Improved Land Evapotranspiration Simulation of the Community Land Model Using a Surrogate-Based Automatic Parameter Optimization Method

Farmland hydrological cycle under agroforestry systems and efficient use of water resources in the karst desertification environment

In karst desertification (KD) regions, surface water (SW) easily enters underground through pore fissures and sinkholes despite the presence of abundant precipitation. Such regions have a typical distribution of "soil above and water below", and, thus, the unique "karst drought" occurs. Hence, an urgent and primary problem in combating KD is to reach highly efficient utilization of water resources in these regions. We selected three karst research areas with different levels of karst desertification and different geomorphic types. By monitoring the storage and transformation of five types of water in the agroforestry system-precipitation, SW, groundwater (GW), soil water (SoW), plant water (PW), the following results were obtained: (1) In KD regions, a positive correlation was found among available precipitation, rainfall, and land evapotranspiration (LE), and LE was approximately equivalent to soil evaporation. (2) To varying degrees, agroforestry brings ecological benefits, including reducing surface runoff, increasing soil infiltration, lowering the transpiration rate, and reducing soil evaporation, thus achieving efficient use of water resources. (3) From 100 % rainfall, the transformation rates of SW, GW, PW, and SoW reached 0.14-12.71 %, 9.43-30.20 %, 9.79-49.97 %, and 40.72-82.58 %, respectively, and SoW showed a larger reserve than the other three types. (4) Drought stress contributes to the improvement of water use efficiency (WUE). Affected by drought stress, WUE was found to be the highest in a medium-intensity karst desertification environment. The transformation mechanisms of the five types of water observed in the agroforestry system provide a reference for efficient utilization of water resources in KD regions as well as theoretical support for addressing karst drought. They are also essential in helping to advance the ecological derivative industry, boosting the economy in karst mountainous areas, and controlling karst desertification.

Performance of Seven Land Surface Schemes in the WRFv4.3 Model for Simulating Precipitation in the Record-Breaking Meiyu Season Over the Yangtze-Huaihe River Valley in China

In 2020, the Yangtze-Huai river valley (YHRV) experienced the highest record-breaking Meiyu season since 1961, which was mainly characterized by the longest duration of precipitation lasting from early-June to mid-July, with frequent heavy rainstorms that caused severe flooding and deaths in China. Many studies have investigated the causes of this Meiyu season and its evolution, but the accuracy of precipitation simulations has received little attention. It is important to provide more accurate precipitation forecasts to help prevent and reduce flood disasters, thereby facilitating the maintenance of a healthy and sustainable earth ecosystem. In this study, we determined the optimal scheme among seven land surface model (LSMs) schemes in the Weather Research and Forecasting model for simulating the precipitation in the Meiyu season during 2020 over the YHRV region. We also investigated the mechanisms in the different LSMs that might affect precipitation simulations in terms of water and energy cycling. The results showed that the simulated amounts of precipitation were higher under all LSMs than the observations. The main differences occurred in rainstorm areas (>12 mm/day), and the differences in low rainfall areas were not significant (<8 mm/day). Among all of the LSMs, the Simplified Simple Biosphere (SSiB) model obtained the best performance, with the lowest root mean square error and the highest correlation. The SSiB model even outperformed the Bayesian model averaging result. Finally, some factors responsible for the differences modeling results were investigated to understand the related physical mechanism.