impact on precipitation. The contribution of soil moisture feedback to summer extremes is larger in 2012 than in 1988 and 1993. This may be because of the presence of strong anomalies in large-scale forcing in 1988 and 1993 that prohibit or favor precipitation, and the lack of such in 2012. This study demonstrates how the contribution of land–atmosphere feedback to the development of seasonal climate anomalies may vary from year to year and highlights its importance in the 2012 drought.

Does Afternoon Precipitation Occur Preferentially over Dry or Wet Soils in Oklahoma?

Soil moisture is an integral part of the climate system and can drive land–atmosphere interactions through the partitioning of latent and sensible heat. Soil moisture feedback to precipitation has been documented in several regions of the world, most notably in the southern Great Plains. However, the impact of soil moisture on precipitation, particularly at short (subdaily) time scales, has not been resolved. Here, in situ soil moisture observations and satellite-based precipitation estimates are used to examine if afternoon precipitation falls preferentially over wet or dry soils in Oklahoma. Afternoon precipitation events during the warm season (May–September) in Oklahoma from 2003 and 2012 are categorized by how favorable atmospheric conditions are for convection, as well as the presence or absence of the Great Plains low-level jet. The results show afternoon precipitation falls preferentially over wet soils when the Great Plains low-level jet is absent. In contrast, precipitation falls preferentially over dry soils when the low-level jet is present. Humidity (temperature) is increased (decreased) as soil moisture increases for all conditions, and convective available potential energy prior to convection is strongest when atmospheric humidity is above normal. The results do not demonstrate a causal link between soil moisture and precipitation, but they do suggest that soil moisture feedback to precipitation could potentially manifest itself over wetter- and drier-than-normal soils, depending on the overall synoptic and dynamic conditions.

Contribution of soil moisture feedback to hydroclimatic variability

While a variety of model experiments and analyses of observations have explored the impact of soil moisture variation on climate, it is not yet clear how large or detectable soil moisture feedback is across spatial and temporal scales. Here, we study the impact of dynamic versus climatological soil moisture in the GISS GCM ModelE (with prescribed sea-surface temperatures) on the variance and on the spatial and temporal correlation scale of hydrologically relevant climate variables (evaporation, precipitation, temperature, cloud cover) over the land surface. We also confirm that synoptic variations in soil moisture have a substantial impact on the mean climate state, because of the nonlinearity of the dependence of evapotranspiration on soil moisture. We find that including dynamic soil moisture increases the interannual variability of seasonal (summer and fall) and annual temperature, precipitation, and cloudiness. Dynamic soil moisture tends to decrease the correlation length scale of seasonal (warm-season) to annual land temperature fluctuations and increase that of precipitation. Dynamic soil moisture increases the persistence of temperature anomalies from spring to summer and from summer to fall, and makes the correlation between land precipitation and temperature fluctuations substantially more negative. Global observation sets that allow determination of the spacetime correlation of variables such as temperature, precipitation, and cloud cover could provide empirical measures of the strength of soil moisture feedback, given that the feedback strength varies widely among models.

Contribution of soil moisture feedback to hydroclimatic variability

While a variety of model experiments and analyses of observations have explored the impact of soil moisture variation on climate, it is not yet clear how large or detectable soil moisture feedback is across spatial and temporal scales. Here, we study the impact of dynamic versus climatological soil moisture in the GISS GCM ModelE (with prescribed sea-surface temperatures) on the variance and on the spatial and temporal correlation scale of hydrologically relevant climate variables (evaporation, precipitation, temperature, cloud cover) over the land surface. We also confirm that synoptic variations in soil moisture have a substantial impact on the mean climate state, because of the nonlinearity of the dependence of evapotranspiration on soil moisture. We find that including dynamic soil moisture increases the interannual variability of seasonal (summer and fall) and annual temperature, precipitation, and cloudiness. Dynamic soil moisture tends to decrease the correlation length scale of seasonal (warm-season) to annual land temperature fluctuations and increase that of precipitation. Dynamic soil moisture increases the persistence of temperature anomalies from spring to summer and from summer to fall, and makes the correlation between land precipitation and temperature fluctuations substantially more negative. Global observation sets that allow determination of the spacetime correlation of variables such as temperature, precipitation, and cloud cover could provide empirical measures of the strength of soil moisture feedback, given that the feedback strength varies widely among models.